A multi-parameter coupling-based plasma ignition optimization method and system
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HUANENG QINGDAO THERMAL POWER CO LTD
- Filing Date
- 2026-02-02
- Publication Date
- 2026-06-16
Smart Images
Figure CN122216640A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of plasma ignition technology, and in particular to a plasma ignition optimization method and system based on multi-parameter coupling. Background Technology
[0002] Plasma ignition technology is an important ignition method for modern coal-fired boilers, and its performance directly affects the unit's start-up efficiency and operating economy. In existing technologies, the control of plasma ignition systems largely relies on operator experience, with parameters adjusted independently through trial and error. This method struggles to effectively handle the complex coupling relationships between multiple parameters such as arc power, airflow, and pulverized coal concentration, leading to frequent problems like flame instability and low ignition efficiency.
[0003] In recent years, some studies have attempted to introduce intelligent control algorithms, such as neural networks and fuzzy inference, to build system models. However, these methods generally suffer from drawbacks such as complex model building processes, large training data requirements, and long implementation cycles. Especially when facing operating conditions such as fluctuating coal quality and environmental changes, existing methods lack adaptability, exhibit slow parameter adjustment responses, and cannot meet real-time optimization needs. Furthermore, over-reliance on complex models leads to difficulties in system maintenance, making it challenging for field engineers to understand and intervene in the control process. Summary of the Invention
[0004] The purpose of this application is to provide a plasma ignition optimization method and system based on multi-parameter coupling to solve the above-mentioned technical problems, aiming to improve the control accuracy of plasma ignition and ensure ignition efficiency.
[0005] In some embodiments of this application, by pre-setting a working condition characteristic model and an optimization control model, the corresponding optimization sub-model is dynamically adjusted according to different combustion conditions of the boiler (ambient temperature, coal characteristics, etc.), thereby improving the strong adaptability of the ignition control system to external disturbances.
[0006] In some embodiments of this application, by dividing a single expected ignition cycle into multiple control nodes, the ignition control parameters for the current cycle are recalculated and adjusted at each node based on the actual operating effect of the previous cycle. By performing rolling optimization of the ignition control parameters, performance deviations caused by external disturbances such as coal quality changes and equipment wear are corrected in real time, ensuring the stability and robustness of the system under uncertain environments.
[0007] In some embodiments of this application, a plasma ignition optimization method based on multi-parameter coupling is provided, including:
[0008] An optimal control model is constructed based on the boiler's historical combustion data; Obtain the ignition requirement task and operating condition feature package, and set the first-level optimization model based on the optimization control model and operating condition feature package; Multiple control nodes are set based on the first-level optimization model and ignition requirements, and the ignition control parameters of each control node are set.
[0009] In some embodiments of this application, an optimization control model is constructed, including: Multiple equipment operation indicators are set based on boiler equipment parameters; Multiple state evaluation indicators and various combustion conditions are set based on historical combustion parameters; Establish a combustion condition sequence A, A=(a1, a2…a…) i …a n ), where a i This represents the i-th combustion condition; n is the number of combustion conditions. Based on the combustion condition series A, a is set sequentially. i For the target combustion condition: Generate a historical data package for the target combustion conditions; A disturbance correction strategy for the target combustion condition is generated based on all equipment operating indicators and historical records. The evaluation sub-strategy for setting target combustion conditions is based on all status evaluation indicators and historical data packages; An optimization sub-model for the target combustion condition is set based on the disturbance correction strategy and the evaluation sub-strategy; Optimization sub-models for each combustion condition are constructed sequentially; Generate an optimization control model based on all optimization sub-models.
[0010] In some embodiments of this application, the evaluation sub-strategy for setting the target combustion condition includes: The operating condition evaluation value c for the target combustion condition is generated based on the historical data package; c=[ η i s i ]; Where θ1 is the number of preset working condition characteristic indicators; η i s is the influencing factor of the i-th operating condition characteristic index; i It is a reference value for generating the i-th operating condition characteristic index based on the historical data package; The weighting factors for each state evaluation index in the target combustion condition are generated based on the historical data package. An evaluation sub-strategy for the target combustion condition is generated based on the operating condition evaluation value c and all weighting factors.
