Subjective cognitive decline (SCD) is the preclinical stage of Alzheimer’s disease (AD). People with SCD have a higher chance of developing mild cognitive impairment and AD than those aging normally. In the present study, we collected resting state functional magnetic resonance imaging (rs-fMRI) data for 69 patients with SCD and 75 normal controls (NC); using statistical analysis, a support vector machine (SVM), and graph convolutional neural networks (GCNs), we examined the brain-related differences between patients with SCD and NC. Clinical scale scores show the best distinguishing ability between patients with SCD and NC, and we further used the two-sample t-test, SVM, and GCN model with an attention mechanism to obtain the top 10 brain regions contributing to performance on recognition tasks. The results showed that the thalamus, and cingulum in the Anatomical Automatic Labeling template showed significant differences between patients with SCD and NC. We further discussed the roles of these identified brain regions in the diagnosis of SCD and AD. Our research thus provided statistical evidence that can aid in identifying early-stage AD.
{"title":"Identifying Biomarkers of Subjective Cognitive Decline Using Graph Convolutional Neural Network for fMRI Analysis","authors":"Zhao Zhang, Guangfei Li, Jiaxi Niu, Sihui Du, Tianxin Gao, Weifeng Liu, Zhenqi Jiang, Xiaoying Tang, Yong Xu","doi":"10.1109/ICMA54519.2022.9856298","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856298","url":null,"abstract":"Subjective cognitive decline (SCD) is the preclinical stage of Alzheimer’s disease (AD). People with SCD have a higher chance of developing mild cognitive impairment and AD than those aging normally. In the present study, we collected resting state functional magnetic resonance imaging (rs-fMRI) data for 69 patients with SCD and 75 normal controls (NC); using statistical analysis, a support vector machine (SVM), and graph convolutional neural networks (GCNs), we examined the brain-related differences between patients with SCD and NC. Clinical scale scores show the best distinguishing ability between patients with SCD and NC, and we further used the two-sample t-test, SVM, and GCN model with an attention mechanism to obtain the top 10 brain regions contributing to performance on recognition tasks. The results showed that the thalamus, and cingulum in the Anatomical Automatic Labeling template showed significant differences between patients with SCD and NC. We further discussed the roles of these identified brain regions in the diagnosis of SCD and AD. Our research thus provided statistical evidence that can aid in identifying early-stage AD.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125423962","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}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856292
Y. Alrubyli, Andrea Bonarini
Unmanned Arial Vehicles (UAVs), and more specifically, quadcopters need to be stable during their flights. Altitude stability is usually achieved by using a PID controller that is built into the flight controller software. Furthermore, the PID controller has gains that need to be tuned to reach optimal altitude stabilization during the quadcopter’s flight. For that, control system engineers need to tune those gains by using extensive modeling of the environment, which might change from one environment and condition to another. As quadcopters penetrate more sectors from the military to the consumer sectors, they have been put into complex and challenging environments more than ever before. Hence, intelligent self-stabilizing quadcopters are needed to maneuver through those complex environments and situations. Here we show that by using online reinforcement learning with minimal background knowledge, the altitude stability of the quadcopter can be achieved using a model-free approach. We found that by using background knowledge and an activation function like Sigmoid, altitude stabilization can be achieved faster with a small memory footprint. In addition, using this approach will accelerate development by avoiding extensive simulations before applying the PID gains to the real-world quadcopter. Our results demonstrate the possibility of using the trial and error approach of reinforcement learning combined with activation function and background knowledge to achieve faster quadcopter altitude stabilization in different environments and conditions.
