This paper introduces four methods of accurate curve drawing based on SolidWorks. By using these four methods, complex contour curves such as involute can be accurately drawn in SolidWorks, so as to improve the efficiency and accuracy of solid parts modeling, and finally improving the accuracy of dynamic simulation, interference test and finite element analysis.
{"title":"Methods of Accurate Curve Drawing Based on 3D Design Software","authors":"Zhongwen Hui","doi":"10.1145/3548608.3559321","DOIUrl":"https://doi.org/10.1145/3548608.3559321","url":null,"abstract":"This paper introduces four methods of accurate curve drawing based on SolidWorks. By using these four methods, complex contour curves such as involute can be accurately drawn in SolidWorks, so as to improve the efficiency and accuracy of solid parts modeling, and finally improving the accuracy of dynamic simulation, interference test and finite element analysis.","PeriodicalId":201434,"journal":{"name":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127640119","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}
With the gradual opening of the interaction method between the internal and external network, how to effectively detect the attack for the internal network through the external network becomes more and more important. However, traditional security protection measures cannot well detect unknown attacks and multi-step attacks, which leads to a constant threat. This paper proposes a network security knowledge graph model based on an extended attack-chain, combined with a multi-layer anomaly detection system to detect the threat lurked in the network. Finally, the application of the multi-layer anomaly detection framework in the security protection for internal and external boundary of state grid information network is prospected.
{"title":"An Anomaly Detection Framework for Internal and External Interaction of Power Grid Information Network based on the Attack-chain Knowledge Graph","authors":"Qianqian Jin, Mingyan Li, Peng Gao, Yenjou Wang","doi":"10.1145/3548608.3559260","DOIUrl":"https://doi.org/10.1145/3548608.3559260","url":null,"abstract":"With the gradual opening of the interaction method between the internal and external network, how to effectively detect the attack for the internal network through the external network becomes more and more important. However, traditional security protection measures cannot well detect unknown attacks and multi-step attacks, which leads to a constant threat. This paper proposes a network security knowledge graph model based on an extended attack-chain, combined with a multi-layer anomaly detection system to detect the threat lurked in the network. Finally, the application of the multi-layer anomaly detection framework in the security protection for internal and external boundary of state grid information network is prospected.","PeriodicalId":201434,"journal":{"name":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","volume":"361 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124542443","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}
The conventional dynamic window approach (DWA) model lacks the time planning capability when simulating the steering process of an unmanned surface vessel (USV). In this paper, we propose a steering time-consuming calculation based on the DWA method in an actual context. In this study, the channel environment model established by the MATLAB software is examined, and the DWM model is modified to calculate the time-consuming steering process of an underwater vessel. Simulations with different steering angles are conducted to verify the applicability and effectiveness of the model in solving this problem of underwater vessel steering in an actual environment. A set of parameters such as heading deviation weight, safety distance weight, sailing speed weight, and simulated trajectory time are selected, and the optimized parameters are screened out according to their sensitivity to the results. The research results show that our proposed method can improve the USV planning ability and enhance the effectiveness of handling related path planning problems.
{"title":"Time-consuming Calculation and Simulation of Unmanned Surface Vessel (USV) Steering Based on Dynamic Window Approach (DWA)","authors":"Yuan Zhou, Liangxiong Dong","doi":"10.1145/3548608.3559189","DOIUrl":"https://doi.org/10.1145/3548608.3559189","url":null,"abstract":"The conventional dynamic window approach (DWA) model lacks the time planning capability when simulating the steering process of an unmanned surface vessel (USV). In this paper, we propose a steering time-consuming calculation based on the DWA method in an actual context. In this study, the channel environment model established by the MATLAB software is examined, and the DWM model is modified to calculate the time-consuming steering process of an underwater vessel. Simulations with different steering angles are conducted to verify the applicability and effectiveness of the model in solving this problem of underwater vessel steering in an actual environment. A set of parameters such as heading deviation weight, safety distance weight, sailing speed weight, and simulated trajectory time are selected, and the optimized parameters are screened out according to their sensitivity to the results. The research results show that our proposed method can improve the USV planning ability and enhance the effectiveness of handling related path planning problems.","PeriodicalId":201434,"journal":{"name":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124679741","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}
The pulse of human body is affected by heart and blood, and carries important information reflecting the state of human body. Deep learning has made a breakthrough in features extracting for complex signals. The purpose of this paper is to establish a deep neural network to classify and identify the collected pulse data before and after long-time work. Firstly, the abnormal value of the original pulse data is replaced with the value within the normal range, and then the pulse length sequence 30 is divided into a short sequence of 75 consecutive sampling points. Finally, a deep neural network model is established to input short pulse sequence and output the corresponding physiological state. After training, the final classification accuracy of advanced neural network is 0.79 on 3200 training sets and 0.78 on 800 test sets. The pulse data before and after long-time work were effectively classified.
