Method and apparatus for controlling sliding speed of fire grate segment of waste incinerator

Abstract

Disclosed is a method for controlling a sliding speed of a fire grate segment of a waste incinerator, comprising the following steps: acquiring a flame image in a furnace, and determining a flame parameter of the flame image on the basis of the flame image; acquiring a parameter related to soft measurement modeling of a material layer on a fire grate segment, so as to obtain a parameter of the material layer, parameters of the material layer comprising thickness of the material layer, degree of offset between two sides of the material layer, and area of the material layer; inputting the flame parameter and the parameter of the material layer into a parameter fusion model, to generate a waste incineration parameter, and determining the speed of waste combustion on the basis of the waste incineration parameter, the waste incineration parameter being the time required for waste incineration; determining the intensity of waste combustion on the basis of the speed of waste combustion, determining the position of the flame on the fire grate segment on the basis of the intensity of waste combustion, and determining the sliding speed of the fire grate segment on the basis of the position of the flame on the fire grate segment. This resolves the problem in the prior art that it is necessary to manually determine the sliding speed required by a fire grate.

Description

Method and device for controlling sliding speed of grate piece of waste incinerator TECHNICAL FIELD

[0001] The present application relates to the technical field of waste incineration, and in particular to a method and device for controlling sliding speed of grate piece of waste incinerator. BACKGROUND

[0002] In the operation of a grate-type waste incinerator, the movement of waste on the grate needs to rely on the sliding grate, and the traditional control method requires manual adjustment of the sliding speed of the grate according to the waste being burned. Some control systems also preset the sliding speed of the sliding grate.

[0003] This method requires manual adjustment of the sliding speed of the grate according to the burning situation. On the other hand, for the sliding speed that relies on automatic adjustment of the control system, changes in the calorific value of the waste and the intensity of the burning can cause it to be unable to adapt, and ultimately manual adjustment is required. SUMMARY

[0004] The main purpose of the present application is to provide a method and device for controlling the sliding speed of the grate piece of a waste incinerator, a computer device and a storage medium, to solve the problem of manual adjustment of the sliding speed of the grate required by the prior art.

[0005] To achieve the above purpose, the present application adopts the following technical solutions:

[0006] A method for controlling the sliding speed of the grate piece of a waste incinerator, comprising the following steps:

[0007] Obtaining a flame image in the hearth, and determining a flame parameter of the flame image according to the flame image;

[0008] Obtaining parameters related to soft-sensing modeling of the charge layer on the grate piece, to obtain the parameters of the charge layer, which include the thickness of the charge layer, the degree of offset of the two sides of the charge layer and the area of the charge layer;

[0009] Inputting the flame parameter and the parameters of the charge layer into a parameter fusion model to generate a parameter of waste incineration, and determining the speed of waste combustion according to the parameter of waste incineration; wherein the parameter of waste incineration is the time required for waste incineration;

[0010] Determining the intensity of waste combustion according to the speed of waste combustion, determining the position of the flame on the grate piece according to the intensity of waste combustion, and determining the sliding speed of the grate piece according to the position of the flame on the grate piece.

[0011] In some embodiments, the obtaining of the flame image in the hearth and the determination of the flame parameter of the flame image according to the flame image comprises:

[0012] acquire a flame image through a flame sensor, pre-process the flame image to obtain a first flame image; the pre-processing includes denoising the flame image and adjusting the brightness of the flame image;

[0013] extract features from the first flame image according to a convolutional neural network to obtain feature parameters of the first flame image as feature parameters of the flame image.

[0014] In some embodiments, the step of acquiring parameters of the material layer in the hearth includes:

[0015] acquire an image of the material layer in the hearth through a digital flame camera, and extract features from the image of the material layer according to an edge algorithm to obtain first material layer image features;

[0016] determine first material layer image parameters according to the first material layer image features;

[0017] model the first material layer image parameters to calculate the thickness, humidity and area of the material layer.

[0018] In some embodiments, the step of determining flame parameters of the flame image according to the flame image further includes:

[0019] comparing the flame parameters with a preset flame threshold interval through a clustering segmentation algorithm to determine the state of the flame; when the flame parameters are greater than the preset flame threshold interval, the flame is in a first state; when the flame parameters are equal to the preset flame threshold interval, the flame is in a second state; and when the flame parameters are less than the preset flame threshold interval, the flame is in a third state.

[0020] When the flame is in the first state, the combustion is relatively intense, and at this time, the subsequent step is entered to control the intensity of combustion by adjusting the sliding speed of the grate piece;

[0021] When the flame is in the second state, the combustion is in a normal state, and the current state of garbage combustion is maintained;

[0022] When the flame is in the third state, the combustion is in an end state, and at this time, the amount of garbage to be put in is appropriately reduced or cleaning operation is performed.

