Measurement最新文献

{"title":"Multi-scale deformation monitoring and characterization of large-span railway bridge by joint satellite/ground-based InSAR and BDS","authors":"Xinyi Li ,&nbsp;Lv Zhou ,&nbsp;Jun Ma ,&nbsp;Cheng Wang ,&nbsp;Yuanjin Pan ,&nbsp;Yukai Chen ,&nbsp;Di Zhang ,&nbsp;Meilin He","doi":"10.1016/j.measurement.2025.118199","DOIUrl":"10.1016/j.measurement.2025.118199","url":null,"abstract":"<div><div>Combining various monitoring technologies for deformation monitoring of large-span railway bridge helps to gain a comprehensive understanding of the bridge’s dynamic characteristics and deformation characteristics. This paper proposes a joint satellite/ground-based InSAR (Interferometric Synthetic Aperture Radar) and BDS (Beidou Navigation Satellite System) method for the deformation monitoring and analysis of large-span railway bridges. Initially, the satellite-based InSAR is employed to conduct large-scale and long-term deformation monitoring of the Ganjiang Super Bridge. Time series deformation is then analyzed using ESMD (extreme-point symmetric mode decomposition). Following that, ground-based radar interferometry and BDS are employed for small-scale and high-frequency deformation monitoring of critical structural points on the bridge. Lastly, time series deformation and spectral analysis are used to summarize the dynamic characteristics of the bridge. The following conclusions are obtained based on the study: (1) From June 2021 to August 2023, InSAR monitoring results indicated relatively substantial subsidence on the bridge east side, likely due to sediment accumulation; ESMD deformation decomposition revealed a 160-day deformation periodicity and multiple mutations. (2) By comparing the deformation of adjacent points using ground radar interferometry and BDS, it is found that the deformation trends in their monitoring results are relatively similar; both methods excellently capture significant deformation data. (3) BDS monitoring results are related to bridge structural components and force transmission direction; ground-based radar interferometry results are influenced by the bridge structure and external forces; the natural frequency of the Ganjiang Super Bridge is 0.54 Hz.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"256 ","pages":"Article 118199"},"PeriodicalIF":5.2,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144336032","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":"Wire rope lay length measurement based on DT-CWT","authors":"Peiyao Li,&nbsp;Guohua Cao","doi":"10.1016/j.measurement.2025.118041","DOIUrl":"10.1016/j.measurement.2025.118041","url":null,"abstract":"<div><div>The lay length of metal wire rope constitutes a critical parameter in the characterization of wire rope. Its measurement and subsequent analysis can provide valuable insights into the stress conditions and surface integrity of the material. To solve the problem of measuring wire rope lay length, this paper proposes an online wire rope lay length measurement method based on image processing, which consists of two parts: image pre-processing (DT-CWT) and image post-processing (contour search, inter strand positioning). The wire rope texture is directionally reconstructed by DT-CWT. Then the demarcation line between wire rope strands is found by contour finding and screening. Finally, the wire rope lay length is calculated from the rope strand spacing. This method makes full use of the obviousness characteristics of the spacing between the rope strands to measure the height of robust. The method has been tested in the laboratory. The findings indicate that the proposed method is capable of measuring the lay length of steel wire rope in a non-contact manner.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"256 ","pages":"Article 118041"},"PeriodicalIF":5.2,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330920","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":"Nanoengineered biosensors: Advancing coronary artery disease diagnosis with cutting-edge nanomaterials","authors":"Sopan N. Nangare,&nbsp;Namdeo R. Jadhav","doi":"10.1016/j.measurement.2025.118188","DOIUrl":"10.1016/j.measurement.2025.118188","url":null,"abstract":"<div><div>Coronary artery disease (CAD) is a highly prevalent cardiovascular disorder worldwide, underscoring the urgent need for effective diagnostic strategies. Early detection of CAD biomarkers is critical to mitigate mortality rates. Current diagnostic methods face limitations such as low sensitivity, high costs, long processing times, poor selectivity, reliance on contrast agents, and procedural invasiveness. Nanoengineered biosensors have emerged as a transformative alternative, enabling highly sensitive, selective, rapid, cost-effective, label-free, and minimally/non-invasive <em>in vitro</em> detection of CAD biomarkers. This review focuses on the latest advancements in nano-biosensors for early CAD diagnosis. It