Intelligent control method and system for single-tower desulfurization and dust removal device, medium and product

Abstract

The application discloses an intelligent control method and system for a single-tower desulfurization and dust removal device, a medium and a product, and aims to solve the dynamic balance problem of desulfurization and dust removal efficiency. The system collects the inlet flue gas parameters, the desulfurization outlet concentration and the outlet dust concentration in real time, calculates the desulfurization and dust removal efficiency according to the parameters, compares the efficiency with the emission standard threshold, determines the ideal balance, the desulfurization limitation and other operating states, and if the ideal balance is not reached, the priority optimization target is determined. Then, the influence characteristic curve of the desulfurization and dust removal efficiency is constructed. The shared operating parameters (water spraying amount, mortar spraying amount and the like) are determined through the curve, and the priority optimization target is dynamically adjusted to realize the change of the operating state to the ideal balance. Through data collection and analysis, the technical scheme realizes the intelligent collaborative control of the desulfurization and dust removal efficiency by combining the optimization adjustment with the characteristic curve, effectively solves the dynamic balance problem between the desulfurization and dust removal, guarantees the stable and efficient operation of the single-tower desulfurization and dust removal device, and realizes the standard emission of industrial flue gas.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial flue gas desulfurization and dust removal, and particularly relates to an intelligent control method and system for a single-tower desulfurization and dust removal device, a medium and a product. BACKGROUND

[0002] With the continuous advancement of industrialization, the flue gas emissions of industrial enterprises such as coal-fired power plants, steel plants and cement plants have increasingly attracted attention in terms of environmental impact. Sulfur dioxide (SO2) and particulate matter in industrial flue gas are the main sources of air pollution. The former can cause acid rain and atmospheric acidification, and the latter directly affects air quality and human health. Therefore, desulfurization and dust removal treatment of industrial flue gas has become an important research direction in the environmental protection field, and increasingly high requirements have been put forward for the efficiency and operational stability of related devices. In order to achieve emission compliance, the combination of desulfurization devices and dust removal devices is commonly used in related technologies to process SO2 and particulate matter in flue gas in steps. However, how to achieve collaborative processing of desulfurization and dust removal through a single-tower device under limited space and cost conditions has become an important technical challenge in the treatment of industrial flue gas.

[0003] In related technologies, a single-tower desulfurization and dust removal device mainly removes particulate matter through downstream dust removal equipment while performing a desulfurization reaction in the tower. For example, in a semi-dry desulfurization process, SO2 in flue gas reacts with an absorbent slurry (such as lime slurry) to form solid particles by spraying the absorbent slurry, and then the collection of particulate matter is completed through an electrostatic precipitator (ESP) or a fabric filter (FF); while in a wet desulfurization process, the removal of SO2 is achieved by spraying an absorbent in a spray tower, and part of the particulate matter is preliminarily removed through gas-liquid separation or a wet dust removal device. These devices usually adjust operating parameters such as the amount of absorbent sprayed, the intensity of the spray, the strength of the electric field of the electric dust collector, etc. to enhance the processing effect of SO2 and particulate matter.

[0004] However, the above-mentioned single-tower desulfurization and dust removal device in related technologies has some deficiencies. When the flue gas conditions fluctuate greatly, since desulfurization and dust removal are two different physical and chemical processes, the adjustment of operating parameters often presents a nonlinear correlation. In related technologies, since the synergistic effect of operating parameters on desulfurization efficiency and dust removal efficiency is not fully considered, it is difficult to achieve dynamic balance between the two, resulting in a problem of a decline in one efficiency or even emission exceeding the standard. SUMMARY

[0005] In view of the above technical problems and defects, the purpose of the present application is to provide an intelligent control method and system for a single-tower desulfurization and dust removal device, a medium and a product, which can solve the problem of dynamic balance between desulfurization efficiency and dust removal efficiency in a single-tower desulfurization and dust removal device through intelligent collaborative control methods.

[0006] In a first aspect, an intelligent control method of a single-tower desulfurization and dust removal device is provided, including: collecting in real time an inlet flue gas parameter, a desulfurization outlet concentration and an outlet dust concentration, the inlet flue gas parameter including a flue gas flow, an inlet concentration, a dust concentration and a temperature; calculating a current desulfurization efficiency and a dust removal efficiency according to the inlet flue gas parameter, the desulfurization outlet concentration and the outlet dust concentration; comparing the desulfurization efficiency and the dust removal efficiency with an emission standard threshold to obtain a current operating state, the operating state including an ideal balance, desulfurization limitation, dust removal limitation and double limitation; if the operating state is not the ideal balance, determining a priority optimization target, the priority optimization target indicating a main limited function in the operating state; based on test data and operating history data, constructing an influence characteristic curve of the shared operating parameter on the desulfurization efficiency and the dust removal efficiency; and dynamically adjusting the priority optimization target according to the influence characteristic curve to make the operating state reach the ideal balance, the influence characteristic curve being generated according to a shared operating parameter, the shared operating parameter including a water injection amount or a slurry injection amount.

[0007] By adopting the above technical solution, the inlet flue gas parameter, the desulfurization outlet SO2 concentration and the outlet dust concentration are collected in real time, wherein the inlet flue gas parameter covers key indicators such as flue gas flow and inlet SO2 concentration. These real-time data provide a basis for subsequent calculation and analysis. Based on accurate raw data, the current desulfurization efficiency and the dust removal efficiency can be accurately calculated. Accurate operating data is obtained, which truly reflects the device operating state, thereby providing a reliable basis for subsequent comparison with the emission standard threshold and judgment of the operating state, so that the system can timely optimize and adjust the dynamic balance of the desulfurization efficiency and the dust removal efficiency, and ensure real-time and accurate grasp of the device operating condition.

[0008] Optionally, in the above embodiment, the current desulfurization efficiency and the dust removal efficiency are calculated according to the inlet flue gas parameter, the desulfurization outlet concentration and the outlet dust concentration, specifically including: obtaining the desulfurization efficiency by dividing the difference between the inlet concentration and the desulfurization outlet concentration by the inlet concentration; and obtaining the dust removal efficiency by dividing the difference between the inlet dust concentration and the outlet dust concentration by the inlet dust concentration.

[0009] By adopting the above technical solution, specific calculation methods are used, i.e. the desulfurization efficiency is calculated by dividing the difference between the inlet SO2 concentration and the desulfurization outlet concentration by the inlet SO2 concentration, and the dust removal efficiency is calculated by dividing the difference between the inlet dust concentration and the outlet dust concentration by the inlet dust concentration. This calculation method based on raw data can intuitively and accurately quantify the actual effect of the device in desulfurization and dust removal. The specific values calculated provide data support for subsequent comparison of the desulfurization efficiency and the dust removal efficiency with the emission standard threshold, so that it can be clearly judged whether the device meets the environmental protection requirements, thereby providing a core basis for accurate determination of the operating state and ensuring that the quantitative evaluation of the device treatment effect is scientific and reliable.

[0010] Optionally, in the above embodiment, the desulfurization efficiency and the dust removal efficiency are compared with the emission standard threshold to obtain the current running state, specifically including: comparing the current desulfurization efficiency and the dust removal efficiency with a preset emission standard threshold, the emission standard threshold including a desulfurization emission standard threshold or a dust removal emission standard threshold; if the desulfurization efficiency is lower than the emission standard threshold, it is determined that the current running state is a desulfurization limited state; if the dust removal efficiency is lower than the emission standard threshold, it is determined that the current running state is a dust removal limited state; if the desulfurization efficiency and the dust removal efficiency both meet the emission standard threshold, it is determined that the current running state is an ideal balance state; if the desulfurization efficiency and the dust removal efficiency are both lower than the respective emission standard threshold, it is determined that the current running state is a double limited state.

[0011] By using the above technical solution, the current desulfurization efficiency and dust removal efficiency are compared with the preset desulfurization and dust removal emission standard threshold, and the running state is determined according to the comparison result. This way can comprehensively and systematically classify the device running state, and clearly define different states such as ideal balance and desulfurization limited. Accurate running state determination provides a clear direction for subsequent determination of priority optimization target, so that the system can accurately attack different running problems, avoid blind adjustment, ensure that the optimization work is targeted, improve the pertinence and effectiveness of device running, and ensure that the device running meets the environmental protection standard.

[0012] Optionally, in the above embodiment, if the running state is not the ideal balance, the priority optimization target is determined, specifically including: if the current running state is the desulfurization limited, the desulfurization efficiency is determined as the priority optimization target; if the current running state is the dust removal limited, the dust removal efficiency is determined as the priority optimization target; if the current running state is the double limited, the desulfurization efficiency and the dust removal efficiency are both determined as the priority optimization target.

[0013] By using the above technical solution, the corresponding priority optimization target is determined according to different running states. When the running state is desulfurization limited, the desulfurization efficiency is determined as the priority optimization target, and the same is true for other running states. This targeted target determination method can make the system focus on the key problems of the current device running and solve the most urgent limited function first. In the subsequent optimization process, resources and adjustment direction are concentrated, optimization efficiency is improved, resources are not wasted on non-key problems, and the device can quickly and effectively improve the main problems and improve the overall running performance under different running conditions.

[0014] Optionally, in the above embodiment, the dynamically adjusting the priority optimization target according to the influence characteristic curve specifically comprises: obtaining the shared operation parameter meeting the synergistic sweet spot region based on the influence characteristic curve and in combination with the priority optimization target; and dynamically adjusting the water injection amount or the slurry injection amount according to the shared operation parameter to adjust the priority optimization target.

[0015] By adopting the above technical solution, the shared operation parameter meeting the synergistic sweet spot region is obtained based on the influence characteristic curve in combination with the priority optimization target, and the water injection amount or the slurry injection amount is dynamically adjusted accordingly. The influence characteristic curve shows the influence law of the shared operation parameter on the desulfurization efficiency and the dust removal efficiency, and the synergistic sweet spot region can be used to find the operation parameter that has the maximum positive influence on the priority optimization target and the minimum negative influence on the secondary target. By accurately adjusting the shared operation parameter, the priority optimization target is effectively improved, and the secondary target is also considered, so that a balance between the two is sought, the running state is changed to an ideal balance, and the comprehensive performance and efficiency of the device are improved.

[0016] Optionally, in the above embodiment, the influence characteristic curve specifically comprises: the influence characteristic curve comprises a positive influence region, a negative influence region and a synergistic sweet spot region; the positive influence region is used to represent an interval in which the shared operation parameter is increased and the desulfurization efficiency and the dust removal efficiency are simultaneously improved; the negative influence region is used to represent an interval in which the shared operation parameter is increased and the desulfurization efficiency and the dust removal efficiency are decreased; and the synergistic sweet spot region is used to represent an interval in which the shared operation parameter has the maximum positive influence on the priority optimization target and the minimum negative influence on the secondary target, the secondary target being another target other than the priority optimization target.

[0017] By adopting the above technical solution, the influence characteristic curve is divided into the positive influence region, the negative influence region and the synergistic sweet spot region. This partitioning method clearly shows different influence intervals of the shared operation parameter on the desulfurization efficiency and the dust removal efficiency. In the optimization process, the staff can quickly locate the appropriate operation parameter interval according to different running states and priority optimization targets. For example, when looking for a parameter balancing the two efficiencies, the synergistic sweet spot region can be directly referred to, so as to avoid invalid adjustment in the negative influence region, reduce the blindness of adjustment, improve the accuracy and efficiency of optimization, and provide scientific guidance for realizing efficient operation of the device.

[0018] Optionally, in the above embodiment, after the dynamic adjustment of the priority optimization target according to the influence characteristic curve, the method further comprises: if the dynamic adjustment has an adverse effect on the secondary target, formulating a compensatory optimization strategy for eliminating the adverse effect on the secondary target; adjusting an auxiliary parameter collected in real time by the compensatory optimization strategy, the auxiliary parameter including a desulfurizer dosage, an electric dust collector electric parameter or other adjustable operating parameters; after adjusting the auxiliary parameter, re-evaluating the current operating state; if the current operating state still does not reach the ideal balance, returning to the dynamic adjustment step to continue adjusting the shared operating parameter and the auxiliary parameter until the operating state reaches the ideal balance.

[0019] In a second aspect, the embodiments of the present application provide an intelligent control system of a single-tower desulfurization and dust removal device, including: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is configured to store computer program codes, the computer program codes including computer instructions, and the one or more processors invoke the computer instructions to enable the electronic device to perform the method described in the first aspect or the second aspect and any possible implementation manner of the first aspect or the second aspect.

[0020] In a third aspect, the present application provides a computer-readable storage medium including instructions that, when executed on the electronic device, cause the electronic device to perform the method described in the first aspect or the second aspect and any possible implementation manner of the first aspect or the second aspect.

[0021] In a fourth aspect, the present application provides a computer program product including instructions that, when executed on the electronic device, cause the electronic device to perform the method described in the first aspect or the second aspect and any possible implementation manner of the first aspect or the second aspect.

[0022] It can be understood that the intelligent control system of a single-tower desulfurization and dust removal device provided in the second aspect, the storage medium provided in the third aspect and the computer program product provided in the fourth aspect are all used to execute the method provided in the present application. Therefore, the beneficial effects that can be achieved thereby can refer to the beneficial effects in the corresponding method, which will not be described here again.

[0023] The one or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0024] 1. By adopting the above technical scheme, the inlet flue gas parameters, the desulfurization outlet SO2 concentration and the outlet dust concentration are collected in real time, which comprehensively reflects the state of the flue gas before entering the device and the effect after treatment. Real-time and accurate data collection provides a reliable basis for calculating the current desulfurization efficiency and dust removal efficiency, ensuring that the calculation result can truly reflect the device running state. And accurate efficiency calculation is the basis for judging the running state. Only when the running state is clear, can it be known whether the desulfurization efficiency and the dust removal efficiency are unbalanced. In this way, real-time collection of parameters becomes the primary link for the entire system to master the device running dynamics and find efficiency imbalance problems, providing key data support for subsequent adjustment to achieve dynamic balance, ensuring that the system can respond to efficiency imbalance in a timely manner.

[0025] 2. By adopting the above technical scheme, based on the influence characteristic curve combined with the priority optimization target, the shared operation parameters meeting the collaborative sweet spot area are obtained, and the water injection amount or the slurry injection amount is dynamically adjusted. The influence characteristic curve intuitively presents the relationship between the shared operation parameters and the desulfurization efficiency and the dust removal efficiency, and the collaborative sweet spot area indicates the parameter range that can maximize the positive influence on the priority optimization target while minimizing the negative influence on the secondary target. When the priority optimization target is determined, adjusting the shared operation parameters in the collaborative sweet spot area can efficiently improve the priority optimization target and minimize the negative impact on the secondary target. In this way, under different running states, the gap between the desulfurization efficiency and the dust removal efficiency can be gradually narrowed through such precise adjustment, promoting the two to tend towards dynamic balance and realizing efficient and stable operation of the device.

[0026] 3. By adopting the above technical scheme, when the dynamic adjustment has an adverse effect on the secondary target, a compensatory optimization strategy is formulated to adjust the auxiliary parameters and reevaluate the running state. In the process of dynamically adjusting the shared operation parameters to optimize the priority target, the secondary target may be adversely affected, causing the originally unbalanced desulfurization efficiency and dust removal efficiency to further deviate from the balanced state. At this time, the compensatory optimization strategy adjusts the desulfurizer dosage, the electric dust collector electric parameter and other auxiliary parameters to compensate for the damage to the secondary target caused by dynamic adjustment. Re-evaluating the running state can monitor the adjustment effect in real time. If the ideal balance has not been achieved, continue to adjust the shared operation parameters and auxiliary parameters. Through this cyclic optimization mechanism, the priority target is improved while the secondary target is stabilized, gradually achieving dynamic balance of the desulfurization efficiency and the dust removal efficiency, and ensuring that the device can also operate efficiently under complex working conditions. BRIEF DESCRIPTION OF DRAWINGS

[0027] The accompanying drawings, which are incorporated herein and constitute part of the specification, illustrate embodiments consistent with the application and, together with the description, further serve to explain the principles of the application. It is apparent that the accompanying drawings are only some embodiments of the application, and other drawings can be obtained from the accompanying drawings without creative labor for those skilled in the art. In the drawings:

[0028] Figure 1 is a flowchart of an intelligent control method of a single-tower desulfurization and dust removal device according to an embodiment of the application;

[0029] Figure 2 is another flowchart of an intelligent control method of a single-tower desulfurization and dust removal device according to an embodiment of the application;

[0030] Figure 3 is a schematic diagram of an entity device structure of an intelligent control system of a single-tower desulfurization and dust removal device according to an embodiment of the application. DETAILED DESCRIPTION

[0031] The terms used in the following embodiments of the application are only for the purpose of describing specific embodiments and are not intended to be limiting of the application. As used in the specification, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "and / or," as used herein, refers to any or all possible combinations of one or more of the associated listed items.

[0032] Hereinafter, the terms "first" and "second" are only for the purpose of description, and cannot be understood as implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first" and "second" can explicitly or implicitly include one or more of the features, and in the description of the embodiments of the application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0033] It should also be noted that, unless otherwise explicitly specified and limited, the terms "set", "connected" and the like in the embodiments of the application should be understood in a broad sense. For example, "connected" can be fixedly connected, or detachably connected, or integrally connected; can be mechanically connected, or electrically connected; can be directly connected, or indirectly connected through an intermediate medium; can be internal communication of two elements; can be wired communication connection, or wireless communication connection. For those skilled in the art, the specific meaning of the above terms in the application can be understood according to the specific circumstances. The embodiments of the application are described in detail as follows.

[0034] With the increasing global awareness of environmental protection and the continuous tightening of industrial emission standards, efficient and economical control of pollutants such as sulfur dioxide and dust in industrial flue gas has become a key link for the sustainable development of industrial enterprises. Single-tower desulfurization and dust removal devices have been widely used in many industries such as power generation, steel, chemical industry, and waste incineration due to their compact structure, small footprint, and relatively low investment and operating costs. However, the operation control of such integrated devices, especially how to achieve the synergistic and efficient desulfurization and dust removal under complex and variable working conditions, still faces many challenges. Real-time fluctuations in inlet flue gas parameters (such as flue gas flow, concentration, dust concentration, temperature, etc.), as well as the internal coupling and mutual influence between desulfurization and dust removal processes in the shared operating units (such as the spray system) in the tower, make it a complex technical problem to achieve a sustained dynamic balance between the two efficiencies.

[0035] Currently, the control methods for single-tower desulfurization and dust removal devices still have some deficiencies in practice. Many existing control strategies focus on setting fixed operating parameters based on experience or using feedback control logic for a single target. Such methods can meet the basic requirements when the device design conditions or flue gas parameters are relatively stable, but their adaptability is limited when faced with drastic fluctuations in inlet flue gas conditions or gradual changes in equipment performance. They often fail to perform real-time and comprehensive evaluation and dynamic adjustment of desulfurization and dust removal efficiencies, leading to excessive use of consumables such as desulfurizing agents and water resources, increasing operating costs; or in some extreme conditions, there may be a risk of insufficient treatment efficiency, leading to emissions exceeding standards. More importantly, traditional methods often ignore the complex interaction between the desulfurization and dust removal processes through shared operating parameters (such as water or slurry injection), and lack a mechanism that can accurately identify and utilize this influence to achieve overall optimization.

[0036] To solve the above technical problems, effectively improve the operation intelligent level, resource utilization efficiency and pollutant collaborative control ability of the single-tower desulfurization and dust removal device, the embodiment of the application provides an intelligent control method, system, medium and product of a single-tower desulfurization and dust removal device. The method constructs a dynamic and closed-loop intelligent control system based on real-time data driving. It collects the inlet flue gas parameters and outlet pollutant concentration in real time and comprehensively, dynamically calculates the current desulfurization efficiency and dust removal efficiency, and compares them with the preset emission standard threshold, so as to accurately judge the instantaneous operation state of the device. On this basis, the method innovatively introduces the core mechanism of the "influence characteristic curve of shared operating parameters on desulfurization efficiency and dust removal efficiency" constructed based on test data and operation history data. When the operation state is not ideal, the system can determine the priority optimization target, and intelligently and dynamically adjust the shared operating parameters according to the characteristic curve, maintain the dynamic balance between the desulfurization efficiency and the dust removal efficiency, and finally realize the efficient, stable, economic and continuous standard operation of the device under various working conditions.

[0037] As shown in Figure 1 , it is a flowchart of an intelligent control method of a single-tower desulfurization and dust removal device according to an embodiment of the application.

[0038] The intelligent control method of a single-tower desulfurization and dust removal device according to an embodiment of the application will be described in detail below. Figure 1 The method can be applied to an intelligent control system of a single-tower desulfurization and dust removal device (hereinafter referred to as the system). The method comprises the following steps: 101, real-time acquisition of inlet flue gas parameters, desulfurization outlet concentration and outlet dust concentration, wherein the inlet flue gas parameters include flue gas flow, inlet concentration, dust concentration and temperature;

[0039] The system obtains data through high-precision sensors deployed in different positions of the device. At the inlet of the flue gas, a flue gas flow sensor, a SO2 concentration sensor, a dust concentration sensor and a temperature sensor are installed. The system continuously monitors and collects data of various parameters of the inlet flue gas through these sensors.

[0040] When collecting these data, the system will do it at a certain frequency, for example, collecting data once every second, to ensure that the obtained data is real-time and continuous. The collected data will be temporarily stored in the cache area of the system, waiting for further processing and analysis. At the same time, the system also has a data verification function, which will reasonably check the collected data. For example, if the detected inlet SO2 concentration is negative or the temperature exceeds the normal physical range (such as below absolute zero or above the highest temperature that the flue gas can reach), the system will determine that the data is abnormal and automatically re-collect or issue an alarm to prompt the staff to check and handle, to ensure the accuracy and reliability of the collected data, and provide a solid data foundation for subsequent calculation and analysis.

[0041] 102. Calculate the current desulfurization efficiency and dust removal efficiency according to the inlet flue gas parameters, the desulfurization outlet concentration, and the outlet dust concentration;

[0042] After obtaining accurate real-time data, the system calculates the current desulfurization efficiency and dust removal efficiency.

[0043] When the system performs calculations, it stores the desulfurization efficiency and dust removal efficiency data obtained each time to form historical data records. These historical data can not only be used to analyze the processing efficiency trends of the device at different time periods and under different operating conditions, but also provide reference for subsequent performance evaluation and optimization. At the same time, the system will preliminarily analyze and judge the calculation results. For example, if the desulfurization efficiency or dust removal efficiency obtained by continuous calculation is lower than the historical average level, the system will mark possible problems and start the preliminary troubleshooting mechanism to check whether there are sensor failures, equipment operation abnormalities, etc., so as to discover potential problems in the running process of the device in time and provide important clues for subsequent adjustment of the running state.

[0044] 103. Compare the desulfurization efficiency and the dust removal efficiency with the emission standard threshold to obtain the current running state, which includes ideal balance, desulfurization limited, dust removal limited, and double limited.

[0045] After completing the calculation of desulfurization efficiency and dust removal efficiency, the system will compare these two key indicators with the pre-set emission standard threshold in detail, so as to accurately judge the current running state of the device. The emission standard threshold is determined comprehensively according to national and local environmental protection regulations, industry standards, and design requirements of the device, etc. Among them, the desulfurization emission standard threshold and the dust removal emission standard threshold are respectively used to measure whether the device meets the environmental protection requirements in terms of desulfurization and dust removal.

[0046] Suppose the local environmental protection department stipulates that the desulfurization emission standard threshold is 90%, and the dust removal emission standard threshold is 95%. The system first compares the calculated desulfurization efficiency with the desulfurization emission standard threshold, and at the same time compares the dust removal efficiency with the dust removal emission standard threshold. If the calculated desulfurization efficiency is 95%, which is greater than the desulfurization emission standard threshold of 90%, and the dust removal efficiency is 97.5%, which is greater than the dust removal emission standard threshold of 95%, then the system determines that the current running state is ideal balance. This means that under the current operating conditions, the desulfurization and dust removal effects of the device have reached or exceeded the environmental protection standard, the device is running stably and efficiently, and can meet the environmental protection requirements.

