改进的HHT方法在旋转机械不对中故障特征提取中的应用

HHT(希尔伯特-黄变换)能够将振动信号分解为有限的具有实际物理意义的模态分量,并由此可对机械故障信号进行特征提取,但噪声的干扰对分解过程和分解结果影响却很大。针对这一不足,本文提出了先利用小波变换技术对含噪故障信号进行消噪处理,再作HHT分析的方法;利用此方法对实测的不对中振动信号进行了故障特征提取和分析。结果表明,该方法克服了直接运用HHT分解方法由噪声带来的不必要的干扰,提高了参数提取的准确性,并由此提高了机械故障诊断率。

A Method for Misalignment Fault Diagnosis in Rotary Machine Based on Improved Hilbert-Huang Transform

Hilbert-Huang Transform(HHT) is a powerful method for nonlinear and non-stationary time series ana-lysis,and is widely used in machinery fault diagnosis.However,it is too sensitive to noise which seriously influences the process and result of Hilbert-Huang Transform.In this paper,an improved HHT method is presented.First,the polluted signal is processed through the signal denoising based on the wavelet transform.Then,it is analyzed by HHT.The real collected vibration signals with fault information are processed and analyzed through this improved method for further extraction and analysis of equipment fault diagnosis.The results indicate that the noises are reduced and the decomposition is more accurate.Thus,the diagnostic rate is improved.