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Space gravitational wave telescopes are critical in achieving precise interstellar laser interferometry. The coupling coefficient is a key metric for evaluating the ultimate performance of a telescope. However, alignment errors during the assembly phase can degrade the wavefront quality of the telescope, intensify coupling noise, and impair overall performance. Currently, no alignment scheme specifically targets the coupling-noise coefficient of telescopes. To address this, this study proposes a sensitivity matrix model that relates misalignment to the coupling coefficient and establishes clear sampling criteria for coupling noise at the exit pupil of the telescope. The model incorporates second-order correction terms, enabling a more accurate characterisation of the relationship between misalignment and tilt-to-length coupling-noise coefficients. Based on this model, an alignment scheme was developed using the coupling coefficient as the evaluation metric. Owing to the significant differences in the magnitudes of sensitivity among different misalignments and their mutual coupling effects, the predicted alignment parameters often differ substantially from the actual values. To resolve this issue, a misalignment grouping strategy was proposed to reduce prediction errors. Additionally, an iterative algorithm and a sequential adjustment strategy for components were provided to ensure alignment effectiveness. Finally, the feasibility of the proposed method was verified using a typical space gravitational wave telescope model. Experimental results show that the method successfully aligned 500 randomly misaligned samples, with all samples satisfying the requirement of a coupling noise of less than 25 pm μ rad−1 after alignment. This method provides new guidance for the alignment of space gravitational wave telescope systems. [ABSTRACT FROM AUTHOR]

Aperture space telescopes are widely used in space debris size information detection and celestial body detection work. For the problem of limited space inside the optical system of large aperture telescopes, a space telescope mounting method based on the intrinsic coefficient sensitivity matrix is proposed by combining the wavefront detection technology. Compared with the traditional sensitivity matrix method, the method in this paper does not need to partition the detector and simplifies the construction of the wavefront reconstruction matrix. Characterisation of the system wave aberration is realised by using the eigenfactors, and the sensitivity matrix model is established according to the amount of misalignment. The experimental tests are carried out on the telescope with a diameter of 1.2 m, and the results show that the root mean square (RMS) values of the wavefront aberration in the centre field of view are less than λ / 16 under the cases of eccentricity misalignment of the sub-mirror and tilting misalignment with the phase-aberration correction, which is of good value for the mounting of space telescope optical systems. [ABSTRACT FROM AUTHOR]

In this paper, for observing the target spacecraft from many viewpoints, we propose a parallelogram fly-around formation design with practical maintenance strategies. First, we present the concept of the parallelogram fly-around formation and analyze the relative motion along a side of the parallelogram formation. Then, the impulse-control algorithms are presented for establishing the parallelogram fly-around formation theoretically, and a rapid method is presented to estimate the range of the multi-loop parallelogram fly-around formation. Furthermore, we present double-stage finite-thrust control strategy that is easily realized in applications for maintaining the fly-around formation. Finally, we verified the effectiveness of the proposed fly-around design and maintenance strategies with numerical simulations. The proposed impulse-control strategy and double-stage finite-thrust control strategy successfully achieved the single- and multi-loop fly-around formation, which provide a practical way for establishing flexible 360° monitor for target spacecraft at an elliptical orbit. [ABSTRACT FROM AUTHOR]

Morelet's crocodile populations have limited distribution along the coast of Mexico, Belize, and Guatemala, and have been greatly affected by human activities. Morelet's crocodile is a species with high ecological and economic value. From an ecological perspective, it is an apex predator in the ecosystems in which it lives. Because of their vulnerable status is essential to have updated information on its populations over time to know their current conservation status. We analyze with a population model the vital rates of importance for the management and conservation of this species. Population growth with the Nocturnal Visual Detection model showed growth (λ = 1.027) over a 100 years, as in modeling Marking and Recapture of Specimens model (λ = 1.026). The largest reproductive value (v) was observed in the Adult stage (0.458). The sensitivity matrix indicated that the most sensitivity was offspring production by Adults (5.59). The data presented here show that the main factors impacting adult survival and the transition from Subadult to Adult stages alter population growth. Using the results of this model to quantitatively compare the conservation strategy can prove extremely useful to discern the parameters that must be taken into consideration and their potential effect on the population. [ABSTRACT FROM AUTHOR]

