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Flexible eddy current array (FECA) sensor is flexible and light in weight, which has broad application prospects in structural health monitoring. But, the sensor’s sensing channel number is more, increasing the added mass of sensor networks. This paper aims to reduce the sensing channel number by changing the sensing coil layout.

In this paper, FECA sensors with series sensing coil (SSC) layout and interactive sensing coil (ISC) layout are proposed, which reduce the number of sensor’s channels by half. Then, the variation of the output signal of the sensor when the crack expands along both sides of the hole is analyzed by simulation model. Finally, the fatigue crack monitoring experiment is carried out.

For the SSC layout, the simulation results show that the amplitude of each SSC group of the sensor increases when the crack propagates to the left or right. For the ISC layout, when the crack propagates on the right side of bolt hole, the induced voltage of each ISC group decreases. When the crack propagates on the left side of bolt hole, the induced voltage of each ISC group increases. The experiment results are consistent with simulation results, which verifies the correctness of simulation model. Compared with SSC layout, the ISC layout can judge the crack propagation direction. And the crack monitoring accuracy is 1 mm.

The research results provide a certain reference for reducing the number of sensor’s sensing channels. Results of the simulation and experiment show that the ISC layout can judge the crack propagation direction, and the crack monitoring accuracy is 1 mm.

This paper aims to propose an effective dynamic calibration and compensation method to solve the problem that the statically calibrated force sensor would produce large dynamic errors when measuring dynamic signals.

The dynamic characteristics of the force sensor are analyzed by modal analysis and negative step dynamic force calibration test, and the dynamic mathematical model of the force sensor is identified based on a generalized least squares method with a special whitening filter. Then, a compensation unit is constructed to compensate the dynamic characteristics of the force measurement system, and the compensation effect is verified based on the step and knock excitation signals.

The dynamic characteristics of the force sensor obtained by modal analysis and dynamic calibration test are consistent, and the time and frequency domain characteristics of the identified dynamic mathematical model agree well with the actual measurement results. After dynamic compensation, the dynamic characteristics of the force sensor in the frequency domain are obviously improved, and the effective operating frequency band is widened from 500 Hz to 1,560 Hz. In addition, in the time domain, the rise time of the step response signal is reduced from 0.29 ms to 0.17 ms, and the overshoot decreases from 26.6% to 9.8%.

An effective dynamic calibration and compensation method is proposed in this paper, which can be used to improve the dynamic performance of the strain-gauge-type force sensor and reduce the dynamic measurement error of the force measurement system.

This paper aims to present a simulation concept and an experimental verification of a novel sensor design for the shaft position measurement based on the eddy current principle and the phase-shift measurement. The simulation method for the sensor characteristic determination is presented. Possible application of a new sensor type is theoretically presented, verified in simulation and compared with experimental results.

Sensor is based on the injection-locking phenomenon between coupled oscillators. Only one sensor per axis is used for position measurement. A pair of the sensing and reference oscillators in the sensor is electrically coupled via the coupling resistor. A change in the inductance for the eddy current sensor is simulated in the finite element method (FEM) software Flux and behavior of the sensor circuit is simulated in the SPICE simulator software LTSpice program. Finally, the simulation results are compared with the measurements conducted on the laboratory test rig.

A novelty in this approach is the usage of only one sensor per axis compared to the well-known differential measurement of the position that uses the opposite pair of the sensing oscillators in the same axis. A methodology for the sensor characteristic determination is presented and experimentally verified.

A new variation of a coupled-oscillator eddy current sensor design is introduced. A simulation approach for the characteristic determination of the sensors based on the weakly coupled oscillators and the injection-locking mechanism is presented.

The purpose of this paper is to consider a capacitive pressure sensor fabricated using low‐temperature cofired ceramic (LTCC) materials and technology as a candidate for an energy‐autonomous sensor application. Designing the 3D capacitive sensor structure, with the cofired thick‐film electrodes inside the narrow air gap in the LTCC substrate, was a challenging task, particularly due to the presence of the parasitic elements influencing the sensor's characteristics.

In this work, different design variants for the thick‐film electrodes of the capacitive sensing structure were studied and compared. The test sensors were designed for the pressure range 0‐10 kPa and manufactured with readout electronics based on a capacitance‐to‐digital conversion.

The typical sensitivity obtained was 4 fF/kPa, and the temperature coefficient of the sensitivity was 0.03%/°C. The design variant with the guard‐ring electrode showed the best rms resolution of 50 Pa. One drawback of the application could be the sensitivity to atmospheric humidity and the influence of the different media.

This paper focuses on the design of a capacitive gas‐pressure sensor in a 3D LTCC structure. The present study provides a good basis for further optimisation of the design of the cofired electrodes in the capacitive sensing structure.

The purpose of this paper is to develop a digital hydrostatic pressure sensor with the required metrological and operational characteristics. The developed sensor is designed to control hydrostatic pressure in wells during various geophysical works and studies.

To obtain the required metrological and operational characteristics of the sensor, a method was developed and applied to reduce the measurement error based on the calibration algorithm and the sensor model.

By using the developed calibration algorithm and the mathematical model of the sensor, it was possible to compensate for the measurement errors of the hydrostatic pressure sensor.

In the course of this research, tests of the developed sensor were carried and the maximum/minimum of measurement result errors was determined.

Multi‐sensor data fusion (MSDF) is defined as the process of integrating information from multiple sources to produce the most specific and comprehensive unified data about an entity, activity or event. Multi‐sensor object recognition is one of the important technologies of MSDF. It has been widely applied in the fields of navigation, aviation, artificial intelligence, pattern recognition, fuzzy control, robot, and so on. Hence, aimed at the type recognition problem in which the characteristic values of object types and observations of sensors are in the form of triangular fuzzy numbers, the purpose of this paper is to propose a new fusion method from the viewpoint of decision‐making theory.

