CN114963195A - Automatic incineration control system of garbage furnace - Google Patents
Automatic incineration control system of garbage furnace Download PDFInfo
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- CN114963195A CN114963195A CN202210673481.7A CN202210673481A CN114963195A CN 114963195 A CN114963195 A CN 114963195A CN 202210673481 A CN202210673481 A CN 202210673481A CN 114963195 A CN114963195 A CN 114963195A
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- 239000010813 municipal solid waste Substances 0.000 title claims abstract description 278
- 238000002485 combustion reaction Methods 0.000 claims abstract description 91
- 238000007405 data analysis Methods 0.000 claims abstract description 44
- 238000004458 analytical method Methods 0.000 claims abstract description 22
- 239000000463 material Substances 0.000 claims abstract description 22
- 238000013527 convolutional neural network Methods 0.000 claims abstract description 13
- 238000010801 machine learning Methods 0.000 claims abstract description 9
- 238000003062 neural network model Methods 0.000 claims abstract description 9
- 238000013480 data collection Methods 0.000 claims abstract description 8
- 238000000034 method Methods 0.000 claims abstract description 7
- 238000009825 accumulation Methods 0.000 claims description 26
- 238000012549 training Methods 0.000 claims description 9
- 210000000038 chest Anatomy 0.000 claims description 8
- 239000000203 mixture Substances 0.000 claims description 7
- 238000005303 weighing Methods 0.000 claims description 5
- 239000003550 marker Substances 0.000 claims description 3
- 230000008685 targeting Effects 0.000 claims description 3
- 238000012937 correction Methods 0.000 claims description 2
- 230000001276 controlling effect Effects 0.000 claims 2
- 230000001105 regulatory effect Effects 0.000 claims 1
- 239000002699 waste material Substances 0.000 description 3
- 238000004056 waste incineration Methods 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000009264 composting Methods 0.000 description 1
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
- F23G5/00—Incineration of waste; Incinerator constructions; Details, accessories or control therefor
- F23G5/50—Control or safety arrangements
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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- G06V10/20—Image preprocessing
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E20/00—Combustion technologies with mitigation potential
- Y02E20/12—Heat utilisation in combustion or incineration of waste
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Abstract
The invention discloses an automatic incineration control system of a garbage furnace, which relates to the technical field of automatic incineration of the garbage furnace and comprises a data collection module, a garbage data analysis module, a flame shooting module, a flame analysis module and a combustion control module; the method intelligently judges the main components of the garbage according to the data of the weight, the image, the shape and the size of each part of garbage collected in advance, and sets the hearth of the garbage furnace in advance according to the main components; and then, the material layer thickness and the temperature of the hearth of the garbage furnace are estimated by using a machine learning and CNN neural network model, and the hearth setting of the garbage furnace is automatically adjusted in real time according to the material layer thickness and the temperature of the hearth of the garbage furnace, so that the problems of automatically controlling the temperature of the hearth of the garbage furnace and reducing the labor cost are solved.
Description
Technical Field
The invention belongs to the field of waste incineration, relates to an artificial intelligence technology, and particularly relates to an automatic incineration control system of a waste incinerator.
Background
The municipal refuse treatment method mainly comprises 3 treatment modes of landfill, composting and incineration. The waste incineration is to carry out high-temperature incineration in a closed boiler after the urban domestic waste is centrally treated, and the heat energy and the steam generated by the incineration can be used for generating power through a steam turbine; the method realizes the reduction of harm and quantity of municipal solid waste and resource utilization; when the garbage is incinerated, the burning temperature of the garbage needs to be strictly controlled; otherwise, when the combustion temperature is lower than 850 ℃, insufficient combustion of the garbage is easily caused, and the emission of harmful gas is caused;
however, in the actual combustion process, due to the accumulation of the garbage, the combustion temperature difference is large due to the difference of the components of each part of the garbage and the thickness of the garbage layer; the current main treatment mode is to control the combustion temperature by manually controlling the wind pressure, the feeding speed and the like; however, the method has extremely high requirement on manpower, is difficult to control accurately and is easy to generate errors;
therefore, an automatic incineration control system of the garbage furnace is provided.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides an automatic incineration control system of a garbage furnace, which intelligently judges the main components of garbage according to the data of the weight, the image, the shape and the size of each part of garbage collected in advance, and sets a hearth of the garbage furnace in advance according to the main components; and then, the material layer thickness and the temperature of the hearth of the garbage furnace are estimated by using a machine learning and CNN neural network model, and the hearth setting of the garbage furnace is automatically adjusted in real time according to the material layer thickness and the temperature of the hearth of the garbage furnace, so that the problems of automatically controlling the temperature of the hearth of the garbage furnace and reducing the labor cost are solved.
