Method and system for dynamically adjusting pressure of gas collecting pipe of coke oven based on intelligent control

Abstract

The invention relates to the technical field of intelligent control, in particular to a coke oven gas collecting tube pressure dynamic adjusting method and system based on intelligent control, and the method comprises the steps: obtaining pressure data from a gas collecting tube through a sensor, and storing the pressure data in a time sequence format to obtain a pressure deviation initial sequence; according to the pressure deviation initial sequence, calculating a data difference value and carrying out smoothing processing to obtain a change rate sequence; analyzing the change trend of the change rate sequence, and calculating a secondary difference value to obtain a change acceleration sequence; according to the change rate sequence and the change acceleration sequence, predicting a pressure deviation development trajectory by adopting a filtering method to obtain a predicted deviation trajectory; and if the predicted deviation trajectory exceeds a preset threshold range, obtaining a deviation influence evaluation value through historical data comparative analysis. The problem that the pressure control precision of the coke oven gas collecting pipe is poor in the high-temperature and high-pressure environment is solved, and the pressure adjusting precision of the gas collecting pipe in the high-temperature and high-pressure environment is improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, and in particular to a method and system for dynamic adjustment of coke oven gas collecting pipe pressure based on intelligent control. Background Technology

[0002] In the coking process of a coke oven, the gas collecting pipe system is a crucial link in the internal gas flow and pressure regulation of the coke oven. Its operational stability directly affects coke quality, energy utilization efficiency, and production safety. The pressure inside the gas collecting pipe needs to be maintained within a specific range to ensure uniform gas distribution inside the coke oven and to avoid excessive pressure leading to seal failure or excessive pressure causing air infiltration, which would thus affect the quality of coke production. A similar prior art is Chinese patent CN115167141A, which proposes a brake cylinder pressure control method, including: obtaining the target pressure value of the brake cylinder and the current measured pressure value of the brake cylinder; calculating the difference between the target pressure value and the measured pressure value; if the difference is within a preset range, maintaining the current braking mode; otherwise, using the target pressure value and the measured pressure value as inputs, and obtaining the control quantity for adjusting the brake cylinder pressure based on an extended state observer and a feedback controller, and performing adjustment control; repeating the above steps for iterative control until the brake cylinder pressure reaches the target pressure value and remains stable. This invention solves the problem of accurate control of brake cylinder pressure under uncertain disturbances and improves model accuracy.

[0003] Similar prior art includes Chinese Patent Publication No. CN118377217B, which proposes a method for controlling the opening degree of a butterfly valve, including: determining a control error signal and the rate of change of the error signal based on the current pressure and the preset pressure inside the cavity; determining the actual number of steps corresponding to the current pressure based on the correspondence between the current pressure and a predetermined number of motor steps and the actual pressure; determining the target correction parameter based on the actual number of steps and the correspondence between the number of motor steps and the correction parameter; performing fuzzy processing on the control error signal and the rate of change of the error signal to obtain the PID adjustment amount; determining the PID parameter at the current moment based on the target correction parameter, the PID adjustment amount, and the PID parameter at the initial moment; and calculating the control signal of the butterfly valve based on the PID parameter at the current moment and the PID control algorithm. The control signal is used to control the opening degree of the butterfly valve, which can improve the control accuracy of gas pressure.

[0004] Although both of the aforementioned patent documents have solved the pressure regulation problem, they cannot meet the requirements for precise control under high temperature and high pressure working environment when used for pressure control of gas collecting pipes in coke ovens. Summary of the Invention

[0005] This invention provides a method for dynamic adjustment of coke oven gas collecting pipe pressure based on intelligent control, comprising:

[0006] Pressure deviation data is acquired from the gas collection pipe by a sensor and stored in time series format to obtain an initial pressure deviation sequence; based on the initial pressure deviation sequence, the data difference is calculated and smoothed to obtain a rate of change sequence.

[0007] Analyze the changing trend of the rate of change sequence, calculate the quadratic difference, and obtain the changing acceleration sequence;

[0008] Based on the change rate sequence and the change acceleration sequence, a filtering method is used to predict the development trajectory of the pressure deviation, and the predicted deviation trajectory is obtained.

[0009] If the predicted deviation trajectory exceeds the preset threshold range, a deviation impact assessment value is obtained through historical data comparison and analysis; based on the deviation impact assessment value, pressure regulation parameters are generated, and valve opening adjustment commands are obtained.

[0010] The valve opening adjustment command is used to control the opening of the gas collecting pipe pressure valve, obtain the adjusted pressure deviation data, and obtain the updated pressure deviation sequence. Based on the updated pressure deviation sequence, the adjustment effect is verified, it is determined whether the stable operation conditions are met, and the pressure stability state is obtained.

[0011] As a preferred embodiment of the present invention, the acquisition of the initial sequence of pressure deviation includes:

[0012] The pressure sensor acquires the raw pressure value from the gas collection pipe at a preset real-time data acquisition frequency, and obtains pressure deviation data based on the raw pressure value and the target pressure value.

[0013] The pressure deviation data is initially corrected based on the interference of ambient temperature to obtain the corrected pressure deviation data.

[0014] The corrected pressure deviation data is stored in time sequence as a time series format to generate the initial pressure deviation sequence. The time series format includes timestamps and corresponding pressure deviation values. The initial pressure deviation sequence is used for subsequent data difference calculation and trend analysis.

[0015] As a preferred embodiment of the present invention, the acquisition of the rate of change sequence includes:

[0016] Based on the initial pressure deviation sequence, the data difference between adjacent time points is calculated to obtain the pressure deviation difference sequence; based on pipeline vibration data, the pressure deviation difference sequence is smoothed to obtain a smoothed difference sequence; based on the smoothed difference sequence, the pressure deviation change per unit time is calculated to generate the change rate sequence, wherein the change rate sequence reflects the dynamic change trend of the pressure deviation.