[0023] In some embodiments, the intensity of garbage combustion is determined according to the speed of garbage combustion, and the sliding speed of the grate piece is determined according to the intensity of garbage combustion, including:

[0024] The intensity of garbage combustion is determined according to the speed of garbage combustion, and the sliding speed of the grate piece is determined according to the intensity of garbage combustion, including:

[0025] inputting the speed of the garbage burning into a preset neural network algorithm for calculation to obtain the intensity of the garbage burning corresponding to the flame image;

[0026] adopting a trapezoidal correction algorithm, determining an effective ROI range of the flame based on the intensity of the garbage burning, and determining an effective boundary of the flame;

[0027] dividing the effective boundary of the flame into a first flame image and a second flame image;

[0028] detecting the size of the area of the flame in the first flame image and the second image;

[0029] if the area of the flame in the first flame image is greater than the area of the flame in the second image, accelerating the speed of the grate piece sliding;

[0030] if the area of the flame in the first flame image is less than the area of the flame in the second image, slowing down the speed of the grate piece sliding.

[0031] In some embodiments, after the step of detecting the size of the area of the flame in the first flame image and the second image, the method further comprises:

[0032] if the area of the flame in the first flame image and the area of the flame in the second image, maintaining the speed of the grate piece sliding.

[0033] In some embodiments, after the step of determining the speed of the grate piece sliding according to the speed of the garbage burning, the method further comprises:

[0034] determining whether the determined speed of the grate piece sliding is in a preset range of the speed of the grate piece sliding;

[0035] if the speed of the grate piece sliding is in the preset range, maintaining the speed of the grate piece sliding;

[0036] if the speed of the grate piece sliding is not in the preset range, adjusting the speed of the grate piece sliding until the speed of the grate piece sliding is in the preset range.

[0037] The application also provides a control device for the speed of the grate piece sliding of a garbage incinerator, comprising:

[0038] a first obtaining module for obtaining a flame image in a furnace, and determining a flame parameter of the flame image according to the flame image;

[0039] a second obtaining module for obtaining a parameter of a material layer in the furnace, the parameter of the material layer including the thickness of the material layer, the humidity of the material layer, and the area of the material layer;

[0040] a fusing module for fusing the flame parameter and the parameter of the material layer to generate a parameter of the waste incineration, and determining the speed of the waste combustion according to the parameter of the waste incineration, wherein the parameter of the waste incineration is the time required for the waste incineration;

[0041] a determining module for determining the intensity of the waste combustion according to the speed of the waste combustion, and determining the sliding speed of the grate piece according to the intensity of the waste combustion.

[0042] The application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program,

[0043] The processor implements the steps of the method when executing the computer program.

[0044] The application further provides a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the method when executed by a processor.

[0045] The application has the following beneficial effects:

[0046] The application provides a control method for the sliding speed of a grate piece of a waste incinerator, which comprises the following steps: obtaining a flame image in a hearth, determining a flame parameter of the flame image according to the flame image; obtaining a parameter of a material layer in the hearth, wherein the parameter of the material layer comprises the thickness of the material layer, the humidity of the material layer and the area of the material layer; fusing the flame parameter and the parameter of the material layer to generate a parameter of the waste incineration, and determining the speed of the waste combustion according to the parameter of the waste incineration, wherein the parameter of the waste incineration is the time required for the waste incineration; determining the intensity of the waste combustion according to the speed of the waste combustion, and determining the sliding speed of the grate piece according to the intensity of the waste combustion. The method solves the problem that the sliding speed of the grate piece is manually adjusted according to the waste combustion, and the sliding speed is automatically adjusted by a control system, but the waste incinerator cannot adapt to the changes of the heat value of the waste and the intensity of the combustion, and finally the sliding speed of the grate piece needs to be manually adjusted. The method realizes the effective control of the sliding speed of the grate piece by the flame image and the parameter of the material layer in the hearth, and guarantees the full combustion of the waste and the best beneficial effect. BRIEF DESCRIPTION OF DRAWINGS

[0047] Fig. 1 is a schematic diagram of the steps of the control method for the sliding speed of the grate piece of the waste incinerator according to an embodiment of the application;

[0048] Fig. 2 is a structural block diagram of a control device for the sliding speed of the grate piece of the waste incinerator according to an embodiment of the application;

[0049] Fig. 3 is a structural schematic block diagram of a computer device according to an embodiment of the application;

[0050] Fig. 4 is a schematic block diagram of an effective boundary division structure of a flame according to an embodiment of the present application.

[0051] Reference signs: A, first flame image; B, second flame image; 1, effective boundary of flame; 2, wall; 3, flame. DETAILED DESCRIPTION

[0052] The following detailed description of the embodiments of the present application is provided. It should be emphasized that the following description is merely exemplary and is not intended to limit the scope of the present application and its applications.

