Fault Diagnosis Approach for Pneumatic Control Valves Based on Modified Expert System

被引：7

作者：

Zhang, Daoming ^{[1
]}

Hao, Jixing ^{[1
]}

Chen, Liming ^{[1
]}

Zhou, Linna ^{[1
]}

机构：

[1] China Univ Min & Technol, Sch Informat & Control Engn, Xuzhou, Jiangsu, Peoples R China

来源：

2020 19TH INTERNATIONAL SYMPOSIUM ON DISTRIBUTED COMPUTING AND APPLICATIONS FOR BUSINESS ENGINEERING AND SCIENCE (DCABES 2020) | 2020年

基金：

中国国家自然科学基金;

关键词：

pneumatic control velve; fault diagnosis; expert system; particle swarm optimization algorithm;

D O I：

10.1109/DCABES50732.2020.00035

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper studies the fault diagnosis method of pneumatic control valve. Firstly, the faults characteristics of pneumatic control valves are analyzed according to the operating principle and status of pneumatic control valves; secondly, the expert experience of the fault diagnosis of pneumatic control valves is summarized, which is verified according to the operating mechanism; thirdly, a fault diagnosis approach for pneumatic control valves based on modified expert system is proposed, by combining particle swarm optimization (PSO) algorithm with expert rules. Finally, the availability and advantages of the proposed approach is verified by the designed valve experimental system platform. The results show that compared with the basic expert system-based method, the modified method improves the accuracy and reduces the false negative rate effectively.

引用

页码：104 / 107

页数：4

共 10 条

[1]

[Anonymous], 2014, P IEEE AER C

[2] Introduction to the DAMADICS actuator FDI benchmark study [J].

Bartys, M ;

Patton, R ;

Syfert, M ;

de Las Heras, S ;

Quevedo, J .

CONTROL ENGINEERING PRACTICE, 2006, 14 (06) :577-596

[3] PSO-ELM: A Hybrid Learning Model for Short-Term Traffic Flow Forecasting [J].

Cai, Weihong ;

Yang, Junjie ;

Yu, Yidan ;

Song, Youyi ;

Zhou, Teng ;

Qin, Jing .

IEEE ACCESS, 2020, 8 :6505-6514

[4]

Kennedy J., 1995, P ICNN 95 INT C NEUR, V4, P1942, DOI [10.1109/ICNN.1995.488968., 10.1109/ICNN.1995.488968]

[5]

Li Han, 2011, Control and Decision, V26, P1

[6] Expert system methodologies and applications - a decade review from 1995 to 2004 [J].

Liao, SH .

EXPERT SYSTEMS WITH APPLICATIONS, 2005, 28 (01) :93-103

[7]

Ma J., 2017, CContrast Limited Adaptive Histogram Equalization Based Fusion for Underwater Image Enhancement, DOI [10.20944/preprints201703.0086.v1, DOI 10.20944/PREPRINTS201703.0086.V1]

[8] A novel intelligent controller for combating stiction in pneumatic control valves [J].

Mishra, Puneet ;

Kumar, Vineet ;

Rana, K. P. S. .

CONTROL ENGINEERING PRACTICE, 2014, 33 :94-104

[9] Fault detection and diagnosis of pneumatic valve using Adaptive Neuro-Fuzzy Inference System approach [J].

Subbaraj, P. ;

Kannapiran, B. .

APPLIED SOFT COMPUTING, 2014, 19 :362-371

[10] Data-Driven Robust M-LS-SVR-Based NARX Modeling for Estimation and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking [J].

Zhou, Ping ;

Guo, Dongwei ;

Wang, Hong ;

Chai, Tianyou .

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 29 (09) :4007-4021

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