Atmosphere furnace temperature rise suppression method and system based on multi-environmental-factor regulation and control

Abstract

The invention relates to an atmosphere furnace temperature rise suppression method and system based on multi-environmental-factor regulation and control, and belongs to the technical field of atmosphere furnace control, and the method comprises the following steps: step 1, a temperature sensor array monitors temperature data of each part and uploads the temperature data to a control module, and a gas component analyzer monitors gas component data and uploads the gas component data to the control module; the pressure sensor monitors pressure data and uploads the pressure data to the control module, and the humidity sensor monitors humidity data and uploads the humidity data to the control module; 2, the control module calculates a risk coefficient according to the temperature data, the gas component data, the pressure data and the humidity data; 3, the control module judges whether the risk coefficient exceeds a threshold value or not, if yes, the step 4 is executed, and if not, the step 5 is executed; 4, the control module reduces the heating power according to the risk coefficient, and the step 1 is executed again; and 5, returning to the step 1.

Description

Technical Field

[0001] This invention belongs to the field of atmosphere furnace control technology, specifically relating to a method and system for suppressing temperature rise in atmosphere furnaces based on the regulation of multiple environmental factors. Background Technology

[0002] As a key heating device in the MLCC field, the atmosphere furnace plays a vital role in the debinding and sintering processes of various materials, and its combustion efficiency directly affects the energy consumption and production costs of enterprises.

[0003] Atmosphere furnaces are complex controlled objects characterized by nonlinearity, large time lag, and slow time-varying behavior. Their state and characteristics constantly change as combustion progresses. With changes in operating conditions and adjustments in production processes, the combustion control of atmosphere furnaces requires frequent adjustments. To address this, Chinese Patent CN118936113B discloses an intelligent combustion control system and method for atmosphere furnaces. This system acquires time queues of airflow and exhaust gas temperature values ​​and employs deep learning-based data analysis and processing techniques to analyze the temporal correlation characteristics and time-series propagation aggregation of these values. Based on the global interactive representation characteristics between the temporal propagation features of the airflow and exhaust gas temperature values, it adaptively controls the airflow value at the next time point. This allows for more precise calculation and adjustment of the airflow value to achieve the optimal atmosphere ratio, avoiding under-oxygen or over-oxygen combustion, and reducing fluctuations in operating parameters caused by untimely or inaccurate manual adjustments. Therefore, it provides a more intelligent intelligent combustion control scheme for atmosphere furnaces.

[0004] However, the above scheme only monitors flow rate and exhaust gas temperature, which is too few environmental parameters and may lead to inaccurate monitoring results and imprecise timing for temperature suppression. Therefore, a method and system for suppressing temperature rise in atmosphere furnaces based on the control of multiple environmental factors is needed, which has multiple environmental parameters and high detection accuracy. Summary of the Invention

[0005] To address the aforementioned problems in the existing technology, this invention provides a method and system for suppressing temperature rise in an atmosphere furnace based on the regulation of multiple environmental factors, which features multiple environmental parameters and high detection accuracy.

[0006] The objective of this invention can be achieved through the following technical solutions: A method for suppressing temperature rise in an atmosphere furnace based on the regulation of multiple environmental factors includes the following steps: Step 1: The temperature sensor array monitors temperature data at various locations and uploads it to the control module; the gas composition analyzer monitors gas composition data and uploads it to the control module; the pressure sensor monitors pressure data and uploads it to the control module; and the humidity sensor monitors humidity data and uploads it to the control module. Step 2: The control module calculates the risk factor based on temperature data, gas composition data, pressure data, and humidity data; Step 3: The control module determines whether the risk coefficient exceeds the threshold. If the result is yes, proceed to step 4; otherwise, proceed to step 5. Step 4: The control module reduces the heating power based on the risk factor and returns to Step 1; Step 5: Return to Step 1; As a preferred embodiment of the present invention, step one further includes: a temperature sensor array monitoring temperature data T at various locations and uploading it to the control module; a gas composition analyzer monitoring gas composition data Q and uploading it to the control module; a pressure sensor monitoring pressure data P and uploading it to the control module; and a humidity sensor monitoring humidity data S and uploading it to the control module. Step two further includes: the control module calculating the risk coefficient X = T / T0 + Q / Q0 + P / P0 + S / S0. Step four further includes: the control module adjusting the heating power to X0 / X times the original power.

[0007] As a preferred embodiment of the present invention, step one further includes: after receiving temperature data, gas composition data, pressure data and humidity data, the control module calculates the variance of several data points arranged in reverse chronological order; step two further includes: the control module calculates the risk coefficient based on a weighted average of temperature data, gas composition data, pressure data and humidity data.

