System and method for coordinating control groups to reduce calciner risks

Abstract

The present invention discloses a system and method for reducing the risk of a calcining furnace by a coordinated parameter control group, and relates to the technical field related to calcining furnaces. The system includes: receiving the gypsum calcining task requirements of the calcining furnace; generating a calcining furnace control plan; performing preheating stage control optimization to obtain a first-stage coordinated parameter control group; performing calcining stage control optimization to obtain a second-stage coordinated parameter control group; performing cooling stage control optimization to obtain a third-stage coordinated parameter control group; and combining the first-stage coordinated parameter control group, the second-stage coordinated parameter control group, and the third-stage coordinated parameter control group for calcining. The system solves the technical problems that the existing calcining furnace control has preset fixed parameters, is difficult to accurately respond to complex and changeable working conditions, and cannot perform refined control for each stage, which leads to insufficient risk prevention and control effects and poor production efficiency and product quality. The system realizes risk prediction and prevention and control, and achieves the technical effects of improving production efficiency, product quality, and reducing the operating risks of calcining furnaces.

Description

Technical Field

[0001] The present application relates to the technical field related to calcining furnaces, and in particular to a system and method for coordinating a control group to reduce the risk of a calcining furnace. Background Art

[0002] In today's industrial field, calcining furnaces, as key production equipment, are widely used in building materials, chemical industry, metallurgy and other industries. Among them, gypsum calcination is one of the important process. The gypsum calcination process is not only directly related to the quality and output of the product, but also involves energy consumption, emissions and production safety. Due to the high temperature and complex and changeable chemical reactions in the calcination process, it is often accompanied by risks in multiple stages such as preheating, calcination and cooling, such as material cracking caused by uneven preheating, equipment damage caused by excessive calcination temperature, and product performance degradation caused by too fast cooling. How to effectively reduce the operation risk of calcining furnaces has become a technical problem that needs to be solved urgently in the industry. Traditional calcining furnace control methods mostly rely on manual experience or simple preset fixed operating parameters. It is difficult to accurately respond to complex and changeable working conditions, and only focuses on the overall operating parameters, while ignoring the risks of specific stages such as preheating, calcination and cooling, resulting in limited risk prevention and control effects, thereby affecting the production efficiency and product quality of the calcining furnace.

[0003] Therefore, in the current calcination furnace related technologies, there are technical problems such as preset fixed parameters, difficulty in accurately responding to complex and changeable working conditions, and inability to perform fine control for each stage, which leads to insufficient risk prevention and control effects and poor production efficiency and product quality. Summary of the invention

[0004] The present application provides a system and method for coordinating the control group to reduce the risk of the calciner, thereby solving the technical problems of the existing calciner control, such as the preset fixed parameters, the difficulty in accurately responding to complex and changeable working conditions, and the inability to perform fine control for each stage, which leads to insufficient risk prevention and control effects and poor production efficiency and product quality. The application realizes the prediction and prevention of risks, and achieves the technical effect of improving production efficiency, product quality and reducing the operation risks of the calciner.

[0005] The present application provides a system for reducing the risk of a calcining furnace by coordinating a parameter control group, the system comprising: a calcining demand receiving module, the calcining demand receiving module is used to receive the gypsum calcining task demand of the calcining furnace; a control parsing module, the control parsing module is used to perform control feature parsing on the calcining furnace based on the calcining furnace control decision model and the gypsum calcining task demand, and generate a calcining furnace control scheme; a preheating stage coordination module, the preheating stage coordination module is used to perform preheating stage control optimization on the calcining furnace control scheme based on the preheating risk bilateral constraint, and obtain a first-stage coordinated parameter control group; a calcining stage coordination module, the calcining stage coordination module is used to perform calcining stage control optimization on the calcining furnace control scheme based on the calcining stage risk optimization rule, and obtain a second-stage coordinated parameter control group; a cooling stage coordination module, the cooling stage coordination module is used to perform cooling stage control optimization on the calcining furnace control scheme based on the cooling risk bilateral constraint, and obtain a third-stage coordinated parameter control group; a calcining module, the calcining module is used to perform calcination based on the calcining furnace, in combination with the first-stage coordinated parameter control group, the second-stage coordinated parameter control group, and the third-stage coordinated parameter control group.

[0006] The calcination stage coordination module further performs the following processing: performing calcination stage identification according to the calcination furnace control scheme to obtain the calcination stage control decision of the calcination furnace; the calcination stage risk optimization rule includes the calcination stage multi-feature risk constraints and the calcination stage risk weight conditions, wherein the calcination stage multi-feature risk constraints include the calcination stage quality risk constraints, the calcination stage safety risk constraints and the calcination stage equipment loss risk constraints, and the calcination stage risk weight conditions include the calcination stage quality risk weight, the calcination stage safety risk weight and the calcination stage equipment loss risk weight; according to the calcination stage risk prediction The three channels are used to perform risk prediction on the control decision of the calcination stage to obtain the risk prediction result of the calcination stage; it is determined whether the risk prediction result of the calcination stage satisfies the multi-feature risk constraint of the calcination stage; if the risk prediction result of the calcination stage does not satisfy the multi-feature risk constraint of the calcination stage, the control decision of the calcination stage is optimized according to the multi-feature risk constraint of the calcination stage to generate a second-stage coordinated parameter control space that meets the predetermined capacity; the second-stage coordinated parameter control space is optimized to minimize the calcination risk coupling according to the risk weight condition of the calcination stage to generate the second-stage coordinated parameter control group.

[0007] The calcination stage coordination module also performs the following processing: the three channels for calcination stage risk prediction include a calcination stage quality risk prediction channel, a calcination stage safety risk prediction channel and a calcination stage equipment loss risk prediction channel; the characteristics of the gypsum to be calcined are identified according to the gypsum calcination task requirements to obtain characteristic information of the gypsum to be calcined; based on the characteristic information of the gypsum to be calcined and the calcination stage control decision, according to the calcination stage quality risk prediction channel, a calcination stage quality risk prediction coefficient is obtained; based on the characteristic information of the gypsum to be calcined and the calcination stage control decision, according to the calcination stage safety risk prediction channel, a calcination stage safety risk prediction coefficient is obtained; based on the characteristic information of the gypsum to be calcined and the calcination stage control decision, according to the calcination stage equipment loss risk prediction channel, a calcination stage equipment loss risk prediction coefficient is obtained; the calcination stage quality risk prediction coefficient, the calcination stage safety risk prediction coefficient and the calcination stage equipment loss risk prediction coefficient are added to the calcination stage risk prediction result.

[0008] The calcination stage coordination module also performs the following processing: taking the gypsum calcination task requirement as the calcination stage retrieval constraint and taking the calcination stage control parameter of the calcining furnace as the calcination stage retrieval target; performing retrieval according to the calcination stage retrieval constraint and the calcination stage retrieval target to obtain a calcination stage control parameter record library; performing control interval identification according to the calcination stage control parameter record library to establish a calcination stage adjustment space; adjusting the calcination stage control decision according to the calcination stage adjustment space to obtain a first adjusted calcination control decision; performing risk prediction on the first adjusted calcination control decision according to the calcination stage risk prediction three channels to obtain a first updated calcination stage risk prediction result; judging whether the first updated calcination stage risk prediction result meets the calcination stage multi-feature risk constraint; if the first updated calcination stage risk prediction result meets the calcination stage multi-feature risk constraint, adding the first adjusted calcination control decision to the second stage coordinated parameter control space; continuing to optimize the calcination stage control decision according to the calcination stage adjustment space and the calcination stage multi-feature risk constraint until the decision capacity of the second stage coordinated parameter control space meets the predetermined capacity.