Relevance. The need to develop technical solutions to reduce electrical energy losses in medium-voltage distribution electrical networks of oil and gas fields. Aim. Development of an algorithm for determining the parameters of the operating mode of an electrical network, applicable in a system of optimal control of the network configuration in order to reduce the level of electricity losses in the network. Methods. Mathematical modeling methods and combinatorial optimization methods. The nodal voltage method and the Newton–Raphson method are used to calculate the network operating mode. The mode is corrected using a sensitivity matrix. Results and conclusions. The authors have developed an algorithm for determining the parameters of the electric network operating mode when determining its optimal configuration. Optimization of the optimal configuration is performed based on the criterion of minimum active power losses in lines, taking into account the limitations on the power reserve of the feeding transformer substations and the number of normal breaks on one line. The developed algorithm is based on solving nonlinear systems of equations of nodal voltages using the Newton–Raphson method, as well as on correcting the parameters of the previously calculated operating mode using the sensitivity matrix. The optimal network configuration is determined by solving the combinatorial optimization problem using the branch and bound method. The operation of the algorithm is illustrated by the example of a network section containing two overhead power lines with two power sources and three feeding transformer substations. Based on the results of the analysis of all possible network configurations determined by combinations of normal breaks, it is concluded that the use of the algorithm will reduce the level of active power losses by up to 23.8%, which will increase the efficiency of the electric grid complex.

Water scarcity is a significant global challenge, exacerbated by leakages in water distribution networks. This paper addresses the challenge of detecting leakages in rural and urban–rural water supply systems through hydraulic modelling and a sensitivity analysis. Two distinct real-world network models were studied to assess real and simulated leakage scenarios varying in location and magnitude. A distinct leakage detection approach utilizing outflow measurements from hydrants was tested. Additionally, the effectiveness of various statistical measures—such as correlation, angular closeness, Euclidean distance, Manhattan distance, Chebyshev distance, cosine similarity, and Spearman correlation—were evaluated to determine their efficacy in leakage detection. Different methods for identifying leak candidates were explored and compared, either by selecting a single leak candidate based on similarity measures or by identifying a group of candidates to mark leak hotspots. Density-based spatial clustering of applications with noise was used to assess the number of potential leak candidate groups. The study's findings contribute to the optimization of leak detection strategies in water supply networks, particularly in rural settings, where detection is challenging due to scarce measurement datasets, budget restrictions, and operational constraints. [ABSTRACT FROM AUTHOR]

Indeterminacy of ecological networks--the unpredictability of ecosystem responses to persistent perturbations--is an emergent property of indirect effects a species has on another through interaction chains. Thus, numerous indirect pathways in large, complex ecological communities could make forecasting the long-term outcomes of environmental changes challenging. However, a comprehensive understanding of ecological structures causing indeterminacy has not yet been reached. Here, using random matrix theory (RMT), we provide mathematical criteria determining whether network indeterminacy emerges across various ecological communities. Our analytical and simulation results show that indeterminacy intricately depends on the characteristics of species interaction. Specifically, contrary to conventional wisdom, network indeterminacy is unlikely to emerge in large competitive and mutualistic communities, while it is a common feature in top-down regulated food webs. Furthermore, we found that predictable and unpredictable perturbations can coexist in the same community and that indeterminate responses to environmental changes arise more frequently in networks where predator-prey relationships predominate than competitive and mutualistic ones. These findings highlight the importance of elucidating direct species relationships and analyzing them with an RMT perspective on two fronts: It aids in 1) determining whether the network's responses to environmental changes are ultimately indeterminate and 2) identifying the types of perturbations causing less predictable outcomes in a complex ecosystem. In addition, our framework should apply to the inverse problem of network identification, i.e., determining whether observed responses to sustained perturbations can reconstruct their proximate causalities, potentially impacting other fields such as microbial and medical sciences. [ABSTRACT FROM AUTHOR]

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Eddy current testing is one of the conventional non-destructive testing (NDT) technologies which is widely used in metal defects detection. Defect imaging by eddy current tomography (ECT) has advantages of visualization of defects, large detection area, fast detection speed and avoiding mechanical scanning imaging error. Sensitivity matrix is crucial in reconstructing defect images of metal materials by ECT. This article presents a sensitivity matrix of high conductivity initial estimate for ECT detecting metal materials. A 4 × 4 eddy current planar coil array and a 2 mm thickness titanium plate with defects were designed by both simulation and experiment. Based on the proposed sensitivity matrix, reliability of ECT forward problem linearization was analyzed and image reconstruction with two typical regularization methods ( L 1 and L 2 ) were investigated. Both simulation and experiment results show that ECT forward problem linearization was more accurate and reliable with the proposed sensitivity matrix especially at higher frequency. And L 1 regularization method was verified to be more suitable to reconstruct image of small defects in metal materials. This work expands the original assumption of ECT forward problem linearization, which is of great significance to improve the metal defect image accuracy of ECT. [ABSTRACT FROM AUTHOR]

