Quality control method for chemical component analysis of SCR (selective catalytic reduction) denitration catalyst

Abstract

The invention relates to the technical field of quality control, in particular to an SCR (Selective Catalytic Reduction) denitration catalyst chemical component analysis quality control method which comprises the following steps: acquiring a plurality of chemical component parameters of a target sample; calculating a first evaluation index and a second evaluation index of the target sample according to the chemical component parameters, and generating a quality evaluation result according to the first evaluation index and the second evaluation index; calculating a third evaluation index according to the chemical component parameters of the plurality of reference samples, calculating a fourth evaluation index according to the chemical component parameters of the target sample repeatedly detected for multiple times, and judging the confidence coefficient of the calibration curve according to the third evaluation index and the fourth evaluation index; and if the confidence coefficient of the calibration curve meets a second preset condition, evaluating the to-be-detected sample by using the calibration curve to generate a corresponding detection result. Therefore, the problems of low treatment efficiency, relatively low accuracy and the like of a detection means of an SCR (Selective Catalytic Reduction) catalyst in related technologies are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of quality control, in particular to a quality control method for chemical component analysis of SCR denitration catalyst. BACKGROUND

[0002] As the main source of industrial NOx emissions, coal-fired power plants generally use selective catalytic reduction (SCR) technology for denitration treatment. The core of this technology is the SCR catalyst. Currently, the commercial SCR catalyst is mainly vanadium-titanium system, which uses TiO2 as the carrier, V2O5 as the active component, and adds WO3 or MoO3 as the cocatalyst. The chemical composition content of the catalyst directly affects its performance. The introduction of unqualified raw materials or impurities during production can significantly reduce the quality of the catalyst. During the actual operation of the denitration system, the main chemical components of the catalyst can also change due to the influence of fly ash wear, high-temperature sintering, or deposition of harmful components in the flue gas.

[0003] In related technologies, chemical component analysis methods such as ICP-OES (inductively coupled plasma optical emission spectrometry) and AAS (atomic absorption spectrometry) can provide high accuracy, but the analysis process of each sample is relatively long, resulting in low processing efficiency, which is difficult to meet the real-time monitoring needs in the rapid production environment. For samples containing multiple elements and complex matrix, the results are easily affected by the matrix effect, resulting in low accuracy. SUMMARY

[0004] The present application provides a quality control method for chemical component analysis of SCR denitration catalyst to solve the problems of low processing efficiency and low accuracy of the detection means of the SCR catalyst in related technologies.

[0005] The first aspect of the present application provides a quality control method for chemical component analysis of SCR denitration catalyst, which includes the following steps: obtaining a plurality of chemical component parameters of a target sample of the SCR denitration catalyst; calculating a first evaluation index and a second evaluation index of the target sample according to the chemical component parameters; generating a quality evaluation result of the target sample according to the first evaluation index and the second evaluation index; if the quality evaluation result meets a first preset condition, generating a calibration curve of the target sample according to the chemical component parameters; calculating a third evaluation index according to the chemical component parameters of a plurality of reference samples, calculating a fourth evaluation index according to the chemical component parameters obtained after repeated detection of the target sample, and determining the confidence of the calibration curve of the target sample according to the third evaluation index or the fourth evaluation index, wherein each reference sample is prepared in the same way as the target sample; if the confidence of the calibration curve of the target sample meets a second preset condition, generating a corresponding detection result using the calibration curve to evaluate the target sample of the sample to be tested.

[0006] Optionally, the calculation formula for calculating the first evaluation index of the target sample according to the chemical composition parameter is: ; wherein r is the first evaluation index, is the concentration and intensity corresponding to the nth data point, and n is the total number of data points.

[0007] Optionally, the calculation formula for calculating the second evaluation index of the target sample according to the chemical composition parameter is: M= ; wherein M is the second evaluation index, represents the residual value of different components in the calibration straight line, represents the remaining standard deviation.

[0008] Optionally, the calculation formula for calculating the third evaluation index according to the chemical composition parameters of the plurality of reference samples is: ; wherein t is the third evaluation index, represents the average value of each group of main components, µ represents the theoretical content of each main component, and s represents the standard deviation of each group of main components.

[0009] Optionally, the calculation formula for calculating the fourth evaluation index according to the chemical composition parameters of the target sample obtained after multiple repeated detections is: RSD= ; wherein RSD is the fourth evaluation index, represents the average value of each group of main components, and s represents the standard deviation of each group of main components.