[0017] As a preferred embodiment of the present invention, the acquisition of the changing acceleration sequence includes:

[0018] Based on the measured thermal expansion pressure increment and cooling contraction pressure decrease, a second difference calculation is performed on the change rate sequence to obtain the acceleration data of the change rate.

[0019] Based on the acceleration data, the variable acceleration sequence is generated, wherein the variable acceleration sequence is used to characterize the acceleration characteristics of pressure deviation changes.

[0020] As a preferred embodiment of the present invention, the acquisition of the predicted deviation trajectory includes:

[0021] The current temperature gradient distribution of the gas collecting pipe is obtained, and the temperature gradient distribution, the currently collected pressure data, the set target pressure data, the change rate sequence and the change acceleration sequence within a preset time period before the current time period are input into the prediction model to obtain the prediction deviation trajectory. The temperature gradient is obtained by calculating the ratio of the temperature difference between adjacent temperature sensors set at different locations in the key area of ​​the gas collecting pipe to the distance between them.

[0022] As a preferred embodiment of the present invention, the acquisition of the deviation impact assessment value includes:

[0023] Determine whether the predicted deviation trajectory exceeds a preset threshold range;

[0024] If the deviation exceeds the limit, historical pressure deviation data will be obtained and compared with the requirements for adapting to high temperature and high pressure environments.

[0025] Based on the comparative analysis, the expected impact of the predicted deviation trajectory on system stability is calculated, and the deviation impact assessment value is generated. The deviation impact assessment value is used for the subsequent generation of pressure regulation parameters.

[0026] As a preferred embodiment of the present invention, pressure regulation parameters are generated based on the deviation influence assessment value to obtain a valve opening adjustment command, including:

[0027] Based on the aforementioned deviation impact assessment value, analyze the response characteristics of the pressure valve adjustment sensitivity;

[0028] Based on the analysis results, calculate the parameters required for regulating the pressure of the gas collecting pipe and generate the pressure regulation parameters.

[0029] Based on the pressure regulation parameters, the valve opening adjustment amount is determined, and the valve opening adjustment command is generated. The valve opening adjustment command is used to control the real-time adjustment of the gas collecting pipe pressure valve.

[0030] As a preferred embodiment of the present invention, the step of verifying the adjustment effect and determining whether the stable operating conditions are met based on the updated pressure deviation sequence to obtain a stable pressure state includes:

[0031] Based on the updated pressure deviation sequence and combined with the high-pressure sealing performance requirements, the changing trend of the pressure deviation is analyzed; the adjustment effect of the valve opening adjustment command is verified.

[0032] Based on the adjustment effect, it is determined whether the updated pressure deviation sequence meets the preset stable operating conditions, and the pressure stable state is generated, wherein the pressure stable state characterizes the operating stability of the gas collection pipe system.

[0033] This invention also provides a coke oven gas collecting pipe pressure dynamic adjustment system based on intelligent control, for implementing the above-mentioned method, the system comprising:

[0034] The calculation unit is used to acquire pressure deviation data from the gas collection pipe through a sensor, store it in a time series format to obtain an initial pressure deviation sequence; calculate the data difference based on the initial pressure deviation sequence and perform smoothing to obtain a rate of change sequence; analyze the changing trend of the rate of change sequence, calculate the second difference to obtain a rate of change sequence.

[0035] The prediction unit is used to predict the development trajectory of the pressure deviation based on the change rate sequence and the change acceleration sequence using a filtering method, and obtain the predicted deviation trajectory.

[0036] The generation unit is used to obtain a deviation impact assessment value by comparing and analyzing historical data if the predicted deviation trajectory exceeds a preset threshold range; and to generate pressure regulation parameters and obtain valve opening adjustment instructions based on the deviation impact assessment value.

[0037] The judgment unit is used to control the opening of the gas collecting pipe pressure valve through the valve opening adjustment command, obtain the adjusted pressure deviation data, and obtain the updated pressure deviation sequence; based on the updated pressure deviation sequence, verify the adjustment effect, determine whether the stable operation conditions are met, and obtain the pressure stable state.

[0038] The present invention also provides a computer-readable storage medium storing instructions that, when executed by a processor, implement the above-described method.

[0039] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:

[0040] This invention discloses an intelligent method for adjusting the pressure deviation of a gas collecting pipe. It uses a high-precision sensor to collect pressure data in real time, and combines this with ambient temperature correction and vibration noise reduction to generate an initial pressure deviation sequence. Based on this sequence, the rate of change and acceleration are calculated, and the effects of thermal expansion and contraction are considered. A Kalman filter is then used to predict the pressure deviation trajectory. When the predicted trajectory exceeds a threshold, the impact is evaluated using historical data, and a valve opening adjustment command is generated. This invention also optimizes the adjustment parameters by analyzing the pressure valve sensitivity and cooling medium response characteristics, and considers high-pressure sealing requirements and data delay to verify the adjustment effect. This method can effectively cope with high-temperature and high-pressure environments, achieve precise dynamic adjustment of the gas collecting pipe pressure, and improve system operational stability. Attached Figure Description

[0041] Figure 1 This is a flowchart of the method for dynamic adjustment of coke oven gas collecting pipe pressure based on intelligent control in an embodiment of the present invention;

[0042] Figure 2 This is a flowchart of the method for obtaining the rate of change sequence in an embodiment of the present invention;

[0043] Figure 3 This is a flowchart of the method for obtaining the deviation evaluation value in an embodiment of the present invention;

[0044] Figure 4 This is a structural diagram of a coke oven gas collecting pipe pressure dynamic adjustment system based on intelligent control, as described in an embodiment of the present invention. Detailed Implementation

[0045] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] like Figure 1 The gas collecting pipe pressure regulation method in this embodiment may specifically include:

[0047] Step S1: Obtain pressure data from the gas collection pipe through the sensor, store it in time series format to obtain the initial pressure deviation sequence, calculate the data difference based on the initial pressure deviation sequence and perform smoothing to obtain the rate of change sequence;