Fluorescence molecular tomographic (FMT) reconstruction is commonly solved based on the Jacobian matrix, which is a first-order sensitivity matrix. Basically, using the second-order derivatives for iterative reconstruction can help improve the performance of convergence. In this paper, a reconstruction method of FMT based on the reduction of the second-order sensitivity matrix is proposed. In addition, the strategy of detectors rotation is combined into the inverse reconstruction to further improve the reconstruction quality. The reconstructed results demonstrate that the proposed method accelerates the reconstruction with high precision of inverse solutions. [ABSTRACT FROM AUTHOR]

Magnetometric measurements are widely used to solve the problems of geology, navigation, and some other fields. Currently, there exists a trend to miniaturize magnetometers and reduce their cost. However, the readings of cheap magnetometers are distorted by errors, which require the procedure of calibration. The mathematical models of errors, which are used in most known studies and accepted in this work, are described. The mathematical modeling of magnetometer measurement signals is carried out, and a principle of calibrating a magnetometric sensor by the precise measurement of change in its spatial position in a constant magnetic field is proposed. Estimates are given to the precision of restoring the calibrated parameters and to the signal restoration errors attainable when performing the calibration operations proposed in this paper. [ABSTRACT FROM AUTHOR]

Prosumer communities are integrating renewable energy sources to reduce energy costs and carbon emissions for sustainable and clean energy awareness. However, increasing solar photovoltaic penetration in low-voltage distribution networks leads to serious power quality challenges, such as overvoltage for grid operators and prosumers. Integrating electric vehicles (EVs) as deferable loads can reduce prosumer costs and maximize environmental benefits as EV charging is managed. Therefore, this paper proposes a novel EV charging management that maximizes prosumer communities’ power quality and benefits PV-rich prosumers by applying a dynamic active power curtailment framework. The methodology calculates each prosumer’s maximum power injection into the grid based on their voltage sensitivities. The performance of the developed charging management is examined on the European 906 bus low-voltage distribution networks under unmanaged, managed, and vehicle-to-grid (V2G)-empowered scenarios. The prosumers’ individual and aggregated economic cost-benefit results are analyzed considering increasing EV penetration. The results show that the proposed method considering fair active power curtailment could increase self-consumption and renewable fraction for prosumers. It is observed that increasing EV penetration could reduce the curtailed energy by 14.6%. The V2G-empowered method also increased up to 20% more renewable energy for charging EVs, improved self-consumption and renewable fraction up to 11% and 19.4%. Moreover, the V2G option reduced total costs by up to 37.93%. This work can potentially promote renewable energy sources by modifying consumers’ charging behaviors to be more sustainable and environmentally friendly.

In industrial processes, Electrical Capacitance Tomography (ECT) is a vital non-invasive imaging technique for monitoring multiphase flows. As the speed of flow increases, as for high-speed chemical reactors, it becomes crucial to enhance the acquisition speed to ensure the scan period for one frame is significantly shorter than the time it takes for the fluid to traverse the sensor length. Traditional ECT systems employ a uniform charge integration time across all electrode pairs. To address this challenge without compromising image accuracy and sensitivity, we propose an adaptive integration technique for inter-electrode capacitance measurement. This approach adjusts the charge integration time based on the distance between electrodes, with longer integration times for farther electrode pairs. By doing so, we aim to enhance measurement accuracy while maintaining efficient data acquisition speed. The proposed method is expected to significantly improve the fidelity of ECT images and the overall performance of ECT systems in real-time industrial applications, contributing to better monitoring and control of multiphase flows. Simulations and experimental validation in a high-speed fluid flow demonstrate that our method improves image visibility while maintaining suitable acquisition speeds. The adaptive technique is computationally efficient and scalable to various ECT configurations, promising broader applications in industrial process control and efficiency optimization.

Cellular lattice structures possess high strength-to-weight ratios suitable for advanced lightweight engineering applications. However, their quality and mechanical performance can degrade because of defects introduced during manufacturing or in-service. Their complexity and small length scale features make defects difficult to detect using conventional nondestructive evaluation methods. Here we propose a current injection-based method, electrical resistance tomography (ERT), that can be used to detect damaged struts in conductive cellular lattice structures with their intrinsic electromechanical properties. The reconstructed conductivity distributions from ERT can reveal the severity and location of damaged struts without having to probe each strut. However, the low central sensitivity of ERT may result in image artifacts and inaccurate localization of damaged struts. To address this issue, this study introduces an absolute, high throughput, conductivity reconstruction algorithm for 3D ERT. The algorithm incorporates a strut-based normalized sensitivity map to compensate for lower interior sensitivity and suppresses reconstruction artifacts. Numerical simulations and experiments on fabricated representative cellular lattice structures were performed to verify the ability of ERT to quantitatively identify single and multiple damaged struts. The improved performance of this method compared with classical ERT was observed, based on greatly decreased imaging and reconstructed value errors.

