Regularization sparse filtering method suitable for gear fault diagnosis under variable rotating speed

A sparse filtering and fault diagnosis technology, applied in the testing of mechanical components, testing of machine/structural components, measuring devices, etc., can solve problems such as single mapping between signals and fault types, reduce the generalization ability of data-driven models, and eliminate Influence and realize the effect of fault diagnosis

Active Publication Date: 2020-05-01
SHANDONG UNIV OF SCI & TECH
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Problems solved by technology

However, under variable speed conditions, the mapping between signals and fault types is no longer so simple, which brings severe challenges to mechanical fault diagnosis
[0004] To sum up, the vibration signal generated by the gear at variable speed is an extremely complex non-stationary signal,

Method used

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  • Regularization sparse filtering method suitable for gear fault diagnosis under variable rotating speed
  • Regularization sparse filtering method suitable for gear fault diagnosis under variable rotating speed
  • Regularization sparse filtering method suitable for gear fault diagnosis under variable rotating speed

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Embodiment Construction

[0029] The specific embodiment of the present invention will be further described below in conjunction with accompanying drawing and specific embodiment:

[0030] combine figure 1 , a regularized sparse filtering method suitable for gear fault diagnosis at variable speeds, including the following steps:

[0031] (1) Set different gear health statuses, and manually adjust the frequency converter to control the motor speed to fluctuate randomly within a certain range, thereby obtaining variable speed conditions, and collecting vibration signals of different faulty gears under variable speed conditions; using the original The vibration signal is used as a training sample, and the Z-segment signal is collected from the training sample by the convolution segment method, and these segments form the training set ,in is the jth segment containing N in data points, N in The input dimension used to represent sparse filtering, N out Indicates the output dimension.

[0032] (2) Re...

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Abstract

The invention discloses a regularization sparse filtering method suitable for gear fault diagnosis under variable rotating speed, and relates to the field of fault diagnosis of rotating machinery vibration signals. The method comprises the following steps of firstly, obtaining time-varying rotating speed vibration signals of a gear box under different fault types; secondly, establishing a sparse filtering model (L1/2-sparse filtering) based on L1/2 norm regularization, directly inputting a vibration signal into the model for training, and extracting features; and finally, inputting the extracted features into a Softmax classifier for intelligent diagnosis. According to the regularization method disclosed by the invention, the feature extraction capability of sparse filtering is improved, and the intelligent fault diagnosis of the gear box under the time-varying rotating speed is accurately and reliably realized.

Description

technical field [0001] The invention relates to the field of fault diagnosis of rotating machinery vibration signals, in particular to a regularized sparse filtering method suitable for gear fault diagnosis at variable speeds. Background technique [0002] Mechanical equipment widely used in aerospace, rail transit, engineering vehicles and other fields is evolving towards high speed, automation, multi-function and precision, which makes the structure of mechanical equipment increasingly complex, and the hidden danger of failure continues to rise. The gear is an important mechanism to realize the power transmission and motion conversion of these mechanical equipment, and it is also the main research object of mechanical fault diagnosis. However, most of the traditional fault diagnosis methods are carried out at a constant speed, and there are few researches on the fault diagnosis at a variable speed. The speed of the gears often changes greatly during the working process. F...

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Application Information

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IPC IPC(8): G01M13/021G01M13/028
CPCG01M13/021G01M13/028
Inventor 韩宝坤王金瑞鲍怀谦初振云
Owner SHANDONG UNIV OF SCI & TECH
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