[0010] Optionally, the quality evaluation result of the target sample is determined according to the first evaluation index and the second evaluation index, including: if the first evaluation index approaches the first threshold value and the second evaluation index is less than the second threshold value, the quality evaluation result of the target sample meets the first preset condition, otherwise the quality evaluation result of the target sample does not meet the first preset condition.

[0011] Optionally, the confidence of the target sample calibration curve is determined according to the third evaluation index and the fourth evaluation index, including: if the third evaluation index is less than the third threshold value and the fourth evaluation index is less than the fourth threshold value, it is determined that the confidence of the target sample calibration curve meets the second preset condition, otherwise it is determined that the confidence of the target sample calibration curve does not meet the second preset condition.

[0012] ​Optionally, after the confidence of the target sample calibration curve meets a second preset condition, the method further includes: identifying an average value of a main component detection content and a standard deviation of the main component detection content of the target sample; calculating an upper warning limit, a lower warning limit, an upper action limit and a lower action limit according to the average value of the main component detection content and the standard deviation of the main component detection content; and establishing a sample control chart according to the upper warning limit, the lower warning limit, the upper action limit and the lower action limit.

[0013] Optionally, the generating a corresponding detection result by using the calibration curve to evaluate the to-be-tested sample includes: obtaining a detection value of the to-be-tested sample; if the detection value is within a range of the upper warning limit and the lower warning limit, it is indicated that the detection result of the quality control sample is in a first target state; if the detection value is within a range of the upper action limit and the lower action limit, it is indicated that the detection result of the quality control sample is in a second target state; and if the detection value is outside the range of the upper action limit and the lower action limit, it is indicated that the detection result of the quality control sample is in a third target state.

[0014] Optionally, after the generating a corresponding detection result by using the calibration curve to evaluate the to-be-tested sample, the method further includes: generating a corresponding suggestion report according to the detection result.

[0015] Therefore, the present application has at least the following beneficial effects: The embodiments of the present application can construct a multi-dimensional quality evaluation system by collecting and analyzing multiple chemical component parameters of a target sample; the first and second evaluation indexes are used to preliminarily screen the sample, so as to avoid using unqualified samples to establish a calibration curve, thereby ensuring that the subsequent detection basis data is reliable; the reference sample and the target sample are obtained under the same preparation condition, so as to eliminate errors caused by sample pretreatment differences; the third evaluation index (reference sample consistency) and the fourth evaluation index (target sample repeatability) are combined to comprehensively evaluate the stability and repeatability of the calibration curve; the accuracy and stability of the detection result are ensured, and the four aspects of quality control methods of key parameter evaluation, accuracy evaluation, repeatability evaluation and control chart dynamic monitoring are established, so as to provide a more scientific and accurate basis for catalyst production quality control and operation life management.

[0016] Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following and / or can be learned by practice of the application. BRIEF DESCRIPTION OF DRAWINGS

[0017] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, taken in conjunction with the accompanying drawings, in which: Figure 1A flowchart of an SCR denitration catalyst chemical component analysis quality control method according to an embodiment of the present application is provided. Figure 2 A schematic diagram of an SCR denitration catalyst chemical component analysis quality control method based on XRF detection according to an embodiment of the present application is provided. Figure 3 A V2O5 content control chart according to an embodiment of the present application is provided. Figure 4 A WO3 content control chart according to an embodiment of the present application is provided. Figure 5 A TiO2 content control chart according to an embodiment of the present application is provided. Figure 6 A component content cumulative value quality control chart according to an embodiment of the present application is provided. DETAILED DESCRIPTION

[0018] Embodiments of the present application are described in detail below with reference to examples shown in the accompanying drawings, in which the same or similar numerals indicate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application, and cannot be understood as limiting the present application.

[0019] The present application uses X-ray fluorescence spectrometry to carry out detection of the content of main chemical components in a denitration catalyst, and describes the requirements for the detection instrument and reagents, sample preparation, analysis method and establishment process of the calibration curve. However, in order to ensure that accurate and reliable detection results are obtained, the quality control method for the detection itself should also be established and implemented at the same time as a supplement to the standard content, to guide the stable and orderly development of laboratory detection work.

[0020] The SCR denitration catalyst chemical component analysis quality control method of the embodiments of the present application is described below with reference to the accompanying drawings.

