Baseline drift correction and de-noising method of shaft lining vibration signal in near field of freezing vertical shaft blasting
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摘要: 冻结立井爆破过程中,近区监测信号中含有的基线漂零及噪声成分对其局部特征精细化提取影响显著。在对近区井壁振动信号有效采集基础上,通过互补总体经验模态分解(complementary ensemble empirical mode decomposition, CEEMD)方法、稀疏化基线估计消噪(baseline estimation and de-noising with sparsity, BEADS)方法和隐马尔可夫模型消噪(hidden Markov model de-noising, HMMD)方法等,解决了信号中基线漂移和随机噪声消除难题,并采用交叉小波变换对校正和消噪效果进行了相关性评价。实例分析结果表明:信号中缓变的基线成分遍历信号各个模态分量的整个过程,且主要集中于低频分量中,而噪声则集中在高频分量。组合分析方法对低频基线漂零和高频噪声的处理效果好,是一种高效且相对保幅的信号分析方法,可用于批量信号数据的预处理过程。Abstract: In the process of freezing vertical shaft blasting, the baseline drift and noise in the near area monitoring signal have significant influence on the fine extraction of local characteristics. On the basis of effective acquisition of shaft lining vibration signals in near field of blasting, complementary ensemble empirical mode decomposition (CEEMD) method, baseline estimation and de-noising with sparsity (BEADS) method and hidden Markov model de-noising (HMMD) method and so on are used to solve the problem of baseline drift and random noise elimination in the signal, and the correlation evaluation of correction and noise elimination effect is carried out by cross wavelet transform (CWT). The analysis results show that: the slowly changing baseline component in the signal exists the whole process of each modal component, and it is mainly concentrated in the low frequency component, while the noise is concentrated in the high frequency component. The combined analysis method can deal with low frequency baseline drift and high frequency noise effectively. It is an efficient and relatively amplitude-preserving signal analysis method, and can be used to preprocess of batch blasting vibration signal data.
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表 1 模态分量与原信号相关度
Table 1. Correlation between components and original signals
IMF 相关性系数 IMF 相关性系数 IMF 相关性系数 1 0.4202 5 0.5023 9 0.1083 2 0.4484 6 0.1419 10 0.3707 3 0.3754 7 0.1333 11 0.4540 4 0.4124 8 0.1364 12 0.2940 表 2 不同方法消噪性能指标
Table 2. Indexes of noise reduction performance
去噪方法 评价指标 SNR RMSE CC PE MD 3.442 0.581 0.816 1.758 SVD 20.983 0.379 0.896 1.175 WED 21.397 0.374 0.921 0.492 HMMD 43.371 0.056 0.992 0.244 -
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