Measurement最新文献

{"title":"An electrolyte-gate vertical TFET pH sensor design and simulation analysis","authors":"Dena N. Qasim Agha","doi":"10.1016/j.measurement.2025.117790","DOIUrl":"10.1016/j.measurement.2025.117790","url":null,"abstract":"<div><div>This article examined a vertical Tunnel Field Effect transistor (TFET) based pH sensor with open and closed cavities with heterojunction Gallium Antimonide/Silicon (GaSb/Si) source. The addition of GaSb as a source increases the tunneling efficiency, resulting in a high tunneling current for the TFET pH sensor. The compound material (GaSb) increases the carrier current density, which leads to an increase in the sensitivity of the pH sensor. The ATLAS simulator used the density of states of conduction band (Nc) and valance band (Nv) to evaluate the change of pH in bio electrolyte solution. The density of states for an open and closed cavity has been evaluated with pH modelling of electrolyte solution. The sensitivity of the closed cavity and open cavity configuration is determined along with other electrical parameters like electric field, energy band bending, drain current, transconductance and sensitivities. Both the open and closed cavity configurations showed variation in the electrical behavior. The sensitivity is approximately three times the Nernst limit (59 mV/pH) for the closed (open) cavity voltage sensitivity of 228 mV/pH (287 mV/pH).</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117790"},"PeriodicalIF":5.2,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143934700","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 Faraday rotation effect in SERF Co-Magnetometers using Multi-Reflection cavities","authors":"Jie Zheng ,&nbsp;Xiaolin Gong ,&nbsp;Jie Zhang ,&nbsp;Xing Heng ,&nbsp;Kai Wei","doi":"10.1016/j.measurement.2025.117784","DOIUrl":"10.1016/j.measurement.2025.117784","url":null,"abstract":"<div><div>Enhancing the interaction strength between light and atoms amplifies the Faraday rotation effect, thereby improving the measurement sensitivity of optical rotation detection. This work integrates a multi-reflection cavity into the vapor cell of the SERF co-magnetometer for the first time, increasing the interaction strength between light and atoms. However, the multi-reflection cavity causes the issue of biaxial coupling of the output signal. Additionally, the high operating temperature and high-atomic-density conditions of the SERF co-magnetometer result in complex cavity reflection modes, necessitating an accurate assessment of the completeness of the reflection modes within the cavity. To address the above issues, we first establish a response model that accounts for light propagation in multiple directions, clarifying the impact of the sensitive-axis component on the output signal and improving the system’s measurement accuracy. Subsequently, we propose the reflection mode integrity validation method, which ensures the stable and effective operation of the multi-reflection cavity in the SERF co-magnetometer. Experimental results show that the Faraday rotation effect is enhanced by a factor of 13.6 compared to single-pass, which closely matches the designed 14 reflections, thereby verifying the accuracy of the response model and the reflection count measurement. This paper offers a new approach to enhancing the sensitivity of SERF co-magnetometers and offers guidance for the integration of optical cavities into such systems.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117784"},"PeriodicalIF":5.2,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143934703","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 loosely coupled serial digital image correlation method based on deep learning","authors":"Mingchi Feng,&nbsp;Xuehai Yuan,&nbsp;Hong Xiao,&nbsp;Nanyu Mou,&nbsp;Shuai Huang","doi":"10.1016/j.measurement.2025.117783","DOIUrl":"10.1016/j.measurement.2025.117783","url":null,"abstract":"<div><div>Digital image correlation (DIC) is a non-contact optical measurement method of displacement field, which has been widely used in various fields. Traditional DIC method needs to manually complete the tedious DIC settings such as speckle region selection and subset setting to cope with the background. In order to reduce tedious DIC settings, realize real-time online measurement, and handle various measurement objects with backgrounds, automatic selection of the speckle region is required. A loosely coupled serial measurement network SCorrNet is proposed to automatically segment speckle regions and measure its displacement fields, so as to eliminate the influence of background. With segmented speckle region as the global feature and constraint, the displacement computation is focused on the speckle region using the attention mechanism. To further improve the measurement accuracy and practicability, a diverse dataset with speckle images, background and large deformation is proposed. Finally, the proposed method is compared with traditional and learning-based DIC methods on self-built and public datasets, and validated in two practical experiments. The experimental results show that SCorrNet has high accuracy and speckle segmentation capability to reduce the influence of dynamic background. Therefore, our method has high practical value.