Capacitively coupled electrical impedance tomography (CCEIT) is an attractive improvement of electrical resistance tomography (ERT) that offers contactless measurement and utilizes both the real and imaginary parts of the impedance for monitoring conductive gas-liquid two-phase flows in the industry. The conventional CCEIT adopts the finite element method under the benchmark of conductive liquid background to obtain the sensitivity matrices, which has been validated effective in ERT for the usage of the real part information. However, few researches on the usage of the imaginary part information of the conductive fluid have been reported. More research work should be undertaken to seek the most effective sensitivity calculation benchmark for the imaginary part utilization in CCEIT. In this work, the usage of the imaginary part information under different sensitivity calculation benchmarks is studied and a new image reconstruction strategy is proposed for CCEIT. By comparing the imaginary part sensitivity matrices and the corresponding imaging performance under different backgrounds, the benchmark that can make better use of the imaginary part information is determined. With the determined benchmark, a new image reconstruction strategy of CCEIT, which utilizes the respective effective benchmarks for the image reconstruction of the two parts of the fluid impedance, and employs a novel hybrid image fusion method to obtain the final image, is presented. Research results show that the benchmark of non-conductive gas background is more effective for the usage of the imaginary part information of the conductive gas-liquid two-phase flow. And the experimental results demonstrate the effectiveness of the proposed strategy in obtaining high-quality images. Compared with the conventional image reconstruction strategy of CCEIT, the proposed strategy has better imaging performance. This research provides valuable experience in utilizing the imaginary part information of the fluid impedance and lays a good foundation for the further development of CCEIT. [ABSTRACT FROM AUTHOR]

This paper introduces a sensitivity matrix decomposition regularization (SMDR) method for electric impedance tomography (EIT). Using k-means clustering, the EIT-reconstructed image can be divided into four clusters, derived based on image features, representing posterior information. The sensitivity matrix is then decomposed into distinct work areas based on these clusters. The elimination of smooth edge effects is achieved through differentiation of the images from the decomposed sensitivity matrix and further post-processing reliant on image features. The algorithm ensures low computational complexity and avoids introducing extra parameters. Numerical simulations and experimental data verification highlight the effectiveness of SMDR. The proposed SMDR algorithm demonstrates higher accuracy and robustness compared to the typical Tikhonov regularization and the iterative penalty term-based regularization method (with an improvement of up to 0.1156 in correlation coefficient). Moreover, SMDR achieves a harmonious balance between image fidelity and sparsity, effectively addressing practical application requirements. [ABSTRACT FROM AUTHOR]

We address a claim frequently raised by one author that determination of Earth’s gravity field by satellite observations using traditional methods is mathematically flawed. Specifically, attention is drawn to the practice of setting to zero the initial sensitivity matrix in the variational equations for force model parameters. It is asserted that this would lead to mathematical contradictions. In this paper we establish necessary and sufficient conditions for the initial sensitivity matrix to be zero—conditions that are well founded and accepted worldwide in classical satellite-based determinations of the gravity field. To claim otherwise is shown to be without basis. We inspect a proposed counterexample, and find it, too, requires zero initialization of the sensitivity matrix. In addition, we review proofs and derivations from a classic textbook that also confirm zero initialization. In a numerical exercise, perfect, synthetic data for the central force problem are processed with standard procedures, and results confirm the validity of zero initialization of the sensitivity matrix. [ABSTRACT FROM AUTHOR]

Fiber-optic magnetic field sensors have garnered considerable attention in the field of marine monitoring due to their compact size, robust anti-electromagnetic interference capabilities, corrosion resistance, high sensitivity, ease of multiplexing and integration, and potential for large-scale sensing networks. To enable the detection of marine magnetic field vector information, we propose an optical fiber vector magnetic field sensor that integrates three single-axis sensors in an orthogonal configuration. Theoretical analysis and experimental verification are conducted to investigate its magnetic field and temperature sensing characteristics, and a sensitivity matrix is established to address the cross-sensitivity between the magnetic field and temperature; experimental tests were conducted to assess the vector response of the three-dimensional (3D) vector sensor across the three orthogonal axes; the obtained experimental results illustrate the commendable magnetic field vector response exhibited by the sensor in the orthogonal axes, enabling precise demodulation of vector magnetic field information. This sensor presents several advantages, including cost-effectiveness, easy integration, and reliability vectorially. Consequently, it holds immense potential for critical applications in marine magnetic field network detection. [ABSTRACT FROM AUTHOR]

