Fault prediction method and system for intelligent manufacturing equipment based on neural network model

A neural network model and equipment failure technology, applied in biological neural network models, manufacturing computing systems, predictions, etc., can solve problems such as prolonging equipment maintenance or replacement cycles, inability of production lines to produce effectively, and affecting the production efficiency of intelligent manufacturing production lines. Achieving low production loss

Inactive Publication Date: 2018-12-18
广东人励智能工程有限公司 +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] Improve product manufacturing efficiency and production line utilization efficiency and optimize production line scheduling through intelligent manufacturing; however, failures of production line equipment often cannot be predicted in advance, resulting in failure of effective production i

Method used

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  • Fault prediction method and system for intelligent manufacturing equipment based on neural network model
  • Fault prediction method and system for intelligent manufacturing equipment based on neural network model
  • Fault prediction method and system for intelligent manufacturing equipment based on neural network model

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Embodiment

[0086] see image 3 , image 3 It is a schematic diagram of the structural composition of the intelligent manufacturing equipment fault prediction system based on the neural network model in the embodiment of the present invention.

[0087] Such as image 3 As shown, a device failure time prediction system on an intelligent manufacturing production line, the device failure prediction system includes:

[0088] The first acquiring module 11: used to acquire the parameter of the running time of the equipment, the average running load parameter of the running time and the average running time parameter of each day during the running time;

[0089]In the implementation process of the present invention, corresponding parameter collection is carried out by installing corresponding data parameter collectors or corresponding data parameter collection software on the equipment on the production line of intelligent manufacturing, such as installing running load parameter collection sof...

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Abstract

The invention discloses a fault prediction method and a system for intelligent manufacturing equipment based on a neural network model, wherein, the method comprises the following steps: acquiring a running time-long parameter of the equipment, an average running load parameter in the running time and a daily average running time-long parameter in the running time; According to the running parameters of the equipment, the average running load parameter in the running time and the average running time parameter in the running time, the running data parameter set of the equipment is constructed.The parameters in the constructed equipment operation data parameter set are normalized to obtain the normalized equipment operation data parameter set; the normalized set of equipment running data is input into the trained neural network model to predict and analyze the equipment failure time, and the predicted results are outputted. In the embodiment of the invention, through the trained neuralnetwork model to predict the running data parameters of the equipment, the time when the equipment will fail can be predicted more accurately.

Description

technical field [0001] The invention relates to the technical field of intelligent manufacturing, in particular to a method and system for fault prediction of intelligent manufacturing equipment based on a neural network model. Background technique [0002] Intelligent Manufacturing (Intelligent Manufacturing, IM) is a human-machine integrated intelligent system composed of intelligent machines, intelligent production lines and human experts. It can perform intelligent activities in the manufacturing process, such as analysis, reasoning, judgment, conception and decision-making. Wait. Through the cooperation of humans and intelligent machines, to expand, extend and partially replace the mental work of human experts in the manufacturing process. It updates the concept of manufacturing automation and extends it to flexibility, intelligence and high integration. [0003] Improve product manufacturing efficiency and production line utilization efficiency and optimize productio...

Claims

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Application Information

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IPC IPC(8): G06Q10/00G06Q10/04G06Q50/04G06N3/04
CPCG06Q10/04G06Q10/20G06Q50/04G06N3/045Y02P90/30
Inventor 段鑫陈宇何德辉
Owner 广东人励智能工程有限公司
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