Surface acoustic wave (SAW) sensors enable wireless and passive measurement in harsh environments and are commonly deployed in a spatial distribution to improve performance. However, the current sequential interrogation used in distributed sensing introduces errors due to asynchronous multisignal acquisition and processing. Synchronous excitation and echo signal frequency acquisition on multiple SAW resonators (SAWRs) (synchronous sensing) can avoid this error and improve sensing efficiency. Nevertheless, the practical implementation of SAW synchronous sensing remains unavailable currently. Aiming at this challenge, this article proposes a systematic synchronous frequency estimation technology and achieves high-precision synchronous SAW sensing. First, through derivation of the Cram & eacute;r-Rao lower bound (CRLB) for sensor signals, we establish range guidelines for key parameters about the synchronous sensing scheme (working frequency interval of SAWRs, signal length). This step ensures optimal resource allocation (excitation bandwidth, sampling length) to enhance frequency estimation accuracy and measurement precision. Subsequently, a high-performance multifrequency estimation algorithm is proposed. It combines the proposed adaptive step-size subspace iterative reconstruction algorithm with the improved weighted root-MUSIC algorithm. Monte Carlo experiments demonstrate our algorithm achieves the CRLB-approaching estimation (within 2 dB of mean square error, mse), ensuring the feasibility of the CRLB-derived guidelines. Finally, high-precision synchronous differential SAW pressure sensing is achieved, and our frequency estimation algorithm outperforms conventional algorithms facing the real sensor signals (with estimation variance of 0.18 kHz(2)). Our work establishes a foundation for the practical application of SAW synchronous sensing technology and will advance the development of SAW distributed sensing arrays.

The eddy current displacement sensors (ECDSs) are widely used in precision industrial applications, but they are susceptible to temperature drift under varying temperature conditions, which limits their measurement accuracy. This study proposes a novel temperature compensation method aimed at improving the performance of (ECDS) across a broad temperature range. This method utilizes phase characteristics and dual ac bridge technology to effectively separate the temperature drift of the probe coil from the target displacement changes. In this way, the temperature stability of large-range ECDS is significantly enhanced, and drift caused by temperature changes in the probe coil is further eliminated through temperature calibration. Laboratory tests have shown that this method effectively reduces temperature-related displacement drift from 2093 to 132 ppm/degrees C within a temperature range of 20 degrees C-100 degrees C. The results indicate that the proposed method significantly improves the measurement accuracy and reliability of ECDS in large temperature difference environments, providing important technical support for the precision measurement field.

Torque measurement presents challenges particularly in rotating structures, where traditional measurement methods are often limited. Surface Acoustic Wave (SAW) sensors, with their inherent wireless and passive characteristics, possess unique advantages in mechanical measurements of rotating structures. Currently, most of the existing resonant SAW mechanical sensors suffer from issues of short reading distances or poor signal quality, primarily due to the difficulty in achieving high Q factor of SAW resonators. Additionally, the problem of high temperature coefficient generally exists in the field of SAW sensors, which will seriously interfere with the measurement accuracy of the sensors. In this article, a SAW torque sensor with excellent wireless performance was proposed based on the X-112 degrees Y LiTaO3 substrate due to its large electromechanical coupling coefficient ( K-2 ) and favorable temperature characteristics. We investigated and simulated the characteristics of the sensing element including strain sensitivity, temperature coefficient, Q factor and electromechanical coupling coefficient, and designed SAW resonators on X-112 degrees Y LiTaO3 substrates. The experimental results show that the proposed SAW sensor has higher signal-to-noise ratio (SNR) echo signal quality at the same wireless measurement distance compared with the case traditional high Q factor SAW sensor based on quartz substrate. Moreover, from temperature tests, the proposed SAW sensor has a linear temperature effect, which is beneficial to the compensation of temperature drift. Based on the manufactured SAW sensors, a SAW torque measurement system with wonderful linearity, repeatability, and hysteresis was developed. Our work provides a valuable and promising solution for wireless and passive measurement of mechanical quantities.