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117783"},"PeriodicalIF":5.2,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947089","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":"Modulation crosstalk effect analysis on single-beam SERF atomic magnetic gradiometer","authors":"Tianpeng Chen,&nbsp;Zhiqiang Zheng,&nbsp;Jialong Zhang,&nbsp;Zhizhou Chen,&nbsp;Chen Wei,&nbsp;Zhonghua Ou,&nbsp;Huimin Yue,&nbsp;Yong Liu","doi":"10.1016/j.measurement.2025.117782","DOIUrl":"10.1016/j.measurement.2025.117782","url":null,"abstract":"<div><div>Gradiometers can achieve higher sensitivity, which benefits from their excellent ability to suppress the common mode noise. However, the capability of the dual-modulation gradiometer will be affected by the crosstalk between two pairs of magnetic modulation coils. In this paper, we first establish the crosstalk model for the dual-modulation gradiometer, which reveals both magnetic field variations and magnetic field gradients introduced by the crosstalk in the gradiometer system. Based on the crosstalk coefficient in the proposed model, we can calibrate the modulating magnetic field to maximize the performance of the gradiometer. The experiments indicate that the measured crosstalk coefficients are consistent well with the theory model, and the crosstalk-model-based calibration method can optimize the gradiometer performance. As a result, the calibrated sensitivity of the dual-modulation gradiometer is <span><math><mrow><mrow><mtext>15 fT/</mtext></mrow><msqrt><mrow><mtext>Hz</mtext></mrow></msqrt></mrow></math></span>, which is better than the uncalibrated sensitivity of <span><math><mrow><mrow><mtext>22 fT/</mtext></mrow><msqrt><mrow><mtext>Hz</mtext></mrow></msqrt></mrow></math></span> and is a little worse than the single-modulation gradiometer of <span><math><mrow><mrow><mtext>10 fT/</mtext></mrow><msqrt><mrow><mtext>Hz</mtext></mrow></msqrt></mrow></math></span>. By suppressing the effects of crosstalk, this dual-modulation design of the gradiometer configuration can be used to construct a miniaturized weak magnetic sensor, which is expected to be used for the measurement of fetal magnetocardiography (fMCG).</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117782"},"PeriodicalIF":5.2,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143929326","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 residual stresses in slender support plates in aeroengine inlet case based on the sampling Moiré method","authors":"Qi Qi ,&nbsp;Qinghua Wang ,&nbsp;Tong Ding ,&nbsp;Xiaojun Yan","doi":"10.1016/j.measurement.2025.117781","DOIUrl":"10.1016/j.measurement.2025.117781","url":null,"abstract":"<div><div>This paper proposes a residual stress testing method for slender support plates based on 2D moiré phase analysis, which can non-destructively detect the residual strain field generated on the surface of a specimen. A model of the aeroengine inlet case is used as the experimental object. By fabricating ±45° gratings on the support plate, the issue that traditional gratings cannot be used for deformation calculation in the width direction of the slender support plate was resolved. In the experiments, grating images of the support plate surface under different installation states were recorded, and the Moiré phase difference and displacement distributions in the <em>x</em> and <em>y</em> directions in the Cartesian coordinate system were calculated. A local phase unwrapping algorithm was used to analyse the normal and shear strain distributions on the surface of the support plate under different installation states. Based on the material’s elastic properties, the normal and shear residual stress distributions on the surface of the support plate were also calculated. The experimental results show that after the installation of the plate with actual dimensions larger than the design, the measured plate exhibits tensile residual stress in the radial direction, and the circumferential residual stress is tensile on the outer ring side, while it undergoes a reversal from positive to negative near the inner ring. Additionally, based on the analysis of the displacement distribution, it was found that the support plate underwent bending after the installation of the larger-sized support plate.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117781"},"PeriodicalIF":5.2,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143935445","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":"Prediction of cast iron guide roller wear from multivariate data analysis using supervised machine learning: A case study with production process of construction steel bars","authors":"Abdessamad Harrandou,&nbsp;Otman El Baji,&nbsp;Nabil Ben Said Amrani,&nbsp;Mohammed Reda Britel","doi":"10.1016/j.measurement.2025.117758","DOIUrl":"10.1016/j.measurement.2025.117758","url":null,"abstract":"<div><div>Most industries aim to replace traditional maintenance methods with more sophisticated, data-driven approaches. By incorporating the Industrial Internet of Things (IIoT), maintenance processes become even more efficient, providing predictive insights that