Fault diagnosis based on knowledge pushing in multi-sensor integration hydrogen detection system

WANG Bing; ZHANG Hong-quan; SONG Kai; ZHANG Zhen-yu

doi:10.3788/OPE.20152306.1742

您当前的位置：

首页 >

文章列表页 >

Fault diagnosis based on knowledge pushing in multi-sensor integration hydrogen detection system

更新时间：2020-08-13

- Fault diagnosis based on knowledge pushing in multi-sensor integration hydrogen detection system
- Optics and Precision Engineering Vol. 23, Issue 6, Pages: 1742-1748(2015)
- 作者机构：
  
  1. 哈尔滨工业大学电气工程及自动化学院,黑龙江哈尔滨,150001
  2. 哈尔滨工程大学自动化学院,黑龙江哈尔滨,150001
  3. 哈尔滨工程大学信息与通信工程学院,黑龙江哈尔滨,150001
  4. 中国电子科技集团公司第49研究所,黑龙江哈尔滨,150001
  5. 中国船舶重工集团公司第703研究所,黑龙江哈尔滨,150001
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20152306.1742
  CLC： O659;TP277
- Received：30 December 2014，
  
  Revised：22 January 2015，
  
  Published：25 June 2015
- 稿件说明：
移动端阅览
王冰, 张洪泉, 宋凯等. 多传感器集成氢气检测系统的知识推送故障诊断[J]. 光学精密工程, 2015,23(6): 1742-1748

WANG Bing, ZHANG Hong-quan, SONG Kai etc. Fault diagnosis based on knowledge pushing in multi-sensor integration hydrogen detection system[J]. Editorial Office of Optics and Precision Engineering, 2015,23(6): 1742-1748
王冰, 张洪泉, 宋凯等. 多传感器集成氢气检测系统的知识推送故障诊断[J]. 光学精密工程, 2015,23(6): 1742-1748 DOI： 10.3788/OPE.20152306.1742.

WANG Bing, ZHANG Hong-quan, SONG Kai etc. Fault diagnosis based on knowledge pushing in multi-sensor integration hydrogen detection system[J]. Editorial Office of Optics and Precision Engineering, 2015,23(6): 1742-1748 DOI： 10.3788/OPE.20152306.1742.

摘要

针对现有多传感器集成氢气检测系统不能对自身工作状态进行诊断的缺点

对基于知识的故障诊断专家系统进行了分析

提出了一种基于知识管理和知识主动推送的故障诊断方法.对提出的用于多传感器集成氢气检测系统故障诊断的主要层次结构进行了研究.根据专家系统的基本原理介绍了基于知识推送的专家系统的总体结构.分析了系统故障模式

讨论了故障诊断单元知识库的设计方法.建立了知识主动推送的推理机构模型

给出了其推理方法和步骤.最后

给出了基于知识推送的多传感器集成氢气检测系统故障诊断单元的设计方法.实验结果表明:本方法的故障诊断准确率可达到97%以上

验证了该方法的有效性.提出的方法能够主动将知识在适当的时候传递给决策者

提高了故障诊断的速度和准确度.

Abstract

As multi-sensor integration hydrogen detection systems can not diagnose the working state by itself

an expert system of fault diagnosis based on knowledge was analyzed and a fault diagnosis method based on knowledge management and knowledge pushing was proposed. The hierarchical structure of the fault diagnosis method used in the multi-sensor integration hydrogen detection system was investigated. On the basis of the principle of expert systems

the texture of expert system based on knowledge pushing actively was presented. After the fault modes were analyzed

a knowledge base fault diagnosis design was discussed. Then the method and step of inference engine based on knowledge pushing actively were researched by its established model. Finally

the fault diagnosis unit for multi-sensor integration hydrogen detection system based on knowledge pushing was designed. Experimental results indicate that the fault diagnosis accuracy rate of the proposed method reaches above 97%

which verifies the effectiveness of the method. It can transfer initiatively the knowledge to the decision-maker at opportune moment

and improve the speed and accuracy rate of fault diagnosis.

