Automatic feature extraction of waveform signals for in-process diagnostic performance improvement

Journal of Intelligent Manufacturing

Volumn 12, Issue 3, 2001, Pages 257-268

  Jin, Jionghua ^a   Shi, Jianjun ^b  

^a University of Arizona   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

Author keywords

Automatic feature extraction; Fault diagnosis; Haar transform; Process monitoring; Waveform signals

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DATA COMPRESSION; FEATURE EXTRACTION; FREQUENCY DOMAIN ANALYSIS; LEARNING SYSTEMS; PROCESS CONTROL; RANDOM PROCESSES; TIME DOMAIN ANALYSIS; WAVEFORM ANALYSIS; WAVELET TRANSFORMS;

AUTOMATIC FEATURE EXTRACTION; HAAR TRANSFORMS; PROCESS MONITORING; WAVEFORM SIGNALS;

COMPUTER INTEGRATED MANUFACTURING;

EID: 0035359901     PISSN: 09565515     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1011248925750     Document Type: Article

References (16)

1. Adapted waveform analysis and denoising
2. Model based fault diagnosis of industrial robot, a comparison of different methods
3. Ideal spatial adaptation via wavelet shrinkage
4. Multivariate quality control
5. Feature-preserving data compression of stamping tonnage information using wavelets
6. Online failure detection in face milling using discrete wavelet transform
7. Prediction of spalling on a ball bearing by applying the discrete wavelet transform to vibration signals
8. Monitoring drill condition with wavelet based encoding and neural networks
9. Multivariate control charts for individual observations