Sludge incineration unit multi-working condition adaptive modeling and operation parameter intelligent regulation method

Abstract

The present application relates to the technical field of operation control, and particularly relates to a sludge incineration unit multi-working condition adaptive modeling and operation parameter intelligent regulation and control method, which comprises the following steps: constructing a full-process mechanism model of the sludge incineration unit based on the principles of mass conservation, energy conservation and momentum conservation, and constructing a multi-working condition condition space containing unit operation state parameters, fuel characteristic parameters and external operation environment parameters; performing steady-state simulation and transient-state simulation on the unit working condition switching process under the multi-working condition conditions, and obtaining continuous time sequence change data of the unit operation parameters; analyzing the corresponding relationship between the operation parameters and the working condition changes based on the data, adaptively processing the operation parameters in combination with the unit operation control logic, generating an operation parameter regulation and control scheme corresponding to the current working condition condition, and performing simulation calculation and verification on the regulation and control scheme in the full-process mechanism model, and outputting the operation parameter regulation and control result, so as to realize the modeling and regulation and control of the unit operation parameters under the multi-working condition conditions.

Description

Technical Field

[0001] This invention relates to the field of operation control technology, and in particular to a method for multi-condition adaptive modeling and intelligent control of operating parameters for sludge incinerator units. Background Technology

[0002] As an important technical means for urban sludge treatment and resource utilization, sludge incineration units involve multiple physical processes such as material conversion, energy transfer, and working fluid flow during operation. The units typically maintain stable operation by adjusting key operating parameters through an operation control system. In existing technologies, mechanistic models are usually used to model the unit's operating process in order to analyze the unit's operating status or assist in operation control. These mechanistic models are mostly based on fundamental principles such as mass conservation and energy conservation, describing the unit's operating process and serving as a basic tool for operation analysis or simulation. In existing technologies, there is often a lack of unified correspondence between the model parameters in the mechanistic model and the control parameters used in the actual operation control system of the unit. This makes it difficult for the mechanistic model to directly reflect the unit's operation control logic at the parameter level, resulting in insufficient adaptability when using the mechanistic model for operation analysis or operation control. Summary of the Invention

[0003] To overcome the above shortcomings, this invention provides a method for multi-condition adaptive modeling and intelligent control of operating parameters for sludge incineration units. It aims to improve the problem that mechanistic models cannot directly reflect the unit's operation control logic at the parameter level, thus resulting in insufficient adaptability when using mechanistic models for operation analysis or operation control.

[0004] This invention provides the following technical solution: a method for adaptive modeling and intelligent control of operating parameters for sludge incinerator units under multiple operating conditions, comprising the following steps: S1. Based on the principles of conservation of mass, energy, and momentum, construct a full-process mechanism model for sludge incineration units; S2. Construct a multi-condition space for the sludge incineration unit, and use the unit's operating status parameters, fuel characteristic parameters, and external operating environment parameters as the operating condition inputs and boundary conditions for the whole process mechanism model. S3. In the multi-condition space, based on the whole process mechanism model, steady-state simulation calculation and transient simulation calculation are performed on the operation process of the sludge incineration unit during the operation condition switching process to obtain continuous time-series change data of the unit's operating parameters. S4. Based on continuous time-series change data, analyze the relationship between the unit's operating parameters under different operating conditions, and form a description of the relationship between the operating parameters and the changes in operating conditions; S5. Based on the description of the relationship between operating parameters and combined with the unit operation control logic, adaptive processing of the unit operating parameters is performed to generate an operating parameter control scheme corresponding to the current operating conditions. S6. Simulate and calculate the operation parameter control scheme in the whole process mechanism model, and output the operation parameter control results.

[0005] By adopting the above technical solution, the parameter mapping relationship corresponding to the unit operation control logic is introduced in the process of constructing the whole process mechanism model, and the operating parameters are analyzed and controlled based on the mechanism model under multiple operating conditions. This enables the mechanism model to reflect the actual operation control logic of the unit at the parameter level, thereby solving the problem that the mechanism model and the operation control parameters are difficult to correspond uniformly in the existing technology, resulting in insufficient adaptability of the model in operation analysis or operation control.

[0006] Preferably, in S1, the full-process mechanism model for constructing the sludge incineration unit includes: A material balance model for the unit's material input, output, and conversion processes is established based on the principle of mass conservation. An energy balance model is established based on the principle of energy conservation, considering the energy input, output, and conversion relationships during unit operation. A flow model is established based on the principle of momentum conservation to determine the relationship between the working fluid flow process and pressure changes in the unit. The material balance model, energy balance model, and flow model are coupled to obtain the full-process mechanism model of the sludge incineration unit.

[0007] Preferably, in S1, the full-process mechanism model for constructing the sludge incineration unit further includes: Obtain the control parameters and their corresponding control variables used in the unit's operation control logic; Establish parameter mapping relationships between control variables and corresponding model parameters in the whole-process mechanism model; Based on the parameter mapping relationship, the model parameters in the whole process mechanism model are configured so that the model parameters and control logic parameters correspond in terms of parameter type and value range.

