{"title":"模式识别在航天飞行器结构损伤检测中的应用","authors":"S. Goswami, P. Bhattacharya","doi":"10.1109/EAIT.2012.6407890","DOIUrl":null,"url":null,"abstract":"A Pattern Recognition based damage detection scheme for aerospace vehicle structures is proposed. It involves capturing mechanical vibration signals from plate like structures using displacement sensors; removal of noise and extraction of features using Wavelet Transform based signal processing techniques, and training a Neural Network Ensemble to classify and identify the damages that appear in the structure. A few cases are studied. Encouraging results are found in classifying single damages in the structure. However success rates dropped in case of identifying multiple damages for the same structural form. A sensor placement strategy is then drawn out that improved the results significantly.","PeriodicalId":194103,"journal":{"name":"2012 Third International Conference on Emerging Applications of Information Technology","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Pattern Recognition for damage detection in aerospace vehicle structures\",\"authors\":\"S. Goswami, P. Bhattacharya\",\"doi\":\"10.1109/EAIT.2012.6407890\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A Pattern Recognition based damage detection scheme for aerospace vehicle structures is proposed. It involves capturing mechanical vibration signals from plate like structures using displacement sensors; removal of noise and extraction of features using Wavelet Transform based signal processing techniques, and training a Neural Network Ensemble to classify and identify the damages that appear in the structure. A few cases are studied. Encouraging results are found in classifying single damages in the structure. However success rates dropped in case of identifying multiple damages for the same structural form. A sensor placement strategy is then drawn out that improved the results significantly.\",\"PeriodicalId\":194103,\"journal\":{\"name\":\"2012 Third International Conference on Emerging Applications of Information Technology\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Third International Conference on Emerging Applications of Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EAIT.2012.6407890\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Third International Conference on Emerging Applications of Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EAIT.2012.6407890","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pattern Recognition for damage detection in aerospace vehicle structures
A Pattern Recognition based damage detection scheme for aerospace vehicle structures is proposed. It involves capturing mechanical vibration signals from plate like structures using displacement sensors; removal of noise and extraction of features using Wavelet Transform based signal processing techniques, and training a Neural Network Ensemble to classify and identify the damages that appear in the structure. A few cases are studied. Encouraging results are found in classifying single damages in the structure. However success rates dropped in case of identifying multiple damages for the same structural form. A sensor placement strategy is then drawn out that improved the results significantly.