Measurement Science and Technology最新文献_第6页

A normal tracking differential confocal measurement method for multiple geometric parameters of hemispherical shell resonator with a common reference 利用共同基准对半球形壳体谐振器的多个几何参数进行法线跟踪差分共焦测量的方法

IF 2.4 3区工程技术

Measurement Science and Technology Pub Date : 2024-01-03 DOI: 10.1088/1361-6501/ad1a85

Yuhan Liu, Xiaocheng Zhang, Yuan Fu, Yun Wang, Zhuxian Yao, Weiqian Zhao

引用次数: 0

A Bayesian CNN-based Fusion Framework of Sensor Fault Diagnosis 基于贝叶斯 CNN 的传感器故障诊断融合框架

IF 2.4 3区工程技术

Measurement Science and Technology Pub Date : 2024-01-03 DOI: 10.1088/1361-6501/ad1a86

Beiyan He, Chunli Zhu, Zhongxiang Li, Chun Hu, Dezhi Zheng

{"title":"A Bayesian CNN-based Fusion Framework of Sensor Fault Diagnosis","authors":"Beiyan He, Chunli Zhu, Zhongxiang Li, Chun Hu, Dezhi Zheng","doi":"10.1088/1361-6501/ad1a86","DOIUrl":"https://doi.org/10.1088/1361-6501/ad1a86","url":null,"abstract":"\u0000 Sensors equipped on the high-speed train provide large amounts of data which contributes to its state monitoring. However, it is challenging to distinguish whether the fault originates from the mechanical component or the sensors themselves. The main difficulties lie in the biased amount of normal and fault data as well as the deficiency of multi-source data’s inherent correlation. In this paper, we propose a Bayesian Convolutional neural networks (CNN)-based fusion framework to enhance the ability to identify sensor errors. The framework utilizes wavelet time-frequency maps to extract abnormal features, employs a Bayesian CNN to obtain spatial features from a single sensor, integrates multi-source features via Bidirectional Long Short-Term Memory Network (Bi-LSTM) and enhances the acquired spatial and temporal features using an attention mechanism. The enhanced information finally generated leads to precise identification of the sensor faults. The proposed feature-level fusion framework and the associated attention mechanism facilitate discovering the inherent correlation and filtering of irrelevant information. Results indicate that our proposed method achieves 95.4% in terms of accuracy, which outperforms methods relying on feature extraction with single-source sensors by 7.8%.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"97 23","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139387927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A receptive field transfer strategy via layer-aligned distillation learning for fault signal denoising 通过层对齐蒸馏学习实现故障信号去噪的感受野转移策略

IF 2.4 3区工程技术

Measurement Science and Technology Pub Date : 2023-12-29 DOI: 10.1088/1361-6501/ad19bf

Huaxiang Pu, Ke Zhang, Haifeng Li

引用次数: 0

Transfer Learning for Bearing Fault Diagnosis: Adaptive Batch Normalization and Combined Optimization method 轴承故障诊断的迁移学习：自适应批量归一化和组合优化方法

IF 2.4 3区工程技术

Measurement Science and Technology Pub Date : 2023-12-29 DOI: 10.1088/1361-6501/ad19c2

Xueyi Li, Kaiyu Su, Daiyou Li, Qiushi He, Zhijie Xie, Xiangwei Kong

引用次数: 0

A meticulous covariance adaptive Kalman filter for satellite attitude estimation 用于卫星姿态估计的精细协方差自适应卡尔曼滤波器

IF 2.4 3区工程技术

Measurement Science and Technology Pub Date : 2023-12-29 DOI: 10.1088/1361-6501/ad19c1

