Advances and new directions in plant-wide disturbance detection and diagnosis

Thornhill, Nina F.; Horch, Alexander

doi:10.1016/j.conengprac.2006.10.011

Cited by 169 publications

(113 citation statements)

References 67 publications

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“…Reasons for these disturbances include hydrodynamic instabilities, compressor trips, sensor faults, sticking control valves, and controller interaction [4]. Due to tight interlinking of process equipment, these disturbances usually propagate through the plant in complex ways and diagnosing the root cause is often a challenge.…”

Section: A Fault Detection and Diagnosis In The Context Of Process Imentioning

confidence: 99%

“…This is because some of the most common sources of disturbances are control-related, such as poor controller tuning, control valve problems, sensors faults, and controller interaction [4]. These problems are aggravated by the fact that control loops are increasingly interconnected due to higher-integrated processes, which results in disturbances spreading across all process.…”

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confidence: 99%

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Importance of auxiliary systems for process fault detection and diagnosis

Cecı́lio

Chen

Thornhill

2011

2011 19th Mediterranean Conference on Control &Amp; Automation (MED)

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Abstract-In industrial processes, fault detection and diagnosis is traditionally applied separately to process and equipment without relating the information on both systems. This paper shows the interaction during fault propagation between the process and its auxiliary systems, i.e. mechanical, electrical and utility systems. Evidence is given with an industrial case study. The relevance of this finding is demonstrated by showing the advantages of including information from electrical and mechanical data in a root cause diagnosis test.

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Section: A Fault Detection and Diagnosis In The Context Of Process Imentioning

confidence: 99%

mentioning

confidence: 99%

Importance of auxiliary systems for process fault detection and diagnosis

Cecı́lio

Chen

Thornhill

2011

2011 19th Mediterranean Conference on Control &Amp; Automation (MED)

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“…The first assumption is accepted a priori, which holds for most plants (Thornhill and Horch, 2007). The second assumption is also satisfied, as a complete randomised experiment design is used to ensure that the data samples are unrelated to the time trends of disturbances.…”

Section: Experimental Designmentioning

confidence: 99%

“…Because most process control loops are approximately linear within a specific operating region, the time trends of a controlled variable are often regarded as Gaussian . Furthermore, the non-Gaussianity of a time series in a control loop is often an indication that the loop might be performing poorly (Choudhury et al, 2004;Thornhill and Horch, 2007). When the l y i and r y i are used to represent the mean and standard deviation of the time series of y i , the probability density function (PDF) can be depicted as follows:…”

Section: Functional Performance Of the Pid Controllersmentioning

confidence: 99%

Economic performance assessment of two ROM ore milling circuit controllers

Wei¹,

Craig²

2009

Minerals Engineering

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a b s t r a c tEconomic performance assessment of control systems is receiving increasing attention in both academia and industry. A relevant framework is proposed in Bauer and Craig (Bauer, M., Craig, I.K., 2008. Economic assessment of advanced process control -a survey and framework. Journal of Process Control 18 (1), 2-18) based on a comprehensive survey of the methods for economic analysis of advanced process control systems. The framework provides a formal procedure for the economic assessment of control systems. A practically motivated simulation study is used to cast the economic performance assessment of a nonlinear model predictive controller and three single-loop PID controllers for a run-of-mine milling circuit into this framework. Performance functions of the milling circuit, which dynamically relate the circuit process variables to monetary values, are developed based on a survey study on milling circuits and an in-depth literature study.

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“…One frequent cause of poor process performance is the presence of plant-wide periodical disturbances (Thornhill and Horch, 2007) whose effect can spread through the entire plant, inhibiting the process from achieving a more profitable operating point. Nowadays, plants are more coupled and have a large number of recycles because of mass and heat integration.…”

Section: Introductionmentioning

confidence: 99%

Plantwide Periodical Disturbances Isolation and Elimination in a Petrochemical Unit

Farenzena

Kayser²,

Trierweiler

2015

Braz. J. Chem. Eng.

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-Reducing process variability is crucial to reach a more profitable operating point. Periodical disturbances, however, impose barriers to achieve this goal. Their effect can be strong since one disturbance that appears in a specific loop of a highly coupled plant can be seen in several loops. Thus, isolating their source and diagnosing their cause are essential. In this work, we describe the application of spectral independent component analysis to isolate a periodical disturbance that has a strong impact on the final variability in a polyethylene plant located in Southern Brazil. After the first analysis, the source was detected and the cause identified: valve stiction. To identify the cause (valve, bad tuning, or periodic disturbance), we used the methodology based on higher-order statistics. Once the valve problem had been overcome, the product variance was reduced by 93%.

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Advances and new directions in plant-wide disturbance detection and diagnosis

Cited by 169 publications

References 67 publications

Importance of auxiliary systems for process fault detection and diagnosis

Importance of auxiliary systems for process fault detection and diagnosis

Economic performance assessment of two ROM ore milling circuit controllers

Plantwide Periodical Disturbances Isolation and Elimination in a Petrochemical Unit

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