A method for preprocessing temperature data of a crystallizer expert system

Abstract

The present application relates to a kind of crystallizer expert system temperature data preprocessing method, belong to metallurgical industry continuous casting method technical field.The technical scheme of the present application is: the thickness of each face copper plate of crystallizer is measured when continuous casting machine is stopped;After installation and water are passed on the crystallizer, each thermocouple temperature correction and the calculation of each thermocouple temperature standard deviation are carried out;After temperature correction, the frequency spectrum analysis and processing of each thermocouple temperature value are carried out respectively;Each thermocouple temperature value is operated filtering;Temperature value is corrected according to copper plate thickness;The limit of temperature value is carried out using the normal range of thermocouple temperature.The beneficial effects of the present application are: the accuracy of crystallizer thermocouple temperature data is improved, can provide accurate and effective thermocouple temperature data for crystallizer expert system, and guarantee the normal work of crystallizer expert system.

Description

Technical Field

[0001] The invention relates to a preprocessing method for temperature data of a crystallizer expert system, and belongs to the technical field of continuous casting methods in the metallurgical industry. Background Art

[0002] In the 1950s and 1960s, continuous casting technology became widely used in steel mills in developed steel-producing countries such as the United States, Japan, Europe, and South Korea, achieving significant economic benefits. Continuous casting technology also gradually gained widespread application in my country starting in the 1980s and 1990s. Entering the 21st century, my country's continuous casting technology entered a period of rapid development. To date, my country's total steel production has exceeded 1 billion tons, and the continuous casting ratio in the steel industry exceeds 99%. With the rapid development of continuous casting technology worldwide, the trend is towards high casting speeds, high utilization rates, and high quality. However, excessively high casting speeds inevitably lead to unstable heat transfer during continuous casting, resulting in a fragile and uneven solidified strand shell. This inevitably increases the incidence of strand sticking and steel breakout in continuous casting machines, posing unprecedented challenges to continuous casting mold expert systems. With the emerging requirements of continuous casting production, the development of continuous casting mold expert systems based on high-precision, high-accuracy, high-stability, and high-interference resistance of mold thermocouple data has become an urgent need, and experts and scholars at home and abroad have conducted extensive research on this issue.

[0003] During high-speed continuous casting, a fixed number of thermocouples are embedded in appropriate locations within the mold copper plate to perform contact measurement of the billet surface temperature. This allows for real-time monitoring of temperature changes across the billet surface within the continuous casting machine's mold. When billet adhesion occurs, this inevitably alters the heat transfer environment between the billet and the mold, leading to changes in billet surface temperature. This detection method is simple in principle, easy to operate, highly accurate, and highly responsive, helping to locate billet surface defects. Thermocouple temperature is often used as the most important foundational data for various modules of the mold expert system and as a basis for prediction models.

[0004] The detection method based on direct contact measurement of physical temperature is often greatly affected by the on-site working environment. The continuous casting production process faces complex on-site environments such as high temperature, humidity, and dust. During use, thermocouples face the actual problem of inaccurate data in the original signal due to poor shielding, electromagnetic interference, poor contact, etc. The distorted signal will cause the crystallizer expert system to make incorrect judgments. Summary of the Invention

[0005] The purpose of the present invention is to provide a preprocessing method for the temperature data of a crystallizer expert system. Through operations such as correction, limiting, spectrum analysis and filtering, the problem of signal distortion of the original temperature signal of the crystallizer thermocouple caused by poor shielding, electromagnetic interference, poor contact and changes in the thickness of the copper plate is solved, the accuracy of the crystallizer thermocouple temperature data is improved, and accurate and effective thermocouple temperature data can be provided for the crystallizer expert system, thereby ensuring the normal operation of the crystallizer expert system and effectively solving the above-mentioned problems existing in the background technology.

[0006] The technical solution of the present invention is: a method for preprocessing temperature data of a crystallizer expert system, comprising the following steps:

[0007] (1) Measure the thickness of the copper plates on each side of the mold when the continuous casting machine is stopped;

[0008] (2) After the crystallizer is installed online and water is passed through, the temperature of each thermocouple is calibrated and the standard deviation of the temperature of each thermocouple is calculated;

[0009] (3) After temperature correction, spectrum analysis and processing are performed on each thermocouple temperature value;

[0010] (4) Perform filtering operation on each thermocouple temperature value;

[0011] (5) Correct the temperature value according to the thickness of the copper plate;

[0012] (6) Use the normal range of thermocouple temperature to limit the temperature value.

