Measurement最新文献

{"title":"Measurement and experimental study of flow pulsation in high-speed on–off valve based on six pressure sensors","authors":"Fulong Chen ,&nbsp;Hui Huang ,&nbsp;Yuzheng Li ,&nbsp;Guolei Si ,&nbsp;Junshou Su ,&nbsp;Heng Du ,&nbsp;Fuqi Li","doi":"10.1016/j.measurement.2025.118547","DOIUrl":"10.1016/j.measurement.2025.118547","url":null,"abstract":"<div><div>Accurate measurement of flow pulsations in high-speed on–off valve is a key factor for achieving precise noise reduction and high-precision control in digital hydraulic valve control systems. However, current flow meters are limited by technology and can only measure flow pulsations in the range of tens of hertz. Moreover, indirect measurement methods for high-frequency flow pulsations are primarily used for pumps, and their direct application to measuring valve flow pulsations can be influenced by pump sources. Therefore, to realize the accurate measurement of flow pulsations of high-speed on–off valve, based on the propagation characteristics of the pressure wave and the three-feature measurement principle, this paper proposes a high-speed on–off valve flow pulsation testing method using a three-feature six-pressure sensor. Based on the new test method, a high-speed on–off valve flow pulsation test bench is designed. The correctness of the test method is verified by flow meter. The law of flow pulsation of high-speed on–off valve changing with on/off frequency was explored by test bench. The final experimental results show that the test bench can measure the flow pulsation of the valve below 500 Hz, and the measurement error is less than 2 %. At the same time, it is found that the flow pulsation in the system is mainly affected by the high-speed on–off valve, and the amplitude of the flow pulsation decreases with the increase of the switching frequency. This study is of great significance to the accurate vibration and noise reduction of the digital hydraulic valve control system.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"257 ","pages":"Article 118547"},"PeriodicalIF":5.6,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Gaussian intelligent optimization framework for dynamic electrical impedance tomography of 3D lactate monitoring based on TK-Noser priori","authors":"Junwen Peng ,&nbsp;Zihan Zhao ,&nbsp;Jie He ,&nbsp;Kai Liu ,&nbsp;Chen Ye ,&nbsp;Bo Sun ,&nbsp;Jiafeng Yao","doi":"10.1016/j.measurement.2025.118584","DOIUrl":"10.1016/j.measurement.2025.118584","url":null,"abstract":"<div><div>A TK-Noser priori based Gaussian intelligent optimization framework (PB-GIOF) for the 3D dynamic monitoring of lactate in critically ill patients is proposed. This method addresses the challenges of localization and volume estimation caused by random lactate variations. In this study, we first approximated lactate targets of different shapes by stacking multiple 3D Gaussian spheres. Subsequently, a fitness function was formulated, integrating the TK-Noser structural and localization priors, which transformed the complex Gaussian shape reconstruction process into an optimization problem. Finally, the optimization problem was solved using the Horned Lizard Optimization Algorithm (HLOA) due to its effective global and local search capabilities. Simulation results, conducted with eight randomly positioned lactate targets of varying sizes, compared the proposed PB-GIOF algorithm against Tikhonov and TK-Noser regularization algorithms. Reconstruction results demonstrated that PB-GIOF algorithm obtains the best imaging results in almost every targets, the average <em>ICC</em><strong>/</strong><em>RMSE</em> achieve 0.877/0.062, which represents improvements of 18.9 %<strong>/</strong>32.6 % and 3.6 %<strong>/</strong>21.5 % over Tikhonov and TK-Noser algorithms, respectively. Furthermore, PB-GIOF algorithm exhibited robust target localization and volume estimation accuracy. Phantom experiments corroborated the simulation conclusions, demonstrating that PB-GIOF algorithm significantly outperformed TK-Noser algorithm in the performance of complex lactate targets imaging, especially smaller ones (<em>T</em>1 ∼ <em>T</em>3). The average <em>ICC</em><strong>/</strong><em>RMSE</em> of PB-GIOF results is 0.756<strong>/</strong>0.074, improvements of 16.8 % and 19.6 % over TK-Noser algorithm, respectively. Therefore, the proposed PB-GIOF algorithm enables accurate imaging of complex lactate targets, holding promise for the applications in critical lactate monitoring.