Detection of fouling in a cross-flow heat exchanger using a neural network based technique |
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| Authors: | Sylvain Lalot Halldór Pálsson |
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| Affiliation: | 1. Department of Mechanical Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia;2. Department of Built Environment, Liverpool John Moores University, Byron Street, Liverpool, L3 3AF, United Kingdom;3. Department of Chemical Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran;4. Department of Mechanical and Aerospace Engineering Missouri, University of Science and Technology, Rolla, 65409, MO, United States |
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| Abstract: | This paper presents a method for the detection of fouling in a cross-flow heat exchanger. A numerical model is used to generate data when the heat exchanger is clean and corresponding data when fouling occurs. In a first step, the model is used to generate a long time series by simulating a clean heat exchanger. This allows the determination of a neural network model of the heat exchanger. Then, hundred sets of data are generated by simulating a fouled heat exchanger and it is checked that the simple Cusum test can be used to detect fouling without any false alarm, whatever the reference time series is. |
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