Rare earth element detection method and system

Abstract

The invention relates to the technical field of rare earth element detection, and provides a rare earth element detection method and system, and the method comprises the steps: obtaining the parameters of the size distribution degradation degree of aerosol droplets based on the physical wear degree of an atomizer under the current working condition; according to a preset association rule between the characteristics of the rare earth elements and the signal suppression degree and the parameters of the size distribution degradation degree of the aerosol droplets, determining the signal suppression amount of each to-be-detected rare earth element; according to the signal suppression amount, calculating and applying a corresponding correction weight factor, and correcting the original measurement signal value to obtain a corrected signal value; and using the corrected signal values to calculate the proportion between the pre-specified rare earth elements, and outputting the proportion to complete the detection of the rare earth elements. The method has the effect of improving the accuracy and reliability of rare earth element detection.

Description

Technical Field

[0001] This invention relates to the technical field of rare earth element detection, and specifically to a rare earth element detection method and system. Background Technology

[0002] In modern industrial production, the precise detection of specific elements in materials is crucial for ensuring product performance and batch consistency. Especially in the manufacturing of high-performance materials, the precise proportions of rare earth elements are a significant factor determining the final product's performance. Typically, techniques such as inductively coupled plasma optical emission spectrometry (ICP-OES) or intramolecular plasma mass spectrometry (ICP-MS) are used for this detection. The basic principle is that the sample is first atomized into fine aerosols by an nebulizer, then excited or ionized in a plasma, and finally the type and content of the element are determined by detecting the emitted light or ion signals.

[0003] In many industrial production processes, the key quality indicator for a product is not the absolute content of a single rare earth element, but rather the precise ratio between specific rare earth elements. Due to the combined effects of minor degradation of atomizers and inappropriate adjustments to automated instruments, the reported rare earth element ratios in complex industrial samples exhibit a systematic and difficult-to-trace drift. This drift is not a simple linear deviation, but a non-linear effect intricately related to the sample matrix, element types, and instrument aging. Therefore, this ratio distortion cannot be resolved through simple calibration or linear correction, leading to biased product quality assessments and potentially causing incorrect grading of entire production batches, resulting in significant economic losses and production disruptions.

[0004] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0005] This application discloses a method and system for detecting rare earth elements, aiming to solve the problem of distortion in the detection of rare earth element proportions caused by the deterioration of aerosol droplet size distribution due to physical wear of the atomizer and the differential effect of automated compensation mechanisms on the suppression of signals of different rare earth elements in the detection of complex industrial samples.

[0006] The technical solution of this application is as follows: Firstly, this application discloses a method for detecting rare earth elements, including: Based on the physical wear of the atomizer under current operating conditions, parameters are obtained to determine the degree of degradation in aerosol droplet size distribution. Based on the pre-defined correlation rules between rare earth element characteristics and signal suppression degree, as well as the parameter of aerosol droplet size distribution degradation degree, the signal suppression amount that each rare earth element to be tested should be determined. Based on the signal suppression amount, the corresponding correction weight factor is calculated and applied to correct the original measured signal value, thus obtaining the corrected signal value. Using the corrected signal value, the ratio between the pre-specified rare earth elements is calculated and the ratio is output to complete the rare earth element detection.

[0007] This technical solution can effectively solve the problems of aerosol droplet size distribution degradation caused by atomizer wear and the differential impact of automatic compensation mechanism on the suppression of signals of different rare earth elements, thereby achieving accurate detection of rare earth element ratios and overcoming the problem of difficulty in correcting ratio distortion in existing technologies.

[0008] Furthermore, in the rare earth element detection method, the steps of calculating and applying the corresponding correction weighting factor based on the signal suppression amount to correct the original measured signal value and obtain the corrected signal value include: Obtain the adjustment amount of the signal strength made by the automatic compensation mechanism; The original measured signal value is adjusted in reverse according to the adjustment amount to obtain a signal value that has removed the effect of automatic compensation. Based on the signal suppression amount, the corresponding correction weight factor is calculated and applied to correct the signal value after removing the effect of automatic compensation, thus obtaining the corrected signal value.

[0009] This technical solution can accurately isolate the interference of the automated compensation mechanism on the signal, ensuring the accuracy of subsequent correction and further improving the reliability of the test results.

[0010] In some preferred embodiments, the step of obtaining parameters regarding the degree of deterioration in aerosol droplet size distribution based on the physical wear of the atomizer under current operating conditions in the rare earth element detection method includes: Obtain the size distribution parameters of matrix-simulated aerosol droplets generated after the matrix-simulated solution is atomized in an atomizer; Based on the matrix simulation parameters of aerosol droplet size distribution, the impact of matrix physical property fluctuations on aerosol droplet size distribution is quantified. From the actual aerosol droplet size distribution parameters obtained from the test sample, the influence of the physical property fluctuations of the strip matrix on the aerosol droplet size distribution is analyzed, and parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer are obtained.

[0011] This technical solution can effectively distinguish the effects of matrix characteristic fluctuations and atomizer wear on aerosol droplet size distribution, making the assessment of atomizer wear more accurate.

[0012] Furthermore, in the rare earth element detection method, the step of determining the amount of signal suppression that each rare earth element should be subjected to, based on the preset correlation rules between rare earth element characteristics and signal suppression degree, and the parameter of aerosol droplet size distribution degradation degree, includes: A set of calibration samples with known rare earth element content and different matrix properties are introduced according to a preset cycle; Measure the signal response of each rare earth element in the calibration sample; Based on the signal response and the known rare earth element content of the calibration sample, record the actual signal suppression amount of each rare earth element under the current atomizer degradation level; Based on the pre-defined correlation rules between rare earth element characteristics and signal suppression degree, the predicted signal suppression amount is estimated. The actual signal suppression amount is compared with the predicted signal suppression amount to calculate the degree of deviation of the association rule; Based on the degree of deviation, adjust the weight coefficients in the preset association rule between rare earth element characteristics and signal suppression degree to optimize the association rule; Using the adjusted association rules, combined with parameters on the degree of degradation of aerosol droplet size distribution, the amount of signal suppression that each rare earth element to be measured should receive is determined.

[0013] This technical solution can dynamically optimize the correlation rules between rare earth element characteristics and signal suppression degree, making it more accurately reflect the actual working conditions, thereby improving the accuracy of signal suppression determination.

[0014] Based on the above, this application further proposes that, in the rare earth element detection method, the steps for obtaining parameters of the deterioration degree of aerosol droplet size distribution based on the physical wear degree of the atomizer under current operating conditions include: A solution containing tracer particles of at least two different size ranges is introduced according to a preset cycle; Measure the size distribution parameters of aerosol droplets formed after the tracer particle solution is atomized; Calculate the ratio of size distribution parameters to obtain the tracer particle ratio; Obtain the preset correlation rules between wear patterns and tracer particle ratios; By matching the tracer particle ratio with the mode selection association rule, the wear mode of the current atomizer can be identified; Based on the identified wear patterns, parameters for the degree of degradation of the corresponding aerosol droplet size distribution are obtained.

[0015] This technical solution enables rapid and intuitive identification of atomizer wear patterns using tracer particle solutions, providing an efficient and reliable method for obtaining parameters of aerosol droplet size distribution degradation.

