In this paper a sensor fault detection and isolation procedure based on principal component analysis is proposed to monitor an air quality monitoring network. The PCA model of the network is optimal with respect to a reconstruction error criterion. The sensor fault detection is carried out in various residual subspaces using a new detection index. The reconstruction approach allows, on one hand, by combining it with the detection index, to isolate the faulty sensors and, on the other hand, to estimate the fault amplitudes. Diagnosis, principal component analysis, sensor failure detection and isolation, reconstruction approach, air quality monitoring network.
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering