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This study presents a novel, integrated approach to investigating and characterizing the impact of humidity on Insulated-Gate Bipolar Transistors (IGBTs) within large-scale inverter systems. Combining meticulously designed experimental setups and advanced finite element simulations, we delve deep into the complex dynamics of moisture transfer within IGBT modules. Our research demonstrates a meticulously designed experimental setup within a controlled climate chamber, enabling a comprehensive characterization process of the humidity transfer into the IGBT module. The proposed method allows for a detailed study of the moisture distribution as well as the effect of the temperature on the moisture within an IGBT module. We leverage the advanced capabilities of commercial finite element software to complement our experimental findings. These simulations enable a deeper understanding of the moisture distribution's symmetries and provide invaluable insights into simplifying the complex simulations. By integrating these diverse methodologies, we develop a comprehensive approach that deciphers the spatial distribution of humidity within the module and its real-time responses to environmental conditions. This integrated approach holds an immense potential for analyzing optimal system performance and facilitating self-optimization of the inverter by predicting stress induced by humidity.

This survey provides an overview of recent advancements in wireless soil sensing technologies, including the sensors and communication systems used to manage and enhance soil health and crop production for sustainable agricultural practices. The surveyed technologies are categorized by the target sensing parameters, such as moisture, temperature, salinity, pH, nutrient concentration, pressure, and heavy metal content. Special focus is placed on the passive and semi-passive sensing principles for soil data collection, communication systems for transmitting the sensed data, and machine learning approaches for data processing and analysis to assist in informed decision-making in the realization of sustainable agriculture. By comparing existing technologies, we highlight the advantages and disadvantages of these sensing mechanisms, summarize existing challenges of the surveyed soil sensing systems, and identify future research directions that need attention.

P-band radiometry has been demonstrated to have a deeper sensing depth than L-band, making the consideration of multilayer microwave interactions necessary. In addition, the scattering and phase interference effects are different at the P-band, requiring a reconsideration of the need for coherent models. However, the impact remains to be clarified, and understanding the validity and limitations of these models at both L- and P-bands is crucial for their refinement and application. Therefore, two general categories of microwave emission models, including two stratified coherent models (Njoku and Wilhite) and four incoherent models (conventional tau-omega model and three multilayer models being zero-order, first-order, and incoherent solution), were intercompared for the first time on the same dataset. This evaluation utilized observations of L- and P-bands radiometry under different land cover conditions from a tower-based experiment in Victoria, Australia. Model estimations of brightness temperature (TB) were consistent with measurements, with the lowest root mean square error (RMSE) at P-band V-polarization under corn (2 K) and the highest RMSE at L-band H-polarization under bare soil (13 K). Coherent models performed slightly better than incoherent models under bare soil (3 K less RMSE), while the opposite was true under vegetated soil conditions (1 K less RMSE). Coherent and incoherent models showed maximum differences (3 K at P-band and 2 K at L-band), correlating strongly with soil moisture variations at 0–10 cm. Findings suggest that coherent and incoherent models performed similarly; thus, incoherent models may be preferable for estimating TB at L- and P-bands due to reduced computational complexity. [ABSTRACT FROM AUTHOR]

As an emerging technique, P-band (0.3–1 GHz) may improve soil moisture remote sensing compared to L-band (1.4 GHz) Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, because of its greater moisture retrieval depth resulting from its longer wavelength. Consequently, a number of tower-based experiments were undertaken in VIC, Australia, to understand and quantify potential improvements. The study reported here has extended the evaluation of the tau-omega model to a scenario with a dense corn canopy whose vegetation water content (VWC) reached ~20 kg/m2, and compared the soil moisture retrieval performance at P- and L-band. Based on the locally calibrated parameters, the results from both the single-channel algorithm (SCA) and dual-channel algorithm (DCA) approaches presented a clear reduction in vegetation impact at the P-band compared to L-band. While the root-mean-square error (RMSE) for the P-band did not achieve the 0.04- $\text{m}^{3}/\text{m}^{3}$ target accuracy of SMOS and SMAP, i.e., 0.054 $\text{m}^{3}/\text{m}^{3}$ for the SCA and 0.074 $\text{m}^{3}/\text{m}^{3}$ for the DCA, this performance can be regarded as acceptable considering the extremely high VWC. In comparison, the RMSEs at L-band were larger than 0.1 $\text{m}^{3}/\text{m}^{3}$ for both the SCA and the DCA approaches. Additionally, DCA performed better in correlation coefficient and unbiased RMSE, while SCA performed better in RMSE at the P-band due to the larger bias when using DCA. Moreover, the calibrated vegetation parameters at the P-band were found to apply to broader conditions than those at the L-band, likely due to the reduced vegetation impact. [ABSTRACT FROM AUTHOR]

Microelectromechanical devices are known to be sensitive to ambient humidity. This is especially true for devices in moisture sensitive plastic packages such as consumer targeted inertial measurement units. Stress and deformation based effects are shown to be a main contributor to humidity related effects such as performance and offset drifts. This paper shows that stress sensing units embedded in the mechanically coupled electronic control circuitry can be utilized to detect and compensate stress based humidity performance drifts of plastic packaged inertial measurement units. Next to the utilized stress sensor cells themselves a compensation approach is presented, that corrects the humidity based scale factor drift of a MEMS angular rate sensor while a humidity load is applied. This is achieved by finding a symbolic compensation function, which predicts the moisture induced scale factor drift, based only on the stress values within the electronic control circuitry, utilizing genetic symbolic regression. It is demonstrated that, using stress sensors, the humidity induced scale factor drift of two different gyroscope core types can be reduced by a factor of 3, which holds true for parts coming from separate assembly lots. [2022-0013] [ABSTRACT FROM AUTHOR]

Temperature and humidity soundings form the bedrock of modern data assimilation due to their ability to directly constrain the atmospheric state variables. Because of their ability to penetrate clouds and work in all weather conditions, microwave sounders have very large impacts on constraining numerical weather prediction models. Recent advancements in integrated microwave assembly, space-grade high speed analog to digital converters, gigabit-per-second data interconnects, and field programmable gate arrays have enabled a transition from traditional analog detector-based demodulators to digitally channelized systems that allow for hyperspectral, or fine spectral resolution microwave sounders to be viable replacements to the current operational instruments. This article demonstrates that retrievals of temperature and moisture soundings can be improved by as much as 50% when 60–80 appropriately chosen pseudochannels are employed. While the current simulations were limited to cloud free oceans, perhaps even greater benefits can be realized over land and cloud conditions where additional channels can help constrain the surface and clouds. The article also demonstrated the advantages of hyperspectral sensors as a way to detect radio frequency interference in the few Kelvin range, as well as its ability to improve intercalibration efforts due to its ability to match frequency response functions of target sensors.