examines the global prevalence of CAD, discusses key CAD biomarkers, and summarizes the types of biosensors and nanomaterials used in their design. The article highlights customized biosensor platforms developed by researchers, emphasizing their performance in detecting CAD biomarkers in clinical samples (for example: serum, plasma, etc.). As a result, these biosensors demonstrate excellent sensitivity, selectivity, wide linear ranges, low detection limits, stability, and reproducibility. While challenges remain, the progress in nano-biosensor technology holds significant promise for early CAD biomarker detection. Future applications of these advanced biosensors could revolutionize CAD management by enabling timely intervention, ultimately reducing the burden of cardiovascular diseases (CVDs).</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"256 ","pages":"Article 118188"},"PeriodicalIF":5.2,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144306504","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":"Theoretical analysis and experimental study on ice thickness estimation by love wave sensors","authors":"Zheng Zhao ,&nbsp;Yining Yin ,&nbsp;Fanbing Hu ,&nbsp;Xu Gao ,&nbsp;Anyu Hu ,&nbsp;Wen Wang","doi":"10.1016/j.measurement.2025.118191","DOIUrl":"10.1016/j.measurement.2025.118191","url":null,"abstract":"<div><div>The detection of ice thickness holds paramount importance in ensuring the safety of aircraft flights. In this study, we employed Love wave, a highly promising technique for ice detection and measurement of ice thickness. Initially, we scrutinized the dynamic process of stratified icing under the influence of both the heat transfer and flow fields with software COMSOL Multiphysics and developed an effective model for icing thickness incorporating the parameter of contact angle. Subsequently, leveraging the three-layer medium structure, we calculated the relationship between icing thickness and the amplitude attenuation of Love wave to establish a response model for the ice thickness of Love waves based on the acoustic attenuation effect. Based on this, we developed an 80 MHz Love wave sensor for validation, and the experimental results and theoretical calculations exhibit an error of no more than 10 %. In addition, the sensor can measure ice thickness up to 1.5 mm with a resolution greater than 0.05 mm and a sensitivity of approximately 0.4 dB/0.05 mm. This work presents a more accurate theoretical model for ice thickness detection based on Love waves and thoroughly validates the excellent ice thickness detection capability of the Love wave sensor.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"256 ","pages":"Article 118191"},"PeriodicalIF":5.2,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331068","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":"Enhanced dual-stage iterative recovery framework for incomplete data using compressed sensing and convolutional neural networks","authors":"Keyu Wan,&nbsp;Yutong Wang,&nbsp;Weiming Zhang,&nbsp;Jinfeng Wang","doi":"10.1016/j.measurement.2025.118178","DOIUrl":"10.1016/j.measurement.2025.118178","url":null,"abstract":"<div><div>In the structural health monitoring, missing data from faulty sensors significantly undermines the reliability of real-time structural condition evaluation. Existing researches primarily address this issue by employing either compressed sensing algorithms or deep learning-based spatiotemporal models to recover missing signals. However, the former approach is often constrained by strong sparsity assumptions, while the latter fails to fully utilize prior history response, thereby limiting the performance of the network. To address these limitations, this study proposes an enhanced dual-stage iterative recovery framework (EDIRF) for incomplete data using both compressed sensing (CS) and convolutional neural networks (CNN). In the first stage, the CS-based imputation was calculated according to the prior history response of the faulty sensor. In the second stage, CNN is employed to establish a nonlinear spatiotemporal mapping model for the possible response prediction. Finally, the recovery data could be obtained through the proposed EDIRF. Validation on two real bridges demonstrates that the proposed EDIRF achieves high recovery accuracy for both single-channel and multi-channel faulty types, maintaining superior performance with R² consistently above 0.85 under patterns of missing rates of 90% or complex block missing. Additionally, taking the seasonal effect into consideration could enhance the reconstruction performance of EDIRF. Moreover, the surrogate channel strategy is proposed to solve the unavailability of faulty channel in providing prior history responses. Among the current mainstream methods, EDIRF outperforms in both reconstruction accuracy and training efficiency. In summary, the proposed EDIRF provides reliable technical support for bridge health monitoring, demonstrating practical value in engineering.