关键词: Lipschitz指数, Θ-s曲线, 局部极大模, 小波变换, 轴心轨迹, 故障诊断, 航空发动机, 奇异值分解, 声模态, 压气机

Abstract: A novel approach for identification of shaft center orbits is proposed, which bases on wavelet modulus maxima. In this approach, continuous wavelet transforrn is put on @-S diagram of shaft center orbits, then, maxima Iines are extracted and Lipschltz exponents a of every maxima line are calculated by non-linear least square method. The number of maxima Iines with positive a, the mean of the positive a, the number of maxima Iines with negative a and the mean of the negative a are used as features of the shaft center orbits. In succession, the four features are used as the inputs of BP network to classify shaft center orbits. The experimental data of four kinds of faults: rub-impact, oil vvhirl, coupling misalignment and unbalance are used to test the vvavelet modulus maxima based method. The test result indicates that the method can fulfill classification accurately and the method possesses advantages of few features used and of fast training processing of nervvork.

Key words: Shaft center orbit, 8-s diagram, Wavelet transform Modulus maxima Lipschitz exponent, Acoustic mode, Aero-engine, Compressor, Failure diagnosis, Singular value decomposition(SVD)