Multi-source information transmission and classification algorithm for equipment based on compressed sensing

Aiming at the characteristics of various types of equipment in coal preparation plant and the dispersion of monitoring points,a multi-source information wireless transmission and classification algorithm for equipment based on compressed sensing was proposed.By constructing a multi-hop information t...

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Main Authors: Xiaohu ZHAO, Gang WANG, Boming SONG, Jiacheng YU
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2020-02-01
Series:Tongxin xuebao
Subjects:
Online Access:http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020040/
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author Xiaohu ZHAO
Gang WANG
Boming SONG
Jiacheng YU
author_facet Xiaohu ZHAO
Gang WANG
Boming SONG
Jiacheng YU
author_sort Xiaohu ZHAO
collection DOAJ
description Aiming at the characteristics of various types of equipment in coal preparation plant and the dispersion of monitoring points,a multi-source information wireless transmission and classification algorithm for equipment based on compressed sensing was proposed.By constructing a multi-hop information transmission model,the information transmission problem was transformed into the compressed sensing problem of multi-path measurement signals,thereby the measurement matrix acquisition was transformed into the routing problem of the multi-hop information transmission model.Aiming at the large coherence of the obtained measurement matrix and affecting the signal reconstruction effect,the idea of random routing was introduced into the routing construction,and a random dynamic self-organizing routing algorithm was proposed.In order to solve the problem that the time domain features of the reconstructed signal were difficult to accurately classify the fault type,a new time domain feature,the total variation (TV) of the vibration signal,was introduced for the reconstructed signal,and the compensation distance estimation algorithm was adopted to verify the superiority of the introduction of indicators.The analysis of the measured data of the coal preparation plant shows that the proposed multi-source information transmission and classification algorithm can effectively improve the fault recognition accuracy under the condition of improving the real-time transmission efficiency of the monitoring data.
format Article
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institution Kabale University
issn 1000-436X
language zho
publishDate 2020-02-01
publisher Editorial Department of Journal on Communications
record_format Article
series Tongxin xuebao
spelling doaj-art-215ba86f11a84b91af3a675fdd82fb912025-01-14T07:18:31ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2020-02-0141132459732958Multi-source information transmission and classification algorithm for equipment based on compressed sensingXiaohu ZHAOGang WANGBoming SONGJiacheng YUAiming at the characteristics of various types of equipment in coal preparation plant and the dispersion of monitoring points,a multi-source information wireless transmission and classification algorithm for equipment based on compressed sensing was proposed.By constructing a multi-hop information transmission model,the information transmission problem was transformed into the compressed sensing problem of multi-path measurement signals,thereby the measurement matrix acquisition was transformed into the routing problem of the multi-hop information transmission model.Aiming at the large coherence of the obtained measurement matrix and affecting the signal reconstruction effect,the idea of random routing was introduced into the routing construction,and a random dynamic self-organizing routing algorithm was proposed.In order to solve the problem that the time domain features of the reconstructed signal were difficult to accurately classify the fault type,a new time domain feature,the total variation (TV) of the vibration signal,was introduced for the reconstructed signal,and the compensation distance estimation algorithm was adopted to verify the superiority of the introduction of indicators.The analysis of the measured data of the coal preparation plant shows that the proposed multi-source information transmission and classification algorithm can effectively improve the fault recognition accuracy under the condition of improving the real-time transmission efficiency of the monitoring data.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020040/compressed sensingmulti-hop networkrandom routingtotal variationfault classification
spellingShingle Xiaohu ZHAO
Gang WANG
Boming SONG
Jiacheng YU
Multi-source information transmission and classification algorithm for equipment based on compressed sensing
Tongxin xuebao
compressed sensing
multi-hop network
random routing
total variation
fault classification
title Multi-source information transmission and classification algorithm for equipment based on compressed sensing
title_full Multi-source information transmission and classification algorithm for equipment based on compressed sensing
title_fullStr Multi-source information transmission and classification algorithm for equipment based on compressed sensing
title_full_unstemmed Multi-source information transmission and classification algorithm for equipment based on compressed sensing
title_short Multi-source information transmission and classification algorithm for equipment based on compressed sensing
title_sort multi source information transmission and classification algorithm for equipment based on compressed sensing
topic compressed sensing
multi-hop network
random routing
total variation
fault classification
url http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020040/
work_keys_str_mv AT xiaohuzhao multisourceinformationtransmissionandclassificationalgorithmforequipmentbasedoncompressedsensing
AT gangwang multisourceinformationtransmissionandclassificationalgorithmforequipmentbasedoncompressedsensing
AT bomingsong multisourceinformationtransmissionandclassificationalgorithmforequipmentbasedoncompressedsensing
AT jiachengyu multisourceinformationtransmissionandclassificationalgorithmforequipmentbasedoncompressedsensing