Fault Diagnosis of an Air-Handling Unit Using Artificial Neural Networks.
Fault Diagnosis of an Air-Handling Unit Using Artificial
Lee, W. Y.; Park, C.; House, J. M.; Kelly, G. E.
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.
air handling unit; neutral network; fault diagnosis;
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.