help prevent downtime, streamline operations, extend asset lifespan, and optimize maintenance scheduling. Moving from traditional preventive maintenance to a more advanced, data-driven predictive maintenance (PdM) approach, this study investigates the application of machine learning (ML) to predict different sources of wear of cast iron guide rollers used in steel bar production. Leveraging historical data on guide roller replacements from the beginning of 2021 until the end of 2023, several operational parameters were analyzed, including vibration, overload, speed changes, product diameter and others. The problem was treated with two approaches. A linear approach taking the weight of the billets transformed into the final product as an indication of the remaining useful life (RUL) of the guide rollers before a critical level of wear occurs, and a discrete approach by subdividing the weight produced into five categories. For this reason, various ML algorithms, including linear regression (LR), support vector machines (SVM), random forest (RF), logistic regression (LogR), naive bayes (NB), decision tree (DT), and k-nearest neighbor (kNN), were applied to this dataset. The study identifies the primary causes of guide roller wear such as vibration, overload, and speed changes which lead to unplanned downtime, reduced product quality, and increased maintenance costs in industrial settings. It proposes predictive and condition-based solutions aligned with Maintenance 4.0 principles. A thorough comparison of these models was conducted to determine the most suitable algorithm for predicting roller degradation. The models were assessed based on the Mean Squared Error (MSE) and especially on the Root Mean Squared Error (RMSE) for the linear method. While for the multiclass classification method, performances were evaluated using accuracy, precision, F1 score, and recall. Model evaluation revealed the following finding: selecting relevant features from the dataset significantly improved performance for both the linear and discrete methods. The linear method achieved a prediction accuracy of approximately 94 %, while for the multiclass classification method, accuracy, precision, and F1 score reached 99.9 %.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117758"},"PeriodicalIF":5.2,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143921682","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":"HFNet: High-precision robotic grasp detection in unstructured environments using hierarchical RGB-D feature fusion and fine-grained pose alignment","authors":"Ling Tong ,&nbsp;Kun Qian","doi":"10.1016/j.measurement.2025.117775","DOIUrl":"10.1016/j.measurement.2025.117775","url":null,"abstract":"<div><div>The ability of robots to accurately grasp objects in unstructured environments is critical for advancing robotic automation. Current grasp detection methods overlook the distinct semantic and spatial attributes across RGB-D feature layers in such scenarios. Additionally, using Intersection over Union (IoU) loss for pose alignment fails to adequately address variations in grasp angles and dimensions. To resolve these limitations, we propose HFNet, a novel grasp detection network integrating hierarchical RGB-D feature fusion and fine-grained pose alignment strategies to optimize grasp configurations, thereby enhancing robotic applicability in real-world unstructured environments. Specifically, we design: (1) a Relation-aware Cross-modal Feature Fusion (RCFF) module to capture mid-level features (object shapes, edges, textures); (2) a High-level Cross-modal Feature Fusion (HCFF) module to strengthen global shape and semantic relationships. A new fine-grained pose alignment loss further improves measurement precision while reducing low-quality grasps. HFNet achieves state-of-the-art accuracy on benchmark datasets (Cornell, Jacquard) and challenging datasets (CBRGD, OCID_grasp, WISDOM), with a 96.67% success rate in physical robotic experiments. The source code and experiment video are available at: <span><span><em>https://github.com/meiguiz/HFNet</em></span><svg><path></path></svg></span>.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117775"},"PeriodicalIF":5.2,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947141","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":"Anomaly detection of high-speed train braking system based on wireless sensors network","authors":"Nicola Debattisti ,&nbsp;Federico Zanelli ,&nbsp;Nicola Giulietti ,&nbsp;Marco Mauri ,&nbsp;Francesco Castelli-Dezza","doi":"10.1016/j.measurement.2025.117774","DOIUrl":"10.1016/j.measurement.2025.117774","url":null,"abstract":"<div><div>To date, high-speed trains are equipped with a dense network of sensors, which allows for monitoring many operational parameters of the vehicle. The effort made to develop such monitoring and diagnostic systems aims to continuously increase the level of safety, thus ensuring timely intervention in case of anomaly of one or more components. However, some features are still not directly monitored on board but are tracked by systems installed on the infrastructure. One of these features is represented by the detection of brakes temperature, which is significant for condition monitoring and for guaranteeing that the vehicle travels safely. In this work, a custom wireless sensors system was developed to be installed on in-service trains, with embedded temperature sensors for detecting anomalies in the brake system. These sensors are energy-independent and thus completely stand-alone. The data collected by each sensor is then transmitted via Bluetooth Low Energy (BLE) to a Central Control Unit, in which an anomaly detection algorithm has been implemented. This algorithm employs a data fusion strategy, relying on different types of measurements (temperature, acceleration, pressure, etc.) and merging the data of all sensor nodes, to provide real-time alarm notification in case of malfunctioning of the brakes.