Data calibration method and system of spectrograph and storage medium
By building a deep learning model in the spectrometer and using spectral compensation values for calibration, the problem of wavelength deflection error in the spectrometer was solved, and accurate detection under different environmental conditions was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-03-06
- Publication Date
- 2026-04-03
AI Technical Summary
During use, factors such as mechanical stress, thermal stress, and aging can cause wavelength deflection errors in spectrometers, affecting the accuracy of detection results.
By acquiring standard light sources in a laboratory environment to conduct spectral tests, a deep learning model is constructed, and the spectrometer to be calibrated is calibrated using spectral compensation values, including the correction and normalization of temperature, humidity, and carrier gas concentration variables.
This improves the accuracy and reliability of spectrometer test results, ensuring calibration effectiveness under different environmental conditions.
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Figure CN121786470A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of data processing technology, specifically a data calibration method, system, and storage medium for a spectrometer. Background Technology
[0002] During the lifespan of a spectrometer, mechanical stress, thermal stress, aging-related stress, or other stresses can cause changes in the spectrometer. Consequently, the wavelength may no longer deflect to the detector's initial wavelength calibration pixel, but rather to an adjacent pixel. Depending on variations in temperature, humidity, or carrier gas concentration, this effect may also affect several pixels, potentially leading to misinterpretations of wavelengths.
[0003] Therefore, data calibration of the spectrometer is necessary to ensure the accuracy of the detection results. Summary of the Invention
[0004] The purpose of this application is to provide a data calibration method, system, and storage medium for a spectrometer to ensure the accuracy of the detection results.
[0005] To achieve the above objectives, this application discloses the following technical solutions:
[0006] In a first aspect, this application discloses a data calibration method for a spectrometer, the method comprising the following steps:
[0007] A standard light source is obtained in a laboratory environment, and the standard light source is subjected to spectral testing under preset test conditions using laboratory equipment to obtain multiple sets of standard emission spectra and standard reception spectra, and the standard emission spectra and the standard reception spectra are stable.
[0008] The standard light source is subjected to spectral testing using a difference spectrometer under the preset test conditions to obtain multiple sets of test emission spectra and test reception spectra. The difference spectrometer is a known spectrometer that has output data that needs to be calibrated.
[0009] Define the standard emission spectrum and the standard reception spectrum to form a standard training set, and define the test emission spectrum and the test reception spectrum to form a test training set;
[0010] The standard training set, the test training set, and the corresponding test conditions are subjected to deep learning to obtain a spectral calibration model.
[0011] Obtain the spectral compensation value corresponding to each test condition. The spectral compensation value is the difference between the standard received spectrum and the test received spectrum under the same test conditions.
[0012] The spectral compensation value is used to perform spectral calibration on the spectrum to be calibrated corresponding to the spectrometer to be calibrated.
[0013] Preferably, the test conditions include any one of temperature variable, humidity variable, or carrier gas concentration variable.
[0014] Preferably, when the test condition is a carrier gas concentration variable, after obtaining multiple sets of test emission spectra and test reception spectra, data drift calibration is performed on each set of test reception spectra, and the data drift calibrated spectrum is used as the updated test reception spectrum. The test reception spectra in the test training set include the data drift calibrated spectrum.
[0015] Preferably, the data drift calibration specifically includes longitudinal correction and lateral correction.
[0016] Preferably, when the test conditions are temperature or humidity variables, after obtaining multiple sets of test emission spectra and test reception spectra, each set of test reception spectra is normalized, and the normalized spectrum is used as the updated test reception spectrum. The test reception spectra in the test training set include the normalized spectrum.
[0017] Preferably, the spectral calibration using the spectral compensation value for the spectrum to be calibrated of the spectrometer to be calibrated specifically includes:
[0018] The intensity value of each point in the spectrally calibrated spectrum is defined as SI, and the intensity value is calculated using the following formula:
[0019]
[0020] Among them, SI N To determine the spectral value corresponding to the midpoint N of the spectrum to be calibrated after spectral calibration, si N Before spectral calibration, the value of the spectral midpoint N of the spectrum to be calibrated is given. T is the temperature compensation value of the spectrometer to be calibrated in the detection environment. k1 is the weight value corresponding to the temperature condition. W is the humidity compensation value of the spectrometer to be calibrated in the detection environment. k2 is the weight value corresponding to the humidity condition. C is the carrier gas concentration compensation value of the spectrometer to be calibrated in the detection environment. k3 is the weight value corresponding to the carrier gas concentration condition. k1+k2+k3=1.