[0047] If the calculated desulfurization efficiency is less than 90% of the desulfurization emission standard threshold, and the dust removal efficiency is greater than 95% of the dust removal emission standard threshold, the system determines that the current running state is a desulfurization limited state. This indicates that the device has deficiencies in desulfurization and fails to meet environmental protection requirements, and the desulfurization-related operating parameters or equipment need to be adjusted and optimized to improve the desulfurization efficiency.

[0048] When the desulfurization efficiency is greater than the desulfurization emission standard threshold, but the dust removal efficiency is less than the dust removal emission standard threshold, the system determines that the current running state is a dust removal limited state. This indicates that the device has problems in the dust removal process and needs to be analyzed and improved to ensure that the dust removal effect meets environmental protection standards.

[0049] If the calculated desulfurization efficiency is less than the desulfurization emission standard threshold, and the dust removal efficiency is also less than the dust removal emission standard threshold, the system determines that the current running state is a dual-limited state. This means that the device has not met environmental protection requirements in both desulfurization and dust removal, and the system needs to be analyzed in depth and adjusted in both desulfurization and dust removal to restore the device to an ideal balanced state as soon as possible, avoiding environmental penalties or adverse effects on the environment due to non-compliance with emissions standards. After determining the running state, the system displays and records the results to allow the operator to promptly understand the device's running condition and take appropriate measures.

[0050] 104、If the running state is not the ideal balance, determine a priority optimization target, the priority optimization target indicating a main limited function in the running state;

[0051] When the system determines that the running state is not an ideal balance, it starts the process of determining the priority optimization target. This process is a key link to ensure efficient operation of the device and quickly solve efficiency imbalance problems. The system accurately locates the main limited function according to different non-ideal running states to determine the priority optimization target. After determining the priority optimization target, the system stores and marks it, and generates preliminary optimization prompt information. This information is transmitted to the operator, allowing him to clearly understand the current main problem of the device and the optimization direction. For example, the system displays "the current running state is desulfurization limited, the priority optimization target is desulfurization efficiency, and the desulfurizer supply system and reaction conditions should be checked", providing clear guidance for subsequent optimization operations and ensuring that optimization work is targeted and improves device performance.

[0052] 105、Based on the test data and the running history data, construct an influence characteristic curve of the shared operating parameters on the desulfurization efficiency and the dust removal efficiency;

[0053] After determining the priority optimization target, the system needs to build the influence characteristic curve of the shared operating parameters on the desulfurization efficiency and dust removal efficiency to achieve precise and effective optimization adjustment. The construction of this curve is based on the long-term accumulated test data and operation history data of the system, and is an important basis for intelligent control.

[0054] Through data processing and analysis, the system constructs the influence characteristic curve. The curve takes the shared operating parameters as the horizontal coordinate and the desulfurization efficiency and dust removal efficiency as the vertical coordinate, directly showing the influence of the change of water or slurry injection amount on the desulfurization efficiency and dust removal efficiency. The system will label the curve and divide it into positive influence area, negative influence area and collaborative sweet spot area. The positive influence area represents the interval where the increase of the shared operating parameters can simultaneously improve the desulfurization efficiency and dust removal efficiency; the negative influence area represents the interval where the increase of the parameters leads to the decrease of the two efficiencies; and the collaborative sweet spot area is the interval where the positive influence on the priority optimization target is the largest and the negative influence on the secondary target is the smallest.

[0055] 106、According to the influence characteristic curve, the priority optimization target is dynamically adjusted to make the running state reach the ideal balance, and the influence characteristic curve is generated according to the shared operating parameters, which include water or slurry injection amount;

[0056] After the system builds the influence characteristic curve, it dynamically adjusts the priority optimization target according to the curve. The system will develop and execute the corresponding parameter adjustment strategy according to the current running state, priority optimization target and the indication of the influence characteristic curve. By continuously dynamically adjusting according to the influence characteristic curve, the system can accurately adjust the shared operating parameters and auxiliary parameters under different running states, gradually optimize the desulfurization efficiency and dust removal efficiency, and make the running state of the device eventually reach the ideal balance, ensuring the efficient, stable and environmentally friendly operation of the device and realizing the standard emission of industrial flue gas.

[0057] In the above embodiment, the intelligent control method for a single-tower desulfurization and dust removal device provided by the present application realizes the dynamic coordination and precise regulation and control of the shared operating parameters through real-time accurate perception, intelligent diagnosis of bottlenecks, scientific establishment of optimization focus, and construction and use of influence characteristic curves. Through the complete closed-loop intelligent control process, the dynamic balance between desulfurization efficiency and dust removal efficiency is actively sought and maintained in complex working conditions. The value lies in not only ensuring the continuous and stable standard of environmental protection emission, but also improving the overall operation economy and resource utilization efficiency of the device through intelligent collaborative optimization, maximizing the integrated advantages of the single-tower integrated device.

[0058] In the above embodiments, the system dynamically adjusts the priority optimization target by sharing the operation parameter based on the influence characteristic curve, so as to realize the dynamic balance between the desulfurization efficiency and the dust removal efficiency. In actual application, the system may have an adverse effect on the secondary target in the dynamic adjustment of the shared operation parameter. In some embodiments, the system can eliminate the adverse effect on the secondary target by formulating a compensatory optimization strategy.

[0059] The following will be described in combination with Figure 2 The intelligent control method of the single-tower desulfurization and dust removal device provided in the embodiments of the present application is described, Figure 2 is another flowchart of the intelligent control method of the single-tower desulfurization and dust removal device in the embodiments of the present application. The specific description is as follows:

[0060] 201, real-time acquisition of inlet flue gas parameters, desulfurization outlet concentration and outlet dust concentration, wherein the inlet flue gas parameters include flue gas flow, inlet concentration, dust concentration and temperature;

[0061] Step 201 is similar to step 101 described above Figure 1 in the above embodiments, and reference can be made to the description of the above embodiments, which will not be described here again.

[0062] 202, obtaining the desulfurization efficiency by dividing the difference between the inlet concentration and the desulfurization outlet concentration by the inlet concentration;

[0063] After the system obtains the real-time inlet concentration and desulfurization outlet concentration data, the calculation program of the desulfurization efficiency is started immediately. This calculation process is a key step for quantifying the desulfurization performance of the device, and the system strictly follows the established calculation formula to accurately operate the collected data. The calculation formula is as follows:

[0064] Desulfurization efficiency = (inlet SO2 concentration-desulfurization outlet SO2 concentration) ÷ inlet SO2 concentration × 100%

[0065] Taking a single-tower desulfurization and dust removal device of a certain thermal power plant as an example, at a certain monitoring time, the system collects the inlet concentration of 1800 mg / m 3 and the desulfurization outlet concentration of 90 mg / m 3 . The system quickly substitutes these data into the formula for calculation: (1800-90) ÷ 1800 × 100% = 95%, thereby obtaining the desulfurization efficiency of the current device as 95%. In the calculation process, the system strictly controls the accuracy of the data to ensure the accuracy of the calculation result. At the same time, the system stores the desulfurization efficiency data obtained each time to form time series data.

[0066] The system also has a data anomaly processing mechanism. If it is found that the inlet concentration or desulfurization outlet concentration data is abnormal (such as data missing, data exceeding a reasonable range, etc.) during calculation, the system will automatically trigger a data repair program. For example, if the desulfurization outlet concentration data is missing at a certain time, the system will estimate the data using linear interpolation or other appropriate algorithms based on the data before and after the time, ensuring the continuity and accuracy of the desulfurization efficiency calculation.

[0067] In addition, the system will monitor the calculation results in real time, and once it finds that the desulfurization efficiency has a large fluctuation or abnormal decline, it will immediately issue a warning message to prompt the operator to pay attention to the device running state and promptly investigate possible problems, such as insufficient supply of desulfurizer, abnormal reaction temperature, etc., to provide strong support for the stable operation of the device.

[0068] 203、The dedusting efficiency is obtained by dividing the difference between the inlet dust concentration and the outlet dust concentration by the inlet dust concentration.

