Method for determining the thickness of the layer of a grate-type waste incinerator and related device

Abstract

The application discloses a method for determining the thickness of a material layer of a grate-type garbage incinerator and related devices, and relates to the technical field of incineration treatment. The method comprises the following steps: through a garbage layer pressure difference prediction model, two accurate parameters, i.e., a measured current primary air preheater outlet pressure and a current combustion 1 section damper opening degree, are converted into a predicted combustion 1 section garbage layer pressure difference. Based on the current combustion 1 section garbage layer pressure difference, the predicted combustion 1 section garbage layer pressure difference and a preset ratio, a combustion 1 section material layer thickness of the grate-type garbage incinerator is calculated. Based on a grate real-time running speed and a total length of the grate of the grate-type garbage incinerator and the predicted combustion 1 section material layer thickness of the grate-type garbage incinerator, a material transmission algorithm based on an Euler-Lagrange hybrid method is used to dynamically simulate and calculate the material layer thickness distribution of the whole grate, so that the material layer thickness is accurately determined, and the problem that the material layer thickness is difficult to accurately measure in a high-temperature and corrosive environment is avoided.

Description

Technical Field

[0001] This application relates to the field of incineration technology, and in particular to a method and related apparatus for determining the bed thickness of a grate-type waste incinerator. Background Technology

[0002] With the acceleration of urbanization and the continuous expansion of industrial production, grate-type waste incineration technology has become the mainstream method for solid waste treatment, and the application of grate-type waste incinerators is becoming increasingly widespread. During the incineration process, if the feed layer thickness in a grate-type waste incinerator is too thin, the furnace temperature is prone to a sudden rise, leading to grate burnout and temperature collapse; if the feed layer thickness is too thick, incomplete combustion will result in excessive emissions of pollutants. Therefore, the feed layer thickness in a grate-type waste incinerator is a core factor in ensuring stable combustion conditions.

[0003] Currently, non-contact distance sensors are typically installed at the beginning of the drying or combustion section of the incinerator. The distance sensor emits a signal to the waste surface and receives the echo. The distance from the distance sensor to the waste surface is measured by calculating the time difference, and then the thickness of the waste bed in the grate incinerator is calculated.

[0004] However, the internal environment of a grate-type waste incinerator is extremely harsh, with high temperatures, high dust levels, and corrosive gases. The detection mirror of the ranging sensor is easily contaminated, coked, or burned, causing the measurement signal to become inaccurate or completely fail, making it impossible to accurately determine the thickness of the material layer in the grate-type waste incinerator. Summary of the Invention

[0005] In view of the above problems, this application provides a method and related apparatus for determining the bed thickness of a grate-type waste incinerator, in order to accurately determine the bed thickness of the grate-type waste incinerator. The specific solution is as follows:

[0006] The first aspect of this application provides a method for determining the bed thickness in a grate-type waste incinerator, wherein the primary air system of the grate-type waste incinerator includes at least a pressure transmitter, an opening transmitter, and a differential pressure sensor, and the method includes:

[0007] The pressure transmitter is used to obtain the current primary air preheater outlet pressure of the grate-type waste incinerator, the opening degree transmitter is used to obtain the current combustion stage 1 damper opening of the grate-type waste incinerator, the differential pressure sensor is used to obtain the current combustion stage 1 waste layer differential pressure of the grate-type waste incinerator, and the real-time grate operating speed and total grate length of the grate-type waste incinerator are also obtained.

[0008] The current primary air preheater outlet pressure and the current combustion stage damper opening of the grate-type waste incinerator are input into the pre-trained waste bed pressure difference prediction model to obtain the predicted combustion stage waste bed pressure difference of the grate-type waste incinerator.

[0009] Based on the current combustion stage waste bed pressure difference of the grate-type waste incinerator, the predicted combustion stage waste bed pressure difference of the grate-type waste incinerator, and the preset ratio, the predicted combustion stage material bed thickness of the grate-type waste incinerator is calculated.

[0010] Based on the real-time operating speed and total length of the grate of the grate-type waste incinerator, and the predicted thickness of the combustion stage 1 material layer of the grate-type waste incinerator, the material layer thickness of the grate-type waste incinerator is calculated using a material transfer algorithm based on the Euler-Lagrange mixing method.

[0011] In one possible implementation, the training process of the garbage layer pressure difference prediction model includes:

[0012] Multiple training samples with labeled information are obtained. The labeled information includes the historical combustion stage waste layer pressure difference of the grate waste incinerator. Each training sample includes the historical primary air preheater outlet pressure of the grate waste incinerator and the historical combustion stage damper opening of the grate waste incinerator.