Underground mines have gradually entered the stage of deep mining with the consumption of shallow mineral resources, which makes mine ventilation networks generally complicated and the problem of unstable supply of branch airflow volume in deep-level ventilation networks increasingly serious. The scientific distribution of the airflow volume between operation areas has become an important problem in the optimization of mine ventilation systems. This study takes the ventilation system of the Xinli Submine of Sanshandao Gold Mine as an example to analyze the airflow volume regulation demand of the deep-level section stope to further improve the coordination of the airflow volume distribution in the underground mine. The drawing and equivalent simplification of the ventilation network diagram are completed according to the engineering parameters of the target level roadway, and the sensitivity matrix is calculated using a formula. The optimization of the adjustment branch and the formulation of the adjustment scheme are carried out based on the sensitivity matrix. By realizing the adjustment objective of the branch airflow volume via comparing the airflow volume of the ventilation network before and after adjustment, the adjustment scheme can make the airflow volume distribution in the level more balanced. The results of our study show that branch sensitivity theory is theoretically feasible for analyzing and solving the problem of the mine ventilation network, which has certain practical significance for the adjustment of airflow volume in mines. [ABSTRACT FROM AUTHOR]

• Sensitivity matrix of node displacements to element elongations is derived. • Structural displacements are located in the column space of sensitivity matrix. • Its least squares solution can be calculated with any basis for the column space. • A basis is constructed for the column space of sensitivity matrix. • Select active elements by converting passive elements to active elements one by one. The selection of active elements for morphing tensegrities moving toward the target configuration under element length actuations is discussed in this paper considering the structural elastic deformation. The effectiveness of active elements is substantially determined by the sensitivity matrix of the node displacements to the element elongations. It is pointed out that the displacement of the tensegrity induced by the length actuations of active elements must be located in the column space of the sensitivity matrix, and the expected deformation generally cannot be achieved accurately. The actual displacement of the tensegrity closest to the expected motion direction can be calculated using any basis for the column space of the sensitivity matrix. A novel method is therefore proposed to select active elements based on constructing the basis by converting the passive elements to the active elements one by one according to a proposed criterion. Two illustrative examples, an icosahedron tensegrity and an eight-module tensegrity column, are employed to verify the computational efficiency and accuracy of the proposed method in comparison to those of the genetic algorithm. [ABSTRACT FROM AUTHOR]

A physical model of the simplest three-dimensional tensegrity unit was built at human scale out of aluminum. Self-stress implementation and static loading tests were performed on this model. At each step, accurate measurements were obtained for all nodal positions and element forces. For the prestressing phase, elongations were imposed, via mechanical devices, in different combinations of elements, called prestress scenarios. Experimental results are compared to the theoretical self-stress state obtained by singular value decomposition of the equilibrium matrix and to numerical simulations using the dynamic relaxation method. It is shown that internal forces follow the same linear trend for all prestress scenarios even if the geometry is significantly impacted. Compressive tests were conducted by hanging masses from the top nodes. It is shown that there exists a unique load-displacement relation that follows the infinitesimal mechanism direction for a finite distance, which depends on the self-stress level. The paper provides a detailed overview of the simplex's structural behavior using both experimental and numerical results while discussing the limitations of the analysis methods explored. Tensegrity structures are composed of compressive elements floating inside a network of prestressed cables. Their unique aesthetics and mechanical properties have always amazed architects, scientists, and engineers. However, the number of tensegrity structures built for civil purposes remains limited. Reasons behind this include a nonintuitive structural behavior with occurrences of insufficient stiffness and lack of robustness as well as a complex construction process that requires introduction of prestressing forces. Consequently, tensegrity structures are often distrusted in favor of other structural systems. Many studies have focused on finding the conditions required for the existence of self-equilibrated prestressing forces that provide stability and stiffness in tensegrity structures. However, few studies have focused on how these prestressing forces can be implemented in a structure, and the discrepancy between theoretical and numerical approaches. For these reasons, a full-scale physical model of a tensegrity module was built and tested with extreme care on the design and experimental testing. This paper presents a comparison of experimental results using two established analysis methods discussing the differences between experimental measurements and numerical models. [ABSTRACT FROM AUTHOR]

This study examined the benefits and limitations of formulating linear programming models for water distribution network leak detection and localization considering sequences of demands. First, the consistency of sensitivity matrixes for different demand magnitudes and spatially varying nodal demands was investigated to determine if different sensitivity matrixes are needed for each time step and to determine the demands to use for computing the gradient matrixes. Then several unconstrained and constrained models were developed and their detection and localization performance was evaluated for a network in Austin, Texas. To constrain the failure location in time and space, binary (zero–one) integer linear programming (BILP) was used. A set of threshold-based detection rules was applied to test for the anomalies in the time series, and they were compared for a range of realistic leak sizes. Based on the numerical results, the best optimization model was identified considering multiple detection metrics (detection effectiveness, efficiency, and localization). The best BILP model that constrains leak locations spatially and temporally outperformed the unconstrained model in detecting and locating relatively small leaks. [ABSTRACT FROM AUTHOR]