This work, first divides the comprehensive transaction process of sensor signal into two phases. Then, aimed at the type recognition problem, the paper gives the definition of similarity degree between two triangular fuzzy numbers. By solving the maximization optimization model, the vector of characteristic weights is objectively derived. A new fusion method is proposed according to the overall similarity degree.

The results of the experiments show that solving the maximization optimization model improves significantly the objectivity and accuracy of object recognition.

The paper studies the type recognition problem in which the characteristic values of object types and observations of sensors are in the form of triangular fuzzy numbers. By solving the maximization optimization model, the vector of characteristic weights is derived. A new fusion method is proposed. This method improves the objectivity and accuracy of object recognition.

Differential sensor for linear displacement has been optimized in terms of linearity and sensitivity. The optimization of the sensor is carried out with respect to its characteristic displacement‐output voltage.

Response surface methodology and design of experiments have been successfully applied for sensor optimization. First, a full factorial experiment – computation of the quasi‐static electromagnetic field of the sensor using the finite element method – has been performed. Secondary model has been created on the basis of finite element results. Then this model has been optimized with respect to two criteria – linearity and sensitivity.

The mutual influence of both criteria has been studied. In this way an optimal trade‐off between linearity and sensitivity of the sensor was achieved.

Relatively small numbers of optimization criteria have been varied. The results can be further improved by adding additional factors to the study.

The results obtained improve characteristics of this type of sensor and make it low cost alternative to the high‐end linear displacement sensors in low to moderate accuracy applications.

Intelligent and connected vehicle technology is in the ascendant. High-level autonomous driving places more stringent requirements on the accuracy and reliability of environmental perception. Existing research works on multitarget tracking based on multisensor fusion mostly focuses on the vehicle perspective, but limited by the principal defects of the vehicle sensor platform, it is difficult to comprehensively and accurately describe the surrounding environment information.

In this paper, a multitarget tracking method based on roadside multisensor fusion is proposed, including a multisensor fusion method based on measurement noise adaptive Kalman filtering, a global nearest neighbor data association method based on adaptive tracking gate, and a Track life cycle management method based on M/N logic rules.

Compared with fixed-size tracking gates, the adaptive tracking gates proposed in this paper can comprehensively improve the data association performance in the multitarget tracking process. Compared with single sensor measurement, the proposed method improves the position estimation accuracy by 13.5% and the velocity estimation accuracy by 22.2%. Compared with the control method, the proposed method improves the position estimation accuracy by 23.8% and the velocity estimation accuracy by 8.9%.

A multisensor fusion method with adaptive Kalman filtering of measurement noise is proposed to realize the adaptive adjustment of measurement noise. A global nearest neighbor data association method based on adaptive tracking gate is proposed to realize the adaptive adjustment of the tracking gate.

To establish an accurate and sensitive method to characterize the moisture content of a particular environment.

This paper proposes a relatively simple humidity sensor design consisting of electrodes on a suitable substrate coated with a polyimide material. The changes in relative humidity are denoted by a corresponding change in the polyimide material's electrical resistance profile. The design proposed in this work can be microfabricated and integrated with electronic circuitry. This sensor can be fabricated on alumina or silicon substrates. The electrode material can be made up of nickel, gold or aluminum and the thickness of the electrodes ranges typically between 0.2 and 0.3 μm. The sensor consists of an active sensing layer on top of a set of electrodes. The design of the electrodes can be configured for both resistive and capacitive sensing.

The polyimide material's ohmic resistance changes significantly with humidity variations. Changes in resistance as large as 4‐6 orders of magnitude are attainable over the entire operational humidity range.

As the sensitivity varies non‐linearly with the humidity, the measurement has to be carried out over a very wide range in order to calibrate the sensor. The sensitivity and output range of the sensor can be easily controlled by changing the electrode spacing or geometry.

The control of humidity is important in many applications ranging from bio‐medical to space exploration.

A simple, easy to fabricate and measure, and low cost resistive‐type humidity sensor was developed. The realized sensor is suitable for integrating with microfabrication. Hence, multiple sensors of varying sensitivities and output ranges could be integrated on the same chip. Over the last few years, newly emerging micro‐electro‐mechanical‐systems technology and micro‐fabrication techniques have gained popularity and importance in the miniaturization of a variety of sensors and actuators.

The flexibly thin film grid pressure sensor is mainly used to detect the interface pressure distribution between touching objects. Aim at larger measurement error, the strip double sensing layer pressure sensor are designed and fabricated and tested.

Defects and characteristic of the flexibly thin film grid pressure sensor based on piezoresistive effect are analyzed and pointed out in this paper. After comparison of four sensors, the strip double sensing layer pressure sensor was thought to be best.

Experiment shows that the strip double sensing layer pressure sensor could eliminate the measurement error basically and illustrates the validity of measuring the interface pressure distribution between area touching objects.

In this paper, only the strip double sensing layer pressure sensor was used to verify the validity of measuring the static interface pressure distribution between peach and platform. But there also exists some problems such as the adhering reliability of electrode and the unevenness of sensing layer. These problems could be overcome in the future research if the fabricating procedure and ingredient of material could be adjusted correctly.

The strip double sensing layer pressure sensor could be applied to detect the static interface pressure distribution such as peach pressure distribution. For dynamic measurement, this research needs to be done further.

Strip double sensing layer pressure sensor with simple “interlayer” structure and with low manufacture cost is presented to basically eliminate the measurement error of interface pressure distribution of original sensor.