Detection result correction method and system based on multiple steel types

Abstract

The invention is suitable for the technical field of sample correction, and provides a correction method and system based on a multi-steel-grade detection result, and the method comprises the steps: obtaining sample data which comprises the surface state, size and shape of a steel sample, and obtaining experimental data; measuring data of a standard steel sample are obtained, the standard steel sample is a steel sample with definite chemical components, the accuracy of the instrument is judged according to the measuring data of the standard steel sample, and a deviation value is obtained according to a judgment result; multiple deviation values are obtained, a deviation rule is obtained, an error reason is analyzed according to the deviation rule, an average deviation value is calculated according to the deviation rule, and the average deviation value is used for correcting the measured value; the method comprises the following steps: obtaining sample measurement data, correcting according to an average deviation value, obtaining corrected first measurement data, and sending the first measurement data to a display terminal, thereby solving the problems that results are inaccurate and cannot be visually summarized due to manual calculation.

Description

Technical Field

[0001] The invention belongs to the technical field of sample correction, and in particular relates to a correction method and system based on multi-steel detection results. Background Art

[0002] In the process of testing the chemical composition of steel samples by spectrometer, the analysis results of each chemical component in the steel samples are required to be very accurate. However, the spectrometer will have certain deviations during multiple tests, resulting in inaccurate results. The traditional correction method is to manually calculate this deviation value, and after each analysis, subtract or add this deviation value from the result to get the correct result.

[0003] Manual calculations will lead to inaccurate results, and the results cannot be summarized intuitively. Therefore, an external correction method and system based on a national standard sample system for multiple steel grades is needed to correct the steel sample test results, and finally summarize the results and feedback them on the display screen. Summary of the invention

[0004] The purpose of the embodiment of the present invention is to provide a correction method based on multiple steel grade detection results, aiming to solve the problem raised in the third part of the background technology.

[0005] The embodiment of the present invention is implemented as follows: a correction method based on multiple steel grade detection results, the method comprising: Acquire sample data, the sample data including the surface state, size and shape of the steel sample, and acquire experimental data, the experimental data including instrument data and parameter data; Obtaining measurement data of a standard steel sample, wherein the standard steel sample is a steel sample with a clear chemical composition, determining the accuracy of the instrument according to the measurement data of the standard steel sample, and obtaining a deviation value according to the determination result; Obtain multiple deviation values, obtain deviation rules, analyze the error causes according to the deviation rules, calculate the average deviation value according to the deviation rules, and use the average deviation value to correct the measured value; The sample measurement data is acquired, corrected according to the average deviation value, the corrected first measurement data is obtained, and the first measurement data is sent to the display terminal.

[0006] Preferably, the step of obtaining the measurement data of a standard steel sample, wherein the standard steel sample is a steel sample with a clear chemical composition, determining the accuracy of the instrument according to the measurement data of the standard steel sample, and obtaining the deviation value according to the determination result specifically includes: Obtaining measurement data of the standard steel sample, obtaining actual data of the standard steel sample, and comparing the measurement data of the standard steel sample with the actual data of the standard steel sample; Obtaining a comparison result and an error threshold, wherein the error threshold is used to determine whether the instrument can be used. If the comparison result is within the error threshold, it is determined that the instrument can be used; The accuracy of the instrument is determined based on the comparison results, and the deviation value is obtained based on the determination results.

[0007] Preferably, the step of obtaining multiple deviation values, obtaining a deviation rule, analyzing the cause of the error according to the deviation rule, calculating an average deviation value according to the deviation rule, and using the average deviation value to correct the measured value specifically includes: Obtain multiple deviation values, obtain deviation rules, the obtained deviation rules include systematic deviation, random deviation and periodic deviation, and determine the rule type; Analyze the cause of the error according to the deviation law, obtain the deviation value distribution law, and calculate the average deviation value according to the deviation law; The average deviation value verification result is obtained, wherein the verification adopts multiple measurements and the validity of the deviation value is judged according to the verification result.

[0008] Preferably, the step of acquiring sample measurement data, correcting the sample measurement data according to the average deviation value, obtaining the corrected first measurement data, and sending the first measurement data to the display terminal specifically includes: Obtain sample measurement data, correct it according to the average deviation value, and filter out abnormal data, where the difference between the original data and the corrected data is too large; Obtaining the corrected first measurement data, and performing statistical analysis based on the first measurement data, wherein the statistical analysis includes calculating a mean value, a standard deviation, and a maximum value; Draw charts based on statistical analysis and send them to the display terminal.

[0009] Preferably, the parameter data includes spectrometer excitation time and spectrometer excitation energy.

[0010] Another object of an embodiment of the present invention is to provide a correction system based on multiple steel grade detection results, the system comprising: A preparation module is used to obtain sample data, including surface state, size and shape of the steel sample, and to obtain experimental data, including instrument data and parameter data; The standard steel sample module obtains the measurement data of the standard steel sample, wherein the standard steel sample is a steel sample with a clear chemical composition, determines the accuracy of the instrument according to the measurement data of the standard steel sample, and obtains the deviation value according to the determination result; The deviation value module obtains multiple deviation values, obtains the deviation law, analyzes the error cause according to the deviation law, and calculates the average deviation value according to the deviation law. The average deviation value is used to correct the measurement value; The correction module obtains the sample measurement data, performs correction according to the average deviation value, obtains the corrected first measurement data, and sends the first measurement data to the display terminal.

