基于自适应阈值的小波包在松动部件信噪分离中的研究

Research on Signal-noise Separation in Loose Parts Impact Signal Based on Autonomous Adaptive Threshold Wavelet Packets

研究了反应堆主回路系统背景振动噪声的特点。在传统松动部件信号提取方法的基础上,利用对小波包系数加入时间窗的方法实现对去噪阈值进行自适应选取。同时采用了一种新的阈值处理函数对含噪声的松动部件冲击信号进行去噪处理,并对模拟实验装置上采集到的钢球冲击信号进行分析。实验结果表明,本文提出的方法能有效跟踪背景噪声强度的变化,有效抑制背景噪声,准确识别松动部件冲击信号,提取相关特征。

The characteristics of background vibration noise in reactor primary system were studied .Based on the traditional signal extraction methods from loose parts ,the de‐noising autonomous adaptive threshold was chosen by using the method of adding time window to wavelet packets coefficients .At the same time ,a new threshold pro‐cessing function was adapted to implement the de‐noise process to the loose parts impact signal ,and the collected impact signal of steel ball from experimental apparatus was analyzed .The results show that the method in this article can effectively track the change of noise intensity and restrain background noise ,and correctly identify impact signal of loose parts and extract relevant features .