[0008] Preferably, in S2, the multi-condition space for constructing the sludge incinerator unit includes: The operating status parameters that characterize the operating status of the sludge incineration unit, the fuel characteristic parameters that characterize the fuel characteristics, and the external operating environment parameters that characterize the external operating environment are classified and managed. Based on the classified parameters, a working condition space containing multiple sets of parameter combinations is constructed. The working condition space is configured as a unified model input set into the full-process mechanism model.

[0009] Preferably, in S2, the multi-condition space for constructing the sludge incinerator unit further includes: The different working conditions in the multi-working-condition space are numbered, and a corresponding parameter set is established for each working condition. Based on the changes in the unit's operating status, select the operating conditions corresponding to the current operating status from the parameter set; The selected operating conditions are loaded into the full-process mechanism model.

[0010] Preferably, in S3, the steady-state simulation calculation and transient simulation calculation of the operation process of the sludge incinerator unit during the switching of operating conditions include: Before switching operating conditions, steady-state simulation calculations are performed on the unit's operation process under the current operating conditions based on the full-process mechanism model to obtain the corresponding steady-state initial parameters. During the switching of operating conditions, the steady-state initial parameters are used as the initial conditions to perform transient simulation calculations on the unit operation process and obtain the continuous time-series change data of the unit operating parameters during the switching of operating conditions.

[0011] Preferably, in S4, the analysis of the variation relationship of unit operating parameters under different operating conditions based on continuous time-series variation data includes: The operating conditions are identified for continuously changing time-series data, and the unit operating parameters are associated with the corresponding operating conditions. Under the same or similar operating conditions, the time-series variation data of the unit's operating parameters are collected and processed; Based on the aggregated time-series change data, the corresponding relationship between the unit's operating parameters and the changes in operating conditions is determined, forming a description of the operating parameter relationship.

[0012] Preferably, in S4, the analysis of the variation relationship of the unit operating parameters under different operating conditions further includes: Based on operating condition identification information, the unit operating parameters in continuously time-series changing data are grouped and processed. Within each operating condition group, the time-series variation characteristics of the unit's operating parameters are compared and analyzed. Based on the comparative analysis results, the unit operating parameters that correspond to changes in operating conditions were selected and included in the operating parameter relationship description.

[0013] Preferably, in S5, the adaptive processing of the unit operating parameters includes: Based on the description of the relationship between operating parameters, determine the adjustment range of operating parameters corresponding to the current operating conditions; By combining the unit operation control logic, the operating parameters within the adjustment range are constrained to obtain a set of candidate operating parameters; Based on the set of candidate operating parameters, an operating parameter control scheme corresponding to the current operating conditions is generated.

[0014] Preferably, in S6, the simulation calculation of the operating parameter control scheme in the whole process mechanism model and the output of the operating parameter control results include: The operating parameter control scheme is configured as an input parameter into the full-process mechanism model; Based on the full-process mechanism model, the configured operation parameter control scheme is simulated and calculated to obtain the corresponding unit operation parameter simulation results. Consistency verification is performed on the simulation results of unit operating parameters; After passing the consistency check, the results of the operation parameter adjustment are output.

[0015] The present invention has the following beneficial effects: 1. In this invention, by constructing a full-process mechanism model based on the conservation of mass, energy and momentum, and introducing parameter mapping relationships corresponding to the unit operation control logic into the model, the unity of the unit operation mechanism model and the operation control logic at the parameter level is realized, solving the problem that the mechanism model and the actual operation control parameters are difficult to correspond consistently.

[0016] 2. In this invention, by constructing a multi-condition space that includes operating status parameters, fuel characteristic parameters and external operating environment parameters, and by switching simulations of different operating conditions in the same full-process mechanism model, a unified modeling and continuous description of multiple operating conditions of sludge incinerator units is realized, solving the problem of needing to model separately under different operating conditions or the difficulty in switching models.

[0017] 3. In this invention, steady-state simulation calculation and transient simulation calculation are connected during the switching of operating conditions, and the correspondence between operating parameters and changes in operating conditions is established based on the continuous time-series change data obtained during the switching of operating conditions. Then, an operating parameter control scheme corresponding to the current operating conditions is generated and simulated and verified in the model. This realizes the generation and verification of the operating condition association of the operating parameter control scheme and solves the problem of lack of systematic operating condition basis for operating parameter control. Attached Figure Description

[0018] Figure 1 This is a flowchart of the multi-condition adaptive modeling and intelligent control method for operating parameters of sludge incinerator units proposed in this invention. Detailed Implementation

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] In the first embodiment of the present invention, the present invention provides a method for multi-condition adaptive modeling and intelligent control of operating parameters of sludge incinerator units, such as... Figure 1 As shown, it includes the following steps: S1. Based on the principles of conservation of mass, energy, and momentum, construct a full-process mechanism model for sludge incineration units; Furthermore, in S1, the construction of the full-process mechanism model of the sludge incineration unit includes: A material balance model for the unit's material input, output, and conversion processes is established based on the principle of mass conservation. An energy balance model is established based on the principle of energy conservation, considering the energy input, output, and conversion relationships during unit operation. A flow model is established based on the principle of momentum conservation to determine the relationship between the working fluid flow process and pressure changes in the unit. By coupling the material balance model, energy balance model, and flow model, a full-process mechanism model of the sludge incineration unit is obtained.

