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Fault Diagnosis and Temperature Sensor Recovery for an Air-Handling Unit.


pdf icon Fault Diagnosis and Temperature Sensor Recovery for an Air-Handling Unit. (1324 K)
Lee, W. Y.; House, J. M.; Shin, D. R.

ASHRAE Transactions, Vol. 103, No. 1, [pages unknown], 1997.

Keywords:

heating; ventilation; air conditioning; sensors; fault diagnosis; neural network; equations; temperature

Abstract:

This paper describes the use of a two-stage artificial neural network for fault diagnosis in a simulated air-handling unit. The stage one neural network is trained to identify the subsystem in which a fault occurs. The stage two neural network is trained to diagnose the specific cause of a fault at the subsystem level. Regression equations for the supply and mixed-air temperatures are obtained from simulation data and are used to compute input parameters to the neural networkd. Simulation results are presented that demonstrate that, after a successful diagnosis of a supply air temperature sensor fault, the recovered estimate of the supply air temperature obtained from the regression equaiton can be used in a feedback control loop to bring the supply air temperature back to the setpoint value. Results are also presented that illustrate the evolution of the diagnosis of the two-stage artificial neural network from normal operation to various fault modes of operation.