A voltage compensation method, apparatus, device and mass spectrometer
Patent Information
- Application Number
- CN202610450193.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-04-08
- Publication Date
- 2026-07-21
Smart Images
Figure CN122433378A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of mass spectrometry technology, and in particular to a voltage compensation method, apparatus, device and mass spectrometer. Background Technology
[0002] An electrostatic field orbital trap mass spectrometer is a high-resolution mass spectrometry instrument based on the principle of electrostatic confinement of ion motion. By constructing a high-precision electrostatic field, ions are made to oscillate stably within the potential field formed by a specific electrode structure. The charge-to-mass ratio of the ions is accurately calculated by detecting the ion oscillation frequency. This type of mass spectrometer has advantages such as high resolution, high mass accuracy, and wide dynamic range, and has been widely used in fields such as biomedicine, chemical analysis, environmental monitoring, food safety, and high-end materials analysis.
[0003] Existing mass spectrometers typically employ high-precision internal and external electrode structures. By strictly controlling the electrode geometry and dimensional parameters, an approximately ideal electrostatic field distribution is formed, thereby ensuring the stability of ion movement and frequency repeatability in the radial and axial directions. Since electrode surface roughness, geometric errors, and assembly errors all significantly affect the electric field uniformity and ion oscillation frequency, electrode machining accuracy is usually required to reach sub-micron or even higher levels. This places extremely high demands on the machining accuracy and process stability of CNC machining equipment.
[0004] Currently, a segmented electrostatic track ion trap structural design scheme has been proposed. This scheme significantly increases the adjustable degrees of freedom of the system by dividing the originally continuous curved surface electrode into multiple independent electrode segments and applying different bias voltages to each segment. Based on this, it can approximate the ideal superlogarithmic potential distribution to a certain extent, while reducing the mechanical difficulty of precision machining of individual electrode surfaces and improving the feasibility of engineering implementation.
[0005] However, the aforementioned multi-electrode structure introduces a large number of bias voltage adjustment parameters, causing the voltage combinations to grow exponentially. Each voltage combination needs to be verified one by one to determine the optimal voltage combination, which makes the process of determining the optimal voltage combination extremely complex and time-consuming. Summary of the Invention
[0006] This application provides a voltage compensation method, apparatus, device, and mass spectrometer, aiming to solve the technical problem that in the process of voltage compensation of a multi-electrode mass spectrometer, it is necessary to determine the compensation voltage through a large number of complex and time-consuming steps.
[0007] In a first aspect, embodiments of this application provide a voltage compensation method, including: Multiple sets of first voltage combinations are applied to multiple adjustable electrodes on the mass spectrometer track trap structure; Based on the electrostatic field distribution corresponding to the multiple sets of first voltage combinations on the multiple adjustable electrodes, a first frequency variance is determined, which is based on the oscillation frequency corresponding to each radial position on the orbital trap structure. The training dataset is input into a preset prediction model for the first iteration optimization to obtain the second voltage combination. The training dataset includes the multiple sets of first voltage combinations and the first frequency variance. The second voltage combination and the second frequency variance corresponding to the second voltage combination are input into the prediction model for a second iteration optimization to obtain the third voltage combination. Based on the third voltage combination, voltage compensation is performed on each adjustable electrode on the orbital trap structure.
[0008] Optionally, the provision of multiple sets of first voltage combinations on the multiple adjustable electrodes of the mass spectrometer orbital trap structure includes: Measure the machining error parameters of the track trap structure; Based on the aforementioned processing error parameters, an electric field model is performed on the orbital trap structure to determine multiple adjustable electrodes on the mass spectrometer orbital trap structure. Multiple sets of first voltage combinations are applied to the plurality of adjustable electrodes.
[0009] Optionally, determining the first frequency variance based on the electrostatic field distribution corresponding to the multiple sets of first voltage combinations on the multiple adjustable electrodes includes: The optimization range is determined based on the range of ion movement within the orbital trap structure; Based on the electrostatic field distribution of the multiple sets of first voltage combinations on the track trap structure, the potential distribution is fitted within the optimization interval to obtain the potential fitting expression. Based on the potential fitting expression, the oscillation frequency corresponding to each radial position discretely set at a preset distance on the track trap structure is determined; Based on the oscillation frequency corresponding to each radial position, a first frequency variance is determined, which is used to characterize the electric field distribution state.