[0069] The system also calculates the dedusting efficiency. The accurate calculation of the dedusting efficiency is an important basis for evaluating the dedusting performance of the device, and is crucial for ensuring that the particulate matter in industrial flue gas meets the emission standards. The system processes the real-time collected inlet dust concentration and outlet dust concentration data according to a fixed calculation formula. The calculation formula is: Dedusting efficiency = (Inlet dust concentration - Desulfurization outlet dust concentration) ÷ Inlet dust concentration × 100%

[0070] Suppose that during the operation of a single-tower desulfurization and dust removal device in a certain steel plant, the system collects an inlet dust concentration of 600 mg / m 3 and an outlet dust concentration of 15 mg / m 3 . The system calculates according to the formula: (600-15) ÷ 600 × 100% = 97.5%, thus obtaining the dedusting efficiency of the current device as 97.5%. Similar to the calculation of desulfurization efficiency, the system also pays attention to the accuracy and integrity of the data when calculating the dedusting efficiency. For the collected dust concentration data, the system will perform multiple verifications, such as comparing with the data of adjacent monitoring points to check whether the data conforms to the normal variation law. If it is found that the data is abnormal, the system will automatically correct or re-collect the data.

[0071] The system also monitors the dedusting efficiency in real time through an anomaly processing mechanism, repairs or issues a warning message for data anomalies. The system also performs in-depth analysis on the calculation results of the dedusting efficiency. In addition to recording the specific values of each calculation, it also calculates the average value, standard deviation, etc. of the dedusting efficiency within a period of time to evaluate the stability of the dedusting performance of the device.

[0072] 204、compare the current desulfurization efficiency and the dust removal efficiency with preset emission standard thresholds respectively, the emission standard thresholds including a desulfurization emission standard threshold or a dust removal emission standard threshold;

[0073] After the system completes the calculation of the desulfurization efficiency and the dust removal efficiency, it enters the key comparative analysis link. In order to ensure that the industrial flue gas emission meets the environmental protection requirements, the system pre-sets strict desulfurization emission standard thresholds and dust removal emission standard thresholds. The setting of these thresholds comprehensively considers various factors such as national environmental protection regulations, local policies and industry standards, and is an important basis for judging whether the device running state meets the standard. The system compares the calculated current desulfurization efficiency and dust removal efficiency with the corresponding emission standard thresholds one by one.

[0074] Taking a single-tower desulfurization and dust removal device of a certain chemical enterprise as an example, the local environmental protection department stipulates that the desulfurization emission standard threshold is 90%, and the dust removal emission standard threshold is 95%. When the system compares the calculated desulfurization efficiency and dust removal efficiency with these thresholds, it uses an accurate numerical comparison algorithm. If at a certain time, the system calculates that the desulfurization efficiency is 92% and the dust removal efficiency is 96%, the system will automatically judge that the desulfurization efficiency is greater than 90% and the dust removal efficiency is greater than 95%, that is, the current device desulfurization and dust removal effect has reached the environmental protection standard requirements.

[0075] In the comparison process, the system has high-precision numerical processing capability and can accurately identify small numerical differences. At the same time, the system also records and stores the comparison results in real time to form detailed comparison logs. These logs not only contain the specific time, desulfurization efficiency, dust removal efficiency and emission standard threshold of each comparison, but also record the determination of the comparison results. Through the analysis of these logs, the operator can clearly understand the compliance of the device in different time periods and the change trend of the compliance state. In addition, the system will automatically generate corresponding prompt information according to the change of the comparison results. For example, when the desulfurization efficiency or the dust removal efficiency approaches the emission standard threshold, the system will issue a warning prompt to remind the operator to pay attention to the relevant parameters, take measures in advance to prevent emission exceeding the standard, ensure the stable operation of the device, and avoid environmental protection risks and economic losses caused by non-compliance of emission.

[0076] 205、determine the current running state according to the comparison result;

[0077] If the desulfurization efficiency is lower than the emission standard threshold, it is determined that the current running state is a desulfurization limited state;

[0078] If the dust removal efficiency is lower than the emission standard threshold, it is determined that the current running state is a dust removal limited state;

[0079] If both the desulfurization efficiency and the dust removal efficiency meet the emission standard threshold, it is determined that the current operating state is an ideal balance state;

[0080] If both the desulfurization efficiency and the dust removal efficiency are lower than the respective emission standard threshold, it is determined that the current operating state is a double-limited state;

[0081] The system uses a rigorous logical judgment mechanism to accurately determine the operating state of the current device according to the comparison results of the desulfurization efficiency and the dust removal efficiency with the emission standard threshold. This determination process is an important basis for the intelligent control system to achieve precise regulation and directly determines the direction of the subsequent optimization strategy.

[0082] When the system detects that the desulfurization efficiency is lower than the desulfurization emission standard threshold, it immediately determines that the current operating state is a desulfurization-limited state. For example, in the operation of a device in a certain thermal power plant, the calculated desulfurization efficiency is 88%, which is lower than the local desulfurization emission standard threshold of 90%. The system quickly marks the current operating state as desulfurization-limited.

[0083] If the dust removal efficiency is lower than the dust removal emission standard threshold, the system determines that the current operating state is a dust removal-limited state. Suppose that in the operation process of a device in a certain building materials factory, the dust removal efficiency is 94%, which is lower than the dust removal emission standard threshold of 95%. The system promptly determines that the operating state is dust removal-limited.

[0084] When both the desulfurization efficiency and the dust removal efficiency meet the respective emission standard threshold, the system determines that the current operating state is an ideal balance state. For example, in a normally operating large industrial device, the desulfurization efficiency is 93% and the dust removal efficiency is 96%, both of which meet the environmental protection standard requirements. The system confirms that the current state is in an ideal balance state. At this time, the system will continue to monitor the changes of the desulfurization efficiency and the dust removal efficiency to prevent sudden changes in the operating state. At the same time, the system will record and analyze various operating parameters when the operating state is in an ideal balance state, summarize the experience of efficient operation of the device, and provide a reference for subsequent optimization of operating parameters to ensure that the device can maintain an ideal balance state for a long time, achieving efficient and environmentally friendly emission of industrial flue gas.

[0085] On the contrary, if both the desulfurization efficiency and the dust removal efficiency are lower than the respective emission standard threshold, the system determines that the current operating state is a double-limited state.

[0086] 206、If the operating state is not the ideal balance, determine a priority optimization target, which refers to the main limited function in the operating state;

[0087] If the current operating state is desulfurization-limited, the priority optimization target is determined to be the desulfurization efficiency;

[0088] If the current operating state is the dual limitation, the priority optimization target is determined to be the desulfurization efficiency and the dust removal efficiency simultaneously.

[0089] If the current operating state is the dual limitation, the priority optimization target is determined to be the desulfurization efficiency and the dust removal efficiency simultaneously.

[0090] When the system determines that the current operating state is not the ideal balance, it enters the step of determining the priority optimization target, which is a key step to realize the efficient and stable operation of the device. The system accurately locates the main limited function in the operation of the device according to different non-ideal operating states, thereby determining the priority optimization target.

[0091] After determining the priority optimization target, the system takes it as the core basis for subsequent parameter adjustment and strategy formulation, and stores the target information in the database for subsequent tracing and analysis, thereby laying a foundation for realizing the efficient operation of the device.

[0092] 207、Based on the test data and the operation history data, the influence characteristic curve of the shared operation parameter on the desulfurization efficiency and the dust removal efficiency is constructed;

[0093] The influence characteristic curve includes a positive influence area, a negative influence area, and a synergistic sweet spot area;

[0094] The positive influence area is used to represent the interval in which the increase of the shared operation parameter simultaneously improves the desulfurization efficiency and the dust removal efficiency;

[0095] The negative influence area is used to represent the interval in which the increase of the shared operation parameter leads to the decrease of the desulfurization efficiency and the dust removal efficiency;

[0096] The synergistic sweet spot area is used to represent the interval in which the shared operation parameter has the maximum positive influence on the priority optimization target and the minimum negative influence on the secondary target, which is another target other than the priority optimization target;

[0097] After the system determines the priority optimization target, in order to realize precise control, it needs to construct the influence characteristic curve of the shared operation parameter on the desulfurization efficiency and the dust removal efficiency. The construction of this curve relies on the long-term accumulation of test data and operation history data of the system, and is an important basis for realizing intelligent control.