[0021] Specifically, Figure 1 A flowchart of an SCR denitration catalyst chemical component analysis quality control method according to an embodiment of the present application is provided.

[0022] As Figure 1 shown, the SCR denitration catalyst chemical component analysis quality control method includes the following steps: In step S101, a plurality of chemical component parameters of a target sample of an SCR denitration catalyst are obtained.

[0023] It can be understood that the embodiments of the present application can obtain a plurality of chemical component parameters of a target sample of an SCR denitration catalyst, so as to provide more comprehensive and accurate quality evaluation results.

[0024] It should be noted that the SCR denitrification catalysts of the present application all use the software equipped with the X-ray fluorescence spectrometry instrument to detect the X-ray fluorescence intensity of each component in the series of calibration samples, where the chemical composition parameters include V2O5, WO3, TiO2, MoO3, AL2O3, SiO2, CaO, etc., without specific limitation.

[0025] In step S102, a first evaluation index and a second evaluation index of the target sample are calculated according to the chemical composition parameters, and a quality assessment result of the target sample is generated according to the first evaluation index and the second evaluation index. If the quality assessment result meets the first preset condition, a calibration curve of the target sample is generated according to the chemical composition parameters.

[0026] Among them, the first evaluation indicator is the linear correlation coefficient r value, the second evaluation indicator is the residual statistic M value, and the first preset condition is that the linear correlation coefficient r of each chemical composition parameter in the target sample is greater than or equal to 0.997, and the M value is less than 1.5, without specific limitation.

[0027] In the embodiment of the present application, the calculation formula for calculating the first evaluation index of the target sample according to the chemical composition parameters is: ; Among them, r is the first evaluation index, It is The concentration and intensity corresponding to the data points, n is the total number of data points.

[0028] In the embodiment of the present application, the calculation formula for calculating the second evaluation index of the target sample according to the chemical composition parameters is: M= ; Among them, M is the second evaluation index, represents the residual values ​​of different components in the calibration line, represents the residual standard deviation.

[0029] It can be understood that the embodiments of the present application can comprehensively evaluate the sample from multiple angles by comprehensively considering the first evaluation indicator and the second evaluation indicator, reduce the risk of misjudgment caused by a single indicator, and improve the accuracy and efficiency of detection.

[0030] It should be noted that standard samples were prepared and calibration curves were established according to national standard methods. Linearity and outliers were assessed using the linear correlation coefficient (r-value) and residual statistic (M-value) tests. The first evaluation metric is the deviation between the actual and ideal concentrations of one or more key parameters based on the content of the main active ingredient (such as V2O5 and WO3). The second evaluation metric is based on the uniformity, proportionality, or physical properties (such as specific surface area) of the additives or other minor components (such as TiO2 and SiO2). These two evaluation metrics, combined, provide a comprehensive assessment of catalyst quality.

[0031] In an embodiment of the present application, the quality assessment result of the target sample is determined based on the first evaluation indicator and the second evaluation indicator, including: if the first evaluation indicator is close to the first threshold and the second evaluation indicator is less than the second threshold, then the quality assessment result of the target sample meets the first preset condition; otherwise, the quality assessment result of the target sample does not meet the first preset condition.

[0032] It can be understood that the embodiments of the present application can comprehensively evaluate the sample from multiple angles by combining the first evaluation indicator and the second evaluation indicator, reduce the risk of misjudgment caused by a single indicator, improve the accuracy of detection, ensure the reliability of the detection method, and ensure the stability of the detection system.

[0033] It should be noted that the first preset condition is that the linear correlation of the calibration curve meets the detection requirements, there are no abnormal points in the calibration curve, and the data reliability is high.

[0034] Specifically, (1) linear correlation coefficient r value test Using the software provided with the XRF instrument, we measured the X-ray fluorescence intensity of each component in the calibration sample series to generate a series of calibration curves showing a linear relationship between the element concentration and fluorescence intensity. The correlation coefficient, r, was used to verify whether the curve passed through the origin and was straight. The r values ​​for the calibration curves of each component were calculated according to Equation (1) and are shown in Table 1 below.

[0035] Formula (1) Where: It is The concentration and intensity corresponding to the data points, n is the total number of data points.