[0010] Optionally, the step of inputting the training dataset into a preset prediction model for the first iteration of optimization to obtain the second voltage combination includes: A training dataset is constructed using the multiple sets of first voltage combinations as input data and the first frequency variance as output data. The training dataset is input into a preset prediction model for the first iteration optimization to obtain a second voltage combination, which is the voltage combination with the smallest frequency variance predicted by the prediction model.
[0011] Optionally, before inputting the second voltage combination and the second frequency variance corresponding to the second voltage combination into the prediction model for a second iterative optimization to obtain the third voltage combination, the method further includes: The optimization range is determined based on the range of ion movement within the orbital trap structure; Based on the electrostatic field distribution of the multiple sets of second voltage combinations on the track trap structure, the potential distribution is fitted within the optimization interval to obtain the potential fitting expression. Based on the potential fitting expression, the oscillation frequency corresponding to each radial position on the orbital trap structure is determined; The second frequency variance is determined based on the oscillation frequency corresponding to each radial position.
[0012] Optionally, the step of inputting the second voltage combination and the second frequency variance corresponding to the second voltage combination into the prediction model for a second iterative optimization to obtain the third voltage combination includes: The second voltage combination and the second frequency variance corresponding to the second voltage combination are input into the prediction model for a second iterative optimization. The prediction model is iteratively optimized based on the acquisition function. When the number of iterations reaches a preset number, the prediction model is determined to be fully optimized, and a third voltage combination is obtained.
[0013] Optionally, the acquisition function is: Where EI(x) represents the acquisition function, best represents the voltage combination observed by the prediction model in the current iteration round, μ(x) represents the prediction mean of the prediction model in the current iteration round, ξ represents the exploration parameter, Φ(Z) represents the cumulative distribution function, σ(x) represents the prediction standard deviation of the prediction model in the current iteration round, and ϕ(Z) represents the standard probability density function.
[0014] Secondly, embodiments of this application provide a voltage compensation device, comprising: The setting module is used to set multiple sets of first voltage combinations to multiple adjustable electrodes on the mass spectrometer track trap structure; The first determining module is used to determine a first frequency variance based on the electrostatic field distribution corresponding to the multiple sets of first voltage combinations on the multiple adjustable electrodes. The first frequency variance is determined based on the oscillation frequency corresponding to each radial position on the orbital trap structure. The first optimization module is used to input the training dataset into a preset prediction model for the first iteration optimization to obtain the second voltage combination. The training dataset includes the multiple sets of first voltage combinations and the first frequency variance. The second optimization module is used to input the second voltage combination and the second frequency variance corresponding to the second voltage combination into the prediction model for a second iteration optimization to obtain the third voltage combination; A compensation module is used to perform voltage compensation on each adjustable electrode on the orbital trap structure based on the third voltage combination.
[0015] Thirdly, embodiments of this application provide an electronic device, including: a processor, a memory, and a program stored in the memory and executable on the processor, wherein when the program is executed by the processor, it implements the steps of the voltage compensation method as described in the first aspect.
[0016] Fourthly, embodiments of this application provide a mass spectrometer, which is prepared by the voltage compensation method described above.
