Measurement最新文献

{"title":"Multisensor-integrated metrology for multi-scale geometric characterization of aeroengine rotor shafts: adaptive error compensation and industrial validation","authors":"Lei Li ,&nbsp;Bing Li ,&nbsp;Yupeng Shi ,&nbsp;Zijie Sun ,&nbsp;Xiang Wei","doi":"10.1016/j.measurement.2025.119211","DOIUrl":"10.1016/j.measurement.2025.119211","url":null,"abstract":"<div><div>The rotary shaft is a critical component in aeroengines, serving to support transmission parts, transmit torque, and withstand loads. With the rapid advancement of the aviation industry, the precision requirements for shaft components have become increasingly stringent. Traditional measurement techniques often fall short in achieving high-precision and high-efficiency automated measurements. To address this challenge, this study develops a vertical digital measurement system for shafts. Leveraging advanced technologies such as machine vision, optical detection, and deep learning, the system employs a multi-sensor collaborative approach to investigate hardware design, error compensation, the implementation and application of various measurement techniques, and the development of measurement software. By analyzing hundreds of macro and micro characteristics of complex rotary shafts, the system achieves automated measurement with single clamping. The system features an axial measurement range of 1300 mm, a radial measurement range of 120 mm, a measurement cycle of less than 15 min,<!--> <!-->and achieves an expanded uncertainty of 1.2 µm for macro-contour profiling and ±1 µm for runout measurement.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"258 ","pages":"Article 119211"},"PeriodicalIF":5.6,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269078","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":"Simultaneous prediction of Panax ginseng origin and ginsenoside Re content using hyperspectral imaging and a multi-task one-dimensional convolutional neural network","authors":"Xinjie Shen ,&nbsp;Yi Dong ,&nbsp;Haifeng Yu ,&nbsp;Nan Hao ,&nbsp;Jiacong Ping ,&nbsp;Wanjiao Wang ,&nbsp;Menglei Song ,&nbsp;Yu Wang ,&nbsp;Changqing Liu ,&nbsp;Heshui Yu ,&nbsp;Zheng Li","doi":"10.1016/j.measurement.2025.119151","DOIUrl":"10.1016/j.measurement.2025.119151","url":null,"abstract":"<div><div>Origin tracing and saponin content determination are key factors in ginseng quality control, but traditional methods require independent modeling and encounter difficulties in small-sample scenarios. Statistical analysis revealed that ginsenoside Re content exhibits origin-specific associations. In this study, a multi-task one-dimensional convolutional neural network integrating channel attention modules was constructed, combined with hyperspectral technology and an uncertainty-driven dynamic weighting strategy, to achieve simultaneous origin classification and content prediction. The relationship between wavelength, origin, and saponins was analyzed through visualization of attention weights. The model achieved a classification accuracy of 92.59%, F1 score of 0.8969, precision of 0.9125, and recall of 0.8857. The regression task yielded an R² of 0.9074, RMSE of 0.0060, and RPD of 3.2864. Results demonstrate that compared to classical machine learning models such as random forest and support vector machine, as well as single-task 1DCNN, the proposed model exhibits efficient and accurate prediction of ginseng origin and ginsenoside Re content. High-weight channels correspond to wavelengths highly relevant to the prediction tasks. This method provides a novel approach for ginseng origin tracing and quality control, demonstrating the significant potential of multi-task prediction and establishing a foundation for the standardization and industrialization of traditional Chinese medicine.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"258 ","pages":"Article 119151"},"PeriodicalIF":5.6,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270171","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":"Real-time high-precision zenith tropospheric delay stable mapping strategy for sparse stations","authors":"Hao Yang ,&nbsp;Xiufeng He ,&nbsp;Vagner Ferreira ,&nbsp;Susu Song ,&nbsp;Wei Zhan ,&nbsp;Xinzhe Xu ,&nbsp;Shengyue Ji","doi":"10.1016/j.measurement.2025.119210","DOIUrl":"10.1016/j.measurement.2025.119210","url":null,"abstract":"<div><div>Zenith tropospheric delay (ZTD) represents the signal retardation of electromagnetic waves propagating through the neutral atmosphere, serving as both a critical error source in satellite navigation and a valuable parameter for meteorological applications. Global Navigation Satellite System (GNSS) technology provides high-precision ZTD estimation, but sparse station coverage poses fundamental challenges for real-time ZTD mapping, particularly in regions with complex terrain where conventional interpolation methods exhibit limited accuracy due to inadequate characterization of ZTD’s vertical stratification. Here we present a hierarchical framework incorporating two methods: ZTD-ER, combining a three-dimensional voxel empirical model (EZTD) with radial basis function interpolation, and ZTD-GR, integrating Global Forecast System (GFS) data with radial basis function interpolation. The respective average RMSE values are 6.85 mm and 5.90 mm. We found that this represents accuracy improvements of 46–67 % compared to traditional polynomial and spherical harmonic methods, while the EZTD-based approach maintains near-optimal performance (6.85 mm RMSE) even when GFS data is unavailable, demonstrating superior robustness across different elevations and seasons. Our results provide a reliable solution for high-precision real-time ZTD mapping in challenging regions where GNSS networks are sparse. This strategy addresses critical limitations in current tropospheric modeling capabilities, offering enhanced spatial resolution for real-time GNSS meteorological monitoring and improved atmospheric corrections for precision satellite navigation applications. The framework’s operational flexibility and demonstrated accuracy make it particularly valuable for extreme weather early warning systems in sparse stations areas around the world.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"258 ","pages":"Article 119210"},"PeriodicalIF":5.6,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269193","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":"An ECG compression method exploiting a QRS detector for sparse dictionary learning","authors":"Antonia Kovacova ,&nbsp;Grazia Iadarola ,&nbsp;Luca De Vito ,&nbsp;Ondrej Kovac ,&nbsp;Jan Saliga ,&nbsp;Jergus Sevec","doi":"10.1016/j.measurement.2025.119177","DOIUrl":"10.1016/j.measurement.2025.119177","url":null,"abstract":"<div><div>This paper presents a Compressed Sensing (CS) method for electrocardiogram (ECG) using sparse dictionary learning for dimensionality reduction that exploits frames of one heart-depolarization cycle. The ECG signal is first acquired at the Nyquist rate and then segmented into multiple frames, with each frame aligned depending on the QRS complex positions detected by the Pan-Tompkins algorithm. During the training phase, a dictionary built through the Discrete Cosine Transform (DCT) is reduced through the Multiple Measurement Vector (MMV) algorithm. The compression employs the Deterministic Binary Block Diagonal (DBBD) matrix as a sensing matrix. The ECG frames are reconstructed by solving the MMV problem, and individual frames are aligned based on the R-peak value. This proposed method enables efficient data compression while preserving essential ECG signal information. The method achieves a high compression ratio of 12 while maintaining a low PRD, demonstrating its efficiency without compromising signal quality. Reconstruction quality was evaluated using both Weighted Diagnostic Distortion (WDD) and the Wavelet Energy–based Diagnostic Distortion (WEDD) metrics, showing very good to good WDD values up to CR = 12 and WEDD values indicating very good to excellent reconstruction.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"258 ","pages":"Article 119177"},"PeriodicalIF":5.6,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145247837","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":"Correlation analysis of dynamic signal characteristics during whirlwind milling","authors":"Chao Liu ,&nbsp;Youfeng Wei ,&nbsp;Juanjuan Zheng ,&nbsp;Shaofu Huang ,&nbsp;Gang Shen","doi":"10.1016/j.measurement.2025.119209","DOIUrl":"10.1016/j.measurement.2025.119209","url":null,"abstract":"<div><div>Cutting vibration and cutting force are two critical physical variables that offer valuable insights into the screw whirling process. Most previous studies have focused on experimental characterisation or tool motion analysis, lacking research on the intrinsic coupling relationship between vibration and cutting force. This has resulted in a lack of systematic understanding of the dynamic interaction processes within the machining system. This study performs appropriate phase space reconstruction (PSR) on one-dimensional milling signals and uses it to draw a cross-recursive plot (CRP). Based on the structural characteristics of the image, the correlation between signals is discussed qualitatively. A subsequent cross recurrence quantitative analysis (CRQA) is employed to quantitatively evaluate the correlation across different process parameters. Unlike traditional non-linear analysis techniques, the cross-recursive method can capture coupling properties in short-term, non-stationary, non-linear signals. This paper is the first to apply the cross-recursive method to the study of the correlation between vibration and cutting force in dry whirlwind milling. The research results indicate that there is a good continuous correlation between vibration and cutting force under certain combinations of process parameters. At high cutting speeds (V_t = 180 m/min), the use of multiple cutting tools (N_t = 6) significantly reduces the correlation and stability between vibration and force (by approximately 30–35 %). However, at low cutting speeds (V_t = 60 m/min), the use of multiple cutting tools enhances the correlation (by approximately 20 %).