[0011] In some embodiments of this application, the disturbance correction strategy for generating the target combustion condition includes: Establish a sequence of equipment operation indicators B, B=(b1,b2…b i …bm ), where b i Let m be the operating index of the i-th device; m is the number of operating indicators. b is set sequentially according to the equipment operation index series B. i Target operating indicators; Based on historical data packages, generate target operating indicators and disturbance thresholds for each device's operating indicators; Establish a disturbance threshold sequence C, C = (c1, c2, ..., c) for the target operating indicators. i …c m ), where c i The threshold value for the disturbance between the target operating index and the operating index of the i-th device; Based on the disturbance threshold sequence C, a correction sub-strategy is generated for the target operating index within the target combustion condition. The correction sub-strategies for the operating indicators of each device within the target combustion condition are generated sequentially. A disturbance correction strategy for the target combustion condition is generated based on all correction sub-strategies.
[0012] In some embodiments of this application, the ignition control parameters of each control node are set, including: Generate the expected ignition cycle based on the ignition requirements; The first-level operating condition values required for the ignition task are generated based on the first-level optimization model; Multiple time intervals are set within the expected ignition cycle based on the primary operating condition value; Establish a time interval sequence T, T=(t1,t2…t) i …t r ), where t i Let be the i-th time interval within the expected ignition cycle; r is the number of time intervals. Set the start time node of each time interval as the control node; A primary control strategy is generated based on the ignition control parameters of the previous time interval of the current control node. Retrieve the status monitoring packets from the previous time interval; The secondary control strategy for the current control node is generated based on the status monitoring package and the primary control strategy; The ignition control parameters for the current control cycle are set according to the secondary control strategy.
[0013] In some embodiments of this application, the generation of a secondary control strategy for the current control node includes: Generate the current state deviation value f of the control node based on the state monitoring package; f=[ μ i Y(i) (d i -d' i ) 2 ; Among them, θ2 is the number of state evaluation indicators; μ i is the weight factor of the i-th state evaluation indicator set according to the first-level optimization model; d i is the reference value of the i-th state evaluation indicator generated according to the state monitoring package; d' i is the standard reference value of the i-th state evaluation indicator set according to the first-level optimization model; Preset state deviation value threshold F1; If f < F1, set the first-level control strategy as the second-level control strategy of the current regulation node; If f > F1, generate a first-level correction instruction, and generate a second-level control strategy according to the first-level correction instruction.
[0014] In some embodiments of the present application, the first-level correction instruction includes: Generate a fluctuation evaluation value of each device operation index at the current regulation node according to the state monitoring package; Set the device operation index corresponding to the maximum value among all the fluctuation evaluation values as the anchor operation index of the current regulation node; Obtain the disturbance amount c' of the anchor operation index; Construct a first-level correction strategy of the anchor operation index at the current regulation node and a sequence of disturbance amount thresholds C1; C1 = (c 11 , c 12 …c 1i …c 1m ), where c i is the disturbance amount threshold between the target anchor operation index and the i-th device operation index; If c' > c 1i , set the correction amount of the i-th device operation index at the current regulation node according to the first-level correction strategy.
[0015] In some embodiments of the present application, a plasma ignition optimization system based on multi-parameter coupling is provided, including: A central control unit for constructing an optimization control model according to the historical combustion data of the boiler; A monitoring unit including multiple monitoring sub-modules, and the monitoring unit is used to obtain the ignition demand task and the working condition feature package; The central control unit includes: A first control module for setting a first-level optimization model according to the optimization control model and the working condition feature package; A second control module for setting multiple regulation nodes according to the first-level optimization model and the ignition demand task, and setting the ignition control parameters of each regulation node.