[0017] This application provides a voltage compensation method, apparatus, device, and mass spectrometer. The method includes: setting multiple sets of first voltage combinations on multiple adjustable electrodes on a mass spectrometer track trap structure; determining a first frequency variance based on the electrostatic field distribution corresponding to the multiple sets of first voltage combinations on the multiple adjustable electrodes, the first frequency variance being determined based on the oscillation frequency corresponding to each radial position on the track trap structure; inputting a training dataset into a preset prediction model for a first iterative optimization to obtain a second voltage combination, the training dataset including multiple sets of first voltage combinations and the first frequency variance; inputting the second voltage combination and the second frequency variance corresponding to the second voltage combination into the prediction model for a second iterative optimization to obtain a third voltage combination; and performing voltage compensation on each adjustable electrode on the track trap structure based on the third voltage combination. In this application, multiple sets of first voltage combinations are set for multiple adjustable electrodes, and a first frequency variance is determined. These multiple sets of first voltage combinations and the first frequency variance are input into a prediction model for a first iteration optimization to obtain a second voltage combination. The second voltage combination and the second frequency variance are then input into the prediction model for a second iteration optimization to obtain the optimal third voltage combination. This greatly simplifies the steps of determining the optimal voltage combination and reduces the calculation time for determining the compensation voltage. Furthermore, voltage compensation for each adjustable electrode based on the third voltage combination makes the electric field distribution closer to the ideal state, thereby improving the frequency consistency and mass resolution of the mass spectrometer. Attached Figure Description
[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1 This is a schematic flowchart of a voltage compensation method provided in an embodiment of this application; Figure 2 This is a schematic diagram of the orbital trap structure provided in the embodiments of this application; Figure 3 This is one of the schematic diagrams illustrating the types of machining errors in the track trap structure provided in this application embodiment; Figure 4 This is a second schematic diagram illustrating the types of machining errors in the track trap structure provided in this application embodiment; Figure 5 This is a schematic diagram of the frequency variance curve provided in the embodiments of this application; Figure 6 This is a schematic diagram of the radial position distribution provided in the embodiments of this application; Figure 7 This is a schematic diagram of the structure of a voltage compensation device provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation
[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0021] See Figure 1 , Figure 1 This is a schematic flowchart of a voltage compensation method provided in an embodiment of this application, as shown below. Figure 1 As shown in the embodiment of this application, a voltage compensation method includes: S101, set multiple sets of first voltage combinations to multiple adjustable electrodes on the mass spectrometer track trap structure.
[0022] Please see Figure 2 In one optional implementation, the mass spectrometer orbital trap structure can be as follows: Figure 2 As shown, the system includes 10 electrode segments, each of which can be individually biased with a bias voltage. When geometric defects or morphological deviations occur in the electrodes during processing, the actual electrostatic field distribution can be compensated and corrected by adjusting the bias voltage on each segment of the electrode.
[0023] In this step, multiple sets of first voltage combinations are set for multiple adjustable electrodes. The first voltage combinations are randomly generated within a preset voltage range. Voltages within the preset voltage range can ensure the stability of ion movement and also include most of the potential optimized voltages.
[0024] In one alternative embodiment, the first voltage combination comprises 40 groups.
[0025] S102, based on the electrostatic field distribution corresponding to the multiple sets of first voltage combinations on the multiple adjustable electrodes, a first frequency variance is determined, the first frequency variance being determined based on the oscillation frequency corresponding to each radial position on the orbital trap structure.
[0026] In this step, after setting multiple sets of first voltage combinations on multiple adjustable electrodes, the electrostatic field distribution corresponding to the multiple sets of first voltage combinations on the multiple adjustable electrodes is obtained. Based on the electrostatic field distribution, a first frequency variance is determined, wherein the first frequency variance is determined based on the oscillation frequency corresponding to each radial position on the orbital trap structure. For specific implementation details, please refer to subsequent embodiments.
[0027] S103, the training dataset is input into the preset prediction model for the first iteration optimization to obtain the second voltage combination. The training dataset includes the multiple sets of first voltage combinations and the first frequency variance.
[0028] It should be understood that the above prediction model can be a Gaussian Process (GP) regression model.
[0029] In this step, after obtaining multiple sets of first voltage combinations and first frequency variances, the multiple sets of first voltage combinations are used as observation samples, and the first frequency variances are used as observation values to construct a training dataset.
[0030] The training dataset is then input into a pre-defined prediction model for the first iteration of optimization to obtain the second voltage combination.
[0031] S104, the second voltage combination and the second frequency variance corresponding to the second voltage combination are input into the prediction model for a second iteration optimization to obtain the third voltage combination.
[0032] In this step, after obtaining the second voltage combination, the second frequency variance corresponding to the second voltage combination is calculated, and the second voltage combination and the second frequency variance are input into the prediction model for a second iteration optimization to obtain the optimal third voltage combination.
[0033] S105, based on the third voltage combination, voltage compensation is performed on each adjustable electrode on the orbital trap structure.
[0034] In this step, voltage compensation can be performed on each adjustable electrode on the orbital trap structure based on the third voltage combination. Specifically, voltage compensation is performed on each adjustable electrode so that the voltage received by each adjustable electrode is the voltage corresponding to that electrode in the third voltage combination.
