Model-based waste incineration control system

文档序号:1648064 发布日期:2019-12-24 浏览:44次 中文

阅读说明:本技术 一种基于模型的垃圾焚烧控制系统 (Model-based waste incineration control system ) 是由 朱亮 杨仕桥 邵哲如 王健生 洪益州 张二威 张晓军 于 2019-08-26 设计创作,主要内容包括:本发明提供一种基于模型的垃圾焚烧控制系统,所述系统包括:数据采集装置,用以采集与焚烧炉的燃烧过程相关的燃烧过程数据;模型参数优化单元,包括模型处理单元和参数优化单元,所述模型处理单元利用动态燃烧模型将所述燃烧过程数据作为输入变量计算出输出变量,所述输出变量预测与所述焚烧炉的燃烧工况相关的燃烧工况数据,所述动态燃烧模型为根据所述燃烧过程数据和所述燃烧工况数据之间的相关关系建立的计算模型,所述参数优化单元根据所述输出变量计算所述焚烧炉的优化控制参数;自动控制模块,用以根据所述优化控制参数对所述焚烧炉进行自动控制。根据本发明,实现了垃圾焚烧过程的最优控制,提升了焚烧炉的燃烧效率和灼减率。(The invention provides a model-based waste incineration control system, which comprises: a data acquisition device for acquiring combustion process data related to a combustion process of the incinerator; a model parameter optimizing unit including a model processing unit and a parameter optimizing unit, the model processing unit calculating an output variable using a dynamic combustion model with the combustion process data as an input variable, the output variable predicting combustion condition data related to the combustion condition of the incinerator, the dynamic combustion model being a calculation model established according to a correlation between the combustion process data and the combustion condition data, the parameter optimizing unit calculating an optimized control parameter of the incinerator according to the output variable; and the automatic control module is used for automatically controlling the incinerator according to the optimized control parameters. According to the invention, the optimal control of the waste incineration process is realized, and the combustion efficiency and the ignition loss rate of the incinerator are improved.)

1. A model-based waste incineration control system, comprising:

a data acquisition device for acquiring combustion process data related to a combustion process of the incinerator;

a model parameter optimizing unit including a model processing unit and a parameter optimizing unit, the model processing unit calculating an output variable using a dynamic combustion model with the combustion process data as an input variable, the output variable predicting combustion condition data related to the combustion condition of the incinerator, the dynamic combustion model being a calculation model established according to a correlation between the combustion process data and the combustion condition data, the parameter optimizing unit calculating an optimized control parameter of the incinerator according to the output variable;

and the automatic control module is used for automatically controlling the incinerator according to the optimized control parameters.

2. The waste incineration control system of claim 1, wherein the dynamic combustion model comprises a timing model established using MATLAB.

3. The waste incineration control system of claim 1, wherein the dynamic combustion model includes a combustion oxygen amount model and a combustion air-to-fuel ratio model;

the combustion oxygen amount model is used for calculating combustion condition data related to the given amount of the secondary air of the incinerator,

the combustion air-material ratio model is used for calculating combustion working condition data related to the primary air supply quantity of the incinerator, the feeding quantity of the feeding grate and the propelling speed of the incineration grate.

4. The waste incineration control system of claim 3, wherein the input variables of the combustion oxygen volume model include main steam flow, flue gas volume, furnace temperature, exhaust-heat boiler outlet flue gas oxygen content, chimney outlet flue gas oxygen content, feed volume, waste heat value; the output variable of the combustion oxygen quantity model comprises the oxygen content of the flue gas at the outlet of the waste heat boiler; and the oxygen content of the outlet flue gas of the waste heat boiler, which is obtained in the last calculation and is used as the output variable, is used as the input variable used in the next calculation.

5. The refuse incineration control system according to claim 3, wherein the input variables of the combustion air-fuel ratio model include: feeding amount, heat value, primary air quantity and secondary air quantity;

the output variables of the combustion air-fuel ratio model comprise: the main steam flow, the flue gas quantity, the hearth temperature, the oxygen content of the flue gas at the outlet of the waste heat boiler and the oxygen content of the flue gas at the outlet of the chimney.

6. The refuse incineration control system according to claim 1, wherein the parameter optimization unit adaptively adjusts the optimized control parameter according to the output variable.

