Measurement最新文献

{"title":"Comprehensive study of machining mechanism, experimental measurement and numerical analysis in ultrasonic-assisted micro-drilling of printed circuit board","authors":"Moran Xu ,&nbsp;Yixiao Yang ,&nbsp;Xunchen Chu ,&nbsp;Longchao Cao ,&nbsp;Junxiang Li ,&nbsp;Jia Ge ,&nbsp;Shuo Chen ,&nbsp;David Adzah ,&nbsp;Saood Ali ,&nbsp;Wang Cai ,&nbsp;Changping Li ,&nbsp;Tae Jo Ko","doi":"10.1016/j.measurement.2026.120954","DOIUrl":"10.1016/j.measurement.2026.120954","url":null,"abstract":"<div><div>As the core carrier for achieving high-density interconnections in electronic devices, the quality of micro hole fabrication in printed circuit board (PCB) plays a crucial role in determining electrical performance and overall system reliability. Conventional micro drilling (CMD) often leads to defects such as burr formation, copper foil tearing, substrate delamination, and thermal damage, which severely restrict its applicability in high-precision fields. By integrating experimental measurements with finite element simulations, this study systematically verifies the pronounced advantages of ultrasonic-assisted micro-drilling (UAMD) in regulating the cutting process and enhancing machining performance in PCB micro-hole fabrication. Utilizing a self-developed high-frequency ultrasonic vibration spindle system, both CMD and UAMD processes were conducted to analyze the effects of spindle speed and feed rate on drilling thrust, hole entrance/exit morphology, inner wall integrity, chip formation, and tool wear. The experimental measurements are validated through comparison with simulation models. The results indicate that the high-frequency vibrations induced by UAMD markedly enhance cutting force stability and facilitate efficient chip removal. In comparison to CMD, UAMD achieved a maximum reduction of 19.1% in cutting force when drilling copper and 21.5% when drilling glass fiber reinforced polymer (GFRP), accompanied by a 14.8% decrease in the damage factor. Furthermore, tool wear was significantly reduced due to the reduction in heat accumulation. This study shows that UAMD optimizes cutting dynamics, reduces cutting forces, improves chip evacuation and hole-wall integrity, and enhances the consistency and overall quality of PCB micro-holes, providing theoretical and technical support for high-efficiency fabrication in advanced PCB manufacturing.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"271 ","pages":"Article 120954"},"PeriodicalIF":5.6,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387886","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":"Incipient bearing fault diagnosis based on optical fiber sensor and feature-informed geometric partition entropy guided informative frequency band extraction","authors":"Kai Zheng ,&nbsp;Zihao Long ,&nbsp;Pengyuan Zhao ,&nbsp;Jiaquan Tang ,&nbsp;Bo Wei ,&nbsp;Maolin Luo","doi":"10.1016/j.measurement.2026.121003","DOIUrl":"10.1016/j.measurement.2026.121003","url":null,"abstract":"<div><div>Fiber Bragg Grating (FBG) sensors, with advantages of compactness and immunity to electromagnetic interference, offers a transformative solution for overcoming the challenges of bearing fault diagnosis under harsh operating conditions. The FBG dynamic strain signal can be used for detecting early weak bearing fault signal. However, when the FBG dynamic strain signals are processed through second-order differentiation to derive equivalent acceleration signals, the noise is significantly amplified, which poses significant challenges to extract the weak fault feature. To address this issue, this paper proposes a feature-informed geometric partition entropy (FIGPE) guided informative frequency bands (IFBs) extraction strategy for bearing fault diagnosis based on FBG dynamic strain signal. Initially, the cyclostationarity and impulsiveness of the equivalent acceleration signal of FBG strain caused by bearing faults is revealed. After that, a new indicator named as FIGPE with no prior fault information is developed. This indicator comprehensively considers both the cyclostationarity and impulsiveness of the FBG equivalent acceleration signal. Finally, a bandpass filter based on Linear Piecewise Windowing (LPW) is constructed to isolate fault-related frequency components from the signal, where the FIGPE is guided to adaptively determine optimal center frequencies and bandwidth parameters of the filter based on Bayesian optimization. The results show that the proposed method can effectively identify bearing fault features in FBG equivalent acceleration signals without prior knowledge while suppressing noise. Its effectiveness has also been further verified through simulations, experiments, and comparisons with existing methods.