Current and Vibration Signal Feature Engineering for Defect Classification in Rotary Machines
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-4270-1_33
Reference7 articles.
1. William PE, Hoffman MW (2011) Identification of bearing faults using time domain zero-crossings. Mech Syst Sig Proc 25(2011):3078–3088
2. Nayana BR, Geethanjali P (2017) Analysis of statistical time-domain features effectiveness in identification of bearing faults from vibration signal. IEEE Sens J 17(17)
3. Gowid S, Dixon R, Ghani S (2016) Performance comparison between FFT-based segmentation, feature selection and fault identification algorithm and neural network for the condition monitoring of centrifugal equipment. J Dyn Syst, Measur Control 139. https://doi.org/10.1115/1.4035458
4. Allal A, Khechekhouche A (2022) Diagnosis of induction motor faults using the motor current normalized residual harmonic analysis method. Int J Electric Power Energy Syst 141:108219. ISSN 0142-0615, https://doi.org/10.1016/j.ijepes.2022.108219
5. Gritli Y, Di Tommaso AO, Filippetti F, Miceli R, Rossi C, Chatti A (2012) Investigation of motor current signature and vibration analysis for diagnosing rotor broken bars in double cage induction motors. In: International symposium on power electronics power electronics, electrical drives, automation and motion, pp 1360–1365. https://doi.org/10.1109/SPEEDAM.2012.6264465
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3