关键词

Keywords

references

黄斌,陈世静,张文伟,等. 气浮式测力传感器静特性的影响因素[J]. 光学精密工程,2014, 22(2): 390-396. HUANG B, CHEN SH J, ZHANG W W, et al.. Influence factors on static characteristics of flotation force transducers [J]. Opt. Precision Eng., 2014, 22(2): 390-396. (in Chinese)

郑高峰, 何广奇, 刘海燕,等. 电纺氧化锌纳米纤维乙醇、丙酮气敏传感器[J]. 光学精密工程,2014, 22(6): 1555-1561. ZHENG G F, HE G Q, LIU H Y, et al.. Electrospun zinc oxide nanofibrous gas sensors for alcohol and acetone [J]. Opt. Precision Eng., 2014, 22(6): 1555-1561. (in Chinese)

LO K L,NG H S,GRANT D M,et al..Extended Petri net models for fault diagnosis for substation automation [J].IEEE Proceedings : Generation, Transmission and Distribution, 1999,146(3):229-234.

刘晶红, 孙辉, 沈宏海,等. 机载光电成像设备的可测试性系统设计[J]. 光学精密工程,2008, 16(12):2435-2440. LIU J H, SUN H, SHEN H H, et al.. Design of testable system for airborne optoelectronic imaging equipment [J]. Opt. Precision Eng., 2008, 16(12):2435-2440. (in Chinese)

RICADELA A. Microsofts knowledge push [J]. InformationWeek. 2000, (805) :151.

SIONTOROU, CHRISTINA G. A knowledge-based approach to online fault diagnosis of FET biosensors [J]. IEEE Transactions on Instrumentation and Measurement, 2010, 59(9): 2345-2364.

李恺钦. 基于改进遗传算法的航空发动机故障诊断专家系统[D]. 南昌:南昌航空大学,2012. LI K Q. Based on an improved genetic algorithm for aero engine fault diagnosis expert system [D]. Nanchang:School of Aeronautical Manufacturing Engineering Nanchang Hangkong University,2012. (in Chinese)

高美铃. 基于PCA-RS智能技术的齿轮故障诊断研究与应用[D]. 武汉:武汉理工大学,2012. GAO M L.Research and application of gear fault diagnosis based on PCA-RS intellectual technology [D]. Wuhan:Wuhan university of technology,2012. (in Chinese)

杨思锋,王祁,刘鲁. 一种基于知识推送的故障诊断系统[J]. 航空动力学报,2010, 25(1): 203-207. YANG S F, WANG Q, LIU L. Fault diagnosis system based on knowledge pushing [J]. Journal of Aerospace Power, 2010, 25(1): 203-207. (in Chinese)

LEE H J,AHN B S,PARK Y M.A fault diagnosis expert system for distribution substations [J].IEEE Transactions on Power Delivery,2000, 15(1):92-97.

王磊, 陈青, 高湛军. 输电网故障诊断的知识表示方法及其应用[J]. 中国电机工程学报,2012, 32(4): 85-92. WANG L, CHEN Q, GAO ZH J. Representation and application of fault diagnosis knowledge in power transmission grids [J]. Proceedings of the CSEE. 2012, 32(4): 85-92.

Views

337

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Rolling bearing fault diagnosis by improved multiscale amplitude-aware permutation entropy and random forest

Intelligent fault diagnosis of thin wall bearing based on information fusion

Design of hybrid frame for on-orbit flywheel fault diagnosis

Characteristics of double-coil resonant microfluidic chip for oil detection

Detection system of small particles in hydraulic oil

Related Author

Hai-bin WU

Ying WANG

Ting-hao ZHANG

Yin-sheng CHEN

Yan-wei XU

Ming-ming LIU

Yang LIU

Li-hai CHEN

Related Institution

School of Mechatronics Engineering, Henan University of Science and Technology

Control Engineering, Harbin Engineering University

Marine Engineering College, Dalian Maritime University

长春光学精密机械与物理研究所

中国科学院研究生院

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176855 Email：gxjmgc@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