Minimizing airborne molecular contamination (AMC) and moisture significantly decreases the defect rate of semiconductor products during manufacturing. Humid air originating from the fan filter unit (FFU) that is located at the top of a mini-environment (ME) might be transferred into a front opening unified pod (FOUP). Different moisture removal techniques such as diffuser purge and air curtain were applied to minimize the humidity level inside the FOUP. This computational fluid dynamics (CFD) numerical study evaluates the relative humidity (RH) level inside the FOUP subjected to different moisture removal techniques when the door is open. Different practical purge and air curtain flow rates were simulated. The large eddy simulation (LES) model was performed to simulate eddies inside the FOUP and ME. The relative humidity contours were also simulated inside the FOUP and ME. The results of the simulations were verified by experimental RH measurements. The findings show that combining the methods of diffuser purge and air curtain with flow rates of 130 and 360 LPM respectively has the highest moisture removal efficiency. This method can significantly decrease the humidity level inside the FOUP, resulting in a decrease in the defect rate on silicon wafers during manufacturing and storage. [ABSTRACT FROM AUTHOR]

For the safe operation of the power grid, online monitoring of insulator pollution degree is of great significance to the power system. Considering that the insulator contamination mostly is accumulated in the dry season with little rain, it is very valuable to assess the pollution degree with the small leakage current signal measured at low humidity. To this end, this article analyzed the moisture characteristics of contaminated insulators when the insulator temperature is lower than the ambient temperature and found that the water absorption rate of the contamination layer is proportional to the “apparent humidity” at the interface. Then, an assessment method for insulator pollution degree based on contamination moisture at unsaturated humidity (RH < 100%) was proposed, which has application prospects in arid areas. [ABSTRACT FROM AUTHOR]

Microwave tomography (MWT)-based control is a novel idea in industrial heating systems that demands fast data acquisition (DAQ) and real-time imaging algorithms. Uniform diffraction tomography (UDT) is one such technique that can provide real-time imaging. However, its single-input single-output data-based inverse scattering formulation can lead to time-consuming DAQ. In this article, a multistatic uniform diffraction tomography (MUDT) imaging algorithm is proposed for a fixed array MWT system. The MWT system is integrated into the industrial heating unit HEPHAISTOS to estimate the moisture distribution in a polymer foam. In addition, a technique is presented to retrieve the electrical properties of the targets using reconstructed information from MUDT and by investigating the singular values of multistatic scattering data. Through numerical and experimental data for the considered moisture scenarios, the MUDT approach is tested, and its comparison with the UDT approach is shown. Reconstructed results show that in comparison to UDT, the MUDT approach: 1) eliminates the need for mechanical scanning; 2) provides aliasing-free images by following Nyquist sampling criteria; and 3) can resolve multiple targets in the imaging media with significant improvement in the spatial resolution that further augments in the correct retrieval of the dielectric constants of the target. [ABSTRACT FROM AUTHOR]

Electricity distribution companies are in-charge-of supplying stable electric energy to urban customers over a wide geographical area. In these distribution networks, large number of Distribution-Transformers (DTs) are installed on towers or in electric-rooms with the ratings below 1000 kVA, which are the most important assets of distribution companies. Periodic maintenance and test services are not economically feasible for all in-operation transformers. Hence, estimating the remaining useful life and scheduling the maintenance times of DTs are of great technical and economic importance. An analytical approach is presented in this paper for predicting lifetime of DTs based on degree of polymerization. An appropriate Machine-Learning (ML) algorithm trained by measured data is selected for forecasting driven load according to the ambient temperature and humidity and day-hour schedules. The relation of Hot-Spot-Temperature in IEC60076∼7 is modified based on the measured data for accounting unbalanced-loading. Neutral-current is predicted using a trained ML-model. Another approach is proposed for determining times of oil filtering services aiming to minimize the maintenance cost and maximizing the remaining life. The proposed lifetime estimation method is validated by comparing its results with the damaged DT data of a sample network chosen as the case studies for this research, i.e., Bushehr province, Iran. [ABSTRACT FROM AUTHOR]

The corrosion of transformers by multiple sulfides seriously affects the safe operation of transformers. However, there is a lack of quantitative characterization of the extent to which temperature and oxygen as well as changes in sulfide species affect the aging of oil–paper insulation. In this study, the aging characteristics of oil–paper insulation systems were analyzed in terms of the moisture in the oil, moisture in the paper, acid value, and furfural in the presence of multiple sulfides, where the temperature and the oxygen concentration are used as independent variables. A strong positive correlation between the acid value and the furfural obtained by means of Spearman’s correlation analysis. The acid value and furfural content in the oil were then analyzed and compared according to a nonparametric test, and it was found that both the oxygen changes and the temperature changes had a relatively obvious effect on the acid value in the oil. The effect of the temperature change on the furfural was greater than the effect of the oxygen change on the furfural. Finally, a multiple linear regression analysis was performed for the change in the acid value of the oil with the change in the oxygen content and temperature to obtain the linear fitting formulas for the effects of the time, temperature, oxygen content percentage, and sulfide groups on the acid value. This study can be used to quantify the magnitude of the influences of the oxygen, temperature sulfide groups, and other factors on the aging characteristic parameters of the oil–paper insulation system and to provide a certain reference for studying the quantitative characterization of the sulfur corrosion degree by using the change in the acid value in oil. [ABSTRACT FROM AUTHOR]

Although vegetable oil is the best substitute for mineral oil, it exhibits numerous disadvantages, including a high dielectric loss factor, low volume resistivity, and high viscosity. Nanoparticle modification may improve the electrical properties of vegetable oil considerably. In this study, vegetable oil infused with Fe3O4, TiO2, and Al2O3 nanoparticles was investigated. Thermal aging experiments were performed at 100 °C, 130 °C, and 150 °C. The aged vegetable insulating oil was periodically sampled and tested. The results revealed that the nanoparticles with a mass fraction of 0.001% exhibited the best modification effect. The electrical properties of the vegetable insulating oil modified with magnetic nanoparticles were pronounced, whereas the modification effect of nonmagnetic nanoparticles was mild. The general trend of the modification effect of the nanoparticles on vegetable oil became obvious with the increase in the temperature. At the same content, the modification effect of nano-Fe3O4 was superior to that of nano-TiO2 and nano-Al2O3. The results of this study provide experimental and theoretical support for the mechanism of long-term stability of vegetable insulating oil with nanoparticles and can be used to improve the long-term stability of vegetable insulating oil. [ABSTRACT FROM AUTHOR]