[0016] In some embodiments of this application, the central control unit further includes: The third control module is used to set multiple equipment operation indicators based on boiler equipment parameters; Multiple state evaluation indicators and various combustion conditions are set based on historical combustion parameters; Establish a combustion condition sequence A, A=(a1, a2…a…) i …a n ), where a i This represents the i-th combustion condition; n is the number of combustion conditions. Based on the combustion condition series A, a is set sequentially. i For the target combustion condition: Generate a historical data package for the target combustion conditions; A disturbance correction strategy for the target combustion condition is generated based on all equipment operating indicators and historical records. The evaluation sub-strategy for setting target combustion conditions is based on all status evaluation indicators and historical data packages; An optimization sub-model for the target combustion condition is set based on the disturbance correction strategy and the evaluation sub-strategy; Optimization sub-models for each combustion condition are constructed sequentially; Generate an optimization control model based on all optimization sub-models.
[0017] In some embodiments of this application, the second control module is further configured to: Generate the expected ignition cycle based on the ignition requirements; The first-level operating condition values required for the ignition task are generated based on the first-level optimization model; Multiple time intervals are set within the expected ignition cycle based on the primary operating condition value; Establish a time interval sequence T, T=(t1,t2…t) i …t r ), where t i Let be the i-th time interval within the expected ignition cycle; r is the number of time intervals. Set the start time node of each time interval as the control node; A primary control strategy is generated based on the ignition control parameters of the previous time interval of the current control node. Retrieve the status monitoring packets from the previous time interval; The secondary control strategy for the current control node is generated based on the status monitoring package and the primary control strategy; The ignition control parameters for the current control cycle are set according to the secondary control strategy.
[0018] Compared with existing technologies, the plasma ignition optimization method and system based on multi-parameter coupling proposed in this application have the following advantages: By pre-setting the operating condition characteristic model and the optimization control model, the corresponding optimization sub-model is dynamically adjusted according to different combustion conditions of the boiler (ambient temperature, coal characteristics), thereby improving the ignition control system's strong adaptability to external disturbances.
[0019] By dividing the single expected ignition cycle into multiple control nodes, and recalculating and adjusting the ignition control parameters for the current cycle at each node based on the actual operating effect of the previous cycle, the system ensures stability and robustness in uncertain environments by performing rolling optimization of the ignition control parameters and correcting performance deviations caused by external disturbances such as coal quality changes and equipment wear in real time. Attached Figure Description
[0020] Figure 1 This is a schematic flowchart of a plasma ignition optimization method based on multi-parameter coupling in a preferred embodiment of this application. Detailed Implementation
[0021] The specific embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The following examples are used to illustrate this application, but are not intended to limit the scope of this application.
[0022] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They 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, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.
[0023] 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 technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.
[0024] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.
[0025] like Figure 1 As shown, a preferred embodiment of this application provides a plasma ignition optimization method based on multi-parameter coupling, comprising: S101: Construct an optimal control model based on the boiler's historical combustion data; S102: Obtain the ignition requirement task and operating condition feature package, and set the first-level optimization model according to the optimization control model and operating condition feature package; S103: Based on the first-level optimization model and ignition requirements, set multiple control nodes and set the ignition control parameters for each control node.
[0026] Specifically, constructing an optimal control model includes: Multiple equipment operation indicators are set based on boiler equipment parameters; Multiple state evaluation indicators and various combustion conditions are set based on historical combustion parameters; Establish a combustion condition sequence A, A=(a1, a2…a…) i …a n ), where a i This represents the i-th combustion condition; n is the number of combustion conditions. Based on the combustion condition series A, a is set sequentially. i For the target combustion condition: Generate a historical data package for the target combustion conditions; A disturbance correction strategy for the target combustion condition is generated based on all equipment operating indicators and historical records. The evaluation sub-strategy for setting target combustion conditions is based on all status evaluation indicators and historical data packages; An optimization sub-model for the target combustion condition is set based on the disturbance correction strategy and the evaluation sub-strategy; Optimization sub-models for each combustion condition are constructed sequentially; Generate an optimization control model based on all optimization sub-models.
[0027] Specifically, the preferred equipment operating parameters in this application are: ignition power, carrier air volume, primary air volume, and pulverized coal feed rate.
