X-ray fluorescence spectrum analysis device and method for distinguishing 201 steel and 304 steel

Abstract

The invention belongs to the technical field of elemental analysis equipment, and relates to an X-ray fluorescence spectrum analysis device and method for distinguishing 201 steel and 304 steel, and the device comprises a laser emitter which emits laser to measured metal, and generates a periodic micro-nano structure on the surface of a material by using the energy of the laser; the X-ray excitation source is used for emitting X-rays to the detected metal; the prism light splitting device is used for decomposing spectral information into components with different wavelengths and then distributing the components to different silicon drift detectors for acquisition; a plurality of silicon drift detectors collect spectral information and convert the spectral information into electric signals according to energy resolution; the data processor is used for analyzing the electric signal received by the silicon drift detector and converting the electric signal into an energy spectrum for generating elements; and quantitatively determining the content of each element in the sample by adopting an energy spectrum. By adopting the laser transmitter and accurately controlling the detection time, the time difference of X-rays emitted by different elements can be distinguished, so that more accurate analysis is realized.

Description

Technical Field

[0001] The invention belongs to the technical field of element analysis equipment and relates to an X-ray fluorescence spectrum analysis device and method for distinguishing 201 steel and 304 steel. Background Art

[0002] Both 201 steel and 304 steel belong to the category of stainless steel, but they have obvious differences in chemical composition and use. 201 steel is mainly a low-nickel austenitic stainless steel, and its nickel content is usually between 1%-5%, while the manganese content is relatively high, which can reach 5.5%-7.5%. In the spectral analysis, characteristic peaks related to manganese and nitrogen content can be observed. 304 steel is a commonly used austenitic stainless steel with high chromium and nickel. In the spectral analysis of 304 steel, higher characteristic peaks of chromium and nickel can be observed, which is due to their higher content. These characteristic peaks help to distinguish 304 steel from 201 steel.

[0003] The working principle of X-ray fluorescence spectrometry is based on the following key steps: X-ray emission. X-ray fluorescence spectrometry generates high-energy X-ray beams through X-ray tubes. These X-rays act on the sample surface and interact with the atoms in the sample. When high-energy X-rays are irradiated on the sample surface, the energy of the X-rays is sufficient to excite the atoms in the sample. During the excitation process, some atoms in the sample absorb the energy of the X-rays, causing the electrons inside the atoms to jump from low energy levels to high energy levels. The excited atoms are not stable and immediately release their internal electrons and return to their original energy levels. In this process, fluorescence signals are released. These fluorescence signals have specific energy and wavelength, which depends on the type of atom and the energy level structure. The fluorescence signals are captured and converted into electrical signals by the detector, which analyzes the energy and intensity of these signals and converts them into digital data. These data are compared with the previously established standard curve or reference library to determine the presence and content of different elements in the sample.

[0004] According to the analysis results of the element content, it can be distinguished whether the sample is 201 steel or 304 steel. If a sample has a low nickel content and a high manganese content, it is 201 steel; on the contrary, if the nickel content is high and the manganese content is low, it is 304 steel.

[0005] However, existing X-ray fluorescence spectrometry devices have high requirements for the surface roughness of metal samples. Excessive surface roughness may cause X-ray scattering, affecting the accuracy of the signal. In addition, during the detection process, the X-ray fluorescence spectrometry device is easily affected by superposition peaks. This is because the energy spectrum peak ranges of the X-rays emitted by the elements sometimes overlap with each other, making it impossible to accurately distinguish the signals of these elements, and the detector of the device may have certain energy resolution limitations. In the case of overlapping spectrum peaks, it is difficult for the instrument to distinguish these similar spectrum lines, resulting in signal superposition. Summary of the invention

[0006] In view of the problems existing in the prior art, the technical problem to be solved by the present invention is to provide an X-ray fluorescence spectrum analysis device and method for distinguishing 201 steel and 304 steel.

