A heat recovery coke oven distributed control system and intelligent adjustment method

Abstract

The present application relates to coke oven heating technical field, specifically relates to a kind of heat recovery coke oven distributed control system and intelligent adjustment method, including calculation analysis module and multiple execution module, multiple execution module and communication transmission between calculation analysis module, execution module is used to monitor and execute air intake adjustment to heat recovery coke oven, calculation analysis module is used to calculate and analyze the data monitored by execution module;Calculation analysis module includes access unit, processing unit, calculus unit, decision unit and feedback unit, access unit is used to access the data transmission of execution module;The present application can make that whole oven is balanced and stable temperature rise, solved the inconsistency of coking caused by the temperature difference of coke oven, also solved the problem of unstable temperature rise in coking middle period, temperature fluctuation is accurately controlled in ±5 ℃ range, improve the stability of temperature rise, simultaneously can also avoid closing air intake delay after coking late period, cause the problem of local coking cake coking.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of coke oven heating, in particular to a heat recovery coke oven distributed control system and intelligent adjustment method. BACKGROUND

[0002] The coke oven heating process refers to the engineering technology of monitoring and managing the heating process of the coke oven and the thermal state of the oven body during the coking process. The coke oven heating technology plays a crucial role in the steel industry. This technology heats the furnace charge through high-temperature combustion gas to achieve pyrolysis of the furnace charge.

[0003] For example, a coke oven intelligent thermal control method with application number CN202411180575.6 and publication date 20241217 is related to the technical field of coke oven heating and combustion control. The specific implementation scheme is as follows: a physical model of two groups of vertical flues in the coke oven and the carbonization chamber between the two groups of vertical flues is established; based on the mathematical model and the physical model, the real-time coking heat consumption of coal in the carbonization chamber with the coking time is obtained; based on the real-time coking heat consumption, the mature fire falling time, and the measured temperature of the vertical flue, the mixed coal gas flow output to the coke oven is determined; based on the mixed coal gas flow, the mixed coal gas is output to the coke oven, which reduces the cost.

[0004] In order to ensure the internal temperature of the coke oven, the size of the flange type rotary disc is used to control the air volume of the furnace top, thereby regulating the temperature of the furnace top space. In addition, the opening of the upper and lower plug-in plates is used to control the air volume of the four-arch long direction of the coke oven, thereby controlling the temperature of the four-arch long direction and ensuring the temperature balance of the four-arch long direction. However, this method has the following disadvantages:

[0005] First, the original adjustment method has a large human factor, which causes instability of the temperature rising process.

[0006] Second, the large opening in the early stage causes uncontrollable emission factors (nitrogen oxides);

[0007] Third, in the middle stage of coking, the temperature stability control is poor, which easily causes large fluctuations in temperature and affects the quality of coke;

[0008] In the later stage of coking, the closing cannot be timely, which easily causes coking;

[0009] Therefore, the present application provides a heat recovery coke oven distributed control system and intelligent adjustment method to solve the above problems. SUMMARY

[0010] The purpose of the present application is to provide a heat recovery coke oven distributed control system and intelligent adjustment method to solve the above problems in the prior art.

[0011] In order to achieve the above purpose, the present application provides the following technical scheme:

[0012] A heat recovery coke oven distributed control system, comprising a calculation analysis module and a plurality of execution modules, the plurality of execution modules and the calculation analysis module are in communication transmission, the execution module is used for monitoring and executing the air inlet adjustment of the heat recovery coke oven, the calculation analysis module is used for calculating and analyzing the data monitored by the execution module, the execution module is arranged on the five primary air inlets at the top of the heat recovery coke oven and the eight secondary air inlets of the four side arches, the execution module is divided into air volume detection sensors, electric actuators and butterfly valves, the calculation analysis module is programmed by Siemens TIAPortal V17, and the calculation analysis module is a WINCC system, and the WINCC system is loaded on a Siemens 1500 series CPU carrying 72 PNIO substations.

[0013] The calculation analysis module comprises an access unit, a processing unit, a calculation unit, a decision unit and a feedback unit.

[0014] The access unit is used for accessing the data transmitted by the execution module, the access unit is constructed by API client technology, and the access unit specifically receives the data transmitted by the execution module through a wireless network, and it should be noted that API is a set of predefined functions, protocols and tools for constructing software applications, which defines the interaction between software components, so that different software systems can be seamlessly integrated together, and the basic principles of API technology include request-response model, data formatting and security.

[0015] The processing unit is used for processing the data received by the access unit, and the processing unit comprises a classification module and an optimization module, the classification module classifies and induces the data received by the access unit through data classification and induction technology, and the optimization module calculates the data classified by the classification module through abnormal value and missing value identification technology, and the abnormal value calculation process is as follows:

[0016] S2-1. Calculate the statistical quantity: calculate the average value (mean value) and standard deviation statistical quantity of the data set;

[0017] ‌S2-2. Determine the threshold value: according to the average value and the standard deviation, determine a threshold value range, the threshold value is set by adding or subtracting 2 or 3 times the standard deviation from the average value, and the data points exceeding this range will be regarded as outliers;

[0018] ‌S2-3. Result calculation and processing: calculate the distance between data points, obtain outliers, get data outliers, and then mark and delete the outliers.

[0019] The missing value calculation process is as follows:

[0020] S3-1. Search each data in the data set to be calculated by data traversal technology, and compare the data with the normal operation data of the same state of the heat recovery coke oven;

[0021] S3-2. According to the comparison result, confirm the missing value in the data set, and supplement the missing value by reacquiring the operation data of the heat recovery coke oven through the execution module.

[0022] The calculation unit is used for calculating the data processed by the processing unit, and includes a virtual module and a comparison module. The virtual module is constructed according to the past operation data of the heat recovery coke oven. The virtual module virtually simulates the operation process of the heat recovery coke oven through three-dimensional modeling technology. The comparison module is used for judging the data generated by the virtual module and the data processed by the processing unit. The judging steps of the comparison module are as follows:

[0023] S1-1. Data conversion and optimization: convert the data into vectors, and clean the converted vector data;

[0024] S1-2. Data calculation and comparison: calculate the converted vector data through the Euclidean distance formula to obtain the corresponding Euclidean distance 、 , and then compare and process through a comparison formula as follows:

[0025]

[0026] wherein, S is and the comparison value, if 1±0.033%<S<1±0.05%, it indicates and high similarity, the data generated by the virtual module and the data processed by the processing unit are approximately the same;

[0027] S1-3. Result output: calculate the numerical value according to the comparison formula, and output the judgment result of the comparison module.

[0028] The decision unit generates a control decision according to the calculation result of the calculation unit, and includes an intelligent AI module and a screening module. The intelligent AI module searches the past solutions to the problems of the heat recovery coke oven on the enterprise website through keyword search technology. The intelligent AI module also searches the problem solving solutions on the Internet through keyword search technology. The screening module screens the solutions searched by the intelligent AI module through the number of application solutions, and confirms the optimal decision solution.

[0029] The feedback unit is used for applying the regulation decision generated by the decision unit to the coke oven, and the feedback unit is established through remote control technology, and network remote control is specifically selected, and the feedback unit adjusts the operation of the coke oven through direct control of the execution module.

[0030] A heat recovery coke oven intelligent adjustment method, comprising the following steps:

[0031] Step S1, data acquisition: obtaining heat recovery coke oven operation data through sensors, and specifically material proportioning information, material blending coal index, heat recovery coke oven fan frequency, suction size, temperature rising rate, primary and secondary air inlet opening degree;

[0032] Step S2, data analysis: real-time analysis of data through a calculation and analysis module, identification of patterns and trends in the heating process, and description of the coke oven heating process through virtual technology;

[0033] Step S3, data visualization: establishing a variety of temperature rising curve models, and internally setting the temperature rising curve models and experience opening degree, fuzzying the time-temperature and time-opening degree curves, double-fuzzing the time, opening degree and temperature, and using PID for precise adjustment to construct a dynamic visual view;

[0034] Step S4, dynamic adjustment: adjusting the heating parameters according to the real-time data dynamic view, comparing the virtual data with the actual data of the coke oven through the calculation and analysis module, and adjusting the coke oven again according to the comparison result to achieve the ideal heating effect.

[0035] In the above technical solution, the heat recovery coke oven distributed control system and the intelligent adjustment method provided by the application have the following beneficial effects:

[0036] (1) The application can make the whole oven heat up evenly and stably, solve the inconsistency of coking caused by the difference in oven temperature rising, and also solve the problem of unstable temperature rising in the middle of coking, accurately control the temperature fluctuation within ±5℃, improve the stability of temperature rising, and avoid the problem of local coking caused by the delay of closing the air inlet in the later coking period.

