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Ultrasonic water meters have current widespread problems of poor site adaptability, low measurement accuracy, and poor stability. A high-precision intelligent ultrasonic water meter with self-diagnosis function and adaptive technology was proposed in this paper, which is focus on improving the measurement accuracy and repeatability of the small pipe diameters. The hardware circuit design of the ultrasonic water meter studied in this paper adopts the low-power STM32L053 microcontroller with Cortex-M0 core architecture and the high-precision 11 ps time resolution timing chip TDC-GP30 to complete the metering function. The software combines pulse width ratio and amplitude voltage measurement technology to make the water meter have self-diagnosis function, avoid measurement errors caused by accidental factors, improve adaptability and measurement accuracy, also the application of adaptive measurement period method is used to improve measurement repeatability. The software adopts the moving average filtering algorithm, which effectively reduces the fluctuation of the time-of-flight(ToF) difference and improve the measurement accuracy of the flow point in the low zone (between the minimum flow and the boundary flow). The experimental verification results show that the accuracy of the small-caliber ultrasonic water meter can reach within ±1.5 %, and the repeatability is less than 0.5 %. In the face of fluid disturbances, adaptive technology is used in this water meter to adjust the measurement period and carry out self-diagnostic function research, and automatically respond to deal with abnormal faults, thereby realizing the demand for intelligence.

Partial discharge (PD) signal classification analysis on cross-linked polyethylene (XLPE) cables is complex, requiring a comprehensive understanding of the characteristics of PD patterns. In the realm of high-voltage electrical insulation, PD pattern characteristics, such as PD charge and inception voltage, are essential as assessment criteria in diagnostics systems using PD classifiers. This paper provides a review of the various PD patterns and classifiers used by previous researchers, specifically for XLPE cables. In addition, the differences of the studies on various sensor developments based on PD detection in the past 27 years are also discussed. The repeatability, recognition accuracy, recognition speed, and effect of feature sizes on each PD classification method are reviewed and explained. This review indicates that the pattern recognition for PD signal using artificial neural network (ANN) exhibits better performance than the other methods in terms of accuracy and repeatability, and the reduction of feature size does not affect the accuracy of ANN.

A parallel-mechanism-equivalent model for repeatability analysis of an overconstrained kinematic coupling is proposed. An overconstrained Kelvin-type coupling with one additional support is introduced and used for method illustration. Contact forces of the an overconstrained coupling under a preload are computed with the Moore-Penrose inverse, and the deformations are obtained using the Hertz theory. The coupling is equivalently modeled as a 7-SPS parallel mechanism, the spherical joints of which represent centers of supporting balls and contact points, and prismatic joints are used to simulate the deformations. Therefore, the pose error of the coupling due to a preload is analyzed using the well-appraised incremental method for forward kinematics analysis of parallel mechanisms. The uncertainties of the preload are discussed and a boundary-sampling method is proposed for repeatability analysis. The main contribution of this study lies in the greatly simplified repeatability analysis of overconstrained kinematic couplings by the proposed parallel-mechanism-equivalent model and the boundary-sampling method. Finally, the proposed methods are validated by a case study.

Nowadays, traceability, combined with stable and constant identification of industrial parts, is becoming a crucial element of production processes. Laser marking of metal parts is a technology that shows many advantages compared to labeling, inkjet, or dot marking. The advantages include no consumables, faster cycle time, reliability and repeatability of the process, and stability of the markings. In this article, we aim to study the physics associated with the process of laser colour marking on stainless steel X5CrNi18-10 In a certain range of changes in the technological parameters of 20 W fiber laser. Different color characteristics of the surface are also discussed with regard to the laser parameters. The influence of the raster step, the relative speed of the laser beam, as well as the laser pulses frequency on the color marking process were studied. Test fields consisting of matrices of squares have been created. The laser marking is realized with different parameters for each square. Photographic material of the samples in the processing area is presented. A high-resolution metallographic microscope was used. A universal methodology was used to determine the saturation of the studied colors. Experimental studies were conducted several times in order to verify the repeatability of the results. The influence of the parameters of the laser process on the obtained concrete colour is analyzed and the results are summarized. Intervals of the parameters of processing under laser influence for obtaining a specific colour on this steel are also determined.

