CN117420121B - Metal spectrum identification method and system based on collision radiation and spectrum correlation - Google Patents

Abstract

The invention provides a metal spectrum identification method and a system based on collision radiation and spectrum association, which belong to the field of aerospace plasma propulsion, and the method comprises the steps of firstly determining the offset of the central wavelength of a spectrum acquired in an experiment; under the condition of meeting the offset, comprehensively comparing the intensities of the Einstein emission coefficient, the relative intensity, the upper energy level and the lower energy level to perform primary identification of spectral lines; for spectral lines which have the offset meeting the determined range and cannot be distinguished, the energy level structure on the spectral lines is focused, other strong spectral lines with the same upper energy level are found out, whether the spectral lines exist or not is further determined, so that metal spectrum identification of complex structures based on collision radiation and spectrum association is completed, and metal spectral lines of key components in the barium-tungsten hollow cathode can be identified and separated by means of the method.

Description

Metal spectrum identification method and system based on collision radiation and spectrum correlation

Technical Field

The present invention belongs to the field of aerospace plasma propulsion, and in particular, relates to a metal spectrum recognition method and system based on collision radiation and spectrum correlation.

Background technique

With the rapid development of all-electric propulsion satellites, space cargo transportation, and north-south maneuvers, there is an urgent need for high-power electric thrusters. Therefore, the hollow cathode is also expected to operate under high current working conditions, and the high-energy ions generated inside it exacerbate the erosion effect. Due to the weakness of this erosion, long-term erosion test experiments of hundreds or even thousands of hours have always been carried out in the past, and this measurement is limited to rough testing of the quality and shape contour of the material.

In order to further reveal this corrosion mechanism, it is necessary to clarify the types of each corrosion atom. At present, a method for measuring hollow cathode corrosion products through emission spectroscopy has been developed, which can monitor the corrosion product atoms of key components inside the hollow cathode and can perform quantitative analysis, greatly saving manpower and financial resources. However, since the content of the corrosion products to be monitored is extremely low, the spectral lines emitted are very weak and are often mixed with the strong spectral lines of the main working gas, especially the metal spectral lines of some complex structures are extremely difficult to identify. In response to this problem, the present invention proposes a complex structure metal spectral identification method based on collision radiation mechanism and spectral correlation analysis, which can accurately identify the corrosion products of key components inside the electric propulsion hollow cathode, which will well solve the major problem of hollow cathode corrosion diagnosis by emission spectroscopy.

Summary of the invention

In view of the difficulty in identifying complex spectral lines when diagnosing hollow cathode corrosion products through emission spectroscopy, the present invention proposes a metal spectrum identification method and system based on collision radiation and spectral correlation. Starting from the collision radiation mechanism that produces emission spectra, spectral correlation analysis is used to identify weak metal spectra mixed in strong spectral lines. This method can be used to identify and separate metal spectral lines of key components inside complex structures such as barium tungsten hollow cathodes.

The present invention is achieved through the following technical solutions:

Metal spectrum identification method based on collision radiation and spectrum correlation: The method specifically comprises the following steps:

Step 1: determine the offset of the central wavelength of the spectrum collected in the experiment;

Step 2: Under the condition of satisfying the offset, the spectral line is preliminarily identified by comprehensive comparison based on the Einstein emission coefficient A _ki , the relative intensity Rel.Int, the intensity of the upper energy level E _k and the intensity of the lower energy level E _i ;

Step 3. For spectral lines whose offsets meet the range determined in step 1 but still cannot be distinguished according to step 2, focus on the energy level structure of their upper energy levels, find other strong spectral lines with the same upper energy level, and further determine whether these spectral lines exist, so as to complete the spectral identification of complex structure metals based on collision radiation and spectral correlation.

Furthermore, in step 1,

Since the PI spectrometer is equipped with three gratings with different grooves, the different gratings are switched by precise control of the stepper motor in the experiment. The combined effect of vibration and mechanical deformation on the spectrometer will cause a small angle rotation of the optical axis in the optical path system of the spectrometer, that is, the change of the incident angle and diffraction angle.

From the grating equation nλ = d(sinθ-sini), it can be seen that this will eventually lead to a nonlinear shift of the central wavelength;

Where n is the diffraction order, λ is the spectral wavelength, d is the grating constant, θ is the incident angle, and i is the diffraction angle;

When the grating plane is deflected by an angle of α due to a small vibration, the new wavelength λ ₁ corresponding to the original diffraction angle spectrum channel becomes:

Among them, λ ₀ is the original wavelength;

Since the offset caused by the small angle rotation of the optical axis is very small and has a quadratic function relationship with the intrinsic central wavelength of the original spectral channel, it will not change the change of the diffraction order. In the experiment, the standard light source mercury argon lamp is first used to determine the offset of the central wavelength of the spectrometer. The final observed offset is within a certain range.