7. The refuse incineration control system according to claim 6, wherein the parameter optimization unit calculates the optimized control parameter from the output variable using a machine learning model.

8. The refuse incineration control system according to claim 1, wherein the data collection means further collects the combustion condition data of an incinerator.

9. The refuse incineration control system according to claim 1, wherein the parameter optimization unit further compares the output variable calculated by the model processing unit to predict the combustion condition data with the combustion condition data collected by the data collection device to obtain a comparison result, and calculates the optimization control parameter according to the comparison result.

10. The waste incineration control system of claim 1, wherein the optimized control parameters include a primary air flow, a secondary air flow, a feeder grate feed rate, and an incineration grate movement speed.

Technical Field

The invention relates to the field of garbage treatment, in particular to a garbage incineration control system based on a model.

Background

The waste incineration is an old traditional method for treating the waste, and the waste incineration method is one of the main methods for treating the urban waste because the waste is treated by the incineration method, the reduction effect is obvious, the land is saved, various pathogens can be eliminated, and toxic and harmful substances are converted into harmless substances.

In the process of burning the garbage, the burning working condition is complex due to the reasons of unfixed garbage raw materials, complex and variable components and the like. In order to achieve good burnout efficiency and burn-off rate of the garbage, a control system is often used to control the operating state of the incinerator. Specifically, the CEMS data at the tail of the chimney is used as a control basis, the control system generally adopts PID control, and then a control strategy is compiled according to operation experience, and the operation of the whole system under the optimal condition is difficult to guarantee under the control.

Therefore, it is necessary to provide a model-based waste incineration control system to solve the problems in the prior art.

Disclosure of Invention

In this summary, concepts in a simplified form are introduced that are further described in the detailed description. This summary of the invention is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

The invention provides a model-based waste incineration control system, which comprises:

a data acquisition device for acquiring combustion process data related to a combustion process of the incinerator;

a model parameter optimizing unit including a model processing unit and a parameter optimizing unit, the model processing unit calculating an output variable using a dynamic combustion model with the combustion process data as an input variable, the output variable predicting combustion condition data related to the combustion condition of the incinerator, the dynamic combustion model being a calculation model established according to a correlation between the combustion process data and the combustion condition data, the parameter optimizing unit calculating an optimized control parameter of the incinerator according to the output variable;

and the automatic control module is used for automatically controlling the incinerator according to the optimized control parameters.

Illustratively, the dynamic combustion model comprises a timing model established using MATLAB.

Illustratively, the dynamic combustion model comprises a combustion oxygen amount model and a combustion air-fuel ratio model;

the combustion oxygen amount model is used for calculating combustion condition data related to the given amount of the secondary air of the incinerator,

the combustion air-material ratio model is used for calculating combustion working condition data related to the primary air supply quantity of the incinerator, the feeding quantity of the feeding grate and the propelling speed of the incineration grate.

Illustratively, the input variables of the combustion oxygen amount model include main steam flow, flue gas amount, furnace temperature, exhaust-heat boiler outlet flue gas oxygen content, chimney outlet flue gas oxygen content, feeding amount, and garbage heat value; the output variable of the combustion oxygen quantity model comprises the oxygen content of the flue gas at the outlet of the waste heat boiler; and the oxygen content of the outlet flue gas of the waste heat boiler, which is obtained in the last calculation and is used as the output variable, is used as the input variable used in the next calculation.

Illustratively, the input variables of the combustion air-fuel ratio model include: feeding amount, heat value, primary air quantity and secondary air quantity;

the output variables of the combustion air-fuel ratio model comprise: the main steam flow, the flue gas quantity, the hearth temperature, the oxygen content of the flue gas at the outlet of the waste heat boiler and the oxygen content of the flue gas at the outlet of the chimney.

Illustratively, the parameter optimization unit adaptively adjusts the optimization control parameter according to the output variable.

Illustratively, the parameter optimization unit calculates the optimization control parameter from the output variable using a machine learning model.

Illustratively, the data acquisition device also acquires the combustion condition data of an incinerator.

For example, the parameter optimization unit may further compare the output variable calculated by the model processing unit to predict the combustion condition data with the combustion condition data collected by the data collection device to obtain a comparison result, and calculate the optimization control parameter according to the comparison result.

Illustratively, the optimized control parameters comprise primary air volume, secondary air volume, feeding grate feeding volume and burning grate moving speed.

