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Автор Hahn, H.T.
Автор Wilkerson, B.
Автор Stuart, J.
Дата выпуска 1994
dc.description An artificial neural network has been developed that can analyze signals from piezoelectric sensors to detect the location and intensity of low-energy impact on a composite panel. The panel has two piezopolymer sensors attached some distance apart from each other. The signals are analyzed by the artificial neural network using a binary pattern associator. The binary pattern associator facilitates memory build-up during learn ing while simplifying signal discrimination during testing. The impact monitoring system, which consists of the artificial neural network and the piezoelectric sensors, has been used successfully to detect the location and height of impact when a small steel ball is dropped onto a composite laminate.
Издатель Sage Publications
Название An Artificial Neural Network for Low-Energy Impact Monitoring
Тип Journal Article
DOI 10.1177/089270579400700404
Print ISSN 0892-7057
Журнал Journal of Thermoplastic Composite Materials
Том 7
Первая страница 344
Последняя страница 351
Аффилиация Hahn, H.T., Mechanical, Aerospace and Nuclear Engineering Department UCLA Los Angeles, CA 90024-1597
Аффилиация Wilkerson, B., Engineering Science and Mechanics Department The Pennsylvania State University University Park, PA 16802
Аффилиация Stuart, J., Engineering Science and Mechanics Department The Pennsylvania State University University Park, PA 16802
Выпуск 4
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Библиографическая ссылка Kim, I.-G., H.T. Hahn and D. Weems. 1992. "Impact Detection in Smart Composite Structures Using Piezoelectric Sensors," Proc. 6th U.S.-Japan Conf. on Composite Materials, pp. 201-212.
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