Sensor noise and fault judging method based on sparse representation
作者： Xing Zhanqiang , Ji Junjie , Qu Jianfeng , Chai Yi , Ren Hao
DOI:
关键词: Subspace topology 、 Sparse approximation 、 Data set 、 Representation (mathematics) 、 Algorithm 、 Noise (signal processing) 、 Fault (power engineering) 、 Sample (statistics) 、 Signal 、 Computer science
摘要: The invention discloses a sensor noise and fault judging method based on sparse representation. specific includes the following steps: 1. an overcomplete atom library containing normal signals, samples corresponding thereto is built through historical data; 2. hypothesis that linear representation of unknown some category can be effectively realized in subspace by plurality category, mixed signal collected performed with dictionary, i.e., atoms best matched to decomposed found out from are subjected reconstruction obtain new mode; 3. error sample calculated, reconstructed use data set each kind obtained; 4. same used perform training calculate value; 5. judgment calculation error.
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