Measurement Science and Technology最新文献_第7页

CMDS-SLAM: Real-Time Eﬃcient Centralized Multi-Robot Dense Surfel SLAM CMDS-SLAM：实时、高效的集中式多机器人密集曲面 SLAM

Measurement Science and Technology Pub Date : 2024-07-18 DOI: 10.1088/1361-6501/ad64fa

cl z, Zhao Feng, Xiaohui Xiao

引用次数: 0

Surface defect detection for intricate pattern fabrics based on deep learning 基于深度学习的复杂图案织物表面缺陷检测

Measurement Science and Technology Pub Date : 2024-07-18 DOI: 10.1088/1361-6501/ad64f9

Xuerui Wang, Yongjian Zhu, Hongzhan Liu

{"title":"Surface defect detection for intricate pattern fabrics based on deep learning","authors":"Xuerui Wang, Yongjian Zhu, Hongzhan Liu","doi":"10.1088/1361-6501/ad64f9","DOIUrl":"https://doi.org/10.1088/1361-6501/ad64f9","url":null,"abstract":"\u0000 To tackle the challenges in the current detection of patterned fabric defects, such as unbalanced and limited data volume, incomplete extraction of defect features by the network, aliasing effect in feature fusion by the pyramid network, and low accuracy in identifying small targets, this paper proposes a novel single-stage network named ASC-YOLO. Firstly, the CoT-CSP module is introduced into the Backbone network of the YOLOv5s to model the global contextual relationships of defective features. This module compensates for the limitations of the original Cross-Stage Partial Network, which can only extract local feature information. It effectively enhances the comprehensive extraction of various irregular defect features in fabrics and reduces redundant interactions with texture background noise. Subsequently, three types of AttentionC3 modules are proposed and integrated into the Neck enables the model to focus on valuable details related to defect features through weight allocation, significantly enhancing the capability to identify small defects. Finally, an adaptive spatial feature fusion network is designed to optimize the pyramid network by redistributing weights across different feature layers for efficient utilization of multi-level feature information. Additionally, a random erasing approach is proposed to individually enhance the defect images of specific types with a limited number and adjust the corresponding labels simultaneously. This process aims to improve the robustness of the ASC-YOLO network against data noise. Experimental results demonstrate that ASC-YOLO achieves 95.8% accuracy, with mAP@0.5 reaching 83.1%, and significantly reduces frames per second(FPS) from 769 to 159. Meanwhile, the experiments also verify its superiority over other fabric detection methods and its ability to effectively improve the accuracy of fabric defect detection.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":" 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141824778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transfer learning-based channel attention enhancement network combined with Gramian angular domain field for fault diagnosis 基于迁移学习的信道注意力增强网络与格拉米安角域场相结合用于故障诊断

Measurement Science and Technology Pub Date : 2024-07-18 DOI: 10.1088/1361-6501/ad6178

Dongxiao Hou, Jintao Mu, Bo Zhang, Jiahui Chen, Peiming Shi, Shuang Yan

{"title":"Transfer learning-based channel attention enhancement network combined with Gramian angular domain field for fault diagnosis","authors":"Dongxiao Hou, Jintao Mu, Bo Zhang, Jiahui Chen, Peiming Shi, Shuang Yan","doi":"10.1088/1361-6501/ad6178","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6178","url":null,"abstract":"\u0000 Convolutional neural networks are increasingly used in the field of fault diagnosis, in order to give full play to the performance of the network within a certain number of model layers. While ensuring a high diagnostic accuracy, with strong generalization performance. We proposed a method that is simple, but effective. In this paper, we design a network structure for channel attention enhancement based on transfer learning (TL). The low-level is combined with TL to extract generic features of the target domain, and the high-level use a more refined channel attention module to extract and filter the abstract features of the current task object. The structure can fully exploit the fault information without increasing the network depth. Combined with Gramian angular difference field (GADF) to encode the vibration signal into 2D images as the input of the training model for fault diagnosis of rolling bearings. Source and target domains in TL uniformly use GADF encoded maps, effectively reducing the need for labeled samples. In order to validate the effectiveness of the method proposed in this paper, experiments were conducted using two publicly available bearing fault datasets and one laboratory-collected data, respectively. The results show that the proposed method is suitable for fault diagnosis of bearings in complex operating conditions and is highly generalizable.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":" 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141825180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessment of the accuracy and reliability of clinical thermometers for body temperature measurements at the hospital: A laboratory study 评估临床体温计在医院测量体温的准确性和可靠性：实验室研究

Measurement Science and Technology Pub Date : 2024-07-18 DOI: 10.1088/1361-6501/ad64f7

