FDD Algorithm for an AHU Reverse-Return System

Abstract

A fault detection and diagnosis (FDD) algorithm was developed for an AHU reverse-return system for air cooling. These FDD rules were generated using simulation in three steps. Cause-effect rules were established by connecting the faults and their related effects. The FDD rules were developed for the following faults: old valve, fouled return pipe, fault in the outlet air temperature sensor, fault in the temperature sensor for the inlet temperature, bad position of the sensor for pressure difference. The effects of the involved faults were observed on four system performances. The results showed that increase in both the cooling coil rate and the pump rate appear due to faults in sensors. The inaccurate measurement of the pressure difference and the fault in the control valve do not affect the AHU outlet air temperatures. Increase in both the outlet air temperature and the pump power consumption appears due to the fouled return pipes.