Method and system for adjusting and controlling density and temperature of urea solution

Abstract

The invention relates to the technical field of denitration systems, in particular to a urea solution density and temperature adjusting control method and system. Comprising the steps that monitoring points are set according to equipment parameters, and the monitoring points comprise a plurality of first-level monitoring points and a plurality of second-level monitoring points; setting an adjusting period according to the urea demand parameters, and generating an expected ratio curve in the monitoring period according to a preset density-temperature ratio model; generating an operation deviation value according to the preset feedback time node, and judging whether to generate a primary correction strategy according to the operation deviation value; the optimal corresponding relation between the temperature of the urea solution and the density of the urea solution in a single monitoring period is generated according to the constructed density-temperature ratio model, and the ratio of the temperature to the density of the urea solution is adjusted in real time by periodically collecting related data, so that the reaction state of the gasified urea liquid is improved, and the operation cost of a unit is reduced.

Description

Technical Field

[0001] The present application relates to the technical field of denitration systems, and in particular to a method and system for regulating and controlling the density and temperature of a urea solution. Background Art

[0002] The urea pyrolysis SCR denitrification process refers to the process of passing the urea solution through a metering and distribution module system, spraying it into the pyrolysis furnace through a spray gun, decomposing and mixing it with high-temperature hot air, and entering the SCR reactor through the AIG (ammonia injection grid) to react with NOx in the flue gas to produce N2 and H2O.

[0003] When the urea solution has different densities, the temperature corresponding to the optimal gasification state varies. At present, the urea density and temperature are mainly adjusted manually, which greatly increases the workload and labor intensity of personnel and is not conducive to the economic operation of the unit. Summary of the Invention

[0004] The purpose of this application is: to solve the above technical problems, this application provides a method and system for regulating and controlling the density and temperature of urea solution, aiming to improve the efficiency of urea solution density and temperature regulation, reduce the labor intensity of staff, and ensure economical and environmentally friendly operation of the unit.

[0005] In some embodiments of the present application, a method for regulating and controlling the density and temperature of a urea solution is provided, comprising: Setting monitoring points according to equipment parameters, wherein the monitoring points include multiple primary monitoring points and multiple secondary monitoring points; Set the adjustment period according to the urea demand parameters and generate the expected ratio curve within the monitoring period according to the preset density-temperature ratio model; Generate an operation deviation value according to the preset feedback time node, and determine whether to generate a first-level correction strategy based on the operation deviation value.

[0006] In some embodiments of the present application, when generating an operation deviation value according to a preset feedback time node, the process includes: Generate the expected temperature value a' and expected density value b' at the current feedback time node according to the expected ratio curve; Obtain the first-level data packet of each first-level monitoring point at the current feedback time node; Generate the temperature fluctuation value H1 of the current feedback time node based on all the first-level data packets; H1= (a i -a') 2 ; Where θ1 is the number of first-level monitoring points; ai is the temperature reference value of the i-th first-level monitoring point at the current feedback time node; Obtain the secondary data packets of each secondary monitoring point at the current feedback time node; Generate the density fluctuation value H2 at the current feedback time node according to all the secondary data packets; H2 = (b i - b') 2; where, θ2 is the number of secondary monitoring points; bi is the density reference value of the i-th secondary monitoring point at the current feedback time node; Generate the deviation evaluation value f at the current feedback time node.

[0007] In some embodiments of the present application, when generating the deviation evaluation value f at the current feedback time node, it includes: f = e1 * Q1 * H1 + e2 * Q2 * H2 + e3 * Q3 * H3; H3 = { a i / θ1) / b i / θ2)] - [a' / b']} 2 ; where, e1 is a preset first weight coefficient, e2 is a preset second weight coefficient; e3 is a preset third weight coefficient; Q1 is a preset first fixed coefficient; Q2 is a preset second fixed coefficient; Q3 is a preset third fixed coefficient.

