Measurement最新文献

{"title":"Optimization and prediction of mechanical properties of TPU-Based wrist hand orthosis using Bayesian and machine learning models","authors":"Kaplan Kaplan ,&nbsp;Osman Ulkir ,&nbsp;Fatma Kuncan","doi":"10.1016/j.measurement.2025.117405","DOIUrl":"10.1016/j.measurement.2025.117405","url":null,"abstract":"<div><div>This study investigates the optimization and prediction of mechanical properties for a wrist-hand orthosis fabricated using fused deposition modeling (FDM) with thermoplastic polyurethane (TPU). The study examines two critical mechanical properties—Shore D hardness, and surface roughness—that are essential for ensuring functionality and durability in medical applications. Twenty-seven different combinations of printing parameters were tested, varying layer thickness (100–200–300 μm), infill pattern (zigzag, cubic, triangles), and nozzle temperature (210–220–230 °C). The study employs artificial neural network (ANN) and bidirectional long short-term memory (BiLSTM) algorithms for predictive modeling, with bayesian optimization (BO) enhancing the BiLSTM model’s performance. Analysis of variance (ANOVA) identified layer thickness as the most influential parameter for both mechanical properties. The BiLSTM integrated with BO demonstrated superior prediction accuracy compared to conventional ANN and standalone BiLSTM models. Error metrics have been used to measure the accuracy of prediction models. These include R-squared (R2), mean absolute percentage error (MAPE), mean squared error (MSE), and root mean squared error (RMSE). The BiLSTM + BO exhibited exceptional predictive performance for Shore D hardness (R2 = 0.9965, MAPE = 0.4516 %, MSE = 0.0471, RMSE = 0.2170), greatly outperforming both ANN (R2 = 0.3554, MAPE = 6.6569 %) and standalone BiLSTM (R2 = 0.9713, MAPE = 1.1737 %). The optimized BiLSTM demonstrated superior predictive capability for surface roughness (R2 = 0.9983, MAPE = 0.6292 %, MSE = 0.0240, RMSE = 0.1551), greatly exceeding the accuracy of ANN (R2 = 0.6078, MAPE = 10.3351 %) and standalone BiLSTM (R2 = 0.9839, MAPE = 2.0010 %). Validation tests on eight independent samples further confirmed the BiLSTM + BO model’s superior performance, achieving prediction errors of 0.03–0.92 % for Shore D hardness and 0.19–1.25 % for surface roughness, significantly outperforming both ANN (0.46–13.77 % and 2.23–21.47 %) and standalone BiLSTM (0.08–2.68 % and 0.36–4.95 %) models respectively. These results highlight the effectiveness of integrating advanced machine learning (ML) techniques with BO to predict and optimize mechanical properties in additive manufacturing (AM), especially for medical device applications.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"252 ","pages":"Article 117405"},"PeriodicalIF":5.2,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738058","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":"Enhancing sensitivity and measurement range by Multi-layered Vision-Based Tactile Sensor (ML-VBTS): A parametric study and comparative benchmarking","authors":"Mohamad Halwani ,&nbsp;Islam Mohamed Zaid ,&nbsp;Mohamad Salah ,&nbsp;Hussain Sajwani ,&nbsp;Abdulla Ayyad ,&nbsp;Laith AbuAssi ,&nbsp;Yusra Abdulrahman ,&nbsp;Sajid Javed ,&nbsp;Abdelqader Abusafieh ,&nbsp;Yahya Zweiri","doi":"10.1016/j.measurement.2025.117357","DOIUrl":"10.1016/j.measurement.2025.117357","url":null,"abstract":"<div><div>Vision-Based Tactile Sensors (VBTSs) have significantly advanced robotic applications. However, they are often constrained by the inherent trade-off between sensitivity and measurement range, making the simultaneous enhancement of both parameters particularly challenging. This trade-off limits their applicability for applications demanding both subtle force detection and broad measurement capabilities. To address this challenge, we present a multi-layered VBTS (ML-VBTS) that integrates materials with different hardness levels within the tactile skin. Based on the proposed multi-layered design, we conduct a Finite Element Analysis (FEA) to optimize material properties and bridge the gap to real-world sensor performance using a Sim2Real transfer framework. Rigorous experiments on the ML-VBTS demonstrated its superior performance compared to the commercial GelSight mini, achieving approximately a 60% improvement in both sensitivity, with values of 0.9 N/px for normal forces and 0.4 N/px for shear forces, and in measurement range. This proposed sensor design not only enhances the precision and reliability of tactile feedback in advanced robotic applications but also paves the way for broader adoption of VBTS in various industries where sensitive yet broad force measurements are critical.