[0098] The system first retrieves a large amount of test data from the database, which covers multiple test results under different operating conditions and different combinations of operating parameters. For example, in a laboratory environment, the system sets different gradients for water injection and slurry injection, and records the corresponding desulfurization efficiency and dust removal efficiency data. At the same time, the system collects historical data of the device during actual operation, including water injection and slurry injection at different times and different loads in daily production, as well as corresponding desulfurization and dust removal efficiency indicators.

[0099] The system uses advanced data analysis algorithms to deeply process these massive data. Using multivariate regression analysis, decision tree algorithms in machine learning, etc., the nonlinear relationship between shared operating parameters (water injection or slurry injection) and desulfurization efficiency and dust removal efficiency is mined. During the analysis process, the system will classify the data according to different conditions, such as different flue gas flow and temperature intervals, and analyze the influence of shared operating parameters on desulfurization and dust removal efficiency respectively.

[0100] After data processing and analysis, the system constructs an influence characteristic curve. The curve takes shared operating parameters as the horizontal coordinate and desulfurization efficiency and dust removal efficiency as the vertical coordinate, directly presenting the influence trend of water injection or slurry injection on desulfurization efficiency and dust removal efficiency. For example, the curve shows that within a certain range, as the slurry injection increases, the desulfurization efficiency gradually rises, and the dust removal efficiency also improves initially, but when the slurry injection exceeds a certain value, the dust removal efficiency begins to decline. The system further annotates and divides the curve, clearly indicating the positive influence area, negative influence area, and collaborative sweet spot area. The positive influence area indicates the interval where increasing shared operating parameters can simultaneously improve desulfurization efficiency and dust removal efficiency; the negative influence area indicates the interval where increasing parameters will lead to a decrease in both efficiencies; and the collaborative sweet spot area is the interval where the primary optimization target is positively affected the most and the secondary target is negatively affected the least. The constructed influence characteristic curve is stored in the system's model library and regularly updated and optimized based on new data. The curve provides an intuitive and scientific reference for the system's subsequent parameter adjustment and optimization strategy formulation, enabling the system to quickly determine reasonable shared operating parameter adjustment directions and ranges based on different operating states and priority optimization targets.

[0101] 208、Based on the influence characteristic curve and in combination with the priority optimization target, the shared operating parameters that meet the collaborative sweet spot area are obtained;

[0102] After constructing the influence characteristic curve, the system, based on the curve and in combination with the determined priority optimization target, begins to find shared operating parameters that meet the collaborative sweet spot area, which is a key step in achieving the transition of the operating state to an ideal balance.

[0103] Assuming that the current running state is desulfurization limited, the priority optimization target is desulfurization efficiency. The system analyzes the relationship between the water injection amount or the slurry injection amount and the desulfurization efficiency and the dust removal efficiency under the current working condition according to the influence characteristic curve. If the curve shows that the current slurry injection amount is on the left side of the synergistic sweet spot area, in order to improve the desulfurization efficiency, the system will look for a suitable slurry injection amount parameter within the synergistic sweet spot area in the direction indicated by the curve. For example, the current slurry injection amount is 40 cubic meters per hour. Through analysis of the curve, the system finds that when the slurry injection amount increases to 45-50 cubic meters per hour, it is within the synergistic sweet spot area, which can significantly improve the desulfurization efficiency and minimize the negative impact on the dust removal efficiency. The system will recommend 45-50 cubic meters per hour as the slurry injection amount parameter and send this parameter information to the operator. At the same time, the control interface shows the predicted change trend of desulfurization efficiency and dust removal efficiency before and after adjustment, so that the operator can intuitively understand the adjustment effect.

[0104] When the running state is dust removal limited, the priority optimization target is dust removal efficiency. The system also analyzes according to the influence characteristic curve. If the curve shows that the current water injection amount is outside the synergistic sweet spot area, the system will find a water injection amount interval that can effectively improve the dust removal efficiency and has less impact on the desulfurization efficiency.

[0105] If the running state is double limited, the system will analyze the influence characteristic curve more cautiously. The system will consider the improvement needs of desulfurization efficiency and dust removal efficiency and find a best shared operation parameter combination within the synergistic sweet spot area. At the same time, it has a positive impact on the desulfurization efficiency and the dust removal efficiency, and the improvement amplitude of the two is relatively balanced. Thus, the dynamic balance of desulfurization efficiency and dust removal efficiency is gradually realized, and the device reaches the ideal running state.

[0106] 209、According to the shared operation parameter, dynamically adjusting the water injection amount or the slurry injection amount to adjust the priority optimization target;

[0107] After the system determines the shared operation parameter that meets the synergistic sweet spot area, it dynamically adjusts the water injection amount or the slurry injection amount. The system communicates with the actuator of the device in real time to accurately control the adjustment of the water injection amount or the slurry injection amount to achieve the purpose of adjusting the priority optimization target.

[0108] Suppose in a single-tower desulfurization and dust removal device of an industrial boiler, the system determines that the current priority optimization target is desulfurization efficiency, and through the influence characteristic curve, it is concluded that the slurry injection amount should be adjusted from 50 cubic meters per hour to 55 cubic meters per hour. The system first sends instructions to the control unit of the slurry injection system. After receiving the instructions, the control unit drives devices such as the metering pump to gradually increase the slurry injection amount. During the adjustment process, the system monitors the actual change of the slurry injection amount in real time at a very high frequency (such as once per second) to ensure that the actual slurry injection amount is consistent with the target value. At the same time, the system continuously collects desulfurization efficiency and dust removal efficiency data to observe the adjustment effect. As the slurry injection amount increases, the system analyzes the trend of the desulfurization efficiency. If it is found that the desulfurization efficiency gradually increases as expected, for example, from the original 88%, the system will continue to maintain the current adjustment strategy and continuously monitor the data. However, if the desulfurization efficiency does not increase significantly or fluctuates during the adjustment process, the system will quickly activate the emergency mechanism. The system will compare the influence characteristic curve to check whether other factors interfere with the adjustment effect, such as whether the mixer in the absorption tower is running normally, whether the pH value of the slurry is stable, etc. If it is found that the desulfurization reaction is affected by the low pH value of the slurry, the system will simultaneously adjust the alkali addition device to increase the pH value of the slurry, thereby promoting the increase of the desulfurization efficiency.

[0109] In the scenario of adjusting water injection amount, again taking a device in a certain steel plant as an example. When the system determines that the priority optimization target is dust removal efficiency, and calculates that the water injection amount should be adjusted from 30 cubic meters per hour to 33 cubic meters per hour. The system sends control signals to the electric valve of the water injection system to gradually open the valve and increase the water injection amount. During this process, the system not only focuses on the change of the dust removal efficiency, but also closely monitors whether the desulfurization efficiency is affected. Because water injection may change the reaction environment in the absorption tower, thereby affecting the desulfurization effect. If it is found that the desulfurization efficiency shows a downward trend, the system will adjust other related parameters appropriately according to the pre-set priority and compensation strategy, such as increasing the concentration of desulfurization agent, to maintain the stability of the desulfurization efficiency and ensure that the adjustment process not only achieves the priority optimization target, but also takes into account the overall performance of the device.

[0110] 210、detecting whether the dynamic adjustment adversely affects the secondary target;

[0111] After the system completes the dynamic adjustment of the water injection amount or the slurry injection amount, it detects the impact on the secondary target. During the process of improving the priority optimization target, the adjustment of shared operating parameters may have a negative impact on the secondary target. Only by timely discovering and handling these impacts can the dynamic balance of desulfurization efficiency and dust removal efficiency be achieved.

[0112] In the case of limited desulfurization and prioritized optimization of desulfurization efficiency, the system will monitor the changes in the primary target of dust removal efficiency in real time after increasing the amount of shotcrete to improve desulfurization efficiency. The system continuously collects dust removal efficiency data and compares and analyzes the data before adjustment. Assuming that the dust removal efficiency before adjustment is 96%, after increasing the amount of shotcrete, the system detects that the dust removal efficiency has decreased to 94.5% after a period of operation. The system will determine that dynamic adjustment has had an adverse effect on dust removal efficiency. The system will further analyze the reasons for the decrease in dust removal efficiency by retrieving relevant device operating parameters such as the electric field strength of the electrostatic precipitator and the pressure difference of the bag-type dust collector, and combining the influence characteristic curve to determine whether the increase in shotcrete amount has caused changes in slurry droplet size, affecting the capture effect of the dust removal equipment, or other factors.