[0009] The calcination stage coordination module also performs the following processing: according to the second stage coordination parameter control space, extract the mth calcination control decision, where m is a positive integer; based on the calcination risk prediction result corresponding to the mth calcination control decision, normalize and sort it to obtain the calcination risk prediction result of the mth decision; according to the calcination stage risk weight condition, weighted calculation is performed on the calcination risk prediction result of the mth decision to obtain the mth calcination risk coupling coefficient; according to the second stage coordination parameter control space, extract the m+1th calcination control decision, and calculate the m+1th calcination risk coupling coefficient in combination with the calcination stage risk weight condition; based on the mth calcination risk coupling coefficient, the m+1th calcination risk coupling coefficient, the mth calcination control decision and the m+1th calcination control decision, perform current optimization to obtain the current winning calcination risk coupling coefficient and the current winning calcination control decision; based on the current winning calcination risk coupling coefficient, combined with the calcination stage risk weight condition, continue to perform calcination risk coupling minimization optimization on the second stage coordination parameter control space to obtain the second stage coordination parameter control group.

[0010] The preheating stage coordination module also performs the following processing: the preheating risk bilateral constraint includes the calcining furnace preheating risk constraint and the gypsum preheating risk constraint; the preheating stage is identified according to the calcining furnace control scheme to obtain the preheating stage control decision of the calcining furnace; risk prediction is performed based on the preheating stage control decision to obtain the preheating stage risk prediction result, wherein the preheating stage risk prediction result includes the calcining furnace preheating risk prediction coefficient and the gypsum preheating risk prediction coefficient; it is judged whether the preheating stage risk prediction result meets the preheating risk bilateral constraint; if the preheating stage risk prediction result does not meet the preheating risk bilateral constraint, the preheating control parameter of the calcining furnace is back-traced according to the gypsum calcination task requirement to obtain the preheating stage control parameter record library; the preheating stage control parameter record library is sorted to establish the preheating stage adjustment space; the preheating stage control decision is optimally adjusted according to the preheating stage adjustment space to obtain the first stage coordination parameter control group that meets the preheating risk bilateral constraint.

[0011] The cooling stage coordination module also performs the following processing: the cooling risk bilateral constraint includes the calciner cooling risk constraint and the gypsum cooling risk constraint; the cooling stage is identified according to the calciner control scheme to obtain the cooling stage control decision of the calciner; risk prediction is performed based on the cooling stage control decision to obtain a cooling stage risk prediction result, wherein the cooling stage risk prediction result includes the calciner cooling risk prediction coefficient and the gypsum cooling risk prediction coefficient; it is determined whether the cooling stage risk prediction result meets the cooling risk bilateral constraint; if the cooling stage risk prediction result does not meet the cooling risk bilateral constraint, the cooling control parameter of the calciner is backtracked according to the gypsum calcination task requirements to obtain a cooling stage control parameter record library; the cooling stage control parameter record library is sorted to establish a cooling stage adjustment space; the cooling stage control decision is optimally adjusted according to the cooling stage adjustment space to obtain the third stage coordinated control group that meets the cooling risk bilateral constraint.

[0012] The present application also provides a method for reducing the risk of a calciner by a coordinated control group, the method comprising: receiving a gypsum calcination task requirement of a calciner; performing control feature analysis on the calciner based on a calciner control decision model and the gypsum calcination task requirement to generate a calciner control plan; performing preheating stage control optimization on the calciner control plan based on a preheating risk bilateral constraint to obtain a first-stage coordinated control group; performing calcination stage control optimization on the calciner control plan based on a calcination stage risk optimization rule to obtain a second-stage coordinated control group; performing cooling stage control optimization on the calciner control plan based on a cooling risk bilateral constraint to obtain a third-stage coordinated control group; and performing calcination based on the calciner in combination with the first-stage coordinated control group, the second-stage coordinated control group and the third-stage coordinated control group.

[0013] The system and method for reducing the risk of the calcining furnace through the coordinated control group proposed in this application is to receive the gypsum calcining task requirements of the calcining furnace; generate a calcining furnace control plan; optimize the control of the preheating stage to obtain the first-stage coordinated control group; optimize the control of the calcining stage to obtain the second-stage coordinated control group; optimize the control of the cooling stage to obtain the third-stage coordinated control group; combine the first-stage coordinated control group, the second-stage coordinated control group and the third-stage coordinated control group for calcination. It solves the technical problems of the existing calcining furnace control, such as the preset fixed parameters, the difficulty in accurately responding to complex and changeable working conditions, and the inability to perform fine control for each stage, which leads to insufficient risk prevention and control effects and poor production efficiency and product quality. It realizes the prediction and prevention of risks, and achieves the technical effect of improving production efficiency, product quality and reducing the operation risk of the calcining furnace. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present disclosure, the accompanying drawings of the embodiment of the present disclosure will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic diagram of the system structure for reducing the risk of a calcining furnace by coordinating the control group provided in an embodiment of the present application;

[0016] Figure 2 A schematic flow chart of a method for reducing the risk of a calcining furnace by coordinating a control group provided in an embodiment of the present application.

[0017] Description of the reference numerals: calcination demand receiving module 10 , control analysis module 20 , preheating stage coordination module 30 , calcination stage coordination module 40 , cooling stage coordination module 50 , calcination module 60 . DETAILED DESCRIPTION

[0018] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0019] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0020] In the following description, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application.

[0021] Example 1, the present application embodiment provides a system for coordinating the control group to reduce the risk of the calciner, such as Figure 1 As shown, the system comprises:

[0022] Calcination demand receiving module 10, the calcination demand receiving module 10 is used to receive the gypsum calcination task requirements of the calcining furnace. Gypsum calcination task requirements refer to tasks and requirements related to the gypsum calcination process, which are intended to convert gypsum raw materials into cooked gypsum products with specific properties through a calcining furnace. The gypsum calcination task is to subject the gypsum raw materials to high-temperature treatment in a calcining furnace to chemically react and remove part of the crystal water, thereby converting it into cooked gypsum (usually hemihydrate gypsum). The gypsum calcination task requirements at least include raw material requirements, product quality requirements, calcination process control parameters, energy consumption requirements, etc. Specifically, the initial moisture content of the gypsum entering the calcining furnace is clearly defined, which directly affects the calcination temperature and time; the particle size or particle size distribution of the gypsum affects the heat conduction efficiency and calcination uniformity; the gypsum purity in the raw materials, especially the calcium sulfate content, determines the quality of the final product. ; Clarify the target percentage of type II anhydrous gypsum in the final product, the requirements for the final type II anhydrous gypsum particle size to ensure the applicability of the product in subsequent applications, and specify the density of the calcined product to ensure its mechanical strength and stability; the temperature setting of the calcining furnace at each stage, including preheating temperature, calcining temperature and cooling temperature; the time setting for each stage, including preheating time, calcining time and cooling time, to ensure that gypsum stays in each stage for enough time to achieve the expected effect; the heating rate from room temperature to the target calcining temperature affects the thermal stress of the material and the product quality; the requirements for uniformity of temperature distribution in the calcining furnace to avoid local overheating or underheating; during the calcination process, the upper limit of energy consumption is set to control costs and improve efficiency.