Due to rapid temperature rise and insulation moisture, bubbles can generate in the oil-paper insulation of oil-immersed power transformers, which can reduce the dielectric strength of oil-paper insulation and even bring about the risk of insulation breakdown. In order to accurately evaluate the conditions of bubble formation, the physical process of bubble formation in oil-paper insulation is studied in this article. Considering the effects of water vaporization, gas dissolution in oil, and moisture migration on bubble formation, a bubble formation prediction model is constructed. Based on Henry’s law, the dissolution equilibrium of gas in oil is taken into consideration and the upper boundary of the initial temperature of bubble effect (ITBE) envelope is obtained in this model. Based on the moisture equilibrium in oil-paper insulation, the bubble formation process caused by the emergence and rapid evaporation of free water is analyzed, and then, the lower boundary of the ITBE envelope is obtained in this model. The model results show that the moisture content of the pressboard and the presence of free water have a great impact on ITBE. Specifically, the higher the moisture content, the lower the ITBE value. In addition, with the further increase of moisture content, the upper and lower boundaries of the ITBE envelope gradually tend to be the same. However, once free water is present on the surface of cellulose, ITBE decreases rapidly to below 120 °C. The model built in this article is of great significance to study the temperature limit of the power transformer. Hence the ITBE envelope can provide an important theoretical reference for reducing the risk of bubble formation during power transformer operation. [ABSTRACT FROM AUTHOR]

The Hydrometeorological Center of Russia receives agrometeorological information from about 950 stations one time per ten days and the remote sensing Advanced Scatterometer (ASCAT) data from three Meteorological Operational (MetOp) satellites. We suggest a combined objective analysis (OA) of the available water content based on the available water content measurements at agrometeorological stations and on remote sensing data. The new version of OA is constructed using two neural networks and the backpropagation of error to learn it simultaneously. The first neural network is used to convert the ASCAT data into the available water content values, and the second network is used to estimate the inhomogeneities of soil moisture fields. We use the optimal interpolation (OI) method for assimilation of the ground-based data. In the new version, we evaluate the correlation functions (CFs) of inhomogeneous non-Gaussian fields, not from sample statistics but from machine learning methods. The method takes into account the combining of various datasets: ASCAT data, Food and Agriculture Organization (FAO) soil types, European Space Agency (ESA) GlobCover, and National Center for Atmospheric Research (NCAR) climate data. [ABSTRACT FROM AUTHOR]

Encapsulated microelectromechanical measurement units are known to be sensitive to ambient humidity conditions, due to various effects caused by moisture diffusing into and out of the plastic packaging components. This paper focuses on investigating the effect that a change of moisture content has on the transient offset behavior of a packaged MEMS sensor by investigating the output signals of several test devices that only differ in their response to deformation of the MEMS core area. This comprises a novel method of experimentally analyzing the transient drift behavior of a MEMS caused by a deformation of the MEMS core area. This approach enables a back calculation of possible deformation shapes of the core area that explain the observed offset drifts in a given package. It was shown that the humidity response of a MEMS sensor is a strongly transient function that is not proportional to the uptake of water and can therefore significantly differ from their humidity performance at or close to a saturated state. Humidity performance tests that take only this state as point of reference for a performance evaluation cannot correctly estimate the humidity induced offset drifts. It was also shown that the moisture induced offset drifts can be traced back to a superposition of several deformation fields leading to several stages of the humidity response of MEMS sensors. Based on the example of the test devices it was shown that MEMS cores can be optimized to minimize the response of moisture effects. [2021-0212] [ABSTRACT FROM AUTHOR]

In this work, two commercial no clean fluxes, namely, extremely low residue no-clean flux (NCF) (NC-1) and ordinary NCF (NC-2), were used for the preparation of a fine pitch flip-chip package with a $7.6\,\times \,7.6$ mm2 Si die on a $17\,\times \,17$ mm2 organic substrate. One water-soluble (WS) flux was also used for comparison. Moisture sensitivity of the package was evaluated using JESD22-A113D (30 °C/60% relative humidity (RH), 192 h, $3\times $ reflow at 260 °C). Thermal cycling tests were performed following JESD22-A104D (−65 °C to 150 °C). The high-temperature storage life (HTSL) of the packages was investigated using JESD22-A103C (175 °C). Underfill delamination or voids in the package were investigated by confocal scanning acoustic microscopy (C-SAM). Failure characteristics of the packages were also studied using scanning electron microscopy (SEM). After moisture sensitivity level (MSL) test, vehicles prepared by NC-1 and NC-2 showed failure. SEM images revealed severe delamination between underfill and solder mask in the presence of amine/amide and carboxylic acid-based NCF residue. Solder bump crack were found at < 500 cycles for samples prepared with NC-1 which contains tertiary amine and long carbon chain (C8:C10:C12) carboxylic acid-based. However, failure occurred at < 1500 cycles for NC-2 containing secondary amide and shorter carbon chain length (C3) carboxylic acid. Samples prepared using WS did not show any failure for up to 2000 cycles. Thus, NCF-treated assemblies performed poorly in moisture sensitivity and temperature cycling tests. [ABSTRACT FROM AUTHOR]

The intrusion of moisture may induce an abnormal increase in temperature or may even cause fractures in insulation equipment. Therefore, the hygroscopicity of rubber materials must be characterized. However, the existing methods for weighing organic polymer materials, such as silicone rubber, for moisture-absorption tests are time-consuming. In this article, a practical method for testing the moisture-absorption performance of silicone rubber materials for external insulation is proposed. The basic characteristics of the Langmuir diffusion equation for the water-absorption characteristics of silicone rubber are analyzed. A Langmuir curve fitting method based on the contraction–expansion (C–E) algorithm is developed, and its fitting effect is preliminarily verified by combining the experimental errors obtained from the experiment. Results show that the fitting effect has a strong relationship with the initial range of diffusion coefficient, bonding coefficient, and debonding coefficient. The time-consuming process of directly applying the fitting method is reduced from 70 to 50 days. The initial ranges of diffusion, bonding coefficient, and debonding coefficient are determined via the results of molecular simulations and experiments combined with an analysis of the literature. A prediction model is optimized and then validated against the experimental data from the recent literature on the water-absorption characteristics of silicone rubber at different temperatures. The experimental time required to reach saturated water absorption is remarkably reduced from 70 days to 1 day. Therefore, the method developed herein is feasible for engineering applications. Moreover, the entire water-absorption curve can be possibly plotted with an error of not greater than 5% via this prediction method. [ABSTRACT FROM AUTHOR]

Frequency-domain dielectric spectroscopy (FDS) is widely used in the insulation assessment of oil-immersed power equipment, and the moisture in insulating paper could be qualitatively predicted by mathematical approximation. However, due to the still lots unexplored underlying mechanisms, until now, there is still no convincing and physical method for the diagnosis of moisture content. With the aid of spectral decomposition methods, this article aims to explore the effects and mechanism of moisture on the independent dielectric response spectra. First, the measured dielectric response curve is unfolded and reconstructed by derivation of the real part curve. Second, the independent polarization and conductance spectra of damp samples are extracted, and then, the relationships between moisture content in insulating paper and spectral parameters are established quantitatively. The results show that moisture introduces a new polarization in the midfrequency region at room temperature, and both polarization and conductance increase with the moisture content. The multiple adsorption model and the proton exchange model of moisture are employed to illustrate the changes of the polarization and the conductance spectra, respectively. This research provides a methodological reference for the moisture assessment of oil–paper insulation. [ABSTRACT FROM AUTHOR]