Due to the lack of a precise mathematical model for the parasitic capacitance of air-core coils, it has been challenging to develop an accurate overall model for eddy current displacement sensors, thereby hindering comprehensive optimization of sensor dimensions, sensitivity, and anti-interference capabilities. To address this problem, this paper first derives and establishes an accurate mathematical model of the parasitic capacitance in air-core coils, and then integrates it with coil inductance and target coupling characteristics to form a complete modeling framework for eddy current sensors. Experimental results show that the proposed model achieves prediction errors of only 0.90 % and 3.50 % for inductance and capacitance, respectively, closely matching measured values. Guided by this model, a multi-objective optimization algorithm is employed to effectively balance structural dimensions, sensitivity, and anti-interference performance. The optimized sensor achieves a detection signal linearity of 0.05 %, demonstrating significantly enhanced performance. This research provides a solid theoretical basis and methodological support for improving eddy current sensor performance in complex application environments.

This paper proposed a general real-time creep compensation method aiming at creep caused by loading behavior (sudden changes in sensing quantities) for mechanical sensors. Since creep is intricately influenced by various loading factors (occurrence instant, loading amplitude, loading duration, etc.), the existing compensation methods demonstrated inadequate performance due to the widespread use of linear time-invariant (LTI) class models. In this paper, we established a nonlinear memory creep model using historical data as input and proposed a deep neural network (DNN) creep compensation architecture consisting of two independently trained blocks: the data behavior recognition block and the creep compensation & calibration block. The recognition block classifies and identifies different behavior patterns in the input data. Using the output class information, the creep prediction mechanisms of different behavior patterns were separately learned through input dimension expansion, which greatly improved the performance of creep prediction. The creep compensation & calibration block extracts information from the historical input data for creep prediction and the real mechanical loading serves as output labels by adding custom-calculated compensation layer and calibration layer at the end of the block. In the creep compensation experiment of the case sensor, the proposed method has achieved nearly an order of magnitude improvement compared with the traditional methods in the sensor-related performance indicators. Our work offers a promising and comprehensive solution for sensor creep compensation.

Eddy current displacement sensors, recognized for their capabilities of excellent anti-interference capabilities and high-frequency response, are used in the industrial and aerospace sectors. Inherently nonlinear in their large-range displacement measurements, these sensors traditionally require a series of correction curves for accurate measurement. This approach largely stems from the lack of a mathematical model capable of accurately describing the nonlinear behavior. This article introduces a method that involves precisely establishing a mathematical model of the mutual inductance coefficients between the probe of the eddy current displacement sensor and the detection target, thereby effectively calculating the gap between them. The model is applicable to probe coils of various structures and detection targets made of different materials, greatly simplifying the nonlinear correction process. Experimental validation demonstrates the effectiveness of this method for probe coils of different structures or detection targets made of varying materials, with a maximum nonlinearity of less than 1%, confirming its efficiency and accuracy in practical applications.

Focusing on the problem that traditional LVDT measurement circuit requires many high-cost modules and that the performance is relatively low, a LVDT measurement system based on oscillation circuit is proposed and designed. LVDT coil is connected to a high-performance LC oscillator as a resonant inductance. Displacement is obtained by using the frequency shift of the resonance signal. System linearity is improved with the help of the resonator mathematical model and theoretical analysis. The experimental results of the prototype show that under the full displacement state, the frequency range span can reach 73～122 kHz. The sampling rate and resolution can be adjusted according to the actual needs. A submicronic measuring resolution of 16.7 bits is achieved when the sampling rate is 200 Sps and the nonlinearity error is 0.14% FS. The measurement system outperforms the traditional bridge circuit in most aspects, and does not need low distortion excitation and high-precision demodulation module. Besides, it has significant advantages in circuit cost and size.

The thermal cycling system is the key component of the real-time fluorescent polymerase chain reaction (PCR) instrument, which determines the nucleic acid detection efficiency and result accuracy. Aiming at the problems that the thermal cycle of the traditional PCR detection system takes a long time and the temperature control is complicated, a real-time fluorescent PCR thermal cycle system with partition temperature control is designed, including the hardware circuit and mechanical structure of the thermal cycle system. The rapid thermal cycling is achieved by switching the test solution between different constant temperature zones, and the temperature is controlled using an incremental proportional integral derivative (PID) algorithm, with a control precision of ±0.1 ℃. Using Fluent software to establish heat transfer model, the thermal delay phenomenon of the test solution was analyzed to predict the temperature variation pattern of the test solution. A prototype is built for testing and verification, and the heating and cooling rates of the test liquid are 3.8 ℃/s and 4.4 ℃/s. It is verified that the proposed PCR thermal cycling system can effectively improve the detection efficiency.