[0016] As an optional approach, in rare earth element detection methods, the steps for obtaining parameters regarding the degree of deterioration in aerosol droplet size distribution based on the physical wear of the atomizer under current operating conditions include: Simultaneously acquire current ambient temperature, humidity, and air pressure parameters; Based on the baseline correlation established under controlled experimental conditions between the ambient temperature, ambient humidity, ambient air pressure parameters and aerosol droplet size distribution parameters of the atomizer under wear-free conditions, the aerosol droplet size distribution parameters corresponding to the wear-free atomizer are predicted under the current ambient temperature, ambient humidity, and ambient air pressure parameters. By comparing the actual measured aerosol droplet size distribution parameters with the predicted aerosol droplet size distribution parameters, and removing the changes in aerosol droplet size distribution parameters caused by environmental fluctuations, parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer are obtained.

[0017] This technical solution can effectively eliminate the influence of environmental factors on the size distribution of aerosol droplets, making the assessment of physical wear of atomizers more pure and accurate.

[0018] In one embodiment, the rare earth element detection method includes the step of obtaining parameters for the degree of deterioration of aerosol droplet size distribution based on the physical wear degree of the atomizer under current operating conditions, which includes: Simultaneously acquire current sample flow rate, sample pressure, nebulized gas flow rate, and nebulized gas pressure parameters; Based on the correlation between the preset operating parameters and the aerosol droplet size distribution parameters under the wear-free state of the atomizer, the aerosol droplet size distribution parameters corresponding to the wear-free atomizer are predicted under the current sample flow rate, sample pressure, atomizing gas flow rate, and atomizing gas pressure parameters. The measured aerosol droplet size distribution parameters are compared with the predicted aerosol droplet size distribution parameters. The changes in aerosol droplet size distribution parameters caused by fluctuations in sample flow rate, sample pressure, atomizing gas flow rate, and atomizing gas pressure are removed to obtain parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer.

[0019] This technical solution can eliminate the influence of operating parameter fluctuations on aerosol droplet size distribution, thereby more accurately assessing the wear level of the atomizer.

[0020] In another embodiment, the step of obtaining parameters of the deterioration degree of aerosol droplet size distribution based on the physical wear degree of the atomizer under the current operating conditions in the rare earth element detection method includes: Simultaneously acquire the current physicochemical properties of the sample; Based on the baseline correlation between the sample physicochemical properties and aerosol droplet size distribution parameters under the wear-free state of the atomizer, the aerosol droplet size distribution parameters corresponding to the wear-free atomizer are predicted under the current sample physicochemical property parameters. The measured aerosol droplet size distribution parameters are compared with the predicted aerosol droplet size distribution parameters. The changes in aerosol droplet size distribution parameters caused by fluctuations in the physicochemical properties of the sample are removed, and parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer are obtained.

[0021] This technical solution can effectively isolate the influence of changes in the physicochemical properties of the sample on the aerosol droplet size distribution, making the assessment of atomizer wear more accurate.

[0022] To enhance functionality, the rare earth element detection method includes the following steps for obtaining parameters regarding the degree of deterioration in aerosol droplet size distribution based on the physical wear of the atomizer under current operating conditions: Simultaneously acquire the current sample's microbubble content, suspended particle aggregation or dispersion parameters, and characteristic parameters of the microscopic interaction between the sample and the atomizer material; Based on the baseline correlation between the deep physicochemical properties of the sample and the aerosol droplet size distribution parameters under the condition of no wear in the atomizer, the aerosol droplet size distribution parameters corresponding to the no wear atomizer are predicted under the current conditions of trace bubble content, suspended particle aggregation or dispersion parameters, and microscopic interaction between the sample and the atomizer material. The measured aerosol droplet size distribution parameters are compared with the predicted aerosol droplet size distribution parameters. The changes in aerosol droplet size distribution parameters caused by the content of trace bubbles in the sample, the agglomeration or dispersion state parameters of suspended particles, and the fluctuations in characteristic parameters of the micro-interaction between the sample and the atomizer material are removed. The parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer are obtained.

[0023] This technical solution allows for a deeper consideration of the impact of the sample's underlying physicochemical properties on the aerosol droplet size distribution, thereby enabling a more comprehensive and accurate assessment of the physical wear of the atomizer.

[0024] Secondly, this application also discloses a rare earth element detection system for performing rare earth element detection, including: The parameter acquisition and execution module is used to obtain parameters of the degree of degradation of aerosol droplet size distribution based on the physical wear degree of the atomizer under the current operating conditions. The signal suppression determination module is used to determine the amount of signal suppression that each rare earth element to be tested should be subjected to, based on the preset correlation rules between the characteristics of rare earth elements and the degree of signal suppression, as well as the parameters of the degradation degree of aerosol droplet size distribution. The measurement signal correction module is used to calculate and apply the corresponding correction weight factor based on the signal suppression amount to correct the original measurement signal value and obtain the corrected signal value. The element ratio output module is used to calculate the ratio between pre-specified rare earth elements using the calibrated signal value and output the ratio to complete the rare earth element detection.

[0025] This technical solution provides a hardware and software integrated approach to effectively execute rare earth element detection methods, thereby overcoming the distortion problem in rare earth element ratio detection in existing technologies.

[0026] Beneficial Effects: The rare earth element detection method disclosed in this application obtains parameters of the aerosol droplet size distribution degradation degree based on the physical wear degree of the atomizer under current operating conditions. Combining this with the correlation rules between rare earth element characteristics and signal suppression degree, the method determines the signal suppression amount that each tested rare earth element should receive. Based on this, the corresponding correction weighting factor is calculated and applied to correct the original measured signal value. Finally, the corrected signal value is used to calculate and output the ratio between rare earth elements. This method effectively solves the problem of rare earth element ratio detection distortion caused by aerosol droplet size distribution degradation due to micro-erosion of the atomizer nozzle and the inability of automated compensation mechanisms to specifically compensate for the differentiated signal loss of different rare earth elements in existing technologies. Through quantitative evaluation of atomizer wear degree and precise correction of signal suppression amount, this application can eliminate systematic biases of nonlinear and complex correlations, thereby obtaining a more accurate rare earth element ratio, avoiding product quality assessment bias and potential economic losses, and significantly improving the accuracy and reliability of rare earth element detection. Attached Figure Description

[0027] Figure 1 This is a flowchart of a rare earth element detection method according to one embodiment of the present invention; Figure 2 This is a flowchart of a rare earth element detection method according to another embodiment of the present invention; Figure 3 This is a system block diagram of a rare earth element detection system according to another embodiment of the present invention; Explanation of reference numerals in the attached figures: 1. Rare earth element detection system; 11. Parameter acquisition and execution module; 12. Signal suppression determination module; 13. Measurement signal correction module; 14. Element ratio output module. Detailed Implementation

[0028] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0029] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0030] This application proposes a method for detecting rare earth elements, combined with... Figure 1 As shown, it includes: S1, based on the physical wear of the atomizer under the current operating conditions, obtain parameters for the degree of deterioration of the aerosol droplet size distribution; S2. Based on the preset correlation rules between rare earth element characteristics and signal suppression degree, and the parameters of aerosol droplet size distribution degradation degree, determine the amount of signal suppression that each rare earth element to be tested should be subjected to. S3. Based on the signal suppression amount, calculate and apply the corresponding correction weight factor to correct the original measured signal value and obtain the corrected signal value. S4 uses the corrected signal value to calculate the ratio between the pre-specified rare earth elements and outputs the ratio to complete the rare earth element detection.

