{"title":"信号处理和神经网络技术在多层介质超声表征中的应用","authors":"J. Rouvaen, K. Harrouche, M. Ourak, B. El Khaldi","doi":"10.1109/ULTSYM.1994.401690","DOIUrl":null,"url":null,"abstract":"The characterization of multilayered media using ultrasonic waves is classically performed using time of flight reflectometry in the pulsed regime or spectroscopy in the quasi-continuous wave regime. Our aim is to study the performances improvements given by numeric signal processing and neural nets methods. Starting from simple models for layered media, the reflection coefficient for high frequency pulsed ultrasonic waves is computed. The application of homomorphic processing techniques is studied theoretically, taking the transducer frequency response and the overall measurement system signal to noise ratio into account. Neural nets are then considered and it is shown that they provide a valid response in situations where other methods fail","PeriodicalId":394363,"journal":{"name":"1994 Proceedings of IEEE Ultrasonics Symposium","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Application of signal processing and neural net techniques to ultrasonic characterization of multilayered media\",\"authors\":\"J. Rouvaen, K. Harrouche, M. Ourak, B. El Khaldi\",\"doi\":\"10.1109/ULTSYM.1994.401690\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The characterization of multilayered media using ultrasonic waves is classically performed using time of flight reflectometry in the pulsed regime or spectroscopy in the quasi-continuous wave regime. Our aim is to study the performances improvements given by numeric signal processing and neural nets methods. Starting from simple models for layered media, the reflection coefficient for high frequency pulsed ultrasonic waves is computed. The application of homomorphic processing techniques is studied theoretically, taking the transducer frequency response and the overall measurement system signal to noise ratio into account. Neural nets are then considered and it is shown that they provide a valid response in situations where other methods fail\",\"PeriodicalId\":394363,\"journal\":{\"name\":\"1994 Proceedings of IEEE Ultrasonics Symposium\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1994 Proceedings of IEEE Ultrasonics Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ULTSYM.1994.401690\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1994 Proceedings of IEEE Ultrasonics Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ULTSYM.1994.401690","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of signal processing and neural net techniques to ultrasonic characterization of multilayered media
The characterization of multilayered media using ultrasonic waves is classically performed using time of flight reflectometry in the pulsed regime or spectroscopy in the quasi-continuous wave regime. Our aim is to study the performances improvements given by numeric signal processing and neural nets methods. Starting from simple models for layered media, the reflection coefficient for high frequency pulsed ultrasonic waves is computed. The application of homomorphic processing techniques is studied theoretically, taking the transducer frequency response and the overall measurement system signal to noise ratio into account. Neural nets are then considered and it is shown that they provide a valid response in situations where other methods fail