[0007] The present invention is achieved in this way. An X-ray fluorescence spectrometer for distinguishing 201 steel and 304 steel, the device comprising: A laser transmitter emits a laser to the metal being tested. The laser is coaxial with the X-ray and uses the energy of the laser to generate a periodic micro-nano structure on the surface of the material. X-ray excitation source, which emits X-rays to the metal being tested to excite the atoms in the sample; Prism spectrometer: When X-rays interact with the sample, the spectral information generated is decomposed into components of different wavelengths through the prism spectrometer, and then distributed to different silicon drift detectors for collection; Multiple silicon drift detectors collect spectral information and convert it into electrical signals according to energy resolution; The data processor is used to analyze the electrical signal received by the silicon drift detector and convert it into an energy spectrum for generating elements; the energy spectrum is used to quantitatively determine the content of each element in the sample.

[0008] Furthermore, the sample is placed in a sample chamber, and a prism spectrometer is provided above the placement groove of the sample chamber, which is suspended directly above the sample, and the optical signal is decomposed into components of different wavelengths through the prism spectrometer.

[0009] Furthermore, there are three silicon drift detectors to simultaneously detect ion signals of different masses and charge ratios. The silicon drift detectors use a clock synchronization mechanism to ensure that the data acquisition process of each silicon drift detector is based on the same time reference.

[0010] Furthermore, the data processor comprises: Detector interface: an interface connected to the silicon drift detector, used to receive electrical signals from the silicon drift detector. These signals are usually characteristic X-rays generated by the interaction between X-rays and samples, which are converted into electrical signals by the detector; Display interface: An interface connected to a display, used to receive the energy spectrum from a data processor.

[0011] Analog-to-digital converter: converts analog signals into digital signals; Preamplifier: amplifies the weak signal output by the silicon drift detector; Multi-channel analyzer MCA: responsible for multi-channel analysis of input signals, classifying and counting input signals according to different energies to form an X-ray energy spectrum.

[0012] Element identification and quantitative analysis module: Through the built-in element database, the data processor can automatically identify the elements in the spectrum and perform quantitative analysis based on the intensity of the spectral peaks.

[0013] Power Management Unit: Provides a stable power supply for the entire data processor, ensuring its stability and reliability during high-precision processing and long-term operation.

[0014] Furthermore, after the multi-channel analyzer MCA is connected to the silicon drift detector, it will amplify the signal and adjust the signal shape through the forming circuit. The multi-channel analyzer MCA uses an analog-to-digital converter to convert the analog signal into a digital signal. The digital signal represents particles or photons of different energies. The multi-channel analyzer MCA classifies the digital signal and assigns it to different energy channels. Each energy channel corresponds to a specific energy range. Low-energy signals are assigned to low-energy channels, and high-energy signals are assigned to high-energy channels. The multi-channel analyzer MCA performs statistical analysis on the classified signals and finally draws an energy spectrum.

[0015] Furthermore, the element identification and quantitative analysis module receives the energy spectrum, first uses time resolution technology to separate the signals of different elements, and then performs preliminary denoising on the data of each channel through multiple channels to remove random noise or system noise, and eliminate possible system offset or baseline drift in each channel to ensure the accuracy of the signal; if there is a deviation in time or frequency in the data acquisition of each channel, the deviation is corrected to ensure the synchronization of each channel signal; for channel data with different frequencies or wavelengths, spectral difference analysis is performed to distinguish possible superimposed peaks; and non-negative matrix decomposition is used to decompose the superimposed peaks into non-negative components to extract each independent peak.

[0016] Furthermore, the prism spectrometer comprises a surface collimator, an imaging mirror and a prism. The incident light first passes through a surface collimator and enters the prism spectrometer. When propagating inside, it is affected by the refractive surface of the prism, refracted and dispersed, and finally emitted from the surface of the imaging mirror. The parameters of the prism are adjusted to adjust the refraction angle and the distribution of wavelength to achieve different wavelength splitting effects.

[0017] Furthermore, the device is arranged on a laboratory table, the laboratory table comprises an L-shaped seat body, the L-shaped seat body comprises a vertical structure and a base, a groove is provided in the middle of the vertical structure for arranging a detection structure, the detection structure comprises: a hollow cavity, an observation window is arranged at the top of the hollow cavity, an X-ray excitation source is arranged below the observation window, and the X-ray excitation source is arranged at a position that does not block the line of sight through the observation window, A shielding channel coaxial with the hollow cavity is arranged at the lower end of the hollow cavity, a ring member is coaxially arranged at the lower end of the shielding channel, the diameter of the ring member is larger than the shielding channel, a data processor is embedded in the ring inside of the ring member, and a plurality of silicon drift detectors are arranged on the ring surface of the bottom surface of the ring member; An experimental table is arranged on the base facing the inner channel of the annular member. A sample chamber is installed on the experimental table. A prism spectrometer above the sample chamber decomposes the optical signal into components of different wavelengths and distributes them to multiple silicon drift detectors for collection.