[0013] In step (2), the temperature of each thermocouple is calibrated by collecting the values ​​of the crystallizer inlet water temperature for 1 minute and averaging them as T in At the same time, calculate the average temperature of each thermocouple within 1 minute and record it as T1, T2...T n , the subsequent real-time data of each thermocouple temperature is corrected according to the following formula: T 校正 =T+T in -T n , where T 校正 is the temperature value after calibration of the thermocouple, ℃, and T is the temperature value measured by the thermocouple in real time, ℃.

[0014] In the step (2), the method for calculating the standard deviation of each thermocouple temperature is to collect the temperature data of each thermocouple for 1 minute continuously, and obtain the standard deviation of the temperature data of each thermocouple for 1 minute and record it as R1, R2...R n .

[0015] In the step (3), the spectrum analysis method is to continuously sample the temperature value of each thermocouple at a time interval of 0.25s for 5 minutes; repeat this process 6 times to obtain 6 groups of different temperature data, each group of temperature data containing 1200 values; perform fast Fourier transform on each group of temperature data to obtain the spectrum of the group of temperature data, and when the maximum intensity in the spectrum of the 6 groups of temperature data are all at the same frequency point, mark the thermocouple and record the frequency point where the maximum intensity is located.

[0016] In the step (3), the spectrum processing method is as follows: each time new thermocouple temperature data is collected, the temperature data of the marked thermocouple for the last 5 minutes is fast Fourier transformed to obtain the spectrum of the set of temperature data; after removing the recorded frequency points in the spectrum, the spectrum is inverse Fourier transformed; the transformed data is used as spectrum-processed data for subsequent use.

[0017] In step (4), the filtering operation method is that the current temperature value is calculated as follows: Where T is the temperature value after filtering, in °C; T m is the current temperature after the above steps, in °C; T k-1 is the temperature value after the method is used at the previous moment, in °C; a is the empirical coefficient, determined according to the actual crystallizer heat transfer conditions (taken as 0.1-0.3); b is the empirical coefficient, determined according to the actual crystallizer thermocouple hardware conditions (taken as 0.3-0.6); R is the standard deviation of the thermocouple temperature calculated in step 2; T a is the comprehensive temperature deviation, in °C, calculated as follows: T a =0.1×(T m -T k-4 )+0.2×(T m -T k-3 )+0.3×(T m -T k-2 )+0.4×(T m -T k-1 ), where T k-1 is the temperature value after the method is used at the previous moment, in °C; T k-2 is the temperature value after the method is used at the first two moments, in °C; T k-3 is the temperature value after processing by this method at the first three moments, in °C; T k-4 The temperature value after processing by this method at the first four moments, in °C.

[0018] In step (5), the method for correcting the temperature value is to calculate according to the following formula: Where T is the corrected temperature, in °C; T0 is the temperature value after the above steps, in °C; δ is the thickness of the copper plate measured in step 1, in mm; δ0 is the thickness of the new copper plate, in mm; δ min The minimum thickness allowed for copper plate, in mm.

[0019] In step (6), the normal range of the thermocouple temperature is 50-200°C; the method of limiting the temperature value is that the temperature value less than 50°C is limited to 50°C, and the temperature value greater than 200°C is limited to 200°C.

[0020] The beneficial effects of the present invention are as follows: through operations such as correction, limiting, spectrum analysis and filtering, the signal distortion problem of the original signal of the crystallizer thermocouple temperature caused by poor shielding, electromagnetic interference, poor contact and changes in the copper plate thickness is solved, the accuracy of the crystallizer thermocouple temperature data is improved, and accurate and effective thermocouple temperature data can be provided for the crystallizer expert system to ensure the normal operation of the crystallizer expert system. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solutions and advantages of the invention implementation cases clearer, the technical solutions in the invention implementation cases will be clearly and completely described below. Obviously, the implementation cases described are only a small part of the implementation cases of the invention, rather than all the implementation cases. Based on the implementation cases in the invention, all other implementation cases obtained by ordinary technicians in this field without making creative work are within the scope of protection of the invention.

[0022] A method for preprocessing temperature data of a crystallizer expert system comprises the following steps:

[0023] (1) Measure the thickness of the copper plates on each side of the mold when the continuous casting machine is stopped;

[0024] (2) After the crystallizer is installed online and water is passed through, the temperature of each thermocouple is calibrated and the standard deviation of the temperature of each thermocouple is calculated;

[0025] (3) After temperature correction, spectrum analysis and processing are performed on each thermocouple temperature value;

[0026] (4) Perform filtering operation on each thermocouple temperature value;

[0027] (5) Correct the temperature value according to the thickness of the copper plate;

[0028] (6) Use the normal range of thermocouple temperature to limit the temperature value.