[0021] Secondly, this application discloses a data calibration system for a spectrometer, including a standard dataset acquisition module, a test dataset acquisition module, a model acquisition module, and a calibration module;
[0022] The standard dataset acquisition module is configured to: acquire a standard light source in a laboratory environment, perform spectral testing on the standard light source using laboratory equipment according to preset test conditions, and acquire multiple sets of standard emission spectra and standard reception spectra, wherein the standard emission spectra and the standard reception spectra are stable;
[0023] The test dataset acquisition module is configured to: use a difference spectrometer to perform spectral testing on the standard light source according to the preset test conditions, and obtain multiple sets of test emission spectra and test reception spectra, wherein the difference spectrometer is a known spectrometer that has output data that needs to be calibrated;
[0024] The model acquisition module is configured to perform deep learning on the standard training set, the test training set, and the corresponding test conditions to obtain a spectral calibration model, wherein the standard training set consists of the standard emission spectrum and the standard reception spectrum, and the test training set consists of the test emission spectrum and the test reception spectrum;
[0025] The calibration module is configured to: acquire the spectral compensation value corresponding to each test condition, wherein the spectral compensation value is the difference between the standard received spectrum and the test received spectrum under the same test conditions, and use the spectral compensation value to perform spectral calibration on the spectrum to be calibrated corresponding to the spectrometer to be calibrated.
[0026] Preferably, the test conditions include any one of temperature variable, humidity variable, or carrier gas concentration variable.
[0027] Preferably, the spectral calibration using the spectral compensation value for the spectrum to be calibrated of the spectrometer to be calibrated specifically includes:
[0028] The intensity value of each point in the spectrally calibrated spectrum is defined as SI, and the intensity value is calculated using the following formula:
[0029]
[0030] Among them, SI N To determine the spectral value corresponding to the midpoint N of the spectrum to be calibrated after spectral calibration, si N Before spectral calibration, the value of the spectral midpoint N of the spectrum to be calibrated is given. T is the temperature compensation value of the spectrometer to be calibrated in the detection environment. k1 is the weight value corresponding to the temperature condition. W is the humidity compensation value of the spectrometer to be calibrated in the detection environment. k2 is the weight value corresponding to the humidity condition. C is the carrier gas concentration compensation value of the spectrometer to be calibrated in the detection environment. k3 is the weight value corresponding to the carrier gas concentration condition. k1+k2+k3=1.
[0031] Thirdly, this application discloses a computer-readable storage medium storing a computer program executable by a processor, which, when executed by the processor, implements the data calibration method for a spectrometer as described above.
[0032] Beneficial effects: The data calibration method, system and storage medium of the spectrometer in this application construct a spectral calibration model through deep learning using a standard training set and a test training set. During the calibration process of the spectrometer to be calibrated, the corresponding test conditions and the spectrum to be calibrated of the spectrometer to be calibrated are used as the data basis for spectral calibration, thereby calibrating the received spectrum of the spectrometer to be calibrated and achieving the purpose of ensuring the accuracy of its output results. Attached Figure Description
[0033] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, 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.
[0034] Figure 1 A flowchart illustrating the data calibration method for a spectrometer provided in this application embodiment. Detailed Implementation
[0035] The technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.
[0036] In this document, the term "comprising" is intended to cover a 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 limitation, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0037] This embodiment discloses, in its first aspect, as follows: Figure 1 The method for calibrating a spectrometer, as shown, includes the following steps:
[0038] A standard light source is obtained in a laboratory environment, and the standard light source is subjected to spectral testing under preset test conditions using laboratory equipment to obtain multiple sets of standard emission spectra and standard reception spectra, and the standard emission spectra and the standard reception spectra are stable.
[0039] The standard light source is subjected to spectral testing using a difference spectrometer under the preset test conditions to obtain multiple sets of test emission spectra and test reception spectra. The difference spectrometer is a known spectrometer that has output data that needs to be calibrated.
[0040] Define the standard emission spectrum and the standard reception spectrum to form a standard training set, and define the test emission spectrum and the test reception spectrum to form a test training set;
[0041] The standard training set, the test training set, and the corresponding test conditions are subjected to deep learning to obtain a spectral calibration model.