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"271 ","pages":"Article 121003"},"PeriodicalIF":5.6,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387294","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 point cloud registration method based on RGB-D information and voting mechanism","authors":"Yuandong Huang,&nbsp;Jinbo Chen,&nbsp;Mei Liu,&nbsp;Zhiming Wang","doi":"10.1016/j.measurement.2026.120989","DOIUrl":"10.1016/j.measurement.2026.120989","url":null,"abstract":"<div><div>Accurate point cloud registration under RGB-D sensing remains challenging when the data suffer from high noise, low quality, and missing geometric features. This study proposes a RGB-D fusion-based registration method to enhance robustness and accuracy in such adverse conditions. A graph structure is first constructed from initial correspondences, and nodal clustering coefficients are utilized for pruning to improve computational efficiency. An image difference weight is then introduced to evaluate node reliability, while a dynamic visual coefficient refines the node scoring process. Subsequently, a voting mechanism combining geometric and image features is designed to select high-confidence correspondences through node–edge interactions. High-scoring nodes are extracted as initial inliers, followed by RANSAC-based optimization to further refine inlier selection. The proposed method was validated on a custom RGB-D dataset and public datasets. Experimental results demonstrate that the method achieves superior registration precision and stability, especially when dealing with low-quality, weakly geometric, high-noise, or unknown-overlap point clouds, confirming its effectiveness for practical RGB-D measurement applications.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"271 ","pages":"Article 120989"},"PeriodicalIF":5.6,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387335","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 lightweight CNN-ISO collaborative optimization framework addressing high-dimensional redundancy and class imbalance in rolling bearing fault diagnosis","authors":"Siyu Chen ,&nbsp;Bangcheng Zhang ,&nbsp;Xiao He ,&nbsp;Xiaopeng Chang ,&nbsp;Yubo Shao ,&nbsp;Zhi Gao","doi":"10.1016/j.measurement.2026.120912","DOIUrl":"10.1016/j.measurement.2026.120912","url":null,"abstract":"<div><div>A lightweight CNN-ISO collaborative framework with dual feature selection is proposed to address the Accuracy-efficiency trade-off arising from high-dimensional redundancy and class imbalance in rolling bearing fault diagnosis. In the first stage, a one-dimensional CNN automatically extracts 256-dimensional deep features from the raw vibration signals, constituting the initial feature selection phase. In the second stage, an improved snake swarm optimization (ISO) algorithm, guided by a joint fitness function, conducts a synchronous search in both the feature and parameter spaces, thereby achieving simultaneous optimization of feature compression and classification Accuracy. Experimental evaluations on the CWRU, Paderborn, and XJTU-SY datasets show that the proposed framework achieves an average feature compression rate of approximately 0.75 while maintaining an Accuracy above 0.90. Compared with CNN, LSTM, CNN_SVM, and CNN_SO_SVM, it yields a Macro-F1 improvement of approximately 0.10–0.50, particularly on datasets exhibiting inter-class imbalance, with test times ranging from 0.0008 to 0.02 s. These results confirm that the proposed dual feature selection and collaborative optimization strategy not only effectively mitigates high-dimensional redundancy and class imbalance but also offers an efficient and practical solution for real-time fault diagnosis in industrial applications.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"271 ","pages":"Article 120912"},"PeriodicalIF":5.6,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387377","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 VIS-NIR spectral -temporal- spatial resolved measurement system and its application in bio-samples sensing","authors":"Yunfei Li ,&nbsp;Guancheng Li ,&nbsp;Yizhen Wang ,&nbsp;Xiuling Liu ,&nbsp;Fuhong Cai","doi":"10.1016/j.measurement.2026.121000","DOIUrl":"10.1016/j.measurement.2026.121000","url":null,"abstract":"<div><div>Traditional diffuse reflectance spectroscopy (DRS) primarily targets the near‑infrared spectral range and seldom integrates temporal and spatial domain information for a comprehensive investigation of biological tissues. In this work, we present a compact visible–near-infrared system that acquires continuous diffuse reflectance spectra from 400 to 800 nm at multiple source–detector separations ranging from 6.75 to 15.75 mm for transcutaneous measurements. A slit-based detection window improves compactness and collection efficiency, yielding enhanced short-wavelength performance with the signal-to-noise ratio increasing from 1.34 to 6.76 in the 400 to 500 nm range compared with a conventional spectrometer. Comprehensive spectral information enables more accurate extraction of hemoglobin and melanin dynamics, thereby enhancing the analysis in transcutaneous detection applications. The integration of temporal information enables the extraction of pulse waveform signals across the full spectral range of VIS–NIR. Temporal analysis further enables photoplethysmography (PPG) waveform retrieval across the full 400 to 800 nm range, showing strong cross-wavelength synchrony, with a peak-matching score of 0.805. Moreover, the incorporation of spatial information facilitates the extraction of depth-resolved optical properties, enabling the quantification of effective attenuation coefficients to differentiate tissue types. In the 600–700 nm band, the effective attenuation coefficient in the palm is 1.90-fold higher than that in the forearm, consistent with differences in tissue optical properties. This provides a key tool for future clinical physiological monitoring, particularly in overcoming signal variations caused by differences in scattering coefficients among individuals. In the future, the spectral-temporal-spatial resolved measurement system can provide more comprehensive optical information for DRS and holds the potential to enable more accurate monitoring of physiological parameters in clinical settings.