[0053] The terms "first", "second" are used only for the purpose of description and should not be understood as indicating or implying relative importance or implying the number of the technical features indicated. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the embodiments of the present application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0054] For the purpose of understanding, the specific flow of the embodiments of the present application is described below. Referring to Fig. 1, Fig. 1 is a schematic diagram of the steps of the control method of the sliding speed of the grate piece of the waste incinerator according to an embodiment of the present application.

[0055] A control method of the sliding speed of the grate piece of the waste incinerator includes the following steps:

[0056] In step S101, the flame image in the hearth is acquired, and the flame parameters of the flame image are determined according to the flame image;

[0057] It can be understood that the execution subject of the present application can be a control device of the sliding speed of the grate piece of the waste incinerator, and can also be a terminal or a server, and the specific execution subject is not limited herein. The embodiments of the present application are described by taking the server as the execution subject.

[0058] Specifically, first, collect the images of the flame, use appropriate camera equipment or sensors to collect flame images inside the furnace, it should be noted that the above-mentioned camera equipment is a digital color camera. These images can capture the shape, color, brightness and other characteristics of the flame, and the collected flame images are subjected to digital image processing. This may include image enhancement, filtering, edge detection and other processing steps to improve image quality and the accuracy of flame parameter extraction. According to the processed flame image, the flame parameters are extracted by calculation and analysis. These parameters can include the area, brightness, shape, color distribution and other characteristics of the flame. The extracted flame parameters are analyzed and interpreted. Different algorithms and methods can be used to further analyze the characteristics of the flame and compare them with known flame parameter models. The flame image in the furnace can be obtained and the flame parameters can be determined. Such steps can help engineers or researchers to quantitatively analyze and evaluate the flame. According to the extracted flame parameters, the efficiency of the combustion process, the completeness of fuel combustion and possible problems (such as incomplete combustion, temperature gradient, etc.) can be inferred. This helps to optimize the combustion process, improve the design of the furnace and ensure the safety and efficiency of the combustion equipment.

[0059] In step S102, parameters related to the soft measurement modeling of the grate piece upper layer are obtained, and the layer parameters are obtained, including the thickness of the layer, the offset degree of the two sides of the layer, and the area of the layer;

[0060] Specifically, appropriate sensors or measuring devices are used to collect data on the grate piece. The data on the grate piece includes temperature, pressure, humidity, air volume and other information related to the layer. According to the data on the grate piece, the characteristic parameters related to the layer are determined. For example, the thickness of the layer can be inferred from the temperature change, the offset degree of the layer can be inferred from the change in pressure on the left and right sides of the grate, or the area of the layer can be inferred from the change in sensor data. Using the collected data and determined characteristic parameters, a soft measurement model is constructed. Various modeling techniques can be used, such as statistical regression, neural networks, support vector machines, etc. Through model training, the input data is associated with the required layer parameters, the accuracy of the constructed soft measurement model is verified, and necessary optimization is performed. Comparison between the model predicted parameters and the actual measurement results is realized. If the model predicted parameters have a small error compared with the actual measurement results, the model is reliable and accurate. Through soft measurement modeling, the prediction and estimation of layer parameters can be realized. This greatly helps to optimize the control of the upper layer of the grate piece, improves production efficiency and quality. Accurate layer parameters are used to optimize the operation of the grate piece, such as adjusting the thickness of the layer, controlling the offset degree of the layer and estimating the area of the layer. This can better control the heat conduction, combustion efficiency and material utilization of the grate piece. Overall, soft measurement modeling can improve the stability and reliability of the production process, thereby achieving better production results and cost control.

[0061] In step S103, the flame parameters and the parameters of the material layer are input into a parameter fusion model to generate the parameters of the waste incineration, and the speed of the waste combustion is determined according to the parameters of the waste incineration; wherein the parameters of the waste incineration are the time required for waste incineration.

[0062] Specifically, appropriate sensors or measuring devices are used to collect parameters related to the flame and the material layer, including the temperature of the flame, the oxygen concentration, the humidity of the waste, etc. According to the collected parameters related to the flame and the material layer, characteristic parameters related to waste incineration are determined. For example, the characteristic parameters include but are not limited to flame temperature, flame parameters, parameters of the upper material layer, and oxygen concentration. According to the flame temperature, flame parameters, parameters of the upper material layer, and oxygen concentration, the combustion state and speed of the waste are inferred. Using the collected data and the determined characteristic parameters, a parameter fusion model is constructed. Parameter fusion can use various techniques such as statistical methods, machine learning, or artificial intelligence models, etc. Through model training, the above-mentioned characteristic parameters are associated with the parameters of waste incineration. According to the output of the parameter fusion model, the time required for waste incineration is determined. The parameter fusion model is a prediction model that estimates the time required for waste incineration according to the input parameters. Through the determination of the parameter fusion model and the time required for waste incineration, the speed of waste combustion can be controlled. According to the time required for waste incineration, the waste incineration process can be effectively arranged and controlled, improving the efficiency and safety of waste incineration. The parameter fusion model can also be used to monitor and adjust the flame state and effect in real time during the waste incineration process. An accurate parameter fusion model can provide prediction and optimization of the flame combustion speed, helping to ensure full combustion and environmental friendliness of the waste incineration process.

