Published December 1, 2018 | Version v1
Journal article Metadata-only

A Fault Diagnosis System for Main Fan in Coal Mine Based on BP Neural Network

Creators

  • 1. Guizhou Institute of Technology, Guiyang (China)
  • 2. Guizhou Zhonghe Technology Co., Ltd., Guiyang, China 550003 (China)
  • 3. Hunan University of Science and Technology, Xiangtan (China)

Description

By analysing the three-layer structure of BP neural network and the fault characteristics of main fan in coal mine, the BP network structure of fault diagnosis is constructed, and the learning model and algorithm of BP network are designed. The experimental simulation shows that the accuracy of the fault diagnosis of the main fan of the coal mine is improved. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1757-899X/466/1/012061

Additional details

Identifiers

DOI
10.1088/1757-899X/466/1/012061;

Publishing Information

Journal Title
IOP Conference Series. Materials Science and Engineering (Online)
Journal Volume
466
Journal Issue
1
Journal Page Range
[8 p.]
ISSN
1757-899X

Conference

Title
2. Annual International Conference on Cloud Technology and Communication Engineering
Dates
17-19 Aug 2018
Place
Nanjing (China)

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52107357
Subject category
S01: COAL, LIGNITE, AND PEAT; S42: ENGINEERING;
Resource subtype / Literary indicator
Conference
Descriptors DEI
ACCURACY; ALGORITHMS; COAL MINES; COMPUTERIZED SIMULATION; DESIGN; FAULT TREE ANALYSIS; NEURAL NETWORKS
Descriptors DEC
MATHEMATICAL LOGIC; MINES; SIMULATION; SYSTEM FAILURE ANALYSIS; SYSTEMS ANALYSIS; UNDERGROUND FACILITIES