[0021] Furthermore, in S1, the construction of the full-process mechanism model of the sludge incineration unit also includes: Obtain the control parameters and their corresponding control variables used in the unit's operation control logic; Establish parameter mapping relationships between control variables and corresponding model parameters in the whole-process mechanism model; Based on the parameter mapping relationship, the model parameters in the whole process mechanism model are configured so that the model parameters and control logic parameters correspond in terms of parameter type and value range.

[0022] Specifically, the full-process mechanism model of the sludge incineration unit is established based on the systematic analysis of the process flow, equipment structure and operation mechanism of the sludge incineration unit. The model is based on the laws of conservation of mass, energy and momentum, and performs unified modeling of physical processes such as material conversion, energy transfer and working fluid flow during the operation of the sludge incineration unit, so as to form a mechanism description that can reflect the overall operating status of the unit. In the specific implementation process, the material input, output, and transformation relationships involved in the operation of the sludge incinerator unit are first modeled based on the principle of mass conservation. Material input may include sludge entering the incineration system, auxiliary fuel, and air or other media participating in the reaction. Material output may include solid residue, flue gas, and other discharged materials generated after incineration. By describing the material conservation relationship within any control volume, the following mass conservation relationship can be used for modeling: ; in, This indicates the total mass of materials within the body. This indicates the mass flow rate of the material entering the control system. This indicates the mass flow rate of material leaving the control volume. Representing time, a material balance model of the unit's materials changing with operating status is established based on the above relationships; Based on the principle of energy conservation, the energy input, output, and conversion relationships during the operation of the sludge incinerator unit are modeled. Energy input can include the chemical energy input of sludge and auxiliary fuel, and energy output can include effective output energy and energy carried away through flue gas, residue, etc. The energy changes of the control volume can be described by the following energy conservation relationship for modeling: ; in, It indicates the control of the body's total energy. Indicates the input heat flow rate. Indicates the output heat flow rate. Indicates the input power. This represents the output power. An energy balance model for energy transfer and conversion during unit operation is established based on the above energy balance relationship. In the specific implementation process, the flow state of the working fluid during the operation of the sludge incinerator unit is modeled based on the principle of momentum conservation. The working fluid may include flue gas, steam, or other media flowing in the system. By describing the pressure changes and flow velocity changes of the fluid in the pipes or equipment, the following momentum conservation relationship can be used for modeling: ; in, Indicates the density of the working fluid. Indicates the working fluid flow rate. This represents the resultant force acting on the control body. Based on the above relationship, a flow model reflecting the characteristics of working fluid flow and pressure change is established to describe the changes in fluid state under different operating conditions of the unit. The established material balance model, energy balance model and flow model are coupled under a unified time scale. By introducing shared variables into the models, the models are interconnected in calculation. Material changes, energy changes and flow states are solved simultaneously within the same calculation framework, thereby constructing a full-process mechanism model covering the entire operation of the sludge incineration unit, which is used to describe the overall operation mechanism of the unit under different operating conditions. After completing the basic structure construction of the full-process mechanism model, the model parameters are further configured by combining the control logic in the actual operation of the sludge incineration unit. First, the control parameters and their corresponding control variables used in the unit operation control logic are obtained. The control parameters may include set values, limit values ​​or constraint parameters that reflect the unit operation adjustment needs, and the control variables may include the adjustment amount related to the actual equipment operating status. Based on the correspondence between control variables and the physical operating state of the unit, a parameter mapping relationship is established between the control variables and the corresponding model parameters in the whole process mechanism model. The parameter mapping relationship is used to indicate the correspondence between the control logic parameters and the mechanism model parameters, so that the model parameters can reflect the changes in the operating state of the unit under the control logic. Based on the established parameter mapping relationship, the model parameters in the full-process mechanism model are configured to ensure that the model parameters correspond to the control parameters in the unit operation control logic in terms of parameter type and value range. This ensures that the constructed full-process mechanism model is consistent with the actual operation control logic of the unit at the parameter level, providing a foundation for subsequent multi-condition simulation calculations and operation parameter regulation based on the model.

[0023] S2. Construct a multi-condition space for the sludge incineration unit, and use the unit's operating status parameters, fuel characteristic parameters, and external operating environment parameters as the operating condition inputs and boundary conditions for the whole process mechanism model. Furthermore, in S2, the multi-condition space for constructing the sludge incineration unit includes: The operating status parameters that characterize the operating status of the sludge incineration unit, the fuel characteristic parameters that characterize the fuel characteristics, and the external operating environment parameters that characterize the external operating environment are classified and managed. Based on the classified parameters, a working condition space containing multiple sets of parameter combinations is constructed. The working condition space is configured as a unified model input set into the full-process mechanism model.

[0024] Furthermore, in S2, the multi-condition space for constructing the sludge incineration unit also includes: The different working conditions in the multi-working-condition space are numbered, and a corresponding parameter set is established for each working condition. Based on the changes in the unit's operating status, select the operating conditions corresponding to the current operating status from the parameter set; The selected operating conditions are loaded into the full-process mechanism model.

