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Machine tool abnormity identification method and system based on deep learning, and terminal device

An anomaly identification and deep learning technology, applied in the field of industrial inspection, can solve problems such as inability to give guidance information to machine tool maintenance personnel, and inability to identify the type of anomaly, etc., to achieve the effect of improving service life, accurate and more efficient maintenance of machine tools

Inactive Publication Date: 2019-09-06
HEREN KEJI WUHAN LLC
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Problems solved by technology

However, this detection method can only simply determine whether there is an abnormality in the machine tool, but cannot identify the type of abnormality, so it cannot give more detailed guidance information to the machine tool maintenance personnel, and then help the machine tool maintenance personnel to maintain the machine tool more accurately and efficiently

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  • Machine tool abnormity identification method and system based on deep learning, and terminal device
  • Machine tool abnormity identification method and system based on deep learning, and terminal device
  • Machine tool abnormity identification method and system based on deep learning, and terminal device

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Embodiment Construction

[0033] 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.

[0034] The terms "first", "second", "third", "fourth" and the like in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily to describe specific sequence or sequence. It is to be understood that the terms so used are interchangeable under appropriate ...

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Abstract

The invention provides a machine tool abnormity recognition method and system based on deep learning, a terminal device and a computer readable storage medium. For the machine tool abnormity recognition method and system, through collection and data processing of vibration signals and based on deep learning, abnormity and abnormal types of the machine tool are recognized through a neural network model, and detailed guidance information is provided for machine tool maintenance personnel, so that the machine tool maintenance personnel are helped to maintain the machine tool more accurately and more efficiently, and the service life of the machine tool is prolonged.

Description

technical field [0001] The invention relates to the technical field of industrial detection, in particular to a machine tool abnormality recognition method, system and terminal equipment based on deep learning. Background technique [0002] In industrial enterprises, during the long-term use of machine tools, it is inevitable that due to wear, fatigue peeling, fracture, deformation, corrosion, fracture and aging, the performance of the equipment will deteriorate and even fail. [0003] In traditional industrial enterprises, the failure of machine tools is often sudden. When the failure occurs, the machine tool has already experienced a large abnormality, which seriously affects production and even leads to shutdown. The reason is that the slow process of mechanical failure cannot be timely and effective. identify. Some experienced front-line industrial workers and maintenance personnel can assist in judging machine tool abnormalities and identifying the risk of mechanical f...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/00G06N3/08
CPCG06N3/08G06F2218/02G06F2218/08G06F18/2415
Inventor 黄光刊谭兆杰王星泽
Owner HEREN KEJI WUHAN LLC
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