[0023] The control analysis module 20 is used to analyze the control characteristics of the calciner based on the calciner control decision model and the gypsum calcining task requirements, and generate a calciner control plan. The calciner control decision model is a comprehensive control model that integrates multiple parameters such as temperature, atmosphere, material flow, equipment status, etc. It is used to simulate and optimize various control parameters in the calcination process, including temperature control, gas flow regulation, combustion efficiency optimization, etc. Specifically, by inputting different calcination parameters, the reaction process of phosphogypsum in the calciner is simulated, including heat conduction, dehydration reaction, gas release, etc. According to the calcination task requirements, the settings of various control parameters are optimized, such as temperature curve, heating rate, time allocation, etc., to achieve the best calcination effect. In the actual calcination process, according to the real-time monitoring data, the calcination parameters are adjusted to deal with possible abnormal situations to ensure the stability of the process and product quality. Control feature analysis refers to the in-depth analysis of the key parameters and variables in the calciner control process to determine which factors have the greatest impact on the calcination effect and which characteristics require special attention and control. Specifically, identify the key control parameters in the calcination process, such as temperature, time, airflow, combustion efficiency, etc., analyze the sensitivity of these control parameters to the quality of the final product, determine which parameters require more precise control, and adjust and optimize the calcination parameters based on the sensitivity analysis results to improve control accuracy and product quality. Then generate a calciner control plan to guide how to set and adjust the calcination parameters to achieve the expected calcination goals, including temperature control, time management, gas flow pressure control, energy efficiency optimization, etc. Specifically, it includes temperature setting and adjustment methods for preheating, calcination and cooling stages to ensure that the temperature changes in each stage meet the requirements, define the time allocation for each stage, ensure that gypsum stays in each stage for enough time to react and stabilize, set appropriate flow and pressure control strategies for the supply and discharge of gases during the calcination process to ensure the stability and safety of the furnace atmosphere, optimize fuel consumption and heat utilization while meeting task requirements, and reduce production costs.

[0024] The preheating stage coordination module 30 is used to optimize the preheating stage control of the calcining furnace control scheme based on the preheating risk bilateral constraints to obtain the first stage coordinated control group. The preheating risk bilateral constraints refer to the upper and lower limit constraints set in the preheating stage in order to control the risks in the calcining process, including avoiding the risk of thermal stress caused by too rapid temperature rise, and also including preventing the risk of insufficient preheating caused by insufficient temperature or uneven temperature rise. Specifically, the thermal stress constraint refers to the upper limit constraint of the heating rate to prevent the gypsum from cracking or being damaged due to thermal stress caused by the sudden temperature rise. The temperature uniformity constraint refers to the uniformity requirement of the temperature distribution in the furnace to avoid local overheating or underheating and ensure uniform preheating of the entire phosphogypsum batch. The preheating stage control optimization refers to the detailed adjustment and optimization of the control parameters of the calcining furnace under the consideration of the above-mentioned bilateral constraints, which may include Based on the constraints of thermal stress and temperature uniformity, the heating curve of the preheating temperature is adjusted to effectively preheat the gypsum without causing excessive thermal stress. The time of the preheating stage is reasonably allocated to ensure that the gypsum is fully heat-conducted and uniformly preheated in the entire preheating interval, and then the first-stage coordinated parameter control group is obtained, that is, the key parameters of the preheating stage (such as temperature, airflow, heating rate, etc.) are monitored in real time, and dynamically adjusted according to the monitoring data. According to the bilateral constraints of preheating risks, the various subsystems in the calcining furnace, such as the heating system, ventilation system, exhaust system, etc., are coordinated and controlled to achieve overall optimization, and finally the combination of various parameters in the coordination and control preheating stage is obtained.

[0025] The calcination stage coordination module 40 is used to optimize the calcination stage control of the calciner control scheme based on the calcination stage risk optimization rules to obtain the second stage coordination parameter control group. Consider various possible risks in the calcination stage, and adjust the control strategy of the calciner in depth by setting and following the optimization rules to generate a coordination parameter control group responsible for managing the calcination stage, that is, the second stage coordination parameter control group. Specifically, the risk optimization rules of the calcination stage refer to the optimization control rules established during the calcination process to reduce or avoid various potential risks (such as overburning, underburning, equipment wear, gas accumulation, etc.). For example, the overburning risk controls the calcination temperature and time to avoid excessive temperature causing the decomposition of phosphogypsum, the generation of harmful by-products or the deterioration of product quality; the underburning risk ensures that the calcination temperature and time are sufficient to prevent incomplete dehydration of phosphogypsum and affect the generation of type II anhydrous gypsum; the atmosphere control risk maintains a proper atmosphere in the furnace to prevent safety hazards caused by gas accumulation and ensure the smooth progress of the combustion and calcination process. Calcination stage control optimization refers to optimizing and adjusting the various operating parameters of the calcining furnace during the calcination stage under the premise of considering the above-mentioned risk optimization rules to achieve the best calcination effect, such as accurately setting the calcination temperature range to ensure temperature stability and uniformity; reasonably allocating the time of the calcination stage; selecting appropriate fuel and adjusting atmosphere control parameters to ensure sufficient oxygen supply and complete combustion during the calcination process; and then obtaining the second-stage coordination control group, including the temperature, time, atmosphere composition, pressure and other key parameter combinations in the calcination stage in the calcination furnace to ensure that the calcination process is carried out within the predetermined control range. When abnormalities occur in the calcination stage (such as temperature fluctuations, incomplete combustion, etc.), the coordination control group can respond in time, adjust relevant parameters, and maintain the stability of the calcination process.

[0026] The cooling stage coordination module 50 is used to optimize the cooling stage control of the calcining furnace control scheme based on the cooling risk bilateral constraints to obtain the third stage coordinated parameter control group. Various possible risks are considered in the cooling stage, and corresponding constraints are set. By optimizing the control strategy, the safety and stability of the cooling process are ensured, thereby generating the cooling stage coordinated parameter control group, that is, the third stage coordinated parameter control group. Specifically, the cooling stage risk bilateral constraints refer to the upper and lower limit constraints that need to be set during the cooling process to prevent risks that may be caused by excessively fast or uneven temperature drops, including thermal stress caused by excessively fast cooling rates, product defects caused by uneven cooling, and improper airflow or humidity control. Optimizing the cooling stage control of the calcining furnace control scheme refers to optimizing the cooling stage control of the calcining furnace in the cooling stage while considering the cooling stage risk bilateral constraints. The various operating parameters are adjusted and optimized to achieve the best cooling effect. For example, according to the thermal stress constraint, a reasonable cooling rate is set to ensure a smooth temperature drop; by adjusting the speed and direction of the cooling airflow, the temperature of each area in the furnace is evenly distributed; according to the humidity control constraint, the humidity of the cooling airflow is adjusted; and then the third-stage coordinated control group is obtained, including various key parameter combinations in the cooling stage of the calcining furnace, such as temperature, airflow speed, humidity, etc., to ensure that the cooling process is carried out within the predetermined control range. When abnormal conditions occur in the cooling stage (such as temperature fluctuations exceeding the limit, humidity abnormalities, etc.), the coordinated control group can respond quickly and adjust the relevant parameters to maintain the stability of the cooling process.

[0027] The calcination module 60 is used for calcining based on the calcination furnace in combination with the first stage coordination parameter control group, the second stage coordination parameter control group and the third stage coordination parameter control group. In the gypsum calcination process, the whole calcination process is divided into three main stages of preheating, calcination and cooling through the staged control strategy and coordination mechanism, and each stage is precisely controlled and optimized by a special coordination parameter control group to ensure the efficiency, stability and safety of the whole process. Specifically, the calcination process is carried out in three stages of preheating, calcination and cooling. The coordination parameter control group of each stage is responsible for the corresponding tasks to ensure that each stage is operated under the optimal conditions. During the whole calcination process, the coordination parameter control group of each stage monitors the key parameters in real time through sensors and control systems, and dynamically adjusts according to real-time data to ensure the stability of the process. Through refined control and stage optimization, it is ensured that the produced type II anhydrous gypsum meets the quality standards and has good physical and chemical properties. Through the staged management of the coordination parameter control group, it is ensured that the energy consumption in the calcination process is the lowest and the production efficiency is the highest, while minimizing safety hazards.

[0028] The system for reducing the risk of a calcining furnace by a coordinated control group according to an embodiment of the present invention is used to solve the technical problems that the existing calcining furnace control has preset fixed parameters, is difficult to accurately respond to complex and changeable working conditions, and cannot perform fine control for each stage, which leads to insufficient risk prevention and control effects and poor production efficiency and product quality. It realizes the prediction and prevention of risks, and achieves the technical effect of improving production efficiency, product quality and reducing the operation risk of the calcining furnace. The system for reducing the risk of a calcining furnace by a coordinated control group includes: a calcining demand receiving module 10, a control analysis module 20, a preheating stage coordination module 30, a calcining stage coordination module 40, a cooling stage coordination module 50, and a calcining module 60.

