On the development of a sliding mode observer-based fault diagnosis scheme for a wind turbine benchmark model

Abstract

This paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. The methodology is based on a modified sliding mode observer (SMO) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. The faults are reconstructed using the equivalent output error injection signal. A well-known validated wind turbine benchmark model, developed by Aalborg University and KK-electronic a/c, is utilized to evaluate the FDD scheme. Different sensors and actuator fault scenarios are simulated in the drive train, generator, and pitch & blade subsystems of the benchmark model, and attempts have been made to estimate these faults via the proposed modified SMO. The simulation results confirm the effectiveness of the proposed diagnosis scheme, and the faults are well detected, isolated, and reconstructed in the presence of the measurement noise.