[0036] Table 1 r-values ​​of calibration lines for each component

[0037] The closer the linear correlation coefficient r is to 1, the stronger the linear relationship between the concentration and the fluorescence intensity, and the calibration curve model is reliable. As shown in Table (1), the r values of each component in the calibration sample are close to 1, indicating that the linear correlation degree of the calibration curve meets the detection requirements. On the contrary, if the r value deviates from 1, it indicates that there are problems such as "measurement error, large instrument background interference, and abnormal data points" in the preparation process of the calibration sample and the calibration curve, and they should be prepared again.

[0038] (2) Residual statistics M value test The closer the linear correlation coefficient r is to 1, the stronger the linear relationship between the concentration and the fluorescence intensity, but it cannot reflect the dispersion degree of the data points deviating from the fitting straight line. Therefore, it is necessary to further test the residual statistics M value of the series of calibration curves in (1). The M value of each calibration curve data point is calculated according to formula (2), as shown in Table 2.

[0039] M= ; Formula (2) In the formula: represents the residual value (the difference between the theoretical value and the actual value) of different components in the calibration straight line, represents the remaining standard deviation (square root of residual sum of squares).

[0040]

[0041] By testing the linear correlation coefficient r and the residual statistics M, a data accurate and reliable test working curve with high fitting degree can be obtained, which improves the accuracy of detection, ensures the reliability of the detection method, and ensures the stability of the detection system.

[0042] In step S103, a third evaluation index is calculated according to the chemical component parameters of the plurality of reference samples, a fourth evaluation index is calculated according to the chemical component parameters obtained after repeated detection of the target sample, and the confidence of the calibration curve of the target sample is determined according to the third evaluation index and the fourth evaluation index, wherein the preparation method of each reference sample and the target sample is the same.

[0043] The third evaluation index is t-statistics, and the fourth evaluation index is RSD (relative standard deviation), which is not specifically limited.

[0044] In the embodiments of the present application, the calculation formula of the third evaluation index calculated according to the chemical component parameters of the plurality of reference samples is: ; In the formula, t is the third evaluation index, represents the average value of each group of main components, µ represents the theoretical content of each main component, s represents the standard deviation of each group of main components, and n represents the number of tests.

[0045] In the embodiment of the present application, the calculation formula of the fourth evaluation index calculated according to the chemical composition parameters obtained after multiple repeated detections of the target sample is: RSD= ; Wherein, RSD is the fourth evaluation index, represents the average value of each group of main components, and s represents the standard deviation of each group of main components.

[0046] It can be understood that the third and fourth evaluation indexes can be calculated by referring to the chemical composition parameters of the reference sample and the target sample, respectively, to judge the confidence of the calibration curve, improve the reliability of the detection data, optimize the efficiency of the detection process, and effectively guarantee the accuracy of the XRF detection result.

[0047] It should be noted that the third evaluation index (based on multiple reference samples) reflects the consistency between different batches of samples; the fourth evaluation index (based on multiple detections of the target sample) reflects the stability of repeated measurements of a single sample, and the combination of the two can comprehensively evaluate whether the calibration curve is stable and reliable.

[0048] In the embodiment of the present application, the confidence of the target sample calibration curve is determined according to the third evaluation index and the fourth evaluation index, including: if the third evaluation index is less than the third threshold value and the fourth evaluation index is less than the fourth threshold value, it is determined that the confidence of the target sample calibration curve meets the second preset condition, otherwise it is determined that the confidence of the target sample calibration curve does not meet the second preset condition.

[0049] Wherein, the third threshold value can be 3.7074, the fourth threshold value can be 5%, and the second preset condition is that there is no significant difference between the detection result of each component content and the theoretical content, the accuracy meets the detection requirement, the measurement repeatability is good, and is not limited.

[0050] It can be understood that the third threshold value and the fourth threshold value can be used to determine the confidence of the target sample calibration curve, and the confidence of the calibration curve directly affects the detection result of the sample to be detected. By strict threshold judgment, the stability and reliability of the calibration curve can be ensured, thereby improving the reliability of the entire detection system.

[0051] It should be noted that the third evaluation index is less than the third threshold value: the consistency between the reference samples is good, the preparation process is stable, and the calibration curve is suitable for this type of sample. The fourth evaluation index is less than the fourth threshold value: the results of the target sample in multiple repeated detections have smaller fluctuations, and the detection system has good repeatability. Combining the two can comprehensively evaluate the reliability and stability of the calibration curve, and ensure the accuracy of the detection results. If any evaluation index exceeds the corresponding threshold value, it means that there may be problems such as system error or calibration curve drift. At this time, the re-calibration or re-inspection process can be triggered immediately to avoid invalid detection.

