کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7545347 | 1489596 | 2018 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An Image Processing Approach to Machine Fault Diagnosis Based on Visual Words Representation
ترجمه فارسی عنوان
یک روش پردازش تصویر برای تشخیص خطاهای ماشین بر اساس نمایه واژه های دیداری
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کلمات کلیدی
نظارت بر وضعیت، تشخیص الگو، مهندسی قابلیت اطمینان،
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی صنعتی و تولید
چکیده انگلیسی
Machine fault diagnosis and remaining service life prognosis provide the basis for condition-based maintenance, and is key to operational reliability. Accurate assessment of machine health requires effective analysis of vibration data, which is typically performed by examining the change in frequency components. One limitation associated with these methods is the empirical knowledge required for fault feature selection. This paper presents an image processing approach to automatically extract features from vibration signal, based on visual words representation. Specifically, a time-frequency image of vibration signal is obtained through wavelet transform, which is then used to extract “visual word” features for recognizing fault related patterns. The extracted features are subsequently fed into sparse representation-based classifier for classification. Evaluation using experimental bearing data confirmed the effectiveness of the developed method with a classification accuracy of 99.7%.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Manufacturing - Volume 19, 2018, Pages 42-49
Journal: Procedia Manufacturing - Volume 19, 2018, Pages 42-49
نویسندگان
Jianjing Zhang, Peng Wang, Robert X. Gao, Ruqiang Yan,