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"257 ","pages":"Article 118584"},"PeriodicalIF":5.6,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Carrier phase common-view time transfer based on PPP with broadcast ephemeris","authors":"Runmin Lu ,&nbsp;Jie Zhang ,&nbsp;Shiming Zhong ,&nbsp;Jinyang Han ,&nbsp;Zihan Liang ,&nbsp;Qian Cui ,&nbsp;Zecheng Hu ,&nbsp;Bibo Peng","doi":"10.1016/j.measurement.2025.118597","DOIUrl":"10.1016/j.measurement.2025.118597","url":null,"abstract":"<div><div>As a high-precision time transfer technique, GNSS PPP time transfer is widely used. However, in a delayed or limited network access environment, the satellite precise products required for PPP time transfer are unavailable. This paper proposes a carrier phase common-view time transfer method based on PPP with broadcast ephemeris. The method first performs time correction on the broadcast ephemeris and solves the PPP parameters. Then, all parameters except the receiver clock offset are substituted into the carrier phase observation equation to calculate the clock offset of the receiver relative to each satellite. Finally, the common-view method is employed, utilizing the optimal modified Allan variance and threshold model to select one satellite from the common-view satellites of both stations. Alternatively, it is also possible to use only BDS GEO satellites as common-view satellites to complete the process. The clock offsets of the two stations are subtracted to complete the time transfer. The experiment involved six IGS stations linked with UTC(k) and two stations equipped with external VCH-1008 hydrogen atomic clocks, forming four links. The results show that during the 30-day time transfer of the zero-baseline WDC5-WDC6, the time transfer standard deviation of this method reached 0.022 ns. Compared to broadcast ephemeris PPP, the time transfer precision of the four links improved by an average of 51 %. For average time intervals shorter than 3000 s, the frequency stability of the four links improved by an average of 85.8 % compared to broadcast ephemeris PPP. Additionally, the carrier phase common-view time transfer results using only the BDS C60 (GEO) satellite outperforming those obtained using BDS broadcast ephemeris PPP.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"257 ","pages":"Article 118597"},"PeriodicalIF":5.6,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High sensitive, wide detection range 3D symmetrical porous Ecoflex foam sensor for intelligent detection","authors":"Longhua Zeng,&nbsp;Jingping Yao,&nbsp;Huixian Ye,&nbsp;Shengping Dai,&nbsp;Wentong Chen,&nbsp;Yan Sui","doi":"10.1016/j.measurement.2025.118575","DOIUrl":"10.1016/j.measurement.2025.118575","url":null,"abstract":"<div><div>Flexible sensors feature high sensitivity, stretchability and biocompatibility, and have great application potential in medical monitoring, human-computer interaction and wearable devices, etc. However, the development of flexible sensor with both wide detection range and high sensitivity remains a significant challenge. Here, the pore distribution structure of the foam was simulated and analyzed by ANSYS. It was found that the three-layer symmetrical structure foam model with large pores on both sides and small pores in the middle exhibits better strain range and mechanical strength. Therefore, a highly compressible 3D symmetrical porous structure carbon nanotubes (CNTs)/carbon black (CB) Ecoflex foam piezoresistive pressure sensor was prepared by salt-template method. The three-layer symmetrical structure foam exhibited higher mechanical compressibility (119 kPa) and better fatigue resistance. The assembled piezoresistive sensor exhibited exceptional performance characteristics, including high sensitivity (0.045 kPa⁻¹ within the range of 0–11.25 kPa), rapid response time (220 ms), and a broad detection range (0–108 kPa). These attributes render it well-suited for applications in domains such as handwriting recognition systems and elbow flexion monitoring. Additionally, the piezoresistive sensor can be integrated into a 3 × 3 sensor matrix for pressure identification in application s including sleep posture monitoring, pressure sore prevention.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"257 ","pages":"Article 118575"},"PeriodicalIF":5.6,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scalable automated traffic flow monitoring system for viaducts: A data-fusion approach for vehicle mass estimation","authors":"Leonardo Iacussi ,&nbsp;Paolo Chiariotti ,&nbsp;Nicola Giulietti ,&nbsp;Emanuele Zappa ,&nbsp;Alfredo Cigada","doi":"10.1016/j.measurement.2025.118478","DOIUrl":"10.1016/j.measurement.2025.118478","url":null,"abstract":"<div><div>Efficient infrastructure management requires real-time traffic monitoring to address rising vehicle loads and enable timely maintenance. This study presents a data-fusion approach combining acceleration-based and vision-based systems to classify vehicles and estimate their weight over time. Validated on a real viaduct and benchmarked against a reference P-WIM (Pavement Weigh-In-Motion) system, the fused method significantly improves vehicle mass estimation compared to vision-only methods based on the YOLOv11 model. The combined system achieves individual mass estimation errors of 15% for light and 30% for heavy vehicles. However, cumulative traffic load estimation yields a total error of just 1.5%, as individual errors tend to sink over time. Relying solely on vision leads to a consistent 5% overestimation, underscoring the added value of acceleration data. While not a replacement for high-precision P-WIM systems, this scalable approach enables continuous, network-wide traffic load monitoring using existing infrastructure, supporting smarter maintenance planning and enhanced structural health management.