[0025] Specifically, the multi-condition space of the sludge incineration unit is constructed based on the analysis of the operating condition change characteristics during the unit's operation. This multi-condition space is used to uniformly describe the unit's operation under different operating states, different fuel conditions, and different external operating environments, serving as the operating condition input and boundary conditions for the full-process mechanism model. In the specific implementation process, the operating status parameters reflecting the operating status of the sludge incineration unit, the fuel characteristic parameters reflecting the differences in fuel properties, and the external operating environment parameters reflecting changes in external conditions are first classified and managed. Among them, the operating status parameters may include parameters related to the unit load, operating stage, or adjustment status; the fuel characteristic parameters may include parameters related to sludge composition, moisture, or calorific value; and the external operating environment parameters may include parameters related to ambient temperature, ambient pressure, or external supply conditions. By classifying and managing different types of parameters, the structure of each type of parameter is clearly defined. After completing parameter classification and management, the various parameters are combined according to a unified data structure to construct a condition space containing multiple sets of parameter combinations. Each set of parameter combinations describes a possible unit operating condition. To facilitate unified processing in the model, the multi-condition space can be represented as a set of parameters consisting of multiple condition vectors. For example, a single operating condition can be represented as a parameter vector. ; in, Represents a vector of conditions for a certain operating condition. Indicates the first Each operating condition parameter can be derived from operating status parameters, fuel characteristic parameters, or external operating environment parameters. By constructing multiple different operating condition vectors, an operating condition space covering various operating conditions is formed. The constructed operating condition space is configured as a unified model input set into the full-process mechanism model, so that the mechanism model can load the corresponding parameter values ​​according to different operating condition vectors when performing calculations, thereby describing the changes in the operating state of the unit under multiple operating conditions under the same model structure. To facilitate the management and retrieval of the multi-condition space, different conditions in the condition space are numbered, and a corresponding parameter set is established for each condition. Each parameter set corresponds one-to-one with a condition number and is used to store all parameter information under that condition. During unit operation, based on changes in the unit's operating status, operating conditions that match the current operating status are selected from the established parameter set. This selection process can be based on the current values ​​of the operating status parameters to determine the operating condition number corresponding to the current operating status. After determining the target operating condition, the parameter set corresponding to the operating condition number is loaded into the full-process mechanism model, so that the mechanism model uses the operating condition as the input and boundary conditions in the subsequent calculation process, thereby realizing the modeling and simulation calculation of the operating condition switching of the unit under different operating states. Through the above methods, the system construction, unified management and dynamic calling of sludge incineration units under multiple operating conditions are realized, enabling the full-process mechanism model to be calculated under various operating conditions, providing basic support for subsequent simulation analysis and operation parameter control based on multiple operating conditions.

[0026] S3. In the multi-condition space, based on the whole process mechanism model, steady-state simulation calculation and transient simulation calculation are performed on the operation process of the sludge incineration unit during the operation condition switching process to obtain continuous time-series change data of the unit's operating parameters. Furthermore, in S3, steady-state and transient simulation calculations are performed on the operation of the sludge incinerator unit during the switching of operating conditions, including: Before switching operating conditions, steady-state simulation calculations are performed on the unit's operation process under the current operating conditions based on the full-process mechanism model to obtain the corresponding steady-state initial parameters. During the switching of operating conditions, the steady-state initial parameters are used as the initial conditions to perform transient simulation calculations on the unit operation process and obtain the continuous time-series change data of the unit operating parameters during the switching of operating conditions.

[0027] Specifically, steady-state simulation calculations and transient simulation calculations are carried out on the basis of the constructed multi-condition space. During operation, the current condition is first determined from the multi-condition space, and the current condition is used as the input and boundary conditions of the whole process mechanism model, so that the whole process mechanism model can reflect the material, energy and working fluid flow state of the unit under the condition within a unified calculation framework. In the specific implementation process, before the operating condition switch, steady-state simulation calculations are performed on the unit operation process under the current operating conditions. The steady-state simulation calculations are used to solve the steady-state solution of the unit's operating state under the current operating conditions. To facilitate the steady-state solution, the entire process mechanism model can be written as a system of differential-algebraic equations in state-variable form, where the state vector is used: ; Represents the unit's operating status variables. Indicates time, Indicates the first One state variable, This represents the number of state variables. Let the input vector of the operating conditions be: ; in This represents the set of input and boundary parameters determined by the operating conditions. Indicates the first One input or boundary parameter, Indicating the number of input and boundary parameters, the full-process mechanism model can be represented as: ; in This represents the derivative of the state vector with respect to time. This represents the set of model equations derived from the coupling of mass conservation, energy conservation, and momentum conservation. During steady-state simulation calculations, let... The steady-state solution equation is obtained as follows: ; in This represents the steady-state vector obtained under the current operating conditions. The steady-state initial parameters are obtained by solving the steady-state equations. The steady-state initial parameters may include the values ​​of state variables that characterize the steady-state operating state of the unit and the derived parameters associated with the state variables. During the switching of operating conditions, the input vector corresponding to the target operating condition is updated to... ,in This represents the set of operating condition inputs and boundary parameters that vary with time. The steady-state initial parameters obtained from the steady-state simulation are used as the initial conditions for the transient simulation, ensuring that the transient simulation satisfies the following: ; in This indicates the start time of the operating condition switch, followed by adjustments to the equation set during the operating condition switch: ; Perform time-domain solution to obtain the change process of unit operating state variables over time; During transient simulation calculations, state variables and operating parameters are recorded according to a preset sampling time interval, forming continuous time-series change data. This continuous time-series change data can be represented as a set of sequences ordered by time. ; in Represents a continuously changing data set. Indicates the first Each sampling time, This represents the vector of operating parameters at the corresponding sampling time. Indicates the number of sampling points, and the runtime parameter vector. The components may include parameters directly composed of state variables and derived operating parameters calculated from state variables. Continuous time-series change data of unit operating parameters reflecting the operating condition switching process can be obtained in the above manner. Steady-state simulation and transient simulation are implemented in a connected manner within the same full-process mechanism model framework. Steady-state simulation provides the steady-state initial parameters before the start of the operating condition switch. When the operating condition input changes, transient simulation uses the steady-state initial parameters as the initial conditions to solve the time domain problem and outputs continuous time-series change data during the calculation process. This completes the simulation calculation and data acquisition of the operating condition switch process, providing a data foundation for subsequent analysis of operating parameter relationships and generation of operating parameter control schemes.

