Error Compensation Method of Accelerometer While Drilling Based on DSA

In this article, the problem of accelerometer error compensation in measurement while drilling (MWD) is addressed by introducing a novel method based on the drilling spider algorithm (DSA) for identifying accelerometer error parameters. First, the output model of the micro electro mechanical system (MEMS) accelerometer is established and the error parameters are organized into a solution vector. Design the objective function of DSA through a nonlinear error function, set adaptive upper and lower bounds dimension by dimension, and simultaneously perform global and local updates to identify the error parameters. Introduce a fast oscillation deviation learning based on the centroid at each update to prevent the algorithm from falling into local optima. Finally, apply the DSA algorithm to identify the error parameters of the accelerometer. The results show that after compensation by DSA, the acceleration error is significantly reduced, the range of the well deviation angle is reduced by about 45%, and the root mean square (rms) error is reduced from 1.6° to 0.6°. Compared with particle swarm optimization (PSO) and Portia spider algorithm (PSA) algorithms, DSA has higher accuracy in identifying the error parameters of MEMS accelerometer.