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"252 ","pages":"Article 117357"},"PeriodicalIF":5.2,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738409","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":"Extraction of horizontally curved beam influence lines based on a unilateral step-by-step loading inversion algorithm","authors":"Weipei Zhang,&nbsp;Shujuan Li ,&nbsp;Weichao Guo,&nbsp;Shuai Wang,&nbsp;Wang Qin,&nbsp;Tuo Kang,&nbsp;Miao Zhang","doi":"10.1016/j.measurement.2025.117255","DOIUrl":"10.1016/j.measurement.2025.117255","url":null,"abstract":"<div><div>The influence line is widely used as one of the main characteristic indicators for bridge health monitoring. However, horizontally curved bridges have bending and torsion coupling, and it is difficult to extract the influence line of its lateral distribution. To address this problem, an influence line extraction method based on the unilateral step-by-step loading inversion algorithm is proposed in this paper, which obtains the unilateral wheel-induced influence line by obtaining the increment of the influence line affected only by the additional overturning moment. The influence lines during loading are extracted using Tikhonov regularization, which effectively improves the stability of the results. Using a modified analytical method, horizontally curved beams under statically indeterminate structures are analyzed to obtain the inner and outer wheel bending moment and torque influence line algorithms. A horizontally curved beam vibration and deformation test bed is constructed for step-by-step loading experiments. The results show that the strain influence line under unilateral step-by-step loading is increasing. The deviations between the theoretical influence lines of the inner and outer wheels and the actual influence lines obtained using the RMSE evaluation index are 0.0072 and 0.0047, which proves that the strain influence line extraction algorithm of the unilateral wheel is basically consistent with the trend of the theoretical influence line under the horizontally curved beam of the statically indeterminate structures. The influence line decreases as a whole with the increase of curvature of horizontally curved beams.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"252 ","pages":"Article 117255"},"PeriodicalIF":5.2,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738056","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":"Multi-dimensional force-sensing surgical tool based on one screw-mounted FBGs string","authors":"Mengwen Li ,&nbsp;Qiao Liu ,&nbsp;Penghao Lv ,&nbsp;Jianxun Zhang ,&nbsp;Yu Dai","doi":"10.1016/j.measurement.2025.117343","DOIUrl":"10.1016/j.measurement.2025.117343","url":null,"abstract":"<div><div>To solve the lack of force sensing technology in minimally invasive surgical robots, this paper proposes a novel force-sensing surgical tool (FSST) based on the fiber Bragg gratings(FBGs) string, which is designed to detect the contact force between the end-effector of the FSST and the outside environment in real time. A grating string engraved with four FBGs is designed to match the pitch of the spiral groove on the surgical tool’s shaft to form the FSST. Subsequently, the decoupling matrix is obtained through static calibration experiments to decouple the two radial forces, and the coordinate transformation relationship is further established to map the two forces to the observed CS to obtain the three-dimensional forces. In addition, the accuracy of the FSST is demonstrated by comparing the measurement results with those of commercial force sensor. Finally, we experimentally verified the repeatability of the sensor.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"252 ","pages":"Article 117343"},"PeriodicalIF":5.2,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738410","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":"Efficient structural impact localization via signal curvature energy and probabilistic error function","authors":"Xiufeng Huang,&nbsp;Tao Peng,&nbsp;Shiji Wu,&nbsp;Xuan Ming","doi":"10.1016/j.measurement.2025.117418","DOIUrl":"10.1016/j.measurement.2025.117418","url":null,"abstract":"<div><div>This study presents a novel probabilistic error function-based structural impact localization method that leverages curvature energy to extract Time of Arrival (TOA) values. By iteratively calculating cumulative and curvature energy across sensor signal time points, the first non-zero moment in the curvature energy curve is identified as the TOA. The method eliminates false signals, and using the predicted TOA, an error function encompassing the impact moment is minimized to compute the probability of impact locations within the structure. Experimental results demonstrate average localization error rates of 5.31% and 7.02% for steel plate without stiffeners, steel plate with stiffeners. The minimum localization error rate can reach 0.20%. Key advantages of the proposed method include: (a) an innovative automatic TOA extraction method based on energy curvature is proposed, eliminating the need for manual threshold setting and facilitating implementation; (b) an impact localization method based on a novel probabilistic error function enables the localization of impact sources and determination of impact occurrence time using at least three sensors; (c) elimination the need for wave velocity calculations in structures and removes dependence on preset databases or accurate wave velocity estimates; (d) applicable to both isotropic and anisotropic steel plate structures. The proposed approach demonstrates strong potential for real-time structural health monitoring and impact localization in diverse engineering applications, offering a practical and efficient alternative to conventional methods.