Accelerometer Fault Detection for Rotary Steerable Drilling Tool Systems Under Strong Noises

This article is concerned with the problem of accelerometer fault detection for dynamic point-the-bit rotary steerable drilling tool systems (DPRSDTSs). The essential difficulty of this problem lies primarily in the fact that the accelerometer fault is usually submerged in strong noises induced by the mechanical vibration during the drilling process. First, DPRSDTS is modeled by a time-varying system with multiplicative noises. Subsequently, the fault detection filter and residual generator are designed by means of the Kalman filtering algorithm and the weighted moving average (WMA) method. By choosing suitable weight matrices and window length, the detectability of accelerometer fault can be ensured in a probabilistic sense. In such a case, the real false alarm rate (FAR) and missed detection rate (MDR) are reduced below the allowable level. Finally, the simulations and experiments performed on the DPRSDTS prototype are given to show the feasibility and effectiveness of the developed method.