The speed of drilling has a great relationship with the rock breaking efficiency of the bit. Based on the above background, the purpose of this article is to predict the position of shallow bit based on the vibration signal monitoring of bit broken rock. In this article, first, the mechanical research of drill string is carried out; the basic changes of the main mechanical parameters such as the axial force, torque, and bending moment of drill string are clarified; and the dynamic equilibrium equation theory of drill string system is analyzed. According to the similarity criterion, the corresponding relationship between drilling process parameters and laboratory test conditions is determined. Then, the position monitoring test system of the vibration bit is established. The acoustic emission signal and the drilling force signal of the different positions of the bit in the process of vibration rock breaking are collected synchronously by the acoustic emission sensor and the piezoelectric force sensor. Then, the denoised acoustic emission signal and drilling force signal are analyzed and processed. The mean value, variance, and mean square value of the signal are calculated in the time domain. The power spectrum of the signal is analyzed in the frequency domain. The signal is decomposed by wavelet in the time and frequency domains, and the wavelet energy coefficients of each frequency band are extracted. Through the wavelet energy coefficient calculated by the model, combined with the mean, variance, and mean square error of time-domain signal, the position of shallow buried bit can be analyzed and predicted. Finally, by fitting the results of indoor experiment and simulation experiment, it can be seen that the stress–strain curve of rock failure is basically the same, and the error is about 3.5%, which verifies the accuracy of the model.

钻速与钻头的破岩效率有很大的关系。基于上述背景，本文的目的是基于破岩的振动信号监测来预测浅钻头的位置。本文首先对钻柱进行了力学研究。弄清了钻柱轴向力，扭矩，弯矩等主要力学参数的基本变化；分析了钻柱系统的动平衡方程理论。根据相似性准则，确定钻井工艺参数与实验室试验条件之间的对应关系。然后，建立振动钻头的位置监控测试系统。在振动岩破碎过程中，钻头的不同位置的声发射信号和钻孔力信号由声发射传感器和压电力传感器同步采集。然后，对降噪后的声发射信号和钻孔力信号进行分析处理。在时域中计算信号的平均值，方差和均方值。在频域中分析信号的功率谱。信号在时域和频域中通过小波分解，并提取每个频带的小波能量系数。通过模型计算的小波能量系数，结合时域信号的均值，方差和均方误差，可以对浅埋钻头的位置进行分析和预测。