[0013] The initial waste pressure difference prediction model is trained based on multiple training samples to obtain the waste pressure difference prediction model. The input of the waste pressure difference prediction model is the current primary air preheater outlet pressure of the grate waste incinerator and the current combustion stage 1 damper opening of the grate waste incinerator. The output of the waste pressure difference prediction model is the predicted combustion stage 1 waste pressure difference of the grate waste incinerator.

[0014] In one possible implementation, after obtaining multiple training samples with labeled information, the method further includes:

[0015] Based on the historical combustion stage 1 damper opening of the grate-type waste incinerator, multiple initial sets are obtained, each including the historical primary air preheater outlet pressure of the grate-type waste incinerator and the historical combustion stage 1 waste layer pressure difference of the grate-type waste incinerator.

[0016] Based on the number of historical primary air preheater outlet pressures of the grate-type waste incinerators and the number of historical combustion stage waste pressure differences of the grate-type waste incinerators in each of the initial sets, each of the initial sets is filtered to obtain at least one candidate set.

[0017] Based on the median pressure, upper quartile pressure, lower quartile pressure, median pressure difference of the landfill layer, upper quartile pressure difference of the landfill layer, and lower quartile pressure difference of the landfill layer in each of the obtained candidate sets, the candidate sets are filtered to obtain the target set;

[0018] Based on the historical primary air preheater outlet pressure of the grate-type waste incinerator in the target set, the historical primary combustion stage waste bed pressure difference of the grate-type waste incinerator, and the historical combustion stage damper opening of the grate-type waste incinerator corresponding to the historical primary air preheater outlet pressure and the historical primary combustion stage waste bed pressure difference of the grate-type waste incinerator in the target set, a new training sample is constructed, and the new training sample is used to replace the original training sample.

[0019] In one possible implementation, the material bed thickness of the grate-type waste incinerator is calculated using a material transport algorithm based on the real-time operating speed and total length of the grate, and the predicted thickness of the combustion stage 1 material bed in the grate-type waste incinerator. This calculation includes:

[0020] The total length of the grate in the grate incinerator is discretized to obtain multiple grate grid units, including the current grate grid unit;

[0021] Based on the length of each grate grid unit, the real-time operating speed of the grate in the grate-type waste incinerator, and the preset time period, the grate movement distance is calculated.

[0022] Based on the current grate grid cell and the grate movement distance, determine the target grate grid cell and the target weight corresponding to the target grate grid cell;

[0023] Based on the predicted combustion layer thickness of the grate-type waste incinerator, the target grate grid unit, and the target weight corresponding to the target grate grid unit, the layer thickness of the grate-type waste incinerator is calculated.

[0024] In one possible implementation, the grate-type waste incinerator is connected to client equipment;

[0025] After calculating the bed thickness of the grate-type waste incinerator using a material transport algorithm based on the real-time operating speed and total length of the grate, and the predicted bed thickness of the combustion stage of the grate-type waste incinerator, the method further includes:

[0026] Determine whether the material layer thickness of the grate-type waste incinerator falls within the preset material layer thickness range;

[0027] If the bed thickness of the grate-type waste incinerator does not fall within the preset bed thickness range, an adjustment command is generated so that the client device can adjust the real-time operating speed of the grate of the grate-type waste incinerator based on the adjustment command.

[0028] A second aspect of this application provides a device for determining the bed thickness of a grate-type waste incinerator, wherein the primary air system of the grate-type waste incinerator includes at least a pressure transmitter, an opening transmitter, and a differential pressure sensor, and the device comprises:

[0029] The acquisition unit is used to acquire the current primary air preheater outlet pressure of the grate-type waste incinerator using the pressure transmitter, acquire the current combustion stage damper opening of the grate-type waste incinerator using the opening transmitter, acquire the current combustion stage waste layer pressure difference of the grate-type waste incinerator using the differential pressure sensor, and acquire the real-time grate operating speed and total grate length of the grate-type waste incinerator.

[0030] The input unit is used to input the current primary air preheater outlet pressure of the grate waste incinerator and the current combustion stage damper opening of the grate waste incinerator into the pre-trained waste bed pressure difference prediction model to obtain the predicted combustion stage waste bed pressure difference of the grate waste incinerator.

