深孔台阶爆破近区振动信号中常含有趋势项和高频噪声导致信号畸变失真，严重影响时频特征分析。针对此问题，构建了自适应噪声完备集合经验模态分解(complete ensemble empirical mode decomposition with adaptive noise，CEEMDAN)算法结合基于广义最小最大非凸( generalized minimax concave，GMC)惩罚项的稀疏降噪法与稀疏化基线估计消噪(baseline estimation and de-noising with sparsity，BEADS)算法的联合预处理方法。通过仿真信号验证该方法的可行性。将其应用于实际深孔台阶爆破近区振动信号的处理，并提取重构信号的时频特征，结果表明：在仿真信号实验中，本文构建的预处理方法能在有效保留信号真实成分的前提下消除高频噪声和低频趋势项的影响，相较于其他5种方法重构信号信噪比更高、均方根误差更小。在实测信号分析中，预处理后信号波形恢复正常，高频噪声成分被抑制，低频段频谱更清晰。时频特征分析发现，深孔台阶爆破近区振动信号主频较低，能量主要集中在25~150Hz范围内，极低频和高频能量占比较少。根据时频特征分析结果结合爆破安全规程对爆破参数设计给出了建议。研究结果对爆破振动信号精确分析及制定爆破振动控制措施具有重要意义。

The vibration signals in the near zone of deep-hole bench blasting often contain trend terms and noise components, causing signal distortion and affecting the analysis of time-frequency characteristics. To address this issue, a joint preprocessing method combining ICEEMDAN algorithm, GMC-penalized sparse denoising, and BEADS algorithm is proposed. The feasibility of this method is validated through simulation signals and applied to the processing of actual near-zone vibration signals from deep-hole bench blasting. The time-frequency characteristics of the reconstructed signal are extracted, and the results indicate that the proposed preprocessing method can eliminate the effects of high-frequency noise and low-frequency trend terms while effectively retaining the true components of the signal, achieving a higher signal-to-noise ratio and lower root mean square error compared to five other methods. In the analysis of actual signals, the preprocessed signal waveform is normalized, high-frequency noise is suppressed, and the low-frequency spectrum is clearer. Time-frequency characteristic analysis reveals that the main frequency of near-zone vibration signals from deep-hole bench blasting is low, with energy mainly concentrated in the 25~150 Hz range, and very low and high frequencies having a lesser energy proportion. Recommendations for blast design parameters are made based on the results of time-frequency characteristics analysis and in accordance with blasting safety regulations. This research is significant for precise analysis of blasting vibration signals and for developing vibration control measures.