[0029] In step (2), the temperature of each thermocouple is calibrated by collecting the values ​​of the crystallizer inlet water temperature for 1 minute and averaging them as T in At the same time, calculate the average temperature of each thermocouple within 1 minute and record it as T1, T2...T n , the subsequent real-time data of each thermocouple temperature is corrected according to the following formula: T 校正 =T+T in -T n , where T 校正 is the temperature value after calibration of the thermocouple, ℃, and T is the temperature value measured by the thermocouple in real time, ℃.

[0030] In the step (2), the method for calculating the standard deviation of each thermocouple temperature is to collect the temperature data of each thermocouple for 1 minute continuously, and obtain the standard deviation of the temperature data of each thermocouple for 1 minute and record it as R1, R2...R n .

[0031] In the step (3), the spectrum analysis method is to continuously sample the temperature value of each thermocouple at a time interval of 0.25s for 5 minutes; repeat this process 6 times to obtain 6 groups of different temperature data, each group of temperature data containing 1200 values; perform fast Fourier transform on each group of temperature data to obtain the spectrum of the group of temperature data, and when the maximum intensity in the spectrum of the 6 groups of temperature data are all at the same frequency point, mark the thermocouple and record the frequency point where the maximum intensity is located.

[0032] In the step (3), the spectrum processing method is as follows: each time new thermocouple temperature data is collected, the temperature data of the marked thermocouple for the last 5 minutes is fast Fourier transformed to obtain the spectrum of the set of temperature data; after removing the recorded frequency points in the spectrum, the spectrum is inverse Fourier transformed; the transformed data is used as spectrum-processed data for subsequent use.

[0033] In step (4), the filtering operation method is that the current temperature value is calculated as follows: Where T is the temperature value after filtering, in °C; T m is the current temperature after the above steps, in °C; T k-1 is the temperature value after the method is used at the previous moment, in °C; a is the empirical coefficient, determined according to the actual crystallizer heat transfer conditions (taken as 0.1-0.3); b is the empirical coefficient, determined according to the actual crystallizer thermocouple hardware conditions (taken as 0.3-0.6); R is the standard deviation of the thermocouple temperature calculated in step 2; T a is the comprehensive temperature deviation, in °C, calculated as follows: T a =0.1×(T m-T k-4 )+0.2×(T m -T k-3 )+0.3×(T m -T k-2 )+0.4×(T m -T k-1 ), where T k-1 is the temperature value after the method is used at the previous moment, in °C; T k-2 is the temperature value after the method is used at the first two moments, in °C; T k-3 is the temperature value after processing by this method at the first three moments, in °C; T k-4 The temperature value after processing by this method at the first four moments, in °C.

[0034] In step (5), the method for correcting the temperature value is to calculate according to the following formula: Where T is the corrected temperature, in °C; T0 is the temperature value after the above steps, in °C; δ is the thickness of the copper plate measured in step 1, in mm; δ0 is the thickness of the new copper plate, in mm; δ min The minimum thickness allowed for copper plate, in mm.

[0035] In step (6), the normal range of the thermocouple temperature is 50-200°C; the method of limiting the temperature value is that the temperature value less than 50°C is limited to 50°C, and the temperature value greater than 200°C is limited to 200°C.

[0036] In practical applications, the operating steps of the present invention are as follows:

[0037] The first step is to measure the thickness of the copper plates on each side of the crystallizer when the continuous casting machine is stopped. In this embodiment, the thickness of the two wide copper plates of the crystallizer measured when the continuous casting machine is stopped is 35 mm, and the thickness of the two narrow copper plates is 32 mm.

[0038] The second step is to calibrate the temperature of each thermocouple after the crystallizer is installed and water is supplied. The calibration method for each thermocouple temperature is to collect the crystallizer water inlet temperature values ​​for 1 minute and calculate the average value and record it as T in At the same time, calculate the average temperature of each thermocouple within 1 minute and record it as T1, T2...T n The subsequent real-time data of each thermocouple temperature is corrected according to the following formula: 校正 =T+T in -T n , where T 校正is the temperature value after the thermocouple is calibrated, ℃, T is the temperature value measured by the thermocouple in real time, ℃. In this embodiment, 240 data of the crystallizer inlet water temperature are collected continuously for 1 minute, and the average value is recorded as T in , T in is 28.30℃. At the same time, calculate the average temperature of each thermocouple within 1 minute and record it as T1, T2...T n The average temperature T of a thermocouple n n The subsequent real-time data of the thermocouple are corrected according to the following formula: 校正 =T+28.30-29.35=T-1.05.

