摘要
针对Volterra级数模型在染噪时间序列预测中精度较低,以及收敛速度慢的关键问题,提出了一种基于冗余提升小波包(Redundant Lifting Wavelet Packet,RLWP)及Volterra级数的机械故障预测方法。首先用冗余提升小波包对振动信号进行分解,对分解得到的末层所有频带信号用奇异值分解进行降噪。然后通过构造二阶Volterra级数预测模型对降噪后的各频带信号进行预测。最后用冗余提升小波包重构算法对各频带预测信号重构,获得预测信号。仿真结果表明:结合冗余提升小波包的多分辨率分析及奇异值降噪,能明显提高Volterra级数模型的预测精度及收敛速度。在工程应用中该方法准确预测出了某离心压缩机的不平衡故障。
Considering that the disadvantages of low accuracy and slow convergence rate when using the Volterra series model to predict noisy time series,a new prediction method of mechanical failure based on redundant lifting wavelet packet（RLWP） and Volterra series was presented.Firstly,the vibration signal was decomposed using RLWP algorithm and the sub-bands of the final layer were denoised using singular value decomposition.Then the denoised signal in each band was separately predicted by the constructed second order Volterra series.Finally,the prediction signal was reconstructed using reconstruction algorithm of RLWP.Simulation signal demonstrated that the proposed method can obviously improve the prediction precision and convergence rate.In engineering application,the rotor imbalance failure of a centrifugal compressor was exactly predicted,showing that this method is valid and practicable.
出处
《科学技术与工程》
北大核心
2013年第17期4922-4926,共5页
Science Technology and Engineering
基金
国家自然科学基金(51005247)
北京市教委科研基地建设项目资助
关键词
故障预测
冗余提升小波包
VOLTERRA级数
奇异值分解
多分辨率分析
failure prediction redundant lifting wavelet packet Volterra series singular value decomposition multiresolution analysis