[0028] Specifically, the status assessment indicators include, but are not limited to, multiple parameters that can map the plasma ignition effect, such as total ignition power consumption, furnace pressure fluctuation, flame intensity, flame flicker frequency, and minimum stable combustion load. By quantifying each status assessment indicator, the reference values of each indicator are made to fall within the same range. Furthermore, the higher the reference value of each status assessment indicator, the better the current ignition effect.
[0029] Specifically, the historical data package includes historical operating data for various equipment operating indicators and status assessment indicators, as well as historical data on external operating conditions.
[0030] Specifically, by selecting multiple state evaluation indicators to construct evaluation sub-strategies for each combustion condition, the optimization direction under different combustion conditions can be dynamically adjusted.
[0031] It is understood that in the above embodiments, by pre-setting the operating condition characteristic model and the optimization control model, the corresponding optimization sub-model is dynamically adjusted according to different combustion conditions of the boiler (ambient temperature, coal characteristics), thereby improving the strong adaptability of the ignition control system to external disturbances.
[0032] In a preferred embodiment of this application, the evaluation sub-strategy for setting the target combustion condition includes: The operating condition evaluation value c for the target combustion condition is generated based on the historical data package; c=[ η i s i ]; Where θ1 is the number of preset working condition characteristic indicators; η i s is the influencing factor of the i-th operating condition characteristic index; i It is a reference value for generating the i-th operating condition characteristic index based on the historical data package; The weighting factors for each state evaluation index in the target combustion condition are generated based on the historical data package. An evaluation sub-strategy for the target combustion condition is generated based on the operating condition evaluation value c and all weighting factors.
[0033] Specifically, operating condition characteristic indicators include, but are not limited to, parameters affecting plasma ignition quality such as equipment wear, coal quality, ambient temperature, and ambient humidity. By quantifying each operating condition characteristic indicator, the reference values of all indicators are made to fall within the same range. The higher the reference value of each operating condition characteristic indicator, the lower the likelihood of operational fluctuations.
[0034] Specifically, multiple value ranges for each operating condition characteristic index are generated sequentially, and various combustion operating conditions are constructed based on random combinations of all value ranges. Notably, the value ranges of the characteristic indices for any two combustion operating conditions are not entirely the same.
[0035] Specifically, s i It refers to the median of the value range of the i-th operating condition characteristic index in the corresponding target combustion condition.
[0036] Specifically, the influence factors of each operating condition characteristic index can be set according to the degree of interference they cause to the plasma ignition effect. The greater the degree of interference, the larger the value of the corresponding influence factor.
[0037] Specifically, the higher the operating condition evaluation value, the lower the probability of operational fluctuations in the current combustion conditions.
[0038] Specifically, based on the value range of each characteristic index in the target combustion condition, the weighting factors of each state evaluation index are dynamically adjusted to achieve different optimization directions. For example, when the overall combustion effect is stable under conditions of high coal quality, low ambient humidity, and high ambient temperature, the weighting factors of total ignition power consumption and minimum stable combustion load are increased, thus making the optimization direction the direction of reducing the operating power consumption of the plasma ignition system. When the coal quality is low and the ambient humidity is high, the weighting factors of furnace pressure fluctuation, flame intensity, and flame flashing frequency are increased, thus making the optimization direction the direction of improving ignition stability, etc.
[0039] Specifically, the disturbance correction strategy for generating the target combustion condition includes: Establish a sequence of equipment operation indicators B, B=(b1,b2…b i …b m ), where b i Let m be the operating index of the i-th device; m is the number of operating indicators. b is set sequentially according to the equipment operation index series B. i Target operating indicators; Based on historical data packages, generate target operating indicators and disturbance thresholds for each device's operating indicators; Establish a disturbance threshold sequence C, C = (c1, c2, ..., c) for the target operating indicators. i …c m ), where c i The threshold value for the disturbance between the target operating index and the operating index of the i-th device; Based on the disturbance threshold sequence C, a correction sub-strategy is generated for the target operating index within the target combustion condition. The correction sub-strategies for the operating indicators of each device within the target combustion condition are generated sequentially. A disturbance correction strategy for the target combustion condition is generated based on all correction sub-strategies.
