Journal of Control Science and Engineering

Fault Detection, Isolation, and Prognosis for Complex System


Status
Published

Lead Editor

1Zhejiang University, Zhejiang, China

2Hong Kong University of Science and Technology, Kowloon, Hong Kong

3National Tsing Hua University, Hsinchu, Taiwan

4Harvard University, Cambridge, USA

5Hill-Rom, Batesville, USA


Fault Detection, Isolation, and Prognosis for Complex System

Description

A complex system can be thought of as multiple interdependent working subsystems. With the increasing level of complexity, it may present more frequent unstable operation statuses. Once system faults have occurred, they can cause unrecoverable losses and unacceptable environmental pollution and so forth. It thus demands more effective and efficient techniques to monitor operation status, detect the occurrence and propagation of faults, and enable suitable decision making, before such anomalies result in great damage. As one of the most active research areas over the last few decades, fault diagnosis including detection, isolation, and prognosis has been of importance and necessary for improving the economy and safety of a complex system, ranging from industrial processes, such as steel production, papermaking, car manufacturing, and mineral processing, to biological processes.

In the era of big data of process industries, new challenge emerges for fault diagnosis with amount of data grown exponentially. In particular, there are many uncertainties in the system which show the complexity of characteristics and include multimode and dynamics, multilevel and multiscale, nonlinearities, and strong coupling effects amongst the variables. This special issue focuses on the state of the art of fault diagnosis methods and their different applications, as well as future trends.

Potential topics include but are not limited to the following:

  • Fault diagnosis problems for batch processes
  • Fault prognosis for industrial processes
  • Fault self-recovery/self-healing control
  • Product quality monitoring and prediction
  • Process performance assessment
  • Incipient fault detection and diagnosis
  • Fault modeling, detection, and estimation
  • Fault classification and discrimination
  • Data-driven approaches and knowledge-based approaches
  • Data-driven modeling and operational automation
  • Intelligence-based supervisory control

Articles

  • Special Issue
  • - Volume 2018
  • - Article ID 8783158
  • - Editorial

Fault Detection, Isolation, and Prognosis for Complex System

Chunhui Zhao | Furong Gao | ... | Yongji Fu
  • Special Issue
  • - Volume 2018
  • - Article ID 5205698
  • - Research Article

Time-Varying Fault Diagnosis for Asynchronous Multisensor Systems Based on Augmented IMM and Strong Tracking Filtering

Yanyan Hu | Xiaoling Xue | ... | Kaixiang Peng
  • Special Issue
  • - Volume 2017
  • - Article ID 7097561
  • - Research Article

Modeling of Complex Life Cycle Prediction Based on Cell Division

Fucheng Zhang | Yahui Wang | De Zhang
  • Special Issue
  • - Volume 2017
  • - Article ID 3169172
  • - Research Article

Tooth Fracture Detection in Spiral Bevel Gears System by Harmonic Response Based on Finite Element Method

Yuan Chen | Rupeng Zhu | ... | Yeping Xiong
  • Special Issue
  • - Volume 2017
  • - Article ID 4375690
  • - Research Article

Degradation Data-Driven Remaining Useful Life Estimation in the Absence of Prior Degradation Knowledge

Yong Yu | Changhua Hu | ... | Jianxun Zhang
  • Special Issue
  • - Volume 2017
  • - Article ID 1982879
  • - Research Article

WOS-ELM-Based Double Redundancy Fault Diagnosis and Reconstruction for Aeroengine Sensor

Zhen Zhao | Zhexu Liu | ... | Jingya Liu
  • Special Issue
  • - Volume 2017
  • - Article ID 3614790
  • - Research Article

Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

Hailun Wang | Daxing Xu
  • Special Issue
  • - Volume 2017
  • - Article ID 8168627
  • - Research Article

Development of Fault Identification System for Electric Servo Actuators of Multilink Manipulators Using Logic-Dynamic Approach

V. Filaretov | A. Zuev | ... | A. Protsenko
  • Special Issue
  • - Volume 2017
  • - Article ID 9517385
  • - Research Article

A Bayesian Approach to Control Loop Performance Diagnosis Incorporating Background Knowledge of Response Information

Sun Zhou | Yiming Wang
  • Special Issue
  • - Volume 2017
  • - Article ID 6354208
  • - Research Article

Fault Diagnosis of Nonlinear Uncertain Systems with Triangular Form

Qi Ding | Xiafu Peng | ... | Xiaoqiang Hu
Journal of Control Science and Engineering
 Journal metrics
Acceptance rate15%
Submission to final decision59 days
Acceptance to publication29 days
CiteScore1.900
Impact Factor-
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