When using the statistical inversion framework in microwave tomography (MWT), generally, the real and imaginary parts of the unknown dielectric constant are treated as uncorrelated and independent random variables. Thereby, in the maximum a posteriori estimates, the two recovered variables may show different structural changes inside the imaging domain. In this work, a correlated sample-based prior model is presented to incorporate the correlation of the real part with the imaginary part of the dielectric constant in the statistical inversion framework. The method is used to estimate the inhomogeneous moisture distribution (as dielectric constant) in a large cross section of polymer foam. The targeted application of MWT is in industrial drying to derive intelligent control methods based on tomographic inputs for selective heating purposes. One of the features of the proposed method shows how to integrate lab-based dielectric characterization, often available in MWT application cases, in the prior modeling. The method is validated with numerical and experimental MWT data for the considered moisture distributions. [ABSTRACT FROM AUTHOR]

Planning of biorefinery operations is complicated by the stochastic nature of physical and chemical characteristics of biomass feedstock, such as, moisture level and carbohydrate content. Biomass characteristics affect the performance of the equipment which feed the reactor and the efficiency of the conversion process in a biorefinery. We propose a stochastic optimization model to identify a blend of feedstocks, inventory levels, and operating conditions of equipment to ensure a continuous flowing of biomass to the reactor while meeting the requirements of the biochemical conversion process. We propose a sample average approximation (SAA) of the model, and develop an efficient algorithm to solve the SAA model. A feedstock preprocessing process consists of two-stage grinding and pelleting is used to develop a case study. Extensive numerical analysis are conducted which lead to a number of observations. Our main observation is that sequencing bales based on moisture level and carbohydrate content leads to robust solutions that improve processing time and processing rate of the reactor. We provide a number of managerial insights that facilitate the implementation of the model proposed. Note to Practitioners—This paper is motivated by the challenges faced in the bioenergy industry. The focus of this paper is on plants which use the biochemical conversion process to generate liquid fuels. It has been observed that variations in biomass characteristics, such as moisture content, cause variations in feeding of the system which lead to under-utilization of equipment. A requirement of biochemical conversion process is to maintain the carbohydrate content of biomass processed by the reactor, larger than a threshold. We propose a model that identifies the inventory levels and operating conditions of equipment to ensure a continuous flowing of biomass to the reactor. The goal is to improve equipment utilization while satisfying the requirements of the conversion process. The model is tested using real-life data. We found out that by sequencing bales based on moisture level and carbohydrate content, a plant can reduce variability in the system leading to improved system reliability, higher processing rates of the reactor, and higher throughput. [ABSTRACT FROM AUTHOR]

Inductive power transfer (IPT) has been extensively used to power the sensor nodes embedded into reinforced concrete structures for structural health monitoring (SHM) applications. Due to high dielectric absorption in concrete and hysteresis loss and eddy current loss in reinforced steel, this approach suffers from heavy attenuation and short transmission distance. To tackle the issue, a multicoil inductive power repeater system is proposed, in which the coil not only performs as a power relay but also supplies energy to the local load. Based on the physical model of multicoil coupling, the equivalent circuit is built. The effect of various design parameters (e.g., operating frequency, concrete strength, moisture, and steel types) on the power transfer capability of the proposed IPT system is investigated. A flexible design method using coupling modulation is proposed to achieve equal power distribution among various power relay circuits. Experimental results show that the proposed method can simultaneously provide equal power of 0.6 W to four local loads embedded into reinforced concrete structures with a power variation of less than 7.2%. The IPT system achieves a long distance of 51.5 cm and an efficiency of 47.7%. The results indicate the feasibility of the proposed design method in SHM applications. [ABSTRACT FROM AUTHOR]

This is the first of two articles that present experimental spectra of six soil samples with varying clay contents ranging from 0% to 55% and organic carbon levels ranging from 0% to 3.9%, measured at a small step of moisture change at a temperature of 25 °C. The study was carried out using a method that enables the measurements of the same sample over a wide frequency range of 1 kHz–8.5 GHz and in some cases up to 20 GHz. The relative effective complex permittivity (RCP) is strongly influenced by dielectric relaxation processes due to the Maxwell–Wagner (MW) effect in the frequency range of 10 kHz–8.5 GHz as demonstrated. These processes are aided by the presence of clay in the soil. Up to frequencies of 4–5 GHz, these processes have a weak influence, mainly on the imaginary part of the RCP. This explains why in the dielectric models of Dobson and Mironov, where relaxation processes are ignored, free and physical bound water has high specific conductivity. We demonstrated that organic carbon, even at low content, reduces the real and imaginary parts of the RCP when all other factors are equal. Part II will present the results of using the Debye and Cole–Cole formulas to model relaxation processes. [ABSTRACT FROM AUTHOR]

Ready-to-eat (RTE) millet grain flakes and puffs are gaining importance in the modern era because of their nutritional and health benefits. In this work, air plasma has been generated and bubbled into pearl millet during soaking, followed by analyzing its flaking and puffing characteristics. The voltage 180, 200, and 220 V with airflow rates of 10 and 12 lph for 1 and 2 h was exposed to treat pearl millet samples. An increase in conductivity, total soluble solids (TSS), and drop in pH of the soaked medium was observed with the bubbling of plasma. The plasma bubbling exhibited an improvement in the pearl millet’s flaking and puffing properties. The noteworthy changes ($P < 0.05$) in expansion volume, bulk density, color, moisture content, crispiness, and hardness were observed in flaked and puffed samples. An increase in the expansion ratio (ER) of pearl millet flakes and puffs from 4.2 to 8.3 and 4.9 to 9.5 decreases in bulk density of flakes and puffs from 0.36 to 0.11 and 0.14 to 0.06 kg/m3, respectively, was noticed with the plasma bubbling. The textural properties like the crispiness of the flakes and puffs elevated, and hardness was reduced with the given treatments. The decrement in yellowness index (YI) and increase in whiteness index (WI) was observed in both flaked and puffed samples with the rise in exposure time. The synergistic effect of plasma reactive species in combination with hydration aids in improving grain properties and helps in diversifying the utilization of millet grains. [ABSTRACT FROM AUTHOR]

Utilities prefer to perform a condition-based assessment of power transformer insulation in the least possible shutdown time. It is essential to estimate the values of various insulation condition sensitive performance parameters with higher accuracy. In the present work, a technique for the estimation of performance parameters, moisture content of paper, dissipation factor of the entire oil-paper insulation, paper conductivity, and activation energy is proposed. The evaluation of these parameters using reported techniques requires complete measurement of polarization and depolarization current profile, which requires around 20000 s of measurement time. The present method uses a forecasted polarization current profile obtained from 600 s of measured polarization current data. Detrended Fluctuation Analysis is applied to the forecasted polarization current data obtained from various in-service power transformers to obtain a suitable parameter. It is shown that this parameter maintains well-defined relationships with parameters; moisture content of paper, dissipation factor of oil-paper insulation, paper conductivity, and activation energy. The proposed technique is beneficial for utilities as it eliminates the requirement of measuring depolarization current and return voltage measurement for estimating activation energy. [ABSTRACT FROM AUTHOR]