[0035] In this embodiment, multiple sets of first voltage combinations are set for multiple adjustable electrodes, and a first frequency variance is determined. These multiple sets of first voltage combinations and the first frequency variance are input into a prediction model for a first iterative optimization to obtain a second voltage combination. The second voltage combination and the second frequency variance are then input into the prediction model for a second iterative optimization to obtain the optimal third voltage combination. This greatly simplifies the steps of determining the optimal voltage combination and reduces the calculation time for determining the compensation voltage. Furthermore, applying voltage compensation to each adjustable electrode based on the third voltage combination makes the electric field distribution closer to the ideal state, thereby improving the frequency consistency and mass resolution of the mass spectrometer.
[0036] Optionally, the provision of multiple sets of first voltage combinations on the multiple adjustable electrodes of the mass spectrometer orbital trap structure includes: Measure the machining error parameters of the track trap structure; Based on the aforementioned processing error parameters, an electric field model is performed on the orbital trap structure to determine multiple adjustable electrodes on the mass spectrometer orbital trap structure. Multiple sets of first voltage combinations are applied to the plurality of adjustable electrodes.
[0037] It should be noted that the types of manufacturing errors in the mass spectrometer orbital trap structure include structural symmetry deviations and geometric dimensional deviations. Please refer to [link / reference]. Figure 3 , Figure 3 The black lines represent the ideal orbital trap structure, while the orange lines represent the orbital trap structure with structural symmetry deviations. Please refer to [link / reference]. Figure 4 , Figure 4 The black lines in the middle represent the geometric dimensions of each electrode in an ideal orbital trap structure. Figure 4 The red portion indicates electrode structures with geometric dimensional deviations.
[0038] In this embodiment, the processing error parameters of the track trap structure are measured, and the electric field of the track trap structure containing the processing error is modeled using the finite element method. Based on the modeling results, multiple adjustable electrodes on the track trap structure are determined.
[0039] For example, in Figure 2 In the track trap structure shown, electrodes 3 to 8 are all adjustable electrodes.
[0040] Furthermore, multiple sets of first voltage combinations are set for multiple adjustable electrodes.
[0041] exist Figure 2 In the track trap structure shown, an optional implementation involves setting 40 sets of random voltage combinations on adjustable electrodes 3 to 8. The voltage values of electrodes 4 to 7 randomly range from 0.999 V to 1.001 V, while the voltage values of electrodes 3 and 8 randomly range from 0.95 V to 1.05 V.
[0042] In this embodiment, based on the measured machining error parameters of the orbital trap structure, multiple sets of first voltage combinations are set on multiple adjustable electrodes on the orbital trap structure.
[0043] Optionally, determining the first frequency variance based on the electrostatic field distribution corresponding to the multiple sets of first voltage combinations on the multiple adjustable electrodes includes: The optimization range is determined based on the range of ion movement within the orbital trap structure; Based on the electrostatic field distribution of the multiple sets of first voltage combinations on the track trap structure, the potential distribution is fitted within the optimization interval to obtain the potential fitting expression. Based on the potential fitting expression, the oscillation frequency corresponding to each radial position discretely set at a preset distance on the track trap structure is determined; Based on the oscillation frequency corresponding to each radial position, a first frequency variance is determined, which is used to characterize the electric field distribution state.
[0044] In this embodiment, the optimization range of the orbital trap structure is determined based on the movement range of ions within the orbital trap structure. The electrostatic field distribution corresponding to multiple sets of first voltage combinations is solved using the finite element method. After obtaining the electrostatic field distribution of multiple sets of first voltage combinations on the orbital trap structure, the potential distribution is fitted within the optimization range to obtain the potential fitting expression. Optionally, the potential fitting expression can be expressed as the following formula:
[0045] Where r and z are both cylindrical coordinates, r represents the radius coordinate and z represents the coordinate along the z-axis. All of these represent the potential distribution along the z-axis at different radial positions r, which needs to be obtained through potential fitting. L represents the characteristic dimension of the orbital trap structure.
