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针对微震监测系统中事先难以确定被监测的微震信号振幅大小,无法设置最合适增益问题,提出了一种快、慢增益调整的自适应增益算法.在增益调整时,先使用前一周期采样数据求取其平均值,再和参考值比较,生成快增益调整值,对本周期数据进行快速增益调整;对于一些瞬时的冲击信号,采用慢增益调整,利用LMS自适应增益算法计算慢增益调整值.采用自相关算法对输入的微震信号和随机噪声进行识别,使得微震监测系统对微震信号和随机噪声进行有选择的增益放大.结果表明:利用该自适应增益算法对微震信号和随机噪声进行自适应增益调整,当最大微震信号振幅达到AD量程的90%时,最小微震信号振幅可达到AD量程的30%,而噪声信号接近于0.
Aiming at the difficulty of determining the amplitude of the microseismic signal to be monitored in the microseismic monitoring system and setting the most suitable gain, a fast and slow gain adaptive gain algorithm is proposed. In the gain adjustment, the sampling data of the previous period Calculate the average value, compare with the reference value to generate fast gain adjustment value, and adjust the fast gain of this period data. For some instantaneous impact signals, slow gain adjustment is adopted, and slow gain adjustment value is calculated by LMS adaptive gain algorithm. The autocorrelation algorithm is used to identify the input microseismic signals and random noise, so that the microseismic monitoring system can selectively amplify the microseismic signals and random noise.The results show that the adaptive gain algorithm can adaptively adapt the microseismic signals and random noise When the maximum amplitude of the microseismic signal reaches 90% of the AD range, the minimum amplitude of the microseismic signal can reach 30% of the AD range while the noise signal approaches zero.