[0008] In some embodiments of the present application, when judging whether to generate a primary correction strategy according to the operation deviation value, it includes: Preset a deviation evaluation value threshold F1; If f < F1, no primary correction strategy is generated at the current feedback time node; If f > F1, generate multiple initial correction strategies according to a preset correction model; Establish an initial correction strategy sequence C, C = (c1, c2…c i …c n ), where, c i is the i-th initial correction strategy; n is the number of initial correction strategies; Generate the primary correction strategy at the current feedback time node according to the initial correction strategy sequence C.

[0009] In some embodiments of the present application, when generating the primary correction strategy at the current feedback time node, it includes: Set c i as the target correction strategy in turn according to the initial correction strategy sequence C; Generate the correction benefit value d of the target correction strategy according to a preset evaluation model; d = β i*j i ]; Among them, r1 is the number of adjustment evaluation indicators; β i is the influencing factor of the i-th adjustment evaluation index; j i is the reference value of the i-th adjustment evaluation index generated based on the target correction strategy; Generate the revised return value of each initial revised strategy in sequence; Establish a modified return value series D, D = (d1, d2…d i …d n ), where d i is the revised return value of the i-th initial revised strategy; Set the maximum value d in the modified return value sequence D max The corresponding initial correction strategy is the first-level correction strategy at the current feedback time node.

[0010] In some embodiments of the present application, when a feedback time node is preset, it includes: Generate a monitoring evaluation value k for the current adjustment cycle based on the urea demand parameter; k= η i *g i ]; Among them, r2 is the number of monitoring and evaluation indicators; η i is the influencing factor of the i-th monitoring and evaluation indicator; g i Generate the reference value of the i-th monitoring and evaluation indicator based on the urea demand parameter; Establish multiple time intervals based on monitoring and evaluation values; Set the end time node of each time interval as the feedback time node; Get the deviation evaluation value f' of the current feedback time node; A compensation coefficient is generated according to the deviation evaluation value f', and the duration of the next time interval is corrected according to the compensation coefficient.

[0011] In some embodiments of the present application, a urea solution density and temperature regulation and control system is provided, comprising: The central control unit is used to set monitoring points according to equipment parameters, wherein the monitoring points include multiple primary monitoring points and multiple secondary monitoring points; A monitoring unit, comprising a plurality of monitoring submodules, wherein the monitoring submodules are arranged at each monitoring point; The monitoring unit is used to collect monitoring data from each monitoring point; The central control unit includes: A first processing module is used to set an adjustment period according to a urea demand parameter and generate an expected ratio curve within a monitoring period according to a preset density-temperature ratio model; The second processing module is used to generate an operation deviation value according to a preset feedback time node; The correction module is used to determine whether to generate a first-level correction strategy according to the operation deviation value.

[0012] In some embodiments of the present application, the second processing module is further used to: Generate an expected temperature value a' and an expected density value b' at the current feedback time node according to the expected ratio curve; Obtain the first-level data packets of each first-level monitoring point at the current feedback time node; Generate a temperature fluctuation value H1 at the current feedback time node according to all the first-level data packets; H1 = (a i - a') 2 ; where θ1 is the number of first-level monitoring points; ai is the temperature reference value of the i-th first-level monitoring point at the current feedback time node; Obtain the second-level data packets of each second-level monitoring point at the current feedback time node; Generate a density fluctuation value H2 at the current feedback time node according to all the second-level data packets; H2 = (b i - b') 2; where θ2 is the number of second-level monitoring points; bi is the density reference value of the i-th second-level monitoring point at the current feedback time node; Generate a deviation evaluation value f at the current feedback time node; f = e1 * Q1 * H1 + e2 * Q2 * H2 + e3 * Q3 * H3; H3 = { a i / θ1) / b i / θ2)] - [a' / b']} 2 ; where e1 is a preset first weight coefficient, e2 is a preset second weight coefficient; e3 is a preset third weight coefficient; Q1 is a preset first fixed coefficient; Q2 is a preset second fixed coefficient; Q3 is a preset third fixed coefficient.