[0063] In step S104, the intensity of the waste combustion is determined according to the speed of the waste combustion, the position of the flame on the grate piece is determined according to the intensity of the waste combustion, and the sliding speed of the grate piece is determined according to the position of the flame on the grate piece.

[0064] Specifically, the intensity of the waste combustion is determined according to the speed of the waste combustion: in the waste incinerator, the speed of waste combustion is a key indicator that directly affects the efficiency and stability of combustion. "Combustion speed" is usually indirectly estimated by measuring the heat release rate of waste per unit time or the temperature change rate in the furnace. "The intensity of combustion" is a more intuitive concept that reflects the activity level of the combustion process, such as the height of the flame, the color, the degree of turbulence, etc. A fast and stable combustion rate usually means that the combustion is more intense, while a slow one may indicate that the combustion is not sufficient or there are unburned substances. By monitoring the combustion rate in real time, the intensity of the combustion process can be evaluated, and the operating parameters can be adjusted to ensure that the combustion is neither too violent to cause control difficulties, nor too mild to affect thermal efficiency.

[0065] determine the position of the flame on the grate plate according to the intensity of the garbage burning: the position of the flame on the grate plate is an important variable in combustion control, as it is directly related to the uniformity of garbage heating and combustion efficiency. The "grate plate" is a structural component in the incinerator that carries garbage and allows air to circulate to facilitate combustion. If the burning is intense, the flame may be closer to the front end of the grate plate, because the burning speed is fast, the garbage is quickly consumed, and the flame front advances; on the contrary, when the burning is not so intense, the flame may be concentrated in the middle or rear of the grate plate. By analyzing the intensity of the burning, the control system can dynamically adjust the strategy to ensure that the flame is in the most favorable position for the garbage to burn fully, avoiding local overheating or insufficient combustion.

[0066] determine the sliding speed of the grate plate according to the position of the flame on the grate plate: the "sliding speed of the grate plate" refers to the speed at which the grate plate moves to push the garbage forward, which is crucial to maintaining the ideal thickness of the combustion layer and the surface area of the garbage in contact with oxygen. If the flame is located at the front end of the grate plate, it means that the garbage is burning too fast, so the sliding speed of the grate plate needs to be slowed down to give the garbage more time to stay in the high-temperature zone to ensure complete combustion; on the contrary, if the flame is located at the rear, it means that the burning is slow or the garbage is accumulated, so the sliding speed of the grate plate should be increased to make the new garbage enter the combustion zone faster and promote combustion. By adjusting the sliding speed of the grate plate in real time, the dynamic balance of the combustion layer can be effectively controlled, the combustion efficiency can be optimized, and the emission of pollutants can be reduced. In summary, this scheme monitors the burning speed of the garbage to determine the intensity of the burning, and then adjusts the position of the flame and the sliding speed of the grate plate, forming a closed-loop control strategy aimed at achieving efficient and environmentally friendly garbage incineration.

[0067] In the embodiment of the present application, the flame image in the hearth is obtained, the flame parameter of the flame image is determined according to the flame image, the parameter of the material layer in the hearth is obtained, the parameter of the material layer includes the thickness of the material layer, the humidity of the material layer and the area of the material layer, the flame parameter and the parameter of the material layer are fused to generate the parameter of the garbage incineration, the speed of the garbage burning is determined according to the parameter of the garbage incineration, wherein the parameter of the garbage incineration is the time of incinerating garbage, the intensity of the garbage burning is determined according to the speed of the garbage burning, and the sliding speed of the grate plate is determined according to the intensity of the garbage burning. The sliding speed of the grate plate is effectively controlled by the flame image and the parameter of the material layer in the hearth, and the garbage burning is fully and optimally ensured.

[0068] In a specific embodiment, the process of step S101 can specifically include the following steps:

[0069] (1) Obtain a flame image through a flame sensor, preprocess the flame image to obtain a first flame image; the preprocessing includes denoising the flame image and adjusting the brightness of the flame image;

[0070] (2) Extract features from the first flame image according to a convolutional neural network to obtain feature parameters of the first flame image as the feature parameters of the flame image;

[0071] (3) After the step of obtaining the flame image in the furnace and determining the flame parameters of the flame image, the process includes:

[0072] (31) Inferred motion trajectory and vibration frequency of the flame from the feature parameters of the flame image;

[0073] (32) Determine the state of the flame based on the motion trajectory and vibration frequency of the flame image.