[0048] Specifically, pressure data is acquired in real time from the coke oven gas collecting pipe using high-precision sensors. Since the high temperature and vibration of the coke oven system can interfere with the pressure sensor readings, the raw pressure data collected will generate pressure deviation data based on the difference between the target pressure value and the actual pressure value. To ensure data accuracy, the system also performs temperature compensation, as temperature changes cause the pipe material to expand or contract, thus affecting the pressure sensor measurements. The compensation process is completed using a machine learning model or a preset temperature compensation formula to reduce the impact of temperature fluctuations on the data. An initial pressure deviation sequence is created by storing the corrected pressure deviation data in a time-series format with timestamps. This process ensures that the data acquired by the system accurately reflects the dynamic changes in the gas collecting pipe pressure, providing high-quality basic data for subsequent steps. The differences between adjacent time points in the initial pressure deviation sequence are also calculated to obtain a pressure deviation difference sequence. Since factors such as pipe vibration may introduce noise into the data, these difference sequences will be processed using a weighted average or other smoothing algorithms. By assessing the impact of vibration, the system can automatically adjust the parameters of the smoothing algorithm to ensure that the smoothing process can effectively remove noise without losing the true pressure change information. The processed difference sequence will be used to calculate the pressure change per unit time, i.e., the rate of change sequence. The rate of change sequence can reflect the dynamic trend of pressure change and provide the necessary basic data for subsequent predictive analysis. The above technical solution eliminates external interference and ensures that the system obtains accurate pressure fluctuation data, thereby making pressure regulation more precise.

[0049] Step S2: Analyze the changing trend of the rate of change sequence, calculate the quadratic difference, and obtain the changing acceleration sequence; based on the rate of change sequence and the changing acceleration sequence, use a filtering method to predict the development trajectory of the pressure deviation, and obtain the predicted deviation trajectory;

[0050] Specifically, the changing trend of the rate of change sequence is analyzed, and a changing acceleration sequence is generated by calculating the quadratic difference. The acceleration sequence helps capture the acceleration or deceleration trend of pressure changes, which is crucial for predicting the future trend of pressure fluctuations. By correcting for the pressure changes caused by thermal expansion and cooling contraction, the rate of change sequence is adjusted to ensure it more accurately reflects the actual pressure changes in the system. After obtaining the changing acceleration sequence, a predictive model is used to predict the development trajectory of pressure deviations. By predicting the deviation trajectory, the system can make adjustments when pressure fluctuations are about to exceed a safe threshold, thereby preventing system instability. The above technical solution can effectively predict pressure change trends and provide accurate basis for subsequent regulation.

[0051] Step S3: If the predicted deviation trajectory exceeds the preset threshold range, the deviation impact assessment value is obtained through historical data comparison and analysis; based on the deviation impact assessment value, pressure regulation parameters are generated to obtain valve opening adjustment instructions;

[0052] Specifically, the deviation impact assessment value obtained through historical data comparison and analysis is applied to generate pressure regulation parameters. By evaluating whether the predicted deviation trajectory exceeds a preset threshold range, the system can determine whether the current pressure needs adjustment. If the predicted deviation exceeds the predetermined range, the system generates pressure regulation parameters and generates a valve opening adjustment command through a PID control algorithm. This command is used to control the opening of the gas collecting pipe pressure valve, adjusting the pressure in the gas collecting pipe in real time. During this process, the system automatically adjusts the valve opening according to the speed and direction of pressure changes to ensure that the gas collecting pipe pressure remains within a safe range. The above technical solution can respond quickly and accurately to pressure fluctuations, ensuring dynamic adjustment of the gas collecting pipe pressure and stable system operation.

[0053] Step S4: Control the opening of the gas collecting pipe pressure valve through the valve opening adjustment command, obtain the adjusted pressure data, and obtain the updated pressure deviation sequence;

[0054] Specifically, the system controls the opening of the pressure valve in the gas collecting pipe in real time according to the generated valve opening adjustment command. Adjusting the valve opening aims to change the gas flow rate, thereby directly affecting the pressure level within the gas collecting pipe. This process involves generating a set of parameters calculated based on the deviation impact assessment value and the current pressure state of the system. Specifically, the system first calculates the generated pressure regulation parameters and determines the required valve opening adjustment amount. This adjustment amount determines the degree to which the valve is opened or closed, in order to bring the pressure in the gas collecting pipe as close as possible to the target pressure. After the valve adjustment, the pressure in the gas collecting pipe will change, and the new pressure data will be collected in real time and used to update the pressure deviation sequence; the pressure deviation sequence reflects the difference between the actual pressure and the target pressure. This new data is crucial for subsequent adjustment and verification processes. The above technical solution can accurately control the pressure and generate updated pressure deviation data, ensuring that each adjustment is based on the latest real-time data.

[0055] Step S5: Based on the updated pressure deviation sequence, verify the adjustment effect, determine whether the stable operation conditions are met, and obtain the pressure stable state.

[0056] Specifically, verification is performed based on the updated pressure deviation sequence to ensure that the adjustment effect achieves the expected target. The core purpose of this step is to verify whether the adjusted gas collecting pipe pressure meets the stable operating conditions. The system analyzes updated pressure data and combines it with preset stable operating standards to determine whether the pressure is within the expected range. It assesses the trend of pressure deviation changes, including checking whether the pressure in the gas collecting pipe is stabilizing, whether there are still significant fluctuations, or whether it has reached the set stable range. For example, in coke oven production, the pressure in the gas collecting pipe must be maintained within a strict range to ensure uniform and stable gas flow, preventing excessive pressure from causing seal failure or excessive pressure from causing air infiltration, which would affect coke quality. If the updated pressure deviation sequence shows that the pressure is stabilizing and meets the set threshold, the system considers the adjustment successful and generates a pressure stable state. At this point, the system will continue to operate, maintaining the current operating conditions. If the judgment result indicates that the pressure deviation still has not reached the expected stable condition, the system will readjust the valve opening and continue to adjust the pressure until the pressure reaches the required stable state. This technical solution can adjust and verify the pressure in real time, ensuring the stability and safety of the gas collecting pipe under high temperature and high pressure environments, and preventing pressure fluctuations from adversely affecting coke production.