[0029] The specific configuration of the calcination stage coordination module 40 will be described in detail below. The calcination stage coordination module 40 may further include: identifying the calcination stage according to the calcination furnace control scheme, and obtaining the calcination stage control decision of the calcination furnace. By analyzing the control scheme of the calcination furnace, the key stages of the calcination process (such as preheating, calcination, cooling, etc.) are clarified, and the control strategy required for each stage is identified. Based on the identified calcination stage, the corresponding control decision is made, including specific temperature settings, time arrangements, airflow control and other parameters.

[0030] The calcination stage risk optimization rule includes the calcination stage multi-feature risk constraints and the calcination stage risk weight conditions, wherein the calcination stage multi-feature risk constraints include the calcination stage quality risk constraints, the calcination stage safety risk constraints and the calcination stage equipment loss risk constraints, and the calcination stage risk weight conditions include the calcination stage quality risk weight, the calcination stage safety risk weight and the calcination stage equipment loss risk weight. The quality risk constraints ensure that each step in the calcination process meets the product quality requirements, such as the purity and density of type II anhydrous gypsum. The safety risk constraints ensure the operational safety during the calcination process, including controlling gas emissions and preventing explosion risks. The equipment loss risk constraints prevent excessive wear or damage to the equipment, such as controlling the calcination temperature and reducing equipment corrosion. The calcination stage quality risk weight refers to setting the priority of quality in the entire risk control according to production requirements; the calcination stage safety risk weight is set according to the importance of operational safety, and the calcination stage equipment loss risk weight is set according to the equipment maintenance cost and life.

[0031] According to the three channels of risk prediction in the calcination stage, the control decision of the calcination stage is risk predicted to obtain the risk prediction result of the calcination stage. The three channels of risk prediction in the calcination stage refer to predicting and evaluating the potential risks in the calcination process through three models, including the quality risk prediction channel, the safety risk prediction channel and the equipment loss risk prediction channel. Specifically, based on the historical production data, a quality risk prediction model is established to predict the possible quality deviation under the current conditions, to ensure that the calcination process can continuously produce type II anhydrous gypsum that meets the quality standards, and to avoid product quality problems caused by parameter deviation or abnormality; using the physical model of the calciner, the operating state under different gas compositions and pressure conditions is simulated, safety risks are predicted, and the operation safety during the calcination process is ensured to avoid safety accidents caused by gas accumulation, excessive temperature or other factors, such as fire, explosion, etc.; by analyzing the performance data of the calciner material at high temperature, possible wear and corrosion are predicted, the service life of the equipment is extended, and downtime and maintenance costs are reduced; together, the risk prediction result of the calcination stage is formed.

[0032] Determine whether the risk prediction result of the calcination stage satisfies the multi-feature risk constraint of the calcination stage; if the risk prediction result of the calcination stage does not satisfy the multi-feature risk constraint of the calcination stage, optimize and adjust the control decision of the calcination stage according to the multi-feature risk constraint of the calcination stage, and generate a second-stage coordinated parameter control space that meets the predetermined capacity. Compare the risk prediction result with the multi-feature risk constraint of the calcination stage to determine whether there is a possibility that the risk of quality, safety or equipment exceeds the control range. If the prediction result shows that there may be a risk that exceeds the constraint condition, optimize and adjust the control decision of the calcination stage. Specifically, according to the multi-feature risk constraint of the calcination stage, optimize and adjust the current control decision, for example, by adjusting parameters such as temperature, time, and airflow, find an optimal solution that satisfies the risk constraint condition and maintains production efficiency. After completing the optimization adjustment, generate the second-stage coordinated parameter control space, covering all possible combinations of operating parameters that may meet the predetermined capacity (such as output, quality, etc.).

[0033] According to the risk weight conditions of the calcination stage, the calcination risk coupling minimization optimization is performed on the second stage coordinated parameter control space to generate the second stage coordinated parameter control group. According to the risk weight conditions of the calcination stage, the parameter combination in the second stage coordinated parameter control space is further optimized, that is, the mutual influence between various risks (such as the trade-off between quality and safety, quality and equipment loss) is minimized, and finally the second stage coordinated parameter control group is generated, which is responsible for implementing the adjusted control decisions to ensure that all risks in the calcination process are effectively controlled, while maximizing production efficiency and product quality.

[0034] The specific configuration of the calcination stage coordination module 40 will be described in detail below. The calcination stage coordination module 40 may further include: the three risk prediction channels of the calcination stage include a quality risk prediction channel of the calcination stage, a safety risk prediction channel of the calcination stage, and an equipment loss risk prediction channel of the calcination stage; the characteristics of the gypsum to be calcined are identified according to the gypsum calcination task requirements to obtain characteristic information of the gypsum to be calcined. The phosphogypsum to be calcined is subjected to detailed feature identification, which may include the physical properties of the gypsum (such as particle size, moisture content), chemical composition (such as the purity of calcium sulfate), and possible impurities, etc., to obtain the characteristic information of the gypsum to be calcined, so as to more accurately predict the quality, safety and equipment loss risks that may occur during the calcination process.

[0035] Based on the characteristic information of the gypsum to be calcined and the control decision of the calcination stage, according to the quality risk prediction channel of the calcination stage, the quality risk prediction coefficient of the calcination stage is obtained; based on the characteristic information of the gypsum to be calcined and the control decision of the calcination stage, according to the safety risk prediction channel of the calcination stage, the safety risk prediction coefficient of the calcination stage is obtained; based on the characteristic information of the gypsum to be calcined and the control decision of the calcination stage, according to the equipment loss risk prediction channel of the calcination stage, the equipment loss risk prediction coefficient of the calcination stage is obtained. The control decision in the calcination stage is an operation plan formulated based on the gypsum characteristic information and the operating parameters of the calciner (such as temperature, time, atmosphere, etc.), including how to adjust the calcination parameters to achieve the best effect, which provides a basis for risk prediction. By analyzing how these decisions affect the calcination process, possible risks can be predicted. Specifically, the quality risk prediction channel predicts quality risks based on the characteristics of gypsum (such as purity, moisture content, etc.). For example, a higher moisture content may require a longer calcination time. At the same time, it analyzes the impact of the operating parameters of the calciner on the quality of the final product, generates a quality risk prediction coefficient, and reflects the quality risk level under current conditions; the safety risk prediction channel predicts safety risks based on the composition of gypsum, evaluates the risks of the operating parameters of the calciner (such as furnace pressure, gas flow, temperature, etc.) in actual operation, and generates a safety risk prediction coefficient, which represents the safety risk level under current conditions; the equipment loss risk prediction channel predicts equipment loss risks based on the chemical composition of gypsum (such as acidic impurities), and analyzes the impact of high temperature, long-term calcination and other operations on the equipment, and generates an equipment loss risk prediction coefficient, which is used to evaluate the equipment loss risk under current conditions.

[0036] The calcination stage quality risk prediction coefficient, the calcination stage safety risk prediction coefficient and the calcination stage equipment loss risk prediction coefficient are added to the calcination stage risk prediction result. The risk prediction coefficients obtained from various risk prediction channels (quality, safety, equipment loss) are integrated into the calcination stage risk prediction result to comprehensively evaluate the overall risks that may be faced in the current calcination stage, help optimize the calcination process, minimize risks and improve production efficiency.