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117774"},"PeriodicalIF":5.2,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143921984","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":"Fractal and multifractal characterization of wear surface dynamics for tribopairs in bi-directional seawater pump","authors":"Songlin Nie,&nbsp;Li Shi,&nbsp;Hao He,&nbsp;Hui Ji,&nbsp;Fanglong Yin,&nbsp;Zhonghai Ma","doi":"10.1016/j.measurement.2025.117763","DOIUrl":"10.1016/j.measurement.2025.117763","url":null,"abstract":"<div><div>Traditional roughness parameters are inadequate for characterizing the multi-scale wear surface features for tribopairs in bidirectional seawater pump. This study employs fractal theory, specifically using the box-counting method to calculate the fractal dimension and multifractal spectrum, to investigate the dynamic evolution of carbon fiber polyether ether ketone (CF-PEEK) / 17-4PH stainless steel tribopair under bidirectional sliding conditions. In line with the actual operating conditions of the bidirectional seawater pump, ball-on-disk wear tests were conducted at a load of 20 N, a sliding speed of 0.4 m/s, and commutation frequency (<em>C</em> = 0 ∼ 80). The sensitivity of the fractal dimension was found to be 5.6 times higher than that of traditional surface roughness (<em>R_a</em>) at <em>C</em> = 80, indicating its potential as a high-resolution tool for dynamic monitoring. The multifractal spectrum analysis reveals that lower commutation frequencies (<em>C</em> ≤ 20) result in increased surface fluctuations, whereas higher commutation frequencies stabilize the lubrication layer. Fractal theory effectively captures the dynamic wear surface characteristics, while the multifractal spectrum provides a foundation for monitoring lubrication states and optimizing maintenance strategies for the tribopairs in bi-directional seawater pump.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117763"},"PeriodicalIF":5.2,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924073","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":"Hybrid model of deep learning and contact theory for predicting distributed contact force in space debris de-tumbling","authors":"Chaoqun Qi ,&nbsp;Siqi Peng ,&nbsp;Huibo Zhang ,&nbsp;Wenbo Li ,&nbsp;Shijie Dai ,&nbsp;Min Luo","doi":"10.1016/j.measurement.2025.117767","DOIUrl":"10.1016/j.measurement.2025.117767","url":null,"abstract":"<div><div>Flexible contact-based de-tumbling serves as a critical prerequisite for space debris removal, requiring precise control of distributed contact force to dissipate angular momentum. However, space debris is non-cooperative targets with no accessible interaction information, in which unknown contact forces may induce uncertain dynamic behaviors, posing significant risks to the safe in-orbit execution of debris removal. To address these challenges, this paper proposes a hybrid model combining deep learning with contact theory (CT) that enables accurate distributed force prediction without surface sensors. The hybrid model employs a Deep Long Short-Term Memory Network (DLSTM) to map end-effector concentrated forces to the Pressure Matrix of Finite Contact Elements (PMFCE) at the contact interface. The standard estimation equations for the characteristic parameters of the distributed contact force were derived from the PMFCE using CT, and solved iteratively via the exponentially weighted least squares (EWRLS) method. Additionally, we proposed a full collision cycle measurement method for ground-equivalent contact force, and developed a corresponding experimental setup to support the model training and validation. Experimental results demonstrated the proposed method’s superior predictive performance in both normal and oblique impact scenarios. Furthermore, statistical analysis using correlation coefficients and probability density functions confirmed the method’s superior accuracy and robustness. The results showed that the confidence level for the relative error within the ±10 % interval exceeded 98 %. This approach enables precise distributed force prediction in various contact-based robotic systems, ensuring safety during orbital debris de-tumbling and capture operations.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"253 ","pages":"Article 117767"},"PeriodicalIF":5.2,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143922928","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}