In this article, a novel approach is proposed for accurate moisture content (MC) estimation of cross-linked polyethylene (XLPE) insulation employing electric modulus. Additionally, the variation of real and imaginary part of electric modulus in the argand plane is fitted using Cole-Cole (C-C) model for understanding of distributed relaxation behavior of XLPE insulation. Based on the frequency variation of dielectric parameters, five moisture sensitive parameters are identified and using these parameters, five empirical relationships are proposed for quantitative assessment of MC in XLPE insulation. It is observed that parameters obtained from the complex modulus spectrum yields better accuracy in estimation of MC compared to the parameters obtained from traditional frequency domain spectroscopy (FDS). [ABSTRACT FROM AUTHOR]

Despite the technical popularity of the dielectric response (DR) methods used for the nonintrusive diagnosis of the cellulose insulation condition, it is still considered a challenging and tough task so far to trustworthily interpret the details of the measurement results for further understanding and tracing the insulation changes behind. From a novel perspective of parametric study on the circuital DR equivalence of cellulosic insulation—extended Debye model (EDM), the new dielectric characteristic quantities and the quantification approach to determine the cellulosic moisture condition are investigated in the present study. First, a kind of tailor-made scale-down bushing model is prepared, with its cellulosic condenser body absorbing differently controlled quantities of water to simulate the dampness of real-life insulation, of which the frequency-domain spectroscopy (FDS) is measured under controlled temperatures. Then, the EDM is employed for a parameterized study on the FDS details with the moisture changes, by identifying the model parameters against the FDS curves, whereby the two time-domain dielectric spectra—polarization/depolarization current and return voltage—are transferred from the FDS so that a set of hybrid time–frequency characteristic quantities is proposed, which is revealed to be indicative of the dampness variations of cellulosic insulation. Finally, the principal component analysis and the feature recognition algorithm based on minimum distance are applied to determine the moisture content of the condenser body, which verifies the holistic effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Under temperature and moisture combined, bubbles will be formed in oil-impregnated paper/pressboard (OIP/OIPB). Although many studies have been done to understand the thermo-induced bubble phenomenon in OIPB, the formation mechanism is not, let alone its effect on discharge characteristics and insulation performance of OIPB. In this article, the phenomena and mechanisms of thermally induced bubbles, their effects and mechanisms on the partial discharge (PD), and breakdown characteristics of OIPB are investigated. The results show that the bubble inception temperature (BIT) decreases significantly with the increase of the moisture of OIPB. There is a growth process of bubbles from small to large, and the heating temperature and moisture content of OIPB affect the gas component inside the bubble. Thermal bubbles significantly reduce the PD inception voltage (PDIV) and breakdown voltage (BV), and the PD evolution and dissolved gas components in the oil show significant differences in the presence/absence of bubbles. Interestingly, PDIV and BV start to decrease in a temperature interval before BIT, and we infer that many microbubbles and gaseous channels exist inside OIPB before observable bubbles are formed on the surface. Considering the fibrous porous structure of OIPB and combining it with the bubble nucleation theory, we propose a new model for interpreting bubble formation and insulation degradation. The model suggests that bubbles (vapors) form first in microcavities and holes inside the OIPB and then spill over to the surface to form observable bubbles. The microcavities and pores in the OIPB are filled with gas (vapor) as the main cause of PD inception and insulation degradation. This study contributes to understanding the mechanisms of bubble formation in oil–paper insulation as well as provides a reference for risk assessment during overload operation and diagnosis of bubble-induced related faults of transformers. [ABSTRACT FROM AUTHOR]

Combining the benefits of photothermal conversion in a doped optical fiber with the principle of Fiber Bragg Grating (FBG)-based temperature measurement, a new optical fiber method for the measurement of moisture content has been developed and its performance is reported. This novel all-fiber approach shows the important characteristics of fast response, miniaturization in the design and low power consumption. In this work, a 1480nm pump laser has been used to heat the cobalt-doped fiber used, which has been embedded in the sample under investigation, where the sensor temperature change was obtained by using a FBG written into the cobalt-doped fiber. The fast, in-situ measurement of moisture content developed takes advantage of the linear relationship between the temperature change characteristics experienced during the heating process and the moisture content. To calibrate and characterize the sensor developed, a variable moisture-content test platform was established, and experiments were conducted to investigate the performance of this optical fiber approach. The all-fiber moisture sensor developed in this way has been evaluated by measuring the moisture content of samples of soil and pulverized coal and the data obtained were in good agreement with the results obtained from using the more conventional (and slow) drying method, with a maximum error of just over 1% and a rapid, 2s, optimum measurement time achieved. [ABSTRACT FROM AUTHOR]

An investigation of the influence of unshelled peanut orientation on microwave moisture sensing from measurement of dielectric properties is presented for the first time in this article. A free-space dielectric measurement technique was used for measurement on cleaned unshelled peanuts at 9.6 GHz with a pair of low-cost printed Yagi-Uda antennas. The peanut sample was placed between the transmitting and receiving antennas in a cubical polyester sample container (76 mm $\times76$ mm $\times76$ mm). Influence of orientations of the peanut pods, were studied with 2, 3, 4 and 6-direction measurements of the dielectric properties of the sample. The different measurement directions were obtained by rotation of the cubical sample container. The dielectric properties were determined from measurements of the attenuation and phase-shift caused by the peanut sample when placed between the antennas. The dielectric properties of the peanut sample were found to be dependent on the orientation distribution of pods. The average value of dielectric properties determined from 6-direction measurement was more representative of the dielectric properties of the bulk peanut sample. A temperature-compensated function for the dielectric properties and subsequent moisture content calibration equation were established and used during the in-field testing. Results of the in-field microwave moisture measurements are compared with values obtained by using the official moisture determination method (capacitance-type meter). [ABSTRACT FROM AUTHOR]

The measurement of soil moisture and air humidity is essential to many technological and environmental applications. Sensors provide information that is useful in order to effectively manage and control various processes. This study presents an energy-efficient, highly reliable, ultra-high frequency (UHF) capacitive sensor that can measure moisture/humidity, and liquid levels. As a sensitive part, an interdigital capacitor (IDC) is fed via a coplanar waveguide (CPW) for efficient power transfer. Aside from the sensitive part of the IDC, the structure of the sensor is insensitive to variations in surrounding permittivity, which reduces uncertainty in results and thus improves accuracy. The principle of sensing is based on a reactive phase variation of the input signal upon reflection, whereas its amplitude and phase are actively changing with variations in the dielectric constant of the test medium. Practical testing was conducted on the sensor to determine soil moisture, air humidity, and liquid level measurement. At a fixed UHF frequency of 915 MHz the sensor offers a capacitive sensitivity of 7.5 fF/%WC, 4.5 fF/%RH, and 13.4 fF/mm for soil moisture, air humidity, and water level detection respectively. This new sensor provides high reliability, good sensitivity, low power consumption, and can be implemented in a number of applications, including agriculture, oil, and gas industry, land and water treatment, medical equipment, and biotechnology. [ABSTRACT FROM AUTHOR]

Spatiotemporal distribution of soil moisture is important for hydrometeorological and agricultural applications. There is growing interest in monitoring soil moisture in relation to soil- and land-based natural flood management (NFM), to understand the soil’s ability, via land-use and management changes, and to delay the arrival of flood peaks in nearby watercourses. This article monitors relative surface soil moisture (rSSM) across the Thames Valley, U.K., using Sentinel-1 data, and the Vienna University of Technology (TU-Wien) Change Detection Algorithm, with a novel exploration of monthly and annual normalization factors and spatial averaging. Two pairs of normalization factors are introduced to remove impacts from varying local incidence angles through direct and multiple regression slopes. The spatiotemporal distribution of rSSM values at various spatial resolutions (1000, 500, 250, and 100 m) is assessed. Comparisons with in situ soil moisture data from the COSMOS-UK network show that, while general temporal trends agree, the difference in effective depth of measurements, coupled with vegetation impacts during the growing season, makes comparison with soil moisture observations difficult. Temporal rSSM trends can be retrieved at spatial resolutions down to 100 m, and the rSSM RMSE was found to decrease as the spatial resolution increases. The vegetation effects upon the rSSM are further explored by comparing the two dominant land cover types: Arable and Horticulture, and Improved Grassland. It was found that, while the rSSM retrieval for these land covers was possible, and the general soil moisture trend is clear, overlying vegetation during the summer artificially increased the rSSM values. [ABSTRACT FROM AUTHOR]

In recent years, the semiconductor industry has continued to advance production techniques and reduce chip feature size. The presence of unwanted moisture during the construction of these features increases the risk of chip defects and reduced yield. During production, smaller integrated circuit (IC) products are more sensitive to the presence of moisture. Therefore, increasing the efficiency of moisture control techniques is very important to decrease the product defect rate. Front opening unified pods (FOUPs) are the plastic enclosure boxes that are designed to provide a cleaner environment for semiconductor wafers during manufacturing and storage. Clean dry air (CDA) or nitrogen (N2) can purge moist air out from the FOUP. For the first time, in this study the effect of purge flow rate on the moisture removal efficiency of a loaded FOUP was examined accurately via smoke flow visualization, particle image velocimetry (PIV) and relative humidity (RH) measurement. Moreover, two different wafer arrangements of top-empty and bottom-empty FOUP were investigated. The findings show the bottom-empty FOUP arrangement results in higher purge performance compared to the top-empty FOUP arrangement. Four purge flow rates of 130, 200, 300 and 400 LPM were examined. The findings also show that when the purge flow rate was set to 200 LPM, the lowest level of relative humidity was measured inside the FOUP. Therefore, the purge flow rate of 200 LPM and the bottom- empty FOUP arrangement can minimize the humidity invasion into a loaded FOUP. The findings from this study can be beneficial to the industry to optimize the purge flow rate and to define the most efficient arrangement of the wafers inside the FOUP during manufacturing and storage. This can increase the product quality and reduce energy consumption by decreasing product defects and increasing yield. [ABSTRACT FROM AUTHOR]

An ultra-wide band measurement method for determining the complex refractive index of large-volume objects is presented. The method is intended for industrial non-destructive testing. It uses a frequency-domain technique in which transmitted radio pulses are analyzed and the effects of near field and coupling on the determined refractive index are compensated. Measurements were performed in an industrial setup with electromagnetic sensors buried in the object. The results are presented for woodchips as an object. The refractive index was experimentally determined in the frequency range 0.5-3.0 GHz. Additionally, we designed and manufactured planar quasi-differential elliptical-antennas as electromagnetic sensors. The results from the industrial measurement setup were compared with the results of the laboratory setup, in which the sensors were placed outside the test box and near field and coupling effects could be neglected. The complex refractive index determined for the two setups was in good agreement, which corroborates the proposed method for compensating for coupling and near-field effects. The complex refractive index of woodchips changes with the moisture content. It is experimental verified using the industrial setup that the moisture content can be determined with a 2 percent error. [ABSTRACT FROM AUTHOR]

Soil parameter characterization and the variation of permittivity and resistivity with frequency (dispersion) and current density have been the subject of many experimental studies but significant differences in measured values are found in the literature due to different testing approaches, apparatus, and test sample composition. This article first presents a comprehensive review of this previous body of work. Then, new experiments on soils and electrolytes with test frequencies in the range 1 Hz to 10 MHz and with current densities from 1 to 35 mA/m2 are described. Such results help clarify the effects of frequency, soil moisture, electrolyte concentration, and electrode material on the measured test medium parameters. The contribution of the electrode-electrolyte interface (EEI) and the influence of current density are particularly highlighted. These findings indicate that some previous measurements may have overestimated the measured values of resistivity and permittivity due to the EEI effect. Finally, the test results are compared with soil parameter equations from CIGRE TB781. [ABSTRACT FROM AUTHOR]

Trees have a profound impact on human life that makes their year-round monitoring with dielectric characteristics (DCs) of wood water as controlled parameters of great importance. This article deals with studying some behavior features of DCs of different-type wood water in various phenophases under varying moisture, temperature, and concentrations of dissolved substances. It presents the measurement results of DCs (1.41 GHz) of freshly cut branches of birch sampled from the same tree in different phenophases of 2018–2020. DCs carry the information on the phase composition of water present in plant tissue, volume fractions of bound and free water, concentrations, and types of dissolved substances. For various phenophases, the dependences of refractive (${n}$) and absorption ($\kappa $) indices on volume fraction of water in wood (${W}$) for whole branches are approximated by piecewise broken lines with one (${W} _{{{1}}}$) or two (${W} _{{{1}}}$ and ${W} _{{{2}}}$) break points. We identify three categories of wood water with different DCs and estimate the dielectric properties of bound and free water in wood tissue in different phenophases using the refractive model. The established seasonal dependences (${n}$ , $\kappa $) (${W}$ , ${T}$) and the developed dielectric model make it possible to calculate DCs of wood water. [ABSTRACT FROM AUTHOR]

The investigation on the aging marker for palm fatty acid ester (PFAE)-filled transformer was performed. Sealed aging stainless steel tanks containing transformer components in the same ratio as a 27-MVA power transformer, were aged at 151 °C–168.5 °C for 48–2880 h in a strictly controlled oxygen-free and low initial moisture environment. The generation of 2-furaldehyde (2FAL) and other four kinds of furans including 5-hydroxymethylfurfural (5HMF), 2-furfuryl alcohol (2FOL), 2-acetylfuran (2ACF), and 5-methyl furfural (5MEF) from cellulosic insulating components impregnated in mineral oil (MO) and PFAE after thermally aging tests are determined and compared. The results indicate that the concentration of 2FAL, 2ACF, and 5MEF maintains an increasing trend with the aging time and temperature for both fluids. The correlations between 2FAL and the degree of polymerization (DP) of high-density pressboard (HPB) in both fluids are established. The results demonstrate that 2ACF and 5MEF can also be used as aging markers for transformer in spite of their much lower concentrations in the aged fluids. [ABSTRACT FROM AUTHOR]

