{"title":"自主水下航行器水质传感器信号突变检测新方法","authors":"Jie Shen, Xijun Yan, Zhen Sun, Guofang Lv, Hui Gu","doi":"10.1109/IMCCC.2015.274","DOIUrl":null,"url":null,"abstract":"Autonomous underwater vehicles (AUV) are equipped with a variety of water quality sensors. In this paper, we apply wavelet analysis theory to signals acquired by the AUV and develop a tool for identifying such malfunctions. This paper proposes an abrupt signal change detection method based on wavelet transforms. By selecting a threshold for the high-frequency wavelet coefficients, we were able to detect the abrupt signal. Three evaluation criteria were used in this study to assess signal-to-noise quality. These were combined with experimental analysis, noise detection, and a denoising method which is appropriate for detecting abrupt signal changes.","PeriodicalId":438549,"journal":{"name":"2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Method for Detection of Abrupt Signal Changes in Water Quality Sensors Onboard Autonomous Underwater Vehicles\",\"authors\":\"Jie Shen, Xijun Yan, Zhen Sun, Guofang Lv, Hui Gu\",\"doi\":\"10.1109/IMCCC.2015.274\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Autonomous underwater vehicles (AUV) are equipped with a variety of water quality sensors. In this paper, we apply wavelet analysis theory to signals acquired by the AUV and develop a tool for identifying such malfunctions. This paper proposes an abrupt signal change detection method based on wavelet transforms. By selecting a threshold for the high-frequency wavelet coefficients, we were able to detect the abrupt signal. Three evaluation criteria were used in this study to assess signal-to-noise quality. These were combined with experimental analysis, noise detection, and a denoising method which is appropriate for detecting abrupt signal changes.\",\"PeriodicalId\":438549,\"journal\":{\"name\":\"2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)\",\"volume\":\"70 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMCCC.2015.274\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMCCC.2015.274","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Method for Detection of Abrupt Signal Changes in Water Quality Sensors Onboard Autonomous Underwater Vehicles
Autonomous underwater vehicles (AUV) are equipped with a variety of water quality sensors. In this paper, we apply wavelet analysis theory to signals acquired by the AUV and develop a tool for identifying such malfunctions. This paper proposes an abrupt signal change detection method based on wavelet transforms. By selecting a threshold for the high-frequency wavelet coefficients, we were able to detect the abrupt signal. Three evaluation criteria were used in this study to assess signal-to-noise quality. These were combined with experimental analysis, noise detection, and a denoising method which is appropriate for detecting abrupt signal changes.