[0074] Specifically, the flame image is obtained through a flame sensor, and the image is preprocessed. The preprocessing step can include denoising and adjusting the brightness of the image to improve image quality and processability, and extract the feature parameters of the first flame image: use convolutional neural network (CNN) and other methods to extract features from the first flame image. Convolutional neural network (CNN) can learn local and global features in the image, extract feature parameters that can represent the condition of the flame, such as the shape, color, size, etc. of the flame, and infer the motion trajectory and vibration frequency of the flame: According to the feature parameters of the first flame image, the motion trajectory and vibration frequency of the flame can be estimated by pattern matching or other inference methods. This may involve comparing the differences between image sequences, analyzing the morphological changes of the flame, etc. Based on the inferred motion trajectory and vibration frequency of the flame, the state of the flame can be determined, such as whether the flame is stable, whether there is abnormal vibration, etc. The above-mentioned flame stability is based on the change of the brightness of the flame to further confirm whether the flame is stable, and the abnormal vibration of the flame is detected by the gray value detection technology of the image to confirm whether there is smoke (short-time smoke generated when the slag is discharged from the grate) on the grate within 30s. These information can help monitor and control the state of the flame to support related applications and systems. Through the above steps, the feature parameters of the flame image can be used to infer the state of the flame, thereby realizing the monitoring and control of the flame. This technology can be applied to various fields such as industrial combustion control, fire monitoring and fire safety, etc., which helps to improve the visualization, automation and intelligence level of the flame.

[0075] In a specific embodiment, the process of performing step S102 can specifically include the following steps:

[0076] (1) obtaining an image of the material layer in the furnace by a digital flame camera, extracting features of the image of the material layer according to an edge algorithm to obtain first material layer image features;

[0077] (2) determining first material layer image parameters according to the first material layer image features;

[0078] (3) modeling the first material layer image parameters to calculate the thickness, humidity and area of the material layer.

[0079] Specifically, the material layer image is obtained and features are extracted: the image of the material layer in the furnace is obtained by an infrared image device, and the image is processed using an edge algorithm or other feature extraction method to extract features related to the material layer. These features may include the boundary, texture, color, etc. of the material layer. Determine the first material layer image parameters: based on the feature extraction results, determine the parameters of the first material layer image. These parameters can include information related to the shape, distribution, density, etc. of the material layer. The determination of parameters may involve analyzing and processing the image through measurement or mathematical calculation, modeling and calculating the thickness, humidity and area of the material layer: using the first material layer image parameters, a suitable model is established, such as through machine learning, statistical methods or mathematical models to describe the characteristics of the material layer. Then, using the established model, the thickness, humidity and area of the material layer are calculated, and these steps can help realize quantitative analysis and parameterization of the characteristics of the material layer. They can be widely used in many fields, such as furnace combustion optimization, industrial process control and environmental monitoring, etc. By quantifying the thickness, humidity and area of the material layer, etc. parameters, it can help optimize the combustion process, improve energy efficiency, and provide real-time monitoring and quality control.

[0080] The step of determining the flame parameters of the flame image according to the flame image further comprises:

[0081] (1) comparing the flame parameters with the preset flame threshold interval by a clustering segmentation algorithm to determine the state of the flame; wherein when the flame parameter is greater than the preset flame threshold interval, the flame is in a first state; when the flame parameter is equal to the preset flame threshold interval, the flame is in a second state; when the flame parameter is less than the preset flame threshold interval, the flame is in a third state;

[0082] When the flame is in the first state, the combustion is more intense;

[0083] When the flame is in the second state, the normal combustion state is maintained, and the current garbage combustion state is maintained;

[0084] When the flame is in the third state, the state of the end of combustion is ended.

[0085] Specifically, it needs to be explained that the preset flame threshold interval is +1 to +3 interval or the flame threshold is in the interval of -1 to +1 or the flame threshold is in the interval of -1 to -3. The above-mentioned preset flame threshold interval is not fixed, and is determined according to the situation. The parameters related to the flame, such as temperature, oxygen concentration, etc. are collected. The above-mentioned parameters are used to describe the state and combustion condition of the flame. According to experience or previous research, the preset threshold interval of the flame parameter is determined. The threshold interval is used to divide the flame state into three different categories. The clustering segmentation algorithm such as k-means algorithm is used to compare the flame parameter with the preset flame threshold interval. According to the position of the parameter value in the threshold interval, the flame is divided into first, second and third states. According to the result of the clustering segmentation algorithm, the state of the flame is determined. If the flame parameter is greater than the preset flame threshold interval, the flame is in the first state; if the flame parameter is equal to the preset flame threshold interval, the flame is in the second state; if the flame parameter is less than the preset flame threshold interval, the flame is in the third state. When the flame is in the first state, it indicates that the combustion is relatively intense. It can be understood that the speed of garbage burning is fast or the temperature of the flame is high. When the flame is in the second state, it indicates a normal combustion state. At this time, the current garbage burning state should be maintained. When the flame is in the third state, it indicates that the burning is about to end. In this state, the garbage has been completely burned or is about to be completely burned out, and there is little combustible material left. Such a state is directed to the bottom position of the grate piece, and there is little new garbage added. By determining the state of the flame, appropriate measures can be taken according to different situations. For example, when the flame is in the first state, the sliding speed of the grate piece is appropriately adjusted to control the intensity of the combustion. When the flame is in the third state, the amount of garbage put in is appropriately reduced or cleaning operation is performed; in general, the clustering segmentation is performed according to the flame parameter and the preset flame threshold interval, the state of the flame is classified and determined, and thus the control and optimization of the garbage incineration process are realized. Taking corresponding operations in different states helps to improve the efficiency, safety and environmental protection of garbage incineration.

