Measurement Science and Technology最新文献_第5页

A Novel Capacitive Sensor Interface Based on a Simple Capacitance-to-Phase Converter 基于简单电容-相位转换器的新型电容式传感器接口

Measurement Science and Technology Pub Date : 2024-07-23 DOI: 10.1088/1361-6501/ad6681

Frank J Van Kann, Alexey V Veryaskin

{"title":"A Novel Capacitive Sensor Interface Based on a Simple Capacitance-to-Phase Converter","authors":"Frank J Van Kann, Alexey V Veryaskin","doi":"10.1088/1361-6501/ad6681","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6681","url":null,"abstract":"\u0000 A novel room temperature capacitive sensor interface circuit is proposed and successfully tested, which uses a modified All-Pass filter architecture combined with a simple series resonant tank circuit with a moderate Q-factor. It is fashioned from a discrete inductor with small dissipation resonating with a grounded capacitor acting as the sensing element to obtain a resolution of ∆C ~ 2 zF in a capacitance range of 10 – 30 pF. The circuit converts the change in capacitance to the change in the phase of a carrier signal in a frequency range with a central frequency set up by the tank circuit’s resonant frequency and is configured to act as a close approximation of the ideal All-Pass filter. This cancels out the effects of amplitude modulation when the carrier signal is imperfectly tuned to the resonance. The proposed capacitive sensor interface has been specifically developed for use as a front-end constituent in ultra-precision mechanical displacement measurement systems, such as accelerometers, seismometers, gravimeters and gravity gradiometers, where moving plate grounded air gap capacitors are frequently used. Some other applications of the proposed circuit are possible including the measurement of the electric field, where the sensing capacitor depends on the applied electric field, and cost effective capacitive gas sensors. In addition, the circuit can be easily adapted to function with very small capacitance values (1 - 2 pF) as is typical in MEMS-based transducers.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"117 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141811904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pipeline leak location method based on SSA-VMD with generalized quadratic cross-correlation 基于 SSA-VMD 和广义二次交叉相关的管道泄漏定位方法

Measurement Science and Technology Pub Date : 2024-07-22 DOI: 10.1088/1361-6501/ad6625

Lai hu Peng, Yongchao Hu, Jianyi Zhang, Jianwei Lin

{"title":"Pipeline leak location method based on SSA-VMD with generalized quadratic cross-correlation","authors":"Lai hu Peng, Yongchao Hu, Jianyi Zhang, Jianwei Lin","doi":"10.1088/1361-6501/ad6625","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6625","url":null,"abstract":"\u0000 Natural gas pipelines are an essential part of the economy. Natural gas pipelines may leak after aging, strong vibration signals may be generated in the pipeline when leakage occurs, and vibration signals may be noisy. Traditional variational mode decomposition (VMD) noise reduction methods need to set parameters in advance, and so may not achieve the best decomposition effect. To solve this problem, this paper proposes a method for pipeline leakage location based on the sparrow search algorithm (SSA) optimization of VMD combined with generalized quadratic cross-correlation. The method first calculates the original signal-to-noise ratio, and if the signal-to-noise ratio is low, wavelet threshold denoising is used to process the signal. Then, SSA optimization is used to refine the two key parameters of VMD (penalty parameter α and mode decomposition number K) based on sample entropy. Subsequently, the signal undergoes decomposition into K intrinsic mode function (IMF) components through VMD according to the obtained analysis parameter combination. Then, the IMF components are screened to obtain the reconstructed signal. Finally, the noise reduction signal is obtained. The signal delay after noise reduction is obtained through a generalized quadratic cross-correlation and the accurate leakage position is obtained using the delay. Experiments showed that the minimum relative error of this method could reach 0.6%, which was more accurate than the traditional VMD method, and effectively improved the accuracy of noisy signals in pipeline leakage locations.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"36 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141815137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ERT-Based fetus monitoring system using wearable conductive fabrics 使用可穿戴导电织物的基于 ERT 的胎儿监测系统

Measurement Science and Technology Pub Date : 2024-07-22 DOI: 10.1088/1361-6501/ad6622

A. K. Khambampati, Felipe Alberto Solano Sanchez, M. Jeon, Kyung Youn Kim

引用次数: 0

An adaptive continuous scanning laser Doppler vibrometry technique for measuring vibrational mode shapes of structures with holes 用于测量带孔结构振型的自适应连续扫描激光多普勒测振技术