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"257 ","pages":"Article 118478"},"PeriodicalIF":5.6,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A cost-effective magnetic particle imaging scanner based on mixing-frequency spectra","authors":"Shaoqi Sun ,&nbsp;Shijie Sun ,&nbsp;Yongyan Wang ,&nbsp;Penghui Wang ,&nbsp;Rong Cai ,&nbsp;Wenzhong Liu ,&nbsp;Lijun Xu ,&nbsp;Jing Zhong","doi":"10.1016/j.measurement.2025.118595","DOIUrl":"10.1016/j.measurement.2025.118595","url":null,"abstract":"<div><div>Magnetic particle imaging (MPI) is an innovative medical imaging modality that allows for quantitative visualization of magnetic nanoparticles (MNPs). In this work, we develop a mixing-frequency MPI scanner that uses coprime orthogonal drive fields at 4.98  kHz and 97  Hz to realize a dense, non–uniform 2D Lissajous scanning of the field–free point (FFP). The high- and low-frequency AC magnetic fields drive the MNPs to generate high-order harmonics and their mixing-frequency components. All the mixing-frequency spectra of the MNPs are measured for image reconstruction. Compared to conventional Lissajous sequences, this design reduces the hardware complexity in the drive chain since no decoupling networks are required. Additionally, only one single band–pass filter and impedance matching are needed in the high–frequency transmit side. Phantom experiments are performed to demonstrate the feasibility of the developed mixing-frequency MPI scanner for the visualization of MNPs. Experimental results show that the designed cost–effective MPI scanner achieves an imaging speed of 1 frame per second, a spatial resolution of better than 1.5  mm at gradients of 0.64  T/m and 1.28  T/m in <em>x</em>- and <em>y</em>-direction. The experiments with a series of MNPs with different iron concentration indicate that the scanner achieves a limit of detection of 34.9  µmol/L Fe (195  ng Fe) using synomag–D Plain (hydrodynamic diameter 70 nm) MNPs.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"257 ","pages":"Article 118595"},"PeriodicalIF":5.6,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Underwater two-way acoustic and pressure gauge fusion navigation algorithm utilizing optimal constraints and smoothing","authors":"Yangfan Liu ,&nbsp;Jaume Sanz Subirana ,&nbsp;Tianhe Xu ,&nbsp;Junting Wang ,&nbsp;Wenfeng Nie ,&nbsp;Jianxu Shu","doi":"10.1016/j.measurement.2025.118585","DOIUrl":"10.1016/j.measurement.2025.118585","url":null,"abstract":"<div><div>Underwater long baseline acoustic navigation system is widely used for underwater vehicle navigation. However, traditional methods exhibit a significant increase in the navigation error of the vehicle when the acoustic observation data quality is poor. To address this issue, we propose an underwater acoustic two-way navigation algorithm that incorporates depth constraint and Rauch-Tung-Striebel (RTS) smoothing. Specifically, the proposed algorithm derives a detailed function model for underwater acoustic two-way navigation. Additionally, the position dilution of precision (PDOP) is used to search for optimal constraint information. This constraint information is then integrated into the sound velocity calculation, and the vertical coordinate of the vehicle is constrained in the measurement equation. Finally, the RTS smoother is applied to smooth the constrained acoustic navigation results backward. Experiments conducted on high-quality data demonstrate that the proposed algorithm outperforms traditional methods with an average decrease of 4.42 % in the three-dimensional root mean square (RMS-3D) value of the navigation errors. For the low-quality data, the proposed algorithm shows an average reduction of 85.47 % in the RMS-3D value in contrast to traditional methods. These results suggest that the proposed algorithm exhibits superior accuracy and stability compared to traditional methods, especially in the up direction.