[0042] Obtain the spectral compensation value corresponding to each test condition. The spectral compensation value is the difference between the standard received spectrum and the test received spectrum under the same test conditions.
[0043] The spectral compensation value is used to perform spectral calibration on the spectrum to be calibrated corresponding to the spectrometer to be calibrated.
[0044] In this embodiment, the test conditions include any one of temperature variable, humidity variable, or carrier gas concentration variable.
[0045] In this embodiment, when the test condition involves a carrier gas concentration variable, after obtaining multiple sets of test emission spectra and test reception spectra, data drift calibration is performed on each set of test reception spectra, and the data drift-calibrated spectrum is used as the updated test reception spectrum. The test reception spectra in the test training set include the data drift-calibrated spectrum. Specifically, the data drift calibration includes longitudinal correction and lateral correction. For details, the data drift calibration method can refer to the corresponding method in the spectrometer data drift compensation method disclosed in application number CN201611156557.X. Those skilled in the art can obtain the longitudinal and lateral correction processes and results corresponding to this embodiment based on the prior art description, which will not be elaborated upon here.
[0046] Furthermore, when the test conditions are temperature or humidity variables, after obtaining multiple sets of test emission spectra and test reception spectra, each set of test reception spectra is normalized, and the normalized spectrum is used as the updated test reception spectrum. The test reception spectra in the test training set include the normalized spectrum.
[0047] Through the above-mentioned data drift calibration and normalization process, abnormal data in the received spectrum can be corrected, thereby ensuring that the spectral data obtained by the difference spectrometer under the preset test conditions is reliable. This ensures the accuracy of the spectral calibration model and further ensures the accuracy of the spectral compensation value, ultimately improving the accuracy of the spectral calibration results of the spectrum to be calibrated.
[0048] In this embodiment, the spectral calibration using the spectral compensation value for the spectrum to be calibrated of the spectrometer specifically includes:
[0049] The intensity value of each point in the spectrally calibrated spectrum is defined as SI, and the intensity value is calculated using the following formula:
[0050]
[0051] Among them, SI N To determine the spectral value corresponding to the midpoint N of the spectrum to be calibrated after spectral calibration, si N Before spectral calibration, the value corresponding to the midpoint N of the spectrum to be calibrated is given. T is the temperature compensation value of the spectrometer to be calibrated in the detection environment. k1 is the weight value corresponding to the temperature condition. W is the humidity compensation value of the spectrometer to be calibrated in the detection environment. k2 is the weight value corresponding to the humidity condition. C is the carrier gas concentration compensation value of the spectrometer to be calibrated in the detection environment. k3 is the weight value corresponding to the carrier gas concentration condition. k1+k2+k3=1. The detection environment refers to the environment in which the spectrometer to be calibrated is used for spectral detection.
[0052] By utilizing the aforementioned spectral compensation values to perform spectral calibration on the spectrum to be calibrated corresponding to the spectrometer to be calibrated, spectral calibration of the spectrum to be calibrated corresponding to the spectrometer to be calibrated is achieved. The determination of the weight values is based on the degree of influence of temperature, humidity, and carrier gas concentration on the spectrometer in the detection environment. This degree of influence is determined according to the spectrometer's manufacturer's standards / technical manual; that is, the greater the influence of a factor (temperature, humidity, or carrier gas concentration) on the spectrometer, the greater its corresponding weight value. Combined with the aforementioned data drift calibration process, the final detection result is obtained by summing the result calculated using the weight values and the mean with the spectral value corresponding to the midpoint N of the spectrum to be calibrated before spectral calibration. This balances the influence of the detection environment on the spectrometer, thereby optimizing the detection results and improving their accuracy and reliability.
[0053] This embodiment discloses a data calibration system for a spectrometer applicable to the aforementioned data calibration method for spectrometers, comprising a standard dataset acquisition module, a test dataset acquisition module, a model acquisition module, and a calibration module.