[0008] As a preferred embodiment of the present invention, step one further includes: a temperature sensor array monitoring temperature data T at various locations and uploading it to the control module; a gas composition analyzer monitoring gas composition data Q and uploading it to the control module; a pressure sensor monitoring pressure data P and uploading it to the control module; a humidity sensor monitoring humidity data S and uploading it to the control module; and the control module calculating the variances Ft, Fq, Fp, and Fs of the sequentially uploaded T, Q, P, and S respectively. Step two further includes: the control module calculating the risk coefficient X=(K1×T / T0+K2×Q / Q0+K3×P / P0+K4×S / S0) / (K1+K2+K3+K4), where K1=1 / (1+Ft), K2=1 / (1+Fq), K3=1 / (1+Fp), and K4=(1 / 1+Fs).

[0009] As a preferred embodiment of the present invention, step two further includes: the control module calculating whether the upload time difference of temperature data, gas composition data, pressure data and humidity data exceeds a threshold; step four further includes: reducing the heating power when it is determined that the upload time difference of temperature data, gas composition data, pressure data and humidity data exceeds the threshold.

[0010] A multi-environmental factor-based atmosphere furnace temperature rise suppression system, applicable to the aforementioned multi-environmental factor-based atmosphere furnace temperature rise suppression method, includes a temperature sensor array, a gas composition analyzer, a pressure sensor, a humidity sensor, and a control module. The temperature sensor array monitors temperature data at various points and uploads it to the control module; the gas composition analyzer monitors gas composition data and uploads it to the control module; the pressure sensor monitors pressure data and uploads it to the control module; and the humidity sensor monitors humidity data and uploads it to the control module. The control module calculates a risk coefficient based on the temperature data, gas composition data, pressure data, and humidity data and determines whether a threshold is exceeded. If the determination result is yes, the control module reduces the heating power according to the risk coefficient.

[0011] The beneficial effects of this invention are as follows: (1) By setting up a temperature sensor array, a gas composition analyzer, a pressure sensor and a humidity sensor to detect temperature data, gas composition data, pressure data and humidity data, and calculating the risk coefficient based on the temperature data, gas composition data, pressure data and humidity data, the types of environmental parameters collected are expanded and the detection accuracy is improved. (2) By having the control module calculate the variance of several data arranged in reverse chronological order, and when calculating the risk coefficient based on the weighted average of temperature data, gas composition data, pressure data and humidity data, the weight of a certain parameter in the weighted average is reduced when the variance of a certain parameter is greater than the threshold, and the weight of a certain parameter in the calculation is reduced when the fluctuation of a certain parameter is large and there is a high probability of acquisition deviation, thereby reducing the impact of deviation data on the calculation of risk coefficient. Attached Figure Description

[0012] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0013] Figure 1 This is a block diagram of the control loop of the present invention. Detailed Implementation

[0014] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0015] Please see Figure 1 A method for suppressing temperature rise in an atmosphere furnace based on the regulation of multiple environmental factors includes the following steps: Step 1: The temperature sensor array monitors temperature data at various locations and uploads it to the control module; the gas composition analyzer monitors gas composition data and uploads it to the control module; the pressure sensor monitors pressure data and uploads it to the control module; and the humidity sensor monitors humidity data and uploads it to the control module. Step 2: The control module calculates the risk factor based on temperature data, gas composition data, pressure data, and humidity data; Step 3: The control module determines whether the risk coefficient exceeds the threshold. If the result is yes, proceed to step 4; otherwise, proceed to step 5. Step 4: The control module reduces the heating power based on the risk factor and returns to Step 1; Step 5: Return to Step 1; Specifically, in step one, the temperature sensor array includes several temperature sensors, several gas composition analyzers and several humidity sensors. Several sensors in the temperature sensor array detect data in real time and upload the data to the control module at a frequency of once per second. Specifically, in the above calculation process, step one further includes: the temperature sensor array monitors the temperature data T at various locations and uploads it to the control module; the gas composition analyzer monitors the gas composition data Q and uploads it to the control module; the pressure sensor monitors the pressure data P and uploads it to the control module; and the humidity sensor monitors the humidity data S and uploads it to the control module. Step two further includes: the control module calculates the risk coefficient X = T / T0 + Q / Q0 + P / P0 + S / S0. Step four further includes: the control module adjusts the heating power to X0 / X times the original value. In actual use, environmental parameters are monitored to determine whether the operating conditions of the atmosphere furnace are within the normal range, in order to determine whether conditions are needed and to determine the degree of adjustment. However, if flow rate and exhaust gas temperature are monitored, too few environmental parameters will have a significant impact on the final judgment result when one of the environmental parameters is affected by random factors such as sensor error. The accuracy of the judgment of the furnace operating conditions is not high, and there is a probability that the monitoring results will be inaccurate and the timing of temperature rise suppression will be imprecise. In this invention, by setting up a temperature sensor array, a gas composition analyzer, a pressure sensor, and a humidity sensor to detect four environmental parameters—temperature data, gas composition data, pressure data, and humidity data—and calculating a risk coefficient based on these data, even if one environmental parameter has an error, the error is diluted when multiple environmental parameters are involved in the calculation. Therefore, the types of environmental parameters collected are expanded, and the detection accuracy is improved.

