Measurement最新文献

英文中文

Foreign object detection on vibrating screens: A precision-oriented rotational detection framework with attention mechanisms

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement

Pub Date : 2025-02-24 DOI: 10.1016/j.measurement.2025.117115

Weidong Wang , Xuan Zhao , Yang Song , Yuhan Fan , Yao Cui , Yuxin Wu , Jiangtao Li , Hongjiu Zeng , Ziqi Lv

Foreign objects in coal mining and washing operations pose significant challenges, including equipment wear, production inefficiencies, and safety hazards. Current sorting methods, predominantly manual or based on Horizontal Bounding Box detection, struggle to meet the requirements of dynamic environments due to their inability to accurately predict target orientation and suppress background interference. This study introduces YOLOv5-SROD, a rotational object detection algorithm tailored for foreign object detection on vibrating screens. The model introduces rotating bounding boxes with a Circular Smooth Label strategy, ensuring stable and accurate angle predictions while addressing challenges such as angle jumping. Additionally, the Squeeze-and-Excitation attention mechanism enhances feature extraction in complex scenarios by suppressing noise from reflective water spray and high-glare conditions. Experimental results reveal that YOLOv5-SROD achieves a [email protected] of 84.5%, processes at 30.4 FPS, and features a lightweight design with 21.68 million parameters, outperforming both HBB methods and state-of-the-art rotational detection models. These results highlight YOLOv5-SROD’s capability to deliver real-time, accurate detection in challenging industrial environments, offering a scalable and practical solution for foreign object detection in coal preparation processes.

{"title":"Foreign object detection on vibrating screens: A precision-oriented rotational detection framework with attention mechanisms","authors":"Weidong Wang , Xuan Zhao , Yang Song , Yuhan Fan , Yao Cui , Yuxin Wu , Jiangtao Li , Hongjiu Zeng , Ziqi Lv","doi":"10.1016/j.measurement.2025.117115","DOIUrl":"10.1016/j.measurement.2025.117115","url":null,"abstract":"<div><div>Foreign objects in coal mining and washing operations pose significant challenges, including equipment wear, production inefficiencies, and safety hazards. Current sorting methods, predominantly manual or based on Horizontal Bounding Box detection, struggle to meet the requirements of dynamic environments due to their inability to accurately predict target orientation and suppress background interference. This study introduces YOLOv5-SROD, a rotational object detection algorithm tailored for foreign object detection on vibrating screens. The model introduces rotating bounding boxes with a Circular Smooth Label strategy, ensuring stable and accurate angle predictions while addressing challenges such as angle jumping. Additionally, the Squeeze-and-Excitation attention mechanism enhances feature extraction in complex scenarios by suppressing noise from reflective water spray and high-glare conditions. Experimental results reveal that YOLOv5-SROD achieves a [email protected] of 84.5%, processes at 30.4 FPS, and features a lightweight design with 21.68 million parameters, outperforming both HBB methods and state-of-the-art rotational detection models. These results highlight YOLOv5-SROD’s capability to deliver real-time, accurate detection in challenging industrial environments, offering a scalable and practical solution for foreign object detection in coal preparation processes.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"250 ","pages":"Article 117115"},"PeriodicalIF":5.2,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143511153","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}

引用次数: 0

Combining SfM and deep learning to construct 3D point cloud models of shield tunnels and Realize spatial localization of water leakages

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement

Pub Date : 2025-02-24 DOI: 10.1016/j.measurement.2025.117114

Jinhua Qian , Fei Xue , Tianzuo Wang , Zhongqin Lin , Mingcheng Cai , Feifeng Shou

To address the inefficiency of traditional 3D reconstruction methods for shield tunnels and their limitations in visualization and leakage localization, this study replaces the dense reconstruction process with the generation of cylindrical point clouds using RANSAC to extract tunnel contours from SfM-based sparse point clouds. Experiments show that the structural error of the cylindrical point cloud is only 0.47%, and modeling time is reduced by 80.6%. With its uniform and controllable point density, the cylindrical point cloud enables texture mapping through camera parameters, achieving a 190.81% improvement in texture clarity and a 49.4% reduction in overall modeling time compared to traditional methods. Deep learning is further applied for pixel-level leakage segmentation, enabling spatial annotation in the 3D model. This method provides rapid, clear 3D modeling and efficient leakage detection, aiding in spatial leakage analysis.

