基于标准差中位数的磁共振信号尖峰去除方法

Peak Interference Filtering Method for Surface Nuclear Magnetic Resonance Signals Based on Median of Standard Deviation

针对核磁共振探测(SNMR:Surface Nuclear Magnetic Resonance)信号因受尖峰噪声干扰严重而导致其衰减形态被破坏的问题,提出了基于标准差中位数的尖峰噪声筛选剔除方法。通过对重复采集的数据进行阈值设定,准确识别并剔除信号中混入的随机性强、幅值高的尖峰干扰。仿真实测结果表明,该方法能有效去除大于信号幅值10倍的多处尖峰噪声,同时能较好地还原真实信号的衰减形态。

Signals＇ reliability of SNMR（ Surface Nuclear Magnetic Resonance） is seriously influenced spiky noise caused by operating engineering machinery, in order to solve the problem an algorithm based on the median of standard deviation is developed and operated on artificial SNMR signals. This technique is designed to conduct threshold comparison to recognize and delete those spiky noise of strong randomness and high amplitude. By operating this method on artificial and field SNMR signals, it can be found that many spiky noise with amplitude of 10 times larger than real SNMR signal are removed. The decay shape of real SNMR signal are well restored.