[0054] The standard dataset acquisition module is configured to: acquire a standard light source in a laboratory environment, perform spectral testing on the standard light source using laboratory equipment according to preset test conditions, and acquire multiple sets of standard emission spectra and standard reception spectra, wherein the standard emission spectra and the standard reception spectra are stable;
[0055] The test dataset acquisition module is configured to: use a difference spectrometer to perform spectral testing on the standard light source according to the preset test conditions, and obtain multiple sets of test emission spectra and test reception spectra, wherein the difference spectrometer is a known spectrometer that has output data that needs to be calibrated;
[0056] The model acquisition module is configured to perform deep learning on the standard training set, the test training set, and the corresponding test conditions to obtain a spectral calibration model, wherein the standard training set consists of the standard emission spectrum and the standard reception spectrum, and the test training set consists of the test emission spectrum and the test reception spectrum;
[0057] The calibration module is configured to: acquire the spectral compensation value corresponding to each test condition, wherein the spectral compensation value is the difference between the standard received spectrum and the test received spectrum under the same test conditions, and use the spectral compensation value to perform spectral calibration on the spectrum to be calibrated corresponding to the spectrometer to be calibrated.
[0058] Correspondingly, the test conditions include any one of temperature variables, humidity variables, or carrier gas concentration variables.
[0059] And, the spectral calibration using the spectral compensation value for the spectrum to be calibrated of the spectrometer to be calibrated specifically includes:
[0060] The intensity value of each point in the spectrally calibrated spectrum is defined as SI, and the intensity value is calculated using the following formula:
[0061]
[0062] Among them, SI N To determine the spectral value corresponding to the midpoint N of the spectrum to be calibrated after spectral calibration, si N Before spectral calibration, the value of the spectral midpoint N of the spectrum to be calibrated is given. T is the temperature compensation value of the spectrometer to be calibrated in the detection environment. k1 is the weight value corresponding to the temperature condition. W is the humidity compensation value of the spectrometer to be calibrated in the detection environment. k2 is the weight value corresponding to the humidity condition. C is the carrier gas concentration compensation value of the spectrometer to be calibrated in the detection environment. k3 is the weight value corresponding to the carrier gas concentration condition. k1+k2+k3=1.
[0063] It should be noted that the data calibration system of the spectrometer in this embodiment corresponds to the data calibration method of the spectrometer described above. Therefore, the technical effects it produces correspond to the corresponding technical effects in the data calibration method of the spectrometer, which will not be elaborated here.
[0064] This embodiment discloses a computer-readable storage medium storing a computer program executable by a processor. When the computer program is executed by the processor, it implements the data calibration method for the spectrometer as described above.
[0065] In the embodiments provided in this application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For hardware implementation, the processor may be implemented in one or more of the following: application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, other electronic units designed to implement the functions described herein, or combinations thereof. For software implementation, some or all of the processes of the embodiments may be performed by a computer program instructing the associated hardware. During implementation, the program may be stored in a computer-readable storage medium or transmitted as one or more instructions or code on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. Storage media may be any available medium accessible to a computer. Computer-readable storage media may include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code having the form of instructions or data structures and accessible to a computer.
[0066] Finally, it should be noted that the above description is only a preferred embodiment of this application and is not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.
Claims
1. A data calibration method for a spectrometer, characterized in that, The method includes the following steps: A standard light source is obtained in a laboratory environment, and the standard light source is subjected to spectral testing under preset test conditions using laboratory equipment to obtain multiple sets of standard emission spectra and standard reception spectra, and the standard emission spectra and the standard reception spectra are stable. The standard light source is subjected to spectral testing using a difference spectrometer under the preset test conditions to obtain multiple sets of test emission spectra and test reception spectra. The difference spectrometer is a known spectrometer that has output data that needs to be calibrated. Define the standard emission spectrum and the standard reception spectrum to form a standard training set, and define the test emission spectrum and the test reception spectrum to form a test training set; The standard training set, the test training set, and the corresponding test conditions are subjected to deep learning to obtain a spectral calibration model. Obtain the spectral compensation value corresponding to each test condition. The spectral compensation value is the difference between the standard received spectrum and the test received spectrum under the same test conditions. The spectral compensation value is used to perform spectral calibration on the spectrum to be calibrated corresponding to the spectrometer to be calibrated.
2. The data calibration method for a spectrometer according to claim 1, characterized in that, The test conditions include any one of the following: temperature variable, humidity variable, or carrier gas concentration variable.