Mesh antennas in orbit are periodically affected by solar radiation, earth reflection and space low temperature environment, and the temperature fluctuates in a wide range. Mesh antenna produce large thermal deformation or even obvious thermal disturbance under extreme temperature condition, which seriously deteriorates the surface accuracy and the tension distribution. To improve the shape stability of reflector surface and the rationality of tension distribution, a thermal design optimization method for mesh antenna considering the interaction between cable net and flexible truss is proposed. The equilibrium equation of mesh antenna system under space thermal loads is established based on finite element theory and force density equation. Due to the complexity of directly analyzing the influence of thermal loads on the entire mesh antenna, a research strategy of applying thermal loads step by step from flexible truss to cable network is adopted, and the force density increment equation of cable net under space thermal loads is derived. Then, the force density vector of the cable net is selected as the design variable, and the sum of squares of the thermal deformation of the reflector nodes is taken as the objective function, and the stability optimization model of the reflector in the whole temperature interval is established. Finally, a typical AstroMesh antenna under uniform temperature working conditions is used to illustrate the effectiveness and feasibility of the proposed method. Compared with the traditional optimization method, which can only ensure the better performance of a certain temperature point, the proposed method has better surface accuracy and thermal stability in the whole temperature interval. [ABSTRACT FROM AUTHOR]

In order to process the workpiece with internal gearing power honing technology，the honing wheel is usually dressed with the customized diamond dressing wheel corresponding to the workpiece. A method of internal gearing power honing modification based on flexible dressing of honing wheel is proposed to increase the commonality of diamond dressing wheel，reduce the cost of internal gearing power honing technology. Firstly，the tooth surface mathematical model of dressing and honing is established according to the motion relationship of each axis of gear honing machine. Then，the multi axis linkage of honing wheel dressing is expressed in polynomial form，the influence of each axis movement on the final workpiece tooth surface is expressed as sensitivity matrix，and the polynomial coefficients of each axis are optimized with the target modification tooth surface. Finally，the final tooth surface of the workpiece is calculated according to the optimized motion parameters of honing，and the tooth contact is analyzed. The results show the standard diamond dressing wheel can be used for flexible dressing of honing wheel，and the effective modification workpiece can be machined finally.

Electrical Resistance Tomography (ERT) is a promising technique owing to its low cost, high speed, and visualization features. The sensitivity coefficient plays a significant role in ERT image reconstruction as a priori information. However, the existing methods for calculating sensitivity matrix suffer from poor interpretability and operability. The result leads to an obstacle to improving the quality of the reconstructed images. Therefore, we propose a new sensitivity calculation method that has the advantages of clear physical significance, high robustness, and strong interpretability. We compared the existing and new sensitivity matrices with some metrics, such as correlation coefficient and relative error, and tested the new method’s performance by numerical simulations and experiments. The results show that the new sensitivity matrix is feasible and has better performance in ERT imaging reconstruction, especially in the presence of noise.

Nowadays, electronic devices are taking over the market and touch panel is a necessary part, among which capacitive touch panel has greater development potential and development space because of its high transparency, multitouch support and low cost. Electrical impedance tomography (EIT) is a technology with the goal of reconstructing tissue image with impedance distribution, which can realize the goal of accurate measurement and maintaining the original characteristics of the medium to the greatest extent at the same time. In this paper, we use EIT‐based approach to achieve a large area touch perception imaging system with high light transmittance, which is to obtain the distribution of the permittivity of the touch penal by just detecting the impedance of the electrode scattered around the panel. We use Sensitivity theory to solve the mapping problem between the permittivity distribution and the signal collected by the electrode in the EIT problem. Besides, we innovatively combine LBP with Landweber algorithm to achieve high precision and fast imaging of touch area, which greatly reduces the discomfort caused by inverse problem in EIT method. [ABSTRACT FROM AUTHOR]