Nikorn Shinsuphan, Aphinan Phanthi, Theera Leeudomwong, T. Sanponpute

{"title":"Assessment of the accuracy and reliability of clinical thermometers for body temperature measurements at the hospital: A laboratory study","authors":"Nikorn Shinsuphan, Aphinan Phanthi, Theera Leeudomwong, T. Sanponpute","doi":"10.1088/1361-6501/ad64f7","DOIUrl":"https://doi.org/10.1088/1361-6501/ad64f7","url":null,"abstract":"\u0000 This study aims to assess the accuracy and reliability of two different types of thermometers: contact thermometers and non-contact thermometers at Maharaj Nakorn Chiang Mai Hospital. The comparison method was carried out in a hospital laboratory setting and followed a specific calibration procedure. The mean readings, errors, and measurement uncertainties were reported and categorized according to the manufacturer's labeling models. The maximum permissible errors (MPE) were defined by international standards and clinical acceptances for contact and non-contact thermometers, respectively. The results showed that thermometers of temperature probes (PTs) provided the highest level of accuracy. When compared to a reference standard thermometer (STD), the mean errors were only 0.04 ºC at the calibration point of 37.0 ºC. For digital contact thermometers (CTs), the mean error at the calibration points of 37.0 ºC was 0.24 ºC. Most CT models exhibited high accuracy and reliability. However, the forehead (IRFTs) and ear (IRETs) readings significantly differed from the STD, with over half of all units not meeting the ISO 80601-2-56/ASTM E1965-98 standard requirements. These results suggest that CTs and PTs are highly accurate and reliable devices for measuring body temperature. However, both IRFTs and IRETs could be useful in certain situations, such as screening many people in a short amount of time, but their accuracy should be interpreted with caution and confirmed using a more precise method if necessary.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":" 35","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141827901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ERT Image Reconstruction using marker region segmentation method 使用标记区域分割法重建 ERT 图像

Measurement Science and Technology Pub Date : 2024-07-17 DOI: 10.1088/1361-6501/ad6472

Bo Li, Daoye Yang

引用次数: 0

Online LiDAR-Camera Extrinsic Parameters Self-checking and Recalibration 在线激光雷达-相机外在参数自检和重新校准

Measurement Science and Technology Pub Date : 2024-07-17 DOI: 10.1088/1361-6501/ad6469

Pengjin Wei, Guohang Yan, Xin You, Kun Fang, Tao Ma, Wei Liu, Jie Yang

{"title":"Online LiDAR-Camera Extrinsic Parameters Self-checking and Recalibration","authors":"Pengjin Wei, Guohang Yan, Xin You, Kun Fang, Tao Ma, Wei Liu, Jie Yang","doi":"10.1088/1361-6501/ad6469","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6469","url":null,"abstract":"\u0000 During production, smart cars are equipped with calibrated LiDARs and cameras. However, due to the vibrations that inevitably occur during driving, the sensors' extrinsic parameters may change slightly over time. It is a significant challenge to ensure the ongoing security of these systems throughout the car's lifetime. To address this issue, we propose a self-checking and recalibration algorithm that can continuously detect the sensor data of intelligent vehicles. If the sensor's miscalibration is detected, the data can be repaired promptly to ensure the vehicle's reliability. Our self-checking algorithm extracts features from the point cloud and image and performs pixel-wise comparisons. To improve feature quality, we utilize the patch-wise transformer to enhance local information exchange, which also benefits the subsequent extrinsic recalibration. To facilitate the study, we generate two customized datasets from the KITTI dataset and the Waymo Open Dataset. The experiments conducted on these datasets demonstrate the effectiveness of our proposed method in accurately calibrating the LiDAR and camera systems throughout the car's lifetime. This study is the first to highlight the importance of continually checking the calibrated extrinsic parameters for autonomous driving. Our findings contribute to the broader goal of improving safety and reliability in autonomous driving systems. The dataset and code are available at https://github.com/OpenCalib/LiDAR2camera_self-check.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":" 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141828160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-Factor Quality Assessment of Digital Speckle Pattern for Speckle Projection Profilometry 用于斑点投影轮廓测量的数字斑点模式的多因素质量评估

Measurement Science and Technology Pub Date : 2024-07-17 DOI: 10.1088/1361-6501/ad646a

Yanzhen Dong, Haitao Wu, Xiaobo Chen, Juntong Xi

{"title":"Multi-Factor Quality Assessment of Digital Speckle Pattern for Speckle Projection Profilometry","authors":"Yanzhen Dong, Haitao Wu, Xiaobo Chen, Juntong Xi","doi":"10.1088/1361-6501/ad646a","DOIUrl":"https://doi.org/10.1088/1361-6501/ad646a","url":null,"abstract":"\u0000 The digital speckle pattern (DSP) is an essential component in the speckle projection profilometry (SPP) task, its quality directly affects the results of three-dimensional (3D) shape reconstruction. However, the SPP field lacks specialized numerical metrics for evaluating speckle quality. To address this issue, this study introduces a multi-factor metric (MFM) for comprehensive DSP assessment. Through comparing the metric, optimal parameter ranges for DSP design and the advisable matching subset size can be determined for SPP algorithm. A global indicator named valid feature distribution (VFD) based on scale-invariant feature transform (SIFT) and Delaunay triangulation, is defined to analyze the overall information distribution in DSPs. In addition, MFM incorporates a local metric called mean subset intensity gradient (MSIG), which aids in selecting the suitable radius for different DSPs to balance the accuracy and efficiency. The quality assessment targets the speckle scene images, allowing for the reverse adjustment of the most suitable DSP according to different scenes. The performance of DSPs can be evaluated based on the accuracy and completeness of 3D reconstruction results. By conducting simulation experiments on the 3ds Max platform, the recommended parameter range for DSP can be inferred, including speckle density ratio, speckle diameter, and random variation rate. Appropriate subset sizes for different scenes are also investigated. Furthermore, the MFM is verified on a real binocular speckle device, demonstrating that the measurement standard deviation of a complex workpiece can be reduced to 0.078 mm using the recommended DSP.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":" 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141829559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on wavelet packet energy entropy extraction method for acoustic signal of tunnel lining cavity 隧道衬砌空腔声信号的小波包能量熵提取方法研究