In this paper, we present, for the first time, the advantage of CMOS capacitive sensor for the assessment of dried DNA from an aqueous sample for DNA storage applications. The proposed capacitive sensor consists of a differential capacitance to current converter block based on a core-CBCM circuit, a 300 MHz current controlled oscillator and a 12-bit counter that creates the digital output of the chip. The chip has been fabricated using AMS 0.35µm technology. We demonstrate the functionality and applicability of the proposed sensor for dried DNA nano-mass measurement using single-strand DNA samples. The sensor shows acceptable repeatability in quantifying the DNA nano-mass with a sensitivity of 18.5 aF/ng mass of DNA based on the results described here.

We have designed and fabricated an automated eight-channel phantom simulator of a human electroencephalogram (EEG). This device was developed for use as an automated test bench, a laboratory installation for research or as a precision generator of ultra-low voltage signals for the development of analog circuits in EEG recording devices. In this work, the repeatability of the reproduced EEG and test signals was evaluated. Schemes and experimental results are presented. The obtained data show that the artificial EEG correlates with the original one with a coefficient of 0.8-0.9. The coefficient of variation does not exceed 10%, which indicates a sufficient level of repeatability of EEG reproduction.

The artificial muscles of a biomimetic model of the human stomach require positional control of the (linear track) sliders that the actuated muscles are attached to. A novel servomechanism for positional control of a slider on a linear track has been explored using a basic, low -cost stretch sensor as a means in determining the sliders' absolute position over time. The stretch sensor was constructed from a silicone (PDMS) tube filled with an ionic liquid (saline) and exhibited good characteristics of linearity and low hysteresis. A micro controller was used for conditioning the sensor feedback and software control over the slider positioning. Initial results indicate a coarse approximation is attainable of the slider position relative to its targeted position. However, further testing is required to determine operational life-time and other factors such as repeatability, drift and potential for improved accuracy.

Reducing the diameter of FBG cladding by hydrofluoric acid can improve the sensitivity and response speed of humidity sensor, and has little effect on repeatability.

Due to the Covid-19 pandemic, many places with high traffic of people set up sanitary barriers to screening febrile people. Thermal imagers and pyrometers are the equipment commonly used to measure temperature in these barriers. In this paper, Temperature measurements performed by these instruments were compared considering the regions usually monitored in these barriers: forehead, ear, and wrist. The temperatures of volunteers were recorded after initial acclimatization, a short period of physical exercise, and a rest period after exercise, evaluating the instruments and regions of measurement and the influence of the condition of rest and physical exercise of the person. The compatibility of the performed measurements in each of these three moments was then compared using statistical and metrological tools. The outcomes showed that the pyrometer has low repeatability since its results vary widely among different measurements due to the temperature variation existing within the analyzed region and the difficulty of guaranteeing the same measurement point. As a result, a thermal imager is more recommended for taking body temperature measurements on the forehead and, preferably, on the ear. It was also determined that the wrist, in particular, has a significantly lower temperature than the central body temperature, and thus this is not a recommended region to measure body temperature when screening febrile people.

In this paper, a pressure measurement system is proposed based on reflective optical sensors. An array of nine sensors was embedded into a 3D multi-stack printed sample made of silicone rubber. The sample consisted of nine rectangular cells. The fabricated sample was designed to operate in medium- to high-pressure regimes. A customized Java-based application was developed to synchronize and automate the measurement process between a motorized force measurement test stand and a data acquisition system. The compression tests of a single cell showed good linearity and a dynamic range. Sensitivity and dynamic ranges of 0.001 kPa−1 and 1040 kPa, respectively, were obtained. Depending on the application, the sensitivity and dynamic range can be adjusted by changing the wall thickness of the cells. The proposed system exhibited good repeatability, durability, and dynamic stability over a wide range of applied pressures. The proposed pressure system has potential applications in sports biomechanics and health-monitoring systems.