[0037] (2) The application can establish a virtual operation model of the coke oven through virtual technology, simulate the normal operation process of the coke oven, compare the virtual operation data with the actual data of the coke oven, find the differences in the actual operation of the coke oven, determine whether there is a problem in the actual operation of the coke oven, and automatically generate a solution after finding the problem, directly adjust the coke oven, and quickly avoid the risk problems caused by improper operation of the coke oven.

[0038] (3) The application can make the air intake of the whole coking process controllable, and the emission factors such as nitrogen oxide and oxygen content of a single furnace are within a controllable range, thereby improving the intelligent management degree of the coke oven and reducing the risk of manual management. BRIEF DESCRIPTION OF DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can also be obtained by those skilled in the art according to these drawings.

[0040] Figure 1 The system flowchart provided by the embodiment of the present application is provided for a heat recovery coke oven distributed control system and an intelligent adjustment method.

[0041] Figure 2 The coke oven structure diagram provided by the embodiment of the present application is provided for a heat recovery coke oven distributed control system and an intelligent adjustment method.

[0042] Figure 3 The processing unit diagram provided by the embodiment of the present application is provided for a heat recovery coke oven distributed control system and an intelligent adjustment method.

[0043] Figure 4 The calculation unit diagram provided by the embodiment of the present application is provided for a heat recovery coke oven distributed control system and an intelligent adjustment method.

[0044] Figure 5 The decision unit diagram provided by the embodiment of the present application is provided for a heat recovery coke oven distributed control system and an intelligent adjustment method.

[0045] Figure 6 The method flowchart provided by the embodiment of the present application is provided for a heat recovery coke oven distributed control system and an intelligent adjustment method. DETAILED DESCRIPTION

[0046] In order to make those skilled in the art better understand the technical solutions of the present application, the present application will be further described in detail with reference to the drawings.

[0047] As Figures 1-5As shown, the embodiment of the present application provides a heat recovery coke oven distributed control system, which comprises a calculation and analysis module and a plurality of execution modules, the plurality of execution modules and the calculation and analysis module are in communication transmission, the execution module is used for monitoring and executing air inlet adjustment of the heat recovery coke oven, the calculation and analysis module is used for calculating and analyzing the data monitored by the execution module, the execution module is arranged on five primary air inlets at the top of the heat recovery coke oven and eight secondary air inlets of the four side arches, the execution module is divided into an air volume detection sensor, an electric actuator and a butterfly valve, the calculation and analysis module is programmed by Siemens TIAPortalV17, and the calculation and analysis module is specifically a WINCC system, and the WINCC system is loaded on a Siemens 1500 series CPU which is provided with 72 PNIO substations.

[0048] The calculation and analysis module comprises an access unit, a processing unit, a calculation unit, a decision unit and a feedback unit.

[0049] The access unit is used for accessing the data transmitted by the execution module, the access unit is constructed by API client technology, and the access unit specifically receives the data transmitted by the execution module through a wireless network, and it should be noted that API is a set of predefined functions, protocols and tools for constructing software application programs, which defines the interaction mode between software components, so that different software systems can be seamlessly integrated together, and the basic principles of API technology include request-response model, data formatting and security.

[0050] The processing unit is used for processing the data received by the access unit, and the processing unit comprises a classification module and an optimization module, the classification module classifies and induces the data received by the access unit through data classification and induction technology, and the optimization module calculates the data classified by the classification module through abnormal value and missing value identification technology, and the abnormal value calculation process is as follows:

[0051] S2-1. Calculate the statistical quantity: calculate the average value (mean value) and standard deviation statistical quantity of the data set;

[0052] ‌S2-2. Determine the threshold value: according to the average value and the standard deviation, a threshold value range is determined, the threshold value is set by adding or subtracting 2 or 3 times the standard deviation from the average value, and the data points exceeding this range will be regarded as outliers;

[0053] ‌S2-3. Result calculation and processing: calculate the distance between data points, obtain outliers, get data abnormal values, and then mark and delete the abnormal values.

[0054] The missing value calculation process is as follows:

[0055] S3-1. Search each data in the data set to be calculated by data traversal technology, and compare the data with the same state normal operation data of the heat recovery coke oven;

[0056] S3-2. According to the comparison result, confirm the missing value in the data set, and supplement the missing value by reacquiring the operation data of the heat recovery coke oven through the execution module.