To fully understand the distribution network cable accessories’ moisture fault, the variation in insulation parameters of the cable main insulation of cross-linked polyethylene (XLPE) and the cable accessory reinforced insulation of silicone rubber (SIR) under different moisture conditions are studied experimentally. Furthermore, the effects of typical moisture defect forms and moisture positions on electric field distributions are studied by establishing the interface defect model. The experimental results show that the insulation properties of XLPE after water immersion are more seriously reduced than SIR. The resistivity of XLPE and SIR specimens decreases significantly with the increase in moisture time, decreasing by 90.3% and 48.3% after 720 h, respectively. The relative dielectric constants of the two kinds of specimens increase with different degrees after moisture, increasing by 5.16% and 7.83%, respectively, and the breakdown strength decreases by 18.3% and 13.1% after 720 h, respectively. The simulated results show that the moisture form and position have a great influence on electric field distribution. The electric field distortion caused by water trees’ defect is the most serious, followed by water film defects and water droplet defects. Besides, for different types of moisture defects, the position of the maximum distortion electric field is different. [ABSTRACT FROM AUTHOR]

This article is aimed at quantifying the health condition of the power transformer insulation system through its frequency-domain dielectric characteristic by using the concept of the resistor and fractional calculus. In this regard, the dielectric model of the fractional Poynting–Thomson (PT) is proposed, and a mathematical model for parameter identification of the proposed model is presented. The shuffled frog leaping algorithm (SFLA) is used to realize the parameter identification and the fractional PT model parameters of the oil-paper samples under different insulation health conditions. The influence of moisture and aging on the fractional PT dielectric model parameters is experimentally studied. Results show that, with the increase in the water content within the insulation system, the parameters of the fractional PT model gradually decrease, and there is a strong correlation between the relaxation time and the water content. This facilitates the employment of the fractional PT model parameters to quantify the aging and moisture content of the power transformer insulation system. [ABSTRACT FROM AUTHOR]

Methanol is considered to be a new chemical marker to estimate the aging state of transformer cellulose insulation paper. The key to improve the assessment accuracy is to establish the precise relationship between the concentration of methanol in oil and degree of polymerization (DP) of insulation paper. The previous research in this area has shortcomings and needs to be further improved. In this article, first, an aging assessment basic model (temperature 20 °C, moisture content of insulation paper 0.637%) is established based on the theoretical derivation of cellulose degradation kinetics, and is calculated by 130 °C thermal aging experiment. Furthermore, the effects of different temperatures (20 °C–90 °C) and moisture contents of insulation paper (0.6%–3.4%) on methanol in oil are studied by diffusion experiment. Based on the above effects, the temperature and moisture correction factors are established by mathematical reduction. What is more, a modified model is proposed by integrating the basic model and the correction factors. Eventually, the verification experiment is randomly prepared to test the accuracy of modified model and the result shows that the relative error of DP is within 7%. The physical meaning and accuracy of aging assessment are improved by model derivation and modification of influencing factors. [ABSTRACT FROM AUTHOR]

The traditional method for transformer moisture diagnosis is to establish empirical equations between feature parameters extracted from frequency domain spectroscopy (FDS) and the transformer’s moisture content. However, the established empirical equation may not be applicable to a novel testing environment, resulting in an unreliable evaluation result. In this regard, it is acknowledged that FDS combined with machine learning is more suitable for estimating moisture content in a variety of test environments. Nonetheless, the accuracy of the estimation results obtained using the existing method is limited by the algorithm’s inability to generalize. To address this issue, we propose an AdaBoost algorithm-enhanced back-propagation neural network (BP_AdaBoost). This study creates a database by extracting feature parameters from the FDS that characterize the insulation states of the prepared samples. Then, using the BP_AdaBoost algorithm and the newly constructed database, the moisture estimation models are trained. Finally, the results of the estimation are discussed in terms of laboratory and field transformers. By comparing the proposed BP_AdaBoost algorithm to other intelligence algorithms, it is demonstrated that it not only performs better in generalization, but also maintains a high level of accuracy. [ABSTRACT FROM AUTHOR]

The insulation system in a transformer degrades over time and it needs periodic monitoring for uninterrupted operation of the power system network. Moisture content (MC), acid number, and dissolved gases are the important parameters that establish the aging and degradation status of the transformer liquid insulation. This work focuses on using high-frequency signals nonintrusively for estimating the degradation of the transformer liquid insulation by considering the MC and acid content. A novel nonintrusive and nondestructive testing method using an ${S}$ -band pyramidal horn antenna is introduced in this work to estimate the degradation of the liquid insulation with respect to aging duration. The scattering parameter ${S}_{{11}}$ of the liquid insulation is first characterized and measured in an anechoic chamber to avoid electromagnetic interference (EMI). These tests are performed initially on laboratory-aged mineral oil (MO) samples and a prediction curve of $\vert {S}_{{11}}\vert $ as a function of moisture and acid number is obtained. $\vert {S}_{{11}}\vert $ of the in-service transformer oil samples is then compared with the prediction curve and the degradation status is predicted. It is found that the chosen frequency band is able to differentiate the aging status of MO accurately. This technique can be used for establishing the degradation status of any type of liquid insulation. A miniature version of the proposed technique can be used for portable and faster condition assessment of insulating oils. [ABSTRACT FROM AUTHOR]

This article discusses an advanced method for estimating dc conductivity of oil using parameters evaluated under switching impulse voltage application. Firstly, the effectiveness of switching impulse application for assessing the condition of oil–paper insulation is investigated. Thereafter, the evaluated parameters under switching impulse voltage are fitted by Havriliak and Negami (HN) model for estimating the oil conductivity. The method is applied on oil-impregnated pressboards containing different moistures and a distribution transformer for experimental investigation. Moreover, the limitations of the proposed method are also discussed in this article. [ABSTRACT FROM AUTHOR]

The generation and distribution of furfural are significantly affected by moisture content in the insulating paper. However, the diffusion mechanism of furfural under moisture effect is not clear, hence, this study investigates the effect of moisture on the diffusion characteristics of furfural by combining macro experiment and micro molecular dynamics simulation. The simulation results demonstrate that the increased moisture content in paper accelerates the diffusion of furfural from paper to oil, which is also proved by the experimental data. Then, the results of interaction energy analysis indicate that the increase of moisture enhances the van der Waals force between oil and furfural. The present findings are expected to improve the theoretical level of furfural analysis, which will facilitate the aging evaluation of the transformer insulating paper based on furfural. [ABSTRACT FROM AUTHOR]