[0039] Then calculate the standard deviation of each thermocouple temperature. The calculation method of the standard deviation of each thermocouple temperature is to collect the temperature data of each thermocouple for 1 minute continuously, and calculate the standard deviation of the temperature data of each thermocouple for 1 minute and record it as R1, R2...R n For example, the standard deviation of the temperature data of a certain thermocouple n is 0.056.

[0040] The third step, after temperature correction, spectrum analysis and processing are performed on each thermocouple temperature value. The method of spectrum analysis is to perform continuous sampling of the temperature value of each thermocouple at a time interval of 0.25s for 5 minutes. This process is repeated 6 times to obtain 6 groups of different temperature data, each group of temperature data containing 1200 values. Fast Fourier transform is performed on each group of temperature data to obtain the spectrum of this group of temperature data. When the intensity maximum values ​​in the spectrum of the 6 groups of temperature data are all at the same frequency point, the thermocouple is marked and the frequency point where the intensity maximum value is located is recorded. In the present embodiment, in the spectrum diagram obtained after fast Fourier transform of the 6 groups of temperature data of a certain thermocouple n, the intensity maximum values ​​are all at the 0.25Hz frequency point, so the thermocouple n is marked and the frequency point where the intensity maximum value is located is recorded as 0.25Hz.

[0041] The spectrum processing method is as follows: each time new thermocouple temperature data is collected, a fast Fourier transform is performed on the temperature data of the marked thermocouple for the most recent 5 minutes to obtain the spectrum of the set of temperature data. After removing the recorded frequency points from the spectrum, the spectrum is inversely Fourier transformed. The transformed data is used as the spectrum-processed data for subsequent use. In this embodiment, thermocouple n is marked, so a fast Fourier transform is performed on the temperature data detected by the thermocouple for the most recent 5 minutes to obtain the spectrum of the set of temperature data. After removing the recorded frequency point of 0.25 Hz from the spectrum, the processed spectrum is inversely Fourier transformed. The transformed data is used as the spectrum-processed data for subsequent use.

[0042] The fourth step is to filter each thermocouple temperature value. The filtering method is to calculate the current temperature value according to the following formula: Where T is the temperature value after filtering, in °C; T m is the current temperature after the above steps, in °C; T k-1 is the final temperature value after processing using the method of the present invention at the previous moment, in °C (this moment is the actual temperature detection value during the first calculation); a is the empirical coefficient, which is 0.2 in this embodiment; b is the empirical coefficient, which is 0.4 in this embodiment; R is the standard deviation of the thermocouple temperature calculated in step 2; T a is the comprehensive temperature deviation, in °C, calculated as follows: T a =0.1×(T m -T k-4 )+0.2×(T m -T k-3 )+0.3×(T m -T k-2 )+0.4×(T m -T k-1 ), where T k-1 is the temperature value after the method is used at the previous moment, in °C; T k-2 is the temperature value after the method is used at the first two moments, in °C; T k-3 is the temperature value after processing by this method at the first three moments, in °C; T k-4 The temperature value after the previous four moments are processed by this method, in degrees Celsius. (If the previous moments do not exist, the actual temperature value is used.)

[0043] Step 5: Correct the temperature value according to the thickness of the copper plate. The method for correcting the temperature value is to calculate according to the following formula: Where T is the corrected temperature, in °C; T0 is the temperature value after the above steps, in °C; δ is the thickness of the copper plate measured in step 1, in mm; δ0 is the thickness of the new copper plate, in mm; δ min is the minimum allowable thickness of the copper plate, in mm. In this embodiment, the thickness of the two wide copper plates is measured to be 35 mm, and the thickness of the two narrow copper plates is measured to be 32 mm. The thickness of each new copper plate is 40 mm, and the minimum allowable thickness of each copper plate is 28 mm. Therefore, the wide-side thermocouple temperature is calculated as T = 0.9583 × T0, and the narrow-side thermocouple temperature is calculated as T = 0.9333 × T0.

[0044] Step 6: Use the normal range of thermocouple temperature to limit the temperature value. The normal range of thermocouple temperature is 50-200℃; the method of limiting the temperature value is that the temperature value less than 50℃ is limited to 50℃, and the temperature value greater than 200℃ is limited to 200℃.