[0028] S4. Based on continuous time-series change data, analyze the relationship between the unit's operating parameters under different operating conditions, and form a description of the relationship between the operating parameters and the changes in operating conditions; Furthermore, in S4, the analysis of the relationship between the unit's operating parameters under different operating conditions based on continuous time-series data includes: The operating conditions are identified for continuously changing time-series data, and the unit operating parameters are associated with the corresponding operating conditions. Under the same or similar operating conditions, the time-series variation data of the unit's operating parameters are collected and processed; Based on the aggregated time-series change data, the corresponding relationship between the unit's operating parameters and the changes in operating conditions is determined, forming a description of the operating parameter relationship.

[0029] Furthermore, in S4, the analysis of the variation relationship of unit operating parameters under different operating conditions also includes: Based on operating condition identification information, the unit operating parameters in continuously time-series changing data are grouped and processed. Within each operating condition group, the time-series variation characteristics of the unit's operating parameters are compared and analyzed. Based on the comparative analysis results, the unit operating parameters that correspond to changes in operating conditions were selected and included in the operating parameter relationship description.

[0030] Specifically, the operation parameter relationship analysis is carried out on the basis of obtaining continuous time-series change data of the working condition switching process. The continuous time-series change data consists of operation parameter vectors corresponding to multiple sampling times and corresponds to the working conditions in the multi-working condition space. The operation parameter relationship analysis is used to establish the correspondence between the operation parameter change law and the working condition change under different working conditions, so as to form an operation parameter relationship description that can be called for subsequent adaptive processing of operation parameters. In the specific implementation process, the continuously changing time-series data is first processed by operating condition identification. The operating condition identification is used to indicate the operating condition corresponding to each piece of operating data. To implement the operating condition identification, an operating condition identification value can be assigned to each sampling time based on the number of operating conditions or the characteristics of the parameter set in the operating condition space. For example, the operating condition identification function can be used as follows: ; Indicates the sampling time The corresponding operating condition number, among which This represents the function for identifying operating conditions. Indicates the first Each sampling time, The operating condition number is used to uniquely identify a specific operating condition in a multi-operating condition space. The operating condition identification process establishes a relationship between the operating parameter data and the corresponding operating condition. After completing the operating condition identification, the time series data corresponding to the same or similar operating condition identification are aggregated and processed. Same operating condition identification indicates that the operating data is under the same operating condition, and similar operating condition identification indicates that the operating conditions corresponding to the operating data meet a preset similarity criterion in the parameter space. To avoid limiting specific thresholds, the similarity criterion can adopt a judgment method based on the difference of operating condition parameter vectors. For example, any operating condition can be represented as an operating condition vector. and through the distance function To determine the similarity of operating conditions, among which Represents the first working condition vector. This represents the second working condition vector. The function represents the difference measurement between working condition vectors. When the difference measurement meets the preset similarity criteria, the working conditions are determined to be similar. The data is then processed to form a set of operating parameter data grouped by working condition. Based on the aggregated time-series variation data, the corresponding relationship between operating parameters and operating conditions is determined. The operating parameters can be represented as an operating parameter vector. , Indicates the sampling time The corresponding operating parameter vector, whose components can be key or derived operating parameters of the unit's operation, is used to calculate the statistical characteristics, trends, or ranges of the operating parameter vectors within the same operating condition group. This yields the representation of the operating parameters under that condition, and the representations under different operating conditions are compared to establish a correspondence between operating parameters and operating conditions. This relationship can be described using a mapping structure indexed by the operating condition identifier, for example: ; in This describes the relationship between runtime parameters. Indicates the operating condition number. Indicates the working condition number The corresponding operating parameter relationship entries are used to record the variation characteristics of operating parameters under this operating condition and their correlation with other parameters; To further ensure that the parameters in the description of the relationship between operating parameters have relevance that can be used for subsequent processing, the operating parameters in the continuous time-series change data are grouped based on the operating condition identification information. The grouping process divides the operating parameter data under the same operating condition number or similar operating conditions into the same group, so that each group corresponds to a set of operating conditions, thereby carrying out comparative analysis of the time-series change characteristics of operating parameters within the group. Within each operating condition group, the time-series variation characteristics of the operating parameters are compared and analyzed. This comparison and analysis can be based on the trend characteristics, variation amplitude characteristics, or fluctuation characteristics of the operating parameters over time. Optionally, it can be based on a correlation index between the operating parameters and the operating condition parameters. To avoid limiting the specific algorithm, the correlation index can be expressed in the form of a correlation coefficient. For example, for any operating parameter component within the group... With any operating condition parameter component The correlation coefficient can be expressed as: ; in This represents the correlation coefficient between operating parameter components and condition parameter components. Indicates the working condition number is The number of sampling points within a group, Indicates the sampling time The Each running parameter component Indicates the number within the group The mean of each running parameter component, Indicates the first Each operating condition parameter component Indicates the first The mean value of each operating condition parameter component is used to quantify the correlation between the operating parameters and changes in operating conditions through the aforementioned correlation indicators. Based on the comparative analysis results, operating parameters that correspond to changes in operating conditions are selected. The selection process can be determined based on the correlation index reaching a preset selection criterion or based on the difference characteristics of operating parameters in different operating condition groups reaching a preset difference criterion. The selected operating parameters are included in the operating parameter relationship entries in the operating parameter relationship description, so that the operating parameter relationship description can cover the operating parameters and their change characteristics related to changes in operating conditions, and form a structured data foundation for subsequent adaptive processing of operating parameters.