[0013] In some embodiments of the present application, the correction module is further used to: Preset a deviation evaluation value threshold F1; If f < F1, no first-level correction strategy is generated at the current feedback time node; If f > F1, generate multiple initial correction strategies according to a preset correction model; Establish an initial correction strategy sequence C, C = (c1, c2…ci …c n ), where c i is the i-th initial correction strategy; n is the number of initial correction strategies; According to the initial correction strategy sequence C, set c i Modify strategy for goals; Generate the modified return value d of the target modification strategy based on the preset evaluation model; d= β i *j i ]; Among them, r1 is the number of adjustment evaluation indicators; β i is the influencing factor of the i-th adjustment evaluation index; j i is the reference value of the i-th adjustment evaluation index generated based on the target correction strategy; Generate the revised return value of each initial revised strategy in sequence; Establish a modified return value series D, D = (d1, d2…d i …d n ), where d i is the revised return value of the i-th initial revised strategy; Set the maximum value d in the modified return value sequence D max The corresponding initial correction strategy is the first-level correction strategy at the current feedback time node.

[0014] In some embodiments of the present application, the second processing module is further configured to: Generate a monitoring evaluation value k for the current adjustment cycle based on the urea demand parameter; k= η i *g i ]; Among them, r2 is the number of monitoring and evaluation indicators; η i is the influencing factor of the i-th monitoring and evaluation indicator; g i Generate the reference value of the i-th monitoring and evaluation indicator based on the urea demand parameter; Establish multiple time intervals based on monitoring and evaluation values; Set the end time node of each time interval as the feedback time node; Get the deviation evaluation value f' of the current feedback time node; A compensation coefficient is generated according to the deviation evaluation value f', and the duration of the next time interval is corrected according to the compensation coefficient.

[0015] Compared with the prior art, the method and system for regulating and controlling the density and temperature of a urea solution in the embodiment of the present application have the following beneficial effects: Based on the density-temperature ratio model, the optimal correspondence between the urea solution temperature and the urea solution density within a single monitoring cycle is generated. By periodically collecting relevant data, the ratio of urea solution temperature and density is adjusted in real time to improve the reaction state of urea liquid after gasification and reduce the operating cost of the unit.

[0016] By establishing a correction model, multiple initial correction strategies are set based on the real-time urea solution temperature and density parameters, and the best correction strategy is screened according to the optimization model, the adjustment efficiency of the ratio of urea solution temperature and density is improved, and the labor intensity of staff is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of a method for regulating and controlling the density and temperature of a urea solution in a preferred embodiment of the present application. DETAILED DESCRIPTION

[0018] The following embodiments are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0019] In the description of this application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application.

[0020] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout this application, unless otherwise specified, "plurality" means two or more.

[0021] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.

[0022] like Figure 1As shown, a method for regulating and controlling the density and temperature of a urea solution according to a preferred embodiment of the present application includes: S101: Setting monitoring points according to equipment parameters, the monitoring points include multiple primary monitoring points and multiple secondary monitoring points; S102: setting an adjustment period according to the urea demand parameter, and generating an expected ratio curve within the monitoring period according to a preset density-temperature ratio model; S103: Generate an operation deviation value according to a preset feedback time node, and determine whether to generate a first-level correction strategy based on the operation deviation value.

[0023] Specifically, based on the parameters, a mapping curve of urea solution density and urea solution temperature at different concentrations is generated. The mapping curve refers to the temperature value that the urea solution needs to maintain to reach the optimal reaction state after gasification at a specific urea solution concentration and density.

[0024] Specifically, the first-level monitoring point is used to collect the real-time temperature parameters of the urea solution, and the second-level monitoring point is used to collect the real-time density parameters of the urea solution.