According to the model-based waste incineration control system, the combustion state model is used for predicting the waste incineration combustion condition data, and the control parameters of the incinerator are optimally controlled based on the prediction data, so that the optimal control of the waste incineration process is realized, the burning rate of the waste incineration is improved, the combustion efficiency of the incinerator is improved, and the optimal control of the total amount of smoke is realized.

Drawings

The following drawings of the invention are included to provide a further understanding of the invention. The drawings illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

In the drawings:

FIG. 1 is a block diagram of a model-based waste incineration control system according to the present invention;

fig. 2 is a schematic control principle diagram of a waste incineration control system according to an embodiment of the invention.

Detailed Description

In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the present invention. It will be apparent, however, to one skilled in the art, that the present invention may be practiced without one or more of these specific details. In other instances, well-known features have not been described in order to avoid obscuring the invention.

In order to thoroughly understand the present invention, a detailed description will be provided in the following description to illustrate a method and an apparatus for treating late leachate in an old domestic garbage landfill according to the present invention. It will be apparent that the practice of the invention is not limited to the specific details known to those skilled in the art of waste treatment. The following detailed description of the preferred embodiments of the invention, however, the invention is capable of other embodiments in addition to those detailed.

It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular is intended to include the plural unless the context clearly dictates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

Exemplary embodiments according to the present invention will now be described in more detail with reference to the accompanying drawings. These exemplary embodiments may, however, be embodied in many different forms and should not be construed as limited to only the embodiments set forth herein. It is to be understood that these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of these exemplary embodiments to those skilled in the art. In the drawings, the thicknesses of layers and regions are exaggerated for clarity, and the same elements are denoted by the same reference numerals, and thus the description thereof will be omitted.

In the process of burning the garbage, the burning working condition is complex due to the reasons of unfixed garbage raw materials, complex and variable components and the like. In order to achieve good burnout efficiency and burn-off rate of the garbage, a control system is often used to control the operating state of the incinerator. Specifically, the CEMS data at the tail of the chimney is used as a control basis, the control system generally adopts PID control, and then a control strategy is compiled according to operation experience, and the operation of the whole system under the optimal condition is difficult to guarantee under the control.

In order to solve the problems in the prior art, the invention provides a model-based waste incineration control system, which comprises:

a data acquisition device for acquiring process data related to a reaction process of the semi-dry process reaction tower;

a model parameter optimization unit including a model processing unit and a parameter optimization unit, the model processing unit calculating and outputting variables using a dynamic flue gas processing model with the process data as input variables, wherein the output variables predict flue gas emission data related to flue gas output from the semi-dry process reaction tower, the dynamic flue gas processing model is a calculation model established according to a correlation between the process data and the flue gas emission data, and the parameter optimization unit calculates optimization control parameters of the semi-dry process reaction tower according to the output variables;

and the automatic control module is used for automatically controlling the semi-dry process reaction tower according to the optimized control parameters.

A model-based waste incineration control system according to a present invention will be described with reference to fig. 1 and 2, wherein fig. 1 is a block diagram of the model-based waste incineration control system according to the present invention, and fig. 2 is a schematic control principle diagram of a waste incineration control system according to an embodiment of the present invention.

Referring first to fig. 1, the model-based waste incineration control system includes a data acquisition device 101, a model parameter optimization unit 102, and an automatic control module 103.

The data collecting device 101 is used for collecting the combustion process data related to the garbage input into the incinerator.

The garbage is input into the incinerator for incineration after being collected, classified and dried, and because the components in the garbage are unfixed, diversified and complex, the parameters of the components, humidity, fuel calorific value, incinerator furnace temperature, feeding quantity and the like of the garbage can influence the combustion work. In order for the model parameter optimization unit 102 to build an accurate analysis model, the data collection device 101 collects as much combustion process data as possible.

Exemplarily, the data acquisition device comprises a detection device which is arranged at the feeding end of the incinerator and is used for detecting the heat value and the composition of the garbage input into the incinerator; a feeding amount detection device arranged on the feeding hopper; a flue gas flow measuring device arranged on the incineration hearth, and the like.

It is to be understood that the above examples of data acquisition devices are for illustrative purposes only and that any type of detection device that detects any data may be provided as desired by one skilled in the art.