引用次数: 0

A compact optically pumped potassium atomic magnetometer with high sensitivity under geomagnetic field intensity 在地磁场强度下具有高灵敏度的紧凑型光泵浦钾原子磁强计

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement

Pub Date : 2025-02-23 DOI: 10.1016/j.measurement.2025.117099

Rongtong Zhu , Yi Zhang , Pengcheng Du , Yan Xuan , Feifan Yang , Yuansheng Zhou , Kuan Zhang , Xiaoxun Li , Shuo Sun , Tianshi Cheng , Jianli Li , Shiqiang Zheng , Wei Quan , Jin Li

Atomic magnetometers have garnered significant attention due to their vast potential for applications in life sciences, resource exploration and other fields. This paper proposes a compact optically pumped potassium atomic magnetometer, which simultaneously achieves small volume, high reliability, and high sensitivity for geomagnetic field intensity measurements. The magnetometer employs a single-beam structure integrated with a potassium cell and self-assembled excitation coils, with the sensor probe of 22.3 cm³. The effects of the cell temperature, optical power, and radio frequency field on the amplitude and linewidth of the magnetic resonance signals were analyzed and optimized based on orthogonal design method. As a result, the magnetometer achieved a sensitivity of 1.2 pT/Hz^1/2 for frequencies from 30 Hz to 200 Hz under a magnetic field of 10,000 nT. Additionally, the magnetometer demonstrated rapid responsiveness to dynamic magnetic fields and the ability to detect and differentiate various iron ores. The proposed magnetometer provides a more promising way to implement highly sensitive compact atomic magnetometers under geomagnetic field intensity. It can also broaden prospects in weak magnetic measurement applications in special environments such as aerial magnetic surveys and borehole geomagnetic monitoring.

{"title":"A compact optically pumped potassium atomic magnetometer with high sensitivity under geomagnetic field intensity","authors":"Rongtong Zhu , Yi Zhang , Pengcheng Du , Yan Xuan , Feifan Yang , Yuansheng Zhou , Kuan Zhang , Xiaoxun Li , Shuo Sun , Tianshi Cheng , Jianli Li , Shiqiang Zheng , Wei Quan , Jin Li","doi":"10.1016/j.measurement.2025.117099","DOIUrl":"10.1016/j.measurement.2025.117099","url":null,"abstract":"<div><div>Atomic magnetometers have garnered significant attention due to their vast potential for applications in life sciences, resource exploration and other fields. This paper proposes a compact optically pumped potassium atomic magnetometer, which simultaneously achieves small volume, high reliability, and high sensitivity for geomagnetic field intensity measurements. The magnetometer employs a single-beam structure integrated with a potassium cell and self-assembled excitation coils, with the sensor probe of 22.3 cm<sup>3</sup>. The effects of the cell temperature, optical power, and radio frequency field on the amplitude and linewidth of the magnetic resonance signals were analyzed and optimized based on orthogonal design method. As a result, the magnetometer achieved a sensitivity of 1.2 pT/Hz<sup>1/2</sup> for frequencies from 30 Hz to 200 Hz under a magnetic field of 10,000 nT. Additionally, the magnetometer demonstrated rapid responsiveness to dynamic magnetic fields and the ability to detect and differentiate various iron ores. The proposed magnetometer provides a more promising way to implement highly sensitive compact atomic magnetometers under geomagnetic field intensity. It can also broaden prospects in weak magnetic measurement applications in special environments such as aerial magnetic surveys and borehole geomagnetic monitoring.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"250 ","pages":"Article 117099"},"PeriodicalIF":5.2,"publicationDate":"2025-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520554","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}

引用次数: 0

A harmonic analysis method for power systems based on double frequency-shift filtering

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement

Pub Date : 2025-02-23 DOI: 10.1016/j.measurement.2025.117030

Jiaqi Yu , Jianmin Li , Chengbin Liang , Chen Gong , Bingfan Zhu , Qiang Tang

Harmonics have emerged as a prominent power quality concern in power systems. Accurate estimation of harmonic parameters in the power grid is not only a fundamental requirement for effective harmonic management but also a crucial foundation for power enterprises and users to assess the extent of harmonic impact. Therefore, a harmonic analysis method for power systems based on double frequency-shift filtering is proposed in this paper. The method initially applies frequency-shift filtering to the original grid signal, obtaining the fundamental frequency deviation and forming a new frequency-shift factor. Subsequently, employing the determined fundamental frequency and the updated frequency-shift factor, a secondary frequency-shift filtering is applied to the original grid signal. Finally, the amplitudes and phases of individual harmonics are computed through deduced formulas, utilizing the power grid signal acquired after the secondary frequency-shift filtering. Simulation experiments show the algorithm’s attributes, including notable measurement accuracy, exceptional real-time performance, and robust adaptability. Furthermore, validation of the algorithm’s accuracy and effectiveness is accomplished by testing it on an actual hardware platform.

