A fault identification method of rotating machinerybased on t-SNE
A fault identification method ofrotating machinery is proposed,which combines wavelet packet of time-frequency analysis and manifold learning.Firstly,the sampled vibration signal is decomposed to multilayer information with wavelet packet decomposition(WPD)method.Andevery level data of wavelet packet decomposition is processed bydemodulatingof Hilbert transform.eliminating the high frequency noiseof FIR filterand reducing the data length of the low frequency of resampling.Further,every level data vector is deal with normalization and calculated for the auto power spectrum.Finally,the manifold learning methods of t distributed stochastic neighbor embedding(t-SNE)is applied to do dimension reduction to generate 2D manifold figure data.Different fault forms of gearbox have different manifold features.which is used to identify failure status of equipment.With the experiment test,the feasibility and effectiveness of this identification method is verified.
WPD Hilbert t-SNE 2D manifold figure data
Gu Yuhai He Linfeng Deng Yali
Beijing information science and technology university,Beijing 100192,China
国内会议
南京
英文
152-156
2016-10-01（万方平台首次上网日期，不代表论文的发表时间）