An observer and signal-processing approach to FDI for the industrial actuator benchmark test

Höfling, Th.; Pfeufer, Thomas; Deibert, R.; Isermann, Rolf

doi:10.1016/0967-0661(95)00187-y

Cited by 13 publications

(4 citation statements)

References 10 publications

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“…From mid‐1980s, nonlinear processes were also brought under its ambit. The three main approaches of the model based PMFD strategies namely, models based on parameter estimation, observers and parity equations were developed concurrently (Hofling et al , 1995; Medvedev, 1995; Fuente et al , 1996).…”

Section: Evolution Of Pmfd Strategiesmentioning

confidence: 99%

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Process monitoring and fault detection strategies: a review

Das

Maiti²,

Banerjee³

2012

Int J Qual & Reliability Mgmt

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PurposeMonitoring of a process leading to the detection of faults and determination of the root causes are essential for the production of consistent good quality end products with improved yield. The history of process monitoring fault detection (PMFD) strategies can be traced back to 1930s. Thereafter various tools, techniques and approaches were developed along with their application in diversified fields. The purpose of this paper is to make a review to categorize, describe and compare the various PMFD strategies.Design/methodology/approachTaxonomy was developed to categorize PMFD strategies. The basis for the categorization was the type of techniques being employed for devising the PMFD strategies. Further, PMFD strategies were discussed in detail along with emphasis on the areas of applications. Comparative evaluations of the PMFD strategies based on some commonly identified issues were also carried out. A general framework common to all the PMFD has been presented. And lastly a discussion into future scope of research was carried out.FindingsThe techniques employed for PMFD are primarily of three types, namely data driven techniques such as statistical model based and artificial intelligent based techniques, priori knowledge based techniques, and hybrid models, with a huge dominance of the first type. The factors that should be considered in developing a PMFD strategy are ease in development, diagnostic ability, fault detection speed, robustness to noise, generalization capability, and handling of nonlinearity. The review reveals that there is no single strategy that can address all aspects related to process monitoring and fault detection efficiently and there is a need to mesh the different techniques from various PMFD strategies to devise a more efficient PMFD strategy.Research limitations/implicationsThe review documents the existing strategies for PMFD with an emphasis on finding out the nature of the strategies, data requirements, model building steps, applicability and scope for amalgamation. The review helps future researchers and practitioners to choose appropriate techniques for PMFD studies for a given situation. Further, future researchers will get a comprehensive but precise report on PMFD strategies available in the literature to date.Originality/valueThe review starts with identifying key indicators of PMFD for review and taxonomy was proposed. An analysis was conducted to identify the pattern of published articles on PMFD followed by evolution of PMFD strategies. Finally, a general framework is given for PMFD strategies for future researchers and practitioners.

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Section: Evolution Of Pmfd Strategiesmentioning

confidence: 99%

“…The model based approaches have been applied predominantly in the electrical, automobile and mechanical industries (Hofling et al , 1995; Filaretov et al , 2002; Kimmich et al , 2005). They are employed for detection of sensor and actuator faults in standalone equipment.…”

Section: Priori Knowledge Based Pmfd Strategiesmentioning

confidence: 99%

Process monitoring and fault detection strategies: a review

Das

Maiti²,

Banerjee³

2012

Int J Qual & Reliability Mgmt

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“…Chen and Patton (1999) addressed the usefulness of using adaptive threshold for modelbased FDI. Moreover, as the adaptive threshold takes measurement noise and model uncertainty into account (Patton, Frank, & Clark, 1989;Frank, 1991), this combined approach improves the monitoring performance with increased detection sensitivity and fewer false alarms (Ho¨fing, Pfeufer, Deibert, & Isermann, 1995). The reduction of false alarms is a crucial consideration for any on-line application of a condition monitoring technique.…”

Section: Introductionmentioning

confidence: 98%

The development of an adaptive threshold for model-based fault detection of a nonlinear electro-hydraulic system

Shi

Lennox

et al. 2005

Control Engineering Practice

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“…In the past two decades, there has existed a number of fault detection and diagnosis methods for digital positioners. Some efforts involved model-based approaches: state estimation [1,2,3]; parity equation [4,5]. Other studies focused on using neural networks [6,7] and signal analysis [8].…”

Section: Introductionmentioning

confidence: 99%

A simple method for fault detection of industrial digitial positioners

Huang

Feng²

2008

2008 7th World Congress on Intelligent Control and Automation

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A simple method for detecting stick-slip fault of industrial digital positioners (control valves) in control systems is presented. Only the valve travel setting signal and the actual valve travel signal are required. These two signals are available in most industrial processes, such as DCS. Therefore, the proposed method can be applicable to a large number of digital positioners with digital positioner. Meanwhile, the knowledge of the plant and the digital positioners are not necessary. Real world data sets sampled from a power plant were used to test its efficiency.

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An observer and signal-processing approach to FDI for the industrial actuator benchmark test

Cited by 13 publications

References 10 publications

Process monitoring and fault detection strategies: a review

Process monitoring and fault detection strategies: a review

The development of an adaptive threshold for model-based fault detection of a nonlinear electro-hydraulic system

A simple method for fault detection of industrial digitial positioners

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