Measurement Science and Technology Pub Date : 2024-07-22 DOI: 10.1088/1361-6501/ad6630

Lei Zhang, Chaoping Zang, Tong Jing

{"title":"An adaptive continuous scanning laser Doppler vibrometry technique for measuring vibrational mode shapes of structures with holes","authors":"Lei Zhang, Chaoping Zang, Tong Jing","doi":"10.1088/1361-6501/ad6630","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6630","url":null,"abstract":"\u0000 Continuous Scanning Laser Doppler Vibrometry (CSLDV) enables fast and full-field vibration measurement in an intact area of a structure. This paper further proposes a novel adaptive CSLDV method that can obtain the Operational Deflection Shapes (ODS) and mode shape of structures with holes. Firstly, an adaptive path planning method is applied to the surface of the tested structure, which can automatically adapt to the size and position of round and square holes, as well as the resolution requirements for the measurement. Secondly, based on the symmetry and other characteristics of the planned path, the time domain signal is processed by delay optimization and demodulation to obtain the ODS of each vibration mode. Finally, a modal test is conducted on a flat structure with a square and circle holes as an example. A validation experiment is also performed using SLDV. The results show that the mode shapes obtained from both methods are consistent and the Modal Assurance Criterion (MAC) between them are all above 0.96. The method can realize CSLDV of flat plate structures with arbitrary square and round holes, and has the advantages of high efficiency and dense measurement points, which enhances its engineering applicability.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"28 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141815622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Semi-supervised adaptive anti-noise meta-learning for few-shot industrial gearbox fault diagnosis 用于工业齿轮箱故障诊断的半监督式自适应抗噪元学习技术

Measurement Science and Technology Pub Date : 2024-07-22 DOI: 10.1088/1361-6501/ad662d

Junwei Hu, Chao Xie

{"title":"Semi-supervised adaptive anti-noise meta-learning for few-shot industrial gearbox fault diagnosis","authors":"Junwei Hu, Chao Xie","doi":"10.1088/1361-6501/ad662d","DOIUrl":"https://doi.org/10.1088/1361-6501/ad662d","url":null,"abstract":"\u0000 Real-time and accurate predictive maintenance of industrial equipment is fundamental for ensuring the safety and stability of advanced manufacturing processes. Current fault diagnosis methods based on data mining rely on a large number of labeled samples, and obtaining sufficient labeled data for diagnosing industrial equipment faults is challenging. Meta-learning can achieve the diagnosis of few-shot samples to a certain extent, but the effect is not ideal. Semi-supervision can effectively leverage a large number of unlabeled samples, which is of great practical significance for handling scenarios involving limited labeled samples. However, noise interference can occur when unlabeled samples appear that do not belong to known categories. Therefore, this study proposes adaptive semi-supervised meta-learning networks for noisy few-shot gearbox fault diagnosis. Firstly, a residual network with a Morlet Wavelet layer is used to extract signal features. Next, sample-level attention is defined to select unlabeled samples that are more similar to labeled sample prototypes, thereby reducing the influence of noisy samples. The adaptive metric is used to obtain the relational distance functions of labeled samples and unlabeled samples. Adaptive semi-supervised meta-learning networks uses unlabeled data to refine prototypes for better fault diagnosis. The effectiveness and anti-noise performance of the proposed method are verified by using two gearbox datasets with various few-shot noise scenarios.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"31 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on road crack segmentation based on deep convolution and transformer with multi-branch feature fusion. 基于深度卷积和变换器与多分支特征融合的道路裂缝分割研究。

Measurement Science and Technology Pub Date : 2024-07-22 DOI: 10.1088/1361-6501/ad6628

Yuebo Lai, Bing Liu

{"title":"Research on road crack segmentation based on deep convolution and transformer with multi-branch feature fusion.","authors":"Yuebo Lai, Bing Liu","doi":"10.1088/1361-6501/ad6628","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6628","url":null,"abstract":"\u0000 Efficient and precise identification of road pavement cracks contributes to better evaluation of road conditions. In practical road maintenance and safety assessment, traditional manual crack detection methods are time-consuming, physically demanding, and highly subjective. In addition, crack recognition based on image processing techniques lacks robustness. In this paper, a multi-branch feature fusion road crack segmentation network model (DTPC) based on deep convolution and transformer modules is proposed. The model is used for pixel-level segmentation of road crack images, which is a good solution to the existing needs and helps to repair dangerous cracks promptly in the follow-up work to prevent serious disasters due to crack breakage. Firstly, combine deep convolution with transformer modules to achieve precise local extraction and global contextual feature extraction. Secondly, a dual-channel attention mechanism is em-ployed to help the model better address information loss and positional offset issues. Finally, three-branch outputs are fused to obtain prediction maps that intuitively determine recognition results. The proposed model is tested for accuracy using a dedicated road pavement crack dataset. Results show that compared to mainstream models such as SegFormer, HRNet, PSPNet, and FCN, the DTPC model achieves the highest MIoU score (86.72%) and F1 score (92.49%).","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"25 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bayesian Reconstruction of 3D Particle Positions in High-Seeding Density Flows 高播种密度流体中三维粒子位置的贝叶斯重构

