基于压缩感知的设备多源信息传输与分类算法

赵小虎; 王刚; 宋泊明; 于嘉成

doi:10.11959/j.issn.1000-436x.2020040

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基于压缩感知的设备多源信息传输与分类算法

专题：智慧矿山 | 更新时间：2024-06-05

- 基于压缩感知的设备多源信息传输与分类算法
- Multi-source information transmission and classification algorithm for equipment based on compressed sensing
- 通信学报 2020年41卷第2期页码：13-24
- 作者机构：
  
  1. 矿山互联网应用技术国家地方联合工程实验室，徐州江苏 221000
  2. 中国矿业大学物联网（感知矿山）研究中心，徐州江苏 221000
  3. 西澳大学电气电子与计算机工程系，珀斯 6009
- 作者简介：
  
  [ "赵小虎（1976- ），男，江苏徐州人，博士，中国矿业大学教授、博士生导师，主要研究方向为物联网、机器学习" ]
  [ "王刚（1977- ），男，江苏徐州人，博士，中国矿业大学副教授、硕士生导师，主要研究方向为机器学习、设备故障诊断、压缩感知" ]
  [ "宋泊明（1989- ），男，江苏徐州人，西澳大学博士生，主要研究方向为机器学习、基于微波信号的雨衰估计、层析重构算法等" ]
  [ "于嘉成（1994- ），男，河北沧州人，中国矿业大学硕士生，主要研究方向为机器学习、设备故障诊断等" ]
- 基金信息：
  
  国家重点研发计划基金资助项目(2017YFC0804404)
- DOI：10.11959/j.issn.1000-436x.2020040
  中图分类号： TP18
- 网络出版日期：2020-02，
  
  纸质出版日期：2020-02-25
- 稿件说明：
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赵小虎, 王刚, 宋泊明, 等. 基于压缩感知的设备多源信息传输与分类算法[J]. 通信学报, 2020,41(2):13-24.

Xiaohu ZHAO, Gang WANG, Boming SONG, et al. Multi-source information transmission and classification algorithm for equipment based on compressed sensing[J]. Journal on communications, 2020, 41(2): 13-24.
赵小虎, 王刚, 宋泊明, 等. 基于压缩感知的设备多源信息传输与分类算法[J]. 通信学报, 2020,41(2):13-24. DOI： 10.11959/j.issn.1000-436x.2020040.

Xiaohu ZHAO, Gang WANG, Boming SONG, et al. Multi-source information transmission and classification algorithm for equipment based on compressed sensing[J]. Journal on communications, 2020, 41(2): 13-24. DOI： 10.11959/j.issn.1000-436x.2020040.

摘要

针对选煤厂设备种类繁多、监测点分散的特点，提出了一种基于压缩感知的设备多源信息无线传输与分类算法。通过构建一种多跳信息传输模型，将信息传输问题转换为多路测量信号的压缩感知问题，将测量矩阵获取问题转化为多跳信息传输模型的路由问题。针对所获得的测量矩阵存在较大相干性、影响信号重构效果问题，将随机路由的思想引入路由构建当中，提出了一种随机动态自组织路由算法。为了解决重构后的信号时域特征难以对故障类型进行精确分类的问题，针对重构信号，引入了一种新的时域特征——振动信号的全变分，并通过补偿距离评估算法（CDET）验证了引入指标的优越性。通过选煤厂实测数据分析表明，所提多源信息传输与分类算法在提高监测数据实时传输效率情况下，能够有效提高故障识别精度。

Abstract

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.

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references

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