</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"258 ","pages":"Article 119209"},"PeriodicalIF":5.6,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270179","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":"Design a low-cost solar PV data logger and assess the application and accuracy with off-grid monocrystalline panels","authors":"MD Shouquat Hossain ,&nbsp;Mohamed Bashir Ali Bashir ,&nbsp;Khadiza Akter","doi":"10.1016/j.measurement.2025.119176","DOIUrl":"10.1016/j.measurement.2025.119176","url":null,"abstract":"<div><div>Meteorological parameters significantly influence the photoelectric conversion efficiency of photovoltaic (PV) modules, playing a pivotal role in determining the overall system performance. This research aims to investigate the effects of these parameters on the electrical and thermal performance of off-grid monocrystalline PV panels using an innovative microcontroller-based data logger system. This study conducted an experimental investigation between April and August 2023 to monitor two off-grid PV systems of 100 watts with loads. The record outputs on July 11, 2023, with 69.55 W and 74.51 W for PV-1 and PV-2 modules, respectively, at an irradiance of 982.52 W/m², demonstrate a strong correlation between the PV output power and cell temperature. The best efficiencies reached were 14.65% (PV-1) and 15.98% (PV-2) on June 6, 2023, demonstrating a strong influence of thermal gradients on the performances. The fabricated data logger, based on an ATmega328P microcontroller, incorporates multi-point temperature measurement (5 sensors), triple data export (SD card, USB, and IoT), and real-time monitoring at 95-98% lower cost than commercial alternatives. The results indicated a power loss rise of 6.48-7.58 W/100 W/m² increase in irradiance, corresponding to a temperature sensitivity and efficiency loss of 2.59-2.82%/100 W/m², with a ±1–5% margin. The modularity indicates that the system is well-suited for rural electrification and small-scale off-grid installations. This work extends the capabilities of low-cost PV monitoring by bridging the gap in both spatial thermal resolution and cost, providing a platform for the development of optimized renewable energy interventions in low-resource environments.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"258 ","pages":"Article 119176"},"PeriodicalIF":5.6,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268976","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":"On the measurement of enhanced energy storage in composite concentric helical pipes with RSA-DNN verification","authors":"Lei Chang ,&nbsp;Mohammed A. El-Meligy ,&nbsp;Khalid A. Alnowibet","doi":"10.1016/j.measurement.2025.119154","DOIUrl":"10.1016/j.measurement.2025.119154","url":null,"abstract":"<div><div>This study presents a measurement framework for evaluating the thermal and mechanical response of a concentric helical energy storage unit. The device comprises two coiled pipes: the inner pipe carries a heat-transfer fluid (HTF), and the outer pipe is maintained at the liquidus temperature of a binary solar salt that serves as phase-change material (PCM). The PCM-filled annulus is modeled via the enthalpy–porosity method to capture mushy-zone behavior with temperature-dependent properties for both PCM and HTF. The inner pipe is an Al/AlN metal–matrix composite (MMC); its effective conductivity is computed using the Maxwell–Eucken relation. Transient CFD with energy, momentum, and mass conservation is coupled to a one-way fluid–structure interaction (FSI) step to quantify tube deformation. Model validity is established against published data with a maximum discrepancy of 5.2%. To enable rapid performance estimation, a Reptile Search Algorithm–optimized deep neural network (RSA-DNN) is trained on simulation data to map operating/material inputs to the outlet–inlet temperature rise and to replicate the FSI-informed trends. The surrogate achieves validation R² up to 0.947 and ≤0.5 K absolute error across the operating envelope while preserving expected monotonic trends with mass flow and AlN fraction. As an application, four HTFs are benchmarked: Therminol 62 attains a 48 °C gradient at 200 s with the lowest mass flow (50 g/s), whereas Therminol 66 requires 57.89 g/s. The integration of CFD–FSI modeling with an RSA-optimized DNN surrogate constitutes a novel, data-efficient framework that simultaneously captures thermal and structural responses in PCM-assisted helical systems. This dual focus on thermo-mechanical performance, combined with a metaheuristic-optimized surrogate, goes beyond existing PCM-based exchanger studies. It enables rapid HTF/material screening, reduces reliance on costly simulations, and informs the design of compact, durable, and application-ready energy storage systems.