[0040] Specifically, the disturbance threshold can be set based on historical parameters. When the disturbance of the target operating index is greater than the disturbance threshold of the current equipment operating index, it indicates that the fluctuation of the target operating index has interfered with the operating status of the current equipment operating index. At the same time, the current equipment operating index needs to be adjusted in a coordinated manner to improve the overall combustion efficiency of the boiler.
[0041] It is understood that in the above embodiments, by setting disturbance correction strategies for the operating indicators of each device, the linkage adjustment between the operating indicators of different devices can be realized, thereby achieving overall collaborative optimization of the system.
[0042] In a preferred embodiment of this application, the ignition control parameters for each control node are set, including: Generate the expected ignition cycle based on the ignition requirements; The first-level operating condition values required for the ignition task are generated based on the first-level optimization model; Multiple time intervals are set within the expected ignition cycle based on the primary operating condition value; Establish a time interval sequence T, T=(t1,t2…t) i …t r ), where t i Let be the i-th time interval within the expected ignition cycle; r is the number of time intervals. Set the start time node of each time interval as the control node; A primary control strategy is generated based on the ignition control parameters of the previous time interval of the current control node. Retrieve the status monitoring packets from the previous time interval; The secondary control strategy for the current control node is generated based on the status monitoring package and the primary control strategy; The ignition control parameters for the current control cycle are set according to the secondary control strategy.
[0043] Specifically, the combustion condition corresponding to the current operating condition is determined based on the reference values of each operating condition characteristic index in the obtained operating condition characteristic package, and the optimization sub-model of the corresponding combustion condition in the judgment result is set as the first-level optimization model.
[0044] Specifically, the working condition evaluation value within the evaluation sub-strategy in the first-level optimization model is set as the first-level working condition value. Since a smaller first-level working condition value corresponds to a longer duration of a single time interval, the mapping relationship between the two can be set based on historical parameters.
[0045] Specifically, the expected ignition cycle (i.e., the time from the start of the ignition task to the attainment of a stable combustion state in the boiler) is generated by analyzing the ignition demand task.
[0046] In the preferred embodiment of the embodiment of the present application, generating a secondary control strategy for the current regulation node includes: Generating a state deviation value f of the current regulation node according to the state monitoring packet; f = μ i Y(i) (d i - d' i ) 2 ; Where θ2 is the number of state evaluation indexes; μ i is the weight factor of the i-th state evaluation index set according to the first-level optimization model; d i is the reference value of the i-th state evaluation index generated according to the state monitoring packet; d' i is the standard reference value of the i-th state evaluation index set according to the first-level optimization model; Presetting a state deviation value threshold F1; If f < F1, setting the first-level control strategy as the secondary control strategy of the current regulation node; If f > F1, generating a first-level correction instruction and generating a secondary control strategy according to the first-level correction instruction.
[0047] Specifically, the state deviation value threshold can be set according to historical parameters. When the state deviation value is greater than the preset state deviation value threshold, it indicates that the plasma ignition system did not reach the expected ignition efficiency in the previous time interval, and it is necessary to optimize and correct the control parameters of the operating indexes of each device in time through the first-level correction instruction.
[0048] Specifically, the standard reference value refers to the reference value corresponding to the minimum operating requirements that the operating indexes of each device need to reach in this combustion condition (which can be set according to the historical parameters of the combustion condition corresponding to the first-level optimization model).
[0049] Specifically, the first-level correction instruction includes: Generating a fluctuation evaluation value of the operating indexes of each device at the current regulation node according to the state monitoring packet; Setting the operating index corresponding to the maximum value among all the fluctuation evaluation values as the anchored operating index of the current regulation node; Obtaining the disturbance amount c' of the anchored operating index; Constructing a first-level correction strategy of the anchored operating index at the current regulation node and a disturbance amount threshold sequence C1; C1 = (c 11 , c 12 … c 1i … c 1m ), where c iThe threshold value for the disturbance of the target operating index and the operating index of the i-th device is used to anchor the target; If c'>c 1i The correction amount of the i-th equipment operation index at the current control node is set according to the first-level correction strategy.