{"title":"A harmonic analysis method for power systems based on double frequency-shift filtering","authors":"Jiaqi Yu , Jianmin Li , Chengbin Liang , Chen Gong , Bingfan Zhu , Qiang Tang","doi":"10.1016/j.measurement.2025.117030","DOIUrl":"10.1016/j.measurement.2025.117030","url":null,"abstract":"<div><div>Harmonics have emerged as a prominent power quality concern in power systems. Accurate estimation of harmonic parameters in the power grid is not only a fundamental requirement for effective harmonic management but also a crucial foundation for power enterprises and users to assess the extent of harmonic impact. Therefore, a harmonic analysis method for power systems based on double frequency-shift filtering is proposed in this paper. The method initially applies frequency-shift filtering to the original grid signal, obtaining the fundamental frequency deviation and forming a new frequency-shift factor. Subsequently, employing the determined fundamental frequency and the updated frequency-shift factor, a secondary frequency-shift filtering is applied to the original grid signal. Finally, the amplitudes and phases of individual harmonics are computed through deduced formulas, utilizing the power grid signal acquired after the secondary frequency-shift filtering. Simulation experiments show the algorithm’s attributes, including notable measurement accuracy, exceptional real-time performance, and robust adaptability. Furthermore, validation of the algorithm’s accuracy and effectiveness is accomplished by testing it on an actual hardware platform.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"249 ","pages":"Article 117030"},"PeriodicalIF":5.2,"publicationDate":"2025-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479643","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}

引用次数: 0

Plant Doctor: A hybrid machine learning and image segmentation software to quantify plant damage in video footage

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement

Pub Date : 2025-02-22 DOI: 10.1016/j.measurement.2025.117094

Marc Josep Montagut Marques , Liu Mingxin , Kuri Thomas Shiojiri , Tomika Hagiwara , Kayo Hirose , Kaori Shiojiri , Shinjiro Umezu

Artificial intelligence has significantly advanced the automation of diagnostic processes, benefiting various fields including agriculture. This study introduces an AI-based system for the automatic diagnosis of urban street plants using video footage obtained with accessible camera devices. The system aims to monitor plant health on a day-to-day basis, aiding in the control of disease spread in urban areas. By combining two machine vision algorithms, YOLOv8 and DeepSORT, the system efficiently identifies and tracks individual leaves, extracting the optimal images for health analysis. YOLOv8, chosen for its speed and computational efficiency, locates leaves, while DeepSORT ensures robust tracking in complex environments. For detailed health assessment, DeepLabV3Plus, a convolutional neural network, is employed to segment and quantify leaf damage caused by bacteria, pests, and fungi. The hybrid system, named Plant Doctor, has been trained and validated using a diverse dataset including footage of urban plants in Tokyo. The results demonstrate the robustness and accuracy of the system in diagnosing leaf damage, with potential applications in large-scale urban flora illness monitoring. This approach provides a non-invasive, efficient, and scalable solution for urban tree health management, supporting sustainable urban ecosystems.

{"title":"Plant Doctor: A hybrid machine learning and image segmentation software to quantify plant damage in video footage","authors":"Marc Josep Montagut Marques , Liu Mingxin , Kuri Thomas Shiojiri , Tomika Hagiwara , Kayo Hirose , Kaori Shiojiri , Shinjiro Umezu","doi":"10.1016/j.measurement.2025.117094","DOIUrl":"10.1016/j.measurement.2025.117094","url":null,"abstract":"<div><div>Artificial intelligence has significantly advanced the automation of diagnostic processes, benefiting various fields including agriculture. This study introduces an AI-based system for the automatic diagnosis of urban street plants using video footage obtained with accessible camera devices. The system aims to monitor plant health on a day-to-day basis, aiding in the control of disease spread in urban areas. By combining two machine vision algorithms, YOLOv8 and DeepSORT, the system efficiently identifies and tracks individual leaves, extracting the optimal images for health analysis. YOLOv8, chosen for its speed and computational efficiency, locates leaves, while DeepSORT ensures robust tracking in complex environments. For detailed health assessment, DeepLabV3Plus, a convolutional neural network, is employed to segment and quantify leaf damage caused by bacteria, pests, and fungi. The hybrid system, named Plant Doctor, has been trained and validated using a diverse dataset including footage of urban plants in Tokyo. The results demonstrate the robustness and accuracy of the system in diagnosing leaf damage, with potential applications in large-scale urban flora illness monitoring. This approach provides a non-invasive, efficient, and scalable solution for urban tree health management, supporting sustainable urban ecosystems.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"249 ","pages":"Article 117094"},"PeriodicalIF":5.2,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479626","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}