[0086] Referring to FIG. 2, in a specific embodiment, the intensity of garbage burning is determined according to the speed of garbage burning, and the sliding speed of the grate piece is determined according to the intensity of garbage burning, comprising:

[0087] The speed of garbage burning is input into a preset neural network algorithm for calculation to obtain the intensity of garbage burning corresponding to the flame image;

[0088] A trapezoidal correction algorithm is adopted to determine the effective ROI range of the flame 3 and the effective boundary 1 of the flame based on the intensity of garbage burning. The wall 2 behind the flame 3 in FIG. 2 is shown.

[0089] The effective boundary 1 of the flame is divided into a first flame image A and a second flame image B;

[0090] detecting the size of the flame in the area of the first flame image and the second image;

[0091] if the area of the flame in the first flame image is larger than the area of the flame in the second image, then accelerating the speed of the grate slide;

[0092] if the area of the flame in the first flame image is smaller than the area of the flame in the second image, then decelerating the speed of the grate slide.

[0093] Specifically, the combustion speed to intensity conversion: capture the combustion speed data of the waste in the furnace, which is a basic parameter to measure the combustion process. This data is then input into a specially designed neural network algorithm model. The algorithm is trained to calculate a quantitative indicator representing the "combustion intensity" according to the speed of combustion. This means that the algorithm can understand and predict the activity level of combustion, providing a basis for subsequent decision-making. Determine the effective area of the flame: using the obtained combustion intensity information, the system uses a trapezoidal correction algorithm to accurately define the area of the flame image that is truly involved in effective combustion, i.e. the effective ROI (region of interest) of the flame. The trapezoidal correction is used here to eliminate errors caused by viewing angles or optical distortion, ensuring the accuracy of the analysis and clearly defining the actual active boundary of the flame. Subdivision analysis of the flame image: Next, the identified effective boundary of the flame is divided into two different analysis units: the first flame image and the second flame image. This division helps to further analyze the shape and intensity distribution of the flame from different local details. Area comparison and grate speed adjustment: By comparing the area size of the flame covered in the two divided images, the system can judge the balance of combustion. If the area of the flame in the first flame image is relatively large, it indicates that the combustion front is more intense or concentrated, and the system responds by speeding up the sliding speed of the grate to increase the rate of waste supply, maintaining or enhancing the current high-efficiency combustion state. Conversely, if the area of the second flame image is larger, it shows that the combustion is not concentrated enough or the efficiency is declining, and the system reduces the sliding speed of the grate to reduce the supply of waste, helping to restore the ideal combustion balance and prevent efficiency reduction or increased pollutant emissions caused by insufficient combustion. The whole process shows how to use advanced image processing technology and machine learning algorithms to intelligently control the waste incineration process, ensuring that the combustion is both efficient and environmentally friendly, while optimizing resource utilization and reducing environmental impact.

[0094] In a specific embodiment, the step of detecting the size of the flame in the area of the first flame image and the second image each further comprises the following steps:

[0095] If the area of the flame in the first flame image is equal to the area of the flame in the second flame image, the speed of the grate plate is kept unchanged.

[0096] Specifically, the area of the flame in the first flame image and the area of the flame in the second flame image are detected, and the area of the flame in the first flame image and the area of the flame in the second flame image are compared. If they are equal, the speed of the grate plate is kept unchanged. The above operation can achieve the following effects: keeping the speed of the grate plate unchanged can maintain the stable state of garbage burning, keep the flame in a relatively balanced position, and avoid excessive adjustment. If the area of the flame in the first flame image is equal to the area of the flame in the second flame image, it means that the distribution of the flame on the grate plate is relatively uniform, and there is no need to make a large adjustment of the speed of the grate plate. The garbage incineration process is stable. By keeping the speed of the grate plate stable, stable combustion conditions can be provided to ensure the continuity and controllability of the garbage incineration process. In summary, when the area of the flame in the first flame image is equal to the area of the flame in the second flame image, keeping the speed of the grate plate unchanged helps to maintain a stable garbage incineration state and ensure the continuity and effectiveness of the combustion process.

