Multi-characteristic index bevel gear health status evaluating method

Abstract

The invention belongs to the technical field of helicopter health monitoring and fault diagnosis, and discloses a multi-characteristic index bevel gear health status evaluating method. The multi-characteristic index bevel gear health status evaluating method comprises the steps of obtaining first vibration test data of a normal gear and second vibration test data of a specific fault gear; calculating a mean square root of the test data; calculating the degree of skewness of the test data; calculating the state index of the test data based on sideband analysis; calculating the state index of differential signals of the test data; obtaining the sensitive degrees of the mean square root, the degree of skewness, the state index based on sideband analysis and the state index of the differentialsignals to a specific fault; and adopting the index with the high sensitive degree as the evaluation index of the specific fault, and evaluating the health status of a bevel gear.

Description

technical field [0001] The invention belongs to the technical field of helicopter health monitoring and fault diagnosis, and in particular relates to a multi-feature index bevel gear health state evaluation method. Background technique [0002] According to statistics, among the helicopter flight accidents caused by mechanical failure, 68% of the accidents can be attributed to the failure of power plant and transmission system. As an important part of the transmission system, the tail transmission system of the helicopter has a single-channel complex structure without redundancy, and the consequences of failure are serious. At the same time, its complexity and integration are high, maintenance support is difficult, and maintenance costs are high. Fault diagnosis for it It is very necessary. [0003] At present, the research on gears at home and abroad is mainly carried out in the time domain, frequency domain, and time-frequency domain. Specifically, the gear meshing freque...

AI Technical Summary

Problems solved by technology

Stewart, McFadden, and Zachary have published three classic works in related fields; Dempsey et al. summarize the methods for identifying the health status of gears, focusing on the application of these methods in the FAA and US Army helicopters. At present, foreign countries have improved the gear fault detection based on vibration, but there is very little empirical data to test the fault detection algorithm

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