摘要
针对复杂的齿轮箱振动信号难以提取出故障特征频率的问题,提出了一种将希尔伯特包络解调技术与经验模式分解(EMD)相结合的分析方法。首先对齿轮箱的故障信号进行了EMD分解,得到了本征模态函数(IMF分量),再对IMF分量进行了包络解调,得到了其调制信号,结合调制信号的频率成分可初步判断出齿轮箱中出现故障的齿轮;然后根据IMF分量与初始信号之间相关系数的大小,选择相关系数较大的分量重构信号,相当于对初始信号进行滤波;最后对重构的信号以啮合频率及其倍频为中心频率进行了带通滤波,对得到的信号进行了包络解调分析,再次进行了故障诊断,以验证故障诊断的准确性。整个过程通过对齿轮箱实测故障信号的分析加以验证。研究结果表明,该方法能够准确地提取出齿轮箱的故障特征频率,从而可以对齿轮箱故障进行有效地诊断。
Aiming at solving the problem that the complex fault signal of gearbox is difficult to detect, a fault diagnosis method based on em- pirical mode decomposition(EMD) and Hilbert demodulation was presented. Firstly, the EMD was used to decompose the original complex signal to obtain the intrinsic mode functions(IMFs). Secondly, the Hilbert demodulation technique was applied to the selected IMFs to ex- tract the modulated signal. Then, the gearbox faults can be diagnosed by the frequency of the extracted signal. Thirdly, with setting the mes- hing frequency as the center frequency, a band pass filter was used to filter the signal which was reconstructed by some selected IMFs based on the cross correlation coefficient. And then, the Hilbert demodulation was used again to extract the modulating signal to verify the diag- nosed result. The results of applying to a real inspected signal indicate that this method is effective in gearbox fault detection.
出处
《机电工程》
CAS
2013年第11期1297-1300,1322,共5页
Journal of Mechanical & Electrical Engineering
基金
国家自然科学基金资助项目(51075070
51175079)
关键词
齿轮箱
经验模式分解
希尔伯特解调
故障诊断
gearbox
empirical mode decomposition(EMD)
Hilbert demodulation
fault diagnosis