[0057] Furthermore, the acquisition of the initial sequence of pressure deviations includes:

[0058] The pressure sensor acquires the raw pressure value from the gas collection pipe at a preset real-time data acquisition frequency, and obtains pressure deviation data based on the raw pressure value and the target pressure value.

[0059] The pressure deviation data is initially corrected based on the interference of ambient temperature to obtain the corrected pressure deviation data.

[0060] The corrected pressure deviation data is stored in chronological order as a time series format to generate the initial pressure deviation sequence, wherein the time series format includes timestamps and corresponding pressure deviation values.

[0061] Specifically, during the process of converting coal into coke at high temperatures in a coke oven, the quality of coke is affected by various factors, among which the gas pressure inside the coke oven is one of the important factors. The pressure in the gas collecting pipe mainly affects the flow and distribution of gas in the coke oven, as well as the control of gas inside the oven, thus indirectly affecting the quality of coke. The pressure regulation process in the gas collecting pipe is affected by various factors, such as temperature changes and pipe vibration. These factors can cause certain errors in the raw data of the pressure sensor, thereby affecting the accuracy and stability of pressure regulation. Therefore, a high-precision pressure sensor is used to obtain the raw pressure value from the gas collecting pipe at a preset real-time data acquisition frequency, and the difference between the raw pressure value and the target pressure value is used as the pressure deviation data. Since the ambient temperature fluctuation causes thermal expansion of the pipe material, it directly affects the accuracy of pressure measurement. For example, an increase in temperature may cause the pressure sensor reading to deviate. In order to eliminate this influence, temperature compensation is required for the raw data. This compensation process corrects pressure deviation data using a preset temperature compensation formula or a machine learning model combined with real-time temperature data. The machine learning model is trained on sample data composed of historical raw pressure values, historical ambient temperatures, and target pressure data. This correction method effectively reduces the interference of temperature changes on pressure deviation data, ensuring its accuracy. This step guarantees the stability of pressure deviation data under environmental changes, providing a reliable foundation for subsequent dynamic adjustments. The corrected pressure deviation data is also stored in chronological order as a time series format. This time series format not only provides structured information for subsequent data analysis but also facilitates in-depth analysis of dynamic changes. The time series format includes the pressure deviation value and timestamp for each time point, ensuring the data is arranged chronologically for easy difference calculation and trend analysis. This technical solution clearly shows the pressure deviation changes at each time point, thereby identifying the patterns of pressure fluctuations and providing a basis for pressure regulation.

[0062] Furthermore, the acquisition of the rate of change sequence, such as... Figure 2 As shown, it includes:

[0063] Based on the initial pressure deviation sequence, the data difference between adjacent time points is calculated to obtain the pressure deviation difference sequence; based on pipeline vibration data, the pressure deviation difference sequence is smoothed to obtain a smoothed difference sequence; based on the smoothed difference sequence, the pressure deviation change per unit time is calculated to generate the change rate sequence, wherein the change rate sequence reflects the dynamic change trend of the pressure deviation.

[0064] Specifically, during the real-time adjustment of the coke oven gas collecting pipe pressure, the collected pressure deviation data is not only affected by high temperatures in actual industrial applications, but also frequently accompanied by significant noise and abnormal fluctuations in the complex environment of frequent gas collecting pipe vibration. Traditional processing methods struggle to effectively distinguish between actual pressure changes and external interference, easily leading to delays or misjudgments in the adjustment response, thus affecting the timeliness of gas collecting pipe pressure adjustment and the stability of system operation. Therefore, based on the initial pressure deviation sequence, the data difference between adjacent time points is calculated to obtain a pressure deviation difference sequence. On this basis, the pressure deviation difference sequence is smoothed in conjunction with the degree of influence of pipeline vibration. This smoothing process typically employs a weighted average algorithm. Before smoothing, the degree of vibration influence is first assessed. The degree of vibration influence is a quantitative indicator obtained by measuring the vibration amplitude and frequency of the pipeline. If the vibration amplitude and frequency meet the preset high vibration influence conditions, the preset smoothing window width is automatically increased to enhance noise reduction capabilities; otherwise... The preset smoothing window is narrowed to maintain sensitivity and achieve high-fidelity reproduction of real pressure changes. The smoothed data can more accurately reflect the real pressure change over time and suppress the interference of irrelevant noise on the pressure in the gas collecting pipe. For example, when there is a large mechanical impact outside the pipeline, such as other mechanical equipment in the factory that generates large vibrations, the unsmoothed pressure rate sequence will exhibit high-frequency fluctuations, which can easily lead to misjudgment of the actual pressure condition in the gas collecting pipe. After introducing the smoothing algorithm, short-term anomalies are automatically filtered out. Based on the smoothed difference sequence, the pressure deviation change per unit time is calculated to generate the change rate sequence. The unit time can be 5 seconds. The change rate sequence can continuously reflect the real change of pressure deviation, providing a reliable basis for subsequent adjustment decisions. The above technical solution can eliminate the error caused by complex disturbance factors in the industrial field and obtain the change rate sequence that can reflect the real pressure deviation change, laying the foundation for improving the accurate prediction of gas collecting pipe pressure deviation.

[0065] Furthermore, the acquisition of the changing acceleration sequence includes:

[0066] The rate of change sequence is corrected based on the measured thermal expansion pressure increment and cooling contraction pressure decrease, and a second difference calculation is performed based on the corrected rate of change sequence to obtain acceleration data of the rate of change; according to the acceleration data, the change acceleration sequence is generated, wherein the change acceleration sequence is used to characterize the acceleration characteristics of pressure deviation change.