[0018] A method for distinguishing 201 steel and 304 steel, comprising: The laser is emitted to the metal to be tested, and the laser is coaxial with the X-ray, and the energy of the laser is used to generate a periodic micro-nano structure on the surface of the material; Emit X-rays to the metal being tested to excite the atoms in the sample; When X-rays interact with the sample, the generated spectral information passes through a prism spectrometer, which decomposes the spectral information into components of different wavelengths and then distributes them to different silicon drift detectors for collection; Multiple silicon drift detectors collect spectral information and convert it into electrical signals according to energy resolution, which are then used to generate the energy spectrum of the element; Energy spectrum is used to quantitatively determine the content of each element in the sample.

[0019] Furthermore, the electrical signal is used to generate the energy spectrum of the element, including: amplifying the signal and adjusting the signal shape, converting the analog signal into a digital signal, the digital signal represents particles or photons of different energies, classifying the digital signal, and assigning it to different energy channels. Each energy channel corresponds to a specific energy range. Low-energy signals are assigned to low-energy channels, and high-energy signals are assigned to high-energy channels; statistical analysis is performed on the classified signals, and finally an energy spectrum diagram is drawn.

[0020] Furthermore, for the energy spectrum, time resolution technology is first used to separate signals of different elements, and the separated signals of different elements are subjected to preliminary denoising of the data of each channel through multiple channels to remove random noise or system noise, and eliminate possible system offset or baseline drift in each channel to ensure the accuracy of the signal; if there is a deviation in time or frequency in the data acquisition of each channel, the deviation is corrected to ensure the synchronization of each channel signal; for channel data with different frequencies or wavelengths, spectral difference analysis is performed to distinguish possible superimposed peaks; and non-negative matrix decomposition is used to decompose the superimposed peaks into non-negative components to extract each independent peak.

[0021] Compared with the prior art, the present invention has the following beneficial effects: Compared with the existing X-ray fluorescence spectrometer, the present invention uses a laser emitter and can distinguish the time difference of X-ray emission of different elements by accurately controlling the detection time, thereby achieving more accurate analysis. After separating the spectral lines, multi-channel analysis technology is used to analyze the separated spectral lines of multiple different frequencies or energy ranges, and perform spectrum difference analysis to distinguish possible superposition peaks. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A three-dimensional diagram of an X-ray fluorescence spectrometer provided in an embodiment of the present invention; Figure 2 A front view of the X-ray fluorescence spectrometer analysis device with the box body and the box cover removed provided by the embodiment of the present invention; Figure 3 Side view of the X-ray fluorescence spectrometer analysis device without the box body and the box cover provided by the embodiment of the present invention Figure 4 is a top view of a sample chamber provided by an embodiment of the present invention; Figure 5 It is a schematic diagram of a prism spectrometer provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0024] like Figure 1 As shown, the X-ray fluorescence spectrometer is arranged in a box 10, and the box 10 has a box cover 9. The bottom surface of the box 10 has a recessed portion; the box cover 9 is hinged on the box, and when the box cover is closed on the box, the box cover is located in the recessed portion.

[0025] like Figure 2 and 3 As shown, the X-ray fluorescence spectrometer is arranged on a laboratory table, including an L-shaped base, the L-shaped base includes a vertical structure and a base, a groove is opened in the middle of the vertical structure for setting a detection structure, the detection structure includes: a hollow cavity, an observation window 1 is arranged at the top of the hollow cavity, and a calibrator can also be arranged, the calibrator is used to determine that the laser emitter and the X-ray excitation source are overlooking the sample in the sample chamber. In one embodiment, the calibrator is a device for calibrating the present invention. Before the experiment begins, turn on the laser emitter to observe whether the laser is irradiated vertically to the sample metal. If not, there is a support rod behind the X-ray excitation source, and the calibrator makes the X-ray excitation source movable by changing the position of the support rod. By adjusting, the laser is completely irradiated vertically to the sample metal. Because the laser beam is coaxial with the X-ray, it is also ensured that the X-ray is irradiated vertically to the sample metal. By detecting and correcting possible deviations, the reliability of the experimental results is improved.