[0025] Specifically, when generating the running deviation value according to the preset feedback time node, it includes: Generate the expected temperature value a' and expected density value b' at the current feedback time node according to the expected ratio curve; Obtain the first-level data packet of each first-level monitoring point at the current feedback time node; Generate the temperature fluctuation value H1 of the current feedback time node based on all the first-level data packets; H1= (a i -a') 2 ; Where θ1 is the number of first-level monitoring points; ai is the temperature reference value of the i-th first-level monitoring point at the current feedback time node; Obtain the secondary data packet of each secondary monitoring point at the current feedback time node; Generate the density fluctuation value H2 of the current feedback time node based on all secondary data packets; H2= (b i -b') 2; Wherein, θ2 is the number of secondary monitoring points; bi is the density reference value of the i-th secondary monitoring point at the current feedback time node; Generate the deviation evaluation value f of the current feedback time node.

[0026] Specifically, by setting multiple primary monitoring points and multiple secondary monitoring points, multiple groups of temperature data and multiple groups of density data are collected, avoiding misjudgment caused by single measurement errors, and at the same time monitoring the uniformity state of the urea solution.

[0027] Specifically, the expected ratio refers to the optimal expected ratio curve of urea solution temperature - density generated according to the expected changes in the current concentration of the urea solution and environmental parameters.

[0028] Specifically, its expected temperature value refers to the optimal temperature of the urea solution within the current adjustment cycle, and the expected density value refers to the optimal density of the urea solution within the current adjustment cycle.

[0029] Specifically, when generating the deviation evaluation value f at the current feedback time node, it includes: f = e1 * Q1 * H1 + e2 * Q2 * H2 + e3 * Q3 * H3; H3 = { a i / θ1) / b i / θ2)] - [a' / b']} 2 ; Where, e1 is the preset first weight coefficient, e2 is the preset second weight coefficient; e3 is the preset third weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; Q3 is the preset third fixed coefficient.

[0030] Specifically, by presetting the first fixed coefficient, the second fixed coefficient and the third fixed coefficient, all parameters in the model are normalized, so that each parameter in the model is within the same value range.

[0031] Specifically, the larger the deviation evaluation value, the greater the deviation degree between the current density - temperature ratio of the urea solution and the optimal state, and the worse the reaction state after urea gasification.

[0032] It can be understood that in the above embodiments, according to the constructed density - temperature ratio model, the optimal corresponding relationship between the urea solution temperature and the urea solution density within a single monitoring cycle is generated, and by periodically collecting relevant data, the ratio of the urea solution temperature and density is adjusted in real time, improving the reaction state after urea liquid gasification and reducing the operation cost of the unit.

[0033] In the preferred embodiment of the present application, when judging whether to generate a primary correction strategy according to the operation deviation value, it includes: Presetting a deviation evaluation value threshold F1; If f < F1, no primary correction strategy is generated at the current feedback time node; If f > F1, multiple initial correction strategies are generated according to the preset correction model; Establish the initial correction strategy sequence C, C=(c1,c2…c i …c n ), where c i is the i-th initial correction strategy; n is the number of initial correction strategies; Generate the first-level correction strategy for the current feedback time node based on the initial correction strategy sequence C.

[0034] Specifically, a deviation evaluation threshold is set based on historical monitoring parameters. When the real-time deviation evaluation value exceeds the deviation evaluation threshold, it indicates that the density and temperature of the current urea solution are poorly matched, seriously affecting the subsequent gasification reaction process. Timely adjustments are required to ensure efficient operation of the unit.

[0035] Specifically, when generating the first-level correction strategy for the current feedback time node, it includes: According to the initial correction strategy sequence C, set c i Modify strategy for goals; Generate the modified return value d of the target modification strategy based on the preset evaluation model; d= β i *j i ]; Among them, r1 is the number of adjustment evaluation indicators; β i is the influencing factor of the i-th adjustment evaluation index; j i is the reference value of the i-th adjustment evaluation index generated based on the target correction strategy; Generate the revised return value of each initial revised strategy in sequence; Establish a modified return value series D, D = (d1, d2…d i …d n ), where d i is the revised return value of the i-th initial revised strategy; Set the maximum value d in the modified return value sequence D max The corresponding initial correction strategy is the first-level correction strategy at the current feedback time node.