[0011] Preferably, the standard steel sample module comprises: Standard steel sample unit, obtains standard steel sample measurement data, obtains standard steel sample actual data, and compares standard steel sample measurement data with standard steel sample actual data; An instrument determination unit obtains a comparison result and an error threshold, wherein the error threshold is used to determine whether the instrument can be used. If the comparison result is within the error threshold, the instrument is determined to be usable. The deviation value unit determines the accuracy of the instrument according to the comparison result and obtains the deviation value according to the determination result.

[0012] Preferably, the deviation value module includes: A deviation law unit, which obtains multiple deviation values, obtains deviation laws, wherein the obtained deviation laws include systematic deviations, random deviations and periodic deviations, and determines the law type; The error analysis unit analyzes the error cause according to the deviation law, obtains the deviation value distribution law, and calculates the average deviation value according to the deviation law; The verification unit obtains a verification result of the average deviation value, wherein the verification adopts multiple measurements and determines the validity of the deviation value according to the verification result.

[0013] Preferably, the correction module comprises: A correction unit, which obtains sample measurement data, corrects it according to the average deviation value, and screens out abnormal data, wherein the abnormal data is data whose difference between the original data and the corrected data is too large; An analysis unit, which obtains the corrected first measurement data and performs statistical analysis based on the first measurement data, wherein the statistical analysis includes calculating a mean value, a standard deviation, and a maximum value; The display unit draws charts based on statistical analysis and sends the charts to the display terminal.

[0014] Preferably, the parameter data includes spectrometer excitation time and spectrometer excitation energy.

[0015] The embodiment of the present invention provides a correction method based on the detection results of multiple steel types, which obtains sample data, obtains the surface state, size and shape of the steel sample to be analyzed through the sample data, obtains instrument data and parameter data, and conducts experiments through suitable instruments to obtain instrument data and parameters. These data will provide important basis for subsequent material analysis, performance evaluation and improved design, obtain standard steel sample measurement data, the standard steel sample refers to a steel sample with clear chemical composition and known physical properties, determine the accuracy of the instrument according to the standard steel sample measurement data, obtain comparison results, obtain error thresholds, if the comparison results are within the error threshold, then determine that the instrument can be used, determine the accuracy of the instrument according to the comparison results, obtain deviation values ​​according to the judgment results, obtain multiple deviation values, obtain deviation rules, determine which of the systematic deviation, random deviation and periodic deviation the deviation belongs to, analyze the error cause according to the deviation rules, obtain the deviation value distribution rules, calculate the average deviation value according to the deviation rules, obtain sample measurement data, make corrections according to the average deviation value, filter out abnormal data, perform statistical analysis according to the first measurement data, draw charts according to the statistical analysis, and send the charts to the display terminal, which solves the problem that manual calculations will lead to inaccurate results and the results cannot be summarized intuitively. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flowchart of a method for correcting multiple steel grade detection results provided by an embodiment of the present invention; Figure 2 A flowchart of the steps of obtaining standard steel sample measurement data, determining instrument accuracy based on the standard steel sample measurement data, and obtaining a deviation value based on the determination result provided by an embodiment of the present invention; Figure 3 A flowchart of the steps of obtaining multiple deviation values, analyzing the cause of the error according to the deviation law, and calculating the average deviation value according to the deviation law provided by an embodiment of the present invention; Figure 4 A flowchart of the steps of obtaining sample measurement data, correcting according to an average deviation value, and sending first measurement data to a display terminal provided by an embodiment of the present invention; Figure 5 An architecture diagram of a system for correcting multiple steel grade detection results provided by an embodiment of the present invention; Figure 6 The architecture diagram of the standard steel sample module provided by the embodiment of the present invention; Figure 7 The architecture diagram of the deviation value module provided by the embodiment of the present invention; Figure 8 This is an architectural diagram of a correction module provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0018] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

[0019] like Figure 1 As shown, a correction method based on multiple steel grade detection results is provided in an embodiment of the present invention, and the method includes: S100, acquiring sample data, the sample data including the surface state, size and shape of the steel sample, and acquiring experimental data, the experimental data including instrument data and parameter data.

[0020] In this step, sample data is obtained. The sample data mainly includes the surface state of the steel sample. The surface state of the steel sample includes surface cleanliness, surface smoothness and surface treatment state, whether the surface of the steel sample is clean, whether there are oxides, oil stains or other contaminants. This will directly affect the accuracy of the spectral analysis. Whether the surface of the steel sample is clean, whether there are oxides, oil stains or other contaminants. This will directly affect the accuracy of the spectral analysis. Whether the surface of the steel sample is clean, whether there are oxides, oil stains or other contaminants. This will directly affect the accuracy of the spectral analysis; The specific size of the sample (such as length, width and thickness) has an important impact on the detection effect of the spectrometer. A sample that is too small may lead to unstable signals. The geometric shape of the sample (such as cylindrical, square, flat, etc.) may affect the incident angle and reflection characteristics of the laser or light beam. The overall volume of the sample may affect the signal intensity and detection range of the instrument during analysis. Experimental data are divided into instrument data and parameter data, which are used to describe the specific operation of the experiment and the status of the instrument, such as the specific model of the spectrometer used, such as laser induced breakdown spectrometer (LIBS) or atomic emission spectrometer (AES), the working status of the instrument, such as temperature, humidity, working voltage, light source type, etc. These factors will affect the stability and results of the measurement; The detection parameters set, such as integration time, excitation power, gas flow rate, etc., which will affect the sensitivity and accuracy of the analysis results, the calibration curve or standard sample information used to ensure the reliability of the measurement results, the temperature, humidity, air pressure and other environmental data during the experiment, these factors may have an impact on the measurement results.

