Jin-Yi Deng, Hao Feng, Yu Bai, H. Zhan, Dong-Xiu Feng, Kaixiang Guo, Rong Zeng, Jian-Jian Xia, Yong-Jun Xie
{"title":"基于惯性参考法的沟槽轨道不平顺度动态检测","authors":"Jin-Yi Deng, Hao Feng, Yu Bai, H. Zhan, Dong-Xiu Feng, Kaixiang Guo, Rong Zeng, Jian-Jian Xia, Yong-Jun Xie","doi":"10.1109/ICNSC48988.2020.9238093","DOIUrl":null,"url":null,"abstract":"In recent years, modern tramcar has developed rapidly. The grooved rail is used widely in its main line track. However, at present, the main detection method of its geometric parameters of grooved rail is manual detection, with low working efficiency. Therefore, this paper proposes a set of dynamic detection system of grooved rail irregularity based on inertial reference method, which can realize the detection of grooved rail irregularity such as longitudinal irregularity, alignment irregularity, etc. On the basis of previous work, improvement & application of measuring longitudinal irregularity and alignment irregularity has been proposed. The key points of this improved algorithm are to put forward synthesized filtering algorithm based upon grooved rail's geometric features, which enhances the stability of the detect system; and use the frequency domain integration algorithm, which improves the accuracy of the detect system. Experiment verification shows that the dynamic detection system has the characteristics of high detection accuracy and splendid stability, which provides a new tool for dynamic detection of geometric parameters of grooved rail of modern tramcars.","PeriodicalId":412290,"journal":{"name":"2020 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Dynamic Detection of Grooved Rail Irregularity Based on Inertial Reference Method\",\"authors\":\"Jin-Yi Deng, Hao Feng, Yu Bai, H. Zhan, Dong-Xiu Feng, Kaixiang Guo, Rong Zeng, Jian-Jian Xia, Yong-Jun Xie\",\"doi\":\"10.1109/ICNSC48988.2020.9238093\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, modern tramcar has developed rapidly. The grooved rail is used widely in its main line track. However, at present, the main detection method of its geometric parameters of grooved rail is manual detection, with low working efficiency. Therefore, this paper proposes a set of dynamic detection system of grooved rail irregularity based on inertial reference method, which can realize the detection of grooved rail irregularity such as longitudinal irregularity, alignment irregularity, etc. On the basis of previous work, improvement & application of measuring longitudinal irregularity and alignment irregularity has been proposed. The key points of this improved algorithm are to put forward synthesized filtering algorithm based upon grooved rail's geometric features, which enhances the stability of the detect system; and use the frequency domain integration algorithm, which improves the accuracy of the detect system. Experiment verification shows that the dynamic detection system has the characteristics of high detection accuracy and splendid stability, which provides a new tool for dynamic detection of geometric parameters of grooved rail of modern tramcars.\",\"PeriodicalId\":412290,\"journal\":{\"name\":\"2020 IEEE International Conference on Networking, Sensing and Control (ICNSC)\",\"volume\":\"55 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Networking, Sensing and Control (ICNSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNSC48988.2020.9238093\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Networking, Sensing and Control (ICNSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNSC48988.2020.9238093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic Detection of Grooved Rail Irregularity Based on Inertial Reference Method
In recent years, modern tramcar has developed rapidly. The grooved rail is used widely in its main line track. However, at present, the main detection method of its geometric parameters of grooved rail is manual detection, with low working efficiency. Therefore, this paper proposes a set of dynamic detection system of grooved rail irregularity based on inertial reference method, which can realize the detection of grooved rail irregularity such as longitudinal irregularity, alignment irregularity, etc. On the basis of previous work, improvement & application of measuring longitudinal irregularity and alignment irregularity has been proposed. The key points of this improved algorithm are to put forward synthesized filtering algorithm based upon grooved rail's geometric features, which enhances the stability of the detect system; and use the frequency domain integration algorithm, which improves the accuracy of the detect system. Experiment verification shows that the dynamic detection system has the characteristics of high detection accuracy and splendid stability, which provides a new tool for dynamic detection of geometric parameters of grooved rail of modern tramcars.