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Pile-up Reconstruction Algorithm for High Count Rate Gamma-Ray Spectrometry

机译:高计率伽马射线光谱法的堆积重建算法

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In high count rate γ-ray spectrometry, the pile-up phenomenon turns out to be an important problem with respect to energy resolution and detection efficiency. Pile-up effects occur when two events are detected so close in time that instrumentation cannot properly extract information from both of them. Because this kind of data is incorrect and marginally useful, such data had to be rejected in traditional pulse processors. In times of digital pulse processing however, one can reconstruct piled-up pulse amplitudes by special algebraic approaches. In fully digital signal acquisition, the moving window deconvolution (MWD) method is commonly used. This method requires two parameters to be carefully set, namely the flattop time (dictated by the maximum rise time of the signal) and the shaping time, to accomplish the best possible energy resolution. In this way, the maximum energy resolution is accomplished, but a lot of piled-up events are rejected, reducing detection efficiency. We propose a method that restores some of the pile-up events, using a parallel block MWD implementation where the shaping time parameter differs for every MWD block. Careful detection of as many true events as possible, as well as determining their exact occurrence in time (their respective timestamps) is the key in getting the most out of the measured signal. With proper analysis logic we get more experimental information through reduced dead time, at the cost of controlled and selectively worsened energy resolution, on an event-by-event basis, achieving better overall detection efficiency. This method was tested on real experimental data where the detection efficiency of our method is higher, by a factor of 4.4(9), than the efficiency of a standard method with pile-up rejection at 500 kcps count rate.
机译:在高计数率γ射线光谱法中,堆积现象结果是关于能量分辨率和检测效率的重要问题。当检测到两个事件时发生堆积效果,以便在时间内识别出来无法正确提取它们的信息。因为这种数据不正确且略微有用,所以必须在传统的脉冲处理器中拒绝这种数据。然而,在数字脉冲处理的时间内,可以通过特殊代数方法重建堆积脉冲幅度。在完全数字信号采集中,通常使用移动窗口解卷积(MWD)方法。该方法需要仔细设置两个参数,即圆形时间(由信号的最大上升时间)和成形时间,以实现最佳的能量分辨率。以这种方式,完成了最大能量分辨率,但拒绝了大量堆积事件,降低了检测效率。我们提出了一种方法,该方法使用并行块MWD实现来恢复一些堆积事件,其中整形时间参数对每个MWD块不同。仔细检测尽可能多的真实事件,以及确定它们的确切发生时间(它们各自的时间戳)是充分利用测量信号的关键。通过适当的分析逻辑,我们通过减少死区时间来获得更多的实验信息,以控制和选择性地恶化能量分辨率,实现更好的整体检测效率。在实际实验数据上测试该方法,其中我们方法的检测效率较高,倍率为4.4(9),而不是在500kCPS计数率下堆积抑制的标准方法的效率。

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