{"title":"Study on the Classification of Abnormal pulse signals Based on Deep Neural Network","authors":"Yuzhong Liu, Hualiang Li, Jianmin Wang, Haochuan Zhang, X. Zheng","doi":"10.1145/3548608.3559209","DOIUrl":"https://doi.org/10.1145/3548608.3559209","url":null,"abstract":"The pulse of human body is affected by heart and blood, and carries important information reflecting the state of human body. Deep learning has made a breakthrough in features extracting for complex signals. The purpose of this paper is to establish a deep neural network to classify and identify the collected pulse data before and after long-time work. Firstly, the abnormal value of the original pulse data is replaced with the value within the normal range, and then the pulse length sequence 30 is divided into a short sequence of 75 consecutive sampling points. Finally, a deep neural network model is established to input short pulse sequence and output the corresponding physiological state. After training, the final classification accuracy of advanced neural network is 0.79 on 3200 training sets and 0.78 on 800 test sets. The pulse data before and after long-time work were effectively classified.","PeriodicalId":201434,"journal":{"name":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121109864","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}
Unmanned tractor–trailer vehicles play a particularly important role in various fields today. Vehicle tracking control technology is a key part of automatic driving, and its performance directly determines the vehicle's movement performance and even the success of the task. In this review, the current research status of tractor–trailer vehicles is summarized, several main tracking control methods of the vehicles are classified, and the advantages and disadvantages of each method are summarized. At the same time, the existing problems and future development direction in this field are summarized and prospected.
{"title":"A Review of Tracking Control Method for Tractor-Trailer Vehicles","authors":"Qiang Liu, Xueyuan Li, Yuzheng Zhu, Songhao Li","doi":"10.1145/3548608.3559323","DOIUrl":"https://doi.org/10.1145/3548608.3559323","url":null,"abstract":"Unmanned tractor–trailer vehicles play a particularly important role in various fields today. Vehicle tracking control technology is a key part of automatic driving, and its performance directly determines the vehicle's movement performance and even the success of the task. In this review, the current research status of tractor–trailer vehicles is summarized, several main tracking control methods of the vehicles are classified, and the advantages and disadvantages of each method are summarized. At the same time, the existing problems and future development direction in this field are summarized and prospected.","PeriodicalId":201434,"journal":{"name":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","volume":"25 21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125767411","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}
Yong Li, Zhiyu Yuan, Y. Yang, C. Zhang, Weidong Xia
Based on the analysis of the overheating fault of the medium voltage switch cabinet, the necessity of online temperature monitoring of the medium voltage switch cabinet is discussed. On the basis of classifying and comparing the main current temperature measuring methods, a set of medium voltage switchboard temperature measuring system is studied. The design idea of each module of the system, the selection and assembly of hardware, the design of wireless transceiver module and PC software are described in detail. The performance of the assembled temperature monitoring system is tested. The experimental results show that the system is reliable and can achieve the purpose of real-time temperature monitoring.
{"title":"Research on Online Temperature Monitoring System in Medium Voltage Switching Cabinet","authors":"Yong Li, Zhiyu Yuan, Y. Yang, C. Zhang, Weidong Xia","doi":"10.1145/3548608.3559327","DOIUrl":"https://doi.org/10.1145/3548608.3559327","url":null,"abstract":"Based on the analysis of the overheating fault of the medium voltage switch cabinet, the necessity of online temperature monitoring of the medium voltage switch cabinet is discussed. On the basis of classifying and comparing the main current temperature measuring methods, a set of medium voltage switchboard temperature measuring system is studied. The design idea of each module of the system, the selection and assembly of hardware, the design of wireless transceiver module and PC software are described in detail. The performance of the assembled temperature monitoring system is tested. The experimental results show that the system is reliable and can achieve the purpose of real-time temperature monitoring.","PeriodicalId":201434,"journal":{"name":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130714434","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}
Single frame infrared dim and small target detection is always a difficult subject due to the lack of obvious target features and the difficulty of target extraction.In this paper, with the single frame infrared image dataset as the data source, and dim and small targets as the research object, infrared dim and small targets are extracted by separating the targets from the background. According to the task requirements, this paper proposes an infrared dim and small target extraction algorithm based on the improved HRNet. Based on HRNet, a semantic segmentation network, the algorithm optimizes the processing flow by introducing the attention mechanism module, so as to effectively extract the image surface features and improve the detection precision. In this paper, ablation experiments are conducted in detail in the single frame infrared small target (SIRST) dataset. A comparison is made of the effect of each attention mechanism module added to different positions of the network in HRNet Among them, when SE module (an attention mechanism module) is added to the first two steps of down-sampling in HRNet, the enhanced effect is most obvious, with the value of IoU reaching 76.9%. The experimental results show that the algorithm can be effective in detecting single frame infrared dim and small targets.
{"title":"DST-HRNet: Infrared dim and small target extraction algorithm based on improved HRNet","authors":"Guanting Li, Ping Wang, Tong Zhang","doi":"10.1145/3548608.3559205","DOIUrl":"https://doi.org/10.1145/3548608.3559205","url":null,"abstract":"Single frame infrared dim and small target detection is always a difficult subject due to the lack of obvious target features and the difficulty of target extraction.In this paper, with the single frame infrared image dataset as the data source, and dim and small targets as the research object, infrared dim and small targets are extracted by separating the targets from the background. According to the task requirements, this paper proposes an infrared dim and small target extraction algorithm based on the improved HRNet. Based on HRNet, a semantic segmentation network, the algorithm optimizes the processing flow by introducing the attention mechanism module, so as to effectively extract the image surface features and improve the detection precision. In this paper, ablation experiments are conducted in detail in the single frame infrared small target (SIRST) dataset. A comparison is made of the effect of each attention mechanism module added to different positions of the network in HRNet Among them, when SE module (an attention mechanism module) is added to the first two steps of down-sampling in HRNet, the enhanced effect is most obvious, with the value of IoU reaching 76.9%. The experimental results show that the algorithm can be effective in detecting single frame infrared dim and small targets.","PeriodicalId":201434,"journal":{"name":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130326263","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}
Shuangchang Feng, Yanchun Liang, Jie Chen, Kuangye Niu
The rated load capacity, counterweight and no-load car weight of the elevator are the technical basis for calculating the balance coefficient. The balance coefficient of the elevator is obtained by dividing the difference between the total weight of the counterweight device and the no-load car by the rated load capacity of the elevator. According to the requirements of GB7588-2003, the balance coefficient of traction driven elevator shall be in the range of 0.4-0.5. After the installation of the elevator, the balance coefficient will be tested. The current inspection specification TSG T7001-2009 stipulates that the balance coefficient test method is mainly through the current load curve method. This method needs to carry the weight repeatedly, measure the change of motor current, and obtain the specific value of balance coefficient by fitting the current and load curve. However, this method has high labor intensity and long operation time, requires frequent handling of weights and high labor intensity for operators. Therefore, in this paper, a weight cart for elevator balance coefficient test is designed, which can solve the technical problem of moving weights frequently.