[0045] The present invention solves the problem of systematic deviation in thermocouple temperature measurement by correcting the thermocouple data and the water temperature of the crystallizer during shutdown. It solves the problem of abnormal periodic fluctuation when the thermocouple is subject to electromagnetic interference through thermocouple spectrum analysis and processing. It minimizes the measurement accuracy deviation and environmental random error of thermocouple temperature measurement through targeted filtering algorithm design. It takes reasonable consideration of copper plate wear and temperature anomalies in the production process, and reasonably designs the sequence and coupling method of the series of methods. The method of the present invention solves the problem of signal distortion of the original signal of the crystallizer thermocouple temperature due to poor shielding, electromagnetic interference, poor contact and changes in copper plate thickness, and improves the accuracy of the crystallizer thermocouple temperature data. It can provide accurate and effective thermocouple temperature data for the crystallizer expert system to ensure the normal operation of the crystallizer expert system.

Claims

1. A method for preprocessing temperature data of a crystallizer expert system, characterized in that The following steps are involved: (1) Measure the thickness of the copper plates on each side of the mold when the continuous casting machine is stopped; (2) After the crystallizer is installed online and water is passed through, the temperature of each thermocouple is calibrated and the standard deviation of the temperature of each thermocouple is calculated; (3) After temperature correction, perform spectrum analysis and processing on each thermocouple temperature value; (4) Filter each thermocouple temperature value; (5) Correct the temperature value according to the thickness of the copper plate; (6) Use the normal range of thermocouple temperature to limit the temperature value; In step (4), the filtering operation method is to calculate the current temperature value according to the following formula: , where T is the temperature value after filtering, in °C; T m is the current temperature after the above steps, in °C; T k-1 is the temperature value after the method is used at the previous moment, in °C; a is the empirical coefficient, which is determined according to the actual crystallizer heat transfer conditions and is taken as 0.1-0.3; b is the empirical coefficient, which is determined according to the actual crystallizer thermocouple hardware conditions and is taken as 0.3-0.6; R is the standard deviation of the thermocouple temperature calculated in step (2); T a is the comprehensive temperature deviation, in °C, and is calculated as follows: , where T k-1 is the temperature value after the method is used at the previous moment, in °C; T k-2 is the temperature value after the method is used at the first two moments, in °C; T k-3 is the temperature value after processing by this method at the first three moments, in °C; T k-4 The temperature values ​​after processing by this method at the first four moments are in °C.

2. The method for preprocessing temperature data of a mold expert system according to claim 1, characterized in that: In step (2), the temperature of each thermocouple is calibrated by collecting the crystallizer inlet water temperature values ​​for 1 minute and calculating the average value, which is recorded as T in At the same time, calculate the average temperature of each thermocouple within 1 minute and record it as T1, T2...T n , the subsequent real-time data of each thermocouple temperature is corrected according to the following formula: T 校正 =T+T in -T n , where T 校正 is the temperature value after calibration of the thermocouple, ℃, and T is the temperature value measured by the thermocouple in real time, ℃.

3. The method for preprocessing temperature data of a mold expert system according to claim 1, characterized in that: In step (2), the method for calculating the standard deviation of each thermocouple temperature is to collect the temperature data of each thermocouple for 1 minute continuously, and calculate the standard deviation of the temperature data of each thermocouple for 1 minute and record it as R1, R2...R n .

4. The method for preprocessing temperature data of a mold expert system according to claim 1, characterized in that: In step (3), the spectrum analysis method is to continuously sample the temperature value of each thermocouple at a time interval of 0.25s for 5 minutes; repeat this process 6 times to obtain 6 groups of different temperature data, each group of temperature data containing 1200 values; perform fast Fourier transform on each group of temperature data to obtain the spectrum of the group of temperature data, and when the maximum intensity in the spectrum of the 6 groups of temperature data are all at the same frequency point, mark the thermocouple and record the frequency point where the maximum intensity is located.

5. The method for preprocessing temperature data of a mold expert system according to claim 1, characterized in that: In step (3), the spectrum processing method is to perform a fast Fourier transform on the temperature data of the marked thermocouple for the last 5 minutes each time new thermocouple temperature data is collected to obtain the spectrum of the set of temperature data, remove the recorded frequency points in the spectrum, and then perform an inverse Fourier transform on the spectrum. The transformed data is used as spectrum-processed data for subsequent use.

6. The method for preprocessing temperature data of a mold expert system according to claim 1, characterized in that: In step (5), the method for correcting the temperature value is to calculate according to the following formula: , where T is the corrected temperature, in °C; T0 is the temperature value after the above steps, in °C; is the thickness of the copper plate measured in step (1), in mm; is the thickness of the new copper plate, in mm; The minimum thickness allowed for copper plate, in mm.

7. The method for preprocessing temperature data of a mold expert system according to claim 1, characterized in that: In step (6), the normal range of the thermocouple temperature is 50-200°C; The method of limiting temperature values ​​is that temperature values ​​less than 50°C are limited to 50°C, and temperature values ​​greater than 200°C are limited to 200°C.