In order to achieve the above object, an embodiment according to a first aspect of the present invention provides an automatic incineration control system for a waste incinerator, including a data collection module, a waste data analysis module, a flame shooting module, a flame analysis module, and a combustion control module; wherein, the modules are electrically connected with each other;
the data collection module is used for collecting characteristic data of the garbage mixture in the garbage furnace;
the characteristic data of the garbage mixture comprises the weight of garbage entering a hearth of the garbage furnace, a garbage accumulation image and the size of a garbage accumulation shape;
the weight of the garbage is measured by installing a weigher before entering a hearth of the garbage furnace, and the weigher is used for weighing the garbage when the garbage passes through the weigher;
the garbage accumulation image is formed by installing intelligent cameras at least at three angles before entering a garbage furnace hearth, and the intelligent cameras shoot garbage at least at three angles when the garbage passes by, so that a garbage accumulation image is obtained;
the garbage accumulation shape and size are obtained by combining images of at least three angles shot by an intelligent camera, so that a three-dimensional shape image of garbage and high-length and width data of garbage accumulation are obtained;
the garbage data analysis module is mainly used for analyzing the characteristics of garbage before entering a garbage furnace hearth and the characteristics of garbage after entering the garbage furnace hearth;
the garbage data analysis module comprises a pre-combustion data analysis unit and a during-combustion data analysis unit;
the system comprises a pre-combustion data analysis unit, a garbage furnace and a garbage furnace, wherein the pre-combustion data analysis unit is mainly used for analyzing the weight, the garbage accumulation image and the size of the garbage accumulation shape before garbage enters the garbage furnace;
the pre-combustion data analysis unit sends the identified main components, the garbage weight and the estimated garbage volume to the combustion control module;
the data analysis unit in combustion is mainly used for calculating the thickness of a material layer at each position in a hearth of the garbage furnace after garbage enters the hearth of the garbage furnace for combustion;
the data analysis unit in combustion collects historical feeding speed, furnace temperature, air pressure of an air chamber, grate operation period, main garbage components and estimated garbage layer thickness; training a machine learning model according to the relation between the thickness of a historical garbage material layer and the feeding speed, the temperature in the furnace, the wind pressure of an air chamber, the running period of a grate and the main components of garbage; when the garbage is actually combusted, inputting real-time feeding speed, temperature in the furnace, air pressure of an air chamber, running period of a grate and main components of the garbage by using a trained machine learning module, and obtaining the estimated thickness of a material layer;
the data analysis unit in combustion sends the estimated material layer thickness of each position to the combustion control module;
the flame analysis module is mainly used for analyzing the flame state of the garbage during combustion in the hearth of the garbage furnace;
the flame shooting module is an intelligent camera arranged outside the transparent garbage combustion furnace hearth, and the intelligent camera shoots the flame condition of garbage combustion in the garbage combustion furnace hearth in real time; the intelligent camera sends the shot flame image to the flame analysis module in real time;
the flame analysis module is mainly used for analyzing flame states of different positions in a hearth of the garbage furnace according to the flame images;
the flame analysis module collects images of flames in various garbage furnace hearths with marks in advance; the temperature of the marker is a flame; the flame analysis module takes the collected images of the flame in the hearth of the garbage furnace as input, takes the predicted flame temperature value as output and takes the actually marked flame temperature as a target value by using a CNN neural network model; targeting to minimize the difference between the predicted flame temperature and the actual flame temperature; training a CNN neural network model until the accuracy rate of prediction reaches 95%, and stopping training;
in the actual garbage combustion process, the flame analysis module estimates the flame temperature of each position in the garbage furnace hearth according to the flame image sent by the flame shooting module, and sends the predicted temperature value to the combustion control module;
the combustion control module is mainly used for controlling the combustion temperature in the hearth of the garbage furnace by controlling the feeding speed, the air inlet amount, the air pressure and the grate operation period; the stability of the combustion temperature in the hearth of the garbage furnace is ensured;
compared with the prior art, the invention has the beneficial effects that:
the method intelligently judges the main components of the garbage according to the data of the weight, the image, the shape and the size of each part of garbage collected in advance, and sets the hearth of the garbage furnace in advance according to the main components; and then, the material layer thickness and the temperature of the hearth of the garbage furnace are estimated by using a machine learning and CNN neural network model, and the hearth setting of the garbage furnace is automatically adjusted in real time according to the material layer thickness and the temperature of the hearth of the garbage furnace, so that the problems of automatically controlling the temperature of the hearth of the garbage furnace and reducing the labor cost are solved.
