Ion phase difference prediction and correction method

Abstract

The invention provides an ion phase difference prediction and correction method. The method comprises the following steps: (S1) collecting multiple original transient signals of a standard substance; (S2) the original transient signal is preprocessed, noise is reduced, and a time domain signal f (t) is obtained; (S3) converting the time domain signal f (t) into an amplitude spectrum M (omega) and a phase phi (omega): obtaining an angular frequency omega and the phase phi, wherein the phase phi corresponds to the initial phase phi 0 and the delay time delta t; (S4) according to the angular frequency omega and the phase phi, obtaining an initial phase phi 0 = phi-(a * omega x + b * omega y + c) * delta t, wherein a, b and c are constants; and (S5) converting the time domain signal into an absorption spectrum A (p) by adopting a Fourier algorithm of an absorption mode and combining the ion phase information phi 0. The method has the advantages of accurate peak position and the like.

Description

Technical Field

[0001] The invention relates to mass spectrometry, and in particular to a method for predicting and correcting ion phase differences. Background Art

[0002] In Fourier transform mass spectrometry, there are multiple modes: amplitude spectrum, absorption spectrum, and "enhanced spectrum" represented by thermoelectric (a comprehensive spectrum combining amplitude spectrum and absorption spectrum). Amplitude spectrum is the most commonly used Fourier transform mass spectrometry method because it does not need to consider the phase information of ions. Compared with amplitude spectrum, absorption spectrum has higher resolution, more accurate mass and abundance, but the calculation of absorption spectrum requires clear phase information of sinusoidal components.

[0003] Since there is a delay between the detection time and acceleration time of ions in FT-ICR and electrostatic ion trap mass spectrometry, it is necessary to reverse the time domain data to the initial time t0 with the minimum total phase difference. There are relevant patents and literature on phase correction technology, such as the description in the patent US8853620B2 of Thermoelectric, which uses phase correction technology to correct the initial phase and initial detection time of each ion, thereby calculating the absorption spectrum.

[0004] The existing method requires regular manual tuning, requires the injection of a standard substance mixture covering the high mass range, and the instrument uses an internal algorithm to calculate the ion phase information and calibrate the absorption spectra of ions of different m / z. This method requires high-frequency tuning, is time-consuming, and has low efficiency.

[0005] The results are accurate at the beginning of the calibration, but as time goes by, the phase information of the ions deviates further from the actual information. Until the next tuning to obtain a new phase test, there is a certain deviation between the test results and the initial calibration.

[0006] There is no information feedback during the operation of the instrument. If the parameters or conditions of the instrument change, resulting in a phase difference, the instrument cannot judge and cannot automatically adjust and correct it in real time. Summary of the invention

[0007] In order to solve the deficiencies in the above-mentioned prior art solutions, the present invention provides a method for predicting and correcting ion phase differences.

[0008] The objective of the present invention is achieved through the following technical solutions: A method for predicting and correcting ion phase difference comprises the following steps: (S1) collecting multiple original transient signals of standard substances; (S2) preprocessing the original transient signal to reduce noise and obtain a time domain signal f(t); (S3) Convert the time domain signal f(t) into the amplitude spectrum M(ω) and phase φ(ω): , ; Obtaining angular frequency ω and phase φ, the phase φ corresponds to the initial phase φ0 and the delay time Δt; (S4) According to the angular frequency ω and the phase φ, the initial phase φ0=φ-(a·ω x +b·ω y +c)·Δt, a, b and c are constants; (S5) Using the Fourier algorithm of the absorption mode and combining the ion phase information Φ0, the time domain signal is converted into the absorption spectrum A(p); A(p)= Re(p)·cosφ0+ Im(p)·sinφ0.

[0009] Compared with the prior art, the present invention has the following beneficial effects: 1. The frequency of testing standards will be significantly reduced.

[0010] 2. The data acquisition method is combined with the data preprocessing method, and the peak position accuracy is higher; 3. It has an intelligent automatic correction model that can automatically iterate the phase correction model, so that the long-term correction error of the algorithm is reduced, that is, the accurate phase can still be calculated after a long period of use.

[0011] It can monitor the electrical parameters of the instrument in real time and intelligently, and then correct the calculation model and automatically adjust the correction phase. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The disclosure of the present invention will become easier to understand with reference to the accompanying drawings. It is easy for those skilled in the art to understand that these drawings are only used to illustrate the technical solution of the present invention and are not intended to limit the scope of protection of the present invention. In the drawings: Figure 1 is a flow chart of the ion phase difference prediction and correction method according to the present invention. DETAILED DESCRIPTION

[0013] Figure 1 The following description describes optional specific embodiments of the present invention to teach those skilled in the art how to implement and reproduce the present invention. In order to teach the technical solution of the present invention, some conventional aspects have been simplified or omitted. Those skilled in the art will understand that variations or replacements derived from these specific embodiments will be within the scope of the present invention. Those skilled in the art will understand that the following features can be combined in various ways to form multiple variations of the present invention. Thus, the present invention is not limited to the following optional specific embodiments, but is only limited by the claims and their equivalents. Example

[0014] like Figure 1As shown, a method for predicting and correcting ion phase difference according to an embodiment of the present invention comprises the following steps: (S1) For the linear electrostatic trap, inject the cation calibration solution (195 (Caffeine), 524 (MRFA), 1322, 1422, 1522 (Ultramark)).

[0015] The original transient signal of the standard substance was collected 100 times, with a sampling rate of >100Msps, 16-bit sampling accuracy, and each transient time of 120ms.

[0016] (S2) Preprocessing the original transient signal, specifically: The data is averaged and extracted to 4Msps, and the least square method is used to process the data and fit to obtain a new time domain signal. Every 20 groups of transient signals are averaged to obtain the fitted time domain signal f(t).