[0046] Based on the potential fitting expression, the oscillation frequency corresponding to each radial position on the orbital trap structure is determined. Optionally, it can be obtained using the following formula: Where w represents the oscillation frequency. Both represent the potential distribution along the z-axis at a given radial position r, which needs to be obtained through potential fitting. L represents the characteristic dimension of the surface trap structure, and A represents the amplitude of ion vibration in the z-direction. w0 is expressed by the following formula: Where q is the ion charge and m is the ion mass. Further calculation of the statistical variance of the oscillation frequency corresponding to each radial position yields the first frequency variance. This first frequency variance is used to characterize the frequency consistency between different radial orbits.
[0047] Optionally, the step of inputting the training dataset into a preset prediction model for the first iteration of optimization to obtain the second voltage combination includes: A training dataset is constructed using the multiple sets of first voltage combinations as input data and the first frequency variance as output data. The training dataset is input into a preset prediction model for the first iteration optimization to obtain a second voltage combination, which is the voltage combination with the smallest frequency variance predicted by the prediction model.
[0048] As mentioned above, optionally, the prediction model is a Gaussian process regression model.
[0049] In this embodiment, a training dataset is constructed using multiple sets of first voltage combinations as input data and the first frequency variance as output data. The training dataset is then input into a preset prediction model for the first iteration optimization. A Gaussian process regression model is used to globally model the objective function and predict the voltage combination that minimizes the expected value of the frequency variance, thus obtaining the second voltage combination.
[0050] It should be noted that in an ideal electrostatic orbital trap, the axial oscillation frequency of ions should be independent of the radial position *r*, meaning the oscillation frequency distribution with respect to *r* is constant. When the actual electric field is distorted, the oscillation frequency will change with *r*, causing frequency dispersion of ions on different radial orbits, resulting in spectral peak broadening and reduced mass resolution. Therefore, frequency consistency can be characterized by calculating the variance of the oscillation frequency at different radial positions. The smaller the frequency variance, the weaker the dependence of the frequency on the radial position, the closer the electric field distribution is to the ideal state, and the higher the mass resolution. Therefore, minimizing the frequency variance can be used as the objective function.
[0051] Optionally, before inputting the second voltage combination and the second frequency variance corresponding to the second voltage combination into the prediction model for a second iterative optimization to obtain the third voltage combination, the method further includes: The optimization range is determined based on the range of ion movement within the orbital trap structure; Based on the electrostatic field distribution of the multiple sets of second voltage combinations on the track trap structure, the potential distribution is fitted within the optimization interval to obtain the potential fitting expression. Based on the potential fitting expression, the oscillation frequency corresponding to each radial position on the orbital trap structure is determined; The second frequency variance is determined based on the oscillation frequency corresponding to each radial position.
[0052] In this embodiment, after obtaining the second voltage combination, the second voltage combination is input into the finite element simulation software to re-solve the electric field, and the second rate variance corresponding to the second voltage combination is determined again. The acquisition function in the prediction model is updated based on the second rate variance.
[0053] Specifically, an optimization interval is determined based on the range of ion movement within the orbital trap structure. Based on the electrostatic field distribution of multiple sets of second voltage combinations on the orbital trap structure, a potential distribution is fitted within the optimization interval to obtain a potential fitting expression. The specific implementation method for fitting the potential distribution to obtain the potential fitting expression is the same as in the aforementioned embodiments and will not be repeated here.
[0054] Furthermore, based on the potential fitting expression, the oscillation frequency corresponding to each radial position on the track trap structure is determined, and the second frequency variance is determined according to the oscillation frequency corresponding to each radial position. The specific implementation method for determining the second frequency variance is the same as the aforementioned embodiment, and will not be repeated here.
[0055] Optionally, the step of inputting the second voltage combination and the second frequency variance corresponding to the second voltage combination into the prediction model for a second iterative optimization to obtain the third voltage combination includes: The second voltage combination and the second frequency variance corresponding to the second voltage combination are input into the prediction model for a second iterative optimization. The prediction model is iteratively optimized based on the acquisition function. When the number of iterations reaches a preset number, the prediction model is determined to be fully optimized, and a third voltage combination is obtained.