[0031] The first calculation unit is used to calculate the predicted combustion stage thickness of the grate-type waste incinerator based on the predicted combustion stage waste layer pressure difference and preset ratio.

[0032] The second calculation unit is used to calculate the material layer thickness of the grate-type waste incinerator based on the current combustion stage waste layer pressure difference, the real-time operating speed of the grate and the total length of the grate, and the predicted combustion stage material layer thickness of the grate-type waste incinerator, using a material transport algorithm based on the Euler-Lagrange mixing method.

[0033] In one possible implementation, the device further includes:

[0034] The acquisition unit is used to acquire multiple training samples with labeled information. The labeled information includes the historical combustion stage waste layer pressure difference of the grate waste incinerator. Each training sample includes the historical primary air preheater outlet pressure of the grate waste incinerator and the historical combustion stage damper opening of the grate waste incinerator.

[0035] The training unit is used to train the initial waste pressure difference prediction model based on multiple training samples to obtain the waste pressure difference prediction model. The input of the waste pressure difference prediction model is the current primary air preheater outlet pressure of the grate waste incinerator and the current combustion stage 1 damper opening of the grate waste incinerator. The output of the waste pressure difference prediction model is the predicted combustion stage 1 waste pressure difference of the grate waste incinerator.

[0036] A third aspect of this application provides a computer program product including computer-readable instructions that, when executed on an electronic device, cause the electronic device to implement the method for determining the bed thickness of a grate-type waste incinerator as described in the first aspect or any implementation thereof.

[0037] A fourth aspect of this application provides an electronic device, including at least one processor and a memory connected to the processor, wherein:

[0038] The memory is used to store computer programs;

[0039] The processor is used to execute the computer program so that the electronic device can implement the method for determining the bed thickness of the grate-type waste incinerator according to the first aspect or any implementation thereof.

[0040] The fifth aspect of this application provides a computer storage medium carrying one or more computer programs, which, when executed by an electronic device, enable the electronic device to determine the bed thickness of a grate-type waste incinerator according to the first aspect or any implementation thereof.

[0041] Using the above technical solution, this application provides a method and related apparatus for determining the bed thickness of a grate-type waste incinerator. The primary air system of the grate-type waste incinerator includes at least a pressure transmitter, an opening transmitter, and a differential pressure sensor. The method includes: using the pressure transmitter to obtain the current primary air preheater outlet pressure of the grate-type waste incinerator; using the opening transmitter to obtain the current combustion stage damper opening of the grate-type waste incinerator; and using the differential pressure sensor to obtain the current combustion stage waste bed pressure difference of the grate-type waste incinerator. The model obtains the real-time operating speed and total length of the grate in the grate-type waste incinerator. It inputs the current primary air preheater outlet pressure and the current combustion stage 1 damper opening of the grate-type waste incinerator into a pre-trained waste bed pressure difference prediction model to obtain the predicted combustion stage 1 waste bed pressure difference of the grate-type waste incinerator. Through the waste bed pressure difference prediction model, the two parameters of the easily measurable current primary air preheater outlet pressure and the current combustion stage 1 damper opening are converted into the predicted combustion stage 1 waste bed pressure difference. Based on the current combustion stage waste bed pressure difference, the predicted combustion stage waste bed pressure difference, and the preset ratio of the grate-type waste incinerator, the predicted combustion stage material bed thickness of the grate-type waste incinerator is calculated. Based on the real-time operating speed and total length of the grate of the grate-type waste incinerator, as well as the predicted combustion stage material bed thickness, a material transfer algorithm based on the Euler-Lagrange hybrid method is used to dynamically simulate and extrapolate the material bed thickness distribution throughout the grate. This avoids directly using the material bed thickness measured by the differential pressure sensor under high temperature and corrosive environment, and accurately determines the material bed thickness of the grate-type waste incinerator. Attached Figure Description

[0042] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0043] Figure 1 A flowchart illustrating a method for determining the bed thickness of a grate-type waste incinerator, provided in an embodiment of this application;

[0044] Figure 2 A schematic diagram showing the location of a pressure transmitter and an opening transmitter in a grate-type waste incinerator, provided for an embodiment of this application;

[0045] Figure 3 A schematic diagram illustrating the distribution of initial and new training samples provided for embodiments of this application;

[0046] Figure 4 This is a schematic diagram illustrating the effect of a material layer thickness provided in an embodiment of this application;

[0047] Figure 5 A schematic diagram illustrating the thickness of the material layer as a function of the grate position, provided for an embodiment of this application;

[0048] Figure 6 A schematic diagram of a device for determining the bed thickness of a grate-type waste incinerator provided in an embodiment of this application;

[0049] Figure 7 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0050] The embodiments of this application are described below with reference to the accompanying drawings. The terminology used in the implementation section of this application is for explaining specific embodiments only and is not intended to limit the scope of this application.