[0067] Specifically, because pressure fluctuations in the coke oven gas collecting pipe may be non-linear in complex environments, existing pressure regulation systems struggle to fully account for the complexity of pressure changes. This is especially true under high-temperature and high-pressure conditions, where external factors such as temperature fluctuations and pipe vibrations are not effectively addressed. Traditional systems, relying solely on simple pressure change rate or temperature corrections, cannot accurately capture the acceleration or deceleration trends of pressure changes, and consequently, cannot precisely adjust the pressure in the gas collecting pipe. Therefore, this paper connects the data at each time point in the rate of change sequence and plots a curve, calculating the slope value to quantify the trend direction. The positive slope values ​​are represented in the table. The pressure deviation is shown to increase, with negative values ​​indicating a decreasing trend. Based on the slope distribution, trend inflection points are identified, and dynamic evolution characteristics such as acceleration or deceleration stages are determined. Furthermore, based on the thermal expansion pressure increment and the cooling contraction pressure decrease, a second difference calculation is performed on the aforementioned rate of change sequence to obtain the acceleration data of the rate of change. The calculation process for the thermal expansion pressure increment and the cooling contraction pressure decrease is as follows: [details omitted]. The temperature at the two time points corresponding to the two data points in the initial sequence of the aforementioned rate of change sequence is calculated, and the first and second products of the expansion coefficients of the corresponding pipe material at that temperature are respectively used as the aforementioned rate of change. The thermal expansion or cooling contraction pressure reduction at each data point in the rate of change sequence is used to correct the rate of change sequence. This means that the pressure change between two pressure data points at the ends of a time period in the rate of change sequence may be due to changes in the actual pressure, or pressure changes caused by pipe temperature changes leading to pipe expansion or contraction. Therefore, the rate of change sequence is corrected using the thermal expansion pressure increase or the cooling contraction pressure decrease, i.e., P2(n) = P1(n) + ΔP, where P2(n) is the corrected rate of change. The nth value in the rate sequence, P1(n) is the nth value in the rate sequence before correction, and ΔP is the correction value, which is obtained through empirical actual measurement and is not a fixed value. The difference between two adjacent values ​​is calculated sequentially based on the data order in the rate sequence after correction, i.e., the above-mentioned second difference calculation, to obtain the above-mentioned acceleration data. Based on the above-mentioned acceleration data, the above-mentioned change acceleration sequence is generated. The above technical solution can more accurately capture the small fluctuations and acceleration and deceleration trends of the pressure change process in the gas collecting pipe, providing higher precision data basis for pressure deviation prediction and dynamic adjustment, thereby improving the production quality of coke.

[0068] Furthermore, the acquisition of the predicted deviation trajectory includes:

[0069] The current temperature gradient distribution of the gas collecting pipe is obtained, and the temperature gradient distribution, the currently collected pressure data, the set target pressure data, the change rate sequence and the change acceleration sequence within a preset time period before the current time period are input into the prediction model to obtain the prediction deviation trajectory. The temperature gradient is obtained by calculating the ratio of the temperature difference between adjacent temperature sensors set at different locations in the key area of ​​the gas collecting pipe to the distance between them.

[0070] Specifically, since the temperature inside the gas collecting pipe is the main factor affecting the pressure change cycle within the pipe, the temperature gradient distribution is acquired in real time. This temperature gradient distribution is obtained by calculating the temperature difference between one temperature sensor and an adjacent temperature sensor at different locations in the key area of ​​the gas collecting pipe, divided by the distance between the two temperature sensors. The extreme result represents the temperature gradient between the two sensor locations. The key area best reflects the gas pressure inside the gas collecting pipe. Then, the impact of these temperature gradients on the pressure fluctuation cycle is analyzed. The fluctuation cycle refers to the repetition time interval between the peak and trough of the pressure deviation at the key location in the gas collecting pipe. The key location is where the pressure inside the gas collecting pipe affects the quality of coke production. The currently acquired temperature gradient distribution, the current pressure data inside the gas collecting pipe, the change rate sequence and the change acceleration sequence within a preset time period before the current time period are input into the prediction model to obtain the prediction deviation result. The training process includes: analyzing the correlation between historical temperature gradient distribution and the pressure change cycle within the gas collecting pipe; using the correlation, historical temperature gradient distribution and corresponding historical rate of change and acceleration of change sequences, historical collected pressure values ​​and historical target pressure values ​​as training data; and training the prediction model based on the training data. To obtain the real-time pressure deviation value within the gas collecting pipe, the real-time acquired temperature gradient distribution, the set target pressure data within the gas collecting pipe, the currently collected pressure data within the gas collecting pipe, and the rate of change and acceleration of change sequences within a preset time period prior to the current time period are input into the prediction model to obtain the prediction deviation trajectory. The prediction model can be a Kalman filter model. The prediction deviation trajectory is used for subsequent threshold judgment and deviation impact assessment. This technical solution, through the introduction of the prediction model, can accurately predict the pressure fluctuation cycle characteristics, thereby effectively avoiding the risk of pressure deviation exceeding the preset threshold range and ensuring stable pressure operation within the gas collecting pipe.

[0071] Furthermore, the deviation affects the acquisition of the evaluation value, such as Figure 3 As shown, it includes:

[0072] Determine whether the predicted deviation trajectory exceeds a preset threshold range; if it does, obtain historical pressure deviation data and perform comparative analysis based on the requirements for adapting to high temperature and high pressure environments.

[0073] Based on the comparative analysis, the expected impact of the predicted deviation trajectory on system stability is calculated, and the deviation impact assessment value is generated. The deviation impact assessment value is used for the subsequent generation of pressure regulation parameters.