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"257 ","pages":"Article 118585"},"PeriodicalIF":5.6,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"General phase retrieval technology through deep learning","authors":"Yutao Liu ,&nbsp;Yong Jiang ,&nbsp;Xuchen Zhang ,&nbsp;Shi Qiu ,&nbsp;Xinghu Fu","doi":"10.1016/j.measurement.2025.118582","DOIUrl":"10.1016/j.measurement.2025.118582","url":null,"abstract":"<div><div>Data dependency and generalization issues are core challenges faced by deep learning-based phase retrieval (PR) technology. To address these aforementioned issues, this study developed an end-to-end PR method based on AttR2U-Net. Experimental verification of the PR method was conducted by building a lensless PR system under uniform illumination. A training set comprising 2000 quantitative speckle phases, was constructed using the Monte Carlo method, and their far-field diffraction images were used to train the end-to-end PR model. The experimental results indicated that the average structural similarity index obtained by the trained AttR2U-Net model on the test set is 0.988, peak signal-to-noise ratio is 35.99 dB, and mean squared error (MSE) is 0.00013. Compared with U-Net, the trained AttR2-Unet network showed more than a twofold decrease in the single-phase recovery time, while the MSE value of phase recovery in the test set decreased by one order of magnitude. Generalization analysis revealed that the trained AttR2U-Net model significantly outperformed the trained U-Net model. The proposed method establishes a high-precision mapping between far-field diffraction light-intensity images and wavefront phases, enabling end-to-end high-precision PR for arbitrary images. This capability holds substantial promise for applications in diverse fields such as optical metrology and biomedicine.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"256 ","pages":"Article 118582"},"PeriodicalIF":5.6,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neural network-enhanced dynamic light scattering for accurate sizing of large microparticles","authors":"Faezeh Torabi ,&nbsp;Saeed Ghavami Sabouri","doi":"10.1016/j.measurement.2025.118586","DOIUrl":"10.1016/j.measurement.2025.118586","url":null,"abstract":"<div><div>Dynamic light scattering (DLS) is a well-established technique for measuring particle sizes in colloidal suspensions, but its accuracy significantly diminishes for microparticles due to the dominance of multiple scattering, especially in high-volume samples. In this study, we introduce a data-driven approach using deep neural networks (DNNs) to enhance the performance of DLS for characterizing micron-sized particles. Silica microparticles of defined size ranges were prepared using a sieve tower and suspended in a water-glycerin mixture to ensure stability during measurements. Raw time-resolved scattering signals were recorded without pre-processing and used to train both classification and regression DNNs. Our results demonstrate high accuracy and repeatability in particle sizing for a wide range of sizes. Furthermore, by employing a moving sampling window across the scattering signal, we analyzed the effect of signal segments on classification performance and found that data corresponding to early-time single-scattering regions are crucial for model accuracy. This method opens new possibilities for in situ and real-time particle sizing in complex industrial environments where traditional DLS fails.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"256 ","pages":"Article 118586"},"PeriodicalIF":5.6,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144749901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Innovative cable tension monitoring method based on a three-coil coupled resonance sensor","authors":"Xinyi Chen ,&nbsp;Runchuan Xia ,&nbsp;Hong Zhang ,&nbsp;Jianting Zhou ,&nbsp;Xiaotian Wu ,&nbsp;Leng Liao ,&nbsp;Senhua Zhang","doi":"10.1016/j.measurement.2025.118577","DOIUrl":"10.1016/j.measurement.2025.118577","url":null,"abstract":"<div><div>Cable tension is a crucial indicator of the condition of cable-supported bridges. The traditional resonance-enhanced magnetoelastic (REME) method can be affected by instrument impedance, as it requires connecting equipment to a receiving loop. To address this issue, a three-coil coupled resonance sensor was developed by adding a new set of coils to the existing two-coil REME sensor. Theoretical derivations and experiments confirmed the sensor’s impedance isolation. A relationship between induced voltage and cable tension was established by combining the magnetoelastic effect with electromagnetic induction theory. An experiment involving 18 steel strands demonstrated this relationship through time–frequency domain analysis. When resistors were used with both types of sensors, the three-coil system exhibited less variation in resonant frequency and induced voltage, confirming its effectiveness. Although specimen differences and hysteresis effects decreased linearity, a nonlinear prediction method using the particle swarm optimization–backpropagation algorithm achieved an average absolute error of 3.50 kN, with relative errors under 10% for tension levels exceeding 40 kN. Overall, this method mitigates the influence of test equipment on results, significantly enhancing the applicability of the REME method.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"256 ","pages":"Article 118577"},"PeriodicalIF":5.6,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144724522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}