引用次数: 0

Accurate and adaptive state of health estimation for lithium-ion battery based on patch learning framework

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement

Pub Date : 2025-02-22 DOI: 10.1016/j.measurement.2025.117083

Yuyao Li , Xiangwen Zhang , Ziyang Li , Xudong Li , Gengfeng Liu , Wei Gao

To solve the low accuracy and adaptivity of state of health (SOH) estimation for lithium-ion batteries, a patch learning framework is proposed in this paper. The global model and the patch model are adaptively combined to improve the adaptability and local tracking ability of SOH estimation. The gate recurrent unit model is selected as the global model for its global description capability, and the convolutional neural network-bidirectional long short-term memory model is chosen as the patch model for its local tracking capability. With the global and patch models, the patch learning model is developed by searching the patch segments until the error is below the allowable value. The proposed method is evaluated and compared with some existing methods on our battery aging dataset and public dataset. The experimental results show that the RMSE of the proposed method for all cells is within 0.72%, the MAE is within 0.59% and the MAPE is within 0.66%, and it has the highest accuracy and the best generalization performance compared with GRU, CNN-BiLSTM, SVR, ELM and LSTM methods.

{"title":"Accurate and adaptive state of health estimation for lithium-ion battery based on patch learning framework","authors":"Yuyao Li , Xiangwen Zhang , Ziyang Li , Xudong Li , Gengfeng Liu , Wei Gao","doi":"10.1016/j.measurement.2025.117083","DOIUrl":"10.1016/j.measurement.2025.117083","url":null,"abstract":"<div><div>To solve the low accuracy and adaptivity of state of health (SOH) estimation for lithium-ion batteries, a patch learning framework is proposed in this paper. The global model and the patch model are adaptively combined to improve the adaptability and local tracking ability of SOH estimation. The gate recurrent unit model is selected as the global model for its global description capability, and the convolutional neural network-bidirectional long short-term memory model is chosen as the patch model for its local tracking capability. With the global and patch models, the patch learning model is developed by searching the patch segments until the error is below the allowable value. The proposed method is evaluated and compared with some existing methods on our battery aging dataset and public dataset. The experimental results show that the RMSE of the proposed method for all cells is within 0.72%, the MAE is within 0.59% and the MAPE is within 0.66%, and it has the highest accuracy and the best generalization performance compared with GRU, CNN-BiLSTM, SVR, ELM and LSTM methods.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"250 ","pages":"Article 117083"},"PeriodicalIF":5.2,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143527139","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}

引用次数: 0

Detection of suspended monorail track irregularity based on inertial navigation system and high-speed laser scanner

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement

Pub Date : 2025-02-22 DOI: 10.1016/j.measurement.2025.117101

Wenlin Shen, Huanyun Dai, Jing Zeng, Hao Gao, Lai Wei

Track irregularities are crucial in the study of suspended monorail transportation systems. However, few studies have been conducted on the irregularities and detection principles of suspended monorail tracks (SMT). This study presents a continuous detection principle for track irregularities of suspended monorail beams using an inertial navigation system and a high-speed laser scanner. A motion trajectory calculation and bias correction formula are derived from the motion attitude of the detection trolley, facilitating the modeling of long-wave irregularities. A calculation model for short-wave irregularities is built through feature point extraction, data fitting, and spatial coordinate transformation of point cloud data. Based on these calculation models, an irregularity detection system for SMT was developed. To validate its accuracy and reliability, a field test was conducted on a 2-km experimental line using both the detection system and portable equipment. The test results from the detection system were in close agreement with those from the portable equipment, validating its accuracy. The irregularities of the experimental line included several periodic irregularities related to the unique structure of the track beam, which significantly impact ride comfort and the operational safety of the vehicle.