[0037] The specific configuration of the calcination stage coordination module 40 will be described in detail below. The calcination stage coordination module 40 may further include: using the gypsum calcination task requirement as the calcination stage search constraint, and using the calcination stage control parameter of the calcination furnace as the calcination stage search target; searching according to the calcination stage search constraint and the calcination stage search target to obtain the calcination stage control parameter record library. Using specific production targets (such as gypsum quality, output, purity requirements, etc.) as the constraints of the calcination stage, the acceptable parameter range in the calcination process is limited, such as temperature, time, atmosphere control, etc. The specific operating parameters of the calcination stage (such as temperature curve, time schedule, gas flow rate, etc.) are set as the search target to match the calcination task requirements and find the best operation settings. According to the set constraints and targets, the existing historical data and operation records are searched to obtain the control parameters that best match the current calcination task requirements, and the retrieved control parameter records are sorted to obtain the calcination stage control parameter record library, which contains all the key parameters and their results used in previous operations.

[0038] According to the control parameter record library of the calcination stage, the control interval is identified and the calcination stage adjustment space is established. By analyzing the control parameter record library, the optimal control interval of each parameter is identified, which reflects the optimal operating range of each parameter under the premise of meeting the task requirements. Based on the identified control interval, an adjustment space containing all possible operation combinations is established, that is, the calcination stage adjustment space is established.

[0039] The calcination stage control decision is adjusted according to the calcination stage adjustment space to obtain a first adjusted calcination control decision. The control decision is adjusted in the adjustment space to better match the current calcination task requirements, including temperature adjustment, time adjustment or airflow adjustment operations, thereby obtaining the first adjusted calcination control decision.

[0040] The first adjustment calcination control decision is risk predicted according to the three channels of risk prediction for the calcination stage to obtain the first updated calcination stage risk prediction result. The first adjustment calcination control decision is evaluated using the three channels of risk prediction for the calcination stage (quality, safety, equipment loss) to predict the risks that may arise when executing this decision. Through risk prediction, an updated risk assessment result is obtained, i.e., the first updated calcination stage risk prediction result, which shows the risk level that may be faced under the new control decision.

[0041] Determine whether the first updated calcination stage risk prediction result satisfies the multi-feature risk constraint of the calcination stage; if the first updated calcination stage risk prediction result satisfies the multi-feature risk constraint of the calcination stage, add the first adjusted calcination control decision to the second stage coordinated parameter control space. Compare the first updated calcination stage risk prediction result with the multi-feature risk constraint (such as the upper limit of the risk of quality, safety, and equipment loss) to determine whether the current decision is within an acceptable risk range. If the risk prediction result satisfies the risk constraint, add the first adjusted calcination control decision to the second stage coordinated parameter control space as one of the possible best decisions.

[0042] The control decision of the calcination stage is continuously optimized and adjusted according to the calcination stage adjustment space and the multi-feature risk constraints of the calcination stage until the decision capacity of the second-stage coordinated parameter control space meets the predetermined capacity. A better control decision is continuously sought in the calcination stage adjustment space to further optimize the control strategy and continuously adjust and optimize until enough control decisions that meet the requirements are found in the second-stage coordinated parameter control space (i.e., meet the predetermined capacity requirements) to ensure that there are multiple selectable optimal operation plans in actual production.

[0043] The specific configuration of the calcination stage coordination module 40 will be described in detail below. The calcination stage coordination module 40 may further include: extracting the mth calcination control decision according to the second stage coordination parameter control space, wherein m is a positive integer; normalizing and sorting the calcination risk prediction result corresponding to the mth calcination control decision to obtain the calcination risk prediction result of the mth decision; weighting the calcination risk prediction result of the mth decision according to the calcination stage risk weight condition to obtain the mth calcination risk coupling coefficient; extracting the m+1th calcination control decision according to the second stage coordination parameter control space, and calculating the m+1th calcination risk coupling coefficient in combination with the calcination stage risk weight condition; performing current optimization based on the mth calcination risk coupling coefficient, the m+1th calcination risk coupling coefficient, the mth calcination control decision and the m+1th calcination control decision to obtain the current winning calcination risk coupling coefficient and the current winning calcination control decision; based on the current winning calcination risk coupling coefficient, combined with the calcination stage risk weight condition, continue to perform calcination risk coupling minimization optimization on the second stage coordination parameter control space to obtain the second stage coordination parameter control group.

[0044] Preferably, the mth calcination control decision is extracted from the second-stage coordinated parameter control space, where m is a positive integer, indicating that this is the mth selected control scheme in the coordinated parameter control space. Based on the calcination risk prediction results corresponding to the mth calcination control decision, these risk prediction results include quality risk, safety risk and equipment loss risk, and are normalized to convert the risk prediction results to a unified scale, so as to more intuitively compare the risk levels of different decisions, so as to facilitate subsequent comparison and weighted calculation. According to the risk weight conditions of the calcination stage, the normalized mth calcination risk prediction results are weighted. Usually, based on the actual production priority (such as quality priority, safety priority, etc.), different types of risks are weighted according to their importance. Through weighted calculation, the mth calcination risk coupling coefficient is obtained, which reflects the size of the comprehensive risk under the current conditions. Then, the next one (i.e. The m+1th) calcination control decision is made, the m+1th calcination risk prediction result is normalized, the m+1th calcination risk coupling coefficient is weightedly calculated, and the m+1th calcination risk coupling coefficient is obtained. By comparing the m and m+1th control decisions, it is determined which decision has a lower comprehensive risk under the current conditions. Specifically, the mth calcination risk coupling coefficient and the m+1th calcination risk coupling coefficient are compared, and by analyzing the risk coefficients of the two decisions and their corresponding control parameters, it is determined which decision has more advantages in comprehensive risks, and then the current optimal calcination control decision is determined, and its corresponding risk coupling coefficient is regarded as the current winning calcination risk coupling coefficient; finally, based on the current winning calcination risk coupling coefficient and combined with the risk weight conditions of the calcination stage, further optimization is continued in the second-stage coordinated control space, that is, through step-by-step iteration and comparison, the control decision with the lowest comprehensive risk is found, that is, the second-stage coordinated control group is obtained.

[0045] Below, the specific configuration of the preheating stage coordination module 30 will be described in detail. The preheating stage coordination module 30 may further include: the preheating risk bilateral constraints include calcining furnace preheating risk constraints and gypsum preheating risk constraints. The preheating risk bilateral constraints refer to the upper and lower limit constraints that need to be met in the preheating stage, including calcining furnace preheating risk constraints and gypsum preheating risk constraints. The calcining furnace preheating risk constraints refer to the risks faced by the calcining furnace during the preheating process, such as furnace overheating, uneven airflow, equipment wear, etc.; the gypsum preheating risk constraints refer to the risks that gypsum may face during the preheating process, such as cracks caused by thermal stress, agglomeration caused by uneven water evaporation, etc.; by setting bilateral constraints, ensure that the operating parameters of the preheating stage are within the range allowed by safety and quality.

[0046] According to the control scheme of the calcining furnace, the preheating stage is identified to obtain the control decision of the preheating stage of the calcining furnace; based on the control decision of the preheating stage, risk prediction is performed to obtain the risk prediction result of the preheating stage, wherein the risk prediction result of the preheating stage includes the risk prediction coefficient of the calcining furnace preheating and the risk prediction coefficient of the gypsum preheating. According to the control scheme of the calcining furnace, the key control parameters and operation steps of the preheating stage are identified, and based on the identification results, the specific control decision of the preheating stage is formulated, that is, the control decision of the preheating stage, which may include parameters such as temperature setting, heating rate, and airflow regulation; based on the control decision of the preheating stage, risk prediction is performed, specifically, a risk prediction model is established using historical data, and the risk prediction model is used to perform risk prediction on the control decision of the preheating stage, and the possible risks are evaluated to obtain the risk prediction result of the preheating stage, wherein the risk prediction result of the preheating stage includes the risk prediction coefficient of the calcining furnace preheating and the risk prediction coefficient of the gypsum preheating, wherein the risk prediction coefficient of the calcining furnace preheating is a risk coefficient for evaluating the possible risks of the calcining furnace in the preheating stage; the risk prediction coefficient of the gypsum preheating is a risk coefficient for evaluating the possible risks of the gypsum in the preheating stage.