{"title":"Using Q-learning to Automatically Tune Quadcopter PID Controller Online for Fast Altitude Stabilization","authors":"Y. Alrubyli, Andrea Bonarini","doi":"10.1109/ICMA54519.2022.9856292","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856292","url":null,"abstract":"Unmanned Arial Vehicles (UAVs), and more specifically, quadcopters need to be stable during their flights. Altitude stability is usually achieved by using a PID controller that is built into the flight controller software. Furthermore, the PID controller has gains that need to be tuned to reach optimal altitude stabilization during the quadcopter’s flight. For that, control system engineers need to tune those gains by using extensive modeling of the environment, which might change from one environment and condition to another. As quadcopters penetrate more sectors from the military to the consumer sectors, they have been put into complex and challenging environments more than ever before. Hence, intelligent self-stabilizing quadcopters are needed to maneuver through those complex environments and situations. Here we show that by using online reinforcement learning with minimal background knowledge, the altitude stability of the quadcopter can be achieved using a model-free approach. We found that by using background knowledge and an activation function like Sigmoid, altitude stabilization can be achieved faster with a small memory footprint. In addition, using this approach will accelerate development by avoiding extensive simulations before applying the PID gains to the real-world quadcopter. Our results demonstrate the possibility of using the trial and error approach of reinforcement learning combined with activation function and background knowledge to achieve faster quadcopter altitude stabilization in different environments and conditions.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126716824","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}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856289
Qiang Gao, Guangrui Wei, Yuehui Ji, Yu Song, Junjie Liu, Ning Han
To address the problem of feature information redundancy caused by visual simultaneous localization and mapping algorithm with point and line features in high-texture environment, a fast simultaneous localization and mapping algorithm with point and line feature based on image entropy is proposed. In this paper, we first propose a new feature extraction strategy, which determines the parameters of the feature extractor by image entropy; then, the idea of weighting is introduced in pose estimation, and the point and line features are weighted by the image entropy; finally, we test our method using the KITTI and EuRoC dataset, and demonstrate that our method improves the real-time performance of the system while ensuring the accuracy and robustness of the system.
{"title":"Fast Simultaneous Localization and Mapping Algorithm with Point and Line Feature Based on Image Entropy","authors":"Qiang Gao, Guangrui Wei, Yuehui Ji, Yu Song, Junjie Liu, Ning Han","doi":"10.1109/ICMA54519.2022.9856289","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856289","url":null,"abstract":"To address the problem of feature information redundancy caused by visual simultaneous localization and mapping algorithm with point and line features in high-texture environment, a fast simultaneous localization and mapping algorithm with point and line feature based on image entropy is proposed. In this paper, we first propose a new feature extraction strategy, which determines the parameters of the feature extractor by image entropy; then, the idea of weighting is introduced in pose estimation, and the point and line features are weighted by the image entropy; finally, we test our method using the KITTI and EuRoC dataset, and demonstrate that our method improves the real-time performance of the system while ensuring the accuracy and robustness of the system.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115014165","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}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9855905
Jun Hou, Xiufen Ye
Accurate 3D reconstruction of underwater scenes is very important in various fields related to underwater operation. Multi-beam bathymetry sonar can be used to reconstruct terrain map of seafloor. However, this 3D map is not able to express details of objects well. Accurate underwater targets can only be reconstructed through the camera. However, the existing research has problems such as sparse point cloud in real-time reconstruction and time-consuming for dense point cloud reconstruction. In this paper, we propose an underwater real-time 3D reconstruction system based on stereo camera. Aiming at the problem of blurred underwater images, we propose a lightweight image enhancement algorithm. For the problem of real-time point cloud generation, we adopt the method of computing disparity maps by using stereo cameras. We fuse edge information in the process of computing the disparity map, which improves the accuracy of the disparity map. For multi-view point cloud stitching, we propose a fusion stitching method based on SLAM system and dense point cloud. Our method has been tested in indoor pools and sea areas near the marina respectively. The experimental results show that our method has certain advantages in the 3D reconstruction effect and accuracy of underwater objects.