{"title":"Detection of suspended monorail track irregularity based on inertial navigation system and high-speed laser scanner","authors":"Wenlin Shen, Huanyun Dai, Jing Zeng, Hao Gao, Lai Wei","doi":"10.1016/j.measurement.2025.117101","DOIUrl":"10.1016/j.measurement.2025.117101","url":null,"abstract":"<div><div>Track irregularities are crucial in the study of suspended monorail transportation systems. However, few studies have been conducted on the irregularities and detection principles of suspended monorail tracks (SMT). This study presents a continuous detection principle for track irregularities of suspended monorail beams using an inertial navigation system and a high-speed laser scanner. A motion trajectory calculation and bias correction formula are derived from the motion attitude of the detection trolley, facilitating the modeling of long-wave irregularities. A calculation model for short-wave irregularities is built through feature point extraction, data fitting, and spatial coordinate transformation of point cloud data. Based on these calculation models, an irregularity detection system for SMT was developed. To validate its accuracy and reliability, a field test was conducted on a 2-km experimental line using both the detection system and portable equipment. The test results from the detection system were in close agreement with those from the portable equipment, validating its accuracy. The irregularities of the experimental line included several periodic irregularities related to the unique structure of the track beam, which significantly impact ride comfort and the operational safety of the vehicle.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"250 ","pages":"Article 117101"},"PeriodicalIF":5.2,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548706","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}

引用次数: 0

A robust scaling registration method for rail profile inspection

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement

Pub Date : 2025-02-22 DOI: 10.1016/j.measurement.2025.116972

Long Liu , Bing Yi , Jia Liu

Accurate measurement of rail profile wear is crucial for railroad monitoring and maintenance, ensuring the security of railway transport. Therefore, laser sensor-based profile measurement has been widely adopted to verify whether the geometric shape of the rail meets service requirements. However, two major challenges — profile distortion and noise points — significantly affect the accuracy of measurement results. Hence, this paper presents a robust scaling point set registration method to address these issues. Firstly, we outline the challenges of rail profile inspection using laser sensors and formulate the coordination alignment problem. Then, we propose a robust scaling point set registration method (RSPM) that utilizes a scaled German–McClure loss function to calibrate profile distortion, which is resilient to noise points and outliers. Finally, we evaluate and apply the proposed method for rail profile inspection. Experimental results demonstrate that the proposed method performs well in terms of distorted profile calibration, noise points, and outlier resistance when compared with the iterative closest point and reweighted-scaling iterative closest point methods.

{"title":"A robust scaling registration method for rail profile inspection","authors":"Long Liu , Bing Yi , Jia Liu","doi":"10.1016/j.measurement.2025.116972","DOIUrl":"10.1016/j.measurement.2025.116972","url":null,"abstract":"<div><div>Accurate measurement of rail profile wear is crucial for railroad monitoring and maintenance, ensuring the security of railway transport. Therefore, laser sensor-based profile measurement has been widely adopted to verify whether the geometric shape of the rail meets service requirements. However, two major challenges — profile distortion and noise points — significantly affect the accuracy of measurement results. Hence, this paper presents a robust scaling point set registration method to address these issues. Firstly, we outline the challenges of rail profile inspection using laser sensors and formulate the coordination alignment problem. Then, we propose a robust scaling point set registration method (RSPM) that utilizes a scaled German–McClure loss function to calibrate profile distortion, which is resilient to noise points and outliers. Finally, we evaluate and apply the proposed method for rail profile inspection. Experimental results demonstrate that the proposed method performs well in terms of distorted profile calibration, noise points, and outlier resistance when compared with the iterative closest point and reweighted-scaling iterative closest point methods.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"249 ","pages":"Article 116972"},"PeriodicalIF":5.2,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143479625","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}

引用次数: 0

Opportunities and challenges of noise interference suppression algorithms for dynamic ECG signals in wearable devices: A review

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement

Pub Date : 2025-02-22 DOI: 10.1016/j.measurement.2025.117067

Juya Zhang , Yu Guo , Xinming Dong , Tong Wang , Jinhai Wang , Xin Ma , Huiquan Wang

The primary obstacle in using wearable devices to record dynamic Electrocardiogram (ECG) signal for more efficient analysis of cardiac problems is noise interference, which can cause signal distortion and impact the accuracy of diagnosis and analysis. This paper examines noise suppression methods and their recent advancements in the time domain, frequency domain, time–frequency domain, and artificial intelligence domain, it assesses the various types of noise suppression, the advantages and disadvantages of the algorithms, real-time capabilities, noise reduction effectiveness, and performance metrics. This study also innovatively investigates the general applicability and specificity of the algorithms, discusses the shortcomings of the current ECG datasets, how to learn by analogy for noise reduction algorithms, the interpretability of the models as well as pointing out the problems and constraints of the existing algorithms for wearable devices as well as providing a unique perspective for future research directions.