Drawings
Fig. 1 is a schematic diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an automatic incineration control system of a garbage furnace comprises a data collection module, a garbage data analysis module, a flame shooting module, a flame analysis module and a combustion control module; wherein, the modules are electrically connected with each other;
the data collection module is mainly used for collecting characteristic data of the garbage mixture in the garbage furnace;
the characteristic data of the garbage mixture comprise the weight of garbage entering a hearth of the garbage furnace, a garbage accumulation image and the size of a garbage accumulation shape;
the garbage weight is measured by a weighing device arranged before entering a hearth of the garbage furnace, and the weighing device is used for weighing the garbage when the garbage passes through;
the garbage accumulation image is obtained by installing intelligent cameras at least at three angles before entering a garbage furnace hearth, and shooting garbage at least at three angles by the intelligent cameras when the garbage passes through the intelligent cameras;
the garbage accumulation shape and size are obtained by combining images of at least three angles shot by an intelligent camera, so that a three-dimensional shape image of garbage and high-length and width data of garbage accumulation are obtained;
the garbage data analysis module is mainly used for analyzing the characteristics of garbage before entering a garbage furnace hearth and the characteristics of garbage after entering the garbage furnace hearth;
the garbage data analysis module comprises a pre-combustion data analysis unit and a during-combustion data analysis unit;
the system comprises a pre-combustion data analysis unit, a garbage furnace and a garbage furnace, wherein the pre-combustion data analysis unit is mainly used for analyzing the weight, the garbage accumulation image and the size of the garbage accumulation shape before garbage enters the garbage furnace;
the method for analyzing the garbage data before entering the hearth of the garbage furnace by the pre-combustion data analysis unit comprises the following steps of:
step S1: the pre-combustion data analysis unit estimates the volume of the garbage stack according to the shape and size data of the garbage stack;
step S2: the data analysis unit judges the density of the garbage according to the weight of the garbage and the volume of the garbage stacked before combustion;
step S3: the pre-combustion data analysis unit judges the most probable main components in the garbage through a CNN image recognition technology according to the image accumulated by the garbage; and further correcting the identified main components by combining the density of the garbage; the correction scheme is that when the difference between the density of the identified main component and the estimated density of the garbage is larger than a density difference threshold value rho, the pre-combustion data analysis unit continuously compares the main component with the second possibility judged by the CNN image identification technology; until the difference between the identified main component density and the estimated garbage density is smaller than a density difference threshold value rho; the density difference threshold value rho is set according to practical experience;
the pre-combustion data analysis unit sends the identified main components, the garbage weight and the estimated garbage volume to the combustion control module;
the data analysis unit in combustion is mainly used for calculating the thickness of a material layer at each position in a hearth of the garbage furnace after garbage enters the hearth of the garbage furnace for combustion;
it can be understood that when the garbage is burned in the hearth of the garbage furnace, the thickness of the garbage layer in the hearth of the garbage furnace cannot be directly measured due to overhigh burning temperature; evaluation can only be done by visual observation or by indirect means;
furthermore, in practical observation, the influence factors influencing the thickness of the material layer in each area mainly comprise the feeding speed, the temperature in the furnace, the wind pressure of the air chamber, the running period of the grate, the main components of the garbage and the like;
it can be understood that the feeding speed, the temperature in the furnace, the air pressure of the air chamber, the operation period of the grate and the main components of the garbage can be obtained in advance;
the data analysis unit in combustion collects historical feeding speed, furnace temperature, air pressure of an air chamber, grate operation period, main garbage components and estimated garbage layer thickness; training a machine learning model according to the relation between the thickness of a historical garbage material layer and the feeding speed, the temperature in the furnace, the wind pressure of an air chamber, the running period of a grate and the main components of garbage; when the garbage is actually combusted, inputting real-time feeding speed, temperature in the furnace, air pressure of an air chamber, running period of a grate and main components of the garbage by using a trained machine learning module, and obtaining the estimated thickness of a material layer;
the data analysis unit in combustion sends the estimated material layer thickness of each position to the combustion control module;
the flame analysis module is mainly used for analyzing the flame state of the garbage during combustion in the hearth of the garbage furnace;
it can be understood that the combustion sufficiency of the garbage is different according to different temperatures of the hearth of the garbage furnace, main components of the garbage and the material layer thickness of the garbage in the combustion process of the garbage; so that the flame conditions of the garbage at different positions are different; the flame condition comprises flame color and flame size;