[0021] These data help researchers understand the relationship between experimental conditions and measurement results. By recording and organizing these data in a standardized manner, they can provide a reliable basis for subsequent analysis, deviation identification, and result correction.

[0022] S200, obtaining measurement data of a standard steel sample, wherein the standard steel sample is a steel sample with a clear chemical composition, determining the accuracy of the instrument according to the measurement data of the standard steel sample, and obtaining a deviation value according to the determination result.

[0023] In this step, obtain the measurement data of standard steel samples. Standard steel samples usually refer to samples with known and certified chemical compositions. Using these standard samples for measurement can help researchers confirm the accuracy of the instrument and calculate the deviation value. Before measuring the standard steel sample, it is necessary to ensure the preparation of the instrument. Make sure that the spectrometer is properly calibrated before measurement. Set the instrument parameters according to the standard operating procedures, including integration time and excitation power. Determine the accuracy of the instrument based on the measurement data of the standard steel sample. If the deviation value is within the acceptable range, usually ±5%, the instrument is considered to be accurate. Obtain the deviation value based on the judgment result, deviation value = measured value − theoretical value.

[0024] S300, obtaining multiple deviation values, obtaining a deviation rule, analyzing the error cause according to the deviation rule, and calculating an average deviation value according to the deviation rule, wherein the average deviation value is used to correct the measurement value.

[0025] In this step, multiple deviation values ​​are obtained. In the analysis of steel sample composition, deviation values ​​may appear during spectrometer detection. This phenomenon is quite common in actual operation. The deviation value refers to the difference between the actual detection value and the theoretical value or standard value during multiple detections. The reason for the deviation value needs to be determined. For example, the performance and calibration status of the spectrometer will directly affect the accuracy of the detection.

[0026] If the equipment is not regularly maintained or calibrated inaccurately during use, deviations may occur during detection. The operator's technical level and operational norms are also important factors affecting detection deviations. The state and uniformity of the steel sample also have a great impact on the spectral analysis results. Changes in environmental conditions will also affect the stability of spectral analysis. Therefore, it is necessary to obtain the deviation law, analyze the cause of the error according to the deviation law, calculate the average deviation value according to the deviation law, and after obtaining multiple deviation values, perform statistical analysis to find out the law of the deviation value. By analyzing the deviation values, the law can be identified. After finding the deviation law, the measurement results can be corrected and sorted according to these laws to make them closer to the true composition of the steel sample.

[0027] S400, acquiring sample measurement data, performing correction according to the average deviation value, obtaining corrected first measurement data, and sending the first measurement data to a display terminal.

[0028] In this step, sample measurement data is obtained. For systematic deviations, a direct correction method can be used. For example, if it is determined that the measurement results are generally low, the average value of the deviation can be added back to each measurement result for compensation correction; for random deviations, the impact of the error can be reduced by taking the average value through multiple measurements. Random errors usually follow a normal distribution, and taking the average of multiple measurements will be closer to the true value; for periodic deviations, it is necessary to find out the root cause and make adjustments, or correct it according to the periodic law. For example, if the ambient temperature has a significant impact on the measurement results, compensation calculations can be performed within a certain temperature range; Different correction methods can be used for different deviation types to obtain the corrected first measurement data, and send the first measurement data to the display terminal. After collating and correcting the data, the purpose of summarizing is to extract useful information and help understand the overall trend of the measurement results. Commonly used summarizing methods include statistical analysis, chart display, data comparison, etc.

[0029] like Figure 2 As shown, as a preferred embodiment of the present invention, the step of obtaining the measurement data of a standard steel sample, wherein the standard steel sample is a steel sample with a clear chemical composition, determining the accuracy of the instrument according to the measurement data of the standard steel sample, and obtaining the deviation value according to the determination result specifically includes: S201, obtaining measurement data of a standard steel sample, obtaining actual data of the standard steel sample, and comparing the measurement data of the standard steel sample with the actual data of the standard steel sample.

[0030] In this step, obtain the measurement data of standard steel samples. Standard steel samples usually refer to samples with known and certified chemical compositions. Using these standard samples for measurement can help researchers confirm the accuracy of the instrument and calculate the deviation value. Standard steel samples are usually provided by relevant institutions (such as national standards laboratories) and have clear chemical compositions, which are suitable for instrument calibration and performance verification.

[0031] The actual data of the standard steel sample is obtained, and the measurement data of the standard steel sample is compared with the actual data of the standard steel sample detected by the spectrometer. According to the measurement results, the accuracy of the instrument can be determined by the measurement results.