{"title":"Opportunities and challenges of noise interference suppression algorithms for dynamic ECG signals in wearable devices: A review","authors":"Juya Zhang , Yu Guo , Xinming Dong , Tong Wang , Jinhai Wang , Xin Ma , Huiquan Wang","doi":"10.1016/j.measurement.2025.117067","DOIUrl":"10.1016/j.measurement.2025.117067","url":null,"abstract":"<div><div>The primary obstacle in using wearable devices to record dynamic Electrocardiogram (ECG) signal for more efficient analysis of cardiac problems is noise interference, which can cause signal distortion and impact the accuracy of diagnosis and analysis. This paper examines noise suppression methods and their recent advancements in the time domain, frequency domain, time–frequency domain, and artificial intelligence domain, it assesses the various types of noise suppression, the advantages and disadvantages of the algorithms, real-time capabilities, noise reduction effectiveness, and performance metrics. This study also innovatively investigates the general applicability and specificity of the algorithms, discusses the shortcomings of the current ECG datasets, how to learn by analogy for noise reduction algorithms, the interpretability of the models as well as pointing out the problems and constraints of the existing algorithms for wearable devices as well as providing a unique perspective for future research directions.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"250 ","pages":"Article 117067"},"PeriodicalIF":5.2,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520483","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}

引用次数: 0

Microwave spectrum detection with adjustable instantaneous response bandwidth based on NV center microscope

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement

Pub Date : 2025-02-22 DOI: 10.1016/j.measurement.2025.117040

Zhonghao Li , Jiaxuan Zhang , Chenyu Yang , Huanfei Wen , Zongmin Ma , Hao Guo , Xin Li , Jun Tang , Jun Liu

The achievement of high-precision microwave spectrum detection relies on instantaneous high-bandwidth microwave measurement technologies. Here, the measurement for broadband microwave with adjustable instantaneous bandwidth has been realized. Firstly, the model between the spatial magnetic field gradient and resonant frequency of nitrogen-vacancy (NV) center is established. Based on the optically detected magnetic resonance (ODMR), the manipulation of spatial magnetic gradient field, and wide field imaging technology, the broadband measurement of microwave is realized. Then, by adjusting the distribution of spatial magnetic field gradient, the bandwidth can be tuned and expanded up to 1.3 GHz. Finally, the instantaneous response is verified with synchronous multi-frequency detection in 2.6 GHz, 3.3 GHz and 3.9 GHz and the optimal sensitivity of approximately 0.40 μT/Hz ^1/2. These results showed broadband multi-frequency microwave instantaneous detection and provided an important technical basis for quantum spectrum analysis, high instantaneous bandwidth spectrum synchronous detection and electromagnetic multi-frequency recognition.

{"title":"Microwave spectrum detection with adjustable instantaneous response bandwidth based on NV center microscope","authors":"Zhonghao Li , Jiaxuan Zhang , Chenyu Yang , Huanfei Wen , Zongmin Ma , Hao Guo , Xin Li , Jun Tang , Jun Liu","doi":"10.1016/j.measurement.2025.117040","DOIUrl":"10.1016/j.measurement.2025.117040","url":null,"abstract":"<div><div>The achievement of high-precision microwave spectrum detection relies on instantaneous high-bandwidth microwave measurement technologies. Here, the measurement for broadband microwave with adjustable instantaneous bandwidth has been realized. Firstly, the model between the spatial magnetic field gradient and resonant frequency of nitrogen-vacancy (NV) center is established. Based on the optically detected magnetic resonance (ODMR), the manipulation of spatial magnetic gradient field, and wide field imaging technology, the broadband measurement of microwave is realized. Then, by adjusting the distribution of spatial magnetic field gradient, the bandwidth can be tuned and expanded up to 1.3 GHz. Finally, the instantaneous response is verified with synchronous multi-frequency detection in 2.6 GHz, 3.3 GHz and 3.9 GHz and the optimal sensitivity of approximately 0.40 μT/Hz <sup>1/2</sup>. These results showed broadband multi-frequency microwave instantaneous detection and provided an important technical basis for quantum spectrum analysis, high instantaneous bandwidth spectrum synchronous detection and electromagnetic multi-frequency recognition.</div></div>","PeriodicalId":18349,"journal":{"name":"Measurement","volume":"249 ","pages":"Article 117040"},"PeriodicalIF":5.2,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487100","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}

引用次数: 0

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全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

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全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

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