[0056] In this embodiment, the second voltage combination and the second frequency variance corresponding to the second voltage combination are input into the prediction model for a second iterative optimization. During the second iterative optimization process using the prediction model, a data acquisition function is introduced, and the prediction model is iteratively optimized based on this function. Optionally, the data acquisition function is: Where EI(x) represents the acquisition function, best represents the voltage combination observed by the prediction model in the current iteration round, μ(x) represents the prediction mean of the prediction model in the current iteration round, ξ represents the exploration parameter, Φ(Z) represents the cumulative distribution function, σ(x) represents the prediction standard deviation of the prediction model in the current iteration round, and ϕ(Z) represents the standard probability density function.
[0057] To enhance the convergence stability of the algorithm in the later stages, an exploration parameter that gradually decays with the number of iterations is introduced in the second iteration. This allows the acquisition function to gradually transition from global exploration to a local fine search focused on minimizing the predicted mean, thereby improving optimization efficiency and ensuring that the algorithm eventually converges to a stable and optimal voltage combination.
[0058] In this embodiment, when the number of iterations reaches a preset number, the prediction model is determined to be fully optimized, and a third voltage combination is obtained. Optionally, the number of iterations is 30.
[0059] To understand the technical effects of the voltage compensation method provided in this application, please refer to [link / reference needed]. Figure 5 and Figure 6 .
[0060] Please see Figure 5 , Figure 5 The blue curve represents the variance of the frequency corresponding to each radial position before optimization, and the orange curve represents the frequency variance after optimization using the voltage compensation method provided in this application. Figure 5 It can be seen that after voltage compensation of the adjustable electrode, the frequency variance is significantly reduced, which indicates that the frequency dependence on radial position is significantly weakened and the electric field distribution is closer to the ideal state, thus which is beneficial to improving the quality resolution.
[0061] Please see Figure 6 , Figure 6 The orange curve in the figure represents the distribution of the ion oscillation frequency with respect to the radial position r before optimization under the condition of geometric processing error; the blue curve represents the distribution of the ion oscillation frequency with respect to the radial position r after optimization using the voltage compensation method provided in this application under the condition of geometric processing error.
[0062] pass Figure 6 It can be seen that before optimization, the frequency exhibits a significant shift with radial position. However, after voltage compensation and optimization, the frequency distribution with respect to r becomes relatively consistent, approaching a constant distribution. This indicates that the voltage compensation method provided in this application can effectively reduce the frequency's dependence on radial position, thereby suppressing frequency dispersion between different radial orbits and improving frequency consistency and quality resolution.
[0063] Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of a voltage compensation device provided in an embodiment of this application, as shown below. Figure 7 As shown, the voltage compensation device 700 includes: Setting module 701 is used to set multiple sets of first voltage combinations to multiple adjustable electrodes on the mass spectrometer track trap structure. The first determining module 702 is used to determine a first frequency variance based on the electrostatic field distribution corresponding to the multiple sets of first voltage combinations on the multiple adjustable electrodes. The first frequency variance is determined based on the oscillation frequency corresponding to each radial position on the orbital trap structure. The first optimization module 703 is used to input the training dataset into a preset prediction model for the first iteration optimization to obtain the second voltage combination. The training dataset includes the multiple sets of first voltage combinations and the first frequency variance. The second optimization module 704 is used to input the second voltage combination and the second frequency variance corresponding to the second voltage combination into the prediction model for a second iterative optimization to obtain a third voltage combination; The compensation module 705 is used to perform voltage compensation on each adjustable electrode on the orbital trap structure based on the third voltage combination.
[0064] Optionally, the setting module 701 is specifically used for: Measure the machining error parameters of the track trap structure; Based on the aforementioned processing error parameters, an electric field model is performed on the orbital trap structure to determine multiple adjustable electrodes on the mass spectrometer orbital trap structure. Multiple sets of first voltage combinations are applied to the plurality of adjustable electrodes.
[0065] Optionally, the first determining module 702 is specifically used for: The optimization range is determined based on the range of ion movement within the orbital trap structure; Based on the electrostatic field distribution of the multiple sets of first voltage combinations on the track trap structure, the potential distribution is fitted within the optimization interval to obtain the potential fitting expression. Based on the potential fitting expression, the oscillation frequency corresponding to each radial position discretely set at a preset distance on the track trap structure is determined; Based on the oscillation frequency corresponding to each radial position, a first frequency variance is determined, which is used to characterize the electric field distribution state.