[0032] S202, obtaining a comparison result and an error threshold, wherein the error threshold is used to determine whether the instrument can be used. If the comparison result is within the error threshold, it is determined that the instrument can be used.

[0033] In this step, the comparison results are obtained. If the measured data of the standard steel sample is consistent with the actual data of the standard steel sample without error, it means that the detection result of the spectrometer is correct. If there is an error between the measured data of the standard steel sample and the actual data of the standard steel sample, the error value is compared with the threshold. The threshold is set to ±5%. If the error value is within the threshold range, the instrument is considered to be accurate; if it exceeds the range, it is necessary to consider recalibrating the instrument or reviewing the operating process.

[0034] S203, determining the accuracy of the instrument according to the comparison result, and obtaining a deviation value according to the determination result.

[0035] In this step, the accuracy of the instrument is determined based on the comparison results. If the error value is within the threshold range, the instrument detection result is determined to be accurate. The deviation value is obtained based on the determination result. The deviation value is the difference between the measured value and the theoretical value. The calculation formula is as follows: Deviation value = measured value − theoretical value; Check the deviation value of each element to determine whether it is within the acceptable range. The relative deviation can be further calculated to evaluate the relative accuracy of each measurement. Relative deviation = deviation value / theoretical value × 100%.

[0036] like Figure 3 As shown, as a preferred embodiment of the present invention, the steps of obtaining multiple deviation values, obtaining deviation rules, analyzing the error causes according to the deviation rules, calculating the average deviation value according to the deviation rules, and using the average deviation value to correct the measured value specifically include: S301, obtaining multiple deviation values, obtaining deviation patterns, wherein the obtained deviation patterns include systematic deviation, random deviation and periodic deviation, and determining the pattern type.

[0037] In this step, multiple deviation values ​​are obtained. After obtaining multiple deviation values, statistical analysis can be performed to find the pattern of the deviation values. If the deviation values ​​of multiple measurements are close or show a certain regularity, such as most of the deviations are negative or positive, it may indicate that there is a systematic error. For example, if the calibration of the spectrometer is inaccurate or there is a consistency problem in the sample processing method, it is a systematic deviation; If the deviation value distribution has no obvious regularity and the standard deviation is large, it may be caused by random errors in the experiment, such as ambient temperature fluctuations, inconsistent sample surface conditions, etc. In this case, the random error can be smoothed by increasing the number of measurements, which is a random deviation; If the deviation value changes with time, environmental conditions, etc. and shows periodic fluctuations, then we can consider whether there are factors such as instrument aging, instability of the experimental environment, etc., which is a periodic deviation.

[0038] S302, analyzing the cause of the error according to the deviation law, obtaining the deviation value distribution law, and calculating the average deviation value according to the deviation law.

[0039] In this step, the cause of the error is analyzed according to the deviation law, the distribution law of the deviation value is obtained, the average value of all deviation values ​​is calculated, and whether there is a systematic deviation is determined. If the average deviation is negative or positive, it may mean that some problems in the instrument or operation process cause the overall measurement result to be too high or too low; Calculate the standard deviation of the deviation value to evaluate the fluctuation range of the deviation. If the standard deviation is large, it means that there are many random errors in the measurement process, and further control of experimental conditions may be required; Calculate the standard deviation of the deviation values ​​to assess the fluctuation range of the deviation. If the standard deviation is large, it means that there are many random errors in the measurement process, and further control of experimental conditions may be required.

[0040] Average deviation = sum of deviation values ​​ / number of deviation values Assume that when analyzing the silicon (Si) content of a steel sample, 5 measurements are taken and the results are -0.05%, -0.02%, -0.01%, -0.03%, and -0.04%. The average deviation = (-0.05 + -0.02 + -0.01 + -0.03 + -0.04) / 5 = -0.03%.

[0041] S303, obtaining a verification result of the average deviation value, wherein the verification adopts multiple measurements, and the validity of the deviation value is judged according to the verification result.

[0042] In this step, the average deviation value verification result is obtained, and multiple measurements are performed again to check whether the deviation-corrected result is closer to the theoretical value. By measuring the standard sample, the deviation between the corrected silicon (Si) content and the standard value is reduced, proving that the correction is effective, which indicates the validity of the deviation value.

[0043] like Figure 4 As shown, as a preferred embodiment of the present invention, the steps of acquiring sample measurement data, correcting according to the average deviation value, obtaining the corrected first measurement data, and sending the first measurement data to the display terminal specifically include: S401, acquiring sample measurement data, correcting it according to the average deviation value, and filtering out abnormal data, wherein the abnormal data is data with a large difference between the original data and the corrected data.

[0044] In this step, sample measurement data is obtained to ensure that all measurement data have been corrected for deviations. The original data is compared with the corrected data to filter out abnormal data. All corrected measurement data are classified and sorted, usually according to element composition, sample batch, time and other classification dimensions, so as to facilitate subsequent summary; For example, when measuring the silicon (Si) content of steel samples, they can be classified and sorted according to the measurement time or sample batch.

[0045] S402, obtaining the corrected first measurement data, and performing statistical analysis based on the first measurement data, wherein the statistical analysis includes calculating a mean value, a standard deviation, and a maximum value.