{"title":"Design of Weight Cart for Elevator Balance Coefficient Test","authors":"Shuangchang Feng, Yanchun Liang, Jie Chen, Kuangye Niu","doi":"10.1145/3548608.3559238","DOIUrl":"https://doi.org/10.1145/3548608.3559238","url":null,"abstract":"The rated load capacity, counterweight and no-load car weight of the elevator are the technical basis for calculating the balance coefficient. The balance coefficient of the elevator is obtained by dividing the difference between the total weight of the counterweight device and the no-load car by the rated load capacity of the elevator. According to the requirements of GB7588-2003, the balance coefficient of traction driven elevator shall be in the range of 0.4-0.5. After the installation of the elevator, the balance coefficient will be tested. The current inspection specification TSG T7001-2009 stipulates that the balance coefficient test method is mainly through the current load curve method. This method needs to carry the weight repeatedly, measure the change of motor current, and obtain the specific value of balance coefficient by fitting the current and load curve. However, this method has high labor intensity and long operation time, requires frequent handling of weights and high labor intensity for operators. Therefore, in this paper, a weight cart for elevator balance coefficient test is designed, which can solve the technical problem of moving weights frequently.","PeriodicalId":201434,"journal":{"name":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131796055","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}
Zhipeng Li, Jiangtao Han, Yongzhi Wang, Yang Su, X. Ren
With the development of geophysical electromagnetic data processing and interpretation technology, it is very important to study new techniques and methods for developing electromagnetic software. Based on this background, this paper proposes a good method of sferic removal based on resource management and multi-language programming. This method introduces the mechanism to integrate Fortran and C# together in detailed including data conversion between two languages. Fortran algorithms are compiled as DLL libraries as back-end computing resource, WinForms developed by C# as front-end graphic user interface, users can use GUI to interact with back-end functions to complete sferic removal task. The experimental results show this method can deal with big sferic data and verify this way can work effectively and efficiently.
{"title":"Design and implementation of sferic removal method using multi-language programming","authors":"Zhipeng Li, Jiangtao Han, Yongzhi Wang, Yang Su, X. Ren","doi":"10.1145/3548608.3559314","DOIUrl":"https://doi.org/10.1145/3548608.3559314","url":null,"abstract":"With the development of geophysical electromagnetic data processing and interpretation technology, it is very important to study new techniques and methods for developing electromagnetic software. Based on this background, this paper proposes a good method of sferic removal based on resource management and multi-language programming. This method introduces the mechanism to integrate Fortran and C# together in detailed including data conversion between two languages. Fortran algorithms are compiled as DLL libraries as back-end computing resource, WinForms developed by C# as front-end graphic user interface, users can use GUI to interact with back-end functions to complete sferic removal task. The experimental results show this method can deal with big sferic data and verify this way can work effectively and efficiently.","PeriodicalId":201434,"journal":{"name":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131297034","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}
Gas user data has the characteristics of large amount of data and multiple attributes, while traditional user clustering algorithms usually use the distance between samples as the division standard of similarity. This distance calculation method ignores the influence of different data attributes on clustering. In order to solve this problem, this paper proposes a clustering algorithm based on PCA and attribute weighted distance (PAWDK). The method is divided into two stages: feature extraction and attribute weighted clustering. First, PCA is performed on the data to reduce redundant attributes; secondly, a method is defined. The dispersion function reflecting the difference of the attribute characteristics weights the attribute characteristics; then, the distance between the data attributes is calculated according to the weighted attribute characteristics, and the weighted attribute distance of all attributes is summed as the similarity distance between samples; finally, the weighted attribute distance is used as the division standard of kmeans clustering algorithm to cluster data. Experiments show that compared with other clustering methods, PAWDK can effectively reduce noise, achieve the goal of effectively clustering high-dimensional user data, and is closer to the characteristics of real user data set division.
{"title":"Research on Gas User Clustering Algorithm: Based on PCA and Attribute Weighting","authors":"Xinbo Ai, Qinfang Ji","doi":"10.1145/3548608.3559307","DOIUrl":"https://doi.org/10.1145/3548608.3559307","url":null,"abstract":"Gas user data has the characteristics of large amount of data and multiple attributes, while traditional user clustering algorithms usually use the distance between samples as the division standard of similarity. This distance calculation method ignores the influence of different data attributes on clustering. In order to solve this problem, this paper proposes a clustering algorithm based on PCA and attribute weighted distance (PAWDK). The method is divided into two stages: feature extraction and attribute weighted clustering. First, PCA is performed on the data to reduce redundant attributes; secondly, a method is defined. The dispersion function reflecting the difference of the attribute characteristics weights the attribute characteristics; then, the distance between the data attributes is calculated according to the weighted attribute characteristics, and the weighted attribute distance of all attributes is summed as the similarity distance between samples; finally, the weighted attribute distance is used as the division standard of kmeans clustering algorithm to cluster data. Experiments show that compared with other clustering methods, PAWDK can effectively reduce noise, achieve the goal of effectively clustering high-dimensional user data, and is closer to the characteristics of real user data set division.","PeriodicalId":201434,"journal":{"name":"Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131149343","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}
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