With continued reference to fig. 1, the model parameter optimization unit 102 includes a model processing unit 1021 and a parameter optimization unit 1022.

The model processing unit 1021 calculates combustion condition data relating to the combustion condition of the incinerator from the combustion process data collected by the data collection device 101 using the dynamic combustion model. Wherein an output variable is calculated using the combustion process data as an input variable, the output variable predicting combustion condition data relating to a combustion condition of the incinerator.

The dynamic combustion model is a calculation model established according to the correlation between the combustion process data and the combustion condition data. Illustratively, the dynamic combustion model comprises a timing model established using MATLAB.

With continued reference to fig. 1, the model parameter optimizing unit 102 further includes a parameter optimizing unit 1022, and the parameter optimizing unit 1022 outputs the optimized control parameters of the incinerator according to the combustion condition data calculated by the model processing unit 1021.

In one example according to the invention, the optimization control parameters include the oxygen supply amount of the secondary air controller, the air supply amount of the primary air, the feeding amount of the feeding grate, the advancing speed of the incineration grate and the like.

Since the incinerator has more control parameters and complicated control conditions, in order to realize accurate control of the incinerator, according to one example of the invention, oxygen demand and air-fuel ratio (ratio of primary air and secondary air to fuel quantity) in the combustion process are respectively modeled to obtain combustion condition data respectively related to the oxygen demand and the air-fuel ratio, so that a subsequent parameter optimization unit respectively obtains related optimized control parameters by using the combustion condition data.

The following describes an exemplary process of establishing a combustion oxygen amount model and a combustion air-fuel ratio model using MATLB, respectively.

Further, illustratively, the step of modeling the amount of oxygen combusted using MATLAB comprises:

s1: analyzing the reaction mechanism of the incinerator, and establishing an original model of the combustion oxygen amount of the incinerator; this step is carried out by theoretical analysis by the worker.

S2: carrying out a waste incineration test; this step is carried out at the site of waste incineration. Specifically, the waste incineration test is performed under the conditions of different waste components and heat values, different primary air intake and secondary air intake, and the like.

S3: and collecting process data and combustion condition data when the incinerator burns the garbage. Specifically, in step S2, a data acquisition device is used to collect process data related to the incineration process at the beginning of incineration, such as main steam flow, flue gas amount, furnace temperature (first flue, exhaust-heat boiler outlet, etc.), exhaust-heat outlet flue gas oxygen content, feeding amount, garbage heat value, etc., related to time variable; and combustion condition data related to the secondary air volume control in the incineration process of the incinerator after incineration, such as ash thermal ignition reduction rate, CO emission, feeding quantity, hearth temperature, oxygen content at an outlet of a waste heat boiler, oxygen content at an outlet of a chimney and the like.

S4: the combustion process data and the combustion condition data related to the time variable collected in the above step S3 are subjected to correlation analysis, and the combustion process data and the combustion condition data significantly related to the oxygen demand control of the incinerator are screened. In one example according to the invention, the screened combustion process data includes main steam flow, flue gas amount, furnace temperature (first flue, exhaust heat boiler outlet, etc.), stack outlet flue gas oxygen content, feed amount, heat value. The combustion condition data related to the control of the secondary air volume in the incineration process of the incinerator comprises the oxygen quantity of the outlet of the waste heat boiler.

S5: and verifying the established original model according to the screened combustion process data and the screened combustion condition data.

The whole modeling process is established in a mode of combining a mechanism model and a plurality of element linear regression equations, so that the established dynamic combustion model can accurately reflect the correlation between the combustion process data and the combustion condition data, and the calculation accuracy of the model processing unit can be improved. Meanwhile, the time sequence model established in the modeling process enables the model processing unit to reflect the current combustion state and the previous combustion state of the incinerator after processing the combustion process data related to the time variable. In the established combustion oxygen amount model, the model input variables comprise: the method comprises the following steps of (1) main steam flow, flue gas quantity, hearth temperature (a first flue, a waste heat boiler outlet and the like), waste heat outlet flue gas oxygen content, chimney outlet flue gas oxygen content, feeding quantity and heat value; the model output variable comprises the oxygen content of the flue gas at the outlet of the waste heat boiler. And the oxygen content of the flue gas at the outlet of the waste heat boiler at the last time is used as the model input to calculate to obtain the model output used for predicting the oxygen content of the flue gas at the outlet of the waste heat boiler at the next time, so that the iterative calculation of the model is realized. And the obtained oxygen content of the flue gas at the outlet of the waste heat boiler output by the model is used as a related variable of the secondary air controller to realize the optimization of the control parameter of the secondary air controller in a parameter optimization unit.