[0052] Specifically, the accuracy of the instrument and the calibration curve is evaluated by the difference between the actual value and the theoretical value of the standard sample, combined with t-value test. Vanadium-titanium commercial honeycomb denitration catalyst is used as a quality control sample, and is tested for 10 consecutive days under the same detection conditions. The repeatability is evaluated by the relative standard deviation (RSD≤5%) of the detection results of the main components.

[0053] (1) Accuracy evaluation implementation mode: Under the working conditions of the XRF instrument, 8 standard samples made in the same way are detected by using the calibration curve tested in the "calibration curve key parameter evaluation", and the accuracy evaluation results are shown in Table 3.

[0054] Table 3 Accuracy evaluation results

[0055] This method compares whether the difference between the theoretical value and the actual value of the standard sample is significant by inferring the probability of the difference occurring through t-distribution theory. According to formula (3), the statistic t is calculated: Formula (3) In the formula: µ represents the average value of each group of main components, µ represents the theoretical content of each main component, s represents the standard deviation of each group of main components, and n represents the number of tests.

[0056] By looking up the t-distribution table, the size of the statistic t and the critical value t(n-1) is compared to determine whether there is a significant difference between the detection results and the theoretical content. Taking the confidence probability as 99%, α=0.01, looking up the t-distribution table, t α / 2 (7)=3.7074. The experimental results show that the statistic t of each main component is less than t α / 2(7), it is illustrated that there is no significant difference between the detection results of the content of each component and the theoretical content, and the accuracy meets the detection requirements. When the statistical quantity t is greater than t(n-1), it is not satisfied that the determination index, which indicates that there is a significant error in the system, and the detection method itself and the operation process need to be investigated and corrected. Whether it is a systematic error or a random error can be judged by the recovery rate experiment, the accuracy of the test method using certified reference materials, the standardization of the operation process, the correct handling of abnormal values, and the improvement of the detection accuracy.

[0057] (2) Reproducibility evaluation implementation: The calibration curve tested in the "calibration curve key parameter evaluation" was used to carry out 10 times of reproducibility detection on the quality control sample, and the detection and evaluation results are shown in Table 4.

[0058] Table 4 Reproducibility test results of quality control sample

[0059] The smaller the RSD value, the smaller the fluctuation of the detection data, and the more stable the detection results. Generally, RSD less than 5% is selected, if RSD is less than the determination value, it indicates that the measurement reproducibility is good; and if RSD is higher than the determination value, it indicates that the measurement reproducibility is poor, and the possible errors and disturbances in the detection process should be investigated and excluded.

[0060] In step S104, if the confidence of the calibration curve of the target sample meets the second preset condition, the corresponding detection result is generated by using the calibration curve to evaluate the to-be-measured sample.

[0061] It can be understood that the calibration curve meeting the confidence requirement can be used to analyze the to-be-measured sample in the embodiments of the present application, which ensures the high precision and high reproducibility of the detection results, can effectively reduce the systematic error caused by factors such as instrument drift and environmental interference, and improves the consistency of the detection results; the detection results of some samples are found to be abnormal in the detection process, the quality control capability is enhanced, the detection process efficiency is optimized, and the stability and accuracy of the detection are improved.

[0062] In the embodiments of the present application, after the confidence of the target sample calibration curve meets the second preset condition, the average value of the main component detection content and the standard deviation of the main component detection content are identified; the upper limit of the alarm, the lower limit of the alarm, the upper limit of the action and the lower limit of the action are calculated according to the average value of the main component detection content and the standard deviation of the main component detection content; and the sample control chart is established according to the upper limit of the alarm, the lower limit of the alarm, the upper limit of the action and the lower limit of the action.

[0063] It can be understood that the embodiments of the present application can ensure high precision and high repeatability of the test results by calculating the average value and standard deviation of the detection content of the main components. The high-quality calibration curve combined with the control chart can effectively reduce the systematic errors caused by factors such as instrument drift and environmental interference, and improve the consistency of the test results. The control chart can help quickly identify data points that exceed the warning range or action range, and take corrective measures in time; identify and solve potential problems in advance, reduce the risks and losses caused by quality problems, improve the credibility and data quality of the test data, and optimize the efficiency of the test process.

