Sensor fault detection and validation of VAV terminals in air conditioning systems

Abstract

Sensor failure and bias are harmful to the process control of air conditioning systems, resulting in poor control of the indoor environment and waste of energy. A strategy is developed for the flow sensor fault detection and validation of variable air volume (VAV) terminals in air conditioning systems. Principal component analysis (PCA) models at both system and terminal levels are built and employed in the strategy. Sensor faults are detected using both the T2 statistic and square prediction error (SPE) and isolated using the SPE contribution plot. As the reliability and sensitivity of fault isolation may be affected by multiple faults at the system level, a terminal level PCA model is designed to further examine the suspicious terminals. The faulty sensor is reconstructed after it is isolated by the strategy, and the FDD strategy repeats using the recovered measurements until no further fault can be detected. Thus, the sensitivity and robustness of the FDD strategy is enhanced significantly. The sensor fault detection and validation strategy, as well as the sensor reconstruction strategy for fault tolerant control, are evaluated by simulation and field tests.