Also illustratively, the step of modeling the combustion air-fuel ratio using MATLAB includes:

s1: analyzing the reaction mechanism of the incinerator, and establishing an original model of the combustion air-fuel ratio of the incinerator; this step is carried out by theoretical analysis by the worker.

S2: carrying out a waste incineration test; this step is carried out at the site of waste incineration. Specifically, the waste incineration test is performed under the conditions of different waste components and heat values, different primary air intake and secondary air intake, and the like.

S3: and collecting process data and combustion condition data when the incinerator burns the garbage. Specifically, in step S2, the data acquisition device is used to collect process data related to the incineration process at the beginning of incineration, such as the feeding amount and the calorific value of garbage, related to the time variable; after the incineration of the incinerator, combustion condition data related to the primary air volume, the feeding amount and the feeding speed of the incineration grate in the incineration process of the incinerator, such as main steam flow, flue gas volume, hearth temperature (a first flue, an outlet of a waste heat boiler and the like) and flue gas oxygen content at an outlet of a chimney.

S4: the combustion process data and the combustion condition data related to the time variable collected in the above step S3 are subjected to correlation analysis, and the combustion process data and the combustion condition data significantly related to the oxygen demand control of the incinerator are screened. In one example according to the present invention, the screened combustion process data includes a feed amount, a garbage heating value, a primary air volume, and a secondary air volume. Combustion condition data such as main steam flow, flue gas amount, furnace temperature (first flue, exhaust-heat boiler outlet, etc.), and flue gas oxygen content at chimney outlet

S5: and verifying the established original model according to the screened combustion process data and the screened combustion condition data.

The whole modeling process is established in a mode of combining a mechanism model and a plurality of element linear regression equations, so that the established dynamic combustion model can accurately reflect the correlation between the combustion process data and the combustion condition data, and the calculation accuracy of the model processing unit can be improved. Meanwhile, the time sequence model established in the modeling process enables the model processing unit to reflect the current combustion state and the previous combustion state of the incinerator after processing the combustion process data related to the time variable. In the established combustion oxygen amount model, the model input variables comprise: feeding amount, garbage heat value, primary air quantity and secondary air quantity; the model output variables comprise main steam flow, flue gas quantity, hearth temperature (a first flue, a waste heat boiler outlet and the like), waste heat boiler outlet flue gas oxygen content and chimney outlet flue gas oxygen content. And obtaining the variation trend of the degree, load, oxygen content and flue gas emission of the incinerator hearth as related variables of the primary air controller, the feeding grate controller and the incinerator grate controller, and optimizing control parameters of the primary air controller, the feeding grate controller and the incinerator grate controller in a parameter optimization unit to finally realize the optimal control of the total flue gas amount.

The parameter optimization unit 1022 optimizes the incinerator control parameters according to the output variables calculated by the model processing unit 1021 to predict the combustion condition data to obtain optimized control parameters.

Illustratively, the parameter optimization unit 1022 adaptively adjusts the optimization control parameter according to the output variable. In the above model processing units with two models, the parameter optimization unit 1022 optimizes the control parameters of the secondary air controller according to the oxygen content of the exhaust-heat boiler outlet flue gas calculated by the combustion oxygen amount model to obtain optimized control parameters, and optimizes the control parameters of the primary air controller, the feeding grate controller and the incinerator grate controller according to the variation trend of the incinerator furnace degree, load, oxygen amount and flue gas emission calculated by the combustion air-fuel ratio model to obtain optimized control parameters.

Further, illustratively, the parameter optimization unit 1022 calculates the optimization control parameter from the output variable using a machine learning model.

Illustratively, the machine learning model comprises a neural network model. Specifically, in the parameter optimization unit 1022, the combustion condition data calculated by the model processing unit 1021 is converted into calculable standardized data, and the calculable standardized data is calculated by using the neural network model to obtain the optimized control parameters. The data transformation process and the calculation process using the neural network model may be performed by methods known to those skilled in the art, and will not be described herein.

