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标题：Performance Assessment of Heat Exchanger Using Mamdani Based Adaptive Neuro-Fuzzy Inference System (M-ANFIS) and Dynamic Fuzzy Reliability Modeling
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作者：Pravin Kumar Borkar ; Manoj Jha ; M. F. Qureshi 等
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2014
卷号：3
期号：9
页码：16083
DOI：10.15680/IJIRSET.2014.0309043
出版社：S&S Publications
摘要：Performance monitoring system for shell and tube heat exchanger is developed using MamdaniAdaptive Neuro-Fuzzy Inference System (M-ANFIS). Experiments are conducted based on full factorial design ofexperiments to develop a model using the parameters such as temperatures and flow rates. M-ANFIS model for overallheat transfer coefficient of a design /clean heat exchanger system is developed. The developed model is validated andtested by comparing the results with the experimental results. This model is used to assess the performance of heatexchanger with the real/fouled system. The performance degradation is expressed using fouling factor (FF), which isderived from the overall heat transfer coefficient of design system and real system. Hybrid algorithm is the hot issue inComputational Intelligence (CI) study. From in-depth discussion on Simulation Mechanism Based (SMB) classificationmethod and composite patterns, this paper presents the Mamdani model based Adaptive Neural Fuzzy InferenceSystem (M-ANFIS) and weight updating formula in consideration with qualitative representation of inferenceconsequent parts in fuzzy neural networks. M-ANFIS model adopts Mamdani fuzzy inference system which hasadvantages in consequent part. Experiment results of applying M-ANFIS to evaluate Reliable Performance Assessmentof Heat Exchanger show that M-ANFIS, as a new hybrid algorithm in computational intelligence, has great advantagesin non-linear modeling, membership functions in consequent parts, scale of training data and amount of adjustedparameters. This paper proposes a new perspective and methodology to model the fouling factor (FF) of the heatexchanger using the fuzzy reliability theory. We propose to use the indicator or performance or substitute variablewhich is very well understood by the power plant engineer to fuzzify the states of heat exchanger.
关键词：Heat exchanger; Overall heat transfer coefficient; Fouling factor (FF); Fuzzy reliability; performance;characteristics; Mamdani Adaptive Neuro-Fuzzy Inference System (M-ANFIS).