Fault diagnosis method and system for industrial equipment data

A fault diagnosis system and technology of industrial equipment, applied in the field of fault diagnosis, can solve problems such as many parameters and affecting parameter optimization

Inactive Publication Date: 2021-04-09
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the traditional particle swarm optimization algorithm is easy to fall into the local optimal solution, and there are too many parameters to be set. These defects will affect the results of parameter optimization.

Method used

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  • Fault diagnosis method and system for industrial equipment data
  • Fault diagnosis method and system for industrial equipment data
  • Fault diagnosis method and system for industrial equipment data

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Embodiment Construction

[0085] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0086] The purpose of the present invention is to provide a fault diagnosis method and system for industrial equipment data, which improves the accuracy of fault diagnosis.

[0087] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0088] figure 1 It is a schematic flo...

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Abstract

The invention relates to a fault diagnosis method and system for industrial equipment data, and the method comprises the steps: obtaining the detection data of a plurality of sensors under various types of faults, and enabling the number of the detection data of each sensor to be more than one; constructing a deep belief network for each sensor; optimizing each deep belief network, and determining a network hyper-parameter of each deep belief network; training each optimized deep belief network by taking the detection data of the sensor as input and taking the probability of the fault type corresponding to the detection data of the sensor as output; inputting to-be-diagnosed detection data into the trained deep belief networks, and outputting probabilities of a plurality of fault types; and adopting an improved DS evidence theory based on a Pearson coefficient to carry out decision-making layer fusion on the probability values of the fault types, and outputting the fault types. According to the invention, the accuracy of fault diagnosis is improved.

Description

technical field [0001] The invention relates to the technical field of fault diagnosis, in particular to a fault diagnosis method and system for industrial equipment data. Background technique [0002] At present, industrial production is constantly developing in the direction of complexity, intelligence and precision. However, in the development process of the industrial Internet, there are still various problems such as information islands, data heterogeneity, and data compatibility. Manufacturing Execution System (MES) is an information management system for the workshop execution layer, which can provide enterprises with functions such as production plan management, production process control, and product quality management, and can well solve information islands and data heterogeneity. , Data compatibility and other issues. [0003] In the field of fault diagnosis in industrial production, the interconnection of equipment data can be realized through the MES system. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08G06N3/04G06N3/00G06F17/16
CPCG06N3/084G06N3/006G06F17/16G06N3/045
Inventor 柴森春王昭洋王统铭姚分喜张百海崔灵果李慧芳
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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