[0047] Determine whether the risk prediction result of the preheating stage meets the bilateral constraint of the preheating risk; if the risk prediction result of the preheating stage does not meet the bilateral constraint of the preheating risk, backtrack the preheating control parameters of the calcining furnace according to the gypsum calcination task requirements to obtain a preheating stage control parameter record library. Compare the risk prediction result with the preset bilateral constraint to determine whether the current control decision meets the safety and quality requirements. If the risk prediction result of the preheating stage does not meet the bilateral constraint of the preheating risk, backtrack the preheating control parameters of the calcining furnace according to the gypsum calcination task requirements, analyze historical data and previous operation records, find possible optimization paths, and organize the control parameters obtained from the backtracking analysis into a record library, namely the preheating stage control parameter record library.

[0048] Organize the control parameter record library of the preheating stage and establish the preheating stage adjustment space; optimize and adjust the control decision of the preheating stage according to the preheating stage adjustment space to obtain the first stage coordinated control group that meets the bilateral constraint of the preheating risk. Based on the control parameter record library of the preheating stage, establish the adjustment space of the preheating stage. This adjustment space contains all possible control parameter combinations that meet the bilateral constraint. In the preheating stage adjustment space, optimize and adjust the control decision to find multiple control parameter combinations that can simultaneously meet the calciner preheating risk constraint and the gypsum preheating risk constraint. Through optimal adjustment, finally generate a control decision set that meets the bilateral constraint of the preheating risk, which constitutes the first stage coordinated control group of the preheating stage, and is used in the actual preheating operation to ensure that the entire calcination process is in the best control state, as well as the safety of the preheating process and the quality of the gypsum.

[0049] The specific configuration of the cooling stage coordination module 50 will be described in detail below. The cooling stage coordination module 50 may further include: the cooling risk bilateral constraint includes a calciner cooling risk constraint and a gypsum cooling risk constraint. The cooling risk bilateral constraint includes two aspects of constraint conditions. The calciner cooling risk constraint involves the risks that the calciner may face during the cooling stage, such as thermal stress and equipment wear caused by the rapid temperature drop of the furnace body; the gypsum cooling risk constraint involves the risks that gypsum may face during the cooling stage, such as gypsum structure damage and crack generation caused by a sudden drop in temperature; to ensure that the cooling process will neither damage the equipment nor affect the final quality of the gypsum.

[0050] According to the control scheme of the calciner, the cooling stage is identified to obtain the control decision of the cooling stage of the calciner. According to the control scheme of the calciner, the key control parameters and operation steps of the cooling stage are identified, and based on the identification results, specific control decisions of the cooling stage are made, which may include the cooling rate, how to control the rate of temperature drop to ensure that thermal stress caused by sudden cooling does not occur; airflow control, the flow rate, direction and temperature of the airflow during the cooling process to ensure uniform cooling; time arrangement, the duration of the cooling stage, to ensure that the gypsum is fully cooled without cracking.

[0051] Based on the control decision of the cooling stage, risk prediction is performed to obtain the risk prediction result of the cooling stage, wherein the risk prediction result of the cooling stage includes the calciner cooling risk prediction coefficient and the gypsum cooling risk prediction coefficient. The cooling process of the calciner is simulated by computer, and the risk situations that may occur in the cooling stage are predicted according to different control parameter settings in the control decision of the cooling stage, that is, the risk prediction result of the cooling stage is obtained, and the risk prediction result of the cooling stage includes the calciner cooling risk prediction coefficient and the gypsum cooling risk prediction coefficient. The calciner cooling risk prediction coefficient is used to indicate the degree of risk that the calciner may face in the cooling stage, and the influencing factors include the thermal stress of the furnace body, the wear rate of the equipment, the airflow control, etc., and the problems that may occur in the calciner during the cooling stage, such as furnace body cracks, equipment damage, etc., are predicted; the gypsum cooling risk prediction coefficient is used to indicate the degree of risk that the gypsum may face in the cooling stage, and the influencing factors include the cooling rate of the gypsum, the structural integrity, etc., and the problems that may occur in the gypsum during the cooling stage, such as crack generation, structural damage, etc., are predicted.

[0052] Determine whether the risk prediction result of the cooling stage satisfies the bilateral constraint of the cooling risk; if the risk prediction result of the cooling stage does not satisfy the bilateral constraint of the cooling risk, backtrack the cooling control parameters of the calcining furnace according to the gypsum calcining task requirements to obtain a cooling stage control parameter record library. Compare the risk prediction result of the cooling stage with the preset bilateral constraint to determine whether the current control decision meets the safety and quality requirements. If the risk prediction result does not satisfy the bilateral constraint, backtrack the cooling control parameters of the calcining furnace according to the gypsum calcining task requirements, analyze the historical data and operation records, find the optimization path, and organize the control parameters obtained from the backtracking analysis into a record library, that is, obtain the cooling stage control parameter record library.

[0053] Organize the control parameter record library of the cooling stage and establish a cooling stage adjustment space; optimize and adjust the control decision of the cooling stage according to the cooling stage adjustment space to obtain the third stage coordinated parameter control group that meets the cooling risk bilateral constraint. Based on the cooling stage control parameter record library, establish an adjustment space for the cooling stage of a calciner. This cooling stage adjustment space contains all possible control parameter combinations that meet the cooling risk bilateral constraint. Then, in the cooling stage adjustment space, optimize and adjust the control decision to find multiple control parameter combinations that can simultaneously meet the calciner cooling risk constraint and the gypsum cooling risk constraint. Specifically, through optimal adjustment, a control decision set that meets the cooling risk bilateral constraint is finally generated, that is, the third stage coordinated parameter control group is obtained. Cooling operations are performed according to the decisions in this cooling stage coordinated parameter control group to ensure that the entire cooling process is in the best control state, thereby ensuring the safety of the cooling process and the quality of the gypsum.

[0054] In the above, refer to Figure 1 The system for reducing the risk of a calciner by coordinating the control group according to an embodiment of the present invention is described in detail. Figure 2 A method for reducing the risk of a calciner by a coordinated control group according to an embodiment of the present invention is described.

[0055] Example 2, a method for coordinating the control group to reduce the risk of the calciner, such as Figure 2As shown, the method includes: receiving a gypsum calcining task requirement of a calcining furnace; performing control feature analysis on the calcining furnace based on a calcining furnace control decision model and the gypsum calcining task requirement to generate a calcining furnace control plan; performing preheating stage control optimization on the calcining furnace control plan based on a preheating risk bilateral constraint to obtain a first-stage coordinated parameter control group; performing calcining stage control optimization on the calcining furnace control plan based on a calcining stage risk optimization rule to obtain a second-stage coordinated parameter control group; performing cooling stage control optimization on the calcining furnace control plan based on a cooling risk bilateral constraint to obtain a third-stage coordinated parameter control group; and performing calcination based on the calcining furnace in combination with the first-stage coordinated parameter control group, the second-stage coordinated parameter control group and the third-stage coordinated parameter control group.

[0056] The calcination stage coordination module is used to optimize the calcination stage control of the calciner control scheme based on the calcination stage risk optimization rules to obtain the second stage coordination parameter control group, including: identifying the calcination stage according to the calciner control scheme to obtain the calcination stage control decision of the calciner; the calcination stage risk optimization rules include calcination stage multi-feature risk constraints and calcination stage risk weight conditions, wherein the calcination stage multi-feature risk constraints include calcination stage quality risk constraints, calcination stage safety risk constraints and calcination stage equipment loss risk constraints, and the calcination stage risk weight conditions include calcination stage quality risk weights, calcination stage safety risk weights and calcination stage risk weights. The risk weight of equipment loss in the calcination stage is determined; according to the three channels of risk prediction for the calcination stage, risk prediction is performed on the control decision of the calcination stage to obtain the risk prediction result of the calcination stage; it is determined whether the risk prediction result of the calcination stage satisfies the multi-feature risk constraint of the calcination stage; if the risk prediction result of the calcination stage does not satisfy the multi-feature risk constraint of the calcination stage, the control decision of the calcination stage is optimized and adjusted according to the multi-feature risk constraint of the calcination stage to generate a second-stage coordinated parameter control space that meets the predetermined capacity; according to the risk weight condition of the calcination stage, the second-stage coordinated parameter control space is optimized to minimize the calcination risk coupling to generate the second-stage coordinated parameter control group.

