CHEN Xu1, 2, ZHENG Xiaoliang1, 3, 4, XUE Sheng1, 2, 4, PANG Jingyu1, 2, YANG Zhiqiang4
Journal of Vibration and Shock. 2026, 45(16): 101-111.
Measurement-while-drilling lithology measurement is a key link in building a transparent geological model of coal mines. To achieve real-time lithology identification during drilling, a method based on multi-domain features and GWO-SVM is proposed by utilizing the triaxial vibration response near the drill bit. Firstly, the triaxial vibration acceleration signals are decomposed by continuous variational mode decomposition (SVMD), and the IMFs rich in features are selected based on the multi-scale sample entropy criterion and the signals are reconstructed. Then, a statistical feature extraction module for time domain, frequency domain and time-frequency domain features and a recurrence plot (RP) image feature extraction module are constructed. Finally, the statistical features and image features are concatenated into a multi-domain fusion feature vector and input into the SVM classification model optimized by GWO with the Pareto mechanism to achieve lithology identification. To verify the effectiveness of the method, a logging-while-drilling lithology measurement platform was built, a near-bit measurement subassembly was designed, seven types of rock samples made of similar materials were prepared, and a lithology identification dataset was constructed. Through ablation experiments, comparisons of different signal reconstruction methods and different classification models, it is shown that the proposed method achieves an average recognition accuracy of 98.48% for seven types of lithologies under four working conditions. Its signal reconstruction effect is superior to that of variational mode decomposition, empirical mode decomposition and complete ensemble empirical mode decomposition with adaptive noise methods, and its classification performance is significantly better than that of typical models such as BP neural network, K-nearest neighbor algorithm,Decision Tree and MobileViT,It can achieve efficient and accurate lithology identification during drilling.