It should be understood that the description of the parameter optimization unit in the present embodiment using a neural network as an example of the machine learning model is only exemplary, and other machine learning models, such as statistical learning based on a vector machine, deep learning, and the like, are all applicable to the present invention.

The machine learning model is adopted to optimize the control parameters, so that the control parameters can be adaptively optimized and adjusted while the optimized control parameters are accurately calculated and optimized. Specifically, in the process of calculating by using the machine learning model, the reaction result of the incinerator controlled and adjusted by the optimal control parameter can be detected, and the machine learning model is corrected by the detected result to further optimize the machine learning model, thereby further adjusting the output result of the optimal control parameter. Meanwhile, according to the waste incineration control system disclosed by the invention, the full automatic self-adaptive adjustment and control of the incinerator are realized, the manual control burden and errors are effectively reduced, and the control efficiency is improved.

In one example according to the present invention, the parameter optimization unit further compares the output variable calculated by the model processing unit to predict the combustion condition data with the combustion condition data collected by the data collection device to obtain a comparison result, and calculates the optimization control parameter according to the comparison result.

It should be understood that the optimization of the control parameters of the primary air controller, the secondary air controller, the feeding grate controller and the incinerator grate controller by the optimization control unit in the present embodiment is only an example, and those skilled in the art will understand that the control parameters of the controllers of other components of the incinerator can also be optimized by increasing or decreasing the design according to actual needs, so as to achieve accurate control of the incinerator, and the specific control parameters are not limited herein.

In one example according to the present invention, the calculation of the model processing unit and the calculation of the parameter optimization unit in the above-described model parameter control module are implemented on a PLC control panel.

As shown in fig. 1, the control parameter of the lime slurry flow rate calculated by the parameter optimization unit 1022 is transmitted to the automatic control module 103. The automatic control module 103 automatically controls the incinerator according to the optimized control parameters. Illustratively, the automatic control module 103 comprises executable program instructions and a controller, which when executed is capable of effecting control of the lime slurry flow rate of the incinerator, and the like.

Referring to fig. 2, a control principle schematic diagram of a waste incineration control system according to an embodiment of the invention is shown. Before control, the establishment of a model and a parameter optimization unit is realized, and the established model outputs a predicted value related to combustion condition data after model calculation is carried out on the incineration process data of the incineratorThe parameter optimization unit optimizes the control given parameters according to the predicted combustion condition number, the controller outputs the adjustment controller to output u according to the optimized given parameters by combining with the input e of the controller, and adjusts the incinerator by combining with a feedforward factor k under the consideration of other interference, and the adjusted combustion condition data y of the incinerator after combustion and the predicted value of the combustion condition data are output after model processingThe comparison obtained by comparison is used as the self-learning reference of the parameter optimization unit, so that the optimization process of the parameters can be further controlled, and the optimal control of the incinerator is finally realized.

In one example according to the present invention, a communication module is further included. The communication module enables communication between the data acquisition device 101, the model parameter optimization unit 102 and the automatic control module 103. Specifically, the data acquisition device 101 sends acquired combustion process data to the model parameter optimization unit through an I/O port of the communication module, the model processing unit 1021 of the model parameter optimization unit 102 calculates combustion condition data according to the combustion process data to obtain combustion condition data, the parameter optimization unit 1022 calculates optimized control parameters according to the combustion condition data, the model parameter optimization unit 102 sends the optimized control parameters to the automatic control module through the communication module again, and the automatic control module automatically controls an electromagnetic valve and an adjusting valve of an incinerator relevant controller according to the optimized control parameters.

In one example according to the present invention, on the basis that the original incinerator already includes a control system for controlling the incinerator, the present invention can also be directly implemented on the original incinerator control system, i.e., the communication between the original incinerator control system and the model parameter optimization unit of the present invention is realized through a communication module, and in one example, the model parameter optimization unit according to the present invention is realized on a PLC control board, and the communication between the PLC control board and the original incinerator control system is realized through a communication network.

The present invention has been illustrated by the above embodiments, but it should be understood that the above embodiments are for illustrative and descriptive purposes only and are not intended to limit the invention to the scope of the described embodiments. Furthermore, it will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that many variations and modifications may be made in accordance with the teachings of the present invention, which variations and modifications are within the scope of the present invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.

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