[0031] The "rare earth element detection method" mentioned in this application is typically used in analytical techniques such as inductively coupled plasma optical emission spectrometry (ICP-OES) or inductively coupled plasma mass spectrometry (ICP-MS). In these techniques, the "nebulizer" is the core component, its function being to convert liquid samples into fine aerosol droplets for subsequent excitation or ionization in the plasma. The "parameter of aerosol droplet size distribution degradation" refers to the degree to which the aerosol droplet size distribution deviates from the ideal state after nebulizer wear, such as an increase in average droplet size or a widening of the droplet size distribution. The "correlation rule between rare earth element characteristics and signal suppression degree" describes the inherent law governing the degree of signal suppression for different rare earth elements under a specific degree of aerosol droplet size distribution degradation; this rule can be established through experimental data. The "signal suppression amount" refers to the amount of signal intensity reduction caused by the degradation of the aerosol droplet size distribution for a specific rare earth element. The "correction weighting factor" is a multiplicative factor used to compensate for the signal suppression amount, adjusting the original measured signal value to the true value.

[0032] Specifically, the rare earth element detection method of this application includes the following steps: First, based on the physical wear of the nebulizer under current operating conditions, parameters of the aerosol droplet size distribution degradation are obtained. This step aims to quantify the impact of nebulizer wear on sample atomization performance. For example, the nebulizer can be visually inspected periodically, and the corresponding aerosol droplet size distribution degradation parameters can be manually input based on observed wear marks, nozzle deformation, and other physical characteristics, combined with empirical judgment or preset wear level standards. Alternatively, before each test, atomization tests can be performed using a standard solution, and the aerosol droplet size distribution can be measured using equipment such as a laser diffractometer. The measurement results are then compared with the baseline size distribution produced by a brand-new nebulizer under the same conditions to calculate the aerosol droplet size distribution degradation parameters.

[0033] Secondly, based on the pre-defined correlation rules between rare earth element characteristics and signal suppression levels, as well as parameters regarding the degradation degree of aerosol droplet size distribution, the signal suppression amount that each tested rare earth element should receive is determined. This step aims to predict the signal loss of different rare earth elements under the current atomizer wear condition. For example, a series of experiments can be conducted beforehand to measure the signal responses of various rare earth elements under different degrees of atomizer wear conditions and record their signal suppression amounts. Then, these data are input into a statistical model to establish correlation rules between rare earth element types, their physicochemical properties (such as atomic weight, ionization energy, etc.), and signal suppression amounts. During actual testing, combined with the currently acquired parameters regarding the degradation degree of aerosol droplet size distribution, the signal suppression amount that each tested rare earth element should receive can be determined by looking up tables or calculating using the model.

[0034] Next, based on the aforementioned signal suppression amount, the corresponding correction weighting factor is calculated and applied to correct the original measured signal value, resulting in the corrected signal value. This step aims to compensate for signal loss caused by atomizer wear and restore the signal's authenticity. For example, a reverse compensation correction weighting factor can be calculated based on the signal suppression amount of each rare earth element to be measured. If the signal suppression amount of a certain rare earth element is 20%, the corresponding correction weighting factor can be set to 1 / (1-0.2) = 1.25. Then, multiplying the original measured signal value by this correction weighting factor yields the corrected signal value.

[0035] Finally, using the calibrated signal values, the pre-specified ratios between rare earth elements are calculated and output to complete the rare earth element detection. This step aims to provide accurate rare earth element ratio information. For example, after obtaining the calibrated signal values ​​of all the rare earth elements to be tested, the ratio between a specific pair of rare earth elements, such as the ratio of rare earth element A to rare earth element B, can be calculated according to a preset formula. These ratio values ​​can be displayed directly on the user interface or stored in a database for subsequent analysis and quality control.

[0036] The rare earth element detection method of this application introduces a quantitative assessment of the physical wear of the atomizer and combines it with the correlation rules between the characteristics of rare earth elements and the degree of signal suppression, thereby achieving accurate prediction and correction of the signal suppression amount of different rare earth elements.

[0037] Optional, combined Figure 2 As shown, S3 calculates and applies the corresponding correction weighting factor based on the signal suppression amount to correct the original measured signal value, obtaining the corrected signal value. The steps include: S31, obtain the adjustment amount of the signal strength made by the automatic compensation mechanism; S32, adjust the original measured signal value in reverse according to the adjustment amount to obtain a signal value that removes the effect of automatic compensation; S33. Based on the signal suppression amount, calculate and apply the corresponding correction weight factor to correct the signal value after removing the effect of automatic compensation, and obtain the corrected signal value.

[0038] Specifically, obtaining the adjustment amount of the signal strength by the automatic compensation mechanism refers to acquiring the gain, attenuation, or other forms of signal strength adjustment information automatically applied by the instrument to maintain signal stability or meet preset standards by reading the instrument's internal control parameters, log records, or real-time monitoring data. For example, analytical instruments such as inductively coupled plasma optical emission spectrometry (ICP-OES) or mass spectrometry (ICP-MS) may have functions such as automatic gain control (AGC) or background subtraction. These functions automatically adjust the detector sensitivity or signal processing parameters according to real-time changes in the signal, thereby generating an adjustment amount. The original measured signal value is then adjusted inversely based on this adjustment amount to obtain a signal value free from the influence of automatic compensation. This can be understood as eliminating the automatic compensation effect contained in the original measured signal value. Specifically, if the automatic compensation mechanism amplifies the signal, the original measured signal value needs to be correspondingly reduced; if it attenuates, it needs to be amplified. The purpose is to obtain a signal value that is closer to the pure rare earth element content of the sample without any internal automatic processing, providing a more accurate benchmark for subsequent signal suppression correction based on nebulizer wear. In practical applications, based on the signal suppression amount, a corresponding correction weighting factor is calculated and applied to correct the signal value after removing the influence of automatic compensation. The corrected signal value is obtained after removing the influence of automatic compensation, and then the corresponding correction weighting factor is calculated based on the previously determined signal suppression amount, which reflects the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer. For example, if the signal suppression amount indicates that the signal is suppressed by 10%, the correction weighting factor might be 1 / (1-0.1) = 1.11. This correction weighting factor is applied to the signal value after removing the influence of automatic compensation to obtain the final corrected signal value that accurately reflects the true content of rare earth elements. The purpose is to ensure that the correction process only targets the signal suppression caused by atomizer wear, avoiding confusion or duplicate correction with the instrument's own automatic compensation mechanism.

[0039] Optionally, the steps for obtaining parameters of the aerosol droplet size distribution degradation degree based on the physical wear degree of the atomizer under current operating conditions include: Obtain the size distribution parameters of matrix-simulated aerosol droplets generated after the matrix-simulated solution is atomized in an atomizer; Based on the matrix simulation parameters of aerosol droplet size distribution, the impact of matrix physical property fluctuations on aerosol droplet size distribution is quantified. From the actual aerosol droplet size distribution parameters obtained from the test sample, the influence of the physical property fluctuations of the strip matrix on the aerosol droplet size distribution is analyzed, and parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer are obtained.

[0040] Specifically, obtaining the matrix-simulated aerosol droplet size distribution parameters generated after the matrix-simulated solution is atomized in an atomizer refers to using a known and stable matrix-simulated solution, such as pure acid solution, deionized water, or a standard blank solution of a specific concentration, and atomizing it under the same atomizer and operating conditions as the test sample. By measuring the size distribution of the aerosol droplets formed after the matrix-simulated solution is atomized, a baseline matrix-simulated aerosol droplet size distribution parameter can be obtained. These parameters may include the average droplet diameter, droplet size distribution width, droplet number density, etc. The aim is to establish an aerosol droplet size distribution benchmark that is only affected by the physical properties of the matrix (under no-wear or known-wear conditions).