[0016] During the detection process, for data errors caused by random errors, in addition to diluting the errors by relying on multiple environmental parameters, the impact of the errors can be further reduced by decreasing their calculation weights. To this end, step one also includes: after receiving temperature data, gas composition data, pressure data, and humidity data, the control module calculates the variance of several data points arranged in reverse chronological order; step two also includes: the control module calculates the risk coefficient by weighted averaging of temperature data, gas composition data, pressure data, and humidity data. When the variance of a certain parameter is greater than the threshold, it means that there is a probability of error in examining this part of the data by collecting it sequentially. In this case, the weight of this parameter in the risk coefficient calculation should be reduced. Specifically, in the above weighted average calculation process, step one further includes: the temperature sensor array monitors the temperature data T at various locations and uploads it to the control module; the gas composition analyzer monitors the gas composition data Q and uploads it to the control module; the pressure sensor monitors the pressure data P and uploads it to the control module; the humidity sensor monitors the humidity data S and uploads it to the control module; and the control module calculates the variances Ft, Fq, Fp, and Fs of the uploaded T, Q, P, and S respectively. Step two further includes: the control module calculates the risk coefficient X=(K1×T / T0+K2×Q / Q0+K3×P / P0+K4×S / S0) / (K1+K2+K3+K4), where K1=1 / (1+Ft), K2=1 / (1+Fq), K3=1 / (1+Fp), and K4=(1 / 1+Fs). When the variance of a certain parameter is large, the corresponding Kx value will decrease. For example, if the variance Ft of temperature T is large, it means that the temperature parameter is likely to have an error. At this time, the value of the weight K1=1 / (1+Ft) corresponding to T will decrease. When the variance of a certain parameter is greater than the threshold, the weight of this parameter in the risk coefficient calculation will be reduced. Therefore, by having the control module calculate the variance of several data points arranged in reverse chronological order, and by reducing the weight of a parameter in the weighted average when calculating the risk coefficient based on the weighted average of temperature, gas composition, pressure, and humidity data, and by reducing the weight of a parameter in the weighted average when the variance of a certain parameter is greater than a threshold, and by reducing the weight of a parameter in the calculation when a certain parameter fluctuates greatly and there is a high probability of acquisition deviation, the impact of deviation data on the calculation of the risk coefficient can be reduced.

[0017] In practical use, the above scheme involves multiple sensors. When different sensors monitor environmental parameters and upload data, there is a probability that the upload order will be inconsistent due to timing errors in the control circuit. In this case, when calculating the risk factor, the various environmental parameters involved in the calculation represent the furnace environment at different time points, which is not very representative of the environment at this time. In order to reduce the risk caused by inaccurate environmental parameters, a more conservative heating strategy can be adopted, that is, reducing the heating power. To this end, step two also includes: the control module calculates whether the upload time difference of temperature data, gas composition data, pressure data, and humidity data exceeds the threshold. Step four also includes: reducing the heating power when the upload time difference of temperature data, gas composition data, pressure data, and humidity data exceeds the threshold. Specifically, the control module has a built-in timing module. When the control module receives each environmental parameter, it automatically adds a timestamp to the environmental parameter based on the current time. After performing a risk coefficient calculation, the control module calculates the average time of the environmental parameters involved in the risk coefficient calculation. Then, it calculates the sum of the absolute values ​​of the differences between the time of each environmental parameter and the average time, and determines whether this sum exceeds the threshold range. If the sum exceeds the threshold range, it is determined that the time difference between the upload of the environmental parameters is too large, which may indicate a risk of data asynchrony. At this time, the control module will reduce the heating power and adopt a conservative heating strategy. By calculating whether the time difference between the upload of temperature data, gas composition data, pressure data, and humidity data exceeds a threshold, and reducing the heating power when the time difference exceeds the threshold, the impact of asynchronous environmental parameter acquisition time on furnace temperature regulation is reduced.