Measurement Science and Technology Pub Date : 2024-07-22 DOI: 10.1088/1361-6501/ad6624

Atharva Hans, Sayantan Bhattacharya, Kairui Hao, P. Vlachos, Ilias Bilionis

{"title":"Bayesian Reconstruction of 3D Particle Positions in High-Seeding Density Flows","authors":"Atharva Hans, Sayantan Bhattacharya, Kairui Hao, P. Vlachos, Ilias Bilionis","doi":"10.1088/1361-6501/ad6624","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6624","url":null,"abstract":"\u0000 Measuring particles' three-dimensional (3D) positions using multi-camera images in fluid dynamics is critical for resolving spatiotemporally complex flows like turbulence and mixing. However, current methods are prone to errors due to camera noise, optical configuration and experimental setup limitations, and high seeding density, which compound to create fake measurements (ghost particles) and add noise and error to velocity estimations. We introduce a Bayesian Volumetric Reconstruction (BVR) method, addressing these challenges by using probability theory to estimate uncertainties in particle position predictions. Our method assumes a uniform distribution of particles within the reconstruction volume and employs a model mapping particle positions to observed camera images. We utilize variational inference with a modified loss function to determine the posterior distribution over particle positions. Key features include a penalty term to reduce ghost particles, provision of uncertainty bounds, and scalability through subsampling. In tests with synthetic data and four cameras, BVR achieved 95% accuracy with less than 3% ghost particles and an RMS error under 0.3 pixels at a density of 0.1 particles per pixel (ppp). This shows 57% to 97% less ghost particles and 1.3 to 2 times lower RMS error than standard MART and IPR reconstructions. In an experimental Poiseuille flow measurement, our method closely matched the theoretical solution. Additionally, in a complex cerebral aneurysm basilar tip geometry flow experiment, our reconstructions were dense and consistent with observed flow patterns. Our BVR method effectively reconstructs particle positions in complex 3D flows, particularly in situations with high particle image densities and camera distortions. It distinguishes itself by providing quantifiable uncertainty estimates and scaling efficiently for larger image dimensions, making it applicable across a range of fluid flow scenarios.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"40 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Study on the Tribocharging Properties of MgCO3 Particles Based on LFN-en-A Model 基于 LFN-en-A 模型的 MgCO3 粒子三电荷特性研究

Measurement Science and Technology Pub Date : 2024-07-22 DOI: 10.1088/1361-6501/ad662b

Meixuan Su, Zhipeng Yang, Kewei Cai, Zhiqiang Wang, Song Yang, Guofeng Li

{"title":"Study on the Tribocharging Properties of MgCO3 Particles Based on LFN-en-A Model","authors":"Meixuan Su, Zhipeng Yang, Kewei Cai, Zhiqiang Wang, Song Yang, Guofeng Li","doi":"10.1088/1361-6501/ad662b","DOIUrl":"https://doi.org/10.1088/1361-6501/ad662b","url":null,"abstract":"\u0000 As an efficient and environment-friendly method, electrostatic separation has gradually replaced flotation methods in the separation of magnesite in recent years. In the process of triboelectrostatic separation, the mineral particles are tribocharged driven by the air flow, then the trajectory is shifted under the action of the electric field, so as to realize the separation. The useful mineral in magnesite is MgCO3, but the theoretical research related to the charge characteristics of MgCO3 is not sufficient. Particle image velocimetry (PIV), as an indirect measurement technique, is able to obtain the velocity field of the fluids from images. However, the particles moving in the air have the issues such as excessive speed and small particle size, which make the traditional PIV has low accuracy in estimating the motion of particles. In this paper, a high-speed camera is used to capture the motion trajectory of tribocharged MgCO3 particles in a parallel electric field. A new optical flow method LFN-en-A network based on LiteFlowNet-en network is proposed to compute the particle motion trajectory by combining the deep learning method with the traditional PIV, which realizes the displacement estimation of particles moving in the air. It ultimately realizes the calculation of the charge-to-mass ratio on single particles. Analyzing the accuracy of the LFN-en-A network’s estimation in the experiments, the estimation of LiteFlowNet-en was compared. Changing the shooting frame rate analyzes the optimal one required by the LFN-en-A network. Combining the estimation results of LFN-en-A to calculate the particle charge-to-mass ratio (Q/m), the Q/m of MgCO3 particle was analyzed by changing the experimental conditions in the process of particles’ tribocharging, which provided a new method for particle-to-charge ratio measurement.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141814833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on remote reference denoising method based on non-coaxial and non-coplanar tunnel NMR detection 基于非同轴非共面隧道核磁共振检测的远程参考去噪方法研究