[0041] In this context, quantifying the impact of matrix physical property fluctuations on aerosol droplet size distribution, based on matrix-simulated aerosol droplet size distribution parameters, can be understood as establishing a correlation model between matrix physical properties and aerosol droplet size distribution by comparing matrix-simulated aerosol droplet size distribution parameters generated by different matrix-simulated solutions (or under different matrix physical property conditions). For example, a series of experiments can be conducted beforehand using matrix-simulated solutions with different viscosities, surface tensions, or densities to measure their aerosol droplet size distribution, thereby quantifying the specific degree of influence of these matrix physical property fluctuations on droplet size distribution. The aim is to accurately identify and evaluate the contribution of non-abrasive factors (i.e., matrix effects) to aerosol droplet size distribution.

[0042] In practical applications, to isolate the influence of matrix physical property fluctuations on aerosol droplet size distribution from the actual aerosol droplet size distribution parameters obtained from the test sample, and to obtain parameters reflecting the degree of aerosol droplet size distribution degradation caused by atomizer physical wear, the following steps are taken: First, the actual aerosol droplet size distribution parameters generated after atomization of the test sample under the current operating conditions are measured. Then, using the previously quantified model of the influence of matrix physical property fluctuations on aerosol droplet size distribution, the size distribution changes caused by the sample matrix physical property fluctuations are subtracted or corrected from the actual measured parameters. For example, the matrix effect can be separated from the total size distribution change through mathematical models, regression analysis, or difference calculations. Thus, the remaining size distribution change is considered a parameter mainly caused by the physical wear of the atomizer, reflecting the degree of degradation. The purpose is to ensure that the obtained degradation parameters accurately reflect the wear state of the atomizer itself, rather than other interfering factors.

[0043] In some preferred embodiments, this application is implemented as follows: Assuming that in the rare earth element detection process, inductively coupled plasma optical emission spectrometry (ICP-OES) is used for analysis, the nebulizer is a key component. To accurately assess nebulizer wear, firstly, pure nitric acid solution (as a matrix simulation solution) is used for nebulization under standard operating conditions, and the aerosol droplet size distribution is measured using a laser diffractometer to obtain matrix-simulated aerosol droplet size distribution parameters, for example, an average droplet diameter of 5 micrometers and a distribution width of 1 micrometer. Next, using pre-established experimental data, the effect of different concentrations of nitric acid solution (representing fluctuations in matrix physical properties) on the droplet size distribution is quantified. For example, it is found that for every 0.1% increase in nitric acid concentration, the average droplet diameter decreases by 0.1 micrometers. When the sample to be tested (e.g., ore digest) is introduced into the nebulizer, its matrix may contain a high concentration of acid, causing the actually measured droplet size distribution parameters (e.g., an average droplet diameter of 4.5 micrometers) to include the dual effects of matrix effects and nebulizer wear. At this point, based on the actual matrix concentration of the sample, the droplet size change caused by the matrix effect is calculated using a quantification model (e.g., the matrix effect causes a decrease in the average droplet diameter of 0.2 micrometers). Finally, the actual measured value (4.5 micrometers) is subtracted from the matrix effect (0.2 micrometers) to obtain the droplet size after removing the matrix effect, which is 4.7 micrometers. By comparing this with the reference droplet size of a wear-free atomizer (e.g., 5 micrometers), a droplet size degradation of 0.3 micrometers can be obtained. This degradation parameter is considered to reflect the degree of degradation in aerosol droplet size distribution caused by physical wear of the atomizer.

[0044] Optionally, the step of determining the amount of signal suppression that each rare earth element should be subjected to, based on a preset correlation rule between rare earth element characteristics and signal suppression level, and a parameter of the degree of degradation in aerosol droplet size distribution, includes: A set of calibration samples with known rare earth element content and different matrix properties are introduced according to a preset cycle; Measure the signal response of each rare earth element in the calibration sample; Based on the signal response and the known rare earth element content of the calibration sample, record the actual signal suppression amount of each rare earth element under the current atomizer degradation level; Based on the pre-defined correlation rules between rare earth element characteristics and signal suppression degree, the predicted signal suppression amount is estimated. The actual signal suppression amount is compared with the predicted signal suppression amount to calculate the degree of deviation of the association rule; Based on the degree of deviation, adjust the weight coefficients in the preset association rule between rare earth element characteristics and signal suppression degree to optimize the association rule; Using the adjusted association rules, combined with parameters on the degree of degradation of aerosol droplet size distribution, the amount of signal suppression that each rare earth element to be measured should receive is determined.

[0045] Specifically, introducing calibration samples refers to introducing a set of standard samples with known rare earth element concentrations and different matrix properties into the detection system at preset time intervals or under specific conditions during the detection process. These calibration samples are designed to simulate the complexity of actual test samples, thereby more realistically reflecting the system's performance under current operating conditions. The purpose is to provide reliable reference data for evaluating and adjusting correlation rules.

[0046] The measurement of the signal response of each rare earth element in the calibration sample refers to analyzing the introduced calibration sample using detection equipment to obtain the original signal intensity of each rare earth element under the current system state. These signal responses form the basis for subsequent calculations of the actual signal suppression.

[0047] In practical applications, based on the signal response and the known rare earth element content of the calibration sample, the actual signal suppression of each rare earth element under the current atomizer degradation level is recorded. The actual signal suppression can be understood as the degree of signal intensity attenuation under current operating conditions due to factors such as atomizer wear, relative to the ideal state. This step aims to quantify the actual impact of the current system on the signals of different rare earth elements.

[0048] Furthermore, based on the pre-defined correlation rules between rare earth element characteristics and signal suppression levels, the predicted signal suppression amount is estimated. The predicted signal suppression amount is a theoretical prediction of the signal suppression level based on existing models or empirical formulas, combined with parameters of the inherent characteristics of rare earth elements (such as atomic weight, ionization energy, etc.) and the current degree of degradation of aerosol droplet size distribution.

[0049] Subsequently, the actual signal suppression amount is compared with the predicted signal suppression amount to calculate the deviation of the association rule. The deviation reflects the accuracy of the preset association rule under the current actual operating conditions, that is, the difference between theoretical prediction and actual observation.

[0050] Based on this, the weight coefficients in the pre-defined association rule between rare earth element characteristics and signal suppression degree are adjusted according to the degree of deviation, in order to optimize the association rule. The adjustment of the weight coefficients can employ various algorithms, such as least squares, iterative optimization algorithms, or machine learning methods, with the aim of enabling the association rule to better fit the actual signal suppression situation, thereby improving its prediction accuracy.

[0051] Finally, using the adjusted correlation rules and parameters related to the degradation of aerosol droplet size distribution, the signal suppression amount that each rare earth element should receive was determined. This dynamic adjustment mechanism ensures that the determination of the signal suppression amount can be more accurate and reliable under different operating conditions.

[0052] In some preferred embodiments, it is assumed that during a rare earth element detection process, the initially preset association rule predicts a lower signal suppression level for light rare earth elements (such as La and Ce) and a higher prediction level for heavy rare earth elements (such as Gd and Lu) under a specific atomizer wear condition. To address this issue, a set of calibration samples with known La, Ce, Gd, and Lu contents and different matrix characteristics are introduced at preset intervals. By measuring the signal response of each rare earth element in these calibration samples and combining it with their known contents, the actual signal suppression levels of La, Ce, Gd, and Lu under the current atomizer wear level can be calculated. For example, the actual measured signal suppression level of La is 15%, while the predicted value is 10%; the actual suppression level of Gd is 25%, while the predicted value is 30%. By comparing the actual and predicted values, the deviation of the association rule is calculated. Based on these deviations, the system automatically adjusts the weight coefficients related to light and heavy rare earth elements in the association rule. For example, the weight of light rare earth element signal suppression is increased, while the weight of heavy rare earth element signal suppression is decreased. The adjusted association rule will more accurately reflect the signal suppression under the current operating conditions. Subsequently, when analyzing the actual sample to be tested, this optimized association rule will be used, combined with the parameter of the degree of degradation of aerosol droplet size distribution, to determine the amount of signal suppression that each rare earth element to be tested should receive, thereby ensuring the accuracy of subsequent signal correction and ultimately obtaining more reliable rare earth element ratio detection results.