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"271 ","pages":"Article 121000"},"PeriodicalIF":5.6,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387431","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 multi-stage bearing remaining useful life prediction framework integrating dual-layer data fusion and feature correction","authors":"Zhen Zhang ,&nbsp;Zhijian Wang ,&nbsp;Junyuan Wang ,&nbsp;Zhongxin Chen ,&nbsp;Weibo Ren ,&nbsp;Yanfeng Li ,&nbsp;Wenhua Du ,&nbsp;Lei Donga ,&nbsp;Xin Fan","doi":"10.1016/j.measurement.2026.120991","DOIUrl":"10.1016/j.measurement.2026.120991","url":null,"abstract":"<div><div>In complex operating conditions, multi-sensor data fusion and degradation modeling often face dynamic uncertainties that affect the reliability of Remaining Useful Life (RUL) predictions. To address this issue, this paper proposes a confidence-guided multi-stage RUL prediction framework. First, the Double-layer Time-weighted Multi-sensor Fusion Strategy (DTMFS) algorithm is proposed, which constructs a dual-layer fusion mechanism by dynamically evaluating sensor-level and system-level confidence, guiding adaptive sensor weighting. Second, feature subset selection and primary-auxiliary feature fusion strategies are adopted in Health Indicator (HI) construction to optimize information utilization. An Adaptive Degradation Trajectory Correction (ADTC) method is also proposed to ensure the monotonicity and physical consistency of the HI. Finally, a confidence score(CS) is proposed to dynamically assess model output credibility, enabling adaptive selection in multi-stage modeling. Validation through accelerated bearing degradation experiments, the public XJTU-SY dataset, and the PHM 2012 Challenge dataset shows that the proposed framework significantly enhances prediction stability and reliability.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"271 ","pages":"Article 120991"},"PeriodicalIF":5.6,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387604","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":"Dual-tube electrical sensing zone fusion and dual-Weibull inversion for wide-range particle size measurement of Bayer-process slurry","authors":"Qi Feng ,&nbsp;Hongjian Cao ,&nbsp;Jia Zhao ,&nbsp;Youjian Su ,&nbsp;Jingjing Qiu ,&nbsp;Xiaodong Wang","doi":"10.1016/j.measurement.2026.120986","DOIUrl":"10.1016/j.measurement.2026.120986","url":null,"abstract":"<div><div>Accurate online monitoring of Bayer-process bauxite slurry particle-size distribution underpins process control and optimisation in alumina refineries. However, conventional instruments—including the standard Bayer-process sieving method—provide only offline, narrow-range information and therefore cannot support continuous operation. To address this limitation, we develop a wide-range particle-size distribution reconstruction method that integrates a dual-tube Coulter-Principle sensor with a stitching—fusion inversion strategy. A dual-channel electrical sensing zone system with two partially overlapping apertures provides direct particle-size measurements over approximately 50–640 µm, while a fusion-based inversion model reconstructs the PSD over an inferred range of 1–1000 µm; results below 50 µm are not directly validated by ESZ in this study. The two resulting spectra are combined by an adaptive stitching algorithm that determines a stable overlap interval from local slope characteristics, yielding a smooth and physically consistent composite distribution. Coarse-end reconstruction is further enhanced using Boltzmann weighting and a dual-Weibull inversion model. Across three industrial Bayer slurries, the fused ESZ indices F₁₂₅, F₂₀₀ and F₈₀₀ agree with the Bayer-process sieving method within ±3.3 percentage points. Within the validated operating window (≥50 µm), the method provides stable and reliable particle-size distribution information suitable for online monitoring, blending control and process optimisation in alumina production.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"271 ","pages":"Article 120986"},"PeriodicalIF":5.6,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387613","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 Data-Driven framework for precise geometric measurement of tunnel structures using 3D point clouds and Bayesian optimization","authors":"Fei Meng,&nbsp;Shifan Qiao,&nbsp;Daolong Chen","doi":"10.1016/j.measurement.2026.120931","DOIUrl":"10.1016/j.measurement.2026.120931","url":null,"abstract":"<div><div>The geometric state assessment of complex engineering structures from 3D point clouds is challenged by the insufficient accuracy and poor reproducibility of conventional techniques, which are highly sensitive to processing parameters. To overcome these limitations, a novel data-driven measurement framework is proposed. The framework enhances a conventional dual-plane projection technique by integrating a sliding window mechanism for refined local analysis. A