1,4-bis[2-(5-thiophen-2-yl)-1-benzothiophene]-2,5-dioctyloxybenzene (BOBzBT 2 ) is a functionalized organic pentamer that was used to modify the carbon working electrode surface to be used as a biosensor for creatinine detection. BOBzBT 2 has good solubility characteristics in common organic solvents. Although it is insoluble in water, BOBzBT 2 is able to be stored in a relatively stable condition. In addition, the hydrophobic property of BOBzBT 2 enables it to be reusable. This is especially useful for the non-destructive sensing application besides ensuring stability even in environments with high humidity. The BOBzBT 2 modified sensor was compared to the unmodified sensor to see the improvements in charge transfer. A repeatability test was performed on the modified sensor to determine whether the modified sensor can be used repetitively or only for single use. A reproducibility test was also performed on the modified sensor to determine whether the modified sensor can be used to reproduce consistent data. The BOBzBT 2 modified sensor was compared to the unmodified sensor to see the improvements in charge transfer.

Torsion sensing is a promising technique in a variety of different scientific and industrial applications. In this paper, we present a novel torsion sensor based on the cascaded long-period fiber grating inscribed in a four-mode fiber (CLPFG-FMF). The change in rotatory vector makes resonant wavelength shift, for the twisted CLPFG-FMF. The key factor, which severely impacts on the properties and performance of torsion sensor, is also investigated and discussed. Experimental results show that the resonant wavelength linearly shifts with the torsion rate and the cascaded angle plays an important role in enhancing torsion sensitivity. The proposed torsion sensor achieves optimal sensitivities of -0.519 nm/(rad/m) in counterclockwise and 0.501 nm/(rad/m) in clockwise. The repeatability and stability of the CLPFG-FMF with cascaded angle of 0° are studied as well. The refractive index sensitivity of the CLPFG-FMF with cascaded angle of 0° is -5.20 nm/RIU from 1.3431 to 1.4374 refractive index ranges and the temperature sensitivity is -0.0173 nm/°C from 25 °C to 90 °C. The high sensitivity of torsion sensing is expected to be useful for broad applications across engineering fields.

A new approach to identify and diagnose the quality of extensive and multivariate data is presented, using the gage repeatability and reproducibility (GR&R) study through the weighting of rotated factor scores. The proposal uses axis rotation to improve the explanation and interpretations of latent information, providing a statistically appropriate alternative when dealing with two or more correlated data sets. To analyze data with a significant variance-covariance structure, factor analysis (FA) is applied for calculating the eigenvalues and extracting of the rotated scores. Once obtained, these scores are then weighted with their respective eigenvalue for each factor. This procedure results in a single response vector, which is capable of properly interpreting all of the quality responses analyzed. To illustrate an application of the method, a real data set from a resistance spot welding process is selected, and two different types of rotation are compared. The proposed method provided an output that contemplated all of the significant variability of the data in a unique and significant way. In addition, the method enabled a reduction in the data dimensionality, thus minimizing the time for analysis and computational effort.

Deep learning training typically starts with a random sampling initialization approach to set the weights of trainable layers. Therefore, different and/or uncontrolled weight initialization prevents learning the same model multiple times. Consequently, such models yield different results during testing. However, even with the exact same initialization for the weights, a lack of repeatability, replicability, and reproducibility may still be observed during deep learning for many reasons such as software versions, implementation variations, and hardware differences. In this article, we study repeatability when training deep learning models for segmentation and classification tasks using U-Net and LeNet-5 architectures in two development environments Pytorch and Keras (with TensorFlow backend). We show that even with the available control of randomization in Keras and TensorFlow, there are uncontrolled randomizations. We also show repeatable results for the same deep learning architectures using the Pytorch deep learning library. Finally, we discuss variations in the implementation of the weight initialization algorithm across deep learning libraries as a source of uncontrolled error in deep learning results.