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"252 ","pages":"Article 117418"},"PeriodicalIF":5.2,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143735169","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":"The parametric design of X-ray ptychography systems","authors":"Liyang Zhang ,&nbsp;Yu Han ,&nbsp;Xiaoqi Xi,&nbsp;Chunhui Wang,&nbsp;Lei Li,&nbsp;Mengnan Liu,&nbsp;Qi Zhong,&nbsp;Bin Yan","doi":"10.1016/j.measurement.2025.117404","DOIUrl":"10.1016/j.measurement.2025.117404","url":null,"abstract":"<div><div>X-ray ptychography improves the illumination method of coherent X-ray diffraction imaging (CDI) by shifting the local illumination area to image large samples, while simultaneously improving the convergence speed and reconstruction quality of phase recovery using the constraints imposed by the overlapping of adjacent illumination areas. To improve the imaging resolution and image quality of X-ray ptychography, system parameters such as ray source parameters, illumination probe size, sample-to-detector transmission distance, detector accuracy, etc. need to be rationalized. Rationalizing the imaging system parameters is even more important when using a laboratory light source with lower brightness and coherence or when the size of the experimental field is limited. In this study, we aim to ensure the high resolution of far-field imaging and explore optimizing the system parameter settings based on a simulation method, focusing on the transmission distance between the sample and the detector. First, we design a simulation method that can flexibly adjust the system parameters to overcome the strict limitation of the matching relationship between parameters in the traditional simulation method. Second, we compare the effects of different overlap rates and up-sampling methods on the imaging results under different transmission distances so that the system can realize high quality far-field ptychography imaging under the shortest possible transmission distance. Finally, the system parameters are adjusted to compare the imaging results under different transmission distances, and the rules for setting the transmission distance under different system parameter designs are proposed.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"252 ","pages":"Article 117404"},"PeriodicalIF":5.2,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738412","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":"Smartphone-based measurement of cardiovascular healthcare: Advances and applications","authors":"Xianzhe Chen ,&nbsp;Junxin Chen ,&nbsp;Hongzeng Xu ,&nbsp;Tongyue He ,&nbsp;Mikael Fridenfalk ,&nbsp;Zhihan Lyu","doi":"10.1016/j.measurement.2025.117347","DOIUrl":"10.1016/j.measurement.2025.117347","url":null,"abstract":"<div><div>Smartphones are now being further developed for healthcare monitoring. Owing to the ubiquity of smartphones, it lays the foundation for widespread promotion and can contribute to promoting medical equity. Relying on its portability, continuity, and realtime, it is possible to continuously monitor relevant digital biomarkers anytime, anywhere. Currently, some advanced and interesting works based on smartphones have emerged. This paper surveys the current state of the art in the fast-moving field of smartphones for measurement of cardiovascular healthcare. We systematically explore the capabilities of smartphone-embedded sensors for cardiovascular healthcare and analyze the signals acquired by smartphones. We also summarize the applications of smartphone-based cardiovascular healthcare: cardiac parameter measurement (heart rate, blood oxygen, blood pressure, and blood glucose), and cardiovascular monitoring applications (daily monitoring, healthy vascular aging detection, and disease screening). Smartphone-based disease screening currently only includes some simple cardiovascular diseases. Finally, we discuss the challenges faced in the research.