[0051] The embodiments of this application will now be described with reference to the accompanying drawings. Those skilled in the art will recognize that, with technological advancements and the emergence of new scenarios, the technical solutions provided in the embodiments of this application are equally applicable to similar technical problems.

[0052] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms are interchangeable where appropriate; this is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of elements is not necessarily limited to those elements, but may include other elements not explicitly listed or inherent to those processes, methods, products, or apparatuses.

[0053] To accurately determine the bed thickness of a grate-type waste incinerator, this application provides a method for determining the bed thickness of a grate-type waste incinerator. The method for determining the bed thickness of a grate-type waste incinerator provided in this application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0054] Please see the appendix Figure 1 , Figure 1 This is a flowchart illustrating a method for determining the bed thickness in a grate-type waste incinerator, as provided in an embodiment of this application. The primary air system of this grate-type waste incinerator includes at least a pressure transmitter, an opening transmitter, and a differential pressure sensor. The method may include the following steps:

[0055] Step S101: Use a pressure transmitter to obtain the current primary air preheater outlet pressure of the grate-type waste incinerator, use an opening transmitter to obtain the current combustion stage 1 damper opening of the grate-type waste incinerator, use a differential pressure sensor to obtain the current combustion stage 1 waste layer pressure differential of the grate-type waste incinerator, and obtain the real-time grate operating speed and total grate length of the grate-type waste incinerator.

[0056] It should be noted that a pressure transmitter is a commonly used measuring instrument in industrial automation. Its function is to convert the physical pressure signal of a gas or liquid into a standard, remotely transmittable electrical signal for the control system to read and display. The primary air preheater outlet pressure refers to the pressure measured in the pipeline before the primary air used for combustion in a grate-type waste incinerator enters the furnace after flowing through the air preheater (an energy-saving device that uses waste heat from flue gas to heat the combustion air). This pressure value is a key indicator of whether the air supply system can overcome the resistance of subsequent channels.

[0057] An opening transmitter is a sensor specifically designed to measure the opening degree of devices such as valves, dampers, and baffles. It converts mechanical rotational or linear position information into a standard electrical signal, allowing the control room to remotely monitor the precise opening degree of valves in real time. The grate of a waste incinerator is typically divided into multiple combustion zones along its length (e.g., drying section, combustion section 1, combustion section 2, and burnout section). The damper opening of combustion section 1 specifically refers to the current opening size of the damper controlling the airflow into the first main combustion zone, usually expressed as a percentage. It directly determines the amount of combustion air entering this zone.

[0058] A differential pressure sensor is an instrument used to measure the pressure difference between two points. Combustion section 1 is a zone in the grate, typically where the waste is dried and ignited. Waste bed pressure differential specifically refers to the pressure loss caused by the resistance overcome by primary air as it passes through the waste bed in combustion section 1. Specifically, waste bed pressure differential = pressure in the primary air chamber - pressure in the furnace. The pressure in the primary air chamber is the air pressure provided by the blower before it penetrates the waste bed; the pressure in the furnace is the ambient pressure inside the furnace after the primary air has penetrated the waste bed.

[0059] The real-time operating speed of the grate refers to the current operating speed of the mechanical grate that propels the waste from the inlet to the outlet. The speed directly determines the residence time and processing capacity of the waste in the furnace. The total length of the grate refers to the entire physical length of the grate from the waste inlet to the ash outlet. This fixed parameter, combined with the grate speed, forms the basis for calculating material transfer time and theoretical material layer distribution.

[0060] In this application, four key real-time operating parameters can be collected from the primary air system, combustion control system, and grate drive system of the incinerator. First, the outlet pressure of the primary air after the air preheater is monitored using a pressure transmitter to assess the overall power level of the air supply system. Simultaneously, the current opening of the damper controlling the airflow in the first combustion zone is read using an opening transmitter to accurately grasp the airflow status in that zone, and the current opening of the damper controlling the airflow in the first combustion zone is also read using a differential pressure sensor to accurately grasp the airflow status in that zone, thus determining the ease with which the primary air can pass over the waste in that zone. Furthermore, the system simultaneously acquires the real-time operating speed and total physical length of the grate driving the waste forward; these two parameters together form the basic framework for calculating the material residence and transport process within the furnace. This step efficiently completes the synchronous acquisition of all necessary field data, providing a solid, multi-dimensional data foundation for subsequent model-based intelligent calculations.