[0050] Specifically, a corresponding fluctuation evaluation value is set based on the ratio between the fluctuation of the current equipment operating index in the previous time interval and its corresponding operating range. The larger the ratio, the larger the corresponding fluctuation evaluation value. The mapping relationship between the two can be set based on historical parameters.
[0051] Specifically, the disturbance is the fluctuation of the anchoring index within the previous time interval.
[0052] Specifically, the correction sub-strategy of anchoring the operating index in the first-level optimization model is set as the first-level correction strategy.
[0053] It is understood that in the above embodiments, by dividing multiple control nodes within a single expected ignition cycle, and recalculating and adjusting the ignition control parameters of the current cycle at each node based on the actual operating effect of the previous cycle, the performance deviation caused by external disturbances such as coal quality changes and equipment wear is corrected in real time through rolling optimization of the ignition control parameters, thus ensuring the stability and robustness of the system under uncertain environments.
[0054] In another preferred embodiment of the plasma ignition optimization method based on multi-parameter coupling based on any of the above preferred embodiments, this preferred embodiment provides a plasma ignition optimization system based on multi-parameter coupling, comprising: The central control unit is used to build an optimal control model based on the boiler's historical combustion data; The monitoring unit includes multiple monitoring sub-modules. The monitoring unit is used to acquire ignition requirement tasks and operating condition characteristic packages. The central control unit includes: The first control module is used to set the first-level optimization model based on the optimization control model and the operating condition feature package. The second control module is used to set multiple control nodes based on the first-level optimization model and ignition requirements, and to set the ignition control parameters for each control node.
[0055] In a preferred embodiment of this application, the central control unit further includes: The third control module is used to set multiple equipment operation indicators based on boiler equipment parameters; Multiple state evaluation indicators and various combustion conditions are set based on historical combustion parameters; Establish a combustion condition sequence A, A=(a1, a2…a…) i …a n ), where ai This represents the i-th combustion condition; n is the number of combustion conditions. Based on the combustion condition series A, a is set sequentially. i For the target combustion condition: Generate a historical data package for the target combustion conditions; A disturbance correction strategy for the target combustion condition is generated based on all equipment operating indicators and historical records. The evaluation sub-strategy for setting target combustion conditions is based on all status evaluation indicators and historical data packages; An optimization sub-model for the target combustion condition is set based on the disturbance correction strategy and the evaluation sub-strategy; Optimization sub-models for each combustion condition are constructed sequentially; Generate an optimization control model based on all optimization sub-models.
[0056] In a preferred embodiment of this application, the second control module is further configured to: Generate the expected ignition cycle based on the ignition requirements; The first-level operating condition values required for the ignition task are generated based on the first-level optimization model; Multiple time intervals are set within the expected ignition cycle based on the primary operating condition value; Establish a time interval sequence T, T=(t1,t2…t) i …t r ), where t i Let be the i-th time interval within the expected ignition cycle; r is the number of time intervals. Set the start time node of each time interval as the control node; A primary control strategy is generated based on the ignition control parameters of the previous time interval of the current control node. Retrieve the status monitoring packets from the previous time interval; The secondary control strategy for the current control node is generated based on the status monitoring package and the primary control strategy; The ignition control parameters for the current control cycle are set according to the secondary control strategy.
[0057] According to the first concept of this application, by pre-setting the operating condition characteristic model and the optimization control model, the corresponding optimization sub-model is dynamically adjusted according to different combustion conditions of the boiler (ambient temperature, coal characteristics), thereby improving the strong adaptability of the ignition control system to external disturbances.
[0058] According to the second concept of this application, by dividing a single expected ignition cycle into multiple control nodes, and recalculating and adjusting the ignition control parameters of the current cycle at each node based on the actual operating effect of the previous cycle, the performance deviation caused by external disturbances such as coal quality changes and equipment wear is corrected in real time through rolling optimization of the ignition control parameters, thus ensuring the stability and robustness of the system under uncertain environments.
