基于粒子群算法的多次反射飞行时间质量分析器电压优化
Voltage Optimization of Multiple Reflection Time of Flight Mass Analyzer Based on Particle Swarm Optimization Algorithm
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摘要: 多次反射飞行时间(MR-TOF)是一种新型的质量分析器，常用于分析短寿命离子、分离同重元素和存储离子。随着使用需求的增加，提高MR-TOF质量分析器的分辨能力越来越重要。然而，MR-TOF质量分析器电压参数的优化涉及高维度、高精细度和非线性的问题，很难用解析方法得到最优参数。本研究提出了一种基于粒子群（PSO）算法的MR-TOF质量分析器电压参数优化方法，并对粒子群算法进行改进。在SIMION离子光学仿真平台上对优化方法进行测试，比较了标准粒子群算法和改进粒子群算法的优化结果。结果表明，改进粒子群算法能够获得超过810 000的极限质量分辨率，相比标准粒子群算法有更好的性能。该方法具有操作简单、优化速度快、求解效果好等优点，可为MR-TOF质量分析器的电压优化提供方法参考，从而提高MR-TOF质量分析器的开发效率。
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关键词:
- 多次反射飞行时间质量分析器 /
- 粒子群算法（PSO） /
- 电压优化 /
- 离子光学模拟
Abstract: Time-of-flight mass spectrometry is a commonly mass spectrometry technique that is widely used in biomedicine, environmental science and food science. The multiple reflection time-of-flight (MR-TOF) mass analyzer is a new type of mass analyzer with ultra-high mass resolution and has been used at institutions, such as Helmholtz Centre for Heavy Ion Research (GSI), European Organization for Nuclear Research (CERN) and High Energy Accelerator Research Organization (KEK) to measure short-lived ion masses, separate isobar and store ions. As the demand for use increasing, it is becoming important to improve the resolving power of MR-TOF mass analyzers. However, the optimization of the voltage parameters of MR-TOF mass analyzers is a high-dimensional, highly refined and non-linear problem, which is difficult to solve optimally by analytical method. In this study, a particle swarm optimization (PSO) algorithm-based method for optimizing the voltage parameters of MR-TOF mass analyzers was proposed. The method used an improved particle swarm optimization (IPSO) approach with a inertia weight decay strategy. The optimization method was tested on the SIMION ion optics simulation platform. Considering 133Cs+ ion with E=1.5 keV, δE=8.5 eV, δx=δy=1 mm, δα=δβ=1.5 mrad, a mass resolving power over 8.1×105 was achieved when Δt=0 ns and a mass resolving power over 5.0×105 was achieved when Δt=20 ns. IPSO optimized the best results to achieve the 2nd order focus of time with respect to energy for the MR-TOF mass analyzer, and the deviation of the ion′s half-turn time of flight was within 1.3×10-6. In 20 times experiments, IPSO improved the maximum results by 33%, the average results by 35% and the standard deviation by 29% compared with PSO optimization, providing better solution quality and stability. IPSO′s linear decay strategy effectively controlled the reduction of the voltage update step size and was able to meet the global search and refinement of the MR-TOF mass analyzer voltage parameter optimization problem. It had good convergence and convergence speed. This work provided a fast and effective method for optimizing the voltage parameters of the MR-TOF mass analyzer and helped to improve the performance of this analyzer. The results showed that the IPSO is able to obtain a limiting mass resolution of more than 810 000, which has better performance compared with the PSO. The method has the advantages of simple operation, fast optimization and better solution, which can provide a method reference for voltage optimization of MR-TOF mass analyzer and thus improve the development efficiency of MR-TOF mass analyzer. -
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