Fault diagnosis of analog circuit using spectrogram and LVQ neural network

Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015

Volumn , Issue , 2015, Pages 2673-2678

  Li, Penghua ^a   Zhang, Shunxing ^a   Luo, Dechao ^b   Luo, Hongping ^a  

^a CHONGQING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^b China Automotive Engineering Research Institute   (China)

Author keywords

Analog Fault Diagnosis; Learning Vector Quantization; Local Binary Patterns; Spectrogram

Indexed keywords

ANALOG CIRCUITS; FAILURE ANALYSIS; HIGH PASS FILTERS; NEURAL NETWORKS; SPECTROGRAPHS; TIMING CIRCUITS; VECTOR QUANTIZATION;

ANALOG FAULT DIAGNOSIS; FEATURE EXTRACTION TECHNIQUES; LEARNING VECTOR QUANTIZATION; LEARNING VECTOR QUANTIZATION NEURAL NETWORK; LOCAL BINARY PATTERN (LBP); LOCAL BINARY PATTERNS; SHORT TIME FOURIER TRANSFORMS; SPECTROGRAMS;

FAULT DETECTION;

EID: 84945563649     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CCDC.2015.7162384     Document Type: Conference Paper

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