[0036] Specifically, a single initial correction strategy includes an adjustment strategy for temperature and an adjustment strategy for density. The temperature or density can be changed alone, or the two can be adjusted in conjunction so that the ratio of the adjusted temperature and density reaches the expected value.

[0037] Specifically, the adjustment evaluation indicators include but are not limited to adjustment cost, probability of temperature fluctuation after adjustment, probability of density fluctuation, gasification effect of urea solution after adjustment and other parameters. The larger the benefit evaluation value, the higher the feasibility of the target correction strategy.

[0038] Specifically, the influencing factors of various regulation evaluation indicators are set according to their influence on the operating status of the unit. The greater the influence, the greater the corresponding influence factor.

[0039] Specifically, when presetting feedback time nodes, it includes: Generate a monitoring evaluation value k for the current adjustment cycle based on the urea demand parameter; k= η i *g i ]; Among them, r2 is the number of monitoring and evaluation indicators; η i is the influencing factor of the i-th monitoring and evaluation indicator; g i Generate the reference value of the i-th monitoring and evaluation indicator based on the urea demand parameter; Establish multiple time intervals based on monitoring and evaluation values; Set the end time node of each time interval as the feedback time node; Get the deviation evaluation value f' of the current feedback time node; A compensation coefficient is generated according to the deviation evaluation value f', and the duration of the next time interval is corrected according to the compensation coefficient.

[0040] Specifically, the monitoring and evaluation indicators include, but are not limited to, the number of historical deviations of the urea solution, the expected environmental fluctuations of the urea solution and other parameters. The larger the monitoring and evaluation value, the greater the possibility of fluctuations in the temperature-density ratio of the urea solution.

[0041] Specifically, the larger the deviation evaluation value is, the smaller the corresponding compensation coefficient is, thereby reducing the duration of a single time interval. The duration of the time interval is dynamically adjusted through the compensation coefficient, thereby improving monitoring efficiency.

[0042] It can be understood that in the above embodiment, by establishing a correction model, multiple initial correction strategies are set based on the real-time urea solution temperature and density parameters, and the best correction strategy is screened according to the optimization model, thereby improving the adjustment efficiency of the ratio of urea solution temperature and density and reducing the labor intensity of the staff.

[0043] Based on another preferred embodiment of a method for regulating and controlling the density and temperature of a urea solution in any of the above preferred embodiments, this preferred embodiment provides a urea solution density and temperature regulating and controlling system, comprising: The central control unit is used to set monitoring points according to equipment parameters. The monitoring points include multiple primary monitoring points and multiple secondary monitoring points. The monitoring unit includes a plurality of monitoring submodules, and the monitoring submodules are arranged at each monitoring point; The monitoring unit is used to collect monitoring data from each monitoring point; Specifically, the monitoring unit is preferably a variety of sensors for collecting real-time temperature parameters and real-time density parameters of the urea solution.

[0044] The central control unit includes: A first processing module is used to set an adjustment period according to a urea demand parameter and generate an expected ratio curve within a monitoring period according to a preset density-temperature ratio model; The second processing module is used to generate an operation deviation value according to a preset feedback time node; The correction module is used to determine whether to generate a first-level correction strategy based on the operation deviation value.