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"256 ","pages":"Article 118178"},"PeriodicalIF":5.2,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330978","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":"Correction of the determination for asphalt pavement surface texture depth by sand patch method","authors":"Bo Zhou ,&nbsp;Bochao Zhou ,&nbsp;Zeyuan Han ,&nbsp;Xinrui Xie","doi":"10.1016/j.measurement.2025.118186","DOIUrl":"10.1016/j.measurement.2025.118186","url":null,"abstract":"<div><div>To enhance the accuracy of the sand patch method, this study proposes an improved sand patch method based on the original one through pre-test. The research has demonstrated that the mean texture depth (MTD) by the original sand patch method has a large fluctuation and low accuracy, measured supported by extensive on-site testing with a relative error ranging from 3.4 % to 55.0 %. In order to improve its precision, this study adopted a stepwise sand volume to determine the sand spreading diameter and proposed the steady-state range for both. The results showed that the steady-state range of sand volume and diameter varies under different texture depths. The recommended sand spreading volume for lower texture depth (MTD &lt; 0.5 mm) is 25 ml, and for medium texture depth (0.5 mm &lt; MTD &lt; 1 mm) is 50 ml, and for higher texture depth (1 mm &lt; MTD &lt; 1.25 mm) is 75 ml. To facilitate on-site testing, a sand spreading diameter of 25 cm can be used as the criterion. Starting with a sand volume of 25 ml, the sand is spread incrementally bu step of 25 ml until the diameter reaches 25 cm, then the test data obtained is considered valid. The improved sand patch method has a relative error ranging from 3.3 % to 4.6 %, significantly enhancing the stability and accuracy of pavement texture depth test, successfully overcoming the limitations of the original sand patch method.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"256 ","pages":"Article 118186"},"PeriodicalIF":5.2,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313310","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":"Regionally focused neural-coder model designed for the diagnosis of acute lymphoblastic leukemia disease","authors":"Erdal Başaran ,&nbsp;Gaffari Çelik ,&nbsp;Mesut Toğaçar","doi":"10.1016/j.measurement.2025.118176","DOIUrl":"10.1016/j.measurement.2025.118176","url":null,"abstract":"<div><div>Cancer ranks as the second leading cause of death worldwide, accounting for one in six deaths. Early diagnosis of cancer in patients significantly increases their survival chances by accelerating the treatment process. One of the most prevalent types of cancer today is leukemia, also known as blood cancer. The diagnosis of leukemia involves examining bone marrow smears and peripheral blood smears under a microscope in a laboratory setting, with detailed observation of these two indicators. However, specialists in this field may not always be available, leading to potential human errors. In this study, 3256 publicly available PBS images were used to diagnose Acute Lymphoblastic Leukemia (ALL). Initially, the images were trained using the DarkNet19 ESA model, and deep features of the images were extracted. Then, features were obtained by training the images with the GradCAM algorithm and combining these features with those from the DarkNet19 ESA model. The features were further trained using AutoEncoder networks, doubling the number of features. Finally, effective features were identified using the Harris Hawk optimization algorithms and classified with machine learning algorithms to diagnose ALL from PBS images. As a result, the disease was diagnosed with an accuracy rate of 98.52%. The proposed model enables the early and rapid detection of ALL.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"256 ","pages":"Article 118176"},"PeriodicalIF":5.2,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313326","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":"Comparison of water vapor transmission rates using different measurement methods","authors":"Hajime Yoshida ,&nbsp;Takeo Ebina ,&nbsp;Akira Ono ,&nbsp;Tetsuji Itoh","doi":"10.1016/j.measurement.2025.118180","DOIUrl":"10.1016/j.measurement.2025.118180","url":null,"abstract":"<div><div>Water vapor transmission rates of films were measured by Japanese testing laboratories and the authors using six different methods. The results were analyzed through comparison. The measurement range was from 10⁻³ to 20 g m⁻² day⁻¹ at 40 °C and 90 % relative humidity. Two commercially available clay nanocomposite gas barrier films and three reference films with a small hole were used as samples. The measurements agreed within ±30 % in the range from 1 to 20 g m⁻² day⁻¹ and within ±50 % at around 0.1 g m⁻² day⁻¹. The agreement declined as the water vapor transmission rate decreased. The maximum differences were approximately 13-fold in the measurements of less than 0.1 g m⁻² day⁻¹. The origin of these differences was discussed.