Earticle

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

Abstract
 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

키워드

저자

• Basavaraj S. Anami [ KLE Institute of Technology, Hubli-580030, India ]
• Veerappa B. Pagi [ Basaveshwar Engineering College, Bagalkot-587102, India ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Advanced Science and Technology

• 간기

  월간

• pISSN

  2005-4238

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605