A principal component analysis method for fault detection, fault identification, and fault reconstruction of air-conditioning system sensors is proposed. The principal component analysis method divides the measurement space into principal component subspace and residual subspace. The SPE index and SVI index are used to detect and identify faults, respectively. Along the fault direction, the measurement data gradually approaches the principal component subspace to achieve data reconstruction. The results of sensor fault detection and diagnosis of air-conditioning monitoring system show that the PCA method has good fault detection, identification, and reconstruction capabilities. Keywords : principal component analysis ( PCA) ; sensor fault ;fault detection and diagnosis ;HVAC sys2 tem
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