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2報,ノイズ低減による故障診断への応用(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 II of a pair, illustrates the advantage of the wavelet de-noising procedure on a range of practical examples. We have made a comparison of failure detection-ability between envelope estimator and wavelet-based estimator under the noise condition of machinery. Experiment results have shown that using wavelet de-noising procedure is an effective means to extract early symptoms of machine fault form the heavy noise condition of machinery.
社団法人日本機械学会の論文
2003-11-25