[0026] An X-ray excitation source 2 is arranged under the observation window, and the X-ray excitation source is arranged at a position that does not block the sight through the observation window. A shielding channel 4 coaxial with the hollow cavity is provided at the lower end of the hollow cavity, a ring member 5 is coaxially provided at the lower end of the shielding channel 4, the diameter of the ring member is larger than the shielding channel, a data processor 5 is embedded in the ring inside of the ring member, and a plurality of silicon drift detectors 6 are provided on the ring surface of the bottom surface of the ring member, and the position of the silicon drift detector 6 does not affect the passage of X-rays and lasers; Facing the inner channel of the ring, a laboratory table is set on the base, and a sample chamber 7 is installed on the laboratory table. The plane prism above the sample chamber decomposes the optical signal into components of different wavelengths and distributes them to multiple silicon drift detectors 6 for collection; the sample chamber is a closed space for placing experimental samples. The design of the sample chamber takes into account the interaction between the sample and the excitation source such as laser and X-ray, ensuring that the sample is not disturbed by the outside world when it is excited.

[0027] The X-ray fluorescence spectrometer provided in this embodiment includes: A laser transmitter emits a laser to the metal being tested. The laser is coaxial with the X-ray and uses the energy of the laser to generate a periodic micro-nano structure on the surface of the material. X-ray excitation source, which emits X-rays to the metal being tested to excite the atoms in the sample; Prism spectrometer: When X-rays interact with the sample, the spectral information generated is decomposed into components of different wavelengths through the prism spectrometer, and then distributed to different silicon drift detectors for collection; Multiple silicon drift detectors collect spectral information and convert it into electrical signals according to energy resolution; The data processor is used to analyze the electrical signal received by the silicon drift detector and convert it into an energy spectrum for generating elements; the energy spectrum is used to quantitatively determine the content of each element in the sample.

[0028] Laser transmitter, when the laser beam irradiates the surface of the material, the light energy of the laser is absorbed by the material and converted into heat energy, which will cause local heating of the surface of the material. When the intensity of laser irradiation is high, plasma (i.e. charged particles) may be generated on the surface, which will cause local light field modulation and affect the surface of the material. This high-intensity laser irradiation may cause local reflection and refraction on the surface of the material, forming a periodic microstructure. After the laser irradiates the surface, the reflected light and the incident light will interfere. Under certain conditions, the incident laser beam and the reflected laser beam will produce interference patterns on the surface of the material, forming a periodic surface structure.

[0029] X-ray excitation source is a device that generates X-rays, which is mainly used to excite atoms inside the sample, thereby inducing secondary radiation. This secondary radiation can be captured and analyzed by the detector to obtain the elemental composition and structural information of the sample.

[0030] The silicon drift detector has three, multiple sensors that simultaneously detect ion signals of different masses and charge ratios, and record peaks that may be superimposed. It has high energy resolution and detection efficiency, and it excites electrons in silicon crystals through fluorescent X-rays to generate electrical signals. The fluorescent X-rays emitted by the sample pass through the window of the detector (usually metal or a thin plastic material) and enter the silicon crystal of the silicon drift detector SDD. When the X-rays interact with the silicon crystal in the detector, they release electron and hole pairs (i.e., electron-hole pairs). These carriers will quickly migrate to the electrodes under the action of the electric field, generating a current signal. The intensity and waveform of the current are proportional to the energy of the X-rays, and the signal is ultimately interpreted by the analyzer.

[0031] Silicon Drift Detectors include: The window is the outermost layer of the silicon drift detector, allowing the fluorescent X-rays to pass through and reach the photosensitive layer of the silicon drift detector. The material used is beryllium; The photosensitive layer, which uses semiconductor crystals, is used to absorb fluorescent X-rays and generate measurable electronic signals; A drift electric field for moving electron-hole pairs generated in the photosensitive layer to the electrode structure; Electrode structure: It includes a front electrode and a rear electrode. The front electrode is located at one end of the silicon drift detector and is used to receive electron-hole pairs generated inside the photosensitive layer after fluorescent X-ray irradiation; the rear electrode is located at the other end of the silicon drift detector and receives charges moving from the inside of the photosensitive layer.

