CN118746360A - Energy dispersive X-ray fluorescence spectrometer and calibration method thereof - Google Patents

Abstract

The invention discloses an energy dispersion X-ray fluorescence spectrometer and a correction method thereof, relating to the technical field of spectrometers, the invention comprises a control system, the control system comprises a data module and an analysis module, the data module comprises an acquisition module and an uploading module, the acquisition module is particularly used for acquiring the operation data of the spectrometer, the acquisition module is used for acquiring the data at least comprising environmental data, spectrum signals and equipment operation parameter data, the invention can diagnose the affected environment and spectrum signals of the spectrometer in the running process, judge whether the spectrometer is abnormal under different running conditions, so as to realize the purpose of running monitoring, and filter and correct the spectrum signals, thereby further improving the stability and reliability of the spectrum data and improving the accuracy of the spectrometer.

Description

Energy dispersive X-ray fluorescence spectrometer and calibration method thereof

Technical Field

The present invention relates to the technical field of spectrometers, and in particular to an energy dispersion X-ray fluorescence spectrometer and a calibration method thereof.

Background Art

The energy range of medium-energy X-ray spectrometers is 2 to 5 keV, which is between the energy ranges of soft X-rays and hard X-rays. This energy range covers the absorption edges of chemical elements such as phosphorus, sulfur, and silicon, and plays an important role in life sciences, semiconductors and other fields. In recent years, with the development of medium-energy X-ray spectrometers, higher demands have been placed on their automated monitoring and control systems. For example, spectrometers need to take into account the monitoring needs of a variety of non-standard scientific equipment, such as X-ray sources, X-ray detectors, crystal analyzers, etc.; they need to meet the scientific use needs of different functions, such as X-ray radiation protection, vacuum interconnection protection, spectrometer scanning, etc. In addition, on the basis of achieving the monitoring stability of its industrialization level, the system also needs to have excellent scientific scalability, and can make corresponding functional expansions according to new scientific needs;

Now that the spectrometer is in operation, some factors such as the working environment and spectral signal reception inside the spectrometer will cause inaccurate detection of the spectrometer. Now when the spectrometer equipment has an abnormality, it cannot be determined through self-test.

Summary of the invention

In view of this, the purpose of the present invention is to provide an energy dispersive X-ray fluorescence spectrometer and a correction method thereof, so as to solve the problem in the prior art that when the spectrometer is in operation, the working environment and spectral signals in the spectrometer are subject to some factors which may cause inaccurate spectrometer detection, and when the spectrometer equipment has an abnormality, it cannot be determined through self-test.

According to a first aspect of an embodiment of the present invention, there is provided an energy dispersive X-ray fluorescence spectrometer,

comprising a control system, the control system comprising a data module and an analysis module;

The data module includes an acquisition module and an upload module. The acquisition module is specifically used to acquire the spectrometer operation data. The data acquired by the acquisition module at least includes: environmental data, spectral signals and equipment operation parameter data; the acquisition module at least includes: an environmental data acquisition module, a spectral signal acquisition module, and an equipment operation parameter data acquisition module; the upload module is used to convert the data acquired by the acquisition module into corresponding data electrical signals and upload them to the analysis module;

The environmental data acquisition module includes a temperature detection module and a humidity detection module;

The temperature detection module is used to collect temperature detection data when the spectrometer is running and upload the collected temperature detection data to the upload module;

The humidity detection module is used to detect the humidity when the spectrometer is running and upload the collected humidity detection data to the upload module;

The device operation parameter data acquisition module is used to collect device operation data and upload the device operation data to the upload module; wherein the device operation data includes: device data mainly involved in the work of the excitation spectrum, optical system, and detector;

The spectrum signal acquisition module includes: a spectrum acquisition module and a spectrum data processing module;

The spectrum acquisition module is used to acquire the generated spectrum signals; the spectrum data processing module is used to process the acquired spectrum signals and upload the processed spectrum signals to the analysis module;

The analysis module is used to perform data analysis on the received data electrical signal to determine whether the spectrometer is operating normally, and to analyze the spectral signal processed by the preset spectral data processing module, and to modify the spectral signal in combination with the temperature data of the currently acquired spectral signal to obtain a corrected target spectral signal.

