کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
11007317 | 1521075 | 2018 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Fault identification in PCA method during sensor condition monitoring in a nuclear power plant
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
مهندسی انرژی و فناوری های برق
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Principal component analysis (PCA) is applied in this paper for sensor condition monitoring in a nuclear power plant (NPP). Based on the results of fault detection with PCA method, two different fault identification methods are applied simultaneously to locate the faulty sensor. One is the improved weighted contribution analysis (WCA) method which is based on traditional contribution analysis (TCA) of sensors to Q statistics. The other fault identification method is based on sensor validity index (SVI) in which the iterative reconstruction method is applied to locate the faulty sensor more accurately and quickly. Finally, the fault identification abilities of TCA, WCA and SVI are evaluated with sensor measurements from a real NPP. According to the simulation results, the improved WCA method presents better fault identification performance no matter with single or double sensor faults in the testing samples, and with single sensor fault in the testing samples, SVI method not only can verify the fault identification results by WCA method, but also can accurately reconstruct the measurements of faulty sensor as required during fault identification.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Annals of Nuclear Energy - Volume 121, November 2018, Pages 135-145
Journal: Annals of Nuclear Energy - Volume 121, November 2018, Pages 135-145
نویسندگان
Wei Li, Minjun Peng, Qingzhong Wang,