Fault Diagnosis of Rotating Machines Using Wavelet Transform and Neural Network

J. Ocean Eng. Technol. 2002;16(5):61-65.

웨이블렛 변환과 신경망 알고리즘을 이용한 회전기기 결함진단

최태묵,조대승

부산대학교 조선해양공학과 대학원,부산대학교 조선해양공학과

Keywords: Rotating Machinery, Fault Diagnosis, Wavelet Transform, Neural Network Algorithm

핵심용어: 회전기기, 결함 진단, 웨이블렛 변환, 신경망 알고리즘

Abstract

The fault detection and diagnosis of rotating machinery widely used in plants including the ship are important for maintaining the performance of Plants. Recently, the wavelet transform has been recognized an efficient method to detect a little variation of physical quantities by the synchronous localization of time and frequency domains using the translation and dilation of signals. In this Paper, In order to develop efficient and reliable fault detection and diagnosis system rotating machines, the performance of wavelet transformation to detect a little variation of machine status and neural network to diagnose the cause of machine faults are investigated and experimented.