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"256 ","pages":"Article 118180"},"PeriodicalIF":5.2,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144336033","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 visual six-degree of freedom posture measurement system for evaluation of parallel manipulators using a pyramidal mirror and a phase-encoded binary scale","authors":"Jong-Ahn Kim ,&nbsp;Jae Yong Lee ,&nbsp;Chu-Shik Kang ,&nbsp;Jae Heun Woo","doi":"10.1016/j.measurement.2025.118187","DOIUrl":"10.1016/j.measurement.2025.118187","url":null,"abstract":"<div><div>We propose a vision-based six-degree of freedom (6-DOF) posture measurement system for evaluating parallel manipulators in precision motion control applications. The system acquires 6-DOF information by capturing four coordinate sets of center points from partial images of a phase-encoded binary scale attached to the manipulator’s moving plate. A monocular vision system, combined with a pyramidal mirror and adjustable beam-steering mirrors, enables optimized lines of sight for improved sensitivity and measurement range. A telecentric lens reduces distortion, and a decoding algorithm enhances accuracy. A self-calibration algorithm further refines precision using redundant coordinates. The system achieved axial stability of 0.04 μm and 0.17″, with posture measurement deviations within ±0.58 μm and ±2.8″ compared to a reference system, representing substantial improvements over best existing method with readout stability of 5.4 μm and 8.3″. Sensitivity to uncertainty sources was analyzed using Jacobian matrices. The proposed system provides a compact, high-precision, and practical solution for in situ calibration and performance evaluation of parallel manipulators and robotic systems.</div><div>We propose a vision-based six-degree of freedom (6-DOF) posture measurement system for evaluating parallel manipulators in precision motion control applications. The system acquires 6-DOF information by capturing four coordinate sets of center points from partial images of a phase-encoded binary scale attached to the manipulator’s moving plate. A monocular vision system, combined with a pyramidal mirror and adjustable beam-steering mirrors, enables optimized lines of sight for improved sensitivity and measurement range. A telecentric lens reduces distortion, and a decoding algorithm enhances accuracy. A self-calibration algorithm further refines precision using redundant coordinates. The system achieved axial stability of 0.04 μm and 0.17″, with posture measurement deviations within ±0.58 μm and ±2.8″ compared to a reference system, representing substantial improvements over best existing method with readout stability of 5.4 μm and 8.3″. Sensitivity to uncertainty sources was analyzed using Jacobian matrices. The proposed system provides a compact, high-precision, and practical solution for in situ calibration and performance evaluation of parallel manipulators and robotic systems.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"256 ","pages":"Article 118187"},"PeriodicalIF":5.2,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322823","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":"Robust incremental random RNN for process industries soft sensing","authors":"Wenyi Li ,&nbsp;Wei Dai ,&nbsp;Biao Li ,&nbsp;Conghu Liu","doi":"10.1016/j.measurement.2025.117625","DOIUrl":"10.1016/j.measurement.2025.117625","url":null,"abstract":"<div><div>Recurrent neural networks (RNNs) serve as critical tools for soft-sensing modeling in process industries. However, their network architectures typically require manual tuning, and training data contaminated by abnormal samples can significantly hinder model generalization. To address these limitations, we present an Incremental Random Recurrent Neural Network (IRRNN) model that enables automated architecture expansion and random parameter learning. A tailored Robust Incremental Random (RIR) learning algorithm is subsequently developed for this framework. The algorithm employs derivative-based abnormal samples detection and state resampling techniques to transform contaminated datasets into semi-supervised learning scenarios. This is followed by a constrained optimization approach incorporating quadratic inequality constraints to determine output weights, further fortifying model robustness. Benchmark evaluations and industrial case studies on hematite grinding processes soft sensing demonstrate the proposed method’s superior resilience to abnormal samples and prediction accuracy compared to conventional approaches.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"256 ","pages":"Article 117625"},"PeriodicalIF":5.2,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313311","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}