[0057] The calculation unit is used for calculating the data processed by the processing unit, and includes a virtual module and a comparison module. The virtual module is constructed according to the past operation data of the heat recovery coke oven. The virtual module virtually simulates the operation process of the heat recovery coke oven through a three-dimensional modeling technology. The comparison module is used for judging the data generated by the virtual module and the data processed by the processing unit. The judgment steps of the comparison module are as follows:

[0058] S1-1. Data conversion and optimization: convert the data into vectors, and clean the converted vector data;

[0059] S1-2. Data calculation and comparison: calculate the converted vector data through the Euclidean distance formula to obtain the corresponding Euclidean distance 、 It should be noted that in an n-dimensional space, the Euclidean distance formula is, (wherein, represents the i-th dimensional coordinate of the first point, represents the i-th dimensional coordinate of the second point), and subsequent comparison processing is performed through a comparison formula as follows:

[0060]

[0061] Wherein, S is and the comparison value, if 1±0.033%<S<1±0.05%, it indicates that and have a high similarity, and the data generated by the virtual module is roughly the same as the data processed by the processing unit;

[0062] S1-3. Result output: calculate the value according to the comparison formula, and output the judgment result of the comparison module.

[0063] The decision unit generates a regulation and control decision according to the calculation result of the calculation unit. The decision unit includes an intelligent AI module and a screening module. The intelligent AI module searches the past solutions to the problems of the heat recovery coke oven on the enterprise website through a keyword search technology. The intelligent AI module also searches the problem solving solutions on the Internet through the keyword search technology. The screening module screens the solutions searched by the intelligent AI module through the number of application times of the solutions, and confirms the optimal decision solution.

[0064] The feedback unit is used for applying the regulation decision generated by the decision unit to the coke oven, and the feedback unit is established through remote control technology, and network remote control is specifically selected; the feedback unit adjusts the operation of the coke oven through direct control of the execution module.

[0065] A heat recovery coke oven intelligent regulation method, as shown in the figure, comprises the following steps: Figure 6

[0066] Step S1. Data acquisition: the operation data of the heat recovery coke oven are acquired through sensors, and specifically, the material proportioning information, material blending coal index, heat recovery coke oven fan frequency, suction size, temperature rising rate, primary and secondary air inlet opening degree;

[0067] Step S2. Data analysis: the data are analyzed in real time through a calculation and analysis module, the mode and trend in the heating process are identified, and the coke oven heating process is described through virtual technology;

[0068] Step S3. Data visualization: a variety of temperature rising curve models are established, the temperature rising curve models and experience opening degree are internally built, the time-temperature and time-opening degree curves are fuzzified, the time, opening degree and temperature are doubly fuzzified, the PID is used for precise regulation, and a dynamic visual view is constructed;

[0069] Step S4. Dynamic adjustment: the heating parameters are adjusted according to the real-time data dynamic view, the virtual data are compared with the actual data of the coke oven through the calculation and analysis module, the coke oven is adjusted again according to the comparison result, and ideal heating effect is achieved.

[0070] The above only describes certain exemplary embodiments of the present application in a descriptive manner, and it is needless to say that the described embodiments can be modified in various ways without departing from the spirit and scope of the present application for ordinary skilled in the art. Therefore, the above figures and description are illustrative in nature and should not be understood as limiting the scope of protection of the claims of the present application.​

Claims

1. A distributed control system for a heat recovery coke oven battery, comprising a plurality of execution modules and a computational analysis module, characterized in that: A plurality of said execution modules are in communication transmission with a calculation and analysis module, the execution module is used for monitoring and executing air inlet adjustment of the heat recovery coke oven, and the calculation and analysis module is used for calculating and analyzing the data monitored by the execution module, wherein the data monitored by the execution module includes material ratio information, material blending coal index, heat recovery coke oven fan frequency, suction size, temperature rising rate and primary and secondary air inlet opening degree; The calculation and analysis module includes an access unit, a processing unit, a calculation unit, a decision unit and a feedback unit, the access unit is used for accessing the data transmitted by the execution module, the processing unit is used for processing the data received by the access unit, the calculation unit is used for calculating the data processed by the processing unit, the decision unit generates a control decision according to the calculation result of the calculation unit, and the feedback unit is used for applying the control decision generated by the decision unit to the coke oven; The calculation unit includes a virtual module and a comparison module, the virtual module is constructed according to the past heat recovery coke oven operation data, the virtual module simulates the heat recovery coke oven operation process through three-dimensional modeling technology and generates simulation data, and the comparison module is used for judging the data generated by the virtual module and the data processed by the processing unit, and the judgment steps of the comparison module are as follows: S1-1. Data conversion and optimization: convert the data into vectors and clean the converted vector data; S1-2. Calculation and comparison of data: the transformed vector data is calculated by the Euclidean distance formula to obtain the corresponding Euclidean distance , , and subsequent comparison processing is performed by a comparison formula as follows: wherein, is the real-time data vector distance, is the simulation data vector distance, S is is the contrast value, if 1±0.033%<S<1±0.05%, it indicates that the similarity is high, the data generated by the virtual module running is approximately the same as the data processed by the processing unit; is the contrast value, if 1±0.033%<S<1±0.05%, it indicates that the similarity is high, the data generated by the virtual module running is approximately the same as the data processed by the processing unit; S1-3. Result output: calculate the numerical value according to the comparison formula and output the comparison module judgment result; The decision unit generates a control decision according to the judgment result of the comparison module, when the similarity is not within the above range, the decision unit generates a decision to adjust the air inlet opening degree, and adjusts the air inlet opening degree through the feedback unit.

