分数阶傅里叶变换在轴承故障诊断中的应用 - SHAO Yan; LU Di; YANG Guang-xue (Journal of Harbin University of Science and Technology, 2017)
In fault diagnosis of rolling bearings，the fault signal is easy to be interfered by the ambient noise， Therefore，an approach based on Fractional Fourier Transform( FＲFT) is studied in this research to collect valid data of rolling bearing fault. With utilizing this approach，data can be analyzed by being converted into fractional domain，as well as 3D simulation. Consequently，the fractional can be changed to extract the weak fault to search for the maximum peak of weak fault. According to the analysis，the Fractional Fourier Transform algorithm is able to effectively reduce the mutual interference of other components and noise，and accurately extract the target component. Hence，the research findings are able to prove the validity and feasibility of the approach studied in this paper.