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"258 ","pages":"Article 119154"},"PeriodicalIF":5.6,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269082","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":"Lever-arm based sample deformation transducer for axial and radial measurements in triaxial apparatus","authors":"Marcin Witowski","doi":"10.1016/j.measurement.2025.119206","DOIUrl":"10.1016/j.measurement.2025.119206","url":null,"abstract":"<div><div>This paper presents an innovative non-contact system for measuring axial and radial strains in a triaxial apparatus specifically tailored for small diameter soil specimens. By employing miniature magnetometers positioned both inside and outside the triaxial cell, the design overcomes errors inherent in internal and external sensor mounting and interactions with the test medium. Initial signal conditioning is performed on a microcontroller while a trained neural network translates the non-linear relationship between magnetic field readings and actual displacements. The system achieves a resolution of 0.001 mm and is fully resistant to high pressures and water ingress. Calibration and comparative experiments on standard materials and natural soils demonstrate its superior accuracy in determining elastic moduli, detecting stiffness degradation at very low strains, and identifying yield limits, outperforming conventional external measurement techniques. This versatile approach provides a powerful tool for advanced soil mechanical characterization in both laboratory testing and numerical modeling.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"258 ","pages":"Article 119206"},"PeriodicalIF":5.6,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270170","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":"Shape optimization of microlever for mode-localized accelerometer","authors":"Huizi Li ,&nbsp;Yongcun Hao ,&nbsp;Han Li ,&nbsp;Honglong Chang","doi":"10.1016/j.measurement.2025.119178","DOIUrl":"10.1016/j.measurement.2025.119178","url":null,"abstract":"<div><div>A microlever is an effective approach to increase the sensitivity of MEMS sensors. However, traditional optimization methods for microlevers have limitations in improving the amplification factor. In this paper, a shape optimization method based on the BOBYQA algorithm is utilized in microlever optimization for the first time to improve the amplification factor. Compared with the traditional rectangular microlever, the optimized dragonfly-shaped microlever achieves superior performance under the same dimensions. Mode-localized accelerometers integrating the optimized dragonfly-shaped microlever are fabricated to verify the proposed optimization method. The experimental results show that following shape optimization, the accelerometer achieves a sensitivity of 630/g, which is 264 % higher than before optimization.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"258 ","pages":"Article 119178"},"PeriodicalIF":5.6,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270174","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":"Quantitative assessment of emulsified oil concentration based on near-infrared spectroscopy and multiple machine learning algorithms","authors":"Qian Yan ,&nbsp;Yongchao Hou ,&nbsp;Shunli Yan ,&nbsp;Chunxiao Mu ,&nbsp;Chaorui Li","doi":"10.1016/j.measurement.2025.119204","DOIUrl":"10.1016/j.measurement.2025.119204","url":null,"abstract":"<div><div>Marine emulsified oil is formed from oil wastewater discharged by ships or through wind and wave action following marine oil spills. A rapid quantitative analysis method for emulsified oil concentration is therefore crucial for effective pollution cleanup and disaster assessment. A quantitative assessment method using near-infrared spectroscopy with kernel density estimation (KDE) combined with multiple machine learning algorithms is developed for measuring emulsified oil concentration. Five machine learning models are applied in this study: random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), support vector regression (SVR), and deep neural network (DNN). Laboratory measurements of near-infrared spectra are conducted on six emulsified oil samples using a mini-spectrometer. The characteristic band of the measured spectra is identified and selected, with results consistent with previous studies. The results demonstrate that KDE preprocessing significantly improves the predictive accuracy of all models, resulting in correlation coefficient (<em>R</em>²) values above 0.95 and relative improvements ranging from 5% to 35.1%. Notably, the RF model showed the most substantial improvement from 0.706 to 0.954. Moreover, the DNN model is able to achieve the most accurate prediction among the five machine learning models at the cost of more computation time. The XGBoost model, or the LightGBM model may be a favorable choice when training time is limited. The RF model and the SVR model are limited in prediction accuracy and computation time, respectively.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"258 ","pages":"Article 119204"},"PeriodicalIF":5.6,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145269679","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}