کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
710251 892106 2009 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fault Detection and Diagnosis for Nonlinear Systems: A Support Vector Machine Approach
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مکانیک محاسباتی
پیش نمایش صفحه اول مقاله
Fault Detection and Diagnosis for Nonlinear Systems: A Support Vector Machine Approach
چکیده انگلیسی

AbstractIn this paper, a fault detection and diagnosis (FDD) technique for nonlinear systems based on support vector machines (SVM) is presented. Support vector regression (SVR) has been used in fault detection process and support vector classification (SVC) has been used in diagnosis process. In fault detection process, the confidence band idea represents the normal operating conditions of the system. The upper and the lower boundaries of the confidence band are modelled by two different SVR machines. A fault is detected when an output signal exceeds the upper or lower bounds of the generated confidence band. A support vector multi-classification method, one-against-all, has been used to classify the occurring fault within the group of expected and predefined faults in technical system. The performance of the proposed FDD method is illustrated on simulation example involving a two-tank water level control system under faulty conditions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: IFAC Proceedings Volumes - Volume 42, Issue 19, 2009, Pages 355–360
نویسندگان
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