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Bearing fault identification method and device, computer equipment and storage medium

A fault identification and bearing technology, applied in the field of deep learning, can solve problems such as low accuracy of bearing fault diagnosis, and achieve the effect of improving accuracy and feasibility

Inactive Publication Date: 2019-11-22
哈工大机器人(山东)智能装备研究院
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Problems solved by technology

[0005] The main purpose of the present invention is to provide a bearing fault identification method, device, computer equipment and storage medium to solve the problem of low accuracy of bearing fault diagnosis in the prior art

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  • Bearing fault identification method and device, computer equipment and storage medium
  • Bearing fault identification method and device, computer equipment and storage medium
  • Bearing fault identification method and device, computer equipment and storage medium

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[0033] It should be noted that, in the case of no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and examples.

[0034]In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is an embodiment of a part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0035] It should be noted that the terms "first"...

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Abstract

The invention provides a bearing fault identification method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining a vibration signal of a bearing tobe tested during the working process; converting the vibration signal into an acceleration envelope frequency spectrogram of the bearing to be tested; and inputting the acceleration envelope frequency spectrogram into a pre-trained convolutional neural network to extract image features of the acceleration envelope frequency spectrogram, and identifying fault probability of the bearing to be tested based on the image features. By inputting the envelope frequency spectrogram into the multi-layer convolutional neural network, the method can judge the fault without experience of workers or without carrying out operation of feature extraction feature selection and the like; and through combination of acceleration envelope fault diagnosis and a deep learning recognition method, accuracy and feasibility of fault diagnosis are improved.

Description

technical field [0001] The present invention relates to the technical field of deep learning, in particular to a bearing fault identification method, device, computer equipment and storage medium. Background technique [0002] With the continuous improvement of industrial automation and the continuous advancement of computer technology, intelligent maintenance of equipment has become a feature that various manufacturers continue to pay attention to. Industrial data contains a large amount of information, and it has become a research hotspot in intelligent maintenance to deeply explore the useful information inside big data. With the continuous improvement of data acquisition technology and processing speed, it is possible to continuously iterate and optimize the model. [0003] Bearings are important parts in rotating machinery, but bearings are also one of the vulnerable parts in equipment. When a bearing fails, it not only affects the production efficiency of the factory...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/045
CPCG01M13/045
Inventor 古乐单鹏飞葛红红张海旭李杨
Owner 哈工大机器人(山东)智能装备研究院
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