Sensitivity analysis for PCA-based chiller sensor fault detection

This paper presents an algebraic solution of erroneous sensor's undetectable boundary to evaluate the sensitivity of chiller sensor fault detection based on principal component analysis. Q-statistic of PCA is normally applied as a collective statistical index to detect sensor fault by comparing its value with the threshold. However, Q-statistic has no specific physical meaning and cannot evaluate the sensitivity of the provided method for sensor fault detection. We analyzed the definition of Q-statistic and derived the numerical value of the minimum range not to detect sensor fault. Bias sensor fault of a fielded screw chiller was studied for each sensor in PCA model by introducing different severity levels. Results showed that each sensor has different fault detection sensitivity using the same PCA model. The undetectable boundary can be a criterion used to evaluate the detection sensitivity of PCA-based method easily. (C) 2016 Elsevier Ltd and International Institute of Refrigeration. All rights reserved.