In this paper, an image reconstruction method based on wavelet fusion in electrical capacitance tomography with a rotatable electrode sensor is proposed. This method can weaken the effect of the relative position distribution between the electrodes and the phantom object, thus improving the quality of the reconstructed image. To investigate the reliability of the proposed image reconstruction method, a new mechanical design of a rotatable 12-electrode sensor is introduced. The rotation of the 12-electrode sensor is accomplished by stepping motor and gear sets, which can easily change the measurement position of the electrodes. Five independent datasets of 66 capacitance measurements can be obtained by rotating the electrode sensor 4 times with an angle of 6°from the initial position. Then solving the inverse problem for each of the datasets, 5 reconstructed images are obtained. Finally, the wavelet fusion algorithm is used to fuse the reconstructed images. To verify the validity of the method, this paper evaluates the error case of rotational accuracy, the error case of measurement data and the case of real experiment, respectively. The experimental results indicate that the method can reduce the artifacts in the reconstructed images and improve the quality of the reconstructed images. Meanwhile, this processing method can enhance the shape and edge contour of the measured phantom. • Novel Method: In this paper, an image reconstruction method based on wavelet fusion in electrical capacitance tomography with a rotatable electrode sensor is proposed. By rotating the 12-electrode sensor 4 times at a fixed angle of 6 ∘ , 5 independent sets of measurement data can be obtained. Then solving the inverse problem for each of the datasets, 5 reconstructed images are obtained. Finally, the wavelet fusion method is used to fuse the reconstructed images. • Impactful Results: The experimental results show that the proposed method weakens the artifacts in the reconstructed image and enhances the main pixel point distribution region of the phantom objects. • Comparative Advantage: Compared to previous studies of rotating electrode sensors, the purpose of rotating the electrodes in our method is not to increase the number of measurements, but to perform independent image reconstruction of the 66 capacitance data obtained from each rotation of the 12-electrode sensor. The proposed method has the significant advantage of effectively reducing the artifacts in the reconstructed image, realizing clear target separation, and obtaining a better quality contour image. • Practical Implications: In the mechanical motion of the electrode sensor, the fast reading ability of the system is reduced due to the rotation of the sensor and the addition of fusion algorithm. However, this method can improve the quality of the reconstructed image well, and has great practical significance in the detection application with low real-time requirement. [ABSTRACT FROM AUTHOR]

The recorded responses at predefined sensor placements are used as input to solve an inverse structural damage detection problem. The error rate that noise causes from the recorded responses of the sensors is a significant issue in damage detection methods. Therefore, an optimal number and location of sensors is a goal to achieve the lowest error rate in structural damage detection. To overcome this problem, an algorithm (GVPSS) based on a Geometrical Viewpoint (GV) of optimal sensor placement and Parameter Subset Selection (PSS) method is proposed. The goal of the GVPSS algorithm is to minimize the effect of noise on damage detection problem. Therefore, the fitness function based on error in damage detection is minimized by GVPSS. In this method, the degrees of freedom are arranged to place sensors using a fitness function based on GV theory. Then, the optimal number and location of sensors are found on these arranged the degrees of freedom using the objective function. The efficiency of the proposed method is studied in a 52-bar dome structure under static and dynamic loadings. In the examples, damages are detected in two states: 1) using responses recorded at all DOFs, 2) using responses recorded at the optimal number and location of sensors obtained by GVPSS. The results showed that the damage detection error in state 2 is approximately equal to the error in state 1. Therefore, the GVPSS have the high performance to find the optimal number and location of sensors for structural damage detection. [ABSTRACT FROM AUTHOR]

At the current stage, there is an urgent need for new techniques to dynamically calibrate advanced wide-range (up to 104 N~105 N) triaxial force transducers. Based on this background, this paper proposes a novel impact calibration method, specifically for the triaxial force transducer, with a wide range and high-frequency response. In this method, the Hopkinson bar, which is typically used to test the dynamic mechanical properties of materials, was used as a generator to generate reference input force for the transducer. In addition, unlike conventional methods, the transverse sensitivities of the transducer were given necessary importance in the proposed method. The calibration result of the triaxial force transducer was expressed in a sensitivity matrix, containing three main sensitivity coefficients and six transverse sensitivity coefficients. The least squares method (LSM) was used to fit the sensitivity matrix linearly. Calibration experiments were performed on a typical triaxial force transducer. Several key issues, involving the validity and the test range, of the method were further investigated numerically. The feasibility and validity of the method were eventually confirmed. The test range of the method can be up to 106 N. [ABSTRACT FROM AUTHOR]

In this paper, a novel platform for simultaneous measurement of relative humidity (RH) and temperature using dual Fabry–Perot interferometers (FPIs) based on C-shaped fiber was demonstrated. The sensor was composed by splicing two sections of C-shaped fiber between single mode fiber (SMF). Polydimethylsiloxane (PDMS) and polyvinyl alcohol (PVA) are filled in the two sections of C-shaped fibers to increase sensitivity to temperature and RH. This is the first demonstration that solid polymer materials can be added to the C-shaped fiber interferometers for sensing. In our experiment, RH sensitivities of -0.128 nm/%RH and 0.038 nm/%RH in the range of 20%RH to 45%RH, and temperature sensitivities of 0.022 nm/°C and -0.722 nm/°C in the temperature range of 15 °C to 45°C, were acquired for dual FPIs, respectively. We verified that it is possible to use the sensitivity matrix method to measure two parameters simultaneously. In addition, it has the benefits of simple structure, excellent stability and high sensitivity, and has a broad application prospect in agriculture, food processing and environmental measurement. [ABSTRACT FROM AUTHOR]

