Abstract
The sidebands spaced around the gear meshing content and its harmonics are the commonly used fault indicator in the gear fault diagnosis under the constant rotational speed condition. However, when the gear works under the run-up condition, the variable rotational speed causes smearing to the frequency spectrum, which makes it difficult to recognize the sidebands caused by the local gear fault. This paper proposed a method which combines Fractional Fourier Transform (FrFT) and the Hilbert Transform (HT) to identify the sidebands of signal measured under the run-up process. The HT is utilized to construct the analytic representation of the measured signal, which has a better energy concentration than the measured signal in the fractional domain. Thus, the ability of extracting weak sidebands of FrFT is enhanced. Simulation case study and experimental case study are carried to verify the effectiveness of the proposed method. Tooth cracks of different depth are manufactured artificially to simulate the local fault of different severity. The results show that the weak sidebands which is invisible in the time-frequency representation can be identified by the proposed method. The amplitude of gear meshing content and its sidebands ascends with the growth of the crack depth.
This project is supported by National Natural Science Foundation of China (Grant No. 51775394), Hubei Province Major Science and Technology Innovation Plan (2018AAA024).
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Zhou, Q., Wu, C., Fan, Q. (2020). Gear Fault Diagnosis Under the Run-Up Condition Using Fractional Fourier Transform and Hilbert Transform. In: Tan, J. (eds) Advances in Mechanical Design. ICMD 2019. Mechanisms and Machine Science, vol 77. Springer, Singapore. https://doi.org/10.1007/978-981-32-9941-2_77
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DOI: https://doi.org/10.1007/978-981-32-9941-2_77
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