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A gear state monitoring index extraction method based on a discrete random separation algorithm

A discrete random, extraction method technology, applied in the direction of machine gear/transmission mechanism testing, mechanical component testing, machine/structural component testing, etc., to achieve the effect of state monitoring

Active Publication Date: 2017-09-01
苏州微著设备诊断技术有限公司
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Problems solved by technology

J.Antoni proposed the Discrete random separation (DRS for short) method, which can realize the decoupling of the smooth modulation signal and the shock signal, but there is no literature that uses it for the extraction of gear condition monitoring indicators.

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  • A gear state monitoring index extraction method based on a discrete random separation algorithm
  • A gear state monitoring index extraction method based on a discrete random separation algorithm
  • A gear state monitoring index extraction method based on a discrete random separation algorithm

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Embodiment Construction

[0023] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. This embodiment adopts primary fatigue life data of the axle.

[0024] Such as figure 1 As shown, a gear condition monitoring index extraction method based on discrete random separation algorithm includes the following steps:

[0025] 1) Calculate the maximum and minimum values ​​of the side frequency amplitudes of 1 to 4 times the meshing order of the reference signal: N groups of normal gearbox vibration acceleration signals are sampled through the vibration acceleration sensor, and the sampling frequency is 5120Hz. The axle gear The box is a two-stage transmission, the structure is as follows figure 2 As shown, its structural parameters are as follows: input speed f n =277.5rpm, the first stage is the meshing of the spur gear pair, the number of teeth of the driving gear is z 1 =35, the number of teeth of the driven gear z 2 =35; the sec...

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Abstract

According to a gear state monitoring index extraction method based on a discrete random separation algorithm, the maximum value f[max] and the minimum value f[min] of 1-to-4-times of a side frequency amplitude of a twice-mesh order of a reference signal; the 1-to-4-times of the side frequency amplitude f of the twice-mesh order of a to-be-measured signal is calculated; and finally, a monitoring index is calculated; differential spectrum calculating is carried out according to the maximum value f[max], the minimum value f[min] and the side frequency amplitude f; and then differential spectrum values of all spectral lines are accumulated and summed to be used as the monitoring index. The method of the invention realizes extraction of the monitoring index reflecting the gear running state, and through a vibration acceleration signal, state information of a specific gear is precisely extracted, thereby realizing the state monitoring of the gear.

Description

technical field [0001] The invention belongs to the field of gear fault diagnosis, and in particular relates to a gear state monitoring index extraction method based on a discrete random separation algorithm. Background technique [0002] Gears, as an essential universal component for connecting and transmitting power in mechanical equipment, are widely used in modern industrial equipment such as metal cutting machine tools, aviation, power systems, agricultural machinery, transportation machinery, and metallurgical machinery. However, due to its complex structure and harsh working environment, gears and gearboxes are vulnerable to damage and failure, which directly affects the safe and reliable operation of the equipment and poses a major safety hazard. Therefore, it is very important to realize gear condition monitoring by extracting accurate and effective gear operation condition indicators. [0003] Defects or faults in the gear itself, or faults such as shaft bending, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/02
CPCG01M13/021G01M13/028
Inventor 王琇峰倪泽行和丹
Owner 苏州微著设备诊断技术有限公司
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