[0074] Specifically, by determining whether the predicted deviation trajectory exceeds a set threshold range, it is determined whether the pressure in the gas collecting pipe meets the requirements of the coke production process. The set threshold range includes preset upper and lower limits, which are derived from historical stable operating data. Through the analysis of historical data, a reasonable upper and lower limit range is established for pressure fluctuations under different environmental and operating conditions. When the real-time predicted pressure deviation trajectory exceeds this range, it indicates that the pressure in the gas collecting pipe needs to be adjusted to ensure the coke production quality; otherwise, it does not. When the pressure in the gas collecting pipe needs to be adjusted, in order to improve the adjustment accuracy, historical pressure data is compared and analyzed to confirm whether this deviation will affect the stability of the gas collecting pipe system. The specific implementation steps of the comparative analysis include: calculating the distance between each data point of the current predicted trajectory and the data points of the same time sequence in the historical data, that is, evaluating the similarity between the current trajectory and the historical known deviation trajectory. For example, through the above similarity, it can be found that the current predicted trajectory is very similar to the violent pressure fluctuations that have occurred in the past under high temperature and high pressure conditions. At this point, the system automatically invokes a linear regression model, using the predicted trajectory and historical pressure deviation sequences as input variables to obtain the expected impact on coke oven stability. If similar historical pressure fluctuations have previously caused a 20% decrease in system stability, the regression analysis yields a deviation impact assessment value of 0.75, indicating that the system is already in a high-risk warning state. For example, under conditions of high temperature and high pressure, the weight of historical data may need to be increased to better adapt to this high-temperature and high-pressure working environment. This process ensures that the system can flexibly adjust the impact of historical data according to the actual working conditions, thus making the deviation impact assessment more accurate. Next, the system compares the compared historical data with the predicted deviation trajectory point by point, calculating their similarity. A commonly used method is Euclidean distance calculation, which assesses the similarity between two data vectors by measuring the difference between them.

[0075] After similarity calculation, the system obtains a deviation impact assessment value by fitting the relationship between the predicted deviation trajectory and historical stability effects. This assessment value reflects the expected impact of the current predicted deviation trajectory on system stability. A higher assessment value indicates that the current pressure deviation is more likely to cause instability, while a lower value indicates that the system's pressure deviation is within an acceptable range. The generated deviation impact assessment value will be used as the basis for generating pressure regulation parameters in subsequent steps. This technical solution can not only respond to changes in gas collecting pipe pressure in real time, but also make accurate predictions of future pressure change trends based on comparative analysis of historical data, providing necessary data support for subsequent pressure regulation, predicting potential system risks in advance, and avoiding instability through precise adjustment parameters. Through historical data comparative analysis, the system can adapt to environmental changes in real time, improving the accuracy and stability of the regulation process. At the same time, the correlation analysis of temperature and pressure ensures the reliability of the system in complex environments, especially under extreme conditions such as high temperature and high pressure. The effectiveness and accuracy of this method ensure that the dynamic regulation of gas collecting pipe pressure is more in line with actual needs, thereby improving the overall system operating efficiency and coke production quality.

[0076] Further, based on the deviation impact assessment value, pressure regulation parameters are generated to obtain valve opening adjustment commands, including:

[0077] Based on the deviation impact assessment value, the response characteristics of the pressure valve adjustment sensitivity are analyzed; combined with the analysis results, the parameters required for the gas collecting pipe pressure adjustment are calculated, and pressure adjustment parameters are generated; based on the pressure adjustment parameters, the valve opening adjustment amount is determined, and the valve opening adjustment command is generated, wherein the valve opening adjustment command is used to control the real-time adjustment of the gas collecting pipe pressure valve.

[0078] Specifically, after the system derives a deviation impact assessment value through comparative analysis of historical data, this assessment value provides the basis for generating adjustment parameters. This assessment value reflects the expected impact of the current predicted pressure deviation on the stability of the gas collection pipe system. A higher deviation impact assessment value indicates a greater potential impact on system stability, requiring more rapid and forceful adjustment measures. Therefore, the system adjusts its pressure regulation strategy based on the deviation impact assessment value. In other words, by analyzing the deviation impact assessment value, the system can identify whether the current pressure deviation requires significant or minor adjustments to maintain system stability.

[0079] When generating pressure regulation parameters, the system also considers the regulation response characteristics of the pressure valve's sensitivity. The valve's sensitivity determines the response speed between valve opening and pressure regulation. Based on the deviation impact assessment value, for example, if the assessment value is high, the system may increase the valve's regulation sensitivity, thereby accelerating the pressure regulation process and avoiding system instability caused by excessive pressure fluctuations. Under low assessment values, the system may adopt a more moderate regulation strategy to mitigate pressure changes and ensure stable system operation. Furthermore, the system uses a proportional-integral-derivative (PID) control algorithm to accurately calculate the specific parameters required for pressure regulation. The PID controller can dynamically adjust the valve opening based on real-time pressure changes and their deviations. The proportional term directly determines the valve opening adjustment based on the pressure deviation, the integral term accumulates historical deviations to ensure effective control of long-term pressure change trends, and the derivative term predicts the rate of pressure change, providing a basis for rapid response to pressure fluctuations. The system adjusts the parameter settings in the PID controller according to different deviation impact assessment values ​​to optimize the regulation effect. Specifically, when the deviation affects the evaluation value, the PID controller increases the weights of the proportional and derivative terms, making the pressure regulation response more rapid and preventing the system pressure from being too high or too low. Conversely, when the evaluation value is low, the weight of the integral term increases, thereby better maintaining a stable state when the pressure changes gradually.

[0080] Once the pressure regulation parameters are calculated, the system translates them into specific valve opening adjustment commands. These commands are sent to the pressure valves in the manifold in real time to adjust the valve openings and precisely control pressure changes. For example, if the calculated parameters indicate that the valve opening needs to be increased by 20%, the command will ensure that the valve opens accordingly, effectively reducing pressure fluctuations in the manifold. Simultaneously, the system monitors the valve's actual response to ensure that the pressure regulation meets predetermined standards, preventing system overload or malfunction due to adjustment errors.

[0081] The aforementioned technical solution, through precise calculation of the impact assessment value of deviations and analysis of the response characteristics of pressure regulation parameters and valve sensitivity, ultimately generates precise valve opening adjustment commands via PID control, ensuring that the system's pressure regulation achieves dynamic control on an efficient and stable basis. This process demonstrates the crucial role of intelligent control in high-temperature and high-pressure environments, thereby providing a more reliable guarantee for the stable operation of the gas collecting pipe pressure.