[0017] (S3) Convert the time domain signal f(t) into the amplitude spectrum M(ω) and phase φ(ω): , ; The angular frequency ω and phase φ are obtained, and the phase φ corresponds to the initial phase φ0 and the delay time Δt; the three-point interpolation method is used to identify the peak, and the ω1…ω at the high point of the m / z of the n standard substances are calculated. n .

[0018] (S4) According to the angular frequency ω and the phase φ, the initial phase φ0=φ-(a·ω x +b·ω y +c)·Δt, a, b and c are constants, and the specific method is as follows.

[0019] An exposure correction network based on the Fourier algorithm is designed with interactive modules in the frequency domain and the spatial domain, and a mass spectrometry time domain signal dataset with phase distortion is used to train the network; the exposure correction network consists of an amplitude subnetwork and a phase subnetwork; the amplitude subnetwork is responsible for recovering the amplitude representation, while the phase subnetwork is responsible for reconstructing the phase representation to improve the structure.

[0020] Perform multiple iterations to optimize the Δt corresponding to the target m / z within the mass range, thereby forming an algorithm for phase adaptation of the FTMS mass spectrometer; Δt n+1 =Δt n +0.015·∂Ε / ∂(Δt n ),|t n+1 -t n |≤0.2μs; Δt n+1 is the time offset for the next iteration, Δt nis the time offset of the current iteration, α is the learning rate, and Ε is the error function; The corrected pure absorption spectrum is obtained by using the iterated Δt to identify the peak distribution of the corresponding ions. The difference is measured by error, such as using the cross-correlation coefficient. When the relative standard deviation RSD of the φ0 sample is less than 1.5%, the iteration of Δt is stopped; After Δt stops the iteration, the values ​​of a, b, and c in φ0=2.6·ω+0.0188 are further converged until the RSD decreases to more than 10%.

[0021] The algorithm collects spectrum information of the same usage cycle (within 8 hours) at a certain interval, such as 2 weeks, or a certain number of scans, such as 10,000 times, and fits to generate simulated transient information. At the same time, the fitted model will also be calibrated according to the monitoring indicators of the instrument, because the information of the instrument, such as the ion source, will cause phase deviation, so the normalization of data under different instrument conditions is the prerequisite for fitting. The fitted transient signal can provide valuable phase information for regular correction of the phase model and real-time iteration of the absorption spectrum model of phase correction. Therefore, the advantage of doing this is that the customer does not need to perform fixed standard sample injection to calibrate the phase model, thereby achieving more accurate phase correction, reducing human operations, and better consistency.

[0022] (S5) Using the Fourier algorithm of the absorption mode and combining the ion phase information Φ0, the time domain signal is converted into the absorption spectrum A(p); A(p)= Re(p)·cosφ0+ Im(p)·sinφ0.

Claims

1. A method for predicting and correcting ion phase difference, comprising the following steps: (S1) collecting multiple original transient signals of standard substances; (S2) preprocessing the original transient signal to reduce noise and obtain a time domain signal f(t); (S3) Convert the time domain signal f(t) into the amplitude spectrum M(ω) and phase φ(ω): ， ； Obtaining angular frequency ω and phase φ, the phase φ corresponds to the initial phase φ0 and the delay time Δt; (S4) According to the angular frequency ω and the phase φ, the initial phase φ0=φ-(a·ω x +b·ω y +c)·Δt, a, b and c are constants; (S5) Using the Fourier algorithm of the absorption mode and combining the ion phase information Φ0, the time domain signal is converted into the absorption spectrum A(p); A(p)= Re(p)·cosφ0+ Im(p)·sinφ0.

2. The ion phase difference prediction and correction method according to claim 1, characterized in that: In step (S1), the sampling rate is greater than 100Msps, each transient time is greater than 100ms, and the number of samples is greater than 50.

3. The ion phase difference prediction and correction method according to claim 1, characterized in that: In step (S2), the data is subjected to sliding averaging, and the least square method is used to process the data to obtain a new time domain signal by fitting. Each group of transient signals is averaged to obtain a fitted time domain signal f(t).

4. The ion phase difference prediction and correction method according to claim 1, characterized in that: In step (S4), an exposure correction network based on the Fourier algorithm is designed, interactive modules in the frequency domain and the spatial domain are designed, and a mass spectrometry time domain signal data set with phase distortion is used to train the network; The exposure correction network consists of an amplitude subnetwork and a phase subnetwork; Perform multiple iterations to optimize the Δt corresponding to the target m / z within the mass range, thereby forming an algorithm for phase adaptation of the FTMS mass spectrometer; Δt n+1 =Δt n +α·∂E / ∂(Δt n ),|t n+1 -t n |≤0.2μs; Δt n+1 is the time offset for the next iteration, Δt n is the time offset of the current iteration, α is the learning rate, and Ε is the error function; The corrected pure absorption spectrum is obtained by using the iterated Δt to identify the peak distribution of the corresponding ions. The difference is measured by error. When the relative standard deviation RSD of the φ0 sample is less than the first threshold, the iteration is stopped at Δt. After Δt stops the iteration, it converges to φ0=φ-(a·ω x +b·ω y +c)·Δt until the RSD decreases and reaches the second threshold.

5. The ion phase difference prediction and correction method according to claim 4, characterized in that: As described, the error metric uses the cross-correlation coefficient.

6. The ion phase difference prediction and correction method according to claim 4, characterized in that: The first threshold is 1.5% and the second threshold is 10%.

7. The ion phase difference prediction and correction method according to claim 1, characterized in that: For linear electrostatic traps, use a cation calibration solution.

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