کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6730442 | 504021 | 2016 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An improved fault detection method for incipient centrifugal chiller faults using the PCA-R-SVDD algorithm
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Detecting the faults at the incipient stage is important for keeping chiller systems healthy and saving energy and maintenance cost. Traditional principle component analysis (PCA) and support vector data description (SVDD) methods are insensitive to two common faults, condenser fouling (CdF) and refrigerant leakage (RfL). To improve the fault detection performance, this study proposed a PCA-R-SVDD based method. Instead of principle component subspace (PCs), it develops a SVDD model in the residual subspace (Rs) using the PCA modeling residual data. The SVDD based distance based monitoring statistic was used for fault detection. The proposed method shows significant improvement comparing with the traditional methods due to the better fault data distribution and tighter monitoring statistic. It is sensitive to six common faults. At least 50% of the fault data can be correctly detected even at the least severe fault level. Centrifugal chiller experimental data from the ASHRAE Research Project 1043 (RP-1043) was used to evaluate the methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy and Buildings - Volume 116, 15 March 2016, Pages 104-113
Journal: Energy and Buildings - Volume 116, 15 March 2016, Pages 104-113
نویسندگان
Guannan Li, Yunpeng Hu, Huanxin Chen, Limei Shen, Haorong Li, Min Hu, Jiangyan Liu, Kaizheng Sun,