Measurement Science and Technology Pub Date : 2024-07-22 DOI: 10.1088/1361-6501/ad662f

Yong Sun, Xiaofeng Yi, Cong Li, Zhiqin Yang, Jun Lin

{"title":"Research on remote reference denoising method based on non-coaxial and non-coplanar tunnel NMR detection","authors":"Yong Sun, Xiaofeng Yi, Cong Li, Zhiqin Yang, Jun Lin","doi":"10.1088/1361-6501/ad662f","DOIUrl":"https://doi.org/10.1088/1361-6501/ad662f","url":null,"abstract":"\u0000 The limited space within the tunnel constrains the size of the antenna for NMR detection, thereby significantly impacting the signal-to-noise ratio of NMR signals. Insufficient signal-to-noise ratio data poses substantial challenges to obtaining reliable NMR signals. The paper presents a novel approach to address the challenge of strong background noise in tunnel environments and low signal-to-noise ratio (SNR) data by incorporating the ground multi-channel remote reference denoising method into tunnel NMR advance detection. Specifically designed for narrow tunnels, a multichannel non-coaxial and non-coplanar remote reference denoising method is proposed. Firstly, the effectiveness of the non-coaxial, non-coplanar remote reference denoising method is verified in the laboratory environment. Secondly, the correlation between the detector antenna and the reference antenna is calculated theoretically to ensure the significant correlation between the detector antenna and the reference antenna. Finally, two processing methods of reference denoising and non-reference denoising are carried out respectively by combining the tunnel detection data. By comparing the inversion results and the engineering construction results, the effectiveness of non-coaxial and non-coplanar remote reference denoising methods in tunnel NMR detection is proved, which provides relevant research support for expanding the application of tunnel NMR detection technology.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"10 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141815694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AFO-SLAM: an improved visual SLAM in dynamic scenes using acceleration of feature extraction and object detection AFO-SLAM：利用加速特征提取和目标检测改进动态场景中的视觉 SLAM

Measurement Science and Technology Pub Date : 2024-07-22 DOI: 10.1088/1361-6501/ad6627

Jinbi Wei, Heng Deng, Jihong Wang, Liguo Zhang

{"title":"AFO-SLAM: an improved visual SLAM in dynamic scenes using acceleration of feature extraction and object detection","authors":"Jinbi Wei, Heng Deng, Jihong Wang, Liguo Zhang","doi":"10.1088/1361-6501/ad6627","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6627","url":null,"abstract":"\u0000 In visual simultaneous localization and mapping (SLAM) systems, traditional methods often excel due to rigid environmental assumptions, but face challenges in dynamic environments. To address this, learning-based approaches have been introduced, but their expensive computing costs hinder real-time performance, especially on embedded mobile platforms. In this article, we propose a robust and real-time visual SLAM method towards dynamic environments using acceleration of feature extraction and object detection (AFO-SLAM). First, AFO-SLAM employs an independent object detection thread that utilizes YOLOv5 to extract semantic information and identify the bounding boxes of moving objects. To preserve the background points within these boxes, depth information is utilized to segment target foreground and background with only a single frame, with the points of the foreground area considered as dynamic points and then rejected. To optimize performance, CUDA program accelerates feature extraction preceding point removal. Finally, extensive evaluations are performed on both TUM RGB-D dataset and real scenes using a low-power embedded platform. Experimental results demonstrate that AFO-SLAM offers a balance between accuracy and real-time performance on embedded platforms, and enables the generation of dense point cloud maps in dynamic scenarios.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"42 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141814877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0