首页> 外国专利> PUMP NOISE CANCELLATION METHOD USING EMPIRICAL MODE DECOMPOSITION AND PARTICLE SWARM OPTIMISATION ALGORITHM

PUMP NOISE CANCELLATION METHOD USING EMPIRICAL MODE DECOMPOSITION AND PARTICLE SWARM OPTIMISATION ALGORITHM

机译:基于经验模态分解和粒子群优化算法的泵噪声消除方法

摘要

A pump noise cancellation method using empirical mode decomposition and a particle swarm optimisation algorithm, the method being based on the assumption that the pump noise is a linear combination of a set of bases; after extraction of pump noise samples, using empirical mode decomposition to decompose the extracted pump noise samples into a set of signals acting as bases; by means of a particle swarm optimisation algorithm, finding the coefficients of the best linear combination of said set of bases; and updating the pump noise samples to enhance the noise cancellation effect. The present invention corrects current pump noise samples in a weighted manner in a limited number of noise cancellation periods, gradually converging same into a pump noise waveform in a changed unit period in a limited number of iterations, in order to adapt to the slow change of the pump noise during long-term operation of the system.
机译:一种采用经验模式分解和粒子群优化算法的泵噪声消除方法,该方法基于以下假设:泵噪声是一组基数的线性组合。在提取出泵浦噪声样本后,采用经验模式分解将提取出的泵浦噪声样本分解为一组信号作为基数;通过粒子群优化算法,找到所述基组的最佳线性组合的系数;更新泵噪声样本以增强噪声消除效果。本发明在有限数量的噪声消除周期中以加权方式校正当前的泵噪声样本,以有限的迭代次数在改变的单位周期内将其逐渐收敛为泵噪声波形,以适应噪声的缓慢变化。系统长期运行期间的泵噪声。

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