In this paper, utilizing the technology of color laser marking of stainless steel in industrial productions is investigated from the perspective of repeatability and stability of produced color markings. The color laser marking has remarkable advantages over conventional metal coloring methods; however, in order to implement this technology in industry, the reliability, stability and quality of resulting markings must be endorsed. For this purpose, an AISI 304 color palette made up of fifteen colors was evolved. The dependence of produced colors on different laser processing parameters were analyzed. Afterward, the produced colors were tested utilizing optical, scanning electron and atomic force microscopy, and the configuration of oxide films was specified through Raman spectroscopy. The obtained colors had proper uniformity, brightness, and cover almost all spectral regions. Also, color standardization and palette repeatability test were performed by assessing and evaluating the reflectance spectra of the formed colors. The color palette demonstrated high repeatability for all colors except for one specific color. Moreover, the stability of color markings in terms of environmental, mechanical and chemical resistance was investigated. The resulting colors showed high resistance in most of the environmental conditions; however, exposure to very high temperatures and extreme humidity ( $100^{\circ }\text{C}$ , 90%) and low temperature and extreme humidity ( $- 40^{\circ }\text{C}$ , 90%) leads to deterioration of few colors. Color marks showed high hardness and excellent mechanical stability to external impacts and outstanding resistance to various chemicals, excluding acidic solutions and salts.

An ultrafine frequency linearly tunable single-frequency fiber laser based on the intracavity active tuning is demonstrated. Single-frequency operation can be achieved by an ultrashort cavity and ultranarrow polarization-maintaining fiber Bragg grating. A sub-nanometer-accuracy piezoelectric ceramic actuator with closed-loop mode has been employed to realize the cavity-length active tuning scheme, which can achieve a linear tuning range of >1 GHz with a 3.2-MHz/nm tuning resolution. The periodic tuning repeatability and repeat accuracy show that the scheme can realize linear frequency tuning with great tuning repeatability and high tuning precision.

Joint acoustic emission (JAE) sensing is emerging as a potential modality for quantitative at-home joint health assessment. We designed and validated a low-profile, easy-to-use wearable system for JAE sensing at the wrist. An embedded microcontroller on a wrist-worn printed circuit board is used to record multi-microphone (mic) joint acoustics sampled at 46.875 kHz using an on-board analog-to-digital converter. A flex sensor and a force sensitive resistor (FSR) are sampled at 300 Hz to capture kinematics and mic backing force. Custom sensor casing solutions and real-time user feedback systems enhance audio sensing capabilities at locations both proximal and distal to the wrist. An experiment extracting wrist JAEs from healthy adults (n=6) allowed for comparison to a previously established benchtop JAE sensing system. The acoustic data were bandpass filtered (150 Hz-5.5 kHz). Qualitative observations reveal the wearable system mics successfully capture JAEs. Signal-to-noise ratio (SNR), intraclass correlation coefficient (model 3, k), and coefficients of variability were calculated to evaluate acoustic signal strength and repeatability in both systems' recordings. SNR reveals that JAE acoustic signal strength is higher when recorded using the wearable system than with the benchtop system (p

We present a study of measurement repeatability in soil dielectric spectrum characterization. In this study we employ a novel multi-channel system for 0.05–3 GHz soil dielectric spectrum measurements which allows for simultaneous measurement of six different soil samples. The use of this system makes it possible to easily separate errors due to sample loading and preparation from the errors caused by the cell connection nonrepeatability. Results of our study demonstrate that the limiting factor for the repeatability of soil dielectric-spectrum characterization is the very process of sample preparation and loading. Our results may serve as a first step in the difficult task of establishing an uncertainty analysis for soil dielectric measurements.

A new framework is presented for training neural networks that is based on the characterisation and stabilisation of measurement variations. The framework results in a number of useful properties that maximises the use of data as well as aiding in the interpretation of results in a principled manner. This is achieved via variance stabilisation and a subsequent standardisation step. The method is a general approach that may be used in any context where repeatability data is available. Standardisation in this manner allows goodness of fit to be quantified and measurement data to be interpreted from a statistical perspective. We demonstrate the utility of this framework in the analysis of advanced manufacturing data.