[0097] In a specific embodiment, the process of step S104 can specifically include the following steps:

[0098] (1) After the step of determining the speed of the grate plate according to the speed of the garbage burning, the following steps are included:

[0099] (11) Determine whether the determined speed of the grate plate is in a preset range of the speed of the grate plate;

[0100] (12) If the speed of the grate plate is in the preset range, the speed of the grate plate is kept unchanged. If the speed of the grate plate is not in the preset range, the speed of the grate plate is adjusted until the speed of the grate plate is in the preset range.

[0101] Specifically, whether the grate piece sliding speed is in the preset interval is determined: first, the determined grate piece sliding speed is compared with the preset interval. The preset interval can be a certain range set according to actual needs and optimization targets, and the general operation speed of the grate is 5-30 mm / s. If the determined grate piece sliding speed is already in the preset interval, it indicates that the speed has met the requirements and can remain unchanged. If the grate piece sliding speed is not in the preset interval, it needs to be adjusted. The adjustment method includes increasing or decreasing the value of the grate piece sliding speed, and the adjusted grate piece sliding speed is compared with the preset interval again. If it is still not in the preset interval, the above steps are repeated until the grate piece sliding speed is in the preset interval. Ensuring that the grate piece sliding speed is in the preset interval improves the stability and safety of the grate piece operation. By automatically adjusting the grate piece sliding speed, the system can quickly adapt to different working conditions according to actual needs, improve the efficiency of the grate operation, avoid the grate piece sliding speed exceeding the preset interval, reduce unnecessary energy consumption and equipment damage risk, and optimize the automation degree and overall performance of the waste incineration system by monitoring and adjusting the grate piece sliding speed in real time.

[0102] Referring to FIG. 3, the embodiment also provides a control device for a grate piece sliding speed of a waste incinerator, which comprises:

[0103] A first acquisition module 21 is configured to acquire a flame image in a hearth, and determine a flame parameter of the flame image according to the flame image.

[0104] A second acquisition module 22 is configured to acquire parameters related to soft measurement modeling of a material layer on a grate piece, to obtain the material layer parameters, which include the thickness of the material layer, the offset degree of the two sides of the material layer, and the area of the material layer.

[0105] A fusion module 23 is configured to input the flame parameters and the material layer parameters into a parameter fusion model to generate parameters of waste incineration, and determine the speed of waste combustion according to the parameters of waste incineration. The parameters of waste incineration are the time required for waste incineration.

[0106] A determination module 24 is configured to determine the intensity of waste combustion according to the speed of waste combustion, determine the position of the flame on the grate piece according to the intensity of waste combustion, and determine the grate piece sliding speed according to the position of the flame on the grate piece.

[0107] In the embodiment, the specific implementation of each unit in the above device embodiment is described in the above method embodiment, which will not be repeated here.

[0108] Referring to FIG. 4, the computer device in the embodiment of the present application can be a server, and the internal structure of the computer device can be as shown in FIG. 4. The computer device includes a processor, a memory, a display screen, an input device, a network interface and a database connected through a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The database of the computer device is configured to store corresponding data in the embodiment. The network interface of the computer device is configured to communicate with an external terminal through a network connection. The computer program is executed by the processor to implement the above method.

[0109] Those skilled in the art can understand that the structure shown in FIG. 4 is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied.

[0110] The embodiment of the present application further provides a computer readable storage medium having a computer program stored thereon, and the computer program is executed by the processor to implement the above method. It can be understood that the computer readable storage medium in the embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0111] The present application is described with reference to flowcharts and / or block diagrams of the method, device (system) and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more flows in the flowcharts and / or one or more blocks in the block diagrams.

[0112] The above further describes the present application in conjunction with specific / preferred embodiments, and cannot be deemed to limit the specific implementation of the present application to these descriptions. For those skilled in the art to which the present application belongs, without departing from the concept of the present application, they can make several substitutions or variations to the described embodiments, and these substitutions or variations shall be deemed to fall within the protection scope of the present application. In the description of the present application, the description of the terms "an embodiment", "some embodiments", "a preferred embodiment", "an example", "a specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are contained in at least one embodiment or example of the present application. In the present application, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In the case of no mutual contradiction, those skilled in the art can combine and combine the different embodiments or examples described in the present application and the features of the different embodiments or examples. Although the embodiments of the present application and their advantages have been described in detail, it should be understood that various changes, substitutions and modifications can be made herein without departing from the scope of protection of the patent application.

Claims

1. A method of controlling the sliding speed of a grate piece of a waste incinerator, characterized in that: The method comprises the following steps: obtaining a flame image in a furnace, determining a flame parameter of the flame image according to the flame image; obtaining a parameter related to a soft measurement modeling of a charge layer on a grate piece, obtaining the parameter of the charge layer, the parameter of the charge layer comprising a thickness of the charge layer, a deviation degree of two sides of the charge layer and an area of the charge layer; inputting the flame parameter and the parameter of the charge layer into a parameter fusion model to generate a parameter of waste incineration, determining a speed of waste combustion according to the parameter of waste incineration; wherein the parameter of waste incineration is a time required for waste incineration; determining a degree of intensity of waste combustion according to the speed of waste combustion, determining a position of the flame on the grate piece according to the degree of intensity of waste combustion, and determining a sliding speed of the grate piece according to the position of the flame on the grate piece.