the flame shooting module is an intelligent camera arranged outside the transparent garbage combustion furnace hearth, and the intelligent camera shoots the flame condition of garbage combustion in the garbage combustion furnace hearth in real time; the intelligent camera sends the shot flame image to the flame analysis module in real time;
the flame analysis module is mainly used for analyzing flame states of different positions in a hearth of the garbage furnace according to the flame images;
the flame analysis module collects images of flames in various garbage furnace hearths with marks in advance; the temperature of the marker is a flame; the flame analysis module takes the collected images of the flame in the hearth of the garbage furnace as input, takes the predicted flame temperature value as output and takes the actually marked flame temperature as a target value by using a CNN neural network model; targeting to minimize the difference between the predicted flame temperature and the actual flame temperature; training a CNN neural network model until the accuracy rate of prediction reaches 95%, and stopping training;
in the actual garbage combustion process, the flame analysis module estimates the flame temperature of each position in the garbage furnace hearth according to the flame image sent by the flame shooting module, and sends the predicted temperature value to the combustion control module;
the combustion control module is mainly used for controlling the combustion temperature in the hearth of the garbage furnace by controlling the feeding speed, the air inlet amount, the air pressure and the grate operation period; the stability of the combustion temperature in the hearth of the garbage furnace is ensured;
the combustion control module for controlling the combustion temperature of the hearth of the garbage furnace comprises the following steps:
step P1: before the garbage enters the garbage furnace hearth, the combustion control module estimates the air inlet amount, the air pressure and the grate operation period required in the garbage furnace hearth according to the main components of the garbage, the garbage weight and the estimated garbage volume, and correspondingly sets the garbage furnace hearth;
step P2: when rubbish burns in the rubbish furnace thorax, the material thickness of the layer of estimating and the rubbish furnace thorax temperature of estimation are closed to the combustion control module, estimate the air intake, the wind pressure and the grate operating cycle that need adjust in the rubbish furnace thorax to carry out corresponding setting to rubbish furnace thorax.
The working principle of the invention is as follows:
the data collection module is used for collecting characteristic data of the garbage mixture in the garbage furnace;
the garbage data analysis module is used for analyzing the characteristics of garbage before entering the garbage furnace hearth and the characteristics of garbage after entering the garbage furnace hearth;
the flame shooting module is an intelligent camera arranged outside the transparent garbage combustion furnace hearth, and the intelligent camera shoots the flame condition of garbage combustion in the garbage combustion furnace hearth in real time;
the flame analysis module is mainly used for analyzing the flame states of different positions in the hearth of the garbage furnace according to the flame images;
the combustion control module is mainly used for controlling the combustion temperature in the hearth of the garbage furnace by controlling the feeding speed, the air inlet amount, the air pressure and the grate operation period; the stability of the combustion temperature in the hearth of the garbage furnace is ensured.
The above formulas are all calculated by removing dimensions and taking numerical values thereof, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the closest real situation, and the preset parameters and the preset threshold value in the formula are set by the technical personnel in the field according to the actual situation or obtained by simulating a large amount of data.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the present invention.
Claims (8)
1. An automatic incineration control system of a garbage furnace is characterized by comprising a data collection module, a garbage data analysis module, a flame shooting module, a flame analysis module and a combustion control module; wherein, the modules are electrically connected with each other;
the data collection module is used for collecting characteristic data of the garbage mixture in the garbage furnace;
the garbage data analysis module is used for analyzing the characteristics of garbage before entering a garbage furnace hearth and the characteristics of garbage after entering the garbage furnace hearth; the garbage data analysis module comprises a pre-combustion data analysis unit and a during-combustion data analysis unit;
the flame shooting module is an intelligent camera arranged outside the transparent garbage combustion furnace hearth, and the intelligent camera shoots the flame condition of garbage combustion in the garbage combustion furnace hearth in real time; the intelligent camera sends the shot flame image to the flame analysis module in real time;
the flame analysis module is used for analyzing the flame states of different positions in the hearth of the garbage furnace according to the flame images;
the combustion control module is used for controlling the combustion temperature in the hearth of the garbage furnace by controlling the feeding speed, the air inlet amount, the air pressure and the grate operation period; the stability of the combustion temperature in the hearth of the garbage furnace is ensured.
2. The automatic incineration control system of the garbage furnace according to claim 1, wherein the characteristic data of the garbage mixture comprises the weight of garbage entering the hearth of the garbage furnace, the garbage accumulation image and the size of the garbage accumulation shape.