Sensitivities are shown to play a key role in a highly efficient algorithm, presented in this paper, to establish three fundamental structural system properties: local structural identifiability, local observability, and local strong accessibility. Sensitivities have the advantageous property to be governed by linear dynamics, also if the system itself is nonlinear. By integrating their linear dynamics over a short time period, and by sampling the result, a sensitivity matrix is obtained. If this sensitivity matrix satisfies a rank condition, then the local structural system property under investigation holds. This rank condition will be referred to in this paper as the sensitivity rank condition (SERC). Applying a singular value decomposition (SVD) to the sensitivity matrix not only determines its rank but also pinpoints exactly the system components causing a possible failure to satisfy the local structural system property. The algorithm is highly efficient because integration of linear systems over short time-periods and computation of an SVD are computationally cheap. Therefore, it allows for the handling of large-scale systems in the order of seconds, as opposed to conventional algorithms that mostly rely on Lie series expansions and a corresponding Lie algebraic rank condition (LARC). The SERC and LARC algorithms are mathematically and computationally compared through a series of examples. [ABSTRACT FROM AUTHOR]

As modern power systems become large and complicated, an automated voltage and reactive power control system is required in most developed countries due to the remarkable recent progress in computer networks and information technology. To date, voltage control has depended on human operators in the Korean power system. Accordingly, this paper proposes a universal intelligent voltage control system for bulk power systems based on sensitivity analysis and a main expert system. A detailed state space modeling technique is discussed, and an effective performance index is proposed to accelerate the searching performance of the expert system. As the searching strategy is an important factor for the speed of the expert system, the least-first search algorithm is applied using this performance index. The proposed system has been applied to the Korean power system, showing promising results. [ABSTRACT FROM AUTHOR]

Carbon fiber reinforced polymer (CFRP) is widely utilized due to their superior properties. The structural health monitoring (SHM) for composite materials is crucial to prevent catastrophic failures. Electrical impedance tomography (EIT), which allows for the visualization of the conductivity distribution through the measurement of electrical parameters on the boundary, presents a potential solution for SHM. Existing studies applying EIT to CFRP concentrate on traditional linearization methods that rely on sensitivity matrix, which ignore challenges posed by non-uniform sensitivity. This paper introduces an EIT image reconstruction method that is independent of the sensitivity matrix, offering a novel way for rapid damage detection and real-time SHM. Furthermore, the domain shape transformation is achieved by conformal mapping. Simulations and experiments indicate that the sensitivity-matrix-independent EIT can avoid issues such as blurring in the central region and artifacts near the boundary caused by non-uniform distribution of the sensitivity in the CFRP damage detection. [Display omitted] • The realization of an image reconstruction on CFRP not depending on the sensitivity matrix of EIT. • The implementation of the conformal mapping from a domain with complex boundary to a disk. • The comparative analysis of the proposed method (SMI method) and traditional methods under different forward models. • The SMI method can avoid issues such as blurring and artifacts in the traditional methods. • The use of the SMI method can effectively simplify the EIT-based damage detection process. [ABSTRACT FROM AUTHOR]

Electrical capacitance tomography is a widely used sensor modality for flow imaging in many industrial settings. Adaptive electrical capacitance volume tomography (AECVT) extends the capabilities of traditional ECT by enabling direct volumetric imaging and an improved resolution. Construction of the sensitivity matrix is a necessary step to obtain flow images. This step requires the computation of the electric field inside the sensing domain, which is done via a typical field solver, such as the finite-element method. In this work, we present an efficient and flexible method to construct the sensitivity matrix for AECVT based on individual electrode segment excitations and their judicious combination to form desired matrix elements. We illustrate how the proposed method yields the same sensitivity matrix as the traditional method but at a much lower computational cost. Once all segment contributions are obtained, we also indicate how the proposed method, unlike the traditional approach, can generate the sensitivity matrix on demand for an arbitrary combination of synthetic electrodes and obviating the need for any additional field computations. Finally, we present image reconstruction results for two different experimental scenarios where the mutual capacitance data and the corresponding sensitivity vectors are obtained through the proposed measurement combination scheme. [ABSTRACT FROM AUTHOR]