摘要
快速谱峭度(Fast Kurtogram,FK)通过构造有限冲击响应滤波器从频谱上将信号二分或三分为几个不同频带的分量后,判断每个分量的谱峭度大小以提取调制信息。该方法运算速度很快,但有时包含故障信息的频段无法被均分的谱峭度图容纳,甚至可能导致提取出的分量中无法检测到明显的故障信息。提出一种新的频谱边界划分方法用以优化快速谱峭度,并称之为经验快速谱峭度(Empirical Fast Kurtogram,EFK)。首先,将信号频谱的傅里叶变换函数中代表频谱趋势的成分提取出来,并搜索其极小值点序列;然后,以极小值点在频谱中的位置作为频谱划分的边界,采用Meyer小波构造滤波器并重构信号分量以求取峭度;最终,构造出一种新的快速谱峭度图,选择谱峭度最大的频段提取故障信息。该方法依据信号频谱的趋势划分边界可以有效地避免由于均分频谱导致的不合理现象,模拟信号及滚动轴承内圈、外圈故障信号证明了该方法的有效性。
Fast kurtogram(FK)can be applied to rolling bearing and gearbox fault diagnosis.A finite impulse response filter is constructed to divide the signal into two or three components containing different frequency information from spectrum.Then,whether the spectral kurtosis of each component has failed is determined.The method is fast,but sometimes it is unable to accommodate those bands that actually contain fault information.It may even result in the inability to detect significant fault information from the extracted components.Therefore,FK has obvious and even fatal flaws in dividing the frequency domain.A new method to divide boundaries from the spectrum to optimize the FK is proposed.It is named empirical fast kurtogram(EFK).Firstly,the components representing the spectrum trend in the Fourier transform function of the signal spectrum are extracted and the minimum point sequence is searched.Taking the position of the minimum value in the spectrum as the boundary sequence,the Meyer wavelet is used to construct the filter and reconstruct the signal components to obtain the kurtosis.Finally,a new empirical fast kurtogram is constructed and the fault information is extracted from the frequency band with the largest kurtosis.The method divides boundaries according to the spectrum trend,which can effectively avoid the irrational phenomenon caused by the average spectrum division in the FK method.The effectiveness of the method is demonstrated by the analog signal and the inner and outer ring fault signals of the rolling bearing.
作者
张坤
胥永刚
马朝永
张浩
盛志鹏
ZHANG Kun;XU Yong-gang;MA Chao-yong;ZHANG Hao;SHENG Zhi-peng(Key Laboratory of Advanced Manufacturing Technology,Beijing University of Technology,Beijing 100124,China;Beijing Engineering Research Center of Precision Measurement Technology and Instruments,Beijing University of Technology,Beijing 100124,China)
出处
《振动工程学报》
EI
CSCD
北大核心
2020年第3期636-642,共7页
Journal of Vibration Engineering
基金
国家自然科学基金资助项目(51775005,51675009)。