[0061] Step S102: Input the current primary air preheater outlet pressure and the current combustion stage damper opening of the grate waste incinerator into the pre-trained waste bed pressure difference prediction model to obtain the predicted combustion stage waste bed pressure difference of the grate waste incinerator.

[0062] In this application, the current primary air preheater outlet pressure and the current combustion stage 1 damper opening can be used as input data and fed into a pre-trained waste bed pressure difference prediction model. This model has learned from a large amount of historical operating data, gaining a deep understanding of the complex nonlinear relationship between the supply air pressure, damper opening, and the resistance generated by the waste bed. Upon receiving real-time data, the model immediately performs high-speed calculations and matching, ultimately outputting a highly reliable inference value—the predicted combustion stage 1 waste bed pressure difference. This step achieves intelligent mapping from easily measurable, accurate parameters to difficult-to-measurable, inaccurate parameters. The combustion stage 1 waste bed pressure difference refers to the expected pressure loss or resistance generated when primary air penetrates the waste bed in the combustion stage under the current operating conditions. The specific value of the pressure difference is equal to the pressure of the air before the bed minus the pressure after passing through the bed, reflecting the porosity or density of the bed, i.e., its permeability, providing a crucial intermediate variable for subsequent calculations of the bed thickness. For easier understanding, please refer to [link / reference]. Figure 2 , Figure 2 This is a schematic diagram showing the location of a pressure transmitter and an opening transmitter in a grate-type waste incinerator, as provided in an embodiment of this application.

[0063] The training process of the waste pressure difference prediction model specifically includes: obtaining multiple training samples with labeled information, including the historical combustion stage 1 waste pressure difference of the grate-type waste incinerator. Each training sample includes the historical primary air preheater outlet pressure and the historical combustion stage 1 damper opening of the grate-type waste incinerator. Based on these multiple training samples, the initial waste pressure difference prediction model is trained to obtain the waste pressure difference prediction model. The input to the waste pressure difference prediction model is the current primary air preheater outlet pressure and the current combustion stage 1 damper opening of the grate-type waste incinerator. The output of the waste pressure difference prediction model is the predicted combustion stage 1 waste pressure difference of the grate-type waste incinerator.

[0064] The initial landfill pressure differential prediction model is a pre-built, unverified machine learning framework designed to achieve a specific prediction task (predicting pressure differential from wind pressure and damper opening). It defines the possibilities for learning, while subsequent training utilizes historical data to endow it with true predictive power, transforming it into a tool usable in practical production. Common choices for this initial model include: Artificial Neural Networks: a computational model that mimics the connections of neurons in the human brain, well-suited for learning complex nonlinear relationships. It consists of an input layer, hidden layers, and an output layer; Support Vector Machines: adept at handling regression problems with high-dimensional data and small sample sizes; Random Forests: an ensemble learning algorithm that builds multiple decision trees and combines their results for prediction, typically exhibiting high robustness.

[0065] Specifically, the training of this waste pressure differential prediction model is a typical supervised learning process. First, a high-quality training dataset needs to be constructed, i.e., a large number of labeled training samples are obtained from the incinerator's historical database. Each sample is a snapshot of data at a specific historical moment, containing historical primary air preheater outlet pressure and historical combustion stage 1 damper opening as input features, along with the corresponding historical measured values ​​of the waste pressure differential during combustion stage 1. Obtaining this real pressure differential data typically requires temporary measuring instruments installed during specific periods. Subsequently, using this large number of training samples covering various operating conditions, an initial waste pressure differential prediction model is trained. Through machine learning algorithms, the internal parameters of the model are continuously adjusted to minimize the error between the predicted pressure differential and the actual historical pressure differential, ultimately resulting in a well-trained waste pressure differential prediction model that accurately captures the complex nonlinear relationship between input and output. The input interface of this trained model is defined as receiving real-time primary air preheater outlet pressure and combustion stage 1 damper opening, while its output is an accurate prediction of the waste pressure differential during combustion stage 1, which is difficult to measure directly under current operating conditions.