Measurement Science and Technology Pub Date : 2024-07-17 DOI: 10.1088/1361-6501/ad646e

Boyang Fan, Weigang Zhao, Jinghui Ju, Xiushu Tian, Weikang Zhen, Yong Yang

{"title":"Research on wavelet packet energy entropy extraction method for acoustic signal of tunnel lining cavity","authors":"Boyang Fan, Weigang Zhao, Jinghui Ju, Xiushu Tian, Weikang Zhen, Yong Yang","doi":"10.1088/1361-6501/ad646e","DOIUrl":"https://doi.org/10.1088/1361-6501/ad646e","url":null,"abstract":"\u0000 Tunnel lining cavity is a common disease in high-speed railway tunnels, which seriously affects the safe operation of the line.At present, the commonly used method is manual knocking inspection, but it relies on manual judgment, subjective factors have great influence, and there are errors. This paper proposes a feature extraction method of acoustic vibration signal of tunnel lining cavity based on wavelet packet energy entropy and uses wavelet packet energy entropy to realize the identification of cavity defects.The full-scale simulation model of tunnel with a radius of 6m was constructed by COMSOL and different cavity conditions were set up. The wavelet packet energy entropy characteristics of acoustic signals were extracted and analyzed. The mapping relationship between cavity depth and cavity size and wavelet packet energy entropy was explored. The wavelet packet energy entropy and frequency band distribution characteristics were extracted to realize the identification of cavity defects.The local model which can characterize the whole tunnel is designed and the embedded defects are verified by experiments. The results show that the wavelet packet energy entropy can be used as the identification feature of tunnel lining cavity defects. When the wavelet packet energy entropy is less than 2.53, the existence of tunnel lining cavity defects is characterized.When the wavelet packet energy entropy is in the range of 2.53-2.94, it characterizes the existence of the transition boundary between tunnel lining cavity defect and no disease.This index can be used to realize the rapid and effective identification of cavity defects.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":" 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141830948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancement of DDST-MFAC for tracking performance by using dynamic data reconciliation 利用动态数据调节提高 DDST-MFAC 的跟踪性能

Measurement Science and Technology Pub Date : 2024-07-17 DOI: 10.1088/1361-6501/ad6468

Zhiwen Wang, Amirul Syafiq Sadun, Mingxu Lv, Chongcheng Chen, Peng Cui, Muhammad Ashraf Fauri

{"title":"Enhancement of DDST-MFAC for tracking performance by using dynamic data reconciliation","authors":"Zhiwen Wang, Amirul Syafiq Sadun, Mingxu Lv, Chongcheng Chen, Peng Cui, Muhammad Ashraf Fauri","doi":"10.1088/1361-6501/ad6468","DOIUrl":"https://doi.org/10.1088/1361-6501/ad6468","url":null,"abstract":"\u0000 Model-free adaptive control (MFAC) stands out as an effective data-driven method for addressing nonlinear problems in industrial processes. To maintain good control performance, a data-driven set-point tuning (DDST) method is used to update the virtual set-point of the MFAC system. The DDST-based MFAC (i.e. DDST-MFAC) constantly approaches the target of the process through the nonlinear set-point tuning method. However, due to equipment errors and external interference, industrial sensors often suffer from measurement noise, which can have adverse effects on the control performance. In this article, an available dynamic data reconciliation (DDR) technique is adopted to improve the tracking performance of the DDST-MFAC, which suppresses the impact of process noise by using predicted information and measured data to achieve high-precision requirements for controlling nonlinear processes. Finally, considering both Gaussian and non-Gaussian distribution of measurement noise, the effectiveness of the proposed method was verified through the simulation of a nonlinear nonaffine plant. It is also applied to the steam-water heat exchange process, the control result is improved ultimately.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":" 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141830605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Removing spikes in TianQin-1 inertial sensor data using machine learning method 利用机器学习方法消除天琴一号惯性传感器数据中的尖峰数据

Measurement Science and Technology Pub Date : 2024-07-17 DOI: 10.1088/1361-6501/ad646d

Hongmin Wang, Lin Cai, Zebing Zhou, Zhengyuan Shen

引用次数: 0