[0031] S5. Based on the description of the relationship between operating parameters and combined with the unit operation control logic, adaptive processing of the unit operating parameters is performed to generate an operating parameter control scheme corresponding to the current operating conditions. Furthermore, in S5, adaptive processing of unit operating parameters includes: Based on the description of the relationship between operating parameters, determine the adjustment range of operating parameters corresponding to the current operating conditions; By combining the unit operation control logic, the operating parameters within the adjustment range are constrained to obtain a set of candidate operating parameters; Based on the set of candidate operating parameters, an operating parameter control scheme corresponding to the current operating conditions is generated.

[0032] Specifically, adaptive processing is performed on the basis that the description of the relationship between operating parameters has been completed and the current operating conditions have been determined. Adaptive processing uses the description of the relationship between operating parameters as the data basis and combines it with the unit operation control logic to process the operating parameters in order to form an operating parameter control scheme that matches the current operating conditions. In the specific implementation process, the relationship entries corresponding to the current operating conditions are first read from the description of the operating parameter relationships. The current operating conditions can be determined by the operating condition number or the operating condition parameter vector in the multi-operating condition space. The description of the operating parameter relationships contains the variation characteristics of each operating parameter under different operating conditions and their correlation information. Therefore, the adjustable range of the operating parameters under the current operating conditions can be determined based on this relationship entry. To facilitate the formation of a structured adjustment range, the operating parameters to be processed can be represented as an operating parameter vector. ; in This represents the vector of runtime parameters to be processed. Indicates the first One pending runtime parameter, This indicates the number of runtime parameters to be processed. The adjustment range can be represented as a set of upper and lower bound constraints given for each runtime parameter. ; in This represents the set of operating parameter adjustment ranges. Indicates the first The lower bound of each operating parameter under current operating conditions. Indicates the first The upper bound of each operating parameter under the current operating conditions. The upper and lower bounds of the operating parameters can be derived from the corresponding change characteristics of the operating conditions in the description of the relationship between the operating parameters, or they can be determined in combination with the unit's operating constraint information, thereby completing the determination of the adjustment range of the operating parameters corresponding to the current operating conditions. After determining the adjustment range of operating parameters, the unit operation control logic is used as the source of constraints to constrain the operating parameters within the adjustment range. The unit operation control logic may include the setting rules of the regulating loop, parameter interlocking rules, limit rules, or other operation control rules. To facilitate the expression of control logic constraints in a computable form, control logic constraints can be represented as a set of constraint functions: ; in This represents a constraint function vector generated by the control logic. Each component of the constraint function vector corresponds to a constraint expression of a control logic rule. The zero vector represents the set of candidate operating parameters obtained by filtering operating parameters that satisfy both the adjustment range constraints and the control logic constraints. For example, the set of candidate operating parameters can be represented as: ; in This represents a set of candidate operating parameters. By simultaneously applying adjustment ranges and control logic constraints, the operating parameters are constrained and a set of candidate operating parameters is formed. After obtaining the candidate set of operating parameters, an operating parameter control scheme is generated based on the candidate set of operating parameters. The operating parameter control scheme can be represented in the form of an operating parameter value vector. That is, a set of operating parameter values ​​that meet the constraints are determined from the candidate set of operating parameters as the output of the control scheme. The control scheme is associated with the current operating conditions so that its applicable operating conditions can be clearly identified in subsequent simulation calculations or operation-side calls. To facilitate the generation of operating parameter control schemes, a discretization candidate strategy can be optionally adopted to construct a set of candidate operating parameters. The operating parameters within the adjustment range are discretized and sampled according to a preset step size or a preset value set to form multiple sets of candidate operating parameter vectors. The control logic constraints are checked one by one to retain the candidate operating parameter vectors that meet the constraints, thereby forming a candidate set that can be used for the output of the control scheme. The output of the control scheme can be bound and stored based on the operating condition number of the current operating condition and the candidate operating parameter vectors to support the calling and configuration of the operating parameter control scheme when switching operating conditions. The above method realizes a complete process of determining the adjustment range based on the relationship description of operating parameters, implementing constraint processing in combination with the unit operation control logic to form a set of candidate operating parameters, and generating an operating parameter control scheme corresponding to the current operating conditions based on the set of candidate operating parameters. This provides an input basis for subsequent simulation calculation and result output of the control scheme in the full-process mechanism model.