The emission wavelength of the standard light source mercury-argon lamp is fixed. The emission of the mercury-argon lamp is measured with a spectrometer, and the measured spectral wavelength data is compared with the actual data of the standard mercury-argon lamp to determine the offset of the central wavelength of the spectrometer.

Furthermore, in step 2, the emission intensity of the emission spectrum line is directly determined by the Einstein emission coefficient A _ki : I _ik ∝N _k A _ki hν _ik , hν _ik =E _k -E _i ; therefore, the spectrum line with a larger Einstein emission coefficient will have a larger relative intensity and a greater probability of being observed in the experiment;

In the formula, _Iik is the intensity of the spectral line emitted from the transition from the upper energy state _Ek to the lower energy state _Ei , _Nk is the number of atoms in the excited state of the upper energy level _Ek , Aki _is the Einstein emission coefficient, h is the Planck constant, and _νik is the frequency of the spectrum determined by the upper and lower energy level structure.

Furthermore, in step three, for very strong emission lines, there is a high probability that spectral line transitions of other wavelengths will occur from the same upper energy level. By searching for these spectral lines in the experiment, the unidentifiable spectral lines can be further confirmed.

Metal spectrum identification system based on collision radiation and spectrum correlation:

The recognition system includes a collection module, a preliminary recognition module and a recognition supplement module:

The acquisition module is used to determine the offset of the central wavelength of the spectrum collected in the experiment;

The preliminary identification module is used to perform preliminary identification of the spectrum line by comprehensive comparison based on the Einstein emission coefficient A _ki , the relative intensity Rel.Int, the intensity of the upper energy level E _k and the intensity of the lower energy level E _i under the condition of satisfying the offset;

The identification supplement module focuses on the energy level structure of the upper energy level of the spectral lines whose offsets meet the range determined by the acquisition module but still cannot be distinguished by the preliminary identification module, finds out other strong spectral lines with the same upper energy level, and further determines whether these spectral lines exist, so as to complete the complex structure metal spectrum identification based on collision radiation and spectral correlation.

An electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

A computer-readable storage medium is used to store computer instructions, and when the computer instructions are executed by a processor, the steps of the above method are implemented.

Beneficial effects of the present invention

The spectral line identification method of the present invention is suitable for monitoring metal corrosion products (trace products) of some complex structures in the field of electric propulsion by emission spectroscopy;

The present invention aims at the difficulty of spectral line identification when monitoring corrosion products in the electric propulsion field by emission spectroscopy. Starting from the generation mechanism of emission spectrum, the corrosion products of key components inside the hollow cathode of electric propulsion can be accurately identified, thereby solving a major problem of corrosion diagnosis of the hollow cathode by emission spectroscopy.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 is a flow chart of the method of the present invention;

FIG. 2 is a schematic diagram showing changes in the incident angle and the diffraction angle caused by a small-angle deflection of the optical axis of the grating of the spectrometer according to the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

Combined with Figure 1 and Figure 2.

Metal spectrum identification method based on collision radiation and spectrum correlation: The method specifically comprises the following steps:

Step 1: determine the offset of the central wavelength of the spectrum collected in the experiment;

Since the PI spectrometer is equipped with three gratings with different lines, the different gratings are switched by precise control of the stepper motor in the experiment. The structure is very precise, and any slight vibration will cause changes in the mechanical structure to have a great impact on the accuracy of the spectrometer. The combined effect of these vibrations and mechanical deformations on the spectrometer will cause a small angle rotation of the optical axis in the optical path system of the spectrometer, that is, changes in the incident angle and diffraction angle.

From the grating equation nλ＝d(sinθ-sini), it can be seen that this will eventually lead to a nonlinear shift of the central wavelength;

Where n is the diffraction order, λ is the spectral wavelength, d is the grating constant, θ is the incident angle, and i is the diffraction angle;

When the grating plane is deflected by an angle of α due to a small vibration, the new wavelength λ ₁ corresponding to the original diffraction angle spectrum channel becomes:

Where, λ ₀ is the original wavelength;

Since the offset caused by the small angle rotation of the optical axis is very small and has a quadratic function relationship with the intrinsic central wavelength of the original spectral channel, it will not change the change of the diffraction order. In the experiment, the standard light source mercury argon lamp is first used to determine the offset of the central wavelength of the spectrometer. The final observed offset is within the range of ≤0.5nm.