[0064] In an embodiment of the present application, a calibration curve is used to evaluate the sample to be tested to generate a corresponding test result, including: obtaining a test value of the sample to be tested; if the test value is within the range of an upper warning limit and a lower warning limit, it indicates that the test result of the quality control sample is in a first target state; if the test value is within the range of an upper action limit and a lower action limit, it indicates that the test result of the quality control sample is in a second target state; if the test value falls outside the range of an upper action limit and a lower action limit, it indicates that the test result of the quality control sample is in a third target state.

[0065] Among them, the first target state is that the target sample is in a stable or normal state; the second target state is that the target sample is in a usable state, but has a tendency to be out of control and should be paid attention to; the third target state is that the target sample is in an unstable state and the test result is unreliable. The cause should be checked and corrected before retesting.

[0066] It can be understood that the embodiment of the present application can monitor the quality changes of each batch of samples in the production process in real time through the control chart, and divide the test results into three states to facilitate the adoption of different levels of response measures according to the severity. By comparing with the verified calibration curve and combining the control limit range judgment, it can effectively eliminate misjudgments caused by accidental errors or systematic errors and ensure the reliability of the test results.

[0067] It should be noted that the control chart (including UWL / LWL / UCL / LCL) for XRF detection of the main components of the SCR denitrification catalyst is established through the quality control sample test data, which is used to dynamically monitor the stability of the laboratory testing process.

[0068] Specifically, during the long-term testing process, the test results of the content of each component of the quality control sample in each test are accumulated to calculate the The parameters of average value, UWL (upper warning limit), LWL (lower warning limit), UCL (upper action limit) and LCL (lower action limit) are calculated according to formula (4) to formula (7): Formula (4) Formula (5) Formula (6) Formula (7) In the formula: is the average value of the detection content of the main component, and s is the standard deviation of the detection content of the main component.

[0069] Taking the test sequence as the abscissa and the warning upper and lower limits and the action upper and lower limits as the ordinate, a "quality control sample concentration-control chart" is established. During the daily detection process, the detection results of each quality control sample are marked in the control chart to dynamically determine whether the analysis process is in a controlled state, which is used for the supervision of the daily work of the laboratory.

[0070] Taking the content values of V2O5, WO3 and TiO2 as examples, 30 groups of periodic control charts are intercepted and made as shown in Figures 2 to 5 .

[0071] It can be known from the control chart result that when the detection value is within the warning limit (between the UWL and the LWL), it indicates that the analysis is normal, and the detection result of this time is stable and reliable; when the detection value is outside the warning limit and within the action limit (between the UCL and the LCL), it indicates that the detection result is usable, but has a tendency of being out of control, which should be paid attention to; when the detection value is outside the action limit, it indicates that the detection is out of control, and the detection result is not reliable, which should be checked and retested after correction.

[0072] In the embodiments of the present application, after the corresponding detection result of the to-be-detected sample is generated by using the calibration curve, the corresponding suggestion report is generated according to the detection result.

[0073] It can be understood that the embodiments of the present application can generate the corresponding suggestion report according to the detection result, help relevant personnel to quickly identify problems and take corresponding corrective measures, prevent unqualified products from flowing into the market, improve the quality management efficiency, provide complete quality records, and enhance the customers' confidence in product quality.

[0074] According to the SCR denitration catalyst chemical component analysis quality control method provided in the embodiments of the present application, a multi-dimensional quality evaluation system is constructed by collecting and analyzing multiple chemical component parameters of a target sample; the sample is preliminarily screened by using the first and second evaluation indexes, so as to avoid using unqualified samples to establish a calibration curve, thereby ensuring the reliability of the basic data for subsequent detection; the reference sample and the target sample are obtained under the same preparation condition, so as to exclude the error caused by the difference in sample pretreatment; the stability and repeatability of the calibration curve are comprehensively evaluated in combination with the third evaluation index (reference sample consistency) and the fourth evaluation index (target sample repeatability); and the accuracy and stability of the detection result are ensured.

[0075] The SCR denitration catalyst chemical component analysis quality control method of the present application will be described in detail as follows: The calibration curve key parameter evaluation experiment is as follows: (1) Linear correlation coefficient r value test: certified reference materials are uniformly mixed according to the specified proportion to prepare standard samples, and a calibration curve is prepared, wherein the linear correlation coefficient r value of the calibration curve is greater than or equal to 0.997.