[0113] 211、if the dynamic adjustment has an adverse effect on the secondary target, a compensatory optimization strategy is developed to eliminate the adverse effect on the secondary target;

[0114] Once the system detects that dynamic adjustment has an adverse effect on the secondary target, the development program of the compensatory optimization strategy is immediately started. The system develops a targeted compensation strategy to eliminate the adverse effect on the secondary target and ensure the overall performance of the device. If the dust removal efficiency decreases due to the increase in shotcrete amount during the process of improving desulfurization efficiency, the system will first analyze the specific reasons for the decrease in dust removal efficiency. If it is determined that the increase in shotcrete amount has increased the number of slurry droplets, affecting the electric field characteristics of the electrostatic precipitator, resulting in a decrease in dust removal efficiency. The system will develop the following compensation strategy: on the one hand, appropriately increase the electric field strength of the electrostatic precipitator to enhance the capture ability of particulate matter; on the other hand, adjust the frequency and time of the rapping device to make the particulate matter attached to the electrode plate fall off more effectively and improve the dust removal efficiency. The system will calculate the adjustment range of the electric field strength and the rapping frequency according to the influence characteristic curve and historical experience data. For example, the electric field strength of the electrostatic precipitator is gradually increased from the original 30 kV to 33 kV, and the rapping frequency is increased from 1 time per minute to 1.2 times per minute. After implementing the adjustment, the system continuously monitors the changes in dust removal efficiency, and if the effect is not obvious, it will further fine-tune the parameters until the dust removal efficiency returns to a reasonable level.

[0115] When adjusting the water spray volume to improve dust removal efficiency results in a decrease in desulfurization efficiency, the system will conduct in-depth analysis of the root cause of the decrease in desulfurization efficiency. If it is determined that the temperature in the absorption tower is reduced due to water spray, affecting the desulfurization reaction rate, the system will develop a compensation strategy: increase the input amount of desulfurizing agent, increase the concentration of desulfurizing agent, to speed up the desulfurization reaction; at the same time, start the heating device of the absorption tower, appropriately increase the temperature in the tower, and optimize the desulfurization reaction environment. The system will dynamically adjust the addition amount of desulfurizing agent and the heating temperature according to the real-time monitoring of desulfurization efficiency data and reaction parameters. For example, first increase the desulfurizing agent concentration from the original 10% to 12%, and increase the absorption tower temperature from 50°C to 53°C, then continuously observe the change of desulfurization efficiency. If the desulfurization efficiency still does not meet the expectation, the system will continue to optimize the compensation strategy, such as adjusting the circulating flow of the slurry, enhancing the mass transfer effect of the desulfurization reaction, to ensure that the desulfurization efficiency is effectively restored while the dust removal efficiency is improved, to achieve dynamic balance of desulfurization and dust removal efficiency, to ensure stable and efficient operation of the device, to meet the environmental protection emission requirements.

[0116] 212、Through the compensatory optimization strategy, the real-time collected auxiliary parameters are adjusted, including the amount of desulfurizing agent, the electric parameters of the electric precipitator, or other adjustable operating parameters;

[0117] After the system formulates the compensatory optimization strategy, it immediately enters the auxiliary parameter adjustment stage. Through the communication interface with each subsystem of the device, the system precisely controls the adjustment of auxiliary parameters, ensuring that the compensatory optimization strategy can be effectively implemented, and eliminating the adverse effects of dynamic adjustment on secondary targets.

[0118] For cases involving other adjustable operating parameters, such as adjusting the speed of the agitator in the absorption tower. When the system finds that the slurry mixing is uneven, affecting the desulfurization or dust removal effect, it will adjust the agitator speed according to the compensation strategy. The system sends instructions to the frequency converter of the agitator to change the operating frequency of the motor, thereby adjusting the agitator speed. During the adjustment process, the system will monitor parameters such as the concentration distribution of the slurry and the reaction temperature simultaneously, evaluate the mixing effect, and ensure that the adjusted agitator speed can effectively improve the mixing state of the slurry, and improve the desulfurization and dust removal efficiency. Through precise adjustment of these auxiliary parameters, the system gradually implements the compensatory optimization strategy, laying the foundation for restoring the overall performance of the device.

[0119] 213、After adjusting the auxiliary parameters, the current operating state is re-evaluated;

[0120] After the system completes the adjustment of auxiliary parameters, it immediately starts the re-evaluation program of the current operating state. This process re-monitors and analyzes key indicators such as desulfurization efficiency and dust removal efficiency to determine whether the compensatory optimization strategy is effective and whether the device is close to or has reached the ideal balanced state.

[0121] 214. Determine whether the current operating state has reached the ideal balance;

[0122] 215. If the current operating state has not yet reached the ideal balance, return to the dynamic adjustment step and continue adjusting the shared operating parameters and auxiliary parameters until the operating state reaches the ideal balance.

[0123] When the system determines that the current operating state has not yet reached the ideal balance, it will immediately start a new round of optimization adjustment cycle. Based on the previous analysis results and adjustment experience, the system reconsiders the shared operating parameters and auxiliary parameters, further optimizes the adjustment strategy, and continuously promotes the operating state to approach the ideal balance.

[0124] During the adjustment process, the system will monitor the changes of various parameters and the response of desulfurization efficiency and dust removal efficiency in real time. After each parameter adjustment, the system will wait for a period of time (such as 5-10 minutes) to allow the device to operate stably under the new parameter conditions, so as to obtain accurate efficiency data. If the desulfurization efficiency is improved after this adjustment, but still does not reach the standard, and the dust removal efficiency also appears new fluctuations, the system will further analyze the reasons, and may consider adjusting other auxiliary parameters, such as optimizing the formula of desulfurizer, adjusting the slurry circulation flow of absorption tower, etc.

[0125] The system will continuously repeat this adjustment, monitoring, evaluation and judgment process, and gradually optimize the combination of shared operating parameters and auxiliary parameters. With the adjustment, the system will gradually find the most suitable parameter settings for the current working condition, so that the desulfurization efficiency and dust removal efficiency are gradually improved and stabilized. For example, after multiple adjustments, the desulfurization efficiency is gradually improved from the initial 88% to 91%, and the dust removal efficiency is stabilized at about 96%. When the system finally determines that the operating state has reached the ideal balance, it will stop adjusting and record the current parameter settings as the optimal operating parameters for this working condition, providing a reference for subsequent operation under similar working conditions, ensuring that the device can operate stably and efficiently for a long time, and achieving the standard emission of industrial flue gas.

[0126] In the above embodiment, by adopting the intelligent control method of the single-tower desulfurization and dust removal device provided in the present application, dynamic balance between desulfurization efficiency and dust removal efficiency in the single-tower desulfurization and dust removal device is achieved. The system intelligently optimizes the shared operating parameters by affecting the characteristic curve, maintains the dynamic balance between the desulfurization efficiency and the dust removal efficiency, and actively identifies and compensates for potential "side effects" in the optimization process. This means that when adjusting the shared parameters to improve the priority optimization target, the system can compensate for the damage to the secondary target by adjusting the individual auxiliary parameters. This main adjustment plus auxiliary compensation strategy effectively avoids the dilemma of losing one or the other or repeatedly optimizing the effect when simply relying on shared parameter adjustment, enabling the system to more quickly and stably approach and maintain the ideal state of good desulfurization and dust removal efficiency, thereby significantly improving the overall operation efficiency, resource utilization, and long-term environmental protection compliance reliability of the device.

[0127] The method provided in the above embodiment can be executed by an intelligent control system of the single-tower desulfurization and dust removal device, which is composed of an electronic device. The electronic device in the embodiment of the present application is described from the perspective of hardware processing below. Please refer to Figure 3 , which is a schematic diagram of an entity device structure of the intelligent control system of the single-tower desulfurization and dust removal device in the embodiment of the present application.

[0128] It should be noted that Figure 3 The structure of the intelligent control system of the single-tower desulfurization and dust removal device shown is only an example and should not limit the functions and use range of the embodiment of the present application.

