Sensor fault detection and isolation based on zonotopic Kalman Filter for accelerometer system in drilling tools

Abstract

Sensor faults of the accelerometer system impact the efficiency and security of the drilling process, so the sensor fault detection and isolation are significant. However, there are insufficient relevant studies on the accelerometer system affected by time-varying disturbances with unknown bounds. This paper proposes a residual generator based on the Zonotopic Kalman Filter with the process disturbance estimation, and the bounds of parametric uncertainties and measurement noises are obtained by calibration. Then, a fault detection test is realized by time-varying residual bounds regarded as the combinations of residuals and dynamic thresholds. Moreover, a fault isolation decision is developed by analyzing fault directions. Finally, simulation and experiment results demonstrate the effectiveness of the proposed method. The proposed method estimates time-varying process disturbances and performs better than existing methods. This paper provides a reference for the reliable application of the accelerometer system.