Yuguo Wang, Miaocong Shen, B. Han, Xiaochun Zhu, Jiaxiang Fei, Bin Xie
{"title":"基于电流信号的设备生产信息监控系统的开发","authors":"Yuguo Wang, Miaocong Shen, B. Han, Xiaochun Zhu, Jiaxiang Fei, Bin Xie","doi":"10.1109/cniot55862.2022.00020","DOIUrl":null,"url":null,"abstract":"Traditional machining equipment typically does not provide online production information such as part production quantities, efficiency and abnormal operating conditions. In order to solve this problem, a real-time production information monitoring system for traditional machining equipment based on electric current signal has been development. Firstly, the data acquisition hardware system using current sensors is designed to collect the electric current signal of the equipment being monitored. Next, the current data is processed by calibration algorithm to obtain production process feature vectors. Finally, a feature matching algorithm is used to identify the operating status. Based on the above algorithms, a monitoring software system is realized by C++ programming language on Qt platform. The monitoring experiment was carried out with automobile transmission shaft parts. The experimental results show that the machining start time and end time of each machined part are correctly and timely identified, and the abnormal state of the equipment could be accurately identified. The developed system is suitable for real-time monitoring of the traditional machining equipment.","PeriodicalId":251734,"journal":{"name":"2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of equipment production information monitoring system based on electric current signal\",\"authors\":\"Yuguo Wang, Miaocong Shen, B. Han, Xiaochun Zhu, Jiaxiang Fei, Bin Xie\",\"doi\":\"10.1109/cniot55862.2022.00020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional machining equipment typically does not provide online production information such as part production quantities, efficiency and abnormal operating conditions. In order to solve this problem, a real-time production information monitoring system for traditional machining equipment based on electric current signal has been development. Firstly, the data acquisition hardware system using current sensors is designed to collect the electric current signal of the equipment being monitored. Next, the current data is processed by calibration algorithm to obtain production process feature vectors. Finally, a feature matching algorithm is used to identify the operating status. Based on the above algorithms, a monitoring software system is realized by C++ programming language on Qt platform. The monitoring experiment was carried out with automobile transmission shaft parts. The experimental results show that the machining start time and end time of each machined part are correctly and timely identified, and the abnormal state of the equipment could be accurately identified. The developed system is suitable for real-time monitoring of the traditional machining equipment.\",\"PeriodicalId\":251734,\"journal\":{\"name\":\"2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/cniot55862.2022.00020\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/cniot55862.2022.00020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of equipment production information monitoring system based on electric current signal
Traditional machining equipment typically does not provide online production information such as part production quantities, efficiency and abnormal operating conditions. In order to solve this problem, a real-time production information monitoring system for traditional machining equipment based on electric current signal has been development. Firstly, the data acquisition hardware system using current sensors is designed to collect the electric current signal of the equipment being monitored. Next, the current data is processed by calibration algorithm to obtain production process feature vectors. Finally, a feature matching algorithm is used to identify the operating status. Based on the above algorithms, a monitoring software system is realized by C++ programming language on Qt platform. The monitoring experiment was carried out with automobile transmission shaft parts. The experimental results show that the machining start time and end time of each machined part are correctly and timely identified, and the abnormal state of the equipment could be accurately identified. The developed system is suitable for real-time monitoring of the traditional machining equipment.