[0046] In this step, the corrected first measurement data is obtained. The first measurement data is obtained after the sample measurement data is corrected. After the data is sorted and corrected, the summary is to extract useful information and help understand the overall trend of the measurement results. Commonly used summarization methods include statistical analysis, chart display, data comparison, etc. Calculate the average value of the corrected data as an estimate of the true composition of the steel sample, analyze the discreteness of the data, determine whether the corrected data is more stable, statistically analyze the extreme data in the measured values, and analyze the effectiveness of deviation control.

[0047] S403, drawing a chart based on the statistical analysis, and sending the chart to a display terminal.

[0048] In this step, charts are drawn based on statistical analysis. In order to understand the data more intuitively, the data before and after correction can be drawn into charts, such as line charts, bar charts, scatter charts, etc., to help identify trends and patterns in the measurement data.

[0049] Use line graphs to show the changes in measured values ​​over time or sample numbers, and compare before and after correction; use bar graphs to compare the composition differences of different batches of samples or under different measurement conditions; use scatter plots to show the distribution of different measured values ​​and analyze the randomness of deviations; Sending charts to the display terminal, converting the corrected data into a suitable format, and uploading it to the display terminal via the network or local connection can ensure that the measurement data is effectively managed and displayed to better support decision-making and analysis.

[0050] like Figure 5 As shown, a correction system based on multiple steel grade detection results is provided in an embodiment of the present invention, and the system includes: The preparation module 100 is used to obtain sample data, which includes the surface state, size and shape of the steel sample, and to obtain experimental data, which includes instrument data and parameter data.

[0051] In this system, the preparation module 100 obtains sample data, and the sample data mainly includes the surface state of the steel sample, which includes surface cleanliness, surface smoothness and surface treatment state, whether the surface of the steel sample is clean, whether there are oxides, oil stains or other contaminants. This will directly affect the accuracy of the spectral analysis, whether the surface of the steel sample is clean, whether there are oxides, oil stains or other contaminants. This will directly affect the accuracy of the spectral analysis, whether the surface of the steel sample is clean, whether there are oxides, oil stains or other contaminants. This will directly affect the accuracy of the spectral analysis; The specific size of the sample (such as length, width and thickness) has an important impact on the detection effect of the spectrometer. A sample that is too small may lead to unstable signals. The geometric shape of the sample (such as cylindrical, square, flat, etc.) may affect the incident angle and reflection characteristics of the laser or light beam. The overall volume of the sample may affect the signal intensity and detection range of the instrument during analysis. Experimental data are divided into instrument data and parameter data, which are used to describe the specific operation of the experiment and the status of the instrument, such as the specific model of the spectrometer used, such as laser induced breakdown spectrometer (LIBS) or atomic emission spectrometer (AES), the working status of the instrument, such as temperature, humidity, working voltage, light source type, etc. These factors will affect the stability and results of the measurement; The detection parameters set, such as integration time, excitation power, gas flow rate, etc., which will affect the sensitivity and accuracy of the analysis results, the calibration curve or standard sample information used to ensure the reliability of the measurement results, the temperature, humidity, air pressure and other environmental data during the experiment, these factors may have an impact on the measurement results.

[0052] These data help researchers understand the relationship between experimental conditions and measurement results. By recording and organizing these data in a standardized manner, they can provide a reliable basis for subsequent analysis, deviation identification, and result correction.

[0053] The standard steel sample module 200 is used to obtain measurement data of a standard steel sample, wherein the standard steel sample is a steel sample with a clear chemical composition, and the accuracy of the instrument is determined based on the measurement data of the standard steel sample, and the deviation value is obtained based on the determination result.

[0054] In this system, the standard steel sample module 200 obtains the measurement data of the standard steel sample. The standard steel sample usually refers to a sample with known and certified chemical composition. The measurement using these standard samples can help researchers confirm the accuracy of the instrument and calculate the deviation value. Before measuring the standard steel sample, it is necessary to ensure the preparation of the instrument. Make sure that the spectrometer is properly calibrated before measurement. Set the instrument parameters according to the standard operating procedures, including integration time and excitation power. Determine the accuracy of the instrument based on the measurement data of the standard steel sample. If the deviation value is within the acceptable range, usually ±5%, the instrument is considered to be accurate. Obtain the deviation value based on the judgment result, deviation value = measured value − theoretical value.

[0055] The deviation value module 300 is used to obtain multiple deviation values, obtain deviation rules, analyze the error causes according to the deviation rules, and calculate the average deviation value according to the deviation rules. The average deviation value is used to correct the measurement value.

[0056] In this system, the deviation value module 300 obtains multiple deviation values. In the analysis of steel sample composition, deviation values ​​may appear during spectrometer detection. This phenomenon is relatively common in actual operations. The deviation value refers to the difference between the actual detection value and the theoretical value or standard value during multiple detection processes. It is necessary to determine the cause of the deviation value. For example, the performance and calibration status of the spectrometer will directly affect the accuracy of the detection.

[0057] If the equipment is not regularly maintained or calibrated inaccurately during use, deviations may occur during detection. The operator's technical level and operational norms are also important factors affecting detection deviations. The state and uniformity of the steel sample also have a great impact on the spectral analysis results. Changes in environmental conditions will also affect the stability of spectral analysis. Therefore, it is necessary to obtain the deviation law, analyze the cause of the error according to the deviation law, calculate the average deviation value according to the deviation law, and after obtaining multiple deviation values, perform statistical analysis to find out the law of the deviation value. By analyzing the deviation values, the law can be identified. After finding the deviation law, the measurement results can be corrected and sorted according to these laws to make them closer to the true composition of the steel sample.