The emission wavelength of the standard light source mercury-argon lamp is fixed. The emission of the mercury-argon lamp is measured with a spectrometer, and the measured spectral wavelength data is compared with the actual data of the standard mercury-argon lamp to determine the offset of the central wavelength of the spectrometer.

First, the center wavelength offset of the spectrum collected in the experiment is determined to be within the range of ≤0.5nm by using a laboratory standard light source in the range of 780nm-800nm, wherein the offset of the xenon atomic spectrum line (796.958nm) is specifically 0.22nm.

Step 2: Under the condition of satisfying the offset, the spectral line is preliminarily identified by comprehensive comparison based on the Einstein emission coefficient A _ki , the relative intensity Rel.Int, the intensity of the upper energy level E _k and the intensity of the lower energy level E _i ;

The emission intensity of the emission spectrum line is directly determined by the Einstein emission coefficient A _ki : I _ik ∝N _k A _ki hν _ik , hν _ik = E _k -E _i ; therefore, the spectrum line with a larger Einstein emission coefficient will have a larger relative intensity and a greater probability of being observed in the experiment;

In the formula, _Iik is the intensity of the spectral line emitted from the transition from the upper energy state _Ek to the lower energy state _Ei , _Nk is the number of atoms in the excited state of the upper energy level _Ek , Aki _is the Einstein emission coefficient, h is the Planck constant, and _νik is the frequency of the spectrum determined by the upper and lower energy level structure.

In step two, the upper and lower energy levels directly reflect the electron energy situation inside the plasma. For a hollow cathode, the electron energy is almost below 25eV under normal discharge conditions. Therefore, the upper and lower energy levels of excited atoms caused by electron collision excitation will not exceed this range. This is an important reference point in spectral line identification.

Initial identification of xenon atomic and monovalent xenon ion spectral lines was performed in the 780nm-800nm band. It was eventually found that the 790.46nm spectral line could not be further identified.

Step 3. For spectral lines whose offsets meet the range determined in step 1 but still cannot be distinguished according to step 2, focus on the energy level structure of their upper energy levels. You can refer to relevant literature to find other strong spectral lines with the same upper energy level, and further determine whether these spectral lines exist in the experiment to further distinguish and identify them, and complete the spectral identification of complex structure metals based on collision radiation and spectral correlation.

For spectral lines that cannot be identified by referring to parameters such as the offset of the central wavelength, the Einstein emission coefficient, the relative intensity, and the upper and lower energy levels, find other spectral lines with the same upper energy level structure for the possible unidentifiable spectral lines. This is because for very strong emission spectral lines, there is a high probability that spectral lines of other wavelengths will transition from the same upper energy level. By finding these spectral lines in the experiment, the unidentified spectral lines can be further confirmed.

For the spectral line with a wavelength of 790.46nm, we focus on the upper energy level structure of its possible atoms: barium atoms at 790.5747nm and divalent xenon ions at 790.29nm, and refer to existing literature to find other strong spectral lines with the same upper energy level.

For the barium atom with a wavelength of 790.5747nm, its upper energy level structure is 6s7s 3S 1; other spectral lines with the same upper energy level are 739.2405nm.

For the divalent xenon ion with a wavelength of 790.29 nm, its upper energy level structure is 5s ² 5p ³ (4S ⁰ )6d 3D 3; other spectral lines with the same upper energy level are 420.239 nm.

The experiment further confirmed whether these two spectral lines existed in order to further distinguish and identify them. It was finally discovered that no spectral lines were found near the wavelength of 739.24±0.5nm, but there was a weak spectral line at a wavelength of 420.528nm, which was 0.2nm different from the divalent xenon ion with the same upper energy level structure of NIST. This can well prove that the unidentifiable 790.46nm spectral line above is a divalent xenon ion.

The method of the present invention is also used to successfully identify carbon atoms and tungsten atoms in the plume of the barium tungsten hollow cathode, wherein the carbon mainly originates from the cathode contact electrode, and the tungsten mainly originates from the tungsten top.