3. The automatic incineration control system of the garbage furnace according to claim 2, wherein the garbage weight is obtained by installing a weigher before entering the hearth of the garbage furnace, and the weigher is used for weighing the garbage when the garbage passes through;
the garbage accumulation image is formed by installing intelligent cameras at least at three angles before entering a garbage furnace hearth, and the intelligent cameras shoot garbage at least at three angles when the garbage passes by, so that a garbage accumulation image is obtained;
the garbage accumulation shape and size are combined through images of at least three angles shot by the intelligent camera, and a three-dimensional shape image of garbage and the length, width and height of garbage accumulation are obtained.
4. The automatic incineration control system of the garbage furnace according to claim 1, wherein the pre-combustion data analysis unit is used for analyzing the weight of garbage, the garbage accumulation image and the size of the garbage accumulation shape before the garbage enters the hearth of the garbage furnace;
the method for analyzing the weight, the garbage accumulation image and the garbage accumulation shape and size before entering the hearth of the garbage furnace by the pre-combustion data analysis unit comprises the following steps:
step S1: the pre-combustion data analysis unit estimates the volume of the garbage stack according to the shape and size data of the garbage stack;
step S2: the data analysis unit judges the density of the garbage according to the weight of the garbage and the volume of the garbage stacked before combustion;
step S3: the pre-combustion data analysis unit judges the most probable main components in the garbage through a CNN image recognition technology according to the image accumulated by the garbage; and further correcting the identified main components by combining the density of the garbage;
and the pre-combustion data analysis unit sends the identified main components, the garbage weight and the estimated garbage volume to the combustion control module.
5. The automatic incineration control system of the refuse burner according to claim 4, characterized in that the correction scheme is that when the density difference between the identified main component and the estimated refuse is greater than the density difference threshold value p, the pre-combustion data analysis unit continues to compare the main component with the second possibility judged by the CNN image identification technology; until the difference between the identified main component density and the estimated garbage density is smaller than a density difference threshold value rho; the density difference threshold value rho is set according to practical experience.
6. The automatic incineration control system of the garbage furnace according to claim 1, wherein the during-combustion data analysis unit is configured to calculate a thickness of a material bed at each position in the hearth of the garbage furnace after the garbage enters the hearth of the garbage furnace and is combusted;
the data analysis unit in combustion collects historical feeding speed, furnace temperature, air pressure of an air chamber, grate operation period, main garbage components and estimated garbage layer thickness; training a machine learning model according to the relation between the thickness of a historical garbage material layer and the feeding speed, the temperature in the furnace, the air pressure of an air chamber, the operating cycle of a grate and the main components of garbage; when the garbage is actually combusted, inputting real-time feeding speed, temperature in the furnace, air pressure of an air chamber, running period of a grate and main components of the garbage by using a trained machine learning module, and obtaining the estimated thickness of a material layer;
and the data analysis unit in combustion sends the estimated material layer thickness of each position to the combustion control module.
7. The automatic incineration control system of the garbage furnace according to claim 1, wherein the flame analysis module collects images of flames in various garbage furnace hearths with marks in advance; the temperature of the marker is a flame; the flame analysis module takes the collected images of the flame in the hearth of the garbage furnace as input, takes the predicted flame temperature value as output and takes the actually marked flame temperature as a target value by using a CNN neural network model; targeting to minimize the difference between the predicted flame temperature and the actual flame temperature; training a CNN neural network model until the accuracy rate of prediction reaches 95%, and stopping training;
in the actual garbage combustion process, the flame analysis module estimates the flame temperature of each position in the garbage furnace hearth according to the flame image sent by the flame shooting module, and sends the estimated temperature value to the combustion control module.
8. The automatic incineration control system of the garbage furnace according to claim 1, wherein the combustion control module controls the combustion temperature of the hearth of the garbage furnace comprises the following steps:
step P1: before the garbage enters the garbage furnace hearth, the combustion control module estimates the air inlet amount, the air pressure and the grate operation period required in the garbage furnace hearth according to the main components of the garbage, the garbage weight and the estimated garbage volume, and correspondingly sets the garbage furnace hearth;
step P2: when rubbish burns in the rubbish furnace thorax, the burning control module combines the bed of material thickness of estimation and the rubbish furnace thorax temperature of estimation, estimates the intake, wind pressure and the grate operating cycle that need adjust in the rubbish furnace thorax to the corresponding setting of automatically regulated rubbish furnace thorax.
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Application publication date: 20220830 |