[0058] The correction module 400 is used to obtain sample measurement data, perform correction according to the average deviation value, obtain the corrected first measurement data, and send the first measurement data to the display terminal.

[0059] In this system, the correction module 400 obtains sample measurement data, and a direct correction method can be used for systematic deviations. For example, if it is determined that the measurement results are generally low, the average value of the deviation can be added back to each measurement result for compensation correction; for random deviations, the impact of the error can be reduced by taking the average value through multiple measurements. Random errors usually follow a normal distribution, and taking the average value of multiple measurements will be closer to the true value; for periodic deviations, it is necessary to find out the root cause and make adjustments, or correct it according to the periodic law. For example, if the ambient temperature has a significant impact on the measurement results, compensation calculations can be performed within a certain temperature range; Different correction methods can be used for different deviation types to obtain the corrected first measurement data, and send the first measurement data to the display terminal. After collating and correcting the data, the purpose of summarizing is to extract useful information and help understand the overall trend of the measurement results. Commonly used summarizing methods include statistical analysis, chart display, data comparison, etc.

[0060] like Figure 6 As shown, as a preferred embodiment of the present invention, the standard steel sample module 200 includes: The standard steel sample unit 201 is used to obtain the standard steel sample measurement data, obtain the standard steel sample actual data, and compare the standard steel sample measurement data with the standard steel sample actual data.

[0061] In this module, the standard steel sample unit 201 obtains the measurement data of the standard steel sample. The standard steel sample usually refers to the sample with known and certified chemical composition. The measurement using these standard samples can help researchers confirm the accuracy of the instrument and calculate the deviation value. The standard steel sample is usually provided by relevant institutions (such as national standards laboratories), has a clear chemical composition, and is suitable for instrument calibration and performance verification.

[0062] The actual data of the standard steel sample is obtained, and the measurement data of the standard steel sample is compared with the actual data of the standard steel sample detected by the spectrometer. According to the measurement results, the accuracy of the instrument can be determined by the measurement results.

[0063] The instrument determination unit 202 is used to obtain the comparison result and the error threshold. The error threshold is used to determine whether the instrument can be used. If the comparison result is within the error threshold, it is determined that the instrument can be used.

[0064] In this module, the instrument determination unit 202 obtains the comparison result. If the measured data of the standard steel sample is consistent with the actual data of the standard steel sample without error, it means that the detection result of the spectrometer is correct. If there is an error between the measured data of the standard steel sample and the actual data of the standard steel sample, the error value is compared with the threshold. The threshold is set to ±5%. If the error value is within the threshold range, the instrument is considered to be accurate; if it exceeds the range, it is necessary to consider recalibrating the instrument or reviewing the operating process.

[0065] The deviation value unit 203 is used to determine the accuracy of the instrument according to the comparison result and obtain the deviation value according to the determination result.

[0066] In this module, the deviation value unit 203 determines the accuracy of the instrument according to the comparison result. If the error value is within the threshold range, the instrument detection result is determined to be accurate. The deviation value is obtained according to the determination result. The deviation value is the difference between the measured value and the theoretical value. The calculation formula is as follows: deviation value = measured value − theoretical value; Check the deviation value of each element to determine whether it is within the acceptable range. The relative deviation can be further calculated to evaluate the relative accuracy of each measurement. Relative deviation = deviation value / theoretical value × 100%.

[0067] like Figure 7 As shown, as a preferred embodiment of the present invention, the deviation value module 300 includes: The deviation rule unit 301 is used to obtain multiple deviation values, obtain deviation rules, and the obtained deviation rules include systematic deviation, random deviation and periodic deviation, and determine the rule type.

[0068] In this module, the deviation rule unit 301 obtains multiple deviation values. After obtaining multiple deviation values, statistical analysis can be performed to find the law of the deviation values. If the deviation values ​​of multiple measurements are close to or show a certain regularity, such as most of the deviations are negative or positive, it may indicate that there is a systematic error. For example, if the calibration of the spectrometer is inaccurate or there is a consistency problem in the sample processing method, it is a systematic deviation; If the deviation value distribution has no obvious regularity and the standard deviation is large, it may be caused by random errors in the experiment, such as ambient temperature fluctuations, inconsistent sample surface conditions, etc. In this case, the random error can be smoothed by increasing the number of measurements, which is a random deviation; If the deviation value changes with time, environmental conditions, etc. and shows periodic fluctuations, then we can consider whether there are factors such as instrument aging, instability of the experimental environment, etc., which is a periodic deviation.

[0069] The error analysis unit 302 is used to analyze the cause of the error according to the deviation law, obtain the deviation value distribution law, and calculate the average deviation value according to the deviation law.