[0066] Optionally, the first optimization module 703 is specifically used for: A training dataset is constructed using the multiple sets of first voltage combinations as input data and the first frequency variance as output data. The training dataset is input into a preset prediction model for the first iteration optimization to obtain a second voltage combination, which is the voltage combination with the smallest frequency variance predicted by the prediction model.
[0067] Optionally, the voltage compensation device 700 further includes: The second determining module is used to determine the optimization range based on the range of ion movement within the orbital trap structure; The fitting module is used to fit the potential distribution within the optimization interval based on the electrostatic field distribution of the multiple sets of second voltage combinations on the track trap structure, and obtain the potential fitting expression. The third determining module is used to determine the oscillation frequency corresponding to each radial position on the orbital trap structure based on the potential fitting expression; The fourth determining module is used to determine the second frequency variance based on the oscillation frequency corresponding to each radial position.
[0068] Optionally, the second optimization module 704 is specifically used for: The second voltage combination and the second frequency variance corresponding to the second voltage combination are input into the prediction model for a second iterative optimization. The prediction model is iteratively optimized based on the acquisition function. When the number of iterations reaches a preset number, the prediction model is determined to be fully optimized, and a third voltage combination is obtained.
[0069] Optionally, the acquisition function is:
[0070] Where EI(x) represents the acquisition function, best represents the voltage combination observed by the prediction model in the current iteration round, μ(x) represents the prediction mean of the prediction model in the current iteration round, ξ represents the exploration parameter, Φ(Z) represents the cumulative distribution function, σ(x) represents the prediction standard deviation of the prediction model in the current iteration round, and ϕ(Z) represents the standard probability density function.
[0071] The voltage compensation device is capable of implementing each process of the above-described voltage compensation method, with each technical feature corresponding to the other, and achieving the same technical effect. To avoid repetition, it will not be described again here.
[0072] For details, see Figure 8 This application also provides an electronic device, including a bus 801, a transceiver 802, an antenna 803, a bus interface 804, a processor 805, and a memory 806.
[0073] The processor 805 is used to set multiple sets of first voltage combinations to multiple adjustable electrodes on the mass spectrometer track trap structure. Based on the electrostatic field distribution corresponding to the multiple sets of first voltage combinations on the multiple adjustable electrodes, a first frequency variance is determined, which is based on the oscillation frequency corresponding to each radial position on the orbital trap structure. The training dataset is input into a preset prediction model for the first iteration optimization to obtain the second voltage combination. The training dataset includes the multiple sets of first voltage combinations and the first frequency variance. The second voltage combination and the second frequency variance corresponding to the second voltage combination are input into the prediction model for a second iteration optimization to obtain the third voltage combination. Based on the third voltage combination, voltage compensation is performed on each adjustable electrode on the orbital trap structure.
[0074] exist Figure 8 In this document, a bus architecture (represented by bus 801) is used. Bus 801 can include any number of interconnected buses and bridges, linking various circuits including one or more processors represented by processor 805 and memory represented by memory 806. Bus 801 can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. Bus interface 804 provides an interface between bus 801 and transceiver 802. Transceiver 802 can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by processor 805 is transmitted over a wireless medium via antenna 803, which further receives data and transmits data to processor 805.
[0075] The processor 805 manages the bus 801 and handles general processing, and also provides various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. The memory 806 can be used to store data used by the processor 805 during operation.
[0076] Optionally, the processor 805 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD).
[0077] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
[0078] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.
[0079] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.
Claims
1. A voltage compensation method, characterized in that, include: Multiple sets of first voltage combinations are applied to multiple adjustable electrodes on the mass spectrometer track trap structure; Based on the electrostatic field distribution corresponding to the multiple sets of first voltage combinations on the multiple adjustable electrodes, a first frequency variance is determined, which is based on the oscillation frequency corresponding to each radial position on the orbital trap structure. The training dataset is input into a preset prediction model for the first iteration optimization to obtain the second voltage combination. The training dataset includes the multiple sets of first voltage combinations and the first frequency variance. The second voltage combination and the second frequency variance corresponding to the second voltage combination are input into the prediction model for a second iteration optimization to obtain the third voltage combination. Based on the third voltage combination, voltage compensation is performed on each adjustable electrode on the orbital trap structure.