[0018] This invention also provides an atmosphere furnace temperature rise suppression system based on multi-environmental factor regulation, applicable to the aforementioned atmosphere furnace temperature rise suppression method based on multi-environmental factor regulation. The system includes a temperature sensor array, a gas composition analyzer, a pressure sensor, a humidity sensor, and a control module. The temperature sensor array monitors temperature data at various locations and uploads it to the control module. The gas composition analyzer monitors gas composition data and uploads it to the control module. The pressure sensor monitors pressure data and uploads it to the control module. The humidity sensor monitors humidity data and uploads it to the control module. The control module calculates a risk coefficient based on the temperature data, gas composition data, pressure data, and humidity data, and determines whether a threshold is exceeded. If the determination result is yes, the control module reduces the heating power according to the risk coefficient.

[0019] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for suppressing temperature rise in an atmosphere furnace based on the regulation of multiple environmental factors, characterized in that: Includes the following steps: Step 1: The temperature sensor array monitors temperature data at various locations and uploads it to the control module; the gas composition analyzer monitors gas composition data and uploads it to the control module; the pressure sensor monitors pressure data and uploads it to the control module; and the humidity sensor monitors humidity data and uploads it to the control module. Step 2: The control module calculates the risk factor based on temperature data, gas composition data, pressure data, and humidity data; Step 3: The control module determines whether the risk coefficient exceeds the threshold. If the result is yes, proceed to step 4; otherwise, proceed to step 5. Step 4: The control module reduces the heating power based on the risk factor and returns to Step 1; Step 5: Return to Step 1.

2. The method for suppressing temperature rise in an atmosphere furnace based on the control of multiple environmental factors according to claim 1, characterized in that: Step one further includes: a temperature sensor array monitoring temperature data T at various locations and uploading it to the control module; a gas composition analyzer monitoring gas composition data Q and uploading it to the control module; a pressure sensor monitoring pressure data P and uploading it to the control module; and a humidity sensor monitoring humidity data S and uploading it to the control module. Step two further includes: the control module calculating the risk coefficient X = T / T0 + Q / Q0 + P / P0 + S / S0. Step four further includes: the control module adjusting the heating power to X0 / X times the original power.

3. The method for suppressing temperature rise in an atmosphere furnace based on the control of multiple environmental factors according to claim 1, characterized in that: Step one further includes: after receiving temperature data, gas composition data, pressure data, and humidity data, the control module calculates the variance of several data points arranged in reverse chronological order; Step two further includes: the control module calculates the risk coefficient based on a weighted average of the temperature data, gas composition data, pressure data, and humidity data.

4. The method for suppressing temperature rise in an atmosphere furnace based on the control of multiple environmental factors according to claim 2, characterized in that: Step one further includes: a temperature sensor array monitors temperature data T at various locations and uploads it to the control module; a gas composition analyzer monitors gas composition data Q and uploads it to the control module; a pressure sensor monitors pressure data P and uploads it to the control module; a humidity sensor monitors humidity data S and uploads it to the control module; and the control module calculates the variances Ft, Fq, Fp, and Fs of the sequentially uploaded T, Q, P, and S, respectively. Step two further includes: the control module calculates the risk coefficient X=(K1×T / T0+K2×Q / Q0+K3×P / P0+K4×S / S0) / (K1+K2+K3+K4), where K1=1 / (1+Ft), K2=1 / (1+Fq), K3=1 / (1+Fp), and K4=(1 / 1+Fs).

5. The method for suppressing temperature rise in an atmosphere furnace based on the control of multiple environmental factors according to claim 1, characterized in that: Step two further includes: the control module calculates whether the upload time difference of temperature data, gas composition data, pressure data and humidity data exceeds a threshold; Step four further includes: reducing the heating power when the upload time difference of temperature data, gas composition data, pressure data and humidity data exceeds the threshold.

6. A heating suppression system for an atmosphere furnace based on the regulation of multiple environmental factors, characterized in that: The method for suppressing temperature rise in an atmosphere furnace based on the control of multiple environmental factors, applicable to any one of claims 1 to 5, includes a temperature sensor array, a gas composition analyzer, a pressure sensor, a humidity sensor, and a control module. The temperature sensor array monitors temperature data at various locations and uploads it to the control module. The gas composition analyzer monitors gas composition data and uploads it to the control module. The pressure sensor monitors pressure data and uploads it to the control module. The humidity sensor monitors humidity data and uploads it to the control module. The control module is used to calculate a risk coefficient based on the temperature data, gas composition data, pressure data, and humidity data, and determine whether a threshold is exceeded. When the determination result is yes, the control module reduces the heating power according to the risk coefficient.

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