离子阱质谱仪质量分段校正算法研究

Study on Mass Calibration Segmentation Algorithm of Ion Trap Mass Spectrometer

  • 摘要: 针对质谱仪质量校正过程中分段校正模式下手动分段效率低的问题,本研究设计了一种自动分段校正算法,以提高校正精度,方便快速操作。利用逐点拟合来判断分段区间是否符合要求并确定各分段区间,使质量范围自动分段以减小各检查点的质量偏差。实验结果表明,该算法可将质量范围合理分段,并建立新的线性关系,使各检查点偏差控制在较低的预设范围(0.1 u)内,有效地提高了仪器校正效率及测量精度。

     

    Abstract: In order to ensure the measurement accuracy of ion trap mass spectrometer, it is necessary to perform mass calibration on the instrument when there is a mass shift. Mass calibration can be achieved by improving the stability of the electrical components or upgrading the hardware with significant technical costs. Compared with hardware optimization, mass calibration based on software algorithms can better utilize the performance of existing instruments. Mass calibration can be achieved by manually inputting standard samples or calibration solution parameters. However, mass axis calibration in this way still requires setting specific segmentation points based on the actual situation and manually adjusting them to achieve the desired accuracy. Therefore, to improve the low efficiency with manual segmentation during mass calibration, an automatic segmented calibration algorithm was proposed to improve the calibration accuracy and facilitate rapid operation. The algorithm used point by point fitting to determine whether the segment interval met the requirements and also determined each segment interval. At the same time, the mass axis was automatically segmented to reduce the mass deviation of each checkpoint. This method was compared with traditional method, different deviation thresholds were explored, and multiple instruments were selected to verify this method. The results showed that the algorithm can reasonably segment the mass axis and establish a new linear relationship between electrical parameters and m/z under existing conditions, allowing the deviation of each checkpoint to be controlled within a lower preset range (±01 u), thus improving the instrument's calibration efficiency and measurement accuracy, reducing the difficulty of personnel operation. The significance of this study is that the algorithm only adjusts and optimizes the signals generated by the hardware without changing the structure of the instrument itself, which is helpful for improving the overall performance and stability of the instrument. Moreover, the principle and conclusion of the algorithm are independent of the experimental platform, so it can be applied to a variety of other types of mass spectrometers. For the insufficient points, firstly, the upper limit of accuracy provided by the algorithm itself is still determined by the hardware accuracy of the instrument, so it is only possible to calibrate and optimize the mass axis within a certain accuracy range. Secondly, because the calibration process requires a certain number of reference points, which poses certain requirements for the selection of calibration solutions.

     

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