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Parameter online measurement method based on improved BP neural network

A technology of BP neural network and measurement method, applied in the field of Internet of Things and intelligent manufacturing, BP neural network algorithm, can solve the problems of long parameter acquisition time and untimely abnormal feedback, so as to speed up the convergence speed, improve the feedback adjustment speed, shorten the The effect of training time

Inactive Publication Date: 2018-06-01
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

[0005] Therefore, in order to solve the above-mentioned shortcomings, the present invention provides an online parameter measurement method based on an improved BP neural network, which can overcome the problems of long parameter acquisition time and untimely abnormal feedback in the industrial Internet of Things

Method used

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  • Parameter online measurement method based on improved BP neural network
  • Parameter online measurement method based on improved BP neural network
  • Parameter online measurement method based on improved BP neural network

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Embodiment Construction

[0038] The following will be combined with Figure 1-Figure 3 The present invention is described in detail, and the technical solutions in the embodiments of the present invention are clearly and completely described. Apparently, the described embodiments are only some of the embodiments of the present invention, not all of them. 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.

[0039] The present invention provides an online parameter measurement method based on an improved BP neural network through improvement, which can overcome the problems of long parameter acquisition time and untimely abnormal feedback in the industrial Internet of Things.

[0040] Taking the moisture measurement of wheat in the koji making process as an example, the above-mentioned improved BP neural network algorithm is used to construct a B...

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Abstract

The invention discloses an industrial Internet of Things (IoT) parameter measurement method based on an improved BP neural network. The method includes training of a BP neural network, improvement ofthe BP neural network, and parameter online measurement method work flow of the BP neural network. The method of the invention has a good effect in real-time online measurement of parameters in an intelligent manufacturing IoT system, and can shorten the measurement time of the parameters of the industrial IoT system and improve the feedback regulation speed of the system.

Description

technical field [0001] The invention relates to the technical fields of BP neural network algorithm, Internet of Things and intelligent manufacturing, and specifically relates to an online measurement method for industrial Internet of Things parameters based on an improved BP neural network. Background technique [0002] The online measurement of parameters is the basic link of the industrial Internet of Things system for data perception. How to accurately and real-time perceive the process parameters of the production process is the key to system feedback adjustment. At present, the Internet of Things technology has been widely used in the field of intelligent manufacturing and has become the basic network platform for building intelligent factories. However, with the complexity of the production process, the Internet of Things system still has challenges for the real-time collection and fusion of multiple parameters, and it is difficult to solve the problems of long parame...

Claims

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Application Information

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IPC IPC(8): G05B13/02G05B13/04
CPCG05B13/027G05B13/042G05B13/047G05B13/048
Inventor 李迅波于文杰闫明明王振林杜磊蔡汉斌
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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