[0070] In this module, the error analysis unit 302 analyzes the cause of the error according to the deviation law, obtains the distribution law of the deviation value, calculates the average value of all deviation values, and determines whether there is a systematic deviation. If the average deviation is negative or positive, it may mean that some problems in the instrument or operation process cause the overall measurement result to be too high or too low; Calculate the standard deviation of the deviation value to evaluate the fluctuation range of the deviation. If the standard deviation is large, it means that there are many random errors in the measurement process, and further control of experimental conditions may be required; Calculate the standard deviation of the deviation values ​​to assess the fluctuation range of the deviation. If the standard deviation is large, it means that there are many random errors in the measurement process, and further control of experimental conditions may be required.

[0071] Average deviation = sum of deviation values ​​ / number of deviation values Assume that when analyzing the silicon (Si) content of a steel sample, 5 measurements are taken and the results are -0.05%, -0.02%, -0.01%, -0.03%, and -0.04%. The average deviation = (-0.05 + -0.02 + -0.01 + -0.03 + -0.04) / 5 = -0.03%.

[0072] The verification unit 303 is used to obtain a verification result of the average deviation value, wherein the verification adopts multiple measurements and determines the validity of the deviation value according to the verification result.

[0073] In this module, the verification unit 303 obtains the average deviation value verification result, re-measures multiple times, and checks whether the result after deviation correction is closer to the theoretical value. By measuring the standard sample, the deviation between the corrected silicon (Si) content and the standard value is reduced, proving that the correction is effective, which indicates the validity of the deviation value.

[0074] like Figure 8 As shown, as a preferred embodiment of the present invention, the correction module 400 includes: The correction unit 401 is used to obtain sample measurement data, perform correction according to the average deviation value, and filter out abnormal data, where the abnormal data is data with a large difference between the original data and the corrected data.

[0075] In this module, the correction unit 401 obtains sample measurement data, ensures that all measurement data have been corrected for deviations, compares the original data with the corrected data, screens out abnormal data, and classifies and sorts all corrected measurement data, usually by element composition, sample batch, time and other classification dimensions, for subsequent summary; For example, when measuring the silicon (Si) content of steel samples, they can be classified and sorted according to the measurement time or sample batch.

[0076] The analysis unit 402 is used to obtain the corrected first measurement data and perform statistical analysis based on the first measurement data, wherein the statistical analysis includes calculating the mean value, standard deviation and maximum value.

[0077] In this module, the analysis unit 402 obtains the corrected first measurement data, and obtains the first measurement data after correcting the sample measurement data. After arranging and correcting the data, the induction and summary is to extract useful information and help understand the overall trend of the measurement results. Commonly used induction methods include statistical analysis, chart display, data comparison, etc. Calculate the average value of the corrected data as an estimate of the true composition of the steel sample, analyze the discreteness of the data, determine whether the corrected data is more stable, statistically analyze the extreme data in the measured values, and analyze the effectiveness of deviation control.

[0078] The display unit 403 is used to draw charts according to the statistical analysis and send the charts to the display terminal.

[0079] In this module, the display unit 403 draws charts based on statistical analysis. In order to understand the data more intuitively, the data before and after correction can be drawn into charts, such as line charts, bar charts, scatter plots, etc., to help identify trends and patterns in the measurement data.

[0080] Use line graphs to show the changes in measured values ​​over time or sample numbers, and compare before and after correction; use bar graphs to compare the composition differences of different batches of samples or under different measurement conditions; use scatter plots to show the distribution of different measured values ​​and analyze the randomness of deviations; Sending charts to the display terminal, converting the corrected data into a suitable format, and uploading it to the display terminal via the network or local connection can ensure that the measurement data is effectively managed and displayed to better support decision-making and analysis.

[0081] In one embodiment, a computer device is provided, the computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following steps are implemented: Acquire sample data, the sample data including the surface state, size and shape of the steel sample, and acquire experimental data, the experimental data including instrument data and parameter data; Obtaining measurement data of a standard steel sample, wherein the standard steel sample is a steel sample with a clear chemical composition, determining the accuracy of the instrument according to the measurement data of the standard steel sample, and obtaining a deviation value according to the determination result; Obtain multiple deviation values, obtain deviation rules, analyze the error causes according to the deviation rules, calculate the average deviation value according to the deviation rules, and use the average deviation value to correct the measured value; The sample measurement data is acquired, corrected according to the average deviation value, the corrected first measurement data is obtained, and the first measurement data is sent to the display terminal.

[0082] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the processor performs the following steps: Acquire sample data, the sample data including the surface state, size and shape of the steel sample, and acquire experimental data, the experimental data including instrument data and parameter data; Obtaining measurement data of a standard steel sample, wherein the standard steel sample is a steel sample with a clear chemical composition, determining the accuracy of the instrument according to the measurement data of the standard steel sample, and obtaining a deviation value according to the determination result; Obtain multiple deviation values, obtain deviation rules, analyze the error causes according to the deviation rules, calculate the average deviation value according to the deviation rules, and use the average deviation value to correct the measured value; The sample measurement data is acquired, corrected according to the average deviation value, the corrected first measurement data is obtained, and the first measurement data is sent to the display terminal.