[0076] (2) Residual statistics M value test: the ratio of the absolute value of the residual (the difference between the theoretical value and the actual value) and the remaining standard deviation (the square root of the residual sum of squares) in the calibration curve is used to calculate the statistics M value, and generally the M value is not greater than 1.5. When invalid, the calibration curve needs to be prepared again, otherwise the accuracy of all subsequent evaluations will be affected.

[0077] (3) The accuracy evaluation experiment is as follows: the certified reference materials are uniformly mixed according to a certain proportion to prepare samples, and 8 identical standard samples are prepared, and the theoretical content of each component is obtained. The calibration curve prepared in the calibration curve key parameter evaluation experiment is used to detect the standard samples, and the accuracy of the instrument and the calibration curve is evaluated by the difference between the theoretical value and the actual value. In this method, the t value is used for evaluation. This method infers the probability of difference occurrence through t distribution theory, so as to compare whether the difference between the theoretical value and the actual value of the standard sample is significant. The deviation needs to be corrected, otherwise the repeatability and quality control chart data are not reliable.

[0078] (4) The repeatability evaluation experiment is as follows: 1 fixed and representative vanadium-titanium commercial honeycomb denitration catalyst is selected as the quality control sample (V2O5 content 0.7±0.1wt%, WO3 content 4.4±0.3wt%, TiO2 carrier≥85wt%). In the daily detection process, the quality control sample is detected according to the same sample preparation method and detection conditions (X-ray fluorescence spectrometer, light tube voltage 60kV, tube current 40mA, vacuum, each sample is measured 3 times and the average value is taken) as the actual sample. Before the experiment, the quality control sample is repeatedly measured 3 times every day, and the average value is taken. The detection data of 10 working days are obtained, and 10 groups of detection data are obtained. Record the detection results of V2O5, WO3, TiO2 and other main components, and calculate the relative standard deviation (RSD) of each component detection result, wherein RSD≤5%. When RSD exceeds the standard, the instrument needs to be maintained, otherwise the quality control chart fluctuation increases.

[0079] (5) The control chart is established as follows: the detection results of the quality control sample are accumulated to establish the control chart of the XRF detection denitration catalyst main component method. The control chart is composed of warning upper limit UWL, warning lower limit LWL, action upper limit UCL and action lower limit LCL. The detection results of the quality control sample are marked in the control chart to judge whether the analysis process is in a controlled state, which is used for dynamic supervision of daily work. When the control chart is out of control, the whole process needs to be traced and detected, and the method needs to be recalibrated or checked.

[0080] In summary, the quality control method is established to ensure the scientificity and accuracy of the detection data through the calibration curve key parameter evaluation, accuracy evaluation and repeatability evaluation. The stability of the detection process is dynamically monitored through the control chart, the misjudgment caused by detection error is reduced, and the operation cost is reduced. The traceable quality control method conforming to the national standard is established to provide the monitoring data support for the environmental protection emission standard. The quality control method upgrades the traditional single denitration catalyst chemical composition detection to a complete quality assurance system including multi-parameter evaluation, process control and data analysis, which significantly improves the scientific level of the whole life cycle management of the SCR catalyst.

[0081] In the description of the present specification, the description referring to the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or N embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0082] In addition, the terms "first", "second" are only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "N" is at least two, for example, two, three, etc., unless otherwise specifically limited.

[0083] Any process or method descriptions in flow charts or described elsewhere herein can be understood as representing one or N executable instructions, code segments, or portions of code that include the steps for implementing the custom logic function or process, and the scope of the preferred embodiments of the present application includes additional implementation in which the functions are performed in different orders, including substantially simultaneously, or in reverse order, or in other orders, depending on the functionality involved, as will be understood by those skilled in the art.

[0084] It should be understood that portions of the application can be implemented in hardware, software, firmware, or combinations thereof. In the above embodiments, the N steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As such, if implemented in hardware, and in another embodiment, the implementation can be realized using any or a combination of the following technologies, which are each well known in the art: a discrete logic circuit having logic gates for implementing logic functions upon an application of data signals, an application specific integrated circuit having appropriate combinational logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), or the like.

[0085] Those skilled in the art can understand that all or part of the steps carried out by the above-mentioned embodiment methods can be completed by programs instructing relevant hardware, and the programs can be stored in a computer readable storage medium. When the programs are executed, one or a combination of the steps of the method embodiments is included.