Hereditary Spastic Paraplegia (HSP) is a rare inherited neurological disorder, whose predominant feature is a spastic gait. Gait analysis represents an objective tool to quantify the impairment of gait pattern in patients with HSP, thus supporting diagnosis and monitoring of disease progression. This study contributes to the characterization of HSP pathological gait, providing the assessment of test-retest repeatability of 122 parameters regarding postural sway, anticipatory postural adjustment in step initiation, gait and turn tasks. Data are collected on a cohort of thirty-five HSP patients, performing three consecutive repetitions of the Instrumented Stand and Walk (iSAW) test provided by Mobility Lab gait analysis system by APDM. Intraclass Correlation Coefficient (ICC) is used to assess repeatability. Repeatability Limit (RL) has also been evaluated and compared to the absolute value of difference (DoM) of HSP patients' measurements mean and normative mean of the same variable, in order to understand which variable can better characterize HSP gait with respect to normal gait. Results show that gait and turn measurements are more repeatable than sway and anticipatory postural adjustments variables. Furthermore, this study confirms previous findings in this field, identifying, among other gait parameters, cadence, gait velocity, stride length and RoM of the shanks as the main distinctive parameters of the pathology. Conversely, the RoM of the knees presents excellent repeatability, but low difference between healthy and pathological subjects.

Vibration and noise exposure during emergency neonatal ground and air transport are recognized as hazards for the neonate; however, no standardized test environment exists to reliably quantify such exposure with high repeatability. An on-road test was performed to provide a quantitative measurement of on-road vibrations to be used in the development of the standardized test environment. This paper details the ambulance on-road test instrumentation, analysis, and results. On-road findings indicate that neonates experience vibrations that exceed adult standards; that the power spectral density of the acceleration at the neonate contains peaks (at 2 Hz and 9 Hz) in the frequency range humans are most sensitive (1-20 Hz); and that the damped natural frequency of the patient transport system considered is 9.5 Hz.

The pandemic COVID-19 is still requiring several countermeasures to adopted in order to decrease the virus spread. Among others, face masks have shown their potentiality to reduce the person-to-person transmission. For this reason, several research groups and/or industries focused their supply chain in the production of innovative materials for the face mask design. Considering the surgical mask, several parameters have to be checked before their commercialization, as for example the breathability. This study aims at evaluating the repeatability and reproducibility of the breathability measurement in surgical masks, and at assessing the effects induced by the selected measurement points on the mask. Three samples for each type I, II and IIR masks were tested within the experimental protocol. Breathability was measured by following the UNI EN 14683:2019. Fifteen measurement points were identified for each mask and the measure was repeated five times per each point. Standard deviation across the repeated measures on the single point and across the different tested areas were used to evaluate the repeatability and reproducibility of the procedure, respectively. The measurement uncertainty was also computed. In addition, in order to verify the effects induced by the selection of five points out the available fifteen, as requested by the UNI EN 14683:2019, all combinations of points were tested. Results showed a high value of reproducibility error, leading to the consideration that different areas of the same mask are characterized by different values of breathability. Thus, the selection of the five measurement points to perform the breathability measurement according to the standard is a crucial aspect that can influence the result of mask compliance. The results of the present paper could provide useful information for the standardization of the breathability measurement.

A method for the contactless endpoint detection of gold etching using a quartz-based capacitive detector is reported herein. To design a microfabrication process, the etch rates of materials to be used must be determined to control the etch depth. However, the etch rate changes gradually when the etching solution is used repeatedly. An endpoint and/or etch rate detection method is required to ensure process repeatability in a manufacturing environment. This method should be contactless because the etchants for metals are typically highly corrosive. In this study, a 32 MHz quartz-crystal oscillator is used to detect changes in the concentration of specific ions. The developed method can detect nanometer-order thickness changes during gold etching.