[0045] Specifically, the second processing module is further configured to: Generate the expected temperature value a' and expected density value b' at the current feedback time node according to the expected ratio curve; Obtain the first-level data packet of each first-level monitoring point at the current feedback time node; Generate the temperature fluctuation value H1 of the current feedback time node based on all the first-level data packets; H1= (a i -a') 2 ; Where θ1 is the number of first-level monitoring points; ai is the temperature reference value of the i-th first-level monitoring point at the current feedback time node; Obtain the secondary data packet of each secondary monitoring point at the current feedback time node; Generate the density fluctuation value H2 of the current feedback time node based on all secondary data packets; H2= (b i -b') 2; Wherein, θ2 is the number of secondary monitoring points; bi is the density reference value of the i-th secondary monitoring point at the current feedback time node; Generate the deviation evaluation value f of the current feedback time node; f=e1*Q1*H1+e2*Q2*H2+e3*Q3*H3; H3={[ a i / θ1) / b i / θ2)]-[a' / b']} 2 ; Among them, e1 is the preset first weight coefficient, e2 is the preset second weight coefficient; e3 is the preset third weight coefficient; Q1 is the preset first fixed coefficient; Q2 is the preset second fixed coefficient; Q3 is the preset third fixed coefficient.

[0046] In the preferred embodiment of the embodiment of the present application, the correction module is further configured to: Preset a deviation evaluation value threshold F1; If f < F1, no primary correction strategy is generated at the current feedback time node; If f > F1, generate multiple initial correction strategies according to a preset correction model; Establish an initial correction strategy sequence C, C = (c1, c2…c i …c n ), where c i is the i-th initial correction strategy; n is the number of initial correction strategies; Set c i as the target correction strategy in sequence according to the initial correction strategy sequence C; Generate a correction benefit value d of the target correction strategy according to a preset evaluation model; d = β i *j i ; where r1 is the number of adjustment evaluation indicators; β i is the influence factor of the i-th adjustment evaluation indicator; j i is the reference value of the i-th adjustment evaluation indicator generated based on the target correction strategy; Generate the correction benefit values of each initial correction strategy in sequence; Establish a correction benefit value sequence D, D = (d1, d2…d i …d n ), where d i is the correction benefit value of the i-th initial correction strategy; Set the initial correction strategy corresponding to the maximum value d max in the correction benefit value sequence D as the primary correction strategy at the current feedback time node.

[0047] In the preferred embodiment of the embodiment of the present application, the second processing module is further configured to: Generate a monitoring evaluation value k for the current adjustment period according to the urea demand parameter; k = η i *g i ; where r2 is the number of monitoring evaluation indicators; η i is the influence factor of the i-th monitoring evaluation indicator; g i is the reference value of the i-th monitoring evaluation indicator generated based on the urea demand parameter; Establish multiple time intervals according to the monitoring evaluation value; Set the end time node of each time interval as the feedback time node; Get the deviation evaluation value f' of the current feedback time node; A compensation coefficient is generated according to the deviation evaluation value f', and the duration of the next time interval is corrected according to the compensation coefficient.

[0048] According to the first concept of the present application, the optimal correspondence between the urea solution temperature and the urea solution density within a single monitoring cycle is generated by constructing a density-temperature ratio model, and by periodically collecting relevant data, the ratio of the urea solution temperature and density is adjusted in real time to improve the reaction state of the urea liquid after gasification and reduce the operating cost of the unit.

[0049] According to the second concept of the present application, by establishing a correction model, multiple initial correction strategies are set based on the real-time urea solution temperature and density parameters, and the best correction strategy is screened according to the optimization model, thereby improving the adjustment efficiency of the ratio of urea solution temperature and density and reducing the labor intensity of the staff.

[0050] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and replacements can be made without departing from the technical principles of the present application. These improvements and replacements should also be regarded as the scope of protection of the present application.

Claims

1. A method for regulating and controlling the density and temperature of a urea solution, characterized in that: Including: Setting monitoring points according to equipment parameters, where the monitoring points include multiple primary monitoring points and multiple secondary monitoring points; Setting an adjustment period according to urea demand parameters and generating an expected ratio curve within the monitoring period according to a preset density-temperature ratio model; Generating an operation deviation value according to a preset feedback time node and determining whether to generate a primary correction strategy based on the operation deviation value.