Claims

1. A method for quality control of chemical composition analysis of SCR denitration catalyst, characterized in that: The following steps are involved: Obtain multiple chemical composition parameters of a target sample of an SCR denitration catalyst; Calculating a first evaluation index and a second evaluation index of the target sample according to the chemical composition parameters, generating a quality assessment result of the target sample according to the first evaluation index and the second evaluation index, and if the quality assessment result meets a first preset condition, generating a calibration curve of the target sample according to the chemical composition parameters; A third evaluation index is calculated based on chemical composition parameters of multiple reference samples, a fourth evaluation index is calculated based on chemical composition parameters obtained after multiple repeated tests of the target sample, and the confidence level of the calibration curve of the target sample is determined based on the third evaluation index and the fourth evaluation index, wherein each reference sample and the target sample are prepared in the same manner; If the confidence level of the calibration curve of the target sample meets the second preset condition, the calibration curve is used to evaluate the sample to be tested to generate a corresponding test result.

2. The SCR denitration catalyst chemical composition analysis quality control method according to claim 1, characterized in that: The calculation formula for calculating the first evaluation index of the target sample according to the chemical composition parameters is: ； Among them, r is the first evaluation index, It is The concentration and intensity corresponding to the data points, n is the total number of data points.

3. The SCR denitration catalyst chemical composition analysis quality control method according to claim 1, characterized in that: The calculation formula for calculating the second evaluation index of the target sample according to the chemical composition parameter is: M= ； Among them, M is the second evaluation index, represents the residual values ​​of different components in the calibration line, represents the residual standard deviation.

4. The SCR denitration catalyst chemical composition analysis quality control method according to claim 1, characterized in that: The calculation formula for the third evaluation index calculated based on the chemical composition parameters of multiple reference samples is: ； Among them, t is the third evaluation index, represents the average value of the main components of each group, μ represents the theoretical content of each main component, s represents the standard deviation of the main components of each group, and n represents the number of tests.

5. The SCR denitration catalyst chemical composition analysis quality control method according to claim 1, characterized in that: The calculation formula for calculating the fourth evaluation index based on the chemical composition parameters obtained after repeated testing of the target sample is: RSD= ; Among them, RSD is the fourth evaluation indicator. represents the mean value of each principal component, and s represents the standard deviation of each principal component.

6. The SCR denitration catalyst chemical composition analysis quality control method according to claim 1, characterized in that: Determining the quality assessment result of the target sample according to the first evaluation index and the second evaluation index includes: If the first evaluation index approaches the first threshold and the second evaluation index is less than the second threshold, the quality assessment result of the target sample meets the first preset condition; otherwise, the quality assessment result of the target sample does not meet the first preset condition.

7. The SCR denitration catalyst chemical composition analysis quality control method according to claim 1, characterized in that: Determining the confidence of the target sample calibration curve according to the third evaluation index and the fourth evaluation index includes: If the third evaluation indicators are all less than the third threshold and the fourth evaluation indicators are less than the fourth threshold, it is determined that the confidence of the target sample calibration curve meets the second preset condition; otherwise, it is determined that the confidence of the target sample calibration curve does not meet the second preset condition.

8. The SCR denitration catalyst chemical composition analysis quality control method according to claim 1, characterized in that: After the confidence level of the target sample calibration curve meets a second preset condition, the method includes: Identify the mean and standard deviation of the main component test content of the target sample; Calculate the upper warning limit, lower warning limit, upper action limit and lower action limit based on the average value of the detection content of the main component and the standard deviation of the detection content of the main component; A sample control chart is established based on the upper warning limit, the lower warning limit, the upper action limit and the lower action limit.

9. The SCR denitration catalyst chemical composition analysis quality control method according to claim 8, characterized in that: The method of using the calibration curve to evaluate the sample to be tested to generate the corresponding test result includes: Obtaining a test value of the sample to be tested; If the detection value is within the range of the upper warning limit and the lower warning limit, it indicates that the detection result of the quality control sample is in the first target state; If the test value is within the range of the upper action limit and the lower action limit, it indicates that the test result of the quality control sample is in the second target state; If the detection value falls outside the range of the upper action limit and the lower action limit, it indicates that the detection result of the quality control sample is in the third target state.

10. The SCR denitration catalyst chemical composition analysis quality control method according to claim 1, characterized in that: After the calibration curve is used to evaluate the sample to be tested and generate the corresponding test result, the method includes: Generate a corresponding recommendation report based on the detection results.

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