关键词: 频带混叠, 平移不变性, 双密度双树复小波, 信号降噪, β-环糊精, 包合物, 二烃五硫化物, 磨削性能, 自润滑砂轮

Abstract: In order to improve the deficiencies of classical discrete wavelet transform in extracting early and incipient machinery fault features, double density dual tree complex wavelet basis(DDCWT) is designed by introducing feasible redundancy in the filter bank. The filter bank of DDCWT consists of 2 scaling functions and four wavelet functions which form two Hilbert-coupled wavelet transform pairs, rendering DDCWT basis high regularity, nearly linear phase and nearly shift-invariance. In frequency partition, the central frequencies of DDCWT’s subbands are embedded in transition bands of adjacent subbands of classical wavelet basis, thus achieving better performance in extracting features in transition bands of the latter. By applying DDCWT in a heavy horizontal lathe assembly examination, an assemble fault is detected. In addition, a de-noising method combing neighboring coefficients shrinkage strategy and stationary DDCWT is proposed and this method is applied in fault diagnosis of a gearbox in hot rolling mill. The de-noising method successfully extracts the two-site tooth fault features on the same gear.

Key words: Double density dual tree complex wavelet transform, Frequency aliasing, Shift invariance, Signal de-noising, dialkyl pentasulfide, grinding performance, inclusion, self -lubricated grinding wheel, β-cyclodextrin