[0033] S6. Simulate and calculate the operation parameter control scheme in the whole process mechanism model, and output the operation parameter control results.

[0034] Furthermore, in S6, the operating parameter control scheme is simulated and calculated in the full-process mechanism model, and the operating parameter control results are output, including: The operational parameter control scheme is configured as an input parameter into the full-process mechanism model; Based on the full-process mechanism model, the configured operation parameter control scheme is simulated and calculated to obtain the corresponding unit operation parameter simulation results. Consistency verification is performed on the simulation results of unit operating parameters; After passing the consistency check, the results of the operation parameter adjustment are output.

[0035] Specifically, the simulation calculation and result output of the operating parameter control scheme are performed on the basis that the whole process mechanism model has been built and the operating parameter control scheme has been generated. During the operation, the operating parameter control scheme is configured as the model input parameter into the whole process mechanism model, so that the whole process mechanism model can calculate the control scheme under the corresponding working conditions and output the simulation results corresponding to the control scheme. In the specific implementation process, the operation parameter control scheme can be expressed in the form of an operation parameter value vector and established with the current operating conditions. The configuration process includes binding each operation parameter in the operation parameter control scheme with the corresponding input variable in the whole process mechanism model, and determining the value of the model boundary conditions according to the operating conditions, so that the model input parameters and boundary conditions form a consistent configuration set, thereby completing the input parameter configuration of the operation parameter control scheme. After the input parameters are configured, the configured operation parameter control scheme is simulated based on the full-process mechanism model. The simulation calculation can be performed in steady-state or transient mode, and the simulation results of the operation parameters changing over time can be output within a preset simulation period. The simulation results can be represented as a data set consisting of multiple sampling times and corresponding operation parameter vectors. The simulation results include the calculated values ​​of the unit operation parameters corresponding to the operation parameter control scheme and the calculated values ​​of the operation parameters derived from the model state variables, so as to form the unit operation parameter simulation results. To ensure that the simulation results are consistent with the unit's operation control logic, a consistency check is performed on the simulation results of the unit's operating parameters. This consistency check verifies whether the simulation results meet the constraints of the operation control logic and the parameter boundary conditions of the operating parameter adjustment scheme. The consistency check process can be based on a joint verification of the control logic constraint function set and the operating parameter adjustment range. The operating parameter vector at any given time is denoted as... , Indicates the simulation calculation at time t. The output runtime parameter vector and runtime control logic constraint function vector are denoted as follows: , This indicates the result of constraint calculation on the operating parameter vector based on the operating control logic, determined by: ; To determine the compliance of the simulation results with control logic constraints, whereby... Represents the zero vector, and optionally indicates whether the simulation results of the operating parameters fall within the set of operating parameter adjustment ranges. Verification is performed to determine the consistency between the simulation results of the operating parameters and the set boundaries of the operating parameter control scheme. This represents the set of adjustment ranges for running parameters, and the judgment condition can be expressed as follows: ; When the consistency check meets the preset check criteria, the operation parameter control results are output. The operation parameter control results may include the output values ​​of each operation parameter in the operation parameter control scheme, the corresponding operating condition number or operating condition parameter vector identifier, as well as key data fragments or summary data of the unit operation parameter simulation results output by the simulation calculation. The output format may be optional file format, data interface format or visualization display format, so that it can be called in subsequent operation control, operation analysis or closed-loop update process. In the specific implementation process, when the consistency verification fails to meet the preset verification criteria, the non-constrained operating parameter components, corresponding times, and triggered control logic rules can be selectively recorded, and the recorded information can be returned to the operating parameter control scheme generation stage so as to re-screen and configure the candidate operating parameter set or operating parameter control scheme, thereby forming a control result output process that combines simulation calculation and consistency verification, so as to keep the output of the operating parameter control result consistent with the logical closed loop of the whole process mechanism model calculation process.

[0036] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for multi-condition adaptive modeling and intelligent control of operating parameters for sludge incineration units, characterized in that, Includes the following steps: S1. Based on the principles of conservation of mass, energy, and momentum, construct a full-process mechanism model for sludge incineration units; S2. Construct a multi-condition space for the sludge incineration unit, and use the unit's operating status parameters, fuel characteristic parameters, and external operating environment parameters as the operating condition inputs and boundary conditions for the whole process mechanism model. S3. In the multi-condition space, based on the whole process mechanism model, steady-state simulation calculation and transient simulation calculation are performed on the operation process of the sludge incineration unit during the operation condition switching process to obtain continuous time-series change data of the unit's operating parameters. S4. Based on continuous time-series change data, analyze the relationship between the unit's operating parameters under different operating conditions, and form a description of the relationship between the operating parameters and the changes in operating conditions; S5. Based on the description of the relationship between operating parameters and combined with the unit operation control logic, adaptive processing of the unit operating parameters is performed to generate an operating parameter control scheme corresponding to the current operating conditions. S6. Simulate and calculate the operation parameter control scheme in the whole process mechanism model, and output the operation parameter control results.