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"252 ","pages":"Article 117347"},"PeriodicalIF":5.2,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726014","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":"Investigating horn power and impact of sonication on TiO2@cotton composites with machine learning and computer vision","authors":"Muhammad Tayyab Noman,&nbsp;Nesrine Amor,&nbsp;Michal Petru","doi":"10.1016/j.measurement.2025.117424","DOIUrl":"10.1016/j.measurement.2025.117424","url":null,"abstract":"<div><div>An environmentally friendly sonication method is used to fabricate TiO₂@cotton composites. The process involves using the potential of high-frequency ultrasonic waves to effectively break down the agglomerates of nanoparticles, leading to improved interaction between fabric surface and nanoparticles. Hence, an effective and accurate prediction of sonication parameters (horn power, sonication time, sonication cycle) is of paramount importance for tailoring composite design, structure, and properties. This work is the first attempt to utilise machine learning models to determine particle size, nanoparticles loaded amount on the surface of a substrate, and nanoparticles dispersion index (measure of evenness). A neural network model is implemented to interpret a non-linear complex relationship between input conditions and output results. The prediction of particle size, loaded amount, and particles dispersion is verified by comparing predicted and experimental results, for proposed model’s effectiveness. The relationship between independent and dependent variables is reliably captured. It can be revealed from the results of the proposed models that nanoparticles size, loaded amount on the substrate and nanoparticles dispersion on cotton surface are significantly dependent on sonication attributes.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"252 ","pages":"Article 117424"},"PeriodicalIF":5.2,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143735165","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":"Modeling the complex spatio-temporal dynamics of ocean wave parameters: A hybrid PINN-LSTM approach for accurate wave forecasting","authors":"Zaharaddeen Karami Lawal ,&nbsp;Hayati Yassin ,&nbsp;Daphne Teck Ching Lai ,&nbsp;Azam Che Idris","doi":"10.1016/j.measurement.2025.117383","DOIUrl":"10.1016/j.measurement.2025.117383","url":null,"abstract":"<div><div>This study introduces a hybrid model, PINN-LSTM (Physics-Informed Neural Network-Long Short-Term Memory), developed to enhance wave speed forecasting at depths of 1.5 to 11.5 m over forecast horizons of 6, 12, 24, and 48 h. The hybrid PINN-LSTM model was chosen for its unique capability to integrate the physics-based accuracy of PINNs with the temporal sequence learning strength of LSTM networks, enabling the model to capture both spatial and temporal dynamics effectively. The PINN component leverages a linear wave equation to model shallow water dynamics, while the LSTM component addresses long-term dependencies in time-series data. Comparative analyses against standalone LSTM, GRU, and PINN models, as well as methods reported in recent literature, reveal that the PINN-LSTM model achieves superior accuracy, demonstrating more than a 20% reduction in error metrics (MAE, MSE, RMSE) compared to standalone and numerical models. While attention mechanisms have been proposed for sequence modeling, our findings indicate that the original PINN-LSTM architecture performs more effectively in this context. By addressing gaps in existing approaches, this research underscores the potential of integrating physics-informed models with deep learning techniques, providing a robust solution for ocean wave spatio-temporal dynamics forecasting challenges highlighted in previous studies.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"252 ","pages":"Article 117383"},"PeriodicalIF":5.2,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A practical tactile exploration with enhanced sampling for fast shape estimation","authors":"Feng Luan ,&nbsp;Chengjin Wang ,&nbsp;Zhipeng Wang ,&nbsp;Jiguang Yue ,&nbsp;Yanmin Zhou ,&nbsp;Bin He","doi":"10.1016/j.measurement.2025.117350","DOIUrl":"10.1016/j.measurement.2025.117350","url":null,"abstract":"<div><div>Automated measurement and three-dimensional reconstruction help robots to understand complex environments. In situations of darkness or smoke, tactile perception is pivotal. Here, we propose a tactile exploration method to estimate the shape of objects with Gaussian process implicit surfaces (GPIS), especially considering the sparsity and unevenness nature of tactile data. A data enhancement method is employed to improve the data integrity of tactile exploration for the implicit surface construction, which combines the external and internal position information of the object. In addition, a practical sampling strategy is constructed to improve the reconstruction efficiency limited by the nonuniform distribution of tactile data. This strategy considers the local data sparsity, shape uncertainty, local shape curvature, and exploration path cost for systematic and comprehensive data collection. Simulation and experiment results show that our method improves the model accuracy by 35.03% in the Hausdorff distance with the same sampling steps compared to other methods.</div><div>© 2017 Published by Elsevier.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"252 ","pages":"Article 117350"},"PeriodicalIF":5.2,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738413","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}