Furthermore, the analysis module adopts a distributed computing architecture, including: a distributed computing platform based on Hadoop or Spark.

Furthermore, the spectral data processing module specifically includes a data preprocessing unit and a data correction unit;

The data preprocessing unit is used to perform background removal and noise removal operations on the collected spectral signal to obtain first processed data;

The data correction unit is used to correct the instrument response or the wavelength of the first processed data to eliminate the wavelength shift or nonlinear response in the spectral data.

Furthermore, the control system further comprises:

A spectrometer monitoring and control platform based on PLC and Python is used to monitor and control the medium-energy X-ray spectrometer device in real time.

According to a second aspect of an embodiment of the present invention, a correction method for an energy dispersive X-ray fluorescence spectrometer is provided, which is applied to any one of the energy dispersive X-ray fluorescence spectrometers described above, and is characterized in that the method comprises:

Acquire spectrometer operation data, the spectrometer operation data at least including: environmental data, spectral signals and equipment operation parameter data; the environmental data including: temperature detection data when the spectrometer is running, humidity detection data when the spectrometer is running; the equipment operation parameter data including: equipment data mainly involved in the work of the excitation spectrum, optical system and detector;

The operating data of the spectrometer is uploaded to a preset uploading module, and the temperature detection data when the spectrometer is running and the humidity detection data when the spectrometer is running are used to build an environmental parameter database;

Using the environmental parameter database and the equipment operation parameter data, a fitting function is constructed, and the fitting function is used to judge the change trend of the peak fitting function and the change trend of the trough fitting function under different conditions to determine the operating state of the spectrometer; wherein the fitting function includes: a peak fitting function and a trough fitting function;

The spectral signal is preprocessed, and the preprocessed spectral signal data is combined with the temperature data of the currently acquired spectral signal to modify the spectral signal to obtain a corrected target spectral signal.

Further, the spectral signal is preprocessed, and the preprocessed spectral signal data is combined with the temperature data of the currently acquired spectral signal to modify the spectral signal to obtain a corrected target spectral signal, including:

Performing background removal and noise removal processing on the spectral signal to obtain first processed data;

performing wavelength correction on the first processed data to obtain second processed data;

Using the second processed data, based on the temperature data of the currently acquired spectral signal, and using a preset temperature compensation correction formula, the target spectral signal is corrected to obtain a corrected spectral pixel position;

The temperature compensation correction formula is as follows:

λ＝f[s,Δs(T)] (1)

Wherein, λ is the spectral pixel position in the corrected target spectral signal, s is the spectral pixel position in the target spectral signal, T is the detected temperature, Δs＝a ₀ +a ₁ *T+a ₂ *T2+a ₃ *T3+a ₄ +T4, a ₀ , a ₁ , a ₂ , a ₃ , a ₄ are preset calibration coefficients;

A corrected target spectral signal is obtained based on the corrected spectral pixel position.

The technical solution provided by the embodiments of the present invention may have the following beneficial effects:

It can be understood that the technical solution provided by the present invention includes: the control system includes a data module and an analysis module; the data module includes an acquisition module and an upload module, the acquisition module is specifically used to acquire the operating data of the spectrometer, and the data acquired by the acquisition module at least includes: environmental data, spectral signals and equipment operating parameter data; the acquisition module at least includes: an environmental data acquisition module, a spectral signal acquisition module, and an equipment operating parameter data acquisition module; the upload module is used to convert the data acquired by the acquisition module into corresponding data electrical signals and upload them to the analysis module; the environmental data acquisition module includes a temperature detection module and a humidity detection module; the temperature detection module is used to collect temperature detection data when the spectrometer is running and upload the collected temperature detection data to the upload module; the humidity detection module is used to detect the humidity when the spectrometer is running and upload the collected humidity detection data The data is uploaded to the upload module; the equipment operation parameter data acquisition module is used to collect equipment operation data and upload the equipment operation data to the upload module; wherein the equipment operation data includes: the equipment data mainly involved in the work of the excitation spectrum, the optical system, and the detector; the spectrum signal acquisition module includes: a spectrum acquisition module and a spectrum data processing module; the spectrum acquisition module is used to collect the generated spectrum signal; the spectrum data processing module is used to process the collected spectrum signal and upload the processed spectrum signal to the analysis module; the analysis module is used to perform data analysis on the received data electrical signal to determine whether the spectrometer is operating normally, and analyze the spectrum signal processed by the preset spectrum data processing module, and modify the spectrum signal under the temperature data of the current spectrum signal acquisition to obtain the corrected target spectrum signal. It can be understood that the technical solution provided by the present invention can diagnose the environment and spectrum signal affected by the spectrometer during operation, determine whether the spectrometer is abnormal under different operating conditions, so as to achieve the purpose of operation monitoring, and filter and correct the spectrum signal at the same time, so that the stability and reliability of the spectrum data are further improved, and the accuracy of the spectrometer is improved.