[0129] As Figure 3 shown, the electronic device includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes, such as executing the method described in the above embodiment, according to programs stored in a read-only memory (ROM) 402 or loaded from a storage portion 408 to a random access memory (RAM) 403. Various programs and data required for system operation are also stored in the random access memory (RAM) 403. The central processing unit (CPU) 401, the read-only memory (ROM) 402, and the random access memory (RAM) 403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0130] The following components are connected to the input / output (I / O) interface 405: an input section 406 including an audio input device, a button switch, and the like; an output section 407 including a display, an audio output device, a lamp, and the like; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, and the like. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the input / output (I / O) interface 405 as necessary. A removable media 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is attached to the drive 410 as necessary, so that a computer program read out therefrom is installed in the storage section 408 as necessary.

[0131] In particular, according to embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing a computer program for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network by the communication section 409, and / or installed from the removable media 411. When the computer program is executed by the central processing unit (CPU) 401, various functions defined in the present application are executed.

[0132] Note that specific examples of the computer-readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any appropriate combination thereof. In the present application, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0133] The flow diagrams and the block diagrams in the drawings are illustrations of architectures, functionalities, and operations of possible implementations of systems, methods, and computer program products according to various embodiments of present application. It should be noted that each block in the flow diagrams and the block diagrams can represent a module, a program segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures.

[0134] In particular, the electronic device of the embodiment includes a processor and a memory coupled with the one or more processors, the memory configured to store computer program code comprising computer instructions to be invoked by the one or more processors to cause the electronic device to perform the method provided by the above-described embodiments.

[0135] As another aspect, the present application also provides a computer-readable storage medium, which can be included in the electronic device described in the above embodiments, or can exist separately and not be assembled into the electronic device. The storage medium carries one or more computer programs, which, when executed by a processor of the electronic device, cause the electronic device to implement the method provided in the above embodiments.

[0136] The above-described embodiments are only used to illustrate the technical solutions of the present application, but not limit the technical solutions; even though the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

[0137] In the above embodiments, according to the context, the term "when" can be interpreted as meaning "if" or "after" or "in response to determining" or "in response to detecting". Similarly, according to the context, the phrase "upon determining" or "if detecting (the stated condition or event)" can be interpreted as meaning "if determining" or "in response to determining" or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)".

[0138] Those skilled in the art can understand that all or part of the processes in the above-mentioned method embodiments can be implemented by a computer program instructing relevant hardware to complete, the program can be stored in a computer readable storage medium, and the program can include the processes of the above-mentioned method embodiments when executed. The aforementioned storage medium includes ROM or random storage memory RAM, magnetic disc or optical disc and various storage code medium.

Claims

1. An intelligent control method of a single-tower desulfurization and dust removal device, characterized in that, The method comprises the following steps: Real-time acquisition of inlet flue gas parameters, desulfurization outlet SO2 concentration and outlet dust concentration, wherein the inlet flue gas parameters include flue gas flow, inlet SO2 concentration, dust concentration and temperature; According to the inlet flue gas parameters, the desulfurization outlet SO2 concentration and the outlet dust concentration, the current desulfurization efficiency and dust removal efficiency are calculated; The desulfurization efficiency and the dust removal efficiency are compared with the emission standard threshold to obtain the current running state, and the running state includes ideal balance, desulfurization limitation, dust removal limitation and double limitation; If the running state is not the ideal balance, the priority optimization target is determined, and the priority optimization target refers to the main limited function in the running state; Based on the test data and the operation history data, the influence characteristic curve of the shared operation parameter on the desulfurization efficiency and the dust removal efficiency is constructed; The influence characteristic curve specifically includes: The influence characteristic curve includes a positive influence area, a negative influence area and a synergistic sweet spot area; The positive influence area is used to represent the interval in which the increase of the shared operation parameter simultaneously improves the desulfurization efficiency and the dust removal efficiency; The negative influence area is used to represent the interval in which the increase of the shared operation parameter leads to the decrease of the desulfurization efficiency and the dust removal efficiency; The synergistic sweet spot area is used to represent the interval in which the shared operation parameter has the maximum positive influence on the priority optimization target and the minimum negative influence on the secondary target, and the secondary target is another target except the priority optimization target; According to the influence characteristic curve, the priority optimization target is dynamically adjusted to make the running state reach the ideal balance, and the influence characteristic curve is generated according to the shared operation parameter, and the shared operation parameter includes water injection amount or slurry injection amount.

2. The method of claim 1, wherein, The calculation of the current desulfurization efficiency and dust removal efficiency according to the inlet flue gas parameters, the desulfurization outlet SO2 concentration and the outlet dust concentration specifically includes: The current desulfurization efficiency is obtained by dividing the difference between the inlet SO2 concentration and the desulfurization outlet SO2 concentration by the inlet SO2 concentration; The current dust removal efficiency is obtained by dividing the difference between the inlet dust concentration and the outlet dust concentration by the inlet dust concentration.

3. The method of claim 1, wherein, The comparison of the desulfurization efficiency and the dust removal efficiency with the emission standard threshold to obtain the current running state specifically includes: The current desulfurization efficiency and the dust removal efficiency are compared with the preset emission standard threshold, and the emission standard threshold includes a desulfurization emission standard threshold or a dust removal emission standard threshold; If the desulfurization efficiency is lower than the desulfurization emission standard threshold, but the dust removal efficiency is greater than or equal to the dust removal emission standard threshold, it is determined that the current running state is a desulfurization limitation state; If the dust removal efficiency is lower than the dust removal emission standard threshold, but the desulfurization efficiency is greater than or equal to the desulfurization emission standard threshold, it is determined that the current running state is a dust removal limitation state; If the desulfurization efficiency is greater than or equal to the desulfurization emission standard threshold, and the dust removal efficiency is greater than or equal to the dust removal emission standard threshold, it is determined that the current running state is an ideal balance state. If the desulfurization efficiency is lower than the desulfurization emission standard threshold and the dust removal efficiency is lower than the dust removal emission standard threshold, it is determined that the current operation state is a double-restricted state.

4. The method of claim 1, wherein, If the current operation state is not the ideal balance, a priority optimization target is determined, specifically including: If the current operation state is the desulfurization-restricted state, the priority optimization target is determined to be the desulfurization efficiency. If the current operation state is the dust removal-restricted state, the priority optimization target is determined to be the dust removal efficiency. If the current operation state is the double-restricted state, the priority optimization target is determined to be both the desulfurization efficiency and the dust removal efficiency.

5. The method of claim 1, wherein, The priority optimization target is dynamically adjusted according to the influence characteristic curve, specifically including: Based on the influence characteristic curve, the shared operation parameter that meets the synergistic sweet spot region is obtained in combination with the priority optimization target. The water injection amount or the slurry injection amount is dynamically adjusted according to the shared operation parameter, so as to adjust the priority optimization target.

6. The method of claim 1, wherein, After the priority optimization target is dynamically adjusted according to the influence characteristic curve, the method further includes: If the dynamic adjustment has an adverse effect on the secondary target, a compensatory optimization strategy is formulated, which is used to eliminate the adverse effect on the secondary target. The auxiliary parameter, including the desulfurizing agent dosage, the electric dust remover electric parameter, or other adjustable operation parameters, is adjusted through the compensatory optimization strategy. After the auxiliary parameter is adjusted, the current operation state is re-evaluated. If the current operation state still does not reach the ideal balance, the dynamic adjustment step is returned to continue adjusting the shared operation parameter and the auxiliary parameter until the operation state reaches the ideal balance.

7. An intelligent control system for a single tower desulfurization and dust removal device, characterized in that, comprise one or more processors and a memory; The memory is coupled to the one or more processors, and the memory is configured to store computer program codes, the computer program codes comprising computer instructions, and the one or more processors are configured to invoke the computer instructions to enable the intelligent control system of the single-tower desulfurization and dust removal device to perform the method according to any one of claims 1-6.

8. A computer readable storage medium storing computer instructions, characterized in that, When the computer instructions are executed on the intelligent control system of the single-tower desulfurization and dust removal device, the intelligent control system of the single-tower desulfurization and dust removal device is enabled to perform the method according to any one of claims 1-6.

9. A computer program product, characterised in that, When the computer program product is executed on the intelligent control system of the single-tower desulfurization and dust removal device, the intelligent control system of the single-tower desulfurization and dust removal device is enabled to perform the method according to any one of claims 1-6.

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