[0066] Furthermore, after obtaining multiple training samples with labeled information, the method may further include the following steps: Based on the historical combustion stage 1 damper opening of the grate-type waste incinerator, the historical primary air preheater outlet pressures of the grate-type waste incinerator are grouped to obtain multiple sets of historical primary air preheater outlet pressures. Based on the number of historical primary air preheater outlet pressures in each obtained set, each set of historical primary air preheater outlet pressures is filtered to obtain at least one filtered set of historical primary air preheater outlet pressures. For each filtered set of historical primary air preheater outlet pressures, based on the obtained median, upper quartile, and lower quartile of the filtered set, the historical primary air preheater outlet pressures in the filtered set are further selected to obtain the selected historical primary air preheater outlet pressures. Based on the historical primary air preheater outlet pressure after each screening, and the historical combustion stage 1 damper opening of the grate-type waste incinerator corresponding to the historical primary air preheater outlet pressure after each screening, a new training sample is constructed, and the new training sample is used to replace the original training sample.

[0067] Based on the historical combustion stage 1 air damper opening of the grate-type waste incinerator, multiple initial sets were obtained, each including the historical primary air preheater outlet pressure and the historical combustion stage 1 waste pressure difference of the grate-type waste incinerator. Based on the number of historical primary air preheater outlet pressures and historical combustion stage 1 waste pressure differences in each initial set, the initial sets were filtered to obtain at least one candidate set. Based on the median pressure, upper quartile pressure, lower quartile pressure, and waste pressure difference in each candidate set... The candidate sets are filtered using the median difference, the upper quartile of the waste pressure difference, and the lower quartile of the waste pressure difference to obtain the target set. Based on the historical primary air preheater outlet pressure and the historical primary combustion stage waste pressure difference of the grate-type waste incinerator in the target set, as well as the historical primary air preheater outlet pressure and the historical primary combustion stage waste pressure difference of the grate-type waste incinerator corresponding to the historical combustion stage damper opening of the grate-type waste incinerator in the target set, new training samples are constructed and used to replace the original training samples.

[0068] Specifically, after obtaining a large number of original training samples, this method first performs data grouping to further improve data quality and model training performance. Specifically, it divides all samples based on the key parameter of the historical combustion stage 1 damper opening. Historical data recorded under the same or similar damper openings are grouped together, thus forming multiple initial sets, each distinguished by damper opening, that include the historical primary air preheater outlet pressure and the historical combustion stage 1 waste bed pressure difference of grate-type waste incinerators. The purpose of this step is to enable a more refined analysis of the pressure data distribution characteristics under the same operating conditions (damper opening). Next, the initial sets are filtered for validity. The criterion is the number of historical primary air preheater outlet pressures and the number of historical combustion stage 1 waste bed pressure differences contained in each initial set. If the number of historical primary air preheater outlet pressures or historical waste layer pressure differentials in the initial set is too small (e.g., below a preset threshold), it is considered statistically insufficient and may not represent the stable operating state under that condition; therefore, this initial set will be filtered out. This process ensures that subsequent analyses are based only on pressure sets with sufficient data points and statistical reliability, thus eliminating noise or bias that may be introduced by data sparsity. For each filtered initial set with sufficient data, i.e., the candidate set, a robust screening strategy based on statistical distribution is employed. It first calculates three key statistics for the pressure of the candidate set: the median pressure (representing the distribution center), the upper quartile (Q3, representing the boundary of the top 25%), and the lower quartile (Q1, representing the boundary of the bottom 25%), and three key statistics for the waste layer pressure differential: the median waste layer pressure differential, the upper quartile of the waste layer pressure differential, and the lower quartile of the waste layer pressure differential. Subsequently, these statistics are used to construct a range for identifying outliers (e.g., the commonly used IQR rule, where the normal range is typically between Q1-1.5IQR and Q3+1.5IQR). Historical primary air preheater outlet pressure and historical primary combustion stage waste pressure differential within this range are retained as valid data, while outliers or exceptions significantly deviating from this range are removed. This step is crucial, as it automatically identifies and removes anomalous data points caused by instantaneous sensor false alarms, drastic process fluctuations, or other abnormal operating conditions. Then, using the high-quality historical primary air preheater outlet pressure and historical primary combustion stage waste pressure differential retained after the above rigorous grouping, filtering, and screening, along with their corresponding historical combustion stage damper openings, a completely new training sample set is reconstructed. This new sample set represents the normal operating data of the incinerator under various stable operating conditions, significantly reducing the interference of noise and outliers. Finally, this cleaned, high-quality data is used to replace the original training samples to train the waste pressure differential prediction model.This series of data preprocessing steps greatly improves the quality of the input data, laying a solid foundation for training a more accurate and reliable prediction model. For a clearer understanding, please refer to the documentation. Figure 3 , Figure 3 This is a schematic diagram illustrating the distribution of an initial training sample and a new training sample, provided for an embodiment of this application.