[0059] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and substitutions can be made without departing from the technical principles of this application, and these improvements and substitutions should also be considered within the scope of protection of this application.
Claims
1. A plasma ignition optimization method based on multi-parameter coupling, characterized in that, Comprising: Construct an optimization control model based on the historical combustion data of the boiler; Obtain the ignition demand task and the working condition characteristic package, and set the primary optimization model according to the optimization control model and the working condition characteristic package; Set multiple regulation nodes according to the primary optimization model and the ignition demand task, and set the ignition control parameters for each regulation node.
2. The plasma ignition optimization method based on multi-parameter coupling as described in claim 1, characterized in that, Construct an optimization control model, including: Set multiple equipment operation indexes according to the boiler equipment parameters; Set multiple state evaluation indexes and multiple combustion working conditions according to the historical combustion parameters; Establish a combustion condition sequence A, A=(a1, a2…a…) i …a n ), where a i This represents the i-th combustion condition; n is the number of combustion conditions. Based on the combustion condition series A, a is set sequentially. i For the target combustion condition: Generate a historical record package of the target combustion working condition; Generate a disturbance correction strategy for the target combustion working condition according to all the equipment operation indexes and the historical record package; Set an evaluation sub-strategy for the target combustion working condition according to all the state evaluation indexes and the historical record package; Set an optimization sub-model for the target combustion working condition according to the disturbance correction strategy and the evaluation sub-strategy; Construct the optimization sub-models for each combustion working condition in sequence; Generate an optimization control model according to all the optimization sub-models.
3. The plasma ignition optimization method based on multi-parameter coupling as described in claim 2, characterized in that, Set an evaluation sub-strategy for the target combustion working condition, including: Generate a working condition evaluation value c for the target combustion working condition according to the historical record package; c=[ or i s i ]; Where θ1 is the number of preset working condition characteristic indicators; η i s is the influencing factor of the i-th operating condition characteristic index; i It is a reference value for generating the i-th operating condition characteristic index based on the historical data package; Generate the weight factors of each state evaluation index in the target combustion working condition according to the historical record package; Generate an evaluation sub-strategy for the target combustion working condition according to the working condition evaluation value c and all the weight factors.
4. The plasma ignition optimization method based on multi-parameter coupling as described in claim 3, characterized in that, Generate a disturbance correction strategy for the target combustion working condition, including: Establish a sequence of equipment operation indicators B, B=(b1,b2…b i …b m ), where b i Let m be the operating index of the i-th device; m is the number of operating indicators. b is set sequentially according to the equipment operation index series B. i Target operating indicators; Generate the disturbance threshold values between the target operation index and each equipment operation index according to the historical record package; Establish a disturbance threshold sequence C, C = (c1, c2, ..., c) for the target operating indicators. i …c m ), where c i The threshold value for the disturbance between the target operating index and the operating index of the i-th device; Generate a correction sub-strategy for the target operation index within the target combustion working condition according to the disturbance threshold value sequence C; Generate the correction sub-strategies for each equipment operation index within the target combustion working condition in sequence; Generate a disturbance correction strategy for the target combustion working condition according to all the correction sub-strategies.
5. The plasma ignition optimization method based on multi-parameter coupling as described in claim 4, characterized in that, Set the ignition control parameters for each regulation node, including: Generate an expected ignition cycle according to the ignition demand task; Generate a primary working condition value required for the ignition task according to the primary optimization model; Set multiple time intervals within the expected ignition cycle according to the primary working condition value; Establish a time interval sequence T, T=(t1,t2…t) i …t r ), where t i Let be the i-th time interval within the expected ignition cycle; r is the number of time intervals. Set the start time node of each time interval as a regulation node; Generate a primary control strategy according to the ignition control parameters of the previous time interval of the current regulation node; Obtain the state monitoring package of the previous time interval; Generate a secondary control strategy for the current regulation node according to the state monitoring package and the primary control strategy; Set the ignition control parameters for the current regulation cycle according to the secondary control strategy.