[0032] The drift electric field inside the detector is formed in the detector by the voltage applied by the external power supply, ensuring that electrons and holes can effectively move to the electrode and promote the generated electron-hole pairs to move to the detection electrode. In the electrode structure, the front electrode is usually very thin and usually transparent to ensure that the X-rays can act directly on the surface of the silicon crystal as much as possible to maximize the detection efficiency. The charge moves to the rear electrode under the action of the drift electric field and is transmitted to the subsequent electronic processing system through the change of current. Finally, after the charge conversion and signal processing circuit, the charge signal is converted into an electrical signal that can be further analyzed. The detector contains a charge conversion amplifier (pre-amplifier), which amplifies the weak signal generated from the silicon crystal to a level suitable for subsequent processing.

[0033] Data processors include: Detector interface: an interface connected to the silicon drift detector, used to receive electrical signals from the silicon drift detector. These signals are usually characteristic X-rays generated by the interaction between X-rays and samples, which are converted into electrical signals by the detector; Display interface: an interface connected to the display 8, used to receive the energy spectrum of the data processor. The display is a terminal device in the system for presenting data and results. It displays the results generated by the processor to the user in the form of intuitive images, charts or numerical values. The display in this device is a high-resolution LCD screen that can clearly display the real-time progress of the experiment, parameter adjustments and the final analysis results, providing users with intuitive data feedback and facilitating experimental adjustments and decisions. Analog-to-digital converter: converts analog signals into digital signals; Preamplifier: amplifies the weak signal output by the silicon drift detector; Multi-channel analyzer MCA: responsible for multi-channel analysis of input signals, classifying and counting input signals according to different energies to form an X-ray energy spectrum.

[0034] Element identification and quantitative analysis module: Through the built-in element database, the data processor can automatically identify the elements in the spectrum and perform quantitative analysis based on the intensity of the spectral peaks.

[0035] Power Management Unit: Provides a stable power supply for the entire data processor, ensuring its stability and reliability during high-precision processing and long-term operation.

[0036] like Figure 4 As shown, after the excitation source is prepared, the sample to be tested needs to be placed on a metal placement table 11 in a carefully designed sample chamber. The sample chamber should not only protect the sample from external contamination, but also ensure that the X-rays can evenly and effectively irradiate the sample surface. Above it is a prism spectrometer 12, which decomposes the optical signal into components of different wavelengths and then distributes them to three detectors for collection.

[0037] See also Figure 5 As shown, the prism spectrometer is composed of a surface collimator 13, an imaging mirror 15 and a prism 15. The incident light first passes through a surface collimator to enter the prism spectrometer. When propagating inside, it is affected by the refractive surface of the prism, refracted and dispersed, and finally emitted from the surface of the imaging mirror. The parameters of the prism are adjusted to adjust the refraction angle and the distribution of wavelength to achieve different wave splitting effects.

[0038] like Figure 5 As shown, among the three silicon drift detectors, multiple silicon drift detectors simultaneously detect ion signals of different masses and charge ratios, and record peaks that may be superimposed.

[0039] The data processor is equipped with a multi-channel analyzer MCA. After the multi-channel analyzer MCA is connected to the silicon drift detector, it will amplify the signal and adjust the signal shape through the shaping circuit to measure the energy size more accurately. Then, the multi-channel analyzer MCA uses an analog-to-digital converter (ADC) to convert the analog signal into a digital signal, which represents particles or photons of different energies. Next, the multi-channel analyzer MCA classifies these digital signals and assigns them to different energy channels, each of which corresponds to a specific energy range. Signals with lower energy are assigned to the low energy channel, and signals with higher energy are assigned to the high energy channel. The multi-channel analyzer MCA performs statistical analysis on the classified signals and finally draws an energy spectrum. At the same time, the data processor is equipped with a power management and control unit, which can capture the voltage and current phasors in the power grid in real time, helping system operators to quickly identify abnormal conditions in the power system, such as voltage collapse or grid instability, so as to take timely countermeasures.