This paper proposes a novel mathematical model that has high accuracy based on a multi-objective optimization algorithm for the inductive displacement sensors, which is popular in industrial production due to their simple design and reliable performance. The proposed model uses composite functions to establish the structural parameters of the coil winding. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve a series of non-dominated problems related to the coil structure parameters with the goal of achieving superior sensor performance. Density clustering sorting is used to select the desired non-dominated solutions. The designed sensor has a nonlinearity of 0.16%, and numerical simulations and physical experiments confirm the effectiveness of the new design method.

SAW torque sensor is an important method in torque detection, and sensing element is an important part of sensor. Therefore, the design and analysis of the torque sensing element in SAW technology hold significant importance. In this study, The SAW torque sensing element was simulated and analyzed by finite element simulation software, the SAW torque sensing element was fabricated through the use of MEMS processes. Finally, the SAW torque testing platform was built, and the SAW torque sensing element was tested and analyzed. The results of three loading tests show that the sensitivity of SAW torque sensing element is 4.0045kHz/N•m, 4.0044kHz/N•m and 4.0011kHz/N•m. The results show that the designed SAW torque sensing element has good sensitivity and provide a good guidance for the application of SAW torque sensor.

This article presents a passive wireless weighing sensor based on surface acoustic wave (SAW) technology. It consists of a one-port SAW sensing resonator and force-sensitive structure. Stable temperature (ST)-cut quartz was employed as the piezoelectric substrate of the SAW sensing resonator, and the sensing characteristics of the SAW sensitive resonator were simulated by the finite element method (FEM). The double-connected holes structure was proposed to form a difference sensing unit, which improves the sensitivity of the sensor and can counteract the effects of ambient temperature. Based on the designed force-sensitive structure and SAW sensing resonator, a wireless passive SAW weighing test platform was built and tested. The experimental result shows that the sensor is consistent with the design expectation. The sensitivity of the weighing sensor is 75.35 kHz/kg, and the nonlinear error is 0.17%. Under consecutive loading and unloading of 0–5 kg, the hysteresis is 1.1% and the maximum standard deviation of repeatability under the same load is 2.277 kHz (about 0.6% of the full-scale frequency shift). The difference structure effectively improves the sensitivity and has a good ambient temperature inhibition effect. Under a temperature of 30 °C–60 °C, the frequency shift is within 3 kHz, which is 0.8% of the full scale.

Shipborne dynamic weighing is fundamental in developing marine fishery resources and oceanographic research. It enables the weighing and sorting of seafood, quantitative baiting, and measurement of research sample weights in marine environments. Therefore, developing shipborne dynamic weighing systems is crucial for the integrated exploitation of marine fishery resources. However, research on shipborne dynamic weighing is limited. To address this issue, the study initially analyzed the impact of ship's attitude information on weighing results. Subsequently, a mathematical model for shipborne dynamic weighing, incorporating compensation factors, was constructed. The compensation factors were determined using the Recursive Least Squares (RLS) method. And then real-time weight estimation was updated using Kalman filtering, effectively mitigating the influence of ship oscillations and swaying on weight measurements. Furthermore, a shipborne dynamic weighing system with a 24-bit analog-to-digital converter (ADC) and STM32F4 processor was developed. The system performance was evaluated by simulating the sail of a ship under different sea conditions on a swing platform. The results demonstrate that the average absolute percentage error of the test meets the requirement of less than 1%, and the standard deviation of the error is less than 1% F. S., which essentially meets the weight measurement requirements of marine dynamic weighing and sorting.

The finite element method (FEM) has been applied to extract the coupling-of-modes (COM) parameters of surface acoustic wave (SAW) devices for a long time. It always involves calculating the dispersive curves or harmonic admittance, which makes the extraction process and results sophisticated, time-consuming and inaccurate. Therefore, a simple method is proposed to extract all COM parameters of the SAW devices rapidly and accurately in this paper. It is based on the FEM and combines the stationary analysis with modal analysis. We have described in detail the basic principles and procedures of the proposed method, and made a comprehensive comparison between the proposed method and the other two existing methods. We have also examined the proposed method by extracting COM parameters of some common SAW substrate, and compared our extracted results with those reported in the other literatures. Results show that our proposed method holds higher accuracy and more efficiency (~s order) than the others (~h order). Moreover, our extracted COM parameters are in an excellent agreement with those reported in the other literatures.