{"title":"Real-time Underwater 3D Reconstruction Method Based on Stereo Camera","authors":"Jun Hou, Xiufen Ye","doi":"10.1109/ICMA54519.2022.9855905","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9855905","url":null,"abstract":"Accurate 3D reconstruction of underwater scenes is very important in various fields related to underwater operation. Multi-beam bathymetry sonar can be used to reconstruct terrain map of seafloor. However, this 3D map is not able to express details of objects well. Accurate underwater targets can only be reconstructed through the camera. However, the existing research has problems such as sparse point cloud in real-time reconstruction and time-consuming for dense point cloud reconstruction. In this paper, we propose an underwater real-time 3D reconstruction system based on stereo camera. Aiming at the problem of blurred underwater images, we propose a lightweight image enhancement algorithm. For the problem of real-time point cloud generation, we adopt the method of computing disparity maps by using stereo cameras. We fuse edge information in the process of computing the disparity map, which improves the accuracy of the disparity map. For multi-view point cloud stitching, we propose a fusion stitching method based on SLAM system and dense point cloud. Our method has been tested in indoor pools and sea areas near the marina respectively. The experimental results show that our method has certain advantages in the 3D reconstruction effect and accuracy of underwater objects.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116014304","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}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856120
Xiaolei Wu, Bin Li, Jin Wu, Yaqiao Zhu
Aiming at the excitation trajectory design in the identification of inertial parameters of industrial robots, this paper proposes a step-by-step identification and particle gray wolf optimisation algorithm (PSOGWO) to optimise the design of excitation trajectory parameters. First of all, the robot's minimum inertial parameter observation matrix is derived and established by Newton-Eura recursive method, and the observation matrix condition number criterion is used as the optimisation objective function; secondly, the particle gray wolf optimisation algorithm (PSOGWO) is introduced; finally, the periodic Fourier series that meets multi-constraint conditions is optimised and designed as the incentive trajectory using the particle gray wolf optimisation algorithm (PSOGWO). Experimental results show that the excitation trajectory designed with the proposed optimisation method can fully stimulate the dynamic characteristics of the robot, improve the anti-noise ability of parameter identification, and lay a foundation for accurately obtaining the dynamic parameters of the robot.
{"title":"Optimization of the excitation trajectory of particle gray wolf optimization algorithm","authors":"Xiaolei Wu, Bin Li, Jin Wu, Yaqiao Zhu","doi":"10.1109/ICMA54519.2022.9856120","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856120","url":null,"abstract":"Aiming at the excitation trajectory design in the identification of inertial parameters of industrial robots, this paper proposes a step-by-step identification and particle gray wolf optimisation algorithm (PSOGWO) to optimise the design of excitation trajectory parameters. First of all, the robot's minimum inertial parameter observation matrix is derived and established by Newton-Eura recursive method, and the observation matrix condition number criterion is used as the optimisation objective function; secondly, the particle gray wolf optimisation algorithm (PSOGWO) is introduced; finally, the periodic Fourier series that meets multi-constraint conditions is optimised and designed as the incentive trajectory using the particle gray wolf optimisation algorithm (PSOGWO). Experimental results show that the excitation trajectory designed with the proposed optimisation method can fully stimulate the dynamic characteristics of the robot, improve the anti-noise ability of parameter identification, and lay a foundation for accurately obtaining the dynamic parameters of the robot.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116160793","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}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856396
D. Zhao, Shuxiang Guo, Chuqiao Lyu, Yonggang Yan, Z. Lin
The application of vascular interventional surgery robots (VISR) can protect doctor from radiation effectively. However, the use of vascular interventional surgery robots (VISR) is still subject to some limitations. One of the limitations is that the inconsistency of the master-slave structure leads to the complexity of the entire robot structure. Another limitation is that the operation method of the master manipulator is different from the vascular interventional surgery, which makes it difficult for doctors to use their surgical experience. In this paper, a novel clamping mechanism was proposed. It can be used on both the master side and the slave side with the same structure and the operation methods on the master side is the same as that of traditional surgery. It means that the robot will have the consistency of master-slave structure by using the proposed clamping mechanism, which is advantageous for simplification of robot structure. In addition, a better surgical presence can also be provided to doctors during operation.