It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

FIG1 is a schematic diagram showing the composition of an energy dispersive X-ray fluorescence spectrometer according to an exemplary embodiment;

FIG. 2 is a flowchart showing steps of a calibration method for an energy dispersive X-ray fluorescence spectrometer according to an exemplary embodiment.

DETAILED DESCRIPTION

Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

Embodiment 1

Please refer to FIG. 1 , which is a schematic diagram of a device composition of an energy dispersive X-ray fluorescence spectrometer according to an exemplary embodiment, including:

It includes a control system 10, characterized in that the control system 10 includes a data module 21 and an analysis module 20;

The data module 21 includes an acquisition module 211 and an upload module 212. The acquisition module 211 is specifically used to acquire the spectrometer operation data. The data acquired by the acquisition module 211 at least includes: environmental data, spectral signals and equipment operation parameter data; the acquisition module 211 at least includes: environmental data acquisition module 01 acquisition module 211, spectral signal acquisition module 02 acquisition module 211, equipment operation parameter data acquisition module 03 acquisition module 211; the upload module 212 is used to convert the data acquired by the acquisition module 211 into corresponding data electrical signals and upload them to the analysis module 20;

The environmental data acquisition module 01 acquisition module 211 includes a temperature detection module 011 and a humidity detection module 012;

The temperature detection module 011 is used to collect temperature detection data when the spectrometer is running and upload the collected temperature detection data to the upload module 212;

The humidity detection module 012 is used to detect the humidity when the spectrometer is running and upload the collected humidity detection data to the upload module 212;

The device operation parameter data acquisition module 03 acquisition module 211 is used to collect device operation data and upload the device operation data to the upload module 212; wherein the device operation data includes: device data mainly involved in the work of the excitation spectrum, optical system, and detector;

The spectrum signal acquisition module 02 acquisition module 211 includes: a spectrum acquisition module 021 and a spectrum data processing module 022;

The spectrum acquisition module 021 is used to acquire the generated spectrum signal; the spectrum data processing module 022 is used to process the acquired spectrum signal and upload the processed spectrum signal to the analysis module 20;

The analysis module 20 is used to perform data analysis on the received data electrical signal to determine whether the spectrometer is operating normally, and to analyze the spectral signal processed by the preset spectral data processing module 022, and to modify the spectral signal in combination with the temperature data of the currently acquired spectral signal to obtain a corrected target spectral signal.

In one embodiment, the present invention can diagnose the environment and spectral signals affected by the spectrometer during operation, determine whether the spectrometer has abnormalities under different operating conditions, so as to achieve the purpose of operation monitoring, and at the same time filter and correct the spectral signals to further improve the stability and reliability of the spectral data, thereby improving the accuracy of the spectrometer.

Furthermore, the analysis module 20 adopts a distributed computing architecture, including: a distributed computing platform based on Hadoop or Spark.

Furthermore, the spectral data processing module 022 specifically includes a data preprocessing unit and a data correction unit;

The data preprocessing unit is used to perform background removal and noise removal operations on the collected spectral signal to obtain first processed data;

The data correction unit is used to correct the instrument response or the wavelength of the first processed data to eliminate the wavelength shift or nonlinear response in the spectral data.

Furthermore, the control system 10 further includes:

A spectrometer monitoring and control platform based on PLC and Python is used to monitor and control the medium-energy X-ray spectrometer device in real time.