[0057] According to the three channels of risk prediction for the calcination stage, risk prediction is performed on the control decision of the calcination stage to obtain a risk prediction result for the calcination stage, including: the three channels of risk prediction for the calcination stage include a quality risk prediction channel for the calcination stage, a safety risk prediction channel for the calcination stage and a risk prediction channel for equipment loss in the calcination stage; according to the requirements of the gypsum calcination task, the characteristics of the gypsum to be calcined are identified to obtain characteristic information of the gypsum to be calcined; based on the characteristic information of the gypsum to be calcined and the calcination stage control decision, according to the calcination stage quality risk prediction channel, a calcination stage quality risk prediction coefficient is obtained; based on the characteristic information of the gypsum to be calcined and the calcination stage control decision, according to the calcination stage safety risk prediction channel, a calcination stage safety risk prediction coefficient is obtained; based on the characteristic information of the gypsum to be calcined and the calcination stage control decision, according to the calcination stage equipment loss risk prediction channel, a calcination stage equipment loss risk prediction coefficient is obtained; the calcination stage quality risk prediction coefficient, the calcination stage safety risk prediction coefficient and the calcination stage equipment loss risk prediction coefficient are added to the calcination stage risk prediction result.

[0058] If the risk prediction result of the calcination stage does not meet the multi-feature risk constraint of the calcination stage, the control decision of the calcination stage is optimized and adjusted according to the multi-feature risk constraint of the calcination stage to generate a second-stage coordinated parameter control space that meets the predetermined capacity, including: taking the gypsum calcination task requirement as the calcination stage retrieval constraint, and taking the calcination stage control parameter of the calcination furnace as the calcination stage retrieval target; searching according to the calcination stage retrieval constraint and the calcination stage retrieval target to obtain a calcination stage control parameter record library; identifying the control interval according to the calcination stage control parameter record library to establish a calcination stage adjustment space; adjusting the calcination stage control decision according to the calcination stage adjustment space to obtain Obtain a first adjusted calcination control decision; perform risk prediction on the first adjusted calcination control decision according to the three-channel risk prediction of the calcination stage to obtain a first updated calcination stage risk prediction result; determine whether the first updated calcination stage risk prediction result satisfies the multi-feature risk constraint of the calcination stage; if the first updated calcination stage risk prediction result satisfies the multi-feature risk constraint of the calcination stage, add the first adjusted calcination control decision to the second stage coordinated parameter control space; continue to optimize and adjust the calcination stage control decision according to the calcination stage adjustment space and the multi-feature risk constraint of the calcination stage until the decision capacity of the second stage coordinated parameter control space meets the predetermined capacity.

[0059] The method comprises: performing calcination risk coupling minimization optimization on the second-stage coordinated parameter control space according to the risk weight condition of the calcination stage to generate the second-stage coordinated parameter control group, including: extracting the mth calcination control decision according to the second-stage coordinated parameter control space, wherein m is a positive integer; performing normalization and sorting on the calcination risk prediction result corresponding to the mth calcination control decision to obtain the calcination risk prediction result of the mth decision; performing weighted calculation on the calcination risk prediction result of the mth decision according to the risk weight condition of the calcination stage to obtain the mth calcination risk coupling coefficient; performing weighted calculation on the mth calcination risk prediction result according to the second-stage coordinated parameter control space, Extract the m+1th calcination control decision, and calculate the m+1th calcination risk coupling coefficient in combination with the risk weight conditions of the calcination stage; perform current optimization based on the mth calcination risk coupling coefficient, the m+1th calcination risk coupling coefficient, the mth calcination control decision and the m+1th calcination control decision to obtain the current winning calcination risk coupling coefficient and the current winning calcination control decision; based on the current winning calcination risk coupling coefficient, combined with the risk weight conditions of the calcination stage, continue to perform calcination risk coupling minimization optimization on the second stage coordinated parameter control space to obtain the second stage coordinated parameter control group.

[0060] The preheating stage coordination module is used to optimize the preheating stage control of the calcining furnace control scheme based on the preheating risk bilateral constraint to obtain the first stage coordinated control group, including: the preheating risk bilateral constraint includes the calcining furnace preheating risk constraint and the gypsum preheating risk constraint; the preheating stage is identified according to the calcining furnace control scheme to obtain the preheating stage control decision of the calcining furnace; risk prediction is performed based on the preheating stage control decision to obtain the preheating stage risk prediction result, wherein the preheating stage risk prediction result includes the calcining furnace preheating risk prediction coefficient and the gypsum preheating risk prediction coefficient; it is judged whether the preheating stage risk prediction result meets the preheating risk bilateral constraint; if the preheating stage risk prediction result does not meet the preheating risk bilateral constraint, the preheating control parameter of the calcining furnace is backtracked according to the gypsum calcining task requirement to obtain the preheating stage control parameter record library; the preheating stage control parameter record library is sorted to establish the preheating stage adjustment space; the preheating stage control decision is optimally adjusted according to the preheating stage adjustment space to obtain the first stage coordinated control group that meets the preheating risk bilateral constraint.

[0061] The cooling stage coordination module is used to optimize the cooling stage control of the calcining furnace control scheme based on the cooling risk bilateral constraint to obtain the third stage coordinated control group, and also includes: the cooling risk bilateral constraint includes the calcining furnace cooling risk constraint and the gypsum cooling risk constraint; the cooling stage is identified according to the calcining furnace control scheme to obtain the cooling stage control decision of the calcining furnace; risk prediction is performed based on the cooling stage control decision to obtain a cooling stage risk prediction result, wherein the cooling stage risk prediction result includes the calcining furnace cooling risk prediction coefficient and the gypsum cooling risk prediction coefficient; it is judged whether the cooling stage risk prediction result meets the cooling risk bilateral constraint; if the cooling stage risk prediction result does not meet the cooling risk bilateral constraint, the cooling control parameter of the calcining furnace is backtracked according to the gypsum calcination task requirement to obtain a cooling stage control parameter record library; the cooling stage control parameter record library is sorted to establish a cooling stage adjustment space; the cooling stage control decision is optimally adjusted according to the cooling stage adjustment space to obtain the third stage coordinated control group that meets the cooling risk bilateral constraint.