2. The method for regulating and controlling the density and temperature of the urea solution according to claim 1, wherein: When generating an operation deviation value according to a preset feedback time node, it includes: Generating an expected temperature value a' and an expected density value b' at the current feedback time node according to the expected ratio curve; Obtaining primary data packets of each primary monitoring point at the current feedback time node; Generating a temperature fluctuation value H1 at the current feedback time node according to all primary data packets; H1= (has i -has') 2 ; Where, θ1 is the number of primary monitoring points; ai is the temperature reference value of the i-th primary monitoring point at the current feedback time node; Obtaining secondary data packets of each secondary monitoring point at the current feedback time node; Generating a density fluctuation value H2 at the current feedback time node according to all secondary data packets; H2= (b i -b') 2; Where, θ2 is the number of secondary monitoring points; bi is the density reference value of the i-th secondary monitoring point at the current feedback time node; Generating a deviation evaluation value f at the current feedback time node.

3. The method for regulating and controlling the density and temperature of the urea solution according to claim 2, wherein: When generating a deviation evaluation value f at the current feedback time node, it includes: f = e1 * Q1 * H1 + e2 * Q2 * H2 + e3 * Q3 * H3; H3={[ a i / θ1) / b i / θ2)]-[a' / b']} 2 ; Where, e1 is a preset first weight coefficient, e2 is a preset second weight coefficient; e3 is a preset third weight coefficient; Q1 is a preset first fixed coefficient; Q2 is a preset second fixed coefficient; Q3 is a preset third fixed coefficient.

4. The method for regulating and controlling the density and temperature of the urea solution according to claim 2, wherein: When determining whether to generate a primary correction strategy based on the operation deviation value, it includes: Presetting a deviation evaluation value threshold F1; If f < F1, no primary correction strategy is generated at the current feedback time node; If f > F1, generating multiple initial correction strategies according to a preset correction model; Establish the initial correction strategy sequence C, C=(c1,c2…c i …c n ), where c i is the i-th initial correction strategy; n is the number of initial correction strategies; Generating a primary correction strategy at the current feedback time node according to the initial correction strategy sequence C.

5. The method for regulating and controlling the density and temperature of the urea solution according to claim 4, wherein: When generating a primary correction strategy at the current feedback time node, it includes: According to the initial correction strategy sequence C, set c i Modify strategy for goals; Generating a correction benefit value d of the target correction strategy according to a preset evaluation model; d= b i *j i ]; Among them, r1 is the number of adjustment evaluation indicators; β i is the influencing factor of the i-th adjustment evaluation index; j i is the reference value of the i-th adjustment evaluation index generated based on the target correction strategy; Sequentially generating correction benefit values of each initial correction strategy; Establish a modified return value series D, D = (d1, d2…d i …d n ), where d i is the revised return value of the i-th initial revised strategy; Set the maximum value d in the modified return value sequence D max The corresponding initial correction strategy is the first-level correction strategy at the current feedback time node.

6. The method for regulating and controlling the density and temperature of the urea solution according to claim 4, wherein: When presetting a feedback time node, it includes: Generating a monitoring evaluation value k of the current adjustment period according to urea demand parameters; k= or i *g i ]; Among them, r2 is the number of monitoring and evaluation indicators; η i is the influencing factor of the i-th monitoring and evaluation indicator; g i Generate the reference value of the i-th monitoring and evaluation indicator based on the urea demand parameter; Establishing multiple time intervals according to the monitoring evaluation value; Setting the end time node of each time interval as the feedback time node; Obtaining the deviation evaluation value f' at the current feedback time node; Generating a compensation coefficient according to the deviation evaluation value f' and correcting the duration of the next time interval according to the compensation coefficient.