In the specific implementation, the equipment operation data specifically includes collecting the equipment data mainly involved in the work, such as the excitation spectrum, the optical system, and the detector, recording based on the environmental data obtained above and uploading through the uploading module 212, and the uploaded equipment operation data is subjected to curve analysis through the analysis module 20 based on the environmental parameter database to construct a fitting function, and the fitting function includes a peak fitting function and a trough fitting function, and the equipment operation parameter data collected based on the environmental data is quantitatively analyzed through the analysis module 20. Specifically, in order to analyze whether the spectrometer is working normally, the equipment operation parameters of the spectrometer under different conditions are compared, and the equipment operation parameters are characterized by two groups of functions, namely The peak fitting function and the trough fitting function are used to determine the changing trends of the peak fitting function and the trough fitting function under different conditions. For example, the stability of the spectrometer is better within a specific working range. When the working range is exceeded, the stability will decrease. For example, the higher the temperature, the worse the stability. If, by comparison, it is found that the stability obtained by the peak fitting function and the trough fitting function is more stable, then it is determined that the spectrometer is abnormal. There are two groups of variables, namely, sample variables and environmental condition variables. During analysis, one group of variables is determined to change the other group of variables to determine the stability of the peak fitting function and the trough fitting function under such conditions, so as to determine whether the spectrometer is operating normally.

The spectral signal includes a spectral acquisition module 021 and a spectral data processing module 022 . The spectral acquisition module 021 acquires the generated spectral signal, and then processes it through the spectral data processing module 022 . The processed spectral data is uploaded to the analysis module 20 through the upload module 212 .

The spectral data processing module 022 specifically includes a data preprocessing unit and a data correction unit;

The data preprocessing unit performs background removal and denoising operations on the collected spectral signals; background removal can eliminate background noise and interference from non-sampled substances; denoising is to smooth or reduce noise on the spectral signals to improve data quality;

The data correction unit performs instrument response correction or wavelength correction to eliminate wavelength shift or nonlinear response in the spectral data; the correction method can convert the measured spectral data into accurate and reliable results based on reference standard substances or calibration curves;

The accurate data after being analyzed by the spectrum data processing module 022 is analyzed by the analysis module 20, and the spectrum signal is modified based on the temperature data of the currently acquired spectrum signal;

Correcting the target spectral signal based on the detected temperature includes: substituting the detected temperature into a preset temperature compensation correction formula, i.e., formula (1), to correct the target spectral signal;

λ＝f[s,Δs(T)] (1)

In formula (1), λ is the spectral pixel position in the corrected target spectral signal, s is the spectral pixel position in the target spectral signal, T is the detected temperature, Δs= _a0 + _a1 *T+ _a2 *T2+ _a3 *T3+ _a4 +T4, _a0 , _a1 , _a2 , _a3 , _a4 are preset calibration coefficients; the target spectral signal includes multiple spectral pixel positions, each spectral pixel position is corrected by the above formula to obtain a corrected spectral pixel position, and a corrected target spectral signal is obtained based on the corrected spectral pixel position.

The control system 10 also includes a spectrometer monitoring and control platform based on PLC and Python, through which the medium-energy X-ray spectrometer device is monitored and controlled in real time. The target monitoring requirements of the medium-energy X-ray spectrometer device are met by designing a spectrometer integrated monitoring graphical interface using Python's PyQt5 library;

The spectrometer monitoring program and the spectrometer integrated monitoring graphical interface that have passed the monitoring circuit test are applied to the computer device to obtain the spectrometer monitoring and control platform.

In one embodiment, the present application compares the equipment operating parameters of the spectrometer under different conditions, and the equipment operating parameters are characterized by two sets of functions, to judge the changing trend of the peak fitting function and the changing trend of the trough fitting function under different conditions, to determine whether there is an abnormality in the spectrometer under different operating conditions, so as to achieve the purpose of operation monitoring; at the same time, the spectral signal can be filtered and corrected, so that the stability and reliability of the spectral data are further improved, and the accuracy of the spectrometer is improved.

Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Please refer to FIG. 2 , which is a flowchart of a calibration method for an energy dispersive X-ray fluorescence spectrometer according to an exemplary embodiment. The method includes:

S1. Obtain spectrometer operation data, the spectrometer operation data at least including: environmental data, spectral signal and equipment operation parameter data; the environmental data includes: temperature detection data when the spectrometer is running, humidity detection data when the spectrometer is running; the equipment operation parameter data includes: excitation spectrum, optical system, detector main equipment data;

S2. Upload the spectrometer operation data to a preset upload module, and use the temperature detection data when the spectrometer is running and the humidity detection data when the spectrometer is running to build an environmental parameter database;

S3. Using the environmental parameter database and the equipment operation parameter data, construct a fitting function, and use the fitting function to determine the change trend of the peak fitting function and the change trend of the trough fitting function under different conditions to determine the operating state of the spectrometer; wherein the fitting function includes: a peak fitting function and a trough fitting function;

S4. Preprocess the spectral signal, combine the preprocessed spectral signal data with the temperature data of the currently acquired spectral signal, modify the spectral signal, and obtain a corrected target spectral signal.

In one embodiment, the preprocessing of the spectral signal, combining the preprocessed spectral signal data with the temperature data of the currently acquired spectral signal, modifying the spectral signal, and obtaining a corrected target spectral signal includes:

Performing background removal and noise removal processing on the spectral signal to obtain first processed data;

performing wavelength correction on the first processed data to obtain second processed data;

Using the second processed data, based on the temperature data of the currently acquired spectral signal, and using a preset temperature compensation correction formula, the target spectral signal is corrected to obtain a corrected spectral pixel position;

The temperature compensation correction formula is as follows:

λ＝f[s,Δs(T)] (1)

Wherein, λ is the spectral pixel position in the corrected target spectral signal, s is the spectral pixel position in the target spectral signal, T is the detected temperature, Δs＝a ₀ +a ₁ *T+a ₂ *T2+a ₃ *T3+a ₄ +T4, a ₀ , a ₁ , a ₂ , a ₃ , a ₄ are preset calibration coefficients;

A corrected target spectral signal is obtained based on the corrected spectral pixel position.

In specific implementation, the data preprocessing unit performs background removal, denoising and other operations on the collected spectral signal; background removal can eliminate background noise and interference from non-sampled substances; denoising is to smooth or reduce noise on the spectral signal to improve data quality;

The data correction unit performs instrument response correction or wavelength correction to eliminate wavelength shift or nonlinear response in the spectral data; the correction method can convert the measured spectral data into accurate and reliable results based on reference standard substances or calibration curves;

The accurate data after being analyzed by the spectrum data processing module is analyzed by the analysis module, and the spectrum signal is modified based on the temperature data of the currently acquired spectrum signal;

Correcting the target spectral signal based on the detected temperature includes: substituting the detected temperature into a preset temperature compensation correction formula, i.e., formula (1), to correct the target spectral signal;

The target spectral signal includes a plurality of spectral pixel positions, each spectral pixel position is corrected by using the above formula to obtain a corrected spectral pixel position, and a corrected target spectral signal is obtained based on the corrected spectral pixel position.

The control system also includes a spectrometer monitoring and control platform based on PLC and Python, through which the medium-energy X-ray spectrometer device is monitored and controlled in real time. The target monitoring requirements of the medium-energy X-ray spectrometer device are met by designing a spectrometer integrated monitoring graphical interface using Python's PyQt5 library;

The spectrometer monitoring program and the spectrometer integrated monitoring graphic interface that have passed the monitoring circuit test are applied to the computer device to obtain the spectrometer monitoring and control platform.

It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

It should be noted that, in the description of the present invention, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "plurality" refers to at least two.

Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims (6)

1. An energy dispersive X-ray fluorescence spectrometer, comprising a control system, characterized in that the control system comprises a data module and an analysis module; The data module includes an acquisition module and an upload module. The acquisition module is specifically used to acquire the spectrometer operation data. The data acquired by the acquisition module at least includes: environmental data, spectral signals and equipment operation parameter data; the acquisition module at least includes: an environmental data acquisition module, a spectral signal acquisition module, and an equipment operation parameter data acquisition module; the upload module is used to convert the data acquired by the acquisition module into corresponding data electrical signals and upload them to the analysis module; The environmental data acquisition module includes a temperature detection module and a humidity detection module; The temperature detection module is used to collect temperature detection data when the spectrometer is running and upload the collected temperature detection data to the upload module; The humidity detection module is used to detect the humidity when the spectrometer is running and upload the collected humidity detection data to the upload module; The device operation parameter data acquisition module is used to collect device operation data and upload the device operation data to the upload module; wherein the device operation data includes: device data mainly involved in the work of the excitation spectrum, optical system, and detector; The spectrum signal acquisition module includes: a spectrum acquisition module and a spectrum data processing module; The spectrum acquisition module is used to acquire the generated spectrum signals; the spectrum data processing module is used to process the acquired spectrum signals and upload the processed spectrum signals to the analysis module; The analysis module is used to perform data analysis on the received data electrical signal to determine whether the spectrometer is operating normally, and to analyze the spectral signal processed by the preset spectral data processing module, and to modify the spectral signal in combination with the temperature data of the currently acquired spectral signal to obtain a corrected target spectral signal. 2. An energy dispersive X-ray fluorescence spectrometer according to claim 1, characterized in that the analysis module adopts a distributed computing architecture, including: a distributed computing platform based on Hadoop or Spark. 3. An energy dispersive X-ray fluorescence spectrometer according to claim 1, characterized in that the spectrum data processing module specifically includes a data preprocessing unit and a data correction unit; The data preprocessing unit is used to perform background removal and noise removal operations on the collected spectral signal to obtain first processed data; The data correction unit is used to correct the instrument response or the wavelength of the first processed data to eliminate the wavelength shift or nonlinear response in the spectral data. 4. The energy dispersive X-ray fluorescence spectrometer according to claim 1, wherein the control system further comprises: A spectrometer monitoring and control platform based on PLC and Python is used to monitor and control the medium-energy X-ray spectrometer device in real time. 5. A calibration method for an energy dispersive X-ray fluorescence spectrometer, applied to an energy dispersive X-ray fluorescence spectrometer according to any one of claims 1 to 4, characterized in that the method comprises: Acquire spectrometer operation data, the spectrometer operation data at least including: environmental data, spectral signals and equipment operation parameter data; the environmental data including: temperature detection data when the spectrometer is running, humidity detection data when the spectrometer is running; the equipment operation parameter data including: equipment data mainly involved in the work of the excitation spectrum, optical system and detector; The operating data of the spectrometer is uploaded to a preset uploading module, and the temperature detection data when the spectrometer is running and the humidity detection data when the spectrometer is running are used to build an environmental parameter database; Using the environmental parameter database and the equipment operation parameter data, a fitting function is constructed, and the fitting function is used to judge the change trend of the peak fitting function and the change trend of the trough fitting function under different conditions to determine the operating state of the spectrometer; wherein the fitting function includes: a peak fitting function and a trough fitting function; The spectral signal is preprocessed, and the preprocessed spectral signal data is combined with the temperature data of the currently acquired spectral signal to modify the spectral signal to obtain a corrected target spectral signal. 6. The method according to claim 1, characterized in that the preprocessing of the spectral signal, combining the preprocessed spectral signal data with the temperature data of the currently acquired spectral signal, modifying the spectral signal, and obtaining a corrected target spectral signal, comprises: Performing background removal and noise removal processing on the spectral signal to obtain first processed data; performing wavelength correction on the first processed data to obtain second processed data; Using the second processed data, based on the temperature data of the currently acquired spectral signal, and using a preset temperature compensation correction formula, the target spectral signal is corrected to obtain a corrected spectral pixel position; The temperature compensation correction formula is as follows: λ＝f[s,Δs(T)] (1) Wherein, λ is the spectral pixel position in the corrected target spectral signal, s is the spectral pixel position in the target spectral signal, T is the detected temperature, Δs＝a ₀ +a ₁ *T+a ₂ *T2+a ₃ *T3+a ₄ +T4, a ₀ , a ₁ , a ₂ , a ₃ , a ₄ are preset calibration coefficients; The corrected target spectral signal is obtained based on the corrected spectral pixel position.