This interlaboratory comparison is performed for two reasons: to ensure the repeatability of testing amongst EMC laboratories concerning specific test methods and to evaluate the testing capabilities of these laboratories. The purpose of this paper is to present the application of an interlaboratory comparison method for electromagnetic fields produced by power supply systems, involving two laboratories. An electromagnetic field generator with a frequency of 50 Hz, which is moved from one laboratory to another, is used in order to obtain the data for the final assessment. The results obtained were based on the three-point measurement method in accordance with the standard IEC 61786.

The article deals with experimental measurements by the ultrasonic pass-through direct method. And it compares the reliability and repeatability of measurements when using an exponential probe, which has some advantages, but it is necessary to observe some conditions guaranteeing the repeatability of measurements.

Baropodometry is currently used in many sectors of human movement analysis in both clinical and sports fields. The effects induced on the gathered data by a different feet positions during static tests is still an open question as well as which position guarantees the most reliable and repeatable measures. Thus, the purpose of the study is firstly to test the reliability and repeatability of the baropodometric indices and, secondly, to evaluate their dependency with the position of the feet. Tests were conducted on height healthy subjects, asking them to perform static trials with four different feet positions among the most used in the literature. Each trial was repeated three times for each session and three sessions were performed one week apart. Inter-Class Correlation Coefficient was used to evaluate both the intra- and inter-day reliability, as well the standard deviation was assumed as the index of repeatability. The results showed excellent intra-day and inter-day reliability in almost all parameters analyzed and for all positions, especially regarding parameters related to pressure and footprint area. Lower values emerged for the podalic angle and the parameters concerning the load distribution. The orthostatic position proved to be the most repeatable and reliable. The ANOVA analysis highlighted differences between the self-selected position and the other ones. In conclusion, operator should select the orthostatic position when performing baropodometric analysis and compare obtained indices only if they have been gathered with the same feet positions.

This study relates to the vision module configuration and auto-focus algorithm method to accurately measure misalignment of top and bottom align-keys on the interface of bonded wafer. In general, to measure the center difference of align-keys that exists in the interface between wafers, focus on align-keys and acquire image. However, there is a height difference between align-keys of top and bottom, and the accuracy varies considerably depending on where it is focused on. To improve the accuracy, this study developed a vision module and an auto-focus algorithm to accurately focus and calculate align-key center value differences. The vision module consists of an IR CCD camera and IR lamp to transmit wafers, a laser sensor to measure the interface between bonded wafers, and a piezo z stage to adjust the focal height. In conventional auto-focus algorithms, the Auto-Focus Value(AFV) is simply selected to find the optimal focal height. In this study, each AFV was analyzed through multi-AFV for more precise measurement, and the optimal focal height was derived based on the analyzed results. Finally, the vision repeatability was measured in the whole range in order to verify whether it was measured most precisely at the focal height derived from the auto-focus algorithm developed through this study. Each vision repeatability was calculated and compared. The results showed that the vision repeatability at the optimal focal height derived from the developed algorithm was the best. That is to say, the optimal focal height was well chosen. This research result can be used for wafer alignment when wafer to wafer bonding, and it can be actively used for misalignment measurement of bonded wafers after bonding. In addition, not only wafer level measurements, but also chip to wafer, chip to chip bonding. Also, it can be used for various vision analysis such as alignment analysis and misalignment measurement.

Many robotics applications require interest points that are highly repeatable under varying viewpoints and lighting conditions. However, this requirement is very challenging as the environment changes continuously and indefinitely, leading to appearance changes of interest points with respect to time. This paper proposes to predict the repeatability of an interest point as a function of time, which can tell us the lifespan of the interest point considering daily or seasonal variation. The repeatability predictor (RP) is formulated as a regressor trained on repeated interest points from multiple viewpoints over a long period of time. Through comprehensive experiments, we demonstrate that our RP can estimate when a new interest point is repeated, and also highlight an insightful analysis about this problem. For further comparison, we apply our RP to the map summarization under visual localization framework, which builds a compact representation of the full context map given the query time. The experimental result shows a careful selection of potentially repeatable interest points predicted by our RP can significantly mitigate the degeneration of localization accuracy from map summarization., Comment: Accepted at IEEE International Conference on Robotics and Automation (ICRA) 2021