Bayesian optimization algorithm is subsequently introduced to automate the selection of the sliding window’s critical parameters, thereby eliminating operator subjectivity and ensuring measurement optimality. The entire automated workflow is implemented within a high-performance computational architecture that synergizes MATLAB and C++. Validation through an engineering case study of a tunnel structure demonstrated that the Bayesian optimization converged to an optimal parameter set, minimizing the objective function to 1.4201. The geometric parameters extracted using this optimized method, such as an average cross-sectional ovality of <span><math><mrow><mn>9.65</mn><mo>×</mo><msup><mn>10</mn><mrow><mo>-</mo><mn>5</mn></mrow></msup></mrow></math></span>, exhibited significantly higher sensitivity to local geometric deviations compared to conventional global methods (<span><math><mrow><mn>1.93</mn><mo>×</mo><msup><mn>10</mn><mrow><mo>-</mo><mn>5</mn></mrow></msup></mrow></math></span>). The proposed framework provides a robust and automated solution for 3D geometric measurement, fundamentally improving the accuracy, reliability, and reproducibility of the measurement process for complex structures by systematically addressing parameter uncertainty.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"271 ","pages":"Article 120931"},"PeriodicalIF":5.6,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387617","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":"Measurement of particle parameters of condensed phase products in solid rocket motor plume under the rarefied atmospheric environment","authors":"Feng Yang ,&nbsp;Xueting Ran ,&nbsp;Yu Zhang ,&nbsp;Li Ping ,&nbsp;Chaoqi Xu ,&nbsp;Bin Yang","doi":"10.1016/j.measurement.2026.120926","DOIUrl":"10.1016/j.measurement.2026.120926","url":null,"abstract":"<div><div>To realize particle parameters measurements of condensed phase products in a solid rocket motor (SRM) plume under the rarefied atmospheric environment, a laser diffraction-based particle parameter measurement system was established based on the principle of laser diffraction particle sizing. Static particle size measurements were validated by using standard particles with diameters of 0.8 μm, 1.5 μm, 20 μm, 100 μm and 240 μm. The results indicate that the maximum relative deviation of particle size measurement is 6.7%. On this basis, the measurement system was applied to measure particle parameters of condensed phase products in the SRM plume under the normal and rarefied atmospheric environments. The results show that the volume-weighted mean particle size (D₄₃) of condensed phase products in SRM plume under the rarefied atmospheric environment is approximately 10 μm, which is much smaller than the normal atmospheric environment. The light transmittance of SRM plume under the rarefied atmospheric environment during stable working stage ranges from 96.0% to 98.5%, while that under the normal atmospheric environment is below 30.0%. Furthermore, when distance from the nozzle exit increases, the particle size distribution broadens firstly and then narrows. The above measurement results of particle parameters of condensed phase products in the SRM plume can provide direct data support for the evaluation of plume characteristic signals, plume simulation modeling, and optimization design of SRM.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"271 ","pages":"Article 120926"},"PeriodicalIF":5.6,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387655","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":"MTKS-Mamba: A multi-task knowledge sharing network with Mambaformer for joint battery state estimation","authors":"Ruopeng Wu,&nbsp;Ying Shi,&nbsp;Changjun Xie","doi":"10.1016/j.measurement.2026.120922","DOIUrl":"10.1016/j.measurement.2026.120922","url":null,"abstract":"<div><div>Accurate estimation of state of charge (SOC) and state of health (SOH) for lithium-ion batteries is crucial for electric vehicles. Existing studies typically focus on estimating individual states, with little consideration given to their inherent relationships. In this paper, we propose a joint battery state estimation framework, called MTKS-Mamba, based on a multi-task knowledge sharing network (MTKSN) and a hybrid deep learning architecture Mambaformer. First, through the cycle charging and discharging aging experiment of lithium-ion batteries, the key features are extracted for estimating SOC and SOH. Next, the MTKSN explores inherent relationships between SOC and SOH estimation tasks, sharing knowledge across layers through similar convolutional kernels. Finally, Mambaformer is introduced to capture long-short range dependencies in time series for learning battery aging and charging behaviors. The experimental results show that the proposed method can precisely estimate the SOC and SOH of lithium-ion batteries, with the RMSE and MAE of SOC estimation not exceeding 1.18% and 1.02%, respectively, and the RMSE and MAE of SOH estimation not exceeding 2.44% and 1.78%, respectively, outperforming existing methods in terms of accuracy and robustness.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"271 ","pages":"Article 120922"},"PeriodicalIF":5.6,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147387656","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}