A fuzzy-logic based fault diagnosis strategy for process control loops

Chang, Sue-Joan; Chang, Chuei-Tin

doi:10.1016/s0009-2509(03)00218-5

Cited by 28 publications

(22 citation statements)

References 8 publications

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“…A more comprehensive version can be found either in Chang et al (2002) or in Chang and Chang (2003). Let us use the level control system given in Fig.…”

Section: Implementation Procedures For Loop-free Systemsmentioning

confidence: 99%

“…The process deviations can be determined in real time and then used as the inputs to a FIS for computing the occurrence indices of fault origins. The membership functions used in this study for classifying the process deviations and occurrence indices are the same as those adopted in Chang and Chang (2003). For the sake of brevity, detailed descriptions of these functions are not included in this paper.…”

Section: On-line Implementationmentioning

confidence: 99%

“…However, if a process contains feedback and/or feed forward loops, the intermediate transient states must also be considered. Although a systematic procedure has already been developed in Chang and Chang (2003) to generate the candidate patterns in a feedback control system, there are still needs for further studies since this previous method is applicable only to the single-loop processes with specific limiting constraints imposed upon the "speed" of control action. A more comprehensive analysis has been performed in this work and the resulting pattern-generation strategies are presented in the sequel:…”

Section: Candidate Patterns In Control Systems With Coupled Loopsmentioning

confidence: 99%

“…However, only a conceptual framework was proposed in this original study and, naturally, further improvements are required to facilitate application in a realistic environment. By incorporating the fault propagation patterns in a fuzzy inference system (FIS), Chang et al (2002) and Chang and Chang (2003) developed a systematic fault diagnosis procedure on the basis of fault trees. This method was implemented in two stages according to the flowchart given in Fig.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fuzzy diagnosis method for control systems with coupled feed forward and feedback loops

Chen

Chang

2006

Chemical Engineering Science

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“…A more comprehensive version can be found either in Chang et al (2002) or in Chang and Chang (2003). Let us use the level control system given in Fig.…”

Section: Implementation Procedures For Loop-free Systemsmentioning

confidence: 99%

Section: On-line Implementationmentioning

confidence: 99%

Section: Candidate Patterns In Control Systems With Coupled Loopsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fuzzy diagnosis method for control systems with coupled feed forward and feedback loops

Chen

Chang

2006

Chemical Engineering Science

Self Cite

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“…Artificial intelligence is growing rapidly and its applications to engineering problems have provided effective methods for process monitoring and fault diagnosis 7] . By means of attributes extraction, pattern analysis and cluster analysis, they can accomplish fault detection and diagnosis without the need of precise mathematic model [8] . Despite of predominance over the conventional approaches, single intelligent diagnostic method still suffers its own limitations.…”

Section: Introductionmentioning

confidence: 99%

Intelligent fault diagnosis in lead-zinc smelting process

Gui

Yang

Teng

2007

Int J Automat Comput

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According to the fault characteristic of the imperial smelting process (ISP), a novel intelligent integrated fault diagnostic system is developed. In the system fuzzy neural networks are utilized to extract fault symptom and expert system is employed for effective fault diagnosis of the process. Furthermore, fuzzy abductive inference is introduced to diagnose multiple faults. Feasibility of the proposed system is demonstrated through a pilot plant case study.

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A fault detection method based on horizontal visibility graph‐integrated complex networks: Application to complex chemical processes

Geng

Wang

et al. 2018

Can J Chem Eng

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With the trend towards large-scale structure and complexity in modern chemical processes, it is difficult to describe the system operating status and fault conditions via traditional approaches. In addition, there are obstacles to fault detection research in complex chemical processes due to the characteristics of the equipment hardware used in chemical systems, data collection and handling, strong internal correlations in chemical systems, factors affecting transmission, and randomness and cascade in process failures. Therefore, this paper presents a fault detection method based on horizontal visibility graph (HVG) analysis-integrated complex networks. The data for each variable in the system are regarded as a time series, each time series is modelled into a network by the horizontal visibility algorithm, and each single-layer network corresponding to a time series is abstracted as a node. Meanwhile, the correlation between two single-layer networks is used to characterize the correlation between the corresponding nodes. Moreover, a complex network structure representing the chemical system can be constructed from the correlations. In addition, according to the correlation ratio matrix obtained from the fault state and the normal state, the variance of each node determines the faulty node. Finally, we verify the validity and the effectiveness of the proposed method by applying it to the Tennessee Eastman (TE) process.

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A fuzzy-logic based fault diagnosis strategy for process control loops

Cited by 28 publications

References 8 publications

Fuzzy diagnosis method for control systems with coupled feed forward and feedback loops

Fuzzy diagnosis method for control systems with coupled feed forward and feedback loops

Intelligent fault diagnosis in lead-zinc smelting process

A fault detection method based on horizontal visibility graph‐integrated complex networks: Application to complex chemical processes

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