2. The method for multi-condition adaptive modeling and intelligent control of operating parameters of sludge incinerator units according to claim 1, characterized in that, In S1, the full-process mechanism model for constructing the sludge incineration unit includes: A material balance model for the unit's material input, output, and conversion processes is established based on the principle of mass conservation. An energy balance model is established based on the principle of energy conservation, considering the energy input, output, and conversion relationships during unit operation. A flow model is established based on the principle of momentum conservation to determine the relationship between the working fluid flow process and pressure changes in the unit. The material balance model, energy balance model, and flow model are coupled to obtain the full-process mechanism model of the sludge incineration unit.

3. The method for multi-condition adaptive modeling and intelligent control of operating parameters of sludge incinerator units according to claim 1, characterized in that, In S1, the full-process mechanism model for constructing the sludge incineration unit also includes: Obtain the control parameters and their corresponding control variables used in the unit's operation control logic; Establish parameter mapping relationships between control variables and corresponding model parameters in the whole-process mechanism model; Based on the parameter mapping relationship, the model parameters in the whole process mechanism model are configured so that the model parameters and control logic parameters correspond in terms of parameter type and value range.

4. The method for multi-condition adaptive modeling and intelligent control of operating parameters of sludge incinerator units according to claim 1, characterized in that, In S2, the multi-condition space for constructing the sludge incineration unit includes: The operating status parameters that characterize the operating status of the sludge incineration unit, the fuel characteristic parameters that characterize the fuel characteristics, and the external operating environment parameters that characterize the external operating environment are classified and managed. Based on the classified parameters, a working condition space containing multiple sets of parameter combinations is constructed. The working condition space is configured as a unified model input set into the full-process mechanism model.

5. The method for multi-condition adaptive modeling and intelligent control of operating parameters of sludge incinerator units according to claim 1, characterized in that, In S2, the multi-condition space for constructing the sludge incineration unit also includes: The different working conditions in the multi-working-condition space are numbered, and a corresponding parameter set is established for each working condition. Based on the changes in the unit's operating status, select the operating conditions corresponding to the current operating status from the parameter set; The selected operating conditions are loaded into the full-process mechanism model.

6. The method for multi-condition adaptive modeling and intelligent control of operating parameters of a sludge incinerator unit according to claim 1, characterized in that, In S3, the steady-state simulation calculation and transient simulation calculation of the operation process of the sludge incinerator unit during the switching of operating conditions include: Before switching operating conditions, steady-state simulation calculations are performed on the unit's operation process under the current operating conditions based on the full-process mechanism model to obtain the corresponding steady-state initial parameters. During the switching of operating conditions, the steady-state initial parameters are used as the initial conditions to perform transient simulation calculations on the unit operation process and obtain the continuous time-series change data of the unit operating parameters during the switching of operating conditions.

7. The method for multi-condition adaptive modeling and intelligent control of operating parameters of a sludge incinerator unit according to claim 1, characterized in that, In S4, the analysis of the variation relationship of unit operating parameters under different operating conditions based on continuous time-series variation data includes: The operating conditions are identified for continuously changing time-series data, and the unit operating parameters are associated with the corresponding operating conditions. Under the same or similar operating conditions, the time-series variation data of the unit's operating parameters are collected and processed; Based on the aggregated time-series change data, the corresponding relationship between the unit's operating parameters and the changes in operating conditions is determined, forming a description of the operating parameter relationship.

8. The method for multi-condition adaptive modeling and intelligent control of operating parameters of a sludge incinerator unit according to claim 1, characterized in that, In S4, the analysis of the variation relationship of unit operating parameters under different operating conditions also includes: Based on operating condition identification information, the unit operating parameters in continuously time-series changing data are grouped and processed. Within each operating condition group, the time-series variation characteristics of the unit's operating parameters are compared and analyzed. Based on the comparative analysis results, the unit operating parameters that correspond to changes in operating conditions were selected and included in the operating parameter relationship description.

9. The method for multi-condition adaptive modeling and intelligent control of operating parameters of a sludge incinerator unit according to claim 1, characterized in that, In S5, the adaptive processing of unit operating parameters includes: Based on the description of the relationship between operating parameters, determine the adjustment range of operating parameters corresponding to the current operating conditions; By combining the unit operation control logic, the operating parameters within the adjustment range are constrained to obtain a set of candidate operating parameters; Based on the set of candidate operating parameters, an operating parameter control scheme corresponding to the current operating conditions is generated.

10. The method for multi-condition adaptive modeling and intelligent control of operating parameters of a sludge incinerator unit according to claim 1, characterized in that, In S6, the simulation calculation of the operating parameter control scheme in the whole process mechanism model and the output of the operating parameter control results include: The operating parameter control scheme is configured as an input parameter into the full-process mechanism model; Based on the full-process mechanism model, the configured operation parameter control scheme is simulated and calculated to obtain the corresponding unit operation parameter simulation results. Consistency verification is performed on the simulation results of unit operating parameters; After passing the consistency check, the results of the operation parameter adjustment are output.

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