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.
| Original language | English |
|---|---|
| Pages (from-to) | 675-679 |
| Number of pages | 5 |
| Journal | International Journal of Thermal Sciences |
| Volume | 49 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Apr 2010 |
Bibliographical note
Funding Information:This work would have not been carried out without the French/Icelandic Jules Verne program. Hence, the support of Rannís – The Icelandic Centre for Research – and the French Ministry of Foreign Affairs (under contract EGIDE 18990VL) is greatly acknowledged. This work is also part of the DESURENEIR project partly sponsored by the CNRS. This financial support is also greatly acknowledged.
Other keywords
- Detection
- Fouling
- Heat exchanger
- Neural network
- Numerical modelling