7. A urea solution density and temperature control system, adopting the urea solution density and temperature control method according to any one of claims 1 to 6, characterized in that: Including: A central control unit for setting monitoring points according to equipment parameters, where the monitoring points include multiple primary monitoring points and multiple secondary monitoring points; A monitoring unit including multiple monitoring sub-modules, and the monitoring sub-modules are arranged at each monitoring point; The monitoring unit is used to collect monitoring data of each monitoring point; The central control unit includes: A first processing module for setting an adjustment period according to urea demand parameters and generating an expected ratio curve within the monitoring period according to a preset density-temperature ratio model; The second processing module is used to generate an operation deviation value according to a preset feedback time node; The correction module is used to determine whether to generate a first-level correction strategy according to the operation deviation value.

8. The urea solution density and temperature regulation and control system according to claim 7, characterized in that: The second processing module is further used for: Generating an expected temperature value a' and an expected density value b' at the current feedback time node according to the expected ratio curve; Obtaining the first-level data packets of each first-level monitoring point at the current feedback time node; Generating a temperature fluctuation value H1 at the current feedback time node according to all the first-level data packets; H1= (has i -has') 2 ; Where, θ1 is the number of first-level monitoring points; ai is the temperature reference value of the i-th first-level monitoring point at the current feedback time node; Obtaining the second-level data packets of each second-level monitoring point at the current feedback time node; Generating a density fluctuation value H2 at the current feedback time node according to all the second-level data packets; H2= (b i -b') 2; Where, θ2 is the number of second-level monitoring points; bi is the density reference value of the i-th second-level monitoring point at the current feedback time node; Generating a deviation evaluation value f at the current feedback time node; f = e1 * Q1 * H1 + e2 * Q2 * H2 + e3 * Q3 * H3; H3={[ a i / θ1) / b i / θ2)]-[a' / b']} 2 ; Where, e1 is a preset first weight coefficient, e2 is a preset second weight coefficient; e3 is a preset third weight coefficient; Q1 is a preset first fixed coefficient; Q2 is a preset second fixed coefficient; Q3 is a preset third fixed coefficient.

9. The urea solution density and temperature regulation and control system according to claim 8, characterized in that: The correction module is further used for: Presetting a deviation evaluation value threshold F1; If f < F1, no first-level correction strategy is generated at the current feedback time node; If f > F1, generating multiple initial correction strategies according to a preset correction model; Establish the initial correction strategy sequence C, C=(c1,c2…c i …c n ), where c i is the i-th initial correction strategy; n is the number of initial correction strategies; According to the initial correction strategy sequence C, set c i Modify strategy for goals; Generating a correction benefit value d of the target correction strategy according to a preset evaluation model; d= b i *j i ]; Among them, r1 is the number of adjustment evaluation indicators; β i is the influencing factor of the i-th adjustment evaluation index; j i is the reference value of the i-th adjustment evaluation index generated based on the target correction strategy; Generating the correction benefit values of each initial correction strategy in sequence; Establish a modified return value series D, D = (d1, d2…d i …d n ), where d i is the revised return value of the i-th initial revised strategy; Set the maximum value d in the modified return value sequence D max The corresponding initial correction strategy is the first-level correction strategy at the current feedback time node.

10. The urea solution density and temperature regulation and control system according to claim 9, characterized in that: The second processing module is further used for: Generating a monitoring evaluation value k of the current adjustment period according to the urea demand parameter; k= or i *g i ]; Among them, r2 is the number of monitoring and evaluation indicators; η i is the influencing factor of the i-th monitoring and evaluation indicator; g i Generate the reference value of the i-th monitoring and evaluation indicator based on the urea demand parameter; Establishing multiple time intervals according to the monitoring evaluation value; Setting the end time node of each time interval as the feedback time node; Obtaining a deviation evaluation value f' at the current feedback time node; Generating a compensation coefficient according to the deviation evaluation value f', and correcting the duration of the next time interval according to the compensation coefficient.

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