An accurate discrimination on moisture status of oil-impregnated paper (OIP) bushings is crucial for the maintenance and replacement schedule of bushings. Based on frequency-domain spectroscopy (FDS) measurement and Dissado–Hill (DH) relaxation model, this article proposes a hybrid approach of hidden Markov model and gray wolf optimization (GWO-HMM) for MS estimation of bushings subjected to the ununiform moisture distribution and dynamic time-series modeling. First, simulation models of moisture diffusion and FDS of the OIP bushing were constructed using finite element modeling approach. Then, the GWO algorithm was employed to explore dielectric parameters influenced by moisture in the DH model. Then, the GWO-HMMs was adopted as a classification tool to discriminate the MS of the simulation and experimental data of the bushings. Classification results confirm that the average identification accuracies of the proposed method are 97.17% and 96.81% over these two datasets, which demonstrates the effectiveness of the proposed moisture estimate method for OIP bushings. [ABSTRACT FROM AUTHOR]

Development and deployment of sensing technologies is one of the main steps in achieving sustainability in crop production through precision agriculture. Key sensing methodologies developed for monitoring soil moisture and nutrients with recent advances in the sensing devices reported in literature using those techniques are overviewed in this article. The soil moisture determination has been divided into four main sections describing soil moisture measurement metrics and laboratory-based testing, followed by in-situ, remote and proximal sensing techniques. The application, advantages and limitations for each of the mentioned technologies are discussed. The nutrient monitoring methods are reviewed beginning with laboratory-based methods, ion-selective membrane based sensors, bio-sensors, spectroscopy-based methods, and capillary electrophoresis-based systems for inorganic ion detection. Attention has been given to the core principle of detection while reporting recent sensors developed using the mentioned concepts. The latest works reported on the different sensing methodologies point towards the trend of developing low-cost, easy to use, field-deployable or portable sensing systems aimed towards improving technology adoption in crop production leading to efficient site-specific soil and crop management which in turn will bring us closer to reaching sustainability in the practice of agriculture.

In this paper, a comprehensive review of portable microwave sensors for monitoring moisture content (MC) is presented. MC monitoring is crucial in different industries, particularly food and farming. Microwave-based approaches for measuring the MC of the grains and mineral materials are studied. These approaches are categorized into three groups: S-parameters, dielectric constant, and impedance measurements. While these methods are interrelated, they have differences. The investigated methods use different microwave antenna sensors for MC monitoring, such as coaxial probes, horn antennas, loop antennas, microstrip patch antennas, and frequency selective surface (FSS) antenna. State-of-the-art microwave sensors were investigated thoroughly to clarify the current challenges and possible solutions of MC monitoring. A comparison between the investigated sensors was made to determine their advantages and disadvantages. According to the comparison, sensors operating above 10 GHz suffer from cross-interference. Moreover, microstrip patches can monitor a wide MC range as extensive as 60%. At the same time, the FSS sensor has the highest sensitivity with an error as low as 0.023% at X-band. Microstrip patch and FSS antennas can be printed directly on a flexible, low-loss, and lightweight material to monitor the grain MC. The flexibility, compactness, portability, ease of environment-friendly fabrication, and high sensitivity are among the criteria determining the most suitable microwave sensors for industrial and consumer MC monitoring applications.

The article concerns a method of drying cellulose insulation of distribution transformers with the use of synthetic ester. This method uses the high solubility of water in the ester compared to other dielectric liquids. The method is based on the striving of the oil-paper insulation system for a state of moisture equilibrium. Water migrates from the cellulose insulation of the high moisture content to the synthetic ester which is subjected to continuous drying. The research was carried out on a complex laboratory model reflecting the transformer insulation system. In this model, the drying of the ester was carried out using a molecular sieve with an appropriately selected adsorber weight. To check the drying efficiency of the cellulose insulation, the water content in the pressboard strips taken from the model, both before and after the drying process, was determined. The water content was measured using the Karl Fischer titration method. The research showed the high efficiency of the proposed method of drying. With the ester moisture in the range of 110-130 ppm and the insulation system temperature of about 70 °C, the loss of water in the samples dried for 7 days was over one percentage point. The obtained test results constitute the basis for the validation of the method on distribution transformers.

Contamination control and mitigation is a vital function in the semiconductor manufacturing process, especially with the ever-decreasing feature size of wafers making them more prone and sensitive to contamination. If not properly handled, it could lead to the formation of wafer defects extending to yield reduction and device performance deterioration. Purging the front opening unified pods (FOUP) that carry semiconductor wafers between process steps by the use of diffuser purge and air curtain technology are just two examples of approaches by which contamination could be controlled. With the optimization objective of minimizing both the relative humidity (RH) and total clean dry air (CDA) that would be used by both diffuser-purge and laminar air curtain supply, in this study, the optimum values predicted for the input parameters using the response surface optimization (RSO) tool by Ansys DesignXplorer are as follows: 30 mm air curtain width, 0.3 m/s FFU velocity, 0.3 m/s air curtain velocity and 130.01 l/min flow rate total for the two diffuser-purge. These optimum values of the aforementioned parameters are predicted to maintain the allowable amount of moisture inside the FOUP as specified by the semiconductor industry, while using the least amount of clean dry air. [ABSTRACT FROM AUTHOR]

Microchip features continue to reduce in size year after year. Oxygen (O2) and moisture present in ambient air can cause product defects and therefore lower production yield. Smaller feature sizes are more sensitive to humidity and oxygen, resulting in a greater potential for defects to arise during wafer processing. Therefore, the level of oxygen and moisture needs to be minimized during integrated circuit (IC) manufacturing. Purge gases like clean dry air (CDA) or nitrogen (N2) are commonly used to reduce the level of oxygen and moisture inside a front opening unified pod (FOUP). In this study, purge cleaning performance was experimentally assessed by streamlines flow analysis, particle image velocimetry (PIV), relative humidity (RH) measurement, and oxygen concentration measurements during purging with practical flow rates of 130, 200 and 300 LPM. The experiments show 200 LPM can be the optimum purge flow rate for a high level of cleaning efficiency and a low level of vibration and instabilities. This purge flow rate can be used to increase product quality through a reduction in defect frequency, while reducing annual energy consumption by the semiconductor manufacturing industry. [ABSTRACT FROM AUTHOR]

Adaptive and targeted allocation of mobile sensing agents, in the form of unmanned aerial vehicles (UAVs) with software defined radar (UAV-SDRadar) payloads, enable mapping of surface soil moisture in regions where in situ wireless sensor networks (WSNs) undersample soil moisture or upscaling models perform poorly. This work presents an optimization-based UAV path planning methodology that seeks to maximize UAV flight coverage over areas where a complementing WSN yields upscaled soil moisture estimates with high uncertainty. By recursively mapping soil moisture over such areas, the combined UAV and WSN instrumentation can gradually capture the domain’s true mean soil moisture. A series of numerical simulations are presented to demonstrate the algorithm’s basic function while considering real-world and feasible operational scenarios. [ABSTRACT FROM AUTHOR]