کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
509110 865482 2011 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Using SVM based method for equipment fault detection in a thermal power plant
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Using SVM based method for equipment fault detection in a thermal power plant
چکیده انگلیسی

Due to the growing demand on electricity, how to improve the efficiency of equipment in a thermal power plant has become one of the critical issues. Reports indicate that efficiency and availability are heavily dependant upon high reliability and maintainability. Recently, the concept of e-maintenance has been introduced to reduce the cost of maintenance. In e-maintenance systems, the intelligent fault detection system plays a crucial role for identifying failures. Data mining techniques are at the core of such intelligent systems and can greatly influence their performance. Applying these techniques to fault detection makes it possible to shorten shutdown maintenance and thus increase the capacity utilization rates of equipment. Therefore, this work proposes a support vector machines (SVM) based model which integrates a dimension reduction scheme to analyze the failures of turbines in thermal power facilities. Finally, a real case from a thermal power plant is provided to evaluate the effectiveness of the proposed SVM based model. Experimental results show that SVM outperforms linear discriminant analysis (LDA) and back-propagation neural networks (BPN) in classification performance.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Industry - Volume 62, Issue 1, January 2011, Pages 42–50
نویسندگان
, , , ,