{"title":"A Novel Clamping Mechanism Design for Vascular Interventional Surgery Robot","authors":"D. Zhao, Shuxiang Guo, Chuqiao Lyu, Yonggang Yan, Z. Lin","doi":"10.1109/ICMA54519.2022.9856396","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856396","url":null,"abstract":"The application of vascular interventional surgery robots (VISR) can protect doctor from radiation effectively. However, the use of vascular interventional surgery robots (VISR) is still subject to some limitations. One of the limitations is that the inconsistency of the master-slave structure leads to the complexity of the entire robot structure. Another limitation is that the operation method of the master manipulator is different from the vascular interventional surgery, which makes it difficult for doctors to use their surgical experience. In this paper, a novel clamping mechanism was proposed. It can be used on both the master side and the slave side with the same structure and the operation methods on the master side is the same as that of traditional surgery. It means that the robot will have the consistency of master-slave structure by using the proposed clamping mechanism, which is advantageous for simplification of robot structure. In addition, a better surgical presence can also be provided to doctors during operation.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122617237","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}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856360
Xiaohan Lei, Fei Zhang, Junyi Zhou, Weiwei Shang
Vision-based mobile positioning technology has a broad application prospect. Still, it is easy to be disturbed by external environmental factors, and the positioning accuracy and robustness in a complex environment are poor. Therefore, this paper designs a high-precision visual positioning strategy for a complex environment via fusing stereo visual odometry and Inertial Measurement Unit (IMU) data. A multi-sensor calibration method is utilized to compensate for the measurement error of IMU and the parameter error of the stereo camera. A multi-sensor data synchronization alignment method based on timestamp is also designed to realize the synchronous acquisition and processing of multi-sensor data. Based on the Unscented Kalman Filter (UKF) algorithm, we implement a nonlinear data coupling method to fuse the stereo visual odometry and IMU information to obtain high-precision positioning. In the complex and open laboratory environment, the experimental results of fused localization show that the accuracy and robustness of the mobile robot localization are significantly improved. The global maximum error is reduced by 15%, and the variance is reduced by 5%.
{"title":"Visual Localization Strategy for Indoor Mobile Robots in the Complex Environment","authors":"Xiaohan Lei, Fei Zhang, Junyi Zhou, Weiwei Shang","doi":"10.1109/ICMA54519.2022.9856360","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856360","url":null,"abstract":"Vision-based mobile positioning technology has a broad application prospect. Still, it is easy to be disturbed by external environmental factors, and the positioning accuracy and robustness in a complex environment are poor. Therefore, this paper designs a high-precision visual positioning strategy for a complex environment via fusing stereo visual odometry and Inertial Measurement Unit (IMU) data. A multi-sensor calibration method is utilized to compensate for the measurement error of IMU and the parameter error of the stereo camera. A multi-sensor data synchronization alignment method based on timestamp is also designed to realize the synchronous acquisition and processing of multi-sensor data. Based on the Unscented Kalman Filter (UKF) algorithm, we implement a nonlinear data coupling method to fuse the stereo visual odometry and IMU information to obtain high-precision positioning. In the complex and open laboratory environment, the experimental results of fused localization show that the accuracy and robustness of the mobile robot localization are significantly improved. The global maximum error is reduced by 15%, and the variance is reduced by 5%.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114053423","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}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856176
Xin Wang, Kaiyuan Huo, R. Tang, Jing Ren, Hongpeng Chen, Kaixuan Sun, Lihong Song
Aiming at the shortcomings of existing manual inspection of mask wearing, a multi-functional mobile robot that can realize mask wearing detection, temperature measurement and omni-directional movement of personnel is proposed. The robot uses an omni-directional mobile platform as the main structure, uses double closed-loop PID (Proportion Integral Differential) algorithm and SLAM (Simultaneous Localization and Mapping) technology for motion control, realizes real-time detection of mask wearing based on YOLOv5 deep learning framework, and uses MLX90640 thermal camera to achieve body temperature detection. The system has the advantages of low cost and stable performance, and has potential value of practical application. At the same time, as a project-driven teaching tool, the system has reference value for cultivating students’ ability to solve practical problems.
