Fouling detection in a heat exchanger: A polynomial fuzzy observer approach

Delmotte, François; Dambrine, Michel; Delrot, Sabrina; Lalot, Sylvain

doi:10.1016/j.conengprac.2013.06.004

Cited by 28 publications

(13 citation statements)

References 22 publications

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“…The principle involved in parameter estimation based fault detection is that the specific parameters of the model can be associated with faults. For example, heat transfer coefficient in heat exchanger model can be related to fouling (Delmotte et al, 2013), cross section of outlet holes related to the tank leakage (Johansson, 2000) and specific growth rate, half saturation coefficient and inhibition coefficient which affect the respiration rate in the wastewater treatment (Wimberger and Verde, 2008). With this assumption, parameters of a system are estimated on-line repeatedly using well known parameter estimation methods.…”

Section: Introductionmentioning

confidence: 99%

Parameter estimation using multiparametric programming for implicit Euler’s method based discretization

Mid

Dua

2019

Chemical Engineering Research and Design

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This work presents a study that aims to compare two discretization methods for solving parameter estimation using multiparametric programming. In our earlier work, parameter estimation using multiparametric programming was presented where model parameters were obtained as an explicit function of measurements. In this method, the nonlinear ordinary equations (ODEs) model was discretized by using explicit Euler's method to obtain algebraic

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Section: Introductionmentioning

confidence: 99%

Parameter estimation using multiparametric programming for implicit Euler’s method based discretization

Mid

Dua

2019

Chemical Engineering Research and Design

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“…For instance, Jonsson [8] proposed a non-linear physical state space model in detecting fouling in heat exchangers, which can detect fouling when the heat exchanger operates in transient states. Delmotte [9] applied a fuzzy polynomial Takagi-Sugeno representation method on the detection of the fouling occurring in a counter flow heat exchanger. Lalot [10] presented that the analysis of the evolution of the modulus of the variable computed using the lock-in technique is a simple and sensitive method for fouling detection.…”

Section: Introductionmentioning

confidence: 99%

“…To distinguish different causes and faults of low delta-T syndrome, some researchers proposed various fault detection and diagnosis (FDD) Due to the significant impact of the low delta-T syndrome on building energy performance, extensive studies have been conducted in the last two decades. Many studies focused on identifying the possible reasons of the low delta-T syndrome [5][6][7][8][9][10]. For instance, Chang [5] summarized two typical types of reasons for the low delta-T syndrome as the degradation of the heat transfer performance of coils and the coupling effect among coils.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Explanation and Fault Diagnosis of Low Delta-T Syndrome in Building Chilled Water Systems

Yan

Yang

2018

Buildings

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Low delta-T syndrome often occurs in building chilled water systems, which makes systems fail to operate as efficiently as originally anticipated. Extensive studies have been conducted on the subject of low delta-T syndrome with the aims of investigating the potential causes behind and the ways to keep delta-T high. This paper addresses to explain the causes of degrading delta-T from a mathematic perspective and to analyze the impacts of important operational parameters on the delta-T quantitatively. A simplified global cooling coil model representing the relationship between the total cooling load and the total water flow rate of chilled water systems is developed, which can be used to predict the system delta-T under different load distribution and system operation conditions. It is proved mathematically that the load distribution characteristic is an important factor in influencing the system delta-T of a chilled water system. This finding explains why the system delta-T is always lower than the delta-T of individual coils, particularly under low partial load conditions. A system-level fault detection and diagnosis (FDD) method is proposed for identifying the possible causes of the low delta-T problem. A case study is conducted to validate the proposed global model and FDD method in a real building.

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“…The study demonstrated in addition, the benefit of including models into the design phase and introduced a modified linear model that aided the determination of the optimum design parameters. Various other methods exist which include the neural networks (Riverol and Napolitano, 2005), wavelets (Ingimundardóttir and Lalot, 2011), linear parameter varying (LPV) models (Mercère et al, 2013), fuzzy observers (Delmotte et al, 2008), physical model (Gudmundsson et al, 2009), and Extended Kalman filters (Jonsson et al, 2007). Moreover, Wen et al (2017) employed a multi-resolution wavelet neural network approach for the prediction of fouling resistance of a plate heat exchanger.…”

Section: Models For Predicting Foulingmentioning

confidence: 99%

Fouling Phenomenon and Its Effect on Heat Exchanger: A Review

Ajayi¹,

Ogbonnaya²

2017

Frontiers in Heat and Mass Transfer

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Heat exchangers as a heat transfer device has gained wide applications across different levels of domestic and industrial set-ups. Various studies have been carried out to study, analyse and predict its performance. However, one major phenomenon that limits heat exchanger performance is attributed to fouling. Based on this, various studies and approaches have focused on reduction, elimination and mitigation of fouling. This study therefore focused on this. It reviewed several attempts that have been carried out to understand and mitigate the incidents of fouling in heat exchangers. The study found that despite the existing models developed towards understanding fouling, there is no single model that has provided an accurate prediction of fouling in all the different types of heat exchangers. Also, majority of existing results have limited applications and some of the solutions are only peculiar to particular type of heat exchanger. Further to this, majority of the study results only pointed to small scale laboratory test schemes and there is absence of in-situ measurements that predicts actual (real life) service performance.

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Fouling detection in a heat exchanger: A polynomial fuzzy observer approach

Cited by 28 publications

References 22 publications

Parameter estimation using multiparametric programming for implicit Euler’s method based discretization

Parameter estimation using multiparametric programming for implicit Euler’s method based discretization

Mathematical Explanation and Fault Diagnosis of Low Delta-T Syndrome in Building Chilled Water Systems

Fouling Phenomenon and Its Effect on Heat Exchanger: A Review

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