[0053] Optionally, the steps for obtaining parameters of the aerosol droplet size distribution degradation degree based on the physical wear degree of the atomizer under current operating conditions include: A solution containing tracer particles of at least two different size ranges is introduced according to a preset cycle; Measure the size distribution parameters of aerosol droplets formed after the tracer particle solution is atomized; Calculate the ratio of size distribution parameters to obtain the tracer particle ratio; Obtain the preset correlation rules between wear patterns and tracer particle ratios; By matching the tracer particle ratio with the mode selection association rule, the wear mode of the current atomizer can be identified; Based on the identified wear patterns, parameters for the degree of degradation of the corresponding aerosol droplet size distribution are obtained.

[0054] Specifically, introducing a tracer particle solution containing at least two different size ranges involves selecting inert particles with well-defined and distinguishable sizes, dissolving or dispersing them in a suitable solvent to form a solution used to characterize the atomizer's performance. The size range of these tracer particles can be preset based on the atomizer's expected wear characteristics and the variation range of aerosol droplet size distribution. For example, solutions of polystyrene microspheres with diameters of 1 micrometer and 5 micrometers can be used. The aim is to indirectly reflect the atomizer's ability to form and distribute droplets of different sizes by observing the behavior of the tracer particles during the atomization process.

[0055] Measuring the size distribution parameters of the aerosol droplets formed after atomization of the tracer particle solution can be understood as using techniques such as laser diffraction, dynamic light scattering, or aerosol particle size analyzers to perform real-time or near-real-time measurements on the aerosol droplets generated by the atomizer, in order to obtain statistical parameters such as particle size distribution, median particle size, and standard deviation. The purpose is to quantify the atomization effect of the atomizer on the tracer particle solution under the current wear condition.

[0056] In practical applications, calculating the ratio of size distribution parameters to obtain the tracer particle ratio involves selecting two or more key size distribution parameters (e.g., the peak intensity ratio of tracer particles in different size ranges, the particle number ratio within a specific particle size range, or the average particle size ratio) and obtaining a dimensionless ratio or a ratio with specific physical meaning through mathematical operations. For example, the ratio of the median particle size of aerosol droplets formed by two different sizes of tracer particles can be calculated, or the ratio of the particle volume percentage within a specific particle size range can be calculated. The purpose is to simplify complex size distribution information into one or a few representative values, facilitating subsequent pattern recognition.

[0057] Furthermore, obtaining the pre-defined correlation rules between wear patterns and tracer particle ratios refers to establishing a mapping relationship between different types of physical wear patterns of the atomizer (e.g., nozzle clogging, orifice enlargement, increased surface roughness, etc.) and tracer particle ratios through the accumulation and analysis of a large amount of experimental data in the early stages. These correlation rules can be expressed in the form of lookup tables, decision tree models, regression models, or neural network models. Their purpose is to provide a basis for subsequent identification of atomizer wear patterns.

[0058] Therefore, matching the tracer particle ratio with the mode selection association rules to identify the current atomizer's wear mode involves inputting the real-time measured tracer particle ratio into preset association rules, and using an algorithm to determine which known wear mode the current atomizer best fits. For example, if the tracer particle ratio falls within a specific range, it is identified as the "nozzle clogging" mode. The aim is to correlate abstract changes in size distribution with specific physical wear phenomena.

[0059] Finally, based on the identified wear patterns, parameters indicating the degree of aerosol droplet size distribution degradation are obtained. This means that once a specific wear pattern is determined, the system can retrieve parameters indicating the degree of aerosol droplet size distribution degradation under that wear pattern from a pre-stored database. These parameters can be degradation factors, calibration curves, or specific mathematical model parameters. The purpose is to provide accurate input for subsequent signal suppression determination and correction.

[0060] Optionally, the steps for obtaining parameters of the aerosol droplet size distribution degradation degree based on the physical wear degree of the atomizer under current operating conditions include: Simultaneously acquire current ambient temperature, humidity, and air pressure parameters; Based on the baseline correlation established under controlled experimental conditions between the ambient temperature, ambient humidity, ambient air pressure parameters and aerosol droplet size distribution parameters of the atomizer under wear-free conditions, the aerosol droplet size distribution parameters corresponding to the wear-free atomizer are predicted under the current ambient temperature, ambient humidity, and ambient air pressure parameters. By comparing the actual measured aerosol droplet size distribution parameters with the predicted aerosol droplet size distribution parameters, and removing the changes in aerosol droplet size distribution parameters caused by environmental fluctuations, parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer are obtained.

[0061] The phrase "synchronously acquiring current ambient temperature, humidity, and air pressure parameters" refers to collecting temperature, humidity, and air pressure data in the detection environment in real time or near real time during rare earth element detection. These parameters can be obtained through environmental sensors integrated into the detection system or external environmental monitoring equipment, with the aim of providing a real-time data foundation for subsequent environmental impact assessments.

[0062] "Based on the baseline correlation established under controlled experimental conditions between ambient temperature, humidity, and pressure parameters and aerosol droplet size distribution parameters of an atomizer in a wear-free state, the aerosol droplet size distribution parameters corresponding to a wear-free atomizer under current ambient temperature, humidity, and pressure parameters are predicted." This refers to systematically changing the ambient temperature, humidity, and pressure through a series of controlled experiments when the atomizer is in a brand-new or known wear-free state, and measuring the corresponding aerosol droplet size distribution parameters. A baseline correlation model is then established, which describes how environmental factors affect the aerosol droplet size distribution under ideal wear-free conditions. In actual testing, using the currently acquired environmental parameters and this baseline correlation, the ideal state of the atomizer's aerosol droplet size distribution under current environmental conditions, assuming no wear, can be predicted.

[0063] "Comparing the actually measured aerosol droplet size distribution parameters with the predicted aerosol droplet size distribution parameters, and removing the changes in aerosol droplet size distribution parameters caused by environmental fluctuations, to obtain parameters reflecting the degree of aerosol droplet size distribution degradation caused by atomizer physical wear" refers to comparing the aerosol droplet size distribution parameters obtained through measurement under actual operating conditions, which may be affected by both environmental factors and atomizer wear, with the predicted aerosol droplet size distribution parameters of a wear-free atomizer, which are only affected by environmental factors. Through this comparison, the influence of environmental factors on aerosol droplet size distribution can be quantified and isolated, thereby more accurately separating the degree of aerosol droplet size distribution degradation caused by the atomizer's physical wear itself.

[0064] Optionally, the steps for obtaining parameters of the aerosol droplet size distribution degradation degree based on the physical wear degree of the atomizer under current operating conditions include: Simultaneously acquire current sample flow rate, sample pressure, nebulized gas flow rate, and nebulized gas pressure parameters; Based on the correlation between the preset operating parameters and the aerosol droplet size distribution parameters under the wear-free state of the atomizer, the aerosol droplet size distribution parameters corresponding to the wear-free atomizer are predicted under the current sample flow rate, sample pressure, atomizing gas flow rate, and atomizing gas pressure parameters. The measured aerosol droplet size distribution parameters are compared with the predicted aerosol droplet size distribution parameters. The changes in aerosol droplet size distribution parameters caused by fluctuations in sample flow rate, sample pressure, atomizing gas flow rate, and atomizing gas pressure are removed to obtain parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer.

