Improving heat exchanger supervision using neural networks and rule based techniques

Authors:
Ramon Ferreiro Garcia
Affiliations:
Dept. Industrial Engineering, University of A Coruna, ETSNM, C/Paseo de Ronda, 51, 15011 A Coruna, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

Citing 8
Cited 3

Robust fault detection and diagnosis in a class of nonlinear systems using a neural sliding mode observer

International Journal of Systems Science - Advances in Sliding Mode Observation and Estimation (Part Two)
Confidence estimation of GMDH neural networks and its application in fault detection systems

International Journal of Systems Science
Using neural networks for fault detection in a distillation column

International Journal of Computer Applications in Technology
A recurrent neural-network-based sensor and actuator fault detection and isolation for nonlinear systems with application to the satellite's attitude control subsystem

IEEE Transactions on Neural Networks
Fault detection and diagnosis based on modeling and estimation methods

IEEE Transactions on Neural Networks
SVM based regression schemes for instruments fault accommodation in automotive systems

ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Process fault detection based on modeling and estimation methods-A survey

Automatica (Journal of IFAC)
Fault Detection in Mechanical Systems With Friction Phenomena: An Online Neural Approximation Approach

IEEE Transactions on Neural Networks

Fault detection and precedent-free localization in numerically discretized thermal-fluid systems

Expert Systems with Applications: An International Journal
Expert condition monitoring on hydrostatic self-levitating bearings

Expert Systems with Applications: An International Journal
On-line signature verification using vertical signature partitioning

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	12.06

Visualization

Abstract

The work is aiming to the supervision of heat exchangers fouling monitoring. The fouling known as deposition of undesirable material on the heat transfer surface degrades the performance of heat exchangers. The fouling of heat exchangers in process plants results in a significant cost impact in terms of production losses, energy efficiency, and maintenance costs. To overcome mentioned inconveniences a novel supervision strategy is proposed, reporting innovative techniques and main results of an application tool to diagnose the heat transfer efficiency of a heat exchanger of a pilot plant using neural network based models and parity space approaches associated to a rule based decision making strategy. The developed strategy is fragmented into several modules connected between them following a causal logic flowchart. The first module checks the consistence of the supervision system. The second module monitories the heat exchanger for fouling condition with the ability to diagnose the probable causes of fouling. A third module predicts the remaining operating time under acceptable conditions, associated to a decision making task to schedule the supervision flowchart.