Yang Xiao, Tao Jiang, Guo-Wei Fan, Liu Zhang, Yu Gao, Le Zhang

{"title":"A meticulous covariance adaptive Kalman filter for satellite attitude estimation","authors":"Yang Xiao, Tao Jiang, Guo-Wei Fan, Liu Zhang, Yu Gao, Le Zhang","doi":"10.1088/1361-6501/ad19c1","DOIUrl":"https://doi.org/10.1088/1361-6501/ad19c1","url":null,"abstract":"Aiming at the problems of model errors, non-Gaussian noise and measurement anomaly in the spacecraft attitude estimation system, this article proposes an improved adaptive filtering method based on covariance matching, which solves the problems of simultaneous dynamics model error and measurement model error in the attitude estimation system, and at the same time, effectively reduces the effects of non-Gaussian noise and large outlier situations occurring in the vector measurement sensor. Firstly, an adaptive filtering algorithm based on the innovation sequence estimation covariance is investigated under the framework of multiplicative extended Kalman filtering (MEKF), which is used to correct process noise covariance, then the Sage-Husa adaptive Kalman filtering (SHAKF) method is combined to correct the measurement noise covariance, and finally the meticulous covariance adaptive multiplicative extended Kalman filter (MCA-MEKF) is designed. the proposed algorithm uses both innovation and SHAKF methods to correct the two covariance matrices simultaneously. Several attitude estimation simulation scenarios are set up to simulate the proposed algorithm in the presence of model errors, non-Gaussian noise, and large outlier. The simulation results demonstrate that the proposed algorithm outperforms the conventional algorithms in terms of estimation accuracy and robustness.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":" 33","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139143988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Attention mechanism guided sparse filtering for mechanical intelligent fault diagnosis under variable speed condition 用于变速条件下机械智能故障诊断的注意机制引导稀疏滤波技术

IF 2.4 3区工程技术

Measurement Science and Technology Pub Date : 2023-12-28 DOI: 10.1088/1361-6501/ad197a

Rui Han, Jinrui Wang, Yanbin Wan, Jihua Bao, Xue Jiang, Zongzhen Zhang, Baokun Han, Shanshan Ji

{"title":"Attention mechanism guided sparse filtering for mechanical intelligent fault diagnosis under variable speed condition","authors":"Rui Han, Jinrui Wang, Yanbin Wan, Jihua Bao, Xue Jiang, Zongzhen Zhang, Baokun Han, Shanshan Ji","doi":"10.1088/1361-6501/ad197a","DOIUrl":"https://doi.org/10.1088/1361-6501/ad197a","url":null,"abstract":"Variable speed is one of the common working conditions of mechanical equipment,which poses an important challenge to equipment fault diagnosis. The current solutions have the shortcomings of low computational efficiency and large diagnostic errors. The ability of attention mechanism to automatically extract useful features has begun to attract widespread attention in the field of mechanical intelligent fault diagnosis. Combining the advantages of attention mechanism and unsupervised learning, this paper proposes a squeeze-excitation attention guided sparse filtering (SESF) method for mechanical intelligent fault diagnosis method under variable speed. Firstly, the SE attention mechanism is embedded in SF algorithm to guide model training. Then, unsupervised feature extraction is carried out on the variable speed signal samples. The training results are adaptively screened and weighted to make the model pay more attention to the region with the most classify discrimination, so as to improve the feature extraction ability of the model to obtain useful information. Finally, two sets of gear and bearing tests under variable speed condition are adopted to testify the performance of the proposed method. The experimental results show that the SESF method can overcome the influence of variable speed to achieve accurate recognition of different mechanical faults and is superior to the other methods.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"3 5","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139148744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel unmanned aerial vehicle path planning approach: Sand Cat Optimization Algorithm Incorporating Learned Behaviour 新型无人驾驶飞行器路径规划方法：包含学习行为的沙猫优化算法

IF 2.4 3区工程技术

Measurement Science and Technology Pub Date : 2023-12-28 DOI: 10.1088/1361-6501/ad1977

Kun Hu, yuanbin Mo

引用次数: 0

Research on the tension of steel cord conveyor belts based on transverse vibration modelling 基于横向振动建模的钢丝绳输送带张力研究

IF 2.4 3区工程技术

Measurement Science and Technology Pub Date : 2023-12-28 DOI: 10.1088/1361-6501/ad180d

Xiaoxia Sun, Hui Xiao, Wenjun Meng

{"title":"Research on the tension of steel cord conveyor belts based on transverse vibration modelling","authors":"Xiaoxia Sun, Hui Xiao, Wenjun Meng","doi":"10.1088/1361-6501/ad180d","DOIUrl":"https://doi.org/10.1088/1361-6501/ad180d","url":null,"abstract":"The accurate non-contact tension measurement of steel cord conveyor belt, an important load bearing medium, is critical for long distance belt conveyors. It is necessary to establish the relationship between the conveyor belt transverse vibration and the tension, in order to analyse the conveyor belt tension changes through indirect measurement of transverse vibration. The paper analyses the existing models of transverse vibration in conveyor belts, and finds that these models can hardly directly and accurately calculate the tension of the conveyor belt. Therefore, modifications are needed. Firstly, the paper establishes a dynamic model of the belt conveyor and conducts simulation analysis using RecurDyn software. This allows the authors to obtain the belt tension and transverse vibration displacement of the conveyor belt. Fast Fourier transform is employed to determine the vibration frequency, which is used to evaluate the vibration characteristics of conveyor belts under different operating conditions. Then, the paper conducts simulation analysis on the frequency and tension of the belt conveyor with different idler spacing, and performs nonlinear least squares calculation in MATLAB software to modify the coefficients of the transverse vibration model. This process involves nonlinear fitting, resulting in an improved transverse vibration model. Finally, the modified transverse vibration model is compared with the original model. The modified transverse vibration model can more accurately calculate the tension of the conveyor belt based on its vibration frequency. The validity of the modified model is verified by different types of conveyor belts.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"86 3","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139151848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AIR-CNN: A Lightweight Automatic Image Rectification CNN Used for Barrel Distortion AIR-CNN：用于处理桶形失真问题的轻量级自动图像校正 CNN

