Lele Jin, Zhiwei Kou, Liqiang Liu, Yongsheng Qi, Xiaoming Cui
{"title":"基于改进BP神经网络的风机检测机器人多传感器信息融合算法研究","authors":"Lele Jin, Zhiwei Kou, Liqiang Liu, Yongsheng Qi, Xiaoming Cui","doi":"10.1109/IAEAC54830.2022.9929596","DOIUrl":null,"url":null,"abstract":"The functional structure of the fan operating system is complex, and the condition detection of a single signal source will inevitably result in errors and false alarms. The diagnostic method of information fusion can make full use of more information. Thus the problem can be avoided: the Fan Detection robot is equipped with multiple sensors, and these sensors are fused by a reasonable information fusion algorithm. The fused sensor information can obtain a more accurate statement of the fan. The purpose of saving cost and making the fan run stably aims to reduce man-made overhauls. BP neural network has the capability of non-linear mapping, self-learning and self-adaptation, and the fusion performance is good, the application of a wide range. Therefore, BP Neural Network algorithm can be chosen to carry out sensor information fusion.","PeriodicalId":349113,"journal":{"name":"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","volume":"287 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Research on multi-sensor information fusion algorithm of fan detection robot based on improved BP neural network\",\"authors\":\"Lele Jin, Zhiwei Kou, Liqiang Liu, Yongsheng Qi, Xiaoming Cui\",\"doi\":\"10.1109/IAEAC54830.2022.9929596\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The functional structure of the fan operating system is complex, and the condition detection of a single signal source will inevitably result in errors and false alarms. The diagnostic method of information fusion can make full use of more information. Thus the problem can be avoided: the Fan Detection robot is equipped with multiple sensors, and these sensors are fused by a reasonable information fusion algorithm. The fused sensor information can obtain a more accurate statement of the fan. The purpose of saving cost and making the fan run stably aims to reduce man-made overhauls. BP neural network has the capability of non-linear mapping, self-learning and self-adaptation, and the fusion performance is good, the application of a wide range. Therefore, BP Neural Network algorithm can be chosen to carry out sensor information fusion.\",\"PeriodicalId\":349113,\"journal\":{\"name\":\"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )\",\"volume\":\"287 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAEAC54830.2022.9929596\",\"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 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAEAC54830.2022.9929596","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on multi-sensor information fusion algorithm of fan detection robot based on improved BP neural network
The functional structure of the fan operating system is complex, and the condition detection of a single signal source will inevitably result in errors and false alarms. The diagnostic method of information fusion can make full use of more information. Thus the problem can be avoided: the Fan Detection robot is equipped with multiple sensors, and these sensors are fused by a reasonable information fusion algorithm. The fused sensor information can obtain a more accurate statement of the fan. The purpose of saving cost and making the fan run stably aims to reduce man-made overhauls. BP neural network has the capability of non-linear mapping, self-learning and self-adaptation, and the fusion performance is good, the application of a wide range. Therefore, BP Neural Network algorithm can be chosen to carry out sensor information fusion.