[0065] Specifically, synchronously acquiring the current sample flow rate, sample pressure, nebulized gas flow rate, and nebulized gas pressure parameters refers to monitoring and recording these parameters in real time during rare earth element detection.

[0066] Optionally, the steps for obtaining parameters of the aerosol droplet size distribution degradation degree based on the physical wear degree of the atomizer under current operating conditions include: Simultaneously acquire the current physicochemical properties of the sample; Based on the baseline correlation between the sample physicochemical properties and aerosol droplet size distribution parameters under the wear-free state of the atomizer, the aerosol droplet size distribution parameters corresponding to the wear-free atomizer are predicted under the current sample physicochemical property parameters. The measured aerosol droplet size distribution parameters are compared with the predicted aerosol droplet size distribution parameters. The changes in aerosol droplet size distribution parameters caused by fluctuations in the physicochemical properties of the sample are removed, and parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer are obtained.

[0067] Specifically, "sample physicochemical properties" can be understood as the physicochemical attributes that affect the sample atomization process and aerosol droplet formation characteristics, such as, but not limited to, the sample's viscosity, surface tension, density, pH value, and conductivity. These parameters can be directly monitored in real time by online sensors or obtained through offline analysis. The "benchmark correlation" refers to a model established through numerous experiments, under conditions where the atomizer is brand new or known to be wear-free, that establishes the correspondence between the sample's physicochemical properties and the resulting aerosol droplet size distribution parameters. This model can be a mathematical function, a lookup table, or a machine learning model, and its purpose is to accurately predict the aerosol droplet size distribution that an ideal, wear-free atomizer should produce under given sample physicochemical properties. In practical applications, by inputting the currently measured sample physicochemical properties into this benchmark correlation model, the aerosol droplet size distribution parameters that the wear-free atomizer should produce under the current operating conditions can be "predicted." Subsequently, the actual measured aerosol droplet size distribution parameters were compared with the predicted values. The difference was considered to be the deterioration of the aerosol droplet size distribution caused by physical wear of the atomizer after excluding the influence of the physicochemical properties of the sample.

[0068] In some preferred embodiments, it is assumed that the sample to be tested during rare earth element detection is an industrial wastewater containing a high concentration of salt, whose conductivity and viscosity may be significantly higher than those of conventional standard solutions. First, the physicochemical properties of the wastewater sample are simultaneously acquired via an online sensor, for example, its conductivity is measured to be 1500 μS / cm and its viscosity to be 1.5 cP. The system then invokes a pre-established benchmark correlation model, which was built by testing a series of standard solutions with different conductivity and viscosity under a non-wearing atomizer condition. Based on the current physicochemical properties of the wastewater (conductivity 1500 μS / cm, viscosity 1.5 cP), the model predicts that if the atomizer is in a non-wearing condition, the aerosol droplet size distribution parameters it should produce are: an average droplet diameter of 6.0 μm and a droplet size distribution width of 2.0 μm. Simultaneously, the actual measurement system atomized the wastewater sample and obtained the actual aerosol droplet size distribution parameters, such as an average droplet diameter of 6.8 μm and a droplet size distribution width of 2.3 μm. The actual measured values ​​(6.8 μm, 2.3 μm) were compared with the predicted values ​​(6.0 μm, 2.0 μm). The differences between the two were calculated; for example, the average droplet diameter increased by 0.8 μm, and the droplet size distribution width increased by 0.3 μm. These differences were considered to be due to droplet size distribution degradation caused by physical wear of the atomizer, rather than by the high salinity and viscosity of the sample. Therefore, parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer can be obtained, which can be used for subsequent signal suppression determination and correction.

[0069] Optionally, the steps for obtaining parameters of the aerosol droplet size distribution degradation degree based on the physical wear degree of the atomizer under current operating conditions include: Simultaneously acquire the current sample's microbubble content, suspended particle aggregation or dispersion parameters, and characteristic parameters of the microscopic interaction between the sample and the atomizer material; Based on the baseline correlation between the deep physicochemical properties of the sample and the aerosol droplet size distribution parameters under the condition of no wear in the atomizer, the aerosol droplet size distribution parameters corresponding to the no wear atomizer are predicted under the current conditions of trace bubble content, suspended particle aggregation or dispersion parameters, and microscopic interaction between the sample and the atomizer material. The measured aerosol droplet size distribution parameters are compared with the predicted aerosol droplet size distribution parameters. The changes in aerosol droplet size distribution parameters caused by the content of trace bubbles in the sample, the agglomeration or dispersion state parameters of suspended particles, and the fluctuations in characteristic parameters of the micro-interaction between the sample and the atomizer material are removed. The parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer are obtained.

[0070] Specifically, simultaneously acquiring the current sample's microbubble content, suspended particle aggregation or dispersion parameters, and characteristic parameters of the microscopic interaction between the sample and the atomizer material refers to obtaining these deep-level physicochemical information within the sample in real-time or near real-time using specialized sensors or analytical techniques while performing rare earth element detection. Microbubble content can be understood as the number or volume percentage of tiny bubbles dissolved or entrained in the sample solution, which may affect the droplet breakup and formation process. Suspended particle aggregation or dispersion parameters refer to the degree of aggregation or dispersion of solid particles in the solution, which directly affects the uniformity and size distribution of aerosol droplets. Characteristic parameters of the microscopic interaction between the sample and the atomizer material may include wettability, surface tension, adsorption / desorption behavior, etc., which affect the sample's flow behavior and droplet formation efficiency within the atomizer.

[0071] Furthermore, based on the baseline correlation between the sample's deep physicochemical properties and aerosol droplet size distribution parameters under a wear-free atomizer condition, the aerosol droplet size distribution parameters corresponding to the wear-free atomizer are predicted under the current sample's microbubble content, suspended particle aggregation or dispersion parameters, and microscopic interaction characteristics. This requires systematically studying the aerosol droplet size distribution parameters generated after atomization of samples with different microbubble contents, suspended particle aggregation or dispersion states, and microscopic interaction characteristics through a series of controlled experiments, when the atomizer is in a brand-new or known wear-free condition. This establishes a multi-dimensional baseline correlation model that can accurately predict the aerosol droplet size distribution under ideal wear-free atomizer conditions based on the input sample's deep physicochemical properties.

[0072] Subsequently, the actual measured aerosol droplet size distribution parameters were compared with the predicted aerosol droplet size distribution parameters. The actual measured aerosol droplet size distribution parameters reflect the comprehensive results under the current operating conditions (including the effects of atomizer wear and the deep-seated properties of the sample). By comparing the actual measured values ​​with ideal values ​​predicted based on a wear-free atomizer and the current deep-seated properties of the sample, the changes in aerosol droplet size distribution parameters caused by fluctuations in characteristic parameters such as the content of trace bubbles in the sample, the agglomeration or dispersion state parameters of suspended particles, and the microscopic interactions between the sample and the atomizer materials can be accurately removed. Finally, the residual change or difference obtained can more accurately reflect the degree of aerosol droplet size distribution degradation caused purely by the physical wear of the atomizer.

[0073] In some preferred embodiments, this application is implemented as follows: First, during the rare earth element detection process, a laser scattering particle size analyzer is used to simultaneously measure the real-time size distribution of aerosol droplets formed after sample atomization, obtaining actual aerosol droplet size distribution parameters. Simultaneously, using devices such as conductivity sensors, surface tension meters, and microfluidic imaging systems, the microbubble content of the sample solution, the aggregation or dispersion state parameters of suspended particles (e.g., by measuring the peak value, width, or aggregation index of the particle size distribution), and characteristic parameters of the microscopic interaction between the sample and the atomizer material (such as quartz or polymer) are simultaneously acquired.

