Title :
State recognition system of mechanical equipment based on the VS theory and HSMM
Author :
Qiang Huang ; Qiuping Huang ; Jun Li
Author_Institution :
Jiujiang Univ., Jiujiang, China
Abstract :
It is significant to identify the running-states by obtaining and analyzing the vibration signals to avoid the faults. In this paper, the state recognition system is built based on the feature extraction with Varying Scale (VS) theory and Hidden Semi-Markov model (HSMM) with the example of bushing abrasion on diesel engine. The veracity of state identification can be improved effectively by banding them together. According to experiment and simulation researches, it indicates that the veracity of identification is 97.5% in the 120 test samples after training with 80 training samples. It is satisfied for the demand to the engineering domain and it can be applied for vibration analysis for other complex machineries.
Keywords :
abrasion; condition monitoring; diesel engines; fault diagnosis; feature extraction; hidden Markov models; mechanical engineering computing; vibrations; HSMM; VS theory; bushing abrasion; diesel engine; fault diagnosis; feature extraction; hidden semi Markov model; machineries; mechanical equipment; state recognition system; varying scale theory; vibration analysis; vibration signals; Diesel engines; Feature extraction; Hidden Markov models; Markov processes; Noise reduction; Training; Vibrations; Hidden semi-markov models; Signal analysis; State recognition; Varying scales theory;
Conference_Titel :
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Print_ISBN :
978-1-61284-087-1
DOI :
10.1109/EMEIT.2011.6023389
