دورية أكاديمية
Fault Identification Method of Ball Bearing Based on IAs and SVMs
العنوان: | Fault Identification Method of Ball Bearing Based on IAs and SVMs |
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المؤلفون: | Chen Chao, Yang Zhaojun, Zhang Heng, Xu Binbin, Ye Yifeng, Wang Yankun |
المصدر: | MATEC Web of Conferences, Vol 77, p 01024 (2016) |
بيانات النشر: | EDP Sciences |
سنة النشر: | 2016 |
المجموعة: | Directory of Open Access Journals: DOAJ Articles |
مصطلحات موضوعية: | Engineering (General). Civil engineering (General), TA1-2040 |
الوصف: | In order to effectively identify the bearing running condition, this paper proposed a new method which combines local mean decomposition (LMD) and support vector machine (SVM) together for ball bearing fault identification. Firstly, the gathered vibration signals were decomposed into a number of product functions (PFs) by LMD, with each PF corresponding to an instantaneous amplitude (IA) signal and instantaneous frequency (IF) signal. Then, introduce the concept of fault characteristic amplitude ratios which can be used to construct fault feature vectors; the extracted characteristic features were input into SVM to train and construct the fault identification model; the bearing running state identification was thereby realized. Cases of normal and fault were analyzed. Experimental results show that the proposed algorithm can diagnose the bearing failures reasonable and efficient. |
نوع الوثيقة: | article in journal/newspaper |
اللغة: | English French |
تدمد: | 2261-236X |
العلاقة: | http://dx.doi.org/10.1051/matecconf/20167701024Test; https://doaj.org/toc/2261-236XTest; https://doaj.org/article/66d84e9e40144d98b19921cc04a8c082Test |
DOI: | 10.1051/matecconf/20167701024 |
الإتاحة: | https://doi.org/10.1051/matecconf/20167701024Test https://doaj.org/article/66d84e9e40144d98b19921cc04a8c082Test |
رقم الانضمام: | edsbas.18A898D1 |
قاعدة البيانات: | BASE |
تدمد: | 2261236X |
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DOI: | 10.1051/matecconf/20167701024 |