[0040] The element identification and quantitative analysis module receives the energy spectrum, first uses time resolution technology to separate the signals of different elements, and then performs preliminary denoising on the data of each channel through multiple channels to remove random noise or system noise, and eliminate possible system offset or baseline drift in each channel to ensure the accuracy of the signal; if there is a deviation in time or frequency in the data acquisition of each channel, the deviation is corrected to ensure the synchronization of each channel signal; for channel data with different frequencies or wavelengths, spectral difference analysis is performed to distinguish possible superimposed peaks; and non-negative matrix decomposition is used to decompose the superimposed peaks into non-negative components to extract each independent peak.

[0041] The work of an X-ray fluorescence spectrometer begins with an excitation source. The core of an X-ray excitation source usually includes an electron gun. The cathode is heated in the electron gun, causing it to release electrons. These electrons are accelerated under the action of an electric field. The high voltage applied between the cathode and the anode accelerates the electrons, giving them very high kinetic energy. The accelerated electron beam is directed to the target material. When the high-energy electron beam hits the surface of the target material, they knock the inner electrons in the target material out of orbit, creating vacancies. The high-energy outer electrons fill these vacancies and release X-rays of a specific energy, which corresponds to the characteristics of the target material. The generated X-rays are output from the excitation source through a window. In order to avoid unnecessary radiation in the environment, the X-ray source is usually equipped with a shielding structure that only allows X-rays of a specific wavelength to pass through.

[0042] The analysis principle of the above-mentioned X-ray fluorescence spectrometer for distinguishing 201 steel and 304 steel is: The device emits laser light to the sample in the sample chamber through a laser emitter. Laser-induced periodic surface structure is a surface treatment technology that uses the energy of laser to produce periodic micro-nano structures on the surface of the material. These structures can affect the surface roughness of the material. It is used to improve the friction and lubrication properties of the metal surface and improve the surface coating of the metal.

[0043] The X-ray emission source produces a high-energy X-ray beam that penetrates the sample and interacts with the atoms in the sample. When high-energy X-rays are irradiated onto the surface of the sample, the energy of the X-rays is sufficient to excite the atoms in the sample. During the excitation process, some atoms in the sample absorb the energy of the X-rays, causing the electrons inside the atoms to transition from a low energy level to a high energy level. The emission of fluorescent X-rays, the excited atoms are not stable, and they immediately release their internal electrons and return to their original energy levels. In this process, fluorescent X-rays are released. These fluorescent X-rays have specific energy and wavelength, depending on the type of atom and the energy level structure; the generation of fluorescent signals will not cause damage to the sample; and the intensity of a peak in the fluorescence spectrum is proportional to the concentration of the element in the sample, which can be used for quantitative analysis.

[0044] When the light signal interacts with the sample, the spectral information generated needs to pass through a prism spectrometer to decompose the light signal into components of different wavelengths, which are then distributed to different detectors for collection. Multiple detectors collect the emitted X-rays and convert them into electrical signals based on energy resolution, which are then used to generate the energy spectrum of the element.

[0045] The energy spectrum obtained by the data processor can be used to quantitatively determine the content of each element in the sample, and these data are compared with the previously established standard curve or reference library. Finally, the spectrum is displayed on the monitor.

[0046] The embodiment of the present invention also provides a method for distinguishing 201 steel and 304 steel, comprising emitting a laser to the metal to be tested, wherein the laser is coaxial with the X-ray, and using the energy of the laser to generate a periodic micro-nano structure on the surface of the material; Emit X-rays to the metal being tested to excite the atoms in the sample; When X-rays interact with the sample, the generated spectral information passes through a prism spectrometer, which decomposes the spectral information into components of different wavelengths and then distributes them to different silicon drift detectors for collection; Multiple silicon drift detectors collect spectral information and convert it into electrical signals according to energy resolution, which are then used to generate the energy spectrum of the element; Energy spectrum is used to quantitatively determine the content of each element in the sample.