针对磁异常探测中载体干扰磁场会极大的影响测量结果的问题,提出一种基于RLS算法的磁异常探测载体干扰磁场补偿方法.首先,对磁异常探测中的干扰进行分类,建立测量模型;然后,将模型转换为标准多元线性方程,通过正交约束和线性约束降低共线性,经RLS算法求解模型参数,并进行模型仿真验证算法正确性;最后,进行有无异常载体有限元仿真,通过RLS算法解算无异常时仿真数据获取补偿参数,并用补偿参数对含异常仿真数据进行补偿.结果表明:经补偿误差显著降低,无磁异常实测实验的补后改善比为10.3,该方法可用于磁异常探测中的载体干扰磁场补偿,有效提升了磁异常探测的抗干扰能力,对掩埋物检测、矿产勘探、反潜等工作都具有重要意义.

为实现地磁背景下微弱磁异常目标的远距离探测,解决地磁背景信号远大于目标磁异常信号,导致测试系统分辨率和探测能力受限的问题,文中设计了由测量和补偿2个三轴磁通门磁强计构成的实时动态地磁补偿系统.推导了三轴磁通门磁强计非正交、灵敏度和零点误差对测量结果的影响方式,提出了通过电路参数的合理匹配和优化设计实现转向差校正和地磁补偿的硬件技术方案.实验证明该方案有良好的转向差校正和地磁补偿效果,可以为磁异常信号提供更大的增益范围,能够实现对微小磁异常信号的实时提取与动态检测,具有较好的工程应用价值.

针对采用ARM控制器的测漏仪,设计了一套可针对不同被测对象在线辨识系统参数,进而基于P ID算法控制仪器比例阀的快速充气控制方法.通过充气系统阶跃响应进行系统辨识,获得系统数学模型.采用基于算法自动控制的临界比例度法进行P ID参数整定,并提出了充气系统的P ID参数优化方法.仿真和实验结果表明,系统辨识和参数自整定方法对超调系统和非超调系统均适用,辨识精度较高,控制效果良好,该快速充气方法可有效减少测漏仪的充气时间,提高检测效率.

超声红外热成像以超声作为激励源,能够用于检测多种工件,但是由于热传导效应及空气的散射,检测结果中缺陷边缘较为模糊,成像对比度不高,并且会有温度分布不均引起的"散斑噪声".为解决以上问题,提出了一种对超声红外热成像结果进行缺陷检测和定位的方法,使用限制对比度自适应直方图均衡(contrast limited adaptive histo-gram equalization,简称CLAHE)方法对图像进行对比度增强,用巴特沃斯滤波器进行降噪,根据图像的局部方差特征判断是否有缺陷,并通过形态学处理对缺陷中心进行定位.实验表明,根据局部方差可以对图像进行有效判断,经过形态学处理之后能够准确定位.该研究为通过超声红外热成像实现缺陷检测及定位提供了一种便捷有效的方法.

介绍变电站中纳米技术的应用研究现状和相关实例,分析并展望纳米技术在变电行业的应用前景.

Magnetic nanoparticles (MNPs) are commonly used in biomedical detection due to their capability to bind with some specific antibodies. Quantification of biological entities could be realized by measuring the magnetic response of MNPs after the binding process. This paper presents a contactless scanning prototype based on tunneling magnetoresistance (TMR) sensors for quantification of MNPs present in lateral flow strips (LFSs). The sensing unit of the prototype composes of two active TMR elements, which are parallel and closely arranged to form a differential sensing configuration in a perpendicular magnetic field. Geometrical parameters of the configuration are optimized according to theoretical analysis of the stray magnetic field produced by the test line (T-line) while strips being scanned. A brief description of our prototype and the sample preparation is presented. Experimental results show that the prototype exhibits the performance of high sensitivity and strong anti-interference ability. Meanwhile, the detection speed has been improved compared with existing similar techniques. The proposed prototype demonstrates a good sensitivity for detecting samples containing human chorionic gonadotropin (hCG) at a concentration of 25 mIU/mL. The T-line produced by the sample with low concentration is almost beyond the visual limit and produces a maximum stray magnetic field some 0.247 mOe at the sensor in the x direction.

Pulsed eddy current ( PEC) testing is a new type of non-destructive testing techniques e-merging in recent years. For ferromagnetic materials pulsed eddy current testing, a combined magnetiza-tion method was presented. A DC magnetic field is added to the specimen to change the magnetic permea-bility of the material inspected, to achieve higher detection sensitivity when loading pulsed excitation. Theoretical analysis and experimental results show the effect of the combined magnetization on detection sensitivity.