{"title":"Intelligent Mask Detection and Non-contact Temperature Measurement Mobile Robot based on YOLOv5","authors":"Xin Wang, Kaiyuan Huo, R. Tang, Jing Ren, Hongpeng Chen, Kaixuan Sun, Lihong Song","doi":"10.1109/ICMA54519.2022.9856176","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856176","url":null,"abstract":"Aiming at the shortcomings of existing manual inspection of mask wearing, a multi-functional mobile robot that can realize mask wearing detection, temperature measurement and omni-directional movement of personnel is proposed. The robot uses an omni-directional mobile platform as the main structure, uses double closed-loop PID (Proportion Integral Differential) algorithm and SLAM (Simultaneous Localization and Mapping) technology for motion control, realizes real-time detection of mask wearing based on YOLOv5 deep learning framework, and uses MLX90640 thermal camera to achieve body temperature detection. The system has the advantages of low cost and stable performance, and has potential value of practical application. At the same time, as a project-driven teaching tool, the system has reference value for cultivating students’ ability to solve practical problems.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121935009","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}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856322
Bin Wang, Jiwen Zhang, Dan Wu
In order to solve the difficulty of manual recognizing the characters printed on thin aviation cables, an automatic recognition method by rotating a monocular camera is presented., two indexes that reflect the completeness and centralizer of characters are designed to automatically search an appropriate image of aviation cable captured by the rotated camera. Then, an optimal image-stitching method is proposed by finding the peak point of ‘coincidence of black pixels’, which improve the quality of character image. Moreover, based on the equal-spaced and straight-line distribution of cable characters, the projection algorithm is optimized, and a character extraction algorithm considering the black pixel’s density and degree of centering is developed. Finally, a-multi SVM classifier is designed to achieve highly accurate recognition of confusing characters. The experimental results demonstrate the effectiveness of the recognition method and algorithm.
{"title":"Automatic Recognition Method of Aviation Thin Cable Characters Based on Rotating Monocular Camera","authors":"Bin Wang, Jiwen Zhang, Dan Wu","doi":"10.1109/ICMA54519.2022.9856322","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856322","url":null,"abstract":"In order to solve the difficulty of manual recognizing the characters printed on thin aviation cables, an automatic recognition method by rotating a monocular camera is presented., two indexes that reflect the completeness and centralizer of characters are designed to automatically search an appropriate image of aviation cable captured by the rotated camera. Then, an optimal image-stitching method is proposed by finding the peak point of ‘coincidence of black pixels’, which improve the quality of character image. Moreover, based on the equal-spaced and straight-line distribution of cable characters, the projection algorithm is optimized, and a character extraction algorithm considering the black pixel’s density and degree of centering is developed. Finally, a-multi SVM classifier is designed to achieve highly accurate recognition of confusing characters. The experimental results demonstrate the effectiveness of the recognition method and algorithm.","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129938666","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}
Pub Date : 2022-08-07DOI: 10.1109/ICMA54519.2022.9856046
Naizhao Yu, Jiahao Wang, Lanyong Zhang
In this paper, a novel adaptive interference cancellation algorithm for non-stationary random signal filtering is proposed. An intelligent Electromagnetic Interference measurement system based on Empirical Mode Decomposition (EMD) analysis is designed. the complex electromagnetic radiation signal is decomposed into different natural mode functions by empirical mode decomposition (EMD), which represent signals with different frequency. An improved least mean square (LMS) algorithm is applied to adaptive interference cancellation. The results show that this method has better noise cancellation ability than the traditional adaptive noise cancellation method. At the same time, the new adaptive interference cancellation technology improves the speed and accuracy of electromagnetic radiation measurement. Therefore, it can be introduced into engineering application. Compared with other traditional instruments and manual testing, the system improves the testing efficiency and has good scalability
{"title":"Research on Electromagnetic Interference Canceller Based on Improved Least Mean Square","authors":"Naizhao Yu, Jiahao Wang, Lanyong Zhang","doi":"10.1109/ICMA54519.2022.9856046","DOIUrl":"https://doi.org/10.1109/ICMA54519.2022.9856046","url":null,"abstract":"In this paper, a novel adaptive interference cancellation algorithm for non-stationary random signal filtering is proposed. An intelligent Electromagnetic Interference measurement system based on Empirical Mode Decomposition (EMD) analysis is designed. the complex electromagnetic radiation signal is decomposed into different natural mode functions by empirical mode decomposition (EMD), which represent signals with different frequency. An improved least mean square (LMS) algorithm is applied to adaptive interference cancellation. The results show that this method has better noise cancellation ability than the traditional adaptive noise cancellation method. At the same time, the new adaptive interference cancellation technology improves the speed and accuracy of electromagnetic radiation measurement. Therefore, it can be introduced into engineering application. Compared with other traditional instruments and manual testing, the system improves the testing efficiency and has good scalability","PeriodicalId":120073,"journal":{"name":"2022 IEEE International Conference on Mechatronics and Automation (ICMA)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128215498","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：