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Fault Diagnosis of an Air-Handling Unit Using Artificial Neural Networks.


pdf icon Fault Diagnosis of an Air-Handling Unit Using Artificial Neural Networks. (837 K)
Lee, W. Y.; Park, C.; House, J. M.; Kelly, G. E.

AT-96-3-3;

Fault Detection and Diagnosis for HVAC Systems Symposium. Part 1. Proceedings. American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Inc. (ASHRAE). February 17-21, 1995, Atlanta, GA, 1995.

ASHRAE Transactions, Vol. 102, No. 1, 540-549, 1996.

Keywords:

air handling unit; neutral network; fault diagnosis; pattern recognition

Abstract:

The objective of this study is to describe the application of artificial neural networks to the problem of fault diagnosis in an air-handling unit. Initially, residuals of system variables that can be used to quantify the dominant symptoms of fault modes of operation are selected. Idealized steady-state patterns of the residuals are then defined for each fault mode of operation. The steady-state relationship between the dominant symptoms and the faults is learned by an artificial neural network using the backpropagation algorithm. The trained neural network is applied to experimental data for various faults and successfully idenfities each fault.