ウェーブレット技法を用いたころがり軸受の故障診断法 : 第1報,ウェーブレット縮退によるノイズ低減についての解析(機械力学,計測,自動制御)

概要

論文の詳細を見る
Extracting symptom of bearing faults from noisy signal is a key problem to detect early faults of machinery. An effective method is presented for improving the signal to noise ratio by the wavelet transforms. The paper, which is Part I of a pair, describes wavelet de-noising algorithms and their properties. The relationship between the thresholds for wavelet coefficients and the ability of wavelet de-noise under Gaussian noise is discussed. The advantage of the wavelet de-noising procedure on simulated data is illustrated. Simulated results have shown that using wavelet de-noising procedure is an effective means to extract the signal from noisy data.
社団法人日本機械学会の論文
2003-11-25