Electromagnet fault prediction method based on SA-PSO optimized BP neural network

A BP neural network and fault prediction technology, applied in the field of electromagnet quality, can solve problems such as parameter optimization, slow learning speed, and network training failure

Pending Publication Date: 2020-09-25
WENZHOU UNIVERSITY
View PDF5 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, using the traditional BP neural network for fault prediction without parameter optimization may lead to slow learning speed during error backpropagation, and it is easy to fall into local minimum, and the possibility of network training failure is high

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Electromagnet fault prediction method based on SA-PSO optimized BP neural network
  • Electromagnet fault prediction method based on SA-PSO optimized BP neural network
  • Electromagnet fault prediction method based on SA-PSO optimized BP neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0065] Embodiments of the present invention will be further described below in conjunction with accompanying drawings:

[0066] In order to establish a predictive model with good effect, the present invention gathers the theoretical knowledge and actual cases together, collects the faults of a certain type of AC electromagnet during the use of an electromagnet manufacturing unit within 6 months, and analyzes the specific causes of the faults. parameter changes. The specific parameters are shown in Table 1. The main parameters selected are as follows: the voltage at both ends of the coil, the number of turns of the coil, the frequency of the alternating current, the gap between the iron core and the coil, and the reaction force of the spring. Corresponding faults also have the following 4, namely: no pull-in after power-on, coil heating, electromagnet response too slow, and insufficient suction of the iron core. In order to facilitate the operation of the neural network, each ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an electromagnet fault prediction method based on an SA-PSO optimized BP neural network, and relates to the field of valve body assembly quality. The method comprises the steps: A, analyzing fault types and fault reasons generated by electromagnets, and classifying and setting fault labels according to the fault types; B, determining the structure and parameter setting of the BP neural network according to the fault reason and the fault type, and establishing a three-layer neural network, namely a first model; C, determining the dimension of a particle swarm; D, initializing the speed and parameters of the N-dimensional particles; E, mapping the particles randomly generated in the step D into a weight and a threshold of the BP neural network; F, combining a simulated annealing algorithm and a particle swarm algorithm and alternately operating; G, when the number of iterations and the temperature in the step F meet the requirements, stopping internal cooling; H,combining the first model and the second model to obtain a reliable fault diagnosis result. The method has the advantages of sufficient search and rapid fault diagnosis.

Description

technical field [0001] The invention relates to the field of electromagnet quality, in particular to an electromagnet fault prediction method based on SA-PSO optimized BP neural network. Background technique [0002] An electromagnet is a component that uses the magnetism generated by the iron core to attract the armature to realize the opening and closing function or fix a mechanical part in one position to convert electrical energy into mechanical energy. At present, electromagnets are widely used. For example, the door opening and closing devices of buses or subways that we often see are gradually converted from hydraulic or pneumatic transmission to electromagnets to control the opening and closing of doors. Electromagnets are not only simple in structure The most important thing about easy installation is responsiveness. However, as the degree of automation becomes higher and higher, the reliability of the electromagnet plays a vital role in the operation of these devi...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06K9/62G06N3/00G06N3/04G06N3/08G06F119/14G06F119/08
CPCG06F30/27G06N3/006G06N3/084G06F2119/14G06F2119/08G06N3/048G06N3/045G06F18/24
Inventor 庞继红袁开宇徐安察付培红李勇綦法群王国强
Owner WENZHOU UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap