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摘要：在当代通信系统中，由于信号中常常夹杂着各种复杂元素，所以当中信号分析都是用滤波器来进行的。使用γ谱仪进行的能谱采集与核素识别在核监测中更是一项应用广泛的核心技术，核素识别算法和便携式数字化γ能谱采集技术是数字化谱仪系统的核心与重要组成部分，所以当中的不必要的信号通过FIR低通滤波器来实现去除信号中的噪声，来提高信噪比。数字滤波器是通过数值运算实现滤波，具有处理精度高、灵活、稳定、不存在阻抗匹配问题，可以实现模拟滤波器无法实现的特殊滤波功能。
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从频域的角度来看，γ能谱的统计涨落，即噪声在频域的分布是从-∞~+∞的整个频域范围，而有用的信号都主要分布在频域内低频部分，因此数字滤波器通常使用低通滤波器，使得低频有用信号得以极大的保留，高频噪声得到抑制。 对于不同的低通滤波器构造方法，文献中提出了许多不同的平滑算法。从时域角度出发，有最小二乘法；从频域角度出发，有 FIR 低通滤波法。针对便携式谱仪要求运算简单的特点，本文主要采用C#实现FIR低通滤波去噪平滑。19866
关键词： 便携式γ谱仪；C#；FIR低通滤波器；去噪平滑
Smoothing Algorithm FIR low-pass filter de-noising
Abstract: In modern communication systems , the signal is often mixed with a variety of complex elements, which are signal analysis performed by the filter . Use γ spectrometer spectrum acquisition and nuclide identification in nuclear monitoring is a widely used core technologies , radionuclide identification algorithm and portable digital γ spectrum acquisition technology is an important part of the core and the digital spectrometer system , Therefore, the unwanted signal by which the low -pass FIR filter to effect removal of noise in the signal to noise ratio . The digital filter is realized by numerical filtering operation , with high processing accuracy , flexibility , stability, and there is no impedance matching , special filtering can not be achieved in analog filters .
From the perspective of the frequency domain view , γ spectrum of statistical fluctuation , namely the distribution of noise in the frequency domain is from - ∞ ~ + ∞ entire frequency domain , and useful signals are mainly distributed in the low-frequency portion of the frequency domain , and therefore digital filters are typically low-pass filter , so that the frequency of the useful signal can be greatly retained , high frequency noise is suppressed. Different methods for the low -pass filter structure , proposed in the literature many different smoothing algorithms. From the time domain perspective, there is least squares method ; starting from the frequency domain point of view, there FIR low-pass filtering . Puyi requirements for portable computing simple , this paper mainly uses the C # implementation of FIR low-pass filtering noise smoothing .
Keywords: Portable γ spectrometer; C #; FIR low-pass filter; denoising smoothing
目录
摘要 iii
Abstract iv
目录 v
1 绪论 1
1.1 便携式Γ能谱分析的目的、意义 1
1.2 便携式数字化谱仪的研究现状 1
1.3 论文主要研究内容 4
1.3.1 便携式数字γ能谱仪结构与系统 4
1.3.2 不同低通滤波器的设计方法 4
1.3.3 用C#实现FIR低通滤波去噪平滑算法 4
2 数字γ能谱仪结构与系统 6