[0082] Further, the step of verifying the adjustment effect based on the updated pressure deviation sequence, determining whether the stable operating conditions are met, and obtaining the pressure stable state includes:

[0083] Based on the updated pressure deviation sequence and combined with the high-pressure sealing performance requirements, the changing trend of the pressure deviation is analyzed; the adjustment effect of the valve opening adjustment command is verified.

[0084] Based on the adjustment effect, it is determined whether the updated pressure deviation sequence meets the preset stable operating conditions, and the pressure stable state is generated, wherein the pressure stable state characterizes the operating stability of the gas collection pipe system.

[0085] Specifically, this step verifies the adjustment effect based on the updated pressure deviation sequence to ensure the system reaches a stable operating state. By monitoring and analyzing the updated pressure deviation sequence, the system analyzes the pressure deviation change trend in conjunction with high-pressure sealing performance requirements. The core of data processing lies in using the relationship between historical pressure data and real-time pressure changes to evaluate whether the adjusted pressure deviation meets the preset stable operating conditions. In this process, a compensation mechanism corrects the effect of valve opening adjustment commands to ensure consistency between the actual pressure deviation and the expected target. Specifically, after valve adjustment, new pressure data is fed back in real time. The system evaluates the adjustment effect based on this data to determine whether the pressure stability conditions are met. If met, the system considers the adjustment successful and maintains the current operating state; if not met, further adjustments may be necessary. This ensures the stable operation of the gas collection pipe system, improves overall production efficiency, and reduces the risk of equipment failure. The above technical solution improves the pressure regulation accuracy within the gas collection pipe through feedback regulation, ensuring the reliability of pressure regulation operations in complex industrial environments.

[0086] This invention also provides a coke oven gas collecting pipe pressure dynamic adjustment system based on intelligent control, used to implement the above-mentioned method, such as... Figure 4 As shown, the system includes:

[0087] The calculation unit is used to acquire pressure deviation data from the gas collection pipe through a sensor, store it in a time series format to obtain an initial pressure deviation sequence; calculate the data difference based on the initial pressure deviation sequence and perform smoothing to obtain a rate of change sequence; analyze the changing trend of the rate of change sequence, calculate the second difference to obtain a rate of change sequence.

[0088] The prediction unit is used to predict the development trajectory of the pressure deviation based on the change rate sequence and the change acceleration sequence using a filtering method, and obtain the predicted deviation trajectory.

[0089] The generation unit is used to obtain a deviation impact assessment value by comparing and analyzing historical data if the predicted deviation trajectory exceeds a preset threshold range; and to generate pressure regulation parameters and obtain valve opening adjustment instructions based on the deviation impact assessment value.

[0090] The judgment unit is used to control the opening of the gas collecting pipe pressure valve through the valve opening adjustment command, obtain the adjusted pressure deviation data, and obtain the updated pressure deviation sequence; based on the updated pressure deviation sequence, verify the adjustment effect, determine whether the stable operation conditions are met, and obtain the pressure stable state.

[0091] The present invention also provides a computer-readable storage medium storing instructions that, when executed by a processor, implement the above-described method.

[0092] In summary, this invention provides a method for ensuring precise control of the gas collecting pipe pressure and stable system operation through coordinated operation of multiple steps. Starting from real-time pressure data, the gas collecting pipe pressure is gradually adjusted and its stability is ensured through a series of data processing and analysis steps. These steps complement each other, forming a closed-loop feedback control system capable of achieving efficient and precise pressure regulation under complex high-temperature and high-pressure environments. Specifically, high-precision sensors collect real-time pressure data from the gas collecting pipe and store it in a time-series format, providing a foundation for subsequent data analysis and processing. This initial data sequence is corrected for ambient temperature, eliminating the interference of temperature fluctuations on pressure measurement and ensuring data accuracy. Based on this, the system calculates the pressure difference between adjacent time points and performs smoothing to obtain a pressure deviation rate sequence. This process eliminates noise from external interference such as pipe vibration, ensuring that the rate sequence accurately reflects the true trend of pressure fluctuations. Further analysis of the rate sequence's trend and calculation of the secondary difference yield a change acceleration sequence. Considering the influence of thermal expansion pressure increments and cooling contraction pressure decreases on pressure changes, this process accurately captures the acceleration or deceleration phases of pressure changes. The changing acceleration sequence provides crucial reference data for subsequent predictions, enabling more accurate forecasting of the pressure deviation trajectory. This is further enhanced by combining the Kalman filter algorithm with the predicted pressure deviation trajectory. If the predicted trajectory exceeds a preset threshold range, the system calculates a deviation impact assessment value through historical data comparison and analysis. This assessment value effectively evaluates the impact of the predicted deviation on system stability and provides a basis for subsequent pressure regulation. Based on the deviation impact assessment value, the system generates pressure regulation parameters and uses a proportional-integral-derivative (PID) control algorithm to generate valve opening adjustment commands, dynamically adjusting the valve opening to precisely regulate the pressure in the gas collection pipe.

[0093] After adjustment, the system verifies the adjustment effect and determines whether stable operation conditions are met through a feedback mechanism based on the updated pressure deviation sequence. If the adjustment does not achieve the expected results, the system will readjust to ensure that the gas collecting pipe pressure remains within a stable range. This invention, through the orderly coordination of multiple steps, ensures precise adjustment of the gas collecting pipe pressure and stable system operation, forming a closed-loop control system that can dynamically respond to environmental changes and adjust pressure in real time, thereby improving the quality of coke production.

[0094] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the present invention will not describe the various possible combinations separately. Furthermore, various different embodiments of the present invention can also be arbitrarily combined, as long as they do not violate the spirit of the present invention, and should also be regarded as the content disclosed by the present invention.