[0069] Step S103: Based on the current combustion stage waste bed pressure difference of the grate waste incinerator, the predicted combustion stage waste bed pressure difference of the grate waste incinerator, and the preset ratio, calculate the predicted combustion stage material bed thickness of the grate waste incinerator.

[0070] To convert the pressure difference of the waste bed in the combustion stage into the predicted bed thickness, this step introduces a pre-determined constant—a preset ratio (e.g., 1.2)—based on fluid dynamics principles and extensive operational experience in waste incineration. This ratio primarily depends on the waste's composition, density, particle size, and packing characteristics, establishing a direct linear or simple nonlinear relationship between the waste bed pressure difference and bed thickness. Physically, it can be understood as the pressure difference generated per unit bed thickness, reflecting an empirical coefficient of the waste bed's resistance characteristics. For a specific type of municipal solid waste or waste that has undergone a certain type of pretreatment, its resistance characteristics are relatively stable within a certain range. Therefore, a suitable, optimal average ratio can be determined by statistical analysis of extensive prior test data (e.g., measuring the corresponding pressure difference at different known thicknesses) for the incineration plant.

[0071] In this application, the pressure difference y of the current combustion stage 1 waste layer is... t Compared with the predicted pressure difference of the waste layer in the combustion stage 1 y pre Multiplying the ratio by the preset ratio k, the predicted thickness of the combustion stage 1 material layer y = y is obtained directly. t / y pre ×k. While mathematically simple, this step is crucial in engineering terms. It successfully circumvents the enormous difficulty of directly installing physical instruments to measure thickness in the harsh furnace environment of high temperature, dust, and corrosion, providing a low-cost, high-reliability indirect measurement scheme based on software algorithms. This offers operators a key visual indicator of the state of the combustion core zone.

[0072] Step S104: Based on the real-time operating speed and total length of the grate of the grate-type waste incinerator, and the predicted thickness of the first combustion stage material layer of the grate-type waste incinerator, the material layer thickness of the grate-type waste incinerator is calculated using a material transfer algorithm based on the Euler-Lagrange mixing method.

[0073] In this application, the total length of the grate in the grate-type waste incinerator is first discretized to obtain multiple grate grid cells, including the current grate grid cell. Then, based on the length of each obtained grate grid cell, the real-time operating speed of the grate in the grate-type waste incinerator, and a preset time period, the grate movement distance is calculated. Next, based on the current grate grid cell and the grate movement distance, the target grate grid cell and its corresponding target weight are determined. Finally, based on the predicted combustion layer thickness of the grate-type waste incinerator, the target grate grid cell, and its corresponding target weight, the complete layer thickness of the grate-type waste incinerator is calculated.

[0074] Specifically, to convert the continuously moving grate into a computer-computable model, discretization can be performed first: a continuous grate strip of length L = 10m can be uniformly divided into N = 100 grate grid units along its length, so the length of each grate grid unit is Δx = L / N = 0.1m. Since N grate grid units will generate N+1 nodes (including the start and end points), two arrays h of length N+1 can be created in the program. old and h new , where h old [i] Save the thickness of the material layer at the position i×Δx away from the start point of the grate at the previous moment, so as to realize the mapping of physical space to discrete grid and data storage.

[0075] To simulate the material movement and its resulting thickness distribution changes caused by grate movement within a very short preset time period Δt, this method does not track the movement of every piece of waste (pure Lagrangian method) nor only observe changes at fixed grid points (pure Eulerian method). Instead, it treats the material movement as equivalent to the reverse transmission of thickness values ​​on a fixed grid, which is an efficient and stable numerical method. First, the grid movement δ = (v grate ×Δt) / Δx, where v grate v is the real-time operating speed of the grate in a grate-type waste incinerator. grate ×Δt is the actual physical distance the grate moves forward within a preset time period Δt. Dividing this distance by the length Δx of each grate grid unit gives the number of grid units that the physical distance corresponds to. For easier understanding, an example is given below: v grate =2m / h, Δt=1s, Δx=0.1m. v grate =2m / h can be converted to 0.000556m / s, then δ=(0.000556m / s×1s) / 0.1m=0.00556. This means that in this 1 second, the grate movement causes the material to move backward relative to the grid by a distance of 0.00556 grids.