[0083] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0084] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0085] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0086] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0087] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A correction method based on multiple steel grade detection results, characterized in that: The method comprises: Acquire sample data, the sample data including the surface state, size and shape of the steel sample, and acquire experimental data, the experimental data including instrument data and parameter data; Obtaining measurement data of a standard steel sample, wherein the standard steel sample is a steel sample with a clear chemical composition, determining the accuracy of the instrument according to the measurement data of the standard steel sample, and obtaining a deviation value according to the determination result; Obtain multiple deviation values, obtain deviation rules, analyze the error causes according to the deviation rules, calculate the average deviation value according to the deviation rules, and use the average deviation value to correct the measured value; The sample measurement data is acquired, corrected according to the average deviation value, the corrected first measurement data is obtained, and the first measurement data is sent to the display terminal.

2. The method for correcting the detection results of multiple steel grades according to claim 1 is characterized in that: The step of obtaining the measurement data of the standard steel sample, wherein the standard steel sample is a steel sample with a clear chemical composition, determining the accuracy of the instrument according to the measurement data of the standard steel sample, and obtaining the deviation value according to the determination result specifically includes: Obtaining measurement data of the standard steel sample, obtaining actual data of the standard steel sample, and comparing the measurement data of the standard steel sample with the actual data of the standard steel sample; Obtaining a comparison result and an error threshold, wherein the error threshold is used to determine whether the instrument can be used. If the comparison result is within the error threshold, it is determined that the instrument can be used; The accuracy of the instrument is determined based on the comparison results, and the deviation value is obtained based on the determination results.

3. The method for correcting the detection results of multiple steel grades according to claim 2 is characterized in that: The step of obtaining multiple deviation values, obtaining a deviation rule, analyzing the error cause according to the deviation rule, calculating an average deviation value according to the deviation rule, and using the average deviation value to correct the measured value specifically includes: Obtain multiple deviation values, obtain deviation rules, the obtained deviation rules include systematic deviation, random deviation and periodic deviation, and determine the rule type; Analyze the cause of the error according to the deviation law, obtain the deviation value distribution law, and calculate the average deviation value according to the deviation law; The average deviation value verification result is obtained, wherein the verification adopts multiple measurements and the validity of the deviation value is judged according to the verification result.

4. The method for correcting the detection results of multiple steel grades according to claim 3 is characterized in that: The step of acquiring sample measurement data, correcting it according to the average deviation value, obtaining corrected first measurement data, and sending the first measurement data to the display terminal specifically includes: Obtain sample measurement data, correct it according to the average deviation value, and filter out abnormal data, where the difference between the original data and the corrected data is too large; Obtaining the corrected first measurement data, and performing statistical analysis based on the first measurement data, wherein the statistical analysis includes calculating a mean value, a standard deviation, and a maximum value; Draw charts based on statistical analysis and send them to the display terminal.

5. The method for correcting the detection results of multiple steel grades according to claim 4 is characterized in that: The parameter data includes spectrometer excitation time and spectrometer excitation energy.

6. A correction system based on multiple steel grade detection results, characterized in that: The system comprises: A preparation module is used to obtain sample data, including surface state, size and shape of the steel sample, and to obtain experimental data, including instrument data and parameter data; The standard steel sample module obtains the measurement data of the standard steel sample, wherein the standard steel sample is a steel sample with a clear chemical composition, determines the accuracy of the instrument according to the measurement data of the standard steel sample, and obtains the deviation value according to the determination result; The deviation value module obtains multiple deviation values, obtains the deviation law, analyzes the error cause according to the deviation law, and calculates the average deviation value according to the deviation law. The average deviation value is used to correct the measurement value; The correction module obtains the sample measurement data, performs correction according to the average deviation value, obtains the corrected first measurement data, and sends the first measurement data to the display terminal.

7. The system for correcting the detection results of multiple steel grades according to claim 6, characterized in that: The standard steel sample module includes: Standard steel sample unit, obtains standard steel sample measurement data, obtains standard steel sample actual data, and compares standard steel sample measurement data with standard steel sample actual data; An instrument determination unit obtains a comparison result and an error threshold, wherein the error threshold is used to determine whether the instrument can be used. If the comparison result is within the error threshold, the instrument is determined to be usable. The deviation value unit determines the accuracy of the instrument according to the comparison result and obtains the deviation value according to the determination result.

8. The system for correcting the detection results of multiple steel grades according to claim 7, characterized in that: The deviation value module includes: A deviation law unit, which obtains multiple deviation values, obtains deviation laws, wherein the obtained deviation laws include systematic deviations, random deviations and periodic deviations, and determines the law type; The error analysis unit analyzes the error cause according to the deviation law, obtains the deviation value distribution law, and calculates the average deviation value according to the deviation law; The verification unit obtains a verification result of the average deviation value, wherein the verification adopts multiple measurements and determines the validity of the deviation value according to the verification result.

9. The system for correcting the detection results of multiple steel grades according to claim 8, characterized in that: The correction module comprises: A correction unit, which obtains sample measurement data, corrects it according to the average deviation value, and screens out abnormal data, wherein the abnormal data is data whose difference between the original data and the corrected data is too large; An analysis unit, which obtains the corrected first measurement data and performs statistical analysis based on the first measurement data, wherein the statistical analysis includes calculating a mean value, a standard deviation, and a maximum value; The display unit draws a chart based on the statistical analysis and sends the chart to the display terminal.

10. The system for correcting the detection results of multiple steel grades according to claim 9, characterized in that: The parameter data includes spectrometer excitation time and spectrometer excitation energy.

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