[0047] Electrical signals are used to generate the energy spectrum of elements, including: amplifying the signal and adjusting the signal shape, converting analog signals into digital signals, digital signals represent particles or photons of different energies, classifying digital signals and assigning them to different energy channels. Each energy channel corresponds to a specific energy range. Low-energy signals are assigned to low-energy channels, and high-energy signals are assigned to high-energy channels. Statistical analysis is performed on the classified signals to finally draw an energy spectrum diagram.

[0048] For the energy spectrum, time resolution technology is first used to separate the signals of different elements, and the separated signals of different elements are subjected to preliminary denoising of the data of each channel through multiple channels to remove random noise or system noise, and eliminate possible system offset or baseline drift in each channel to ensure the accuracy of the signal; if there is a deviation in time or frequency in the data acquisition of each channel, the deviation is corrected to ensure the synchronization of each channel signal; for channel data with different frequencies or wavelengths, spectrum difference analysis is performed to distinguish possible superimposed peaks; and non-negative matrix decomposition is used to decompose the superimposed peaks into non-negative components to extract each independent peak.

[0049] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An X-ray fluorescence spectrometer for distinguishing 201 steel and 304 steel, characterized in that: The device includes: A laser transmitter emits a laser to the metal being tested. The laser is coaxial with the X-ray and uses the energy of the laser to generate a periodic micro-nano structure on the surface of the material. X-ray excitation source, which emits X-rays to the metal being tested to excite the atoms in the sample; Prism spectrometer: When X-rays interact with the sample, the spectral information generated is decomposed into components of different wavelengths through the prism spectrometer, and then distributed to different silicon drift detectors for collection; Multiple silicon drift detectors collect spectral information and convert it into electrical signals according to energy resolution; The data processor is used to analyze the electrical signal received by the silicon drift detector and convert it into an energy spectrum for generating elements; the energy spectrum is used to quantitatively determine the content of each element in the sample.

2. The X-ray fluorescence spectrometer for distinguishing 201 steel and 304 steel according to claim 1, characterized in that: The sample is placed in the sample chamber, and a prism spectrometer is arranged above the groove at the placement point of the sample chamber, which is suspended just above the sample, and the light signal is decomposed into components of different wavelengths through the prism spectrometer; there are three silicon drift detectors, which can simultaneously detect ion signals of different masses and charge ratios, and the silicon drift detectors adopt a clock synchronization mechanism to ensure that the data acquisition process of each silicon drift detector is on the same time basis.

3. The X-ray fluorescence spectrometer for distinguishing 201 steel and 304 steel according to claim 2, characterized in that: Data processors include: Detector interface: an interface connected to the silicon drift detector, used to receive electrical signals from the silicon drift detector. These signals are usually characteristic X-rays generated by the interaction between X-rays and samples, which are converted into electrical signals by the detector; Display interface: an interface connected to a display, used to receive the energy spectrum of a data processor; Analog-to-digital converter: converts analog signals into digital signals; Preamplifier: amplifies the weak signal output by the silicon drift detector; Multi-channel analyzer MCA: responsible for multi-channel analysis of input signals, classifying and counting input signals according to different energies to form an X-ray energy spectrum; Element identification and quantitative analysis module: Through the built-in element database, it can automatically identify the elements in the spectrum and perform quantitative analysis based on the intensity of the spectrum peak; Power Management Unit: Provides a stable power supply for the entire data processor, ensuring its stability and reliability during high-precision processing and long-term operation.

4. The X-ray fluorescence spectrometer for distinguishing 201 steel and 304 steel according to claim 3, characterized in that: After the multi-channel analyzer MCA is connected to the silicon drift detector, it will amplify the signal and adjust the signal shape through the shaping circuit. The multi-channel analyzer MCA uses an analog-to-digital converter to convert the analog signal into a digital signal. The digital signal represents particles or photons of different energies. The multi-channel analyzer MCA classifies the digital signal and assigns it to different energy channels. Each energy channel corresponds to a specific energy range. Low-energy signals are assigned to low-energy channels, and high-energy signals are assigned to high-energy channels. The multi-channel analyzer MCA performs statistical analysis on the classified signals and finally draws an energy spectrum.