6. The plasma ignition optimization method based on multi-parameter coupling as described in claim 5, characterized in that, Generate a secondary control strategy for the current regulation node, including: Generate a state deviation value f for the current regulation node according to the state monitoring package; f=[ μ i Y(i) (d i -d' i ) 2 ]; Where θ2 represents the number of state assessment indicators; μ i It is the weight factor of the i-th state evaluation index set according to the first-level optimization model; d i It is a reference value for generating the i-th state evaluation index based on the state monitoring package; d' i It is a standard reference value for setting the i-th state evaluation index based on the first-level optimization model; Preset a state deviation value threshold F1; If f < F1, set the primary control strategy as the secondary control strategy for the current regulation node; If f > F1, generate a primary correction instruction, and generate a secondary control strategy according to the primary correction instruction.
7. The plasma ignition optimization method based on multi-parameter coupling as described in claim 6, characterized in that, The primary correction instruction includes: Generate a fluctuation evaluation value of each equipment operation index at the current regulation node according to the state monitoring package; Set the equipment operation index corresponding to the maximum value among all the fluctuation evaluation values as the anchored operation index at the current regulation node; Obtain the disturbance amount c' of the anchored operation index; Construct a primary correction strategy and a disturbance threshold value sequence C1 of the anchored operation index at the current regulation node; C1 = (c 11 c 12 …c 1i …c 1m ), where c i The threshold value for the disturbance of the target operating index and the operating index of the i-th device is used to anchor the target; If c'>c 1i The correction amount of the i-th equipment operation index at the current control node is set according to the first-level correction strategy.
8. A plasma ignition optimization system based on multi-parameter coupling, employing the plasma ignition optimization method based on multi-parameter coupling as described in any one of claims 1-7, characterized in that, Including: The central control unit is used to build an optimal control model based on the boiler's historical combustion data; The monitoring unit includes multiple monitoring sub-modules, and the monitoring unit is used to acquire ignition requirement tasks and operating condition feature packages; The central control unit includes: The first control module is used to set the first-level optimization model based on the optimization control model and the operating condition feature package. The second control module is used to set multiple control nodes based on the first-level optimization model and ignition requirements, and to set the ignition control parameters for each control node.
9. The plasma ignition optimization system based on multi-parameter coupling as described in claim 8, characterized in that, The central control unit also includes: The third control module is used to set multiple equipment operation indicators based on boiler equipment parameters; Multiple state evaluation indicators and various combustion conditions are set based on historical combustion parameters; Establish a combustion condition sequence A, A=(a1, a2…a…) i …a n ), where a i This represents the i-th combustion condition; n is the number of combustion conditions. Based on the combustion condition series A, a is set sequentially. i For the target combustion condition: Generate a historical data package for the target combustion conditions; A disturbance correction strategy for the target combustion condition is generated based on all equipment operating indicators and historical records. The evaluation sub-strategy for setting target combustion conditions is based on all status evaluation indicators and historical data packages; An optimization sub-model for the target combustion condition is set based on the disturbance correction strategy and the evaluation sub-strategy; Optimization sub-models for each combustion condition are constructed sequentially; Generate an optimization control model based on all optimization sub-models.
10. The plasma ignition optimization system based on multi-parameter coupling as described in claim 9, characterized in that, The second control module is also used for: Generate the expected ignition cycle based on the ignition requirements; The first-level operating condition values required for the ignition task are generated based on the first-level optimization model; Multiple time intervals are set within the expected ignition cycle based on the primary operating condition value; Establish a time interval sequence T, T=(t1,t2…t) i …t r ), where t i Let be the i-th time interval within the expected ignition cycle; r is the number of time intervals. Set the start time node of each time interval as the control node; A primary control strategy is generated based on the ignition control parameters of the previous time interval of the current control node. Retrieve the status monitoring packets from the previous time interval; The secondary control strategy for the current control node is generated based on the status monitoring package and the primary control strategy; The ignition control parameters for the current control cycle are set according to the secondary control strategy.