원문정보
초록
영어
Motorcycles generate different sound patterns under dissimilar working conditions. The generated sound pattern gives a clue of the fault. Mainly the parts of the engine that lead to change in sound are cylinder kit, crank, timing chain, and valve. The parts of the exhaust system that change sound under fault are muffler and silencer. In this study, we analyze the sound signals produced by motorcycles to locate the faults in subsystems. The work proceeds in three stages, the first stage detects the fault, the second stage identifies the faulty subsystem and finally the third stage locates the fault. The overall classification accuracy of the first stage is 0.8019. The work finds interesting applications in troubleshooting of machinery, electronic gadgets, musical instruments and the like.
목차
1. Introduction
2. Review of Literature
3. Proposed Methodology
3.1. Acquisition of Sound Samples
3.2. Segmentation
3.3. Wavelet Packet Feature Extraction
3.4. Artificial Neural Network
4. Results
4.1. Stage 1. Fault Detection
4.2. Stage 2. Subsystem Identification
4.3. Stage 3. Fault Source Localization
4.4. Discussion
5. Conclusion
Acknowledgment
References