Fault detection system and method using multiway principal component analysis

摘要

A fault detection system and method is provided that facilitates detection of faults that are manifest over a plurality of different operational phases. The fault detection system and method use multiway principal component analysis (MPCA) to detect fault from turbine engine sensor data. Specifically, the fault detection system uses a plurality of load vectors, each of the plurality of load vectors representing a principal component in the turbine engine sensor data from the multiple operational phases. The load vectors are preferably developed using sets of historical sensor data. When developed using historical data covering multiple operational phases, the load vectors can be used to detect likely faults in turbine engines. Specifically, new sensor data from the multiple operational phases is projected on to the load vectors, generating a plurality of statistical measures that can be classified to determine if a fault is manifest in the new sensor data.