[0074] Secondly, with the atomizer in a brand-new, wear-free state, a series of simulated samples with different microbubble contents, suspended particle aggregation or dispersion states, and different wettability characteristics were pre-prepared. These simulated samples were atomized, and their aerosol droplet size distribution parameters were measured. Based on these experimental data, a benchmark correlation model was established using machine learning algorithms (e.g., support vector machines or neural networks). This model can predict the aerosol droplet size distribution parameters that should exist under wear-free atomizer conditions, based on the input sample's deep physicochemical properties.

[0075] Finally, during the actual testing of the sample, the real-time acquired parameters of the sample's deep physicochemical properties are input into the aforementioned benchmark correlation model to predict the aerosol droplet size distribution parameters that the wear-free atomizer should produce under the current sample conditions. Subsequently, the actually measured aerosol droplet size distribution parameters are compared point-by-point or statistically with this predicted value. For example, the change in aerosol droplet size distribution caused by fluctuations in the sample's deep properties can be quantified by calculating the root mean square error or the deviation within a specific size range. Subtracting the actual measured value or removing this fluctuation component using other mathematical methods yields a parameter reflecting the degree of aerosol droplet size distribution degradation purely due to the physical wear of the atomizer. This parameter is then used to correct the rare earth element signal to ensure the accuracy of the detection results.

[0076] This application also discloses a rare earth element detection system for performing rare earth element detection, combined with... Figure 3 As shown, the rare earth element detection system 1 includes: The parameter acquisition and execution module 11 is used to acquire parameters of the deterioration degree of aerosol droplet size distribution based on the physical wear degree of the atomizer under the current operating conditions. The signal suppression determination module 12 is used to determine the amount of signal suppression that each rare earth element to be tested should be subjected to based on the preset correlation rules between the characteristics of rare earth elements and the degree of signal suppression, as well as the parameters of the degradation degree of aerosol droplet size distribution. The measurement signal correction module 13 is used to calculate and apply the corresponding correction weight factor according to the signal suppression amount to correct the original measurement signal value and obtain the corrected signal value. The element ratio output module 14 is used to calculate the ratio between pre-specified rare earth elements using the calibrated signal value and output the ratio to complete the rare earth element detection.

[0077] This rare earth element detection system aims to address the problems in traditional rare earth element detection, such as the deterioration of aerosol droplet size distribution due to physical wear of the atomizer, the differential suppression of signals for different rare earth elements, and the inadequacy of existing automated compensation mechanisms. By modularizing the detection process, this system can systematically assess the wear condition of the atomizer, accurately predict and correct the signal suppression of each rare earth element, thereby ensuring the accuracy and reliability of rare earth element ratio detection. The various modules work collaboratively to form a complete closed-loop detection and correction mechanism, effectively improving the accuracy of rare earth element detection in complex industrial samples and avoiding product quality assessment deviations caused by ratio distortion.

[0078] The specific steps of the rare earth element detection method have been described in the above embodiments and will not be repeated here. It should be emphasized that the rare earth element detection system of this application, through its modular design, specifically implements the above method steps as operable system components.

[0079] Specifically, the parameter acquisition and execution module is configured to acquire parameters indicating the degree of aerosol droplet size distribution degradation based on the physical wear of the atomizer under current operating conditions. This module can be a hardware component integrating a sensor interface and a data processing unit; for example, it can be connected to a laser diffractometer to acquire aerosol droplet size distribution data in real time and has a built-in algorithm to calculate the degradation degree parameter. Alternatively, this module can be a software module that receives image data from external detection equipment (such as an optical imaging system) and uses image processing algorithms to analyze the wear condition of the atomizer nozzle, thereby inferring the degree of aerosol droplet size distribution degradation.

[0080] The signal suppression determination module is configured to determine the amount of signal suppression each analyte should receive based on preset correlation rules between rare earth element characteristics and signal suppression levels, as well as parameters related to the degradation degree of aerosol droplet size distribution. This module can include a database storing a large amount of experimental data and correlation rules, and is equipped with an inference engine that determines the signal suppression amount through table lookup or rule-based logical operations based on the input degradation degree parameters and the characteristics of the analyte. Furthermore, this module can also employ a machine learning model, trained on historical data, to learn the complex nonlinear relationship between rare earth element characteristics, atomizer degradation degree, and signal suppression amount, thereby achieving more accurate suppression amount prediction.

[0081] The measurement signal correction module is configured to calculate and apply a corresponding correction weight factor based on the signal suppression amount to correct the original measurement signal value, obtaining the corrected signal value. This module can be a digital signal processor (DSP) that receives the original measurement signal value from a spectrometer or mass spectrometer, determines the suppression amount provided by the module based on the signal suppression, and calculates and applies the correction weight factor in real time. For example, the module can have a built-in floating-point unit to perform multiplication operations, multiplying the original signal value by the correction weight factor. Alternatively, the module can be a software program running on a general-purpose processor, responsible for reading the original signal from the data acquisition card, executing the correction algorithm, and writing the corrected data to memory or sending it to a subsequent processing unit.

[0082] The element ratio output module is configured to use calibrated signal values ​​to calculate and output the ratios between pre-specified rare earth elements, thus completing the rare earth element detection. This module can be a user interface (UI) component responsible for processing the calibrated signal values, calculating the required rare earth element ratios, and presenting the results to the user or transmitting them to other systems via a display, printer, or network interface. For example, the module can include a graphical user interface that allows the user to select the rare earth element pairs for which ratios need to be calculated and displays the calculation results in real-time in chart or numerical form. Furthermore, the module can also have data storage capabilities, storing the detected rare earth element ratio data in a local or cloud database for historical tracking and trend analysis.

[0083] The rare earth element detection system of this application effectively overcomes the challenges faced by existing technologies in rare earth element detection through its unique modular design and collaborative working mechanism. Traditional detection systems often lack the ability to provide real-time, quantitative assessment of the physical wear state of the atomizer, and are also unable to accurately compensate for the differential signal suppression caused by wear of different rare earth elements. The automatic compensation mechanism of existing instruments is usually based on adjusting the overall signal strength, which not only fails to solve the signal distortion problem of specific elements, but may also exacerbate the deviation in the proportion between rare earth elements.

[0084] In contrast, the system in this application precisely quantifies the degree of aerosol droplet size distribution degradation caused by atomizer wear through a parameter acquisition and execution module, and provides customized signal suppression predictions for each analyte rare earth element through a signal suppression determination module that incorporates the characteristics of rare earth elements. Subsequently, the measurement signal correction module applies these precise suppression values ​​for correction, ensuring the authenticity of the original measurement signal. Finally, the element ratio output module calculates and outputs the accurate rare earth element ratio based on the corrected signal value. Therefore, this system provides an integrated and intelligent solution that significantly improves the accuracy and reliability of rare earth element detection. Especially in industrial applications where the requirements for rare earth element ratios are extremely high, it can effectively avoid product quality problems and economic losses caused by detection errors, thus demonstrating significant technological advancement.

[0085] The above are merely embodiments of this application and are not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for detecting rare earth elements, characterized in that, include: Based on the physical wear of the atomizer under current operating conditions, parameters are obtained to determine the degree of degradation in aerosol droplet size distribution. Based on the pre-defined correlation rules between rare earth element characteristics and signal suppression degree, as well as the parameter of aerosol droplet size distribution degradation degree, the signal suppression amount that each rare earth element to be tested should be determined. Based on the signal suppression amount, the corresponding correction weighting factor is calculated and applied to correct the original measured signal value, thereby obtaining the corrected signal value. Using the corrected signal value, the ratio between the pre-specified rare earth elements is calculated and the ratio is output to complete the rare earth element detection.

2. The method for detecting rare earth elements according to claim 1, characterized in that, The step of calculating and applying a corresponding correction weighting factor based on the signal suppression amount to correct the original measured signal value and obtain the corrected signal value includes: Obtain the adjustment amount of the signal strength made by the automatic compensation mechanism; The original measured signal value is adjusted in reverse according to the adjustment amount to obtain a signal value that has removed the effect of automatic compensation. Based on the signal suppression amount, the corresponding correction weight factor is calculated and applied to correct the signal value after removing the influence of automatic compensation, thus obtaining the corrected signal value.

3. The method for detecting rare earth elements according to claim 1, characterized in that, The step of obtaining parameters for the degree of deterioration of aerosol droplet size distribution based on the physical wear of the atomizer under current operating conditions includes: Obtain the size distribution parameters of matrix-simulated aerosol droplets generated after the matrix-simulated solution is atomized in an atomizer; Based on the matrix simulated aerosol droplet size distribution parameters, the influence of matrix physical property fluctuations on aerosol droplet size distribution is quantified. From the actual aerosol droplet size distribution parameters obtained from the test sample, the influence of the physical property fluctuations of the strip matrix on the aerosol droplet size distribution is analyzed, and parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer are obtained.

4. The method for detecting rare earth elements according to claim 1, characterized in that, The step of determining the amount of signal suppression that each rare earth element should receive based on the preset correlation rules between rare earth element characteristics and signal suppression degree, and the parameter of aerosol droplet size distribution degradation degree, includes: A set of calibration samples with known rare earth element content and different matrix properties are introduced according to a preset cycle; Measure the signal response of each rare earth element in the calibration sample; Based on the signal response and the known rare earth element content of the calibration sample, record the actual signal suppression amount of each rare earth element under the current atomizer degradation level; Based on the pre-defined correlation rules between rare earth element characteristics and signal suppression degree, the predicted signal suppression amount is estimated. The actual signal suppression amount is compared with the predicted signal suppression amount to calculate the degree of deviation of the association rule; Based on the degree of deviation, the weight coefficients in the preset association rule between rare earth element characteristics and signal suppression degree are adjusted to optimize the association rule; Using the adjusted association rules, combined with parameters on the degree of degradation of aerosol droplet size distribution, the amount of signal suppression that each rare earth element to be measured should receive is determined.

5. The method for detecting rare earth elements according to claim 1, characterized in that, The step of obtaining parameters for the degree of deterioration of aerosol droplet size distribution based on the physical wear of the atomizer under current operating conditions includes: A solution containing tracer particles of at least two different size ranges is introduced according to a preset cycle; Measure the size distribution parameters of the aerosol droplets formed after the tracer particle solution is atomized; Calculate the ratio of the size distribution parameters to obtain the tracer particle ratio; Obtain the preset correlation rules between wear patterns and tracer particle ratios; The wear mode of the current atomizer is identified by matching the tracer particle ratio with the mode selection association rule. Based on the identified wear patterns, parameters for the degree of degradation of the corresponding aerosol droplet size distribution are obtained.

6. The method for detecting rare earth elements according to claim 1, characterized in that, The step of obtaining parameters for the degree of deterioration of aerosol droplet size distribution based on the physical wear of the atomizer under current operating conditions includes: Simultaneously acquire current ambient temperature, humidity, and air pressure parameters; Based on the baseline correlation established under controlled experimental conditions between the ambient temperature, ambient humidity, ambient air pressure parameters and aerosol droplet size distribution parameters of the atomizer under wear-free conditions, the aerosol droplet size distribution parameters corresponding to the wear-free atomizer are predicted under the current ambient temperature, ambient humidity, and ambient air pressure parameters. By comparing the actual measured aerosol droplet size distribution parameters with the predicted aerosol droplet size distribution parameters, and removing the changes in aerosol droplet size distribution parameters caused by environmental fluctuations, parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer are obtained.

7. The method for detecting rare earth elements according to claim 1, characterized in that, The step of obtaining parameters for the degree of deterioration of aerosol droplet size distribution based on the physical wear of the atomizer under current operating conditions includes: Simultaneously acquire current sample flow rate, sample pressure, nebulized gas flow rate, and nebulized gas pressure parameters; Based on the correlation between the preset operating parameters and the aerosol droplet size distribution parameters under the wear-free state of the atomizer, the aerosol droplet size distribution parameters corresponding to the wear-free atomizer are predicted under the current sample flow rate, sample pressure, atomizing gas flow rate, and atomizing gas pressure parameters. The measured aerosol droplet size distribution parameters are compared with the predicted aerosol droplet size distribution parameters. The changes in aerosol droplet size distribution parameters caused by fluctuations in sample flow rate, sample pressure, atomizing gas flow rate, and atomizing gas pressure are removed to obtain parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer.

8. The method for detecting rare earth elements according to claim 1, characterized in that, The step of obtaining parameters for the degree of deterioration of aerosol droplet size distribution based on the physical wear of the atomizer under current operating conditions includes: Simultaneously acquire the current physicochemical properties of the sample; Based on the baseline correlation between the sample physicochemical properties and aerosol droplet size distribution parameters under the wear-free state of the atomizer, the aerosol droplet size distribution parameters corresponding to the wear-free atomizer are predicted under the current sample physicochemical property parameters. The measured aerosol droplet size distribution parameters are compared with the predicted aerosol droplet size distribution parameters. The changes in aerosol droplet size distribution parameters caused by fluctuations in the physicochemical properties of the sample are removed, and parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer are obtained.

9. The method for detecting rare earth elements according to claim 1, characterized in that, The step of obtaining parameters for the degree of deterioration of aerosol droplet size distribution based on the physical wear of the atomizer under current operating conditions includes: Simultaneously acquire the current sample's microbubble content, suspended particle aggregation or dispersion parameters, and characteristic parameters of the microscopic interaction between the sample and the atomizer material; Based on the baseline correlation between the deep physicochemical properties of the sample and the aerosol droplet size distribution parameters under the condition of no wear in the atomizer, the aerosol droplet size distribution parameters corresponding to the no wear atomizer are predicted under the current conditions of trace bubble content, suspended particle aggregation or dispersion parameters, and microscopic interaction between the sample and the atomizer material. The measured aerosol droplet size distribution parameters are compared with the predicted aerosol droplet size distribution parameters. The changes in aerosol droplet size distribution parameters caused by the content of trace bubbles in the sample, the agglomeration or dispersion state parameters of suspended particles, and the fluctuations in characteristic parameters of the micro-interaction between the sample and the atomizer material are removed. The parameters reflecting the degree of aerosol droplet size distribution degradation caused by physical wear of the atomizer are obtained.

10. A rare earth element detection system for performing rare earth element detection, characterized in that, include: The parameter acquisition and execution module is used to obtain parameters of the degree of degradation of aerosol droplet size distribution based on the physical wear degree of the atomizer under the current operating conditions. The signal suppression determination module is used to determine the amount of signal suppression that each rare earth element to be tested should be subjected to, based on the preset correlation rules between the characteristics of rare earth elements and the degree of signal suppression, as well as the parameters of the degradation degree of aerosol droplet size distribution. The measurement signal correction module is used to calculate and apply the corresponding correction weight factor based on the signal suppression amount to correct the original measurement signal value and obtain the corrected signal value. The element ratio output module is used to calculate the ratio between pre-specified rare earth elements using the corrected signal value, and output the ratio to complete the rare earth element detection.

Images