ترجمه کامپیوتر و مکانیک- 14 صفحه
سال 2008
Optimal feature selection using genetic algorithm for mechanical fault detection of induction motor
انتخاب ویژگی بهینه با استفاده از ژنتیک الگوریتم برای تشخیص نقص مکانیکی موتور القایی
Ngoc-Tu NguyenHong-Hee Lee -Jeong-Min Kwon
http://link.springer.com/article/10.1007/s12206-007-1036-3
دانلود رایگان مقاله انگلیسی - انتخاب ویژگی بهینه با استفاده از ژنتیک الگوریتم
چکیده
علامات لرزش در حوزه زمان در تما م جهات عمودی ,محوری,افقی برای تشخیص نقص موتور القایی مکانیکی اندازه گیری می شود. خیلی ویژگیها از این علامات اقتباس می شود.مشکلی که وجود دارد چگونه پیدا کردن ویژگیهای خوب از میان ویژگی تنظیم شده به منظور دریافت طبقه بندی منعطف است.بر اساس موضوع فاصله ثابت,یک GAتعداد ویژگیهای طبقه بندی اشکال را به وسیله انتخاب بهینه کاهش می دهد.یک درخت تصمیم گیری و ماشین برداری چندگانه برای نشان دادن توانایی و کارایی این شیوه انتخاب استفاده می شوند.مقایسه ها نشان داده که سیستم های تشخیص بعد از انتخاب ویژگی مخصوص عملکرد بهتری نسبت به سیستم معمولی دارند.
کلمات کلیدی:درخت تصمیم گیری,ماشین پشتیبان برداری,GA,موتور القایی,تشخیص نقص مکانیکی
Abstract
Time-domain vibration signals are measured in all horizontal, axial, and vertical directions for induction motor mechanical fault diagnostics. Many features are extracted from these signals. The problem is how to find the good features among the feature set in order to receive reliable classifications. Based on specific distance criteria, a genetic algorithm (GA) is introduced to reduce the number of features by selecting optimized ones for fault classification purpose. A decision tree and multi-class support vector machine are used to illustrate the potentiality and efficiency of this selection method. Comparisons show that the diagnostic systems after selecting specific features perform better than the original system.
Keywords
Mechanical fault detection Induction motor Genetic algorithm Support vector machine Decision tree
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