Claims

1. A method for dynamic adjustment of coke oven gas collecting pipe pressure based on intelligent control, characterized in that, include: Pressure deviation data is acquired from the gas collection pipe by a sensor and stored in a time series format to obtain the initial pressure deviation sequence. Based on the initial pressure deviation sequence, the data difference is calculated and smoothed to obtain the rate of change sequence; Analyze the changing trend of the rate of change sequence, calculate the quadratic difference, and obtain the changing acceleration sequence; Based on the change rate sequence and the change acceleration sequence, a filtering method is used to predict the development trajectory of the pressure deviation, and the predicted deviation trajectory is obtained. If the predicted deviation trajectory exceeds the preset threshold range, a deviation impact assessment value is obtained through historical data comparison and analysis; based on the deviation impact assessment value, pressure regulation parameters are generated, and valve opening adjustment commands are obtained. The valve opening adjustment command is used to control the opening of the gas collecting pipe pressure valve, obtain the adjusted pressure deviation data, and obtain the updated pressure deviation sequence. Based on the updated pressure deviation sequence, the adjustment effect is verified, it is determined whether the stable operation conditions are met, and the pressure stability state is obtained.

2. The method according to claim 1, characterized in that, The acquisition of the initial sequence of pressure deviation includes: The pressure sensor acquires the raw pressure value from the gas collection pipe at a preset real-time data acquisition frequency, and obtains pressure deviation data based on the raw pressure value and the target pressure value. The pressure deviation data is initially corrected based on the interference of ambient temperature to obtain the corrected pressure deviation data. The corrected pressure deviation data is stored in time sequence as a time series format to generate the initial pressure deviation sequence. The time series format includes timestamps and corresponding pressure deviation values. The initial pressure deviation sequence is used for subsequent data difference calculation and trend analysis.

3. The method according to claim 2, characterized in that, The acquisition of the rate of change sequence includes: Based on the initial pressure deviation sequence, the data difference between adjacent time points is calculated to obtain the pressure deviation difference sequence; based on pipeline vibration data, the pressure deviation difference sequence is smoothed to obtain a smoothed difference sequence; based on the smoothed difference sequence, the pressure deviation change per unit time is calculated to generate the change rate sequence, wherein the change rate sequence reflects the dynamic change trend of the pressure deviation.

4. The method according to claim 1, characterized in that, The acquisition of the changing acceleration sequence includes: Based on the measured thermal expansion pressure increment and cooling contraction pressure decrease, a second difference calculation is performed on the change rate sequence to obtain the acceleration data of the change rate. Based on the acceleration data, the variable acceleration sequence is generated, wherein the variable acceleration sequence is used to characterize the acceleration characteristics of pressure deviation changes.

5. The method according to claim 1, characterized in that, The acquisition of the predicted deviation trajectory includes: The current temperature gradient distribution of the gas collecting pipe is obtained, and the temperature gradient distribution, the currently collected pressure data, the set target pressure data, the change rate sequence and the change acceleration sequence within a preset time period before the current time period are input into the prediction model to obtain the prediction deviation trajectory. The temperature gradient is obtained by calculating the ratio of the temperature difference between adjacent temperature sensors set at different locations in the key area of ​​the gas collecting pipe to the distance between them.

6. The method according to claim 1, characterized in that, The deviation affects the acquisition of the evaluation value, including: Determine whether the predicted deviation trajectory exceeds a preset threshold range; If the deviation exceeds the limit, historical pressure deviation data will be obtained and compared with the requirements for adapting to high temperature and high pressure environments. Based on the comparative analysis, the expected impact of the predicted deviation trajectory on system stability is calculated, and the deviation impact assessment value is generated. The deviation impact assessment value is used for the subsequent generation of pressure regulation parameters.

7. The method according to claim 1, characterized in that, Based on the deviation impact assessment value, pressure regulation parameters are generated, and valve opening adjustment commands are obtained, including: Based on the aforementioned deviation impact assessment value, analyze the response characteristics of the pressure valve adjustment sensitivity; Based on the analysis results, calculate the parameters required for regulating the pressure of the gas collecting pipe and generate the pressure regulation parameters. Based on the pressure regulation parameters, the valve opening adjustment amount is determined, and the valve opening adjustment command is generated. The valve opening adjustment command is used to control the real-time adjustment of the gas collecting pipe pressure valve.

8. The method according to claim 1, characterized in that, The step of verifying the adjustment effect based on the updated pressure deviation sequence, determining whether the stable operating conditions are met, and obtaining the pressure stable state includes: Based on the updated pressure deviation sequence and combined with the high-pressure sealing performance requirements, the changing trend of the pressure deviation is analyzed; the adjustment effect of the valve opening adjustment command is verified. Based on the adjustment effect, it is determined whether the updated pressure deviation sequence meets the preset stable operating conditions, and the pressure stable state is generated, wherein the pressure stable state characterizes the operating stability of the gas collection pipe system.

9. A coke oven gas collecting pipe pressure dynamic adjustment system based on intelligent control, used to implement the method as described in any one of claims 1-8, characterized in that, The system includes: The calculation unit is used to acquire pressure deviation data from the gas collection pipe through a sensor, store it in a time series format to obtain an initial pressure deviation sequence; calculate the data difference based on the initial pressure deviation sequence and perform smoothing to obtain a rate of change sequence; analyze the changing trend of the rate of change sequence, calculate the second difference to obtain a rate of change sequence. The prediction unit is used to predict the development trajectory of the pressure deviation based on the change rate sequence and the change acceleration sequence using a filtering method, and obtain the predicted deviation trajectory. The generation unit is used to obtain a deviation impact assessment value by comparing and analyzing historical data if the predicted deviation trajectory exceeds a preset threshold range; and to generate pressure regulation parameters and obtain valve opening adjustment instructions based on the deviation impact assessment value. The judgment unit is used to control the opening of the gas collecting pipe pressure valve through the valve opening adjustment command, obtain the adjusted pressure deviation data, and obtain the updated pressure deviation sequence; based on the updated pressure deviation sequence, verify the adjustment effect, determine whether the stable operation conditions are met, and obtain the pressure stable state.

10. A computer-readable storage medium storing instructions thereon, characterized in that, When the instructions are executed by the processor, they implement the method as described in any one of claims 1-8.

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