用神经网络软件验证电机系统振动数据

M. Evans, A. Trzynadlowski
{"title":"用神经网络软件验证电机系统振动数据","authors":"M. Evans, A. Trzynadlowski","doi":"10.1109/IAS.1992.244464","DOIUrl":null,"url":null,"abstract":"Verification of vibration data in electromachine systems using neural network software is described. Due to a number of factors, the data are often corrupted and therefore it has been usually verified by a visual inspection. The developed neural networks were trained to screen out glitched and clipped waveforms. Satisfactory results were obtained, indicating the feasibility of neural networks for vibrational diagnostics.<<ETX>>","PeriodicalId":110710,"journal":{"name":"Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Verification of vibration data in electromachine systems using neural-network software\",\"authors\":\"M. Evans, A. Trzynadlowski\",\"doi\":\"10.1109/IAS.1992.244464\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Verification of vibration data in electromachine systems using neural network software is described. Due to a number of factors, the data are often corrupted and therefore it has been usually verified by a visual inspection. The developed neural networks were trained to screen out glitched and clipped waveforms. Satisfactory results were obtained, indicating the feasibility of neural networks for vibrational diagnostics.<<ETX>>\",\"PeriodicalId\":110710,\"journal\":{\"name\":\"Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAS.1992.244464\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAS.1992.244464","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

介绍了利用神经网络软件对电机系统振动数据进行验证的方法。由于许多因素,数据经常损坏,因此通常通过目视检查来验证。开发的神经网络被训练来筛除故障和剪切波形。结果令人满意,表明了神经网络用于振动诊断的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Verification of vibration data in electromachine systems using neural-network software
Verification of vibration data in electromachine systems using neural network software is described. Due to a number of factors, the data are often corrupted and therefore it has been usually verified by a visual inspection. The developed neural networks were trained to screen out glitched and clipped waveforms. Satisfactory results were obtained, indicating the feasibility of neural networks for vibrational diagnostics.<>
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信