5. The X-ray fluorescence spectrometer for distinguishing 201 steel and 304 steel according to claim 3, characterized in that: The element identification and quantitative analysis module receives the energy spectrum, first uses time resolution technology to separate the signals of different elements, and then performs preliminary denoising on the data of each channel through multiple channels to remove random noise or system noise, and eliminate possible system offset or baseline drift in each channel to ensure the accuracy of the signal; if there is a deviation in time or frequency in the data acquisition of each channel, the deviation is corrected to ensure the synchronization of each channel signal; for channel data with different frequencies or wavelengths, spectral difference analysis is performed to distinguish possible superimposed peaks; and non-negative matrix decomposition is used to decompose the superimposed peaks into non-negative components to extract each independent peak.

6. The X-ray fluorescence spectrometer for distinguishing 201 steel and 304 steel according to claim 1, characterized in that: The prism spectrometer is composed of a surface collimator, an imaging mirror and a prism. The incident light first passes through a surface collimator and enters the prism spectrometer. When propagating inside, it is affected by the refractive surface of the prism, refracted and dispersed, and finally emitted from the surface of the imaging mirror. The parameters of the prism are adjusted to adjust the refraction angle and the distribution of wavelength to achieve different wave splitting effects.

7. The X-ray fluorescence spectrometer for distinguishing 201 steel and 304 steel according to claim 1, characterized in that: The device is arranged on a laboratory table, and the laboratory table comprises an L-shaped seat body, and the L-shaped seat body comprises a vertical structure and a base, and a groove is provided in the middle of the vertical structure for arranging a detection structure, and the detection structure comprises: a hollow cavity, an observation window is arranged at the top of the hollow cavity, and an X-ray excitation source is arranged below the observation window, and the X-ray excitation source is arranged at a position that does not block the sight through the observation window, A shielding channel coaxial with the hollow cavity is arranged at the lower end of the hollow cavity, a ring member is coaxially arranged at the lower end of the shielding channel, the diameter of the ring member is larger than the shielding channel, a data processor is embedded in the ring inside of the ring member, and a plurality of silicon drift detectors are arranged on the ring surface of the bottom surface of the ring member; An experimental table is arranged on the base facing the inner channel of the annular member. A sample chamber is installed on the experimental table. A prism spectrometer above the sample chamber decomposes the optical signal into components of different wavelengths and distributes them to multiple silicon drift detectors for collection.

8. A method for distinguishing 201 steel and 304 steel, characterized in that: include: The laser is emitted to the metal to be tested, and the laser is coaxial with the X-ray, and the energy of the laser is used to generate a periodic micro-nano structure on the surface of the material; Emit X-rays to the metal being tested to excite the atoms in the sample; When X-rays interact with the sample, the generated spectral information passes through a prism spectrometer, which decomposes the spectral information into components of different wavelengths and then distributes them to different silicon drift detectors for collection; Multiple silicon drift detectors collect spectral information and convert it into electrical signals according to energy resolution, which are then used to generate the energy spectrum of the element; Energy spectrum is used to quantitatively determine the content of each element in the sample.

9. The method for distinguishing 201 steel and 304 steel according to claim 1, characterized in that: Electrical signals are used to generate the energy spectrum of elements, including: amplifying the signal and adjusting the signal shape, converting analog signals into digital signals, digital signals represent particles or photons of different energies, classifying digital signals and assigning them to different energy channels. Each energy channel corresponds to a specific energy range. Low-energy signals are assigned to low-energy channels, and high-energy signals are assigned to high-energy channels. Statistical analysis is performed on the classified signals to finally draw an energy spectrum diagram.

10. The X-ray fluorescence spectrometer for distinguishing 201 steel and 304 steel according to claim 9, characterized in that: For the energy spectrum, time resolution technology is first used to separate the signals of different elements, and the separated signals of different elements are subjected to preliminary denoising of the data of each channel through multiple channels to remove random noise or system noise, and eliminate possible system offset or baseline drift in each channel to ensure the accuracy of the signal; if there is a deviation in time or frequency in the data acquisition of each channel, the deviation is corrected to ensure the synchronization of each channel signal; for channel data with different frequencies or wavelengths, spectrum difference analysis is performed to distinguish possible superimposed peaks; and non-negative matrix decomposition is used to decompose the superimposed peaks into non-negative components to extract each independent peak.

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