The present invention can also be extended to the following steps:

Step 4: Correct measurement errors: Although the offset of the central wavelength is determined in step 1, the actual measurement process may be affected by many factors, including but not limited to environmental noise, equipment errors, sample inhomogeneity, etc. Therefore, in order to obtain accurate results, the wavelength of the spectrometer can be calibrated by a laser of known wavelength; the background noise spectrum is obtained by measuring a blank sample, and then this background spectrum is subtracted from the spectrum of the actual experiment to achieve background noise correction.

Step 5: Repeat measurement and verification: By repeating the measurement, the accuracy and stability of the results can be better ensured. You can also use different experimental equipment and conditions for verification.

Step 6: Use statistical methods to perform final identification of spectral lines: After all data collection and preliminary processing are completed, statistical methods such as principal component analysis and cluster analysis can be used to perform final identification of spectral lines.

Metal spectrum identification system based on collision radiation and spectrum correlation:

The recognition system includes a collection module, a preliminary recognition module and a recognition supplement module:

The acquisition module is used to determine the offset of the central wavelength of the spectrum collected in the experiment;

The preliminary identification module is used to perform preliminary identification of the spectrum line by comprehensive comparison based on the Einstein emission coefficient A _ki , the relative intensity Rel.Int, the intensity of the upper energy level E _k and the intensity of the lower energy level E _i under the condition of satisfying the offset;

The identification supplement module focuses on the energy level structure of the upper energy level of the spectral lines whose offsets meet the range determined by the acquisition module but still cannot be distinguished by the preliminary identification module, finds out other strong spectral lines with the same upper energy level, and further determines whether these spectral lines exist, so as to complete the complex structure metal spectrum identification based on collision radiation and spectral correlation.

An electronic device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

A computer-readable storage medium is used to store computer instructions, and when the computer instructions are executed by a processor, the steps of the above method are implemented.

The memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory, ROM, a programmable read-only memory, PROM, an erasable programmable read-only memory, EPROM, an electrically erasable programmable read-only memory, EEPROM, or a flash memory. The volatile memory may be a random access memory, RAM, which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory static RAM, SRAM, dynamic random access memory dynamic RAM, DRAM, synchronous dynamic random access memory synchronous DRAM, SDRAM, double data rate synchronous dynamic random access memory double data rate SDRAM, DDR SDRAM, enhanced synchronous dynamic random access memory enhanced SDRAM, ESDRAM, synchronous link dynamic random access memory synchlink DRAM, SLDRAM, and direct memory bus random access memory direct rambus RAM, DR RAM. It should be noted that memory of the methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center through a wired method such as coaxial cable, optical fiber, digital subscriber line digital subscriber line, DSL or wireless such as infrared, wireless, microwave, etc. to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium such as a floppy disk, a hard disk, a tape, an optical medium such as a high-density digital video disc digital video disc, DVD, or a semiconductor medium such as a solid state disk solid state disc, SSD, etc.

In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software. The steps of the method disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor for execution, or a combination of hardware and software modules in a processor for execution. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it is not described in detail here.

It should be noted that the processor in the embodiment of the present application can be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiment can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor can be a general-purpose processor, a digital signal processor DSP, an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiment of the present application can be directly embodied as a hardware decoding processor to perform, or the hardware and software modules in the decoding processor can be combined and performed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

The above is a detailed introduction to the metal spectrum identification method and system based on collision radiation and spectral correlation proposed in the present invention, and the principles and implementation methods of the present invention are explained. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims (6)

1. The metal spectrum identification method based on collision radiation and spectrum association is characterized by comprising the following steps of:

the method specifically comprises the following steps:

step one, determining the offset of the central wavelength of a spectrum acquired in an experiment;

in the first step, since the PI spectrometer is equipped with three gratings with different reticles, in the experiment, the different gratings are switched by precisely controlling the stepper motor, and the comprehensive influence of vibration and mechanical deformation on the spectrometer can cause small-angle rotation of the optical axis in the optical path system of the spectrometer, namely, the change of the incident angle and the diffraction angle;

As can be seen from the grating equation nλ=d (sinθ—sini), a nonlinear shift in the center wavelength is eventually caused;

Wherein n is the diffraction order, lambda is the spectral wavelength, d is the grating constant, theta is the incident angle, and i is the diffraction angle;

When the deflection angle of the grating plane is alpha due to the tiny vibration, the grating plane corresponds to the original diffraction angle spectrum channel, and the new spectrum wavelength lambda ₁ after deflection is as follows:

Wherein lambda ₀ is the original wavelength;

