Adaptive Optimization Of Time-of-Flight Mass Spectrometer Ion Optical System Based On Genetic Algorithm

The voltage parameters are critical to the performance of time-of-flight mass spectrometer(TOFMS)such as sensitivity and resolution.The complex mass spectrometer ion optical system has many voltage parameters and requires high accuracy,which brings great challenges to the installation and debugging of mass spectrometer.In addition,the optimal voltage parameters are often not matched with the simulation design parameters due to assembly tolerance,variable environment,device ageing and so on.The conventional step-and-scan method not only is timeconsuming,and the voltage optimization is easy to fall into the local optimal solution.In this study,a genetic algorithm adaptive optimization method for time-of-flight mass spectrometer performance was developed.The validation experiments of mass spectrometry performance optimization were carried out on a home-built multireflection time-of-flight mass spectrometer(MR-TOFMS).The main research work of the paper is as follows:(1)Development of control system for MR-TOFMSThe control system of multiple reflection time-of-flight mass spectrometry is developed based on Lab VIEW platform,which includes the control of hardware devices and the development of state machine structure in different voltage optimization modes.The control of hardware devices includes the high-voltage power supply system and the acquisition card.It realizes the functions of setting,loading and saving of voltage parameters,and trigger of the acquisition card,real-time acquisition,display and automatic saving of spectral data.The development of automatic execution state machine in different voltage optimization modes,including the development of functional modules for single-voltage automatic scanning,multi-voltage adaptive optimization and automatic continuous monitoring.(2)Development of mass spectrum data processing algorithm and multi-voltage parameter adaptive optimization algorithm.The algorithm for spectral data includes screening,extraction,fitting and calculation of target parameters for the characteristic peaks in the full-spectrum data.The genetic algorithm-based multi-voltage parameter adaptive optimization algorithm includes initialization of voltage population,construction of evaluation function based on target parameters,and iterative optimization of voltage population.The algorithms of each part are embedded in the automatic control system designed and developed based on Lab VIEW platform through MATLAB script to realize online adaptive optimization of MR-TOFMS voltage parameters.(3)Test experimentsBased on the MR-TOFMS,and mixture of 10 ppb benzene,toluene and xylene as sample.The step-scan optimization of 2 voltage parameters and the adaptive optimization of 5 voltage parameters in 1.5 cycles were completed.Compared with the step-scan method,the adaptive optimization method has completed a wide range and high-precision global search of 5-voltage parameters in 2.25 hours.The sensitivity and resolution of the optimized mass spectrometer were improved 52.4% and 50.6%respectively.Furthermore,the adaptive optimization of 5 voltage parameters and the automatic continuous monitoring experiment after the 5-voltage adaptive optimization in 4.5 cycles were completed.Compared with the manual optimization,the adaptive optimization method has completed a wide range and high-precision global search of5-voltage parameters in 2.25 hours.The sensitivity and resolution of the optimized mass spectrometer were improved 20% and 35.3% respectively.The experimental results show that the adaptive optimization method based on genetic algorithm can quickly complete the multi-parameter global optimal tuning of the time-of-flight mass spectrometer and effectively improve the performance of the mass spectrometer.