[0062] The system for coordinating the control group to reduce the risk of the calciner provided in the embodiment of the present invention can execute the method for coordinating the control group to reduce the risk of the calciner provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0063] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0064] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A system for coordinating the control group to reduce the risk of the calciner, characterized in that: The system comprises: A calcination demand receiving module, wherein the calcination demand receiving module is used to receive the gypsum calcination task demand of the calcining furnace; A control analysis module, the control analysis module is used to analyze the control characteristics of the calciner based on the calciner control decision model and the gypsum calcining task requirements, and generate a calciner control plan; A preheating stage coordination module, wherein the preheating stage coordination module is used to optimize the preheating stage control of the calcining furnace control scheme based on the preheating risk bilateral constraint to obtain a first stage coordinated control group; A calcination stage coordination module, wherein the calcination stage coordination module is used to optimize the calcination stage control of the calcination furnace control scheme based on the calcination stage risk optimization rule to obtain a second stage coordination parameter control group; A cooling phase coordination module, wherein the cooling phase coordination module is used to optimize the cooling phase control of the calcining furnace control scheme based on the cooling risk bilateral constraint to obtain a third phase coordinated control group; A calcination module, the calcination module is used to perform calcination based on the calcination furnace in combination with the first stage coordination parameter control group, the second stage coordination parameter control group and the third stage coordination parameter control group; The calcination stage coordination module includes the following steps: Identifying the calcination stage according to the calcination furnace control scheme to obtain a calcination stage control decision for the calcination furnace; The calcination stage risk optimization rule includes a calcination stage multi-feature risk constraint and a calcination stage risk weight condition, wherein the calcination stage multi-feature risk constraint includes a calcination stage quality risk constraint, a calcination stage safety risk constraint and a calcination stage equipment loss risk constraint, and the calcination stage risk weight condition includes a calcination stage quality risk weight, a calcination stage safety risk weight and a calcination stage equipment loss risk weight; Performing risk prediction on the control decision of the calcination stage according to the three risk prediction channels of the calcination stage to obtain the risk prediction result of the calcination stage, wherein the three risk prediction channels of the calcination stage include a quality risk prediction channel of the calcination stage, a safety risk prediction channel of the calcination stage, and an equipment loss risk prediction channel of the calcination stage; Determining whether the risk prediction result of the calcination stage satisfies the multi-feature risk constraint of the calcination stage; If the risk prediction result of the calcination stage does not meet the multi-feature risk constraint of the calcination stage, the control decision of the calcination stage is optimized and adjusted according to the multi-feature risk constraint of the calcination stage to generate a second-stage coordinated parameter control space that meets the predetermined capacity; According to the risk weight condition of the calcination stage, the calcination risk coupling minimization optimization is performed on the second stage coordinated parameter control space to generate the second stage coordinated parameter control group.

2. The system according to claim 1, characterized in that The calcination stage coordination module includes the following steps: According to the gypsum calcination task requirements, characteristics of the gypsum to be calcined are identified to obtain characteristic information of the gypsum to be calcined; Based on the characteristic information of the gypsum to be calcined and the control decision of the calcination stage, and according to the quality risk prediction channel of the calcination stage, a quality risk prediction coefficient of the calcination stage is obtained; Based on the characteristic information of the gypsum to be calcined and the control decision of the calcination stage, and according to the safety risk prediction channel of the calcination stage, a safety risk prediction coefficient of the calcination stage is obtained; Based on the characteristic information of the gypsum to be calcined and the control decision of the calcination stage, and according to the equipment loss risk prediction channel of the calcination stage, a calcination stage equipment loss risk prediction coefficient is obtained; The calcination stage quality risk prediction coefficient, the calcination stage safety risk prediction coefficient and the calcination stage equipment loss risk prediction coefficient are added to the calcination stage risk prediction result.

3. The system according to claim 1, characterized in that The calcination stage coordination module includes the following steps: The gypsum calcining task requirement is used as a calcining stage retrieval constraint, and the calcining stage control parameter of the calcining furnace is used as a calcining stage retrieval target; Performing a search according to the calcination stage search constraint and the calcination stage search target to obtain a calcination stage control parameter record library; Identify the control interval according to the calcination stage control parameter record library and establish the calcination stage adjustment space; Adjust the calcination stage control decision according to the calcination stage adjustment space to obtain a first adjusted calcination control decision; Perform risk prediction on the first adjustment calcination control decision according to the three channels of risk prediction for the calcination stage to obtain a first updated calcination stage risk prediction result; Determining whether the first updated calcination stage risk prediction result satisfies the calcination stage multi-feature risk constraint; If the first updated calcination stage risk prediction result satisfies the multi-feature risk constraint of the calcination stage, adding the first adjusted calcination control decision to the second stage coordinated parameter control space; The control decision of the calcination stage is continuously optimized and adjusted according to the calcination stage adjustment space and the multi-feature risk constraints of the calcination stage until the decision capacity of the second stage coordinated parameter control space meets the predetermined capacity.

4. The system according to claim 1, characterized in that The calcination stage coordination module includes the following steps: According to the second stage coordinated parameter control space, extracting the mth calcination control decision, where m is a positive integer; Normalizing and sorting the calcination risk prediction result corresponding to the m-th calcination control decision to obtain the m-th decision calcination risk prediction result; Performing weighted calculation on the m-th decision calcination risk prediction result according to the calcination stage risk weight condition to obtain the m-th calcination risk coupling coefficient; According to the second stage coordinated parameter control space, extract the m+1 calcination control decision, and calculate the m+1 calcination risk coupling coefficient in combination with the calcination stage risk weight condition; Performing current optimization based on the mth calcination risk coupling coefficient, the m+1th calcination risk coupling coefficient, the mth calcination control decision, and the m+1th calcination control decision to obtain a current winning calcination risk coupling coefficient and a current winning calcination control decision; Based on the current winning calcination risk coupling coefficient and in combination with the calcination stage risk weight condition, the second stage coordinated parameter control space is continuously optimized for calcination risk coupling minimization to obtain the second stage coordinated parameter control group.

5. The system according to claim 1, wherein: The preheating stage coordination module executes the following steps: The preheating risk bilateral constraint includes a calciner preheating risk constraint and a gypsum preheating risk constraint; Performing preheating stage identification according to the calcining furnace control scheme to obtain a preheating stage control decision for the calcining furnace; Perform risk prediction based on the preheating stage control decision to obtain a preheating stage risk prediction result, wherein the preheating stage risk prediction result includes a calcining furnace preheating risk prediction coefficient and a gypsum preheating risk prediction coefficient; Determining whether the preheating stage risk prediction result satisfies the preheating risk bilateral constraint; If the preheating stage risk prediction result does not meet the preheating risk bilateral constraint, the preheating control parameters of the calcining furnace are backtracked according to the gypsum calcining task requirements to obtain a preheating stage control parameter record library; Arrange the control parameter record library of the preheating stage and establish the adjustment space of the preheating stage; The preheating stage control decision is optimized and adjusted according to the preheating stage adjustment space to obtain the first stage coordinated control group that meets the preheating risk bilateral constraint.

6. The system according to claim 1, wherein: The cooling stage coordination module executes the following steps: The cooling risk bilateral constraint includes a calciner cooling risk constraint and a gypsum cooling risk constraint; Performing cooling stage identification according to the calcining furnace control scheme to obtain a cooling stage control decision for the calcining furnace; Performing risk prediction based on the cooling stage control decision to obtain a cooling stage risk prediction result, wherein the cooling stage risk prediction result includes a calciner cooling risk prediction coefficient and a gypsum cooling risk prediction coefficient; Determining whether the cooling stage risk prediction result satisfies the cooling risk bilateral constraint; If the cooling stage risk prediction result does not meet the cooling risk bilateral constraint, the cooling control parameters of the calcining furnace are backtracked according to the gypsum calcining task requirements to obtain a cooling stage control parameter record library; Arrange the control parameter record library of the cooling stage and establish the adjustment space of the cooling stage; The cooling stage control decision is optimized and adjusted according to the cooling stage adjustment space to obtain the third stage coordinated control group that meets the cooling risk bilateral constraint.

7. A method for coordinating a control group to reduce the risk of a calciner, characterized in that: The method is applied to the system for reducing the risk of a calcining furnace by a coordinated control group as described in any one of claims 1 to 6, and the method comprises: Receive gypsum calcination task requirements from the calciner; Based on the calcining furnace control decision model and the gypsum calcining task requirements, the control characteristics of the calcining furnace are analyzed to generate a calcining furnace control plan; Based on the preheating risk bilateral constraint, the calciner control scheme is optimized for the preheating stage control to obtain the first stage coordinated control group; Based on the calcination stage risk optimization rule, the calcination stage control scheme of the calcination furnace is optimized to obtain the second stage coordinated control group; Based on the cooling risk bilateral constraint, the calciner control scheme is optimized for the cooling stage control to obtain the third stage coordinated control group; Based on the calcining furnace, calcination is performed in combination with the first stage coordinated parameter control group, the second stage coordinated parameter control group and the third stage coordinated parameter control group.

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