基于数字BPM的强流加速器束流诊断研究

Beam diagnostics is vital important for the accelerator commissioning of high density synchrotron. With the turn-by-turn BPM widely installed in modern accelerator, treating data recorded by turn-by-turn BPM is becoming research hotspots in the field of beam diagnosing. Much information of the beam can be contained in the turn-by-turn data. After the modes are extracted, the lattice will be constructed and some other sources will also be figured, and that is the common process in beam diagnostics. Based on the common modes extraction methods, it is not easy to get the modes because they are always strongly mixed. The Independent Component Analysis is a robust method in data mining and modes extraction, besides separating the strong coupling modes, and it also works well in extracting the weak modes with high noises. These weak modes may correspond to the mismatch of longitudinal motion, injection modes, and nonlinear fields of the magnets, quadruples fringe field, and space charge effects and so on. This subject is not only extracting the strong modes more precisely with the independent component analysis, but also creative on the extracting method of weak modes and the diagnosis scope. The results can also be useful for the heavy-ion accelerator beam diagnostics.

强流同步加速器的束流诊断对于加速器的运行效率至关重要。数字BPM在现代加速器上的广泛使用，使得利用BPM的逐圈数据诊断束流状态成为研究的热点。BPM的逐圈数据富含束流的运动信息，对BPM的逐圈数据进行模式提取，反演得到磁聚焦结构参数以及相关激励源是束流诊断的常用方法。强流同步加速器的模式往往表现出很强的耦合特征，给常规的束流诊断方法带来了很大的困难。独立成分分析方法是一种强健的数据挖据，模式提取方法，不仅能够分离强耦合的模式，也能够在较高的噪声范围下提取到较弱的模式。这些弱模式可能来自于束流纵向的失匹，注入模式的差异，磁铁元件的非线性场、四极磁铁的边缘场，空间电荷效应等。课题拟以独立成分分析方法为基础，不仅能够更加精确地获得BPM逐圈数据中较强模式对应的束流参数，同时在弱模式的提取方法以及其对应的诊断对象方面做创新研究。研究成果对国内重粒子加速器的束流诊断也有很好的参考意义。

强流加速器功率的逐步提高，对加速器束流光学参数的精确控制提出了更高的要求。近年来，随着环形加速器开始大量安装使用逐圈BPM记录束流通过BPM的每圈信息，如何利用逐圈BPM快速获取数据的优点，在加速器运行较为稳定的时间内快速获取束流光学参数是大多数加速器调试运行需要考虑的问题。本课题依托于中国散裂中子源的调束条件，应用基于盲信号分析的独立成分分析方法，在中国散裂中子源调束中快速获取了束流光学参数。同时，为了更好的控制束流光学参数，本课题也利用磁测数据对加速器模型做了更为精确的描述，对影响测量结果的BPM Offset做了标定。