IF 2.4 3区工程技术

Measurement Science and Technology Pub Date : 2023-12-28 DOI: 10.1088/1361-6501/ad1979

Can Zhou, Can Zhou, Hongqiu Zhu, Tianhao Liu

{"title":"AIR-CNN: A Lightweight Automatic Image Rectification CNN Used for Barrel Distortion","authors":"Can Zhou, Can Zhou, Hongqiu Zhu, Tianhao Liu","doi":"10.1088/1361-6501/ad1979","DOIUrl":"https://doi.org/10.1088/1361-6501/ad1979","url":null,"abstract":"Barrel distortions often exist in images captured by wide-angle lenses, and the presence of barrel distortions reduces the label-making accuracy of algorithms and the precision rate of final target detection and semantic recognition. To reduce the interference of barrel distortions on imaging, we have proposed a lightweight image rectification network AIR-CNN for barrel distortion. The network is based on a parameter sharing (PS) convolutional neural network structure, which is trained on the distorted image dataset to predict the pixel displacement field between the distorted image and the rectified image, and finally restores the rectified image based on the predicted pixel displacement field. The experimental results show that the AIR-CNN can greatly reduce the number of network parameters through the parameter sharing mechanism and implicitly learns the texture features by asymmetric convolution (AC) kernels to obtain higher rectification accuracy at a lower computational cost, and automatically obtain the distortion parameters of the camera without special calibration methods. The AIR-CNN outperforms previous image rectification methods in both intuitive and quantitative comparisons (EPE, PSNR, NRMSE, SSIM).","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"19 4","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139152223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi visual images fusion approach for metro tunnel defects based on saliency optimization of pixel level defect image features 基于像素级缺陷图像特征显著性优化的地铁隧道缺陷多视觉图像融合方法

IF 2.4 3区工程技术

Measurement Science and Technology Pub Date : 2023-12-28 DOI: 10.1088/1361-6501/ad197d

Dongwei Qiu, Zhengkun Zhu, Xingyu Wang, Ke-liang Ding, Zhaowei Wang, Yida Shi, Wenyue Niu, Shanshan Wan

{"title":"Multi visual images fusion approach for metro tunnel defects based on saliency optimization of pixel level defect image features","authors":"Dongwei Qiu, Zhengkun Zhu, Xingyu Wang, Ke-liang Ding, Zhaowei Wang, Yida Shi, Wenyue Niu, Shanshan Wan","doi":"10.1088/1361-6501/ad197d","DOIUrl":"https://doi.org/10.1088/1361-6501/ad197d","url":null,"abstract":"The multi vision metro tunnel defect sensing system mainly consists of IRT and RGB cameras, which can automatically identify and extract small tunnel lining surface defects, greatly improving detection efficiency. However, the presence of various issues like train vibration, inconsistent lighting, fluctuations in temperature and humidity leads to the images showing inadequate uniformity in illumination, blurriness, and a decrease in the level of detail. The above issues have led to unsatisfactory fusion processing results for multiple visual images and increased missed detection rates. A multi visual images fusion approach for metro tunnel defects based on saliency optimization of pixel level defect image features is proposed. This method first takes the motion state of the train and the blurry image as constraints to eliminate dynamic blurring in the image. Secondly, Image weights are allocated based on the uniformity of visible light image illumination in the tunnel, as well as real-time temperature and humidity. Finally, image feature extraction and fusion are performed by a U-Net network that integrates channel attention mechanisms. The experimental results demonstrate that this approach improves the image pixel value variation rate by 39.7%, enhances the edge quality by 23%, and outperforms similar approach in terms of average gradient, gradient quality, and sum of difference correlation with improvements of 15.9%, 7.3%, and 26.6% respectively.","PeriodicalId":18526,"journal":{"name":"Measurement Science and Technology","volume":"102 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139149427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0