2. The method of claim 1, wherein: The step of obtaining a flame image in a furnace and determining a flame parameter of the flame image according to the flame image comprises: obtaining a flame image by a flame sensor, pre-processing the flame image to obtain a first flame image, the pre-processing comprising denoising the flame image and adjusting brightness of the flame image; extracting features of the first flame image according to a convolutional neural network to obtain feature parameters of the first flame image as feature parameters of the flame image.

3. The method of claim 1, wherein: the predetermined value is a predetermined value of a sliding speed of the grate piece of the waste incinerator. The step of obtaining the parameter of the charge layer comprises: obtaining an image of the charge layer in the furnace by a digital flame camera, extracting features of the image of the charge layer according to an edge algorithm to obtain first charge layer image features; determining first charge layer image parameters according to the first charge layer image features; modeling the first charge layer image parameters to calculate the thickness of the charge layer, the humidity of the charge layer and the area of the charge layer.

4. The method of claim 1, wherein: The step of determining a flame parameter of a flame image according to the flame image further comprises: comparing the flame parameter and a preset flame threshold interval by a clustering segmentation algorithm to determine a state of the flame; wherein when the flame parameter is greater than the preset flame threshold interval, the flame is in a first state; when the flame parameter is equal to the preset flame threshold interval, the flame is in a second state; and when the flame parameter is less than the preset flame threshold interval, the flame is in a third state; when the flame is in the first state, the combustion is relatively intense, at this time, subsequent steps are entered, and the sliding speed of the grate piece is adjusted to control the degree of intensity of combustion; when the flame is in the second state, the combustion is in a normal state, and the current state of waste combustion is maintained; when the flame is in the third state, the combustion is in an end state, at this time, the amount of waste to be put is appropriately reduced or cleaning operation is performed.

5. The method of claim 1, wherein: the predetermined value is a predetermined value of a sliding speed of the grate piece of the waste incinerator. Determining a degree of intensity of waste combustion according to the speed of waste combustion and determining a sliding speed of the grate piece according to the degree of intensity of waste combustion comprises: determining a degree of intensity of waste combustion according to the speed of waste combustion, determining a sliding speed of the grate piece according to the degree of intensity of waste combustion, comprising: inputting the speed of waste combustion into a preset neural network algorithm to calculate the degree of intensity of waste combustion corresponding to the flame image; determining an effective ROI range of the flame based on the degree of intensity of waste combustion by using a trapezoidal correction algorithm to determine an effective boundary of the flame; dividing the effective boundary of the flame into a first flame image and a second flame image; detecting the size of the area of the flame in the first flame image and the second image; if the area of the flame in the first flame image is greater than the area of the flame in the second image, then accelerating the speed of the grate plate sliding; if the area of the flame in the first flame image is less than the area of the flame in the second image, then slowing down the speed of the grate plate sliding.

6. The method of claim 5, wherein: the predetermined value is a value of the sliding speed of the grate piece of the waste incinerator at which the amount of the waste is equal to or greater than the predetermined amount. after the step of detecting the size of the area of the flame in the first flame image and the second image, further comprising: if the area of the flame in the first flame image and the area of the flame in the second image, then maintaining the speed of the grate plate sliding.

7. The method of claim 1, wherein: the method further comprises: determining a target sliding speed of the grate piece; and adjusting the sliding speed of the grate piece to the target sliding speed. after the step of determining the speed of the grate plate sliding according to the speed of the garbage burning, comprising: determining whether the determined speed of the grate plate sliding is in a preset range of the speed of the grate plate sliding; if the speed of the grate plate sliding is in the preset range, then maintaining the speed of the grate plate sliding; if the speed of the grate plate sliding is not in the preset range, then adjusting the speed of the grate plate sliding until the speed of the grate plate sliding is in the preset range.

8. A control device for the sliding speed of a grate piece of a waste incinerator, characterized in that comprising: a first obtaining module, configured to obtain a flame image in a furnace, and determine a flame parameter of the flame image according to the flame image; a second obtaining module, configured to obtain a parameter of a material layer in the furnace, the parameter of the material layer including a thickness of the material layer, a humidity of the material layer, and an area of the material layer; a fusion module, configured to fuse the flame parameter and the parameter of the material layer, generate a parameter of garbage burning, and determine a speed of the garbage burning according to the parameter of the garbage burning; wherein the parameter of the garbage burning is a time required for garbage burning; a determining module, configured to determine a degree of intensity of garbage burning according to the speed of the garbage burning, and determine the speed of the grate plate sliding according to the degree of intensity of garbage burning. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8. the processor executes the computer program to implement the steps of the method of any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, the computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 7.

Images