2. The method according to claim 1, characterized in that, The provision of multiple sets of first voltage combinations on the multiple adjustable electrodes of the mass spectrometer orbital trap structure includes: Measure the machining error parameters of the track trap structure; Based on the aforementioned processing error parameters, an electric field model is performed on the orbital trap structure to determine multiple adjustable electrodes on the mass spectrometer orbital trap structure. Multiple sets of first voltage combinations are applied to the plurality of adjustable electrodes.
3. The method according to claim 1, characterized in that, The determination of the first frequency variance based on the electrostatic field distribution corresponding to the multiple sets of first voltage combinations on the multiple adjustable electrodes includes: The optimization range is determined based on the range of ion movement within the orbital trap structure; Based on the electrostatic field distribution of the multiple sets of first voltage combinations on the track trap structure, the potential distribution is fitted within the optimization interval to obtain the potential fitting expression. Based on the potential fitting expression, the oscillation frequency corresponding to each radial position discretely set at a preset distance on the track trap structure is determined; Based on the oscillation frequency corresponding to each radial position, a first frequency variance is determined, which is used to characterize the electric field distribution state.
4. The method according to claim 1, characterized in that, The step of inputting the training dataset into a preset prediction model for the first iteration of optimization to obtain the second voltage combination includes: A training dataset is constructed using the multiple sets of first voltage combinations as input data and the first frequency variance as output data. The training dataset is input into a preset prediction model for the first iteration optimization to obtain a second voltage combination, which is the voltage combination with the smallest frequency variance predicted by the prediction model.
5. The method according to claim 1, characterized in that, Before inputting the second voltage combination and the second frequency variance corresponding to the second voltage combination into the prediction model for a second iteration optimization to obtain the third voltage combination, the method further includes: The optimization range is determined based on the range of ion movement within the orbital trap structure; Based on the electrostatic field distribution of the multiple sets of second voltage combinations on the track trap structure, the potential distribution is fitted within the optimization interval to obtain the potential fitting expression. Based on the potential fitting expression, the oscillation frequency corresponding to each radial position on the orbital trap structure is determined; The second frequency variance is determined based on the oscillation frequency corresponding to each radial position.
6. The method according to claim 1, characterized in that, The step of inputting the second voltage combination and the second frequency variance corresponding to the second voltage combination into the prediction model for a second iteration optimization to obtain the third voltage combination includes: The second voltage combination and the second frequency variance corresponding to the second voltage combination are input into the prediction model for a second iterative optimization. The prediction model is iteratively optimized based on the acquisition function. When the number of iterations reaches a preset number, the prediction model is determined to be fully optimized, and a third voltage combination is obtained.
7. The method according to claim 6, characterized in that, The acquisition function is: Where EI(x) represents the acquisition function, best represents the voltage combination observed by the prediction model in the current iteration round, μ(x) represents the prediction mean of the prediction model in the current iteration round, ξ represents the exploration parameter, Φ(Z) represents the cumulative distribution function, σ(x) represents the prediction standard deviation of the prediction model in the current iteration round, and ϕ(Z) represents the standard probability density function.
8. A voltage compensation device, characterized in that, include: The setting module is used to set multiple sets of first voltage combinations to multiple adjustable electrodes on the mass spectrometer track trap structure; The first determining module is used to determine a first frequency variance based on the electrostatic field distribution corresponding to the multiple sets of first voltage combinations on the multiple adjustable electrodes. The first frequency variance is determined based on the oscillation frequency corresponding to each radial position on the orbital trap structure. The first optimization module is used to input the training dataset into a preset prediction model for the first iteration optimization to obtain the second voltage combination. The training dataset includes the multiple sets of first voltage combinations and the first frequency variance. The second optimization module is used to input the second voltage combination and the second frequency variance corresponding to the second voltage combination into the prediction model for a second iteration optimization to obtain the third voltage combination; A compensation module is used to perform voltage compensation on each adjustable electrode on the orbital trap structure based on the third voltage combination.
9. An electronic device, characterized in that, include: A processor, a memory, and a program stored in the memory and executable on the processor, wherein the program, when executed by the processor, implements the steps of the voltage compensation method as described in any one of claims 1 to 7.
10. A mass spectrometer, characterized in that, The mass spectrometer is prepared by the voltage compensation method as described in any one of claims 1 to 7.