| 杨金显,李龙玺,张颖.基于IMOA的随钻陀螺仪误差补偿[J].电子测量与仪器学报,2025,39(11):64-71 |
| 基于IMOA的随钻陀螺仪误差补偿 |
| Error compensation of gyroscope while drilling based on IMOA |
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| DOI： |
| 中文关键词: 随钻测量 MEMS陀螺仪 海猫算法 误差补偿 |
| 英文关键词:measurement while drilling MEMS gyroscope meerkat optimization algorithm error compensation |
| 基金项目:河南省自然科学基金(232300421152)、国家自然科学基金(41672363)项目资助 |
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| Author | Institution |
| Yang Jinxian | 1.School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454003, China;
2.Henan Key Laboratory of Intelligent Detection and Control of Coal Min Equipment, Jiaozuo 454003, China |
| Li Longxi | 1.School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454003, China;
2.Henan Key Laboratory of Intelligent Detection and Control of Coal Min Equipment, Jiaozuo 454003, China |
| Zhang Ying | 1.School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454003, China;
2.Henan Key Laboratory of Intelligent Detection and Control of Coal Min Equipment, Jiaozuo 454003, China |
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| 中文摘要: |
| 针对陀螺仪误差参数受随钻测量环境影响难以辨识的问题，提出一种改进海猫算法(IMOA)对陀螺仪误差进行补偿。首先推导出陀螺仪误差模型并确定需要辨识的误差参数，利用加速度计输出特性建立目标函数并根据内积特性与磁模值相对误差设置约束条件。采用海猫算法(MOA)算法求解误差向量的最优值。在MOA算法的基础上，以加速计相对模值误差重新设置步长，自适应地追踪随钻环境引起的陀螺仪信号改变；设计引导式螺旋全局更新方式，在更新中设置引导因子判断当前搜索方向的优劣并利用逐维奖励机制使得不同参数在信息交流时，较大程度保留了最优解，防止陷入局部最优。设置局部迁移路线，重新定义偏差为当前个体辨识的误差参数与历史最优误差参数的笛卡尔距离；同时加入逐维扰动策略，保留各维误差参数的最优解。最后将IMOA算法应用于识别陀螺仪误差参数，结果表明，IMOA算法补偿后的陀螺输出误差明显减小，井斜角误差由9.54°降低至2.53°，相对于PSO算法和MOA算法具有更高的识别精度。 |
| 英文摘要: |
| Aiming at the problem that the error parameters of the gyroscope are difficult to identify due to the influence of the measurement environment while drilling, an improved meerkat optimization algorithm (IMOA) is proposed to compensate for the gyroscope error. Firstly, the gyroscope error model is derived and the error parameters that need to be identified are determined. The objective function is established by using the output characteristics of the accelerometer, and the constraint conditions are set according to the inner product characteristics and the relative error of the magnetic modulus value. The meerkat optimization algorithm (MOA) is adopted to solve the optimal value of the error vector. Based on the MOA algorithm, the step size is reset with the relative modulus error of the accelerometer to adaptively track the changes in the gyroscope signal caused by the drilling environment. A guided spiral global update method is designed. During the update, a guiding factor is set to judge the superiority or inferiority of the current search direction, and a per-dimensional reward mechanism is utilized to ensure that different parameters retain the optimal solution to a large extent when exchanging information, preventing falling into local optimum. Set the local migration route and redefine the deviation as the cartesian distance between the error parameter of the current individual identification and the historical optimal error parameter; Meanwhile, the per-dimensional perturbation strategy is added to retain the optimal solutions of the error parameters in each dimension. Finally, the IMOA algorithm was applied to identify the error parameters of the gyroscope. The results show that the output error of the gyroscope after compensation by the IMOA algorithm is significantly reduced, and the well slope angle error is reduced from 9.54° to 2.53°. Compared with the PSO algorithm and the MOA algorithm, it has higher recognition accuracy. |
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