Cascade empirical mode decomposition-based gear fault diagnosis method

Abstract

The present invention relates to a cascade empirical mode decomposition-based gear fault diagnosis method. The cascade empirical mode decomposition-based gear fault diagnosis method comprises the steps of using a vibration sensor to monitor the gear fault working condition, and acquiring a gear fault working condition vibration signal; carrying out the fault signal local characteristic extraction on the acquired vibration signal via a multilevel empirical mode decomposition method, and obtaining an intrinsic mode function; carrying out the power spectrum analysis on the obtained intrinsic mode function, extracting the mixed single frequency information of an intrinsic mode function component IMF, and determining whether the mixed single frequency information generates a mode aliasing state; adding an auxiliary signal in an obtained aliasing mode signal IMFj to obtain a new mixed signal; initializing the obtained mixed signal, circulating until all decomposed intrinsic mode functions have no mode aliasing phenomenon; carrying out the power spectrum analysis on the finally obtained intrinsic mode function having no mode aliasing phenomenon to obtain a fault characteristic frequency. The cascade empirical mode decomposition-based gear fault diagnosis method of the present invention can diagnose the gear faults timely and accurately, and avoids the problem that the fault characteristics are difficult to identify.

Description

technical field [0001] The invention relates to a fault diagnosis method, in particular to a gear fault diagnosis method based on cascade empirical mode decomposition for rotating mechanical equipment. Background technique [0002] Among many mechanical equipment, the gearbox is one of the key functional components in the mechanical power device. The gearbox is widely used, such as locomotives, ships, metallurgy, aerospace and other fields. The degree of intelligence of mechanical equipment is getting higher and higher, and safety, reliability and stability have become key factors to measure equipment performance. Gear is an important part of transmission power, and it is also the most prone to failure. Since the gear is affected by uncertain factors of various working conditions during the transmission process, the gear fault diagnosis is facing a greater challenge. Therefore, the research on gear fault diagnosis and fault prediction has become an important part of the ope...

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Problems solved by technology

[0004] In view of the above problems, the purpose of the present invention is to provide a gear fault diagnosis method based on cascaded empirical mode decomposition, which can timely and accurately diagnose gear faults under complex conditions, and can realize self-adaptive loop separation from the original signal The parameters that characterize the fault characteristics are obtained, so that the fault characteristics are more obvious on different time scales, thus avoiding the problem that the fault characteristics are difficult to identify

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