3. The data calibration method for a spectrometer according to claim 2, characterized in that, When the test condition is a carrier gas concentration variable, after obtaining multiple sets of test emission spectra and test reception spectra, data drift calibration is performed on each set of test reception spectra, and the data drift calibrated spectrum is used as the updated test reception spectrum. The test reception spectra in the test training set include the data drift calibrated spectrum.
4. The data calibration method for a spectrometer according to claim 3, characterized in that, The data drift calibration specifically includes longitudinal correction and lateral correction.
5. The data calibration method for a spectrometer according to claim 2, characterized in that, When the test conditions are temperature or humidity variables, after obtaining multiple sets of test emission spectra and test reception spectra, each set of test reception spectra is normalized, and the normalized spectrum is used as the updated test reception spectrum. The test reception spectra in the test training set include the normalized spectrum.
6. The data calibration method for a spectrometer according to claim 1, characterized in that, The aforementioned spectral calibration using the spectral compensation value for the spectrum to be calibrated of the spectrometer specifically includes: The intensity value of each point in the spectrally calibrated spectrum is defined as SI, and the intensity value is calculated using the following formula: Among them, SI N To determine the spectral value corresponding to the midpoint N of the spectrum to be calibrated after spectral calibration, si N Before spectral calibration, the value of the spectral midpoint N of the spectrum to be calibrated is given. T is the temperature compensation value of the spectrometer to be calibrated in the detection environment. k1 is the weight value corresponding to the temperature condition. W is the humidity compensation value of the spectrometer to be calibrated in the detection environment. k2 is the weight value corresponding to the humidity condition. C is the carrier gas concentration compensation value of the spectrometer to be calibrated in the detection environment. k3 is the weight value corresponding to the carrier gas concentration condition. k1+k2+k3=1.
7. A data calibration system for a spectrometer, characterized in that, It includes a standard dataset acquisition module, a test dataset acquisition module, a model acquisition module, and a calibration module; The standard dataset acquisition module is configured to: acquire a standard light source in a laboratory environment, perform spectral testing on the standard light source using laboratory equipment according to preset test conditions, and acquire multiple sets of standard emission spectra and standard reception spectra, wherein the standard emission spectra and the standard reception spectra are stable; The test dataset acquisition module is configured to: use a difference spectrometer to perform spectral testing on the standard light source according to the preset test conditions, and obtain multiple sets of test emission spectra and test reception spectra, wherein the difference spectrometer is a known spectrometer that has output data that needs to be calibrated; The model acquisition module is configured to perform deep learning on the standard training set, the test training set, and the corresponding test conditions to obtain a spectral calibration model, wherein the standard training set consists of the standard emission spectrum and the standard reception spectrum, and the test training set consists of the test emission spectrum and the test reception spectrum; The calibration module is configured to: acquire the spectral compensation value corresponding to each test condition, wherein the spectral compensation value is the difference between the standard received spectrum and the test received spectrum under the same test conditions, and use the spectral compensation value to perform spectral calibration on the spectrum to be calibrated corresponding to the spectrometer to be calibrated.
8. The data calibration system for a spectrometer according to claim 7, characterized in that, The test conditions include any one of the following: temperature variable, humidity variable, or carrier gas concentration variable.
9. The data calibration system for a spectrometer according to claim 7, characterized in that, The aforementioned spectral calibration using the spectral compensation value for the spectrum to be calibrated of the spectrometer specifically includes: The intensity value of each point in the spectrally calibrated spectrum is defined as SI, and the intensity value is calculated using the following formula: Among them, SI N To determine the spectral value corresponding to the midpoint N of the spectrum to be calibrated after spectral calibration, si N Before spectral calibration, the value of the spectral midpoint N of the spectrum to be calibrated is given. T is the temperature compensation value of the spectrometer to be calibrated in the detection environment. k1 is the weight value corresponding to the temperature condition. W is the humidity compensation value of the spectrometer to be calibrated in the detection environment. k2 is the weight value corresponding to the humidity condition. C is the carrier gas concentration compensation value of the spectrometer to be calibrated in the detection environment. k3 is the weight value corresponding to the carrier gas concentration condition. k1+k2+k3=1.
10. A computer-readable storage medium, characterized in that, It stores a computer program that can be executed by a processor, and when the computer program is executed by the processor, it implements the data calibration method of the spectrometer as described in any one of claims 1-6.
Citation Information
Patent Citations
Spectrometer data drift compensation method
CN106769906B