2. A heat recovery coke oven distributed control system according to claim 1, wherein, The execution module is arranged on the five primary air inlets at the top of the heat recovery coke oven and the eight secondary air inlets of the four side arches, and the execution module includes a wind volume detection sensor, an electric actuator and a butterfly valve.

3. A heat recovery coke oven distributed control system according to claim 1, wherein, The calculation and analysis module is programmed by Siemens TIAPortal V17, and the calculation and analysis module is a WINCC system loaded on a Siemens 1500 series CPU with 72 PNIO substations.

4. The heat recovery coke oven distributed control system of claim 1, wherein, The access unit is constructed by API client technology, and the access unit specifically receives the data transmitted by the execution module through a wireless network.

5. A heat recovery coke oven distributed control system according to claim 1 wherein, The processing unit includes a classification module and an optimization module, and the classification module classifies and induces the data received by the access unit through data classification and induction technology.

6. A heat recovery coke oven distributed control system according to claim 5, wherein, The optimization module calculates the data classified by the classification module through outlier and missing value identification technology, and the outlier calculation process is as follows: S2-1. Calculate the statistical quantity: calculate the average value (mean value) and standard deviation statistical quantity of the data set; ‌S2-2. Determine the threshold value: according to the average value and the standard deviation, a threshold value range is determined, the threshold value is set by adding or subtracting 2 or 3 times the standard deviation to the average value, and the data points exceeding this range will be regarded as outliers; ‌S2-3. Result calculation and processing: calculate the distance between data points, obtain outliers, get data outliers, and then mark and delete the outliers.

7. A heat recovery coke oven distributed control system according to claim 6 wherein, The missing value calculation process is as follows: S3-1. Search each data in the data set to be calculated by data traversal technology, and compare the data with the same state normal operation data of the heat recovery coke oven; S3-2. According to the comparison result, confirm the missing value in the data set, and through the execution module, obtain the heat recovery coke oven operation data again, and supplement the missing value.

8. A heat recovery coke oven distributed control system according to claim 1 wherein, The decision unit includes an intelligent AI module and a screening module. The intelligent AI module searches the enterprise website for past solutions to heat recovery coke oven problems through keyword search technology, and also searches the Internet for problem solutions through keyword search technology. The screening module screens the solutions searched by the intelligent AI module by the number of application times to confirm the optimal decision scheme.

9. A heat recovery coke oven distributed control system according to claim 1 wherein, The feedback unit is established by remote control technology. The feedback unit adjusts the operation of the coke oven by directly controlling the execution module.

10. A method for intelligent adjustment of a coke oven for heat recovery, characterized in that, The method comprises the following steps: Step S1. Obtain data: obtain heat recovery coke oven operation data through sensors, and specifically material proportioning information, material blending coal indicators, heat recovery coke oven fan frequency, suction size, temperature rise rate, primary and secondary air inlet opening; Step S2. Data analysis: real-time analysis of data by calculation and analysis module, identify patterns and trends in the heating process, and describe the coke oven heating process through virtual technology to generate simulation data; Step S3. Data visualization: establish multiple temperature rise curve models, and internally build temperature rise curve models and experience opening degree, fuzzy time temperature, time opening degree curve, double fuzzy time, opening degree, temperature, and use PID for precise adjustment to build dynamic visual view, which includes comparison of real-time data and simulation data; Step S4. Dynamic adjustment: adjust the heating parameters according to the real-time data dynamic view, and compare the virtual data with the actual data of the coke oven through the calculation and analysis module. According to the comparison result, when the similarity is not within the predetermined range, adjust the air inlet opening to achieve the ideal heating effect.

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