The offset caused by small angle rotation of the optical axis is very small, and the relationship of the offset and the intrinsic center wavelength of the original spectrum channel is a quadratic function, so that the change of diffraction orders is not changed, in the experiment, the offset of the center wavelength of the spectrometer is firstly determined by using a standard light source mercury argon lamp, and finally the observed offset is in a certain range;

The light-emitting wavelength of the standard light source mercury-argon lamp is fixed, the light-emitting of the mercury-argon lamp is measured by a spectrometer, the measured spectrum wavelength data is compared with the actual standard mercury-argon lamp data, and the offset of the central wavelength of the spectrometer is determined;

Under the condition of meeting the offset, comprehensively comparing the intensities of the Einstein emission coefficient A _ki, the relative intensity Rel.Int, the upper energy level E _k level and the lower energy level E _i level to perform primary identification of spectral lines;

and thirdly, regarding the offset to be within the offset range determined in the first step, but not distinguishing the spectral lines according to the second step, focusing on the energy level structure on the spectral lines, finding out other strong spectral lines with the same upper energy level, and further determining whether the spectral lines exist or not so as to complete the metal spectrum recognition of the complex structure based on collision radiation and spectrum association.

2. The identification method of claim 1, wherein:

In step two, the emission spectrum line emission intensity is directly determined by the einstein emission coefficient a _ki: i _ik∝N_kA_kihν_ik,hν_ik＝E_k-E_i; therefore, the spectral line with a larger Einstein emission coefficient has larger relative intensity, and the observed probability in the experiment is also larger;

where I _ik is the intensity of the emission line from the upper energy state E _k to the lower energy state E _i, N _k is the number of excited atoms at the upper energy state E _k, A _ki Einstein emission coefficient, h is the Planckian constant, and v _ik is the frequency of the spectrum determined by the upper and lower energy structures.

3. The identification method according to claim 2, characterized in that:

in step three, for a very strong emission line, a high probability of spectral line transitions at other wavelengths from the same upper energy level will occur, and the unrecognizable line is further confirmed by searching for these lines in the experiment.

4. A recognition system for performing the method for recognizing a metal spectrum based on collision radiation and spectral correlation as claimed in any one of claims 1 to 3, characterized in that:

The identification system comprises an acquisition module, a preliminary identification module and an identification supplementing module:

the acquisition module is used for determining the offset of the central wavelength of the spectrum acquired in the experiment;

The acquisition module is provided with three gratings with different reticles, different gratings are switched through the accurate control of a stepping motor in experiments, and the comprehensive influence of vibration and mechanical deformation on the spectrometer can cause small-angle rotation of an optical axis in a spectrometer optical path system, namely the change of an incident angle and a diffraction angle;

As can be seen from the grating equation nλ=d (sinθ—sini), a nonlinear shift in the center wavelength is eventually caused;

Wherein n is the diffraction order, lambda is the spectral wavelength, d is the grating constant, theta is the incident angle, and i is the diffraction angle;

When the deflection angle of the grating plane is alpha due to the tiny vibration, the grating plane corresponds to the original diffraction angle spectrum channel, and the new spectrum wavelength lambda ₁ after deflection is as follows:

Wherein lambda ₀ is the original wavelength;

The offset caused by small angle rotation of the optical axis is very small, and the relationship of the offset and the intrinsic center wavelength of the original spectrum channel is a quadratic function, so that the change of diffraction orders is not changed, and the offset of the center wavelength of the spectrometer is determined by using a standard light source mercury argon lamp in an experiment; the final observed offset is within a certain range; the light-emitting wavelength of the standard light source mercury-argon lamp is fixed, the light-emitting of the mercury-argon lamp is measured by a spectrometer, the measured spectrum wavelength data is compared with the actual standard mercury-argon lamp data, and the offset of the central wavelength of the spectrometer is determined;

The primary identification module is used for comprehensively comparing the intensities of the upper energy level E _k level and the lower energy level E _i level according to the Einstein emission coefficient A _ki, the relative intensity Rel.int and the like under the condition of meeting the offset to perform primary identification of spectral lines;

and the identification supplementing module focuses on the energy level structure of the spectral lines which are not distinguishable according to the primary identification module and the range of which the offset meets the determination of the acquisition module, finds out other strong spectral lines with the same upper energy level, and determines whether the spectral lines exist or not so as to complete metal spectrum identification based on collision radiation and spectrum association.

5. An electronic device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 3 when the computer program is executed.

6. A computer readable storage medium storing computer instructions which, when executed by a processor, implement the steps of the method of any one of claims 1 to 3.