Yong Guk Kim, YoungShin Kim, S. H. Lee, Sang-Taeck Moon, M. Jeon, H. Kim
{"title":"被动声呐系统的水声传感器故障检测","authors":"Yong Guk Kim, YoungShin Kim, S. H. Lee, Sang-Taeck Moon, M. Jeon, H. Kim","doi":"10.1109/SPLIM.2016.7528395","DOIUrl":null,"url":null,"abstract":"In this paper, an underwater acoustic sensor fault detection method is proposed that determines whether or not each sensor of multi-channel line array hydrophones malfunctions for passive sonar systems. To this end, the proposed method first measures a short-time root mean square (RMS) value of input signal for each channel. Then, it analyzes the RMS difference between the adjacent channels. In addition, the crossing rate of RMS values (RMSCR) is computed for each channel, and then the average value of RMSCR over all the channels is obtained. Some faulty sensors are identified by comparing the RMS difference with a threshold, and others by comparing the ratio between RMSCR of each of them and the average value of RMSCR with a threshold. In order to evaluate the performance of the proposed method, the precision of detecting fault sensors is measured. Consequently, it is shown that the proposed method works well in underwater environments with average RMS of -18.6 and -9.7 dB.","PeriodicalId":297318,"journal":{"name":"2016 First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Underwater acoustic sensor fault detection for passive sonar systems\",\"authors\":\"Yong Guk Kim, YoungShin Kim, S. H. Lee, Sang-Taeck Moon, M. Jeon, H. Kim\",\"doi\":\"10.1109/SPLIM.2016.7528395\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an underwater acoustic sensor fault detection method is proposed that determines whether or not each sensor of multi-channel line array hydrophones malfunctions for passive sonar systems. To this end, the proposed method first measures a short-time root mean square (RMS) value of input signal for each channel. Then, it analyzes the RMS difference between the adjacent channels. In addition, the crossing rate of RMS values (RMSCR) is computed for each channel, and then the average value of RMSCR over all the channels is obtained. Some faulty sensors are identified by comparing the RMS difference with a threshold, and others by comparing the ratio between RMSCR of each of them and the average value of RMSCR with a threshold. In order to evaluate the performance of the proposed method, the precision of detecting fault sensors is measured. Consequently, it is shown that the proposed method works well in underwater environments with average RMS of -18.6 and -9.7 dB.\",\"PeriodicalId\":297318,\"journal\":{\"name\":\"2016 First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPLIM.2016.7528395\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPLIM.2016.7528395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Underwater acoustic sensor fault detection for passive sonar systems
In this paper, an underwater acoustic sensor fault detection method is proposed that determines whether or not each sensor of multi-channel line array hydrophones malfunctions for passive sonar systems. To this end, the proposed method first measures a short-time root mean square (RMS) value of input signal for each channel. Then, it analyzes the RMS difference between the adjacent channels. In addition, the crossing rate of RMS values (RMSCR) is computed for each channel, and then the average value of RMSCR over all the channels is obtained. Some faulty sensors are identified by comparing the RMS difference with a threshold, and others by comparing the ratio between RMSCR of each of them and the average value of RMSCR with a threshold. In order to evaluate the performance of the proposed method, the precision of detecting fault sensors is measured. Consequently, it is shown that the proposed method works well in underwater environments with average RMS of -18.6 and -9.7 dB.