[0076] The material at any current grate grid cell i at the current time t is transported from the previous grate grid cell i at the previous time (t-Δt) at the position δ in front of it. Therefore, the new material layer thickness h at the current grate grid cell i is... new [i] Requires the material layer thickness distribution h from the previous time step. old The thickness of the material layer at the source point is determined. First, for the current grate grid cell i=50, the position of the source point prev... position =i-δ=50-0.00556=49.99444. Then calculate the target grate mesh element prev in front of the source point. index =floor(prev position =49, floor(x) is the floor function. Then determine the target weight w = prev position -prev index =49.99444-49=0.99444, indicating how close it is to the target grate grid cell 49. Finally, linear interpolation can be used to calculate the thickness h of the new material layer. new [i]=h old [prev index ]×(1-w)+h old [prev index +1]×w,h new

[50] =h old

[49] ×(1-0.99444)+h old

[50] ×0.99444≈h old

[49] ×0.00556+h old

[50] ×0.99444. This operation is performed once for each grate grid cell from i to N, thus completing the entire material layer thickness distribution from h. old to h new The update simulates the effect of grate movement.

[0077] To incorporate real-time, externally calculated data and ensure that the calculated bed thickness of the grate-type waste incinerator remains synchronized with the physical reality, thus preventing error accumulation, the grid index i=0 below the feed inlet at the beginning of the grate is directly overwritten with the calculated value at i=0. This forces the simulated inlet thickness to match the predicted actual thickness in each calculation cycle Δt. This ensures that any error occurs only within a single grid cell and does not accumulate or diffuse along the grate length, guaranteeing the long-term accuracy of the calculated bed thickness of the grate-type waste incinerator across the entire grate length. That is, h new [0]=h input(t) , where h input(t)Let y be the predicted combustion layer thickness of the first stage in a grate-type waste incinerator. The time interval t = t + Δt advances the simulation time, marking the end of the previous calculation cycle and the beginning of the next. old =h new The results of the current calculation are cleverly passed as the initial conditions for the next calculation, ensuring the continuity and causality of the calculation process. Without this step, each calculation would be isolated, making continuous dynamic simulation impossible. By jumping back to the first step, it makes the entire algorithm an infinite loop, thus enabling continuous, real-time simulation of the dynamic changes in the material layer thickness over time. For a clearer understanding, please refer to [link to relevant documentation]. Figure 4 , Figure 4 This is a schematic diagram illustrating the effect of a material layer thickness provided in an embodiment of this application.

[0078] By cyclically executing these four steps, the thickness of the material layer at any point on the entire grate at any time can be output. This forms a high-fidelity digital twin of the material layer thickness, providing a panoramic and real-time data foundation for subsequent automatic optimization control.

[0079] Furthermore, the grate-type waste incinerator is connected to the client equipment. After calculating the bed thickness of the grate-type waste incinerator using a material transfer algorithm based on the real-time operating speed and total length of the grate, as well as the predicted bed thickness of the combustion stage, using the Euler-Lagrange hybrid method, the method may further include the following steps: determining whether the bed thickness of the grate-type waste incinerator falls within a preset bed thickness range. If the bed thickness of the grate-type waste incinerator does not fall within the preset bed thickness range, an adjustment command is generated, causing the client equipment to adjust the real-time operating speed of the grate-type waste incinerator based on the adjustment command.

[0080] In this application, after calculating the thickness of the entire grate bed using advanced algorithms, the process goes beyond simple monitoring and incorporates automatic control logic. The calculated real-time bed thickness value is compared with a pre-set optimal operating range—a preset bed thickness interval (e.g., 1.1m-1.4m) or a danger threshold (e.g., 1.5m). This interval or danger threshold is determined based on extensive combustion experiments and operational experience, ensuring the incinerator operates efficiently, stably, and environmentally friendly. Once the system determines that the current bed thickness deviates from this optimal range or exceeds the danger threshold, it automatically triggers a control response, immediately generating a clear adjustment command. This command is transmitted via the network between the incinerator and client equipment (such as the on-site DCS distributed control system or operator station). Upon receiving the command, the client equipment can automatically or prompt the operator to adjust the critical parameter of the grate's real-time operating speed. For example, if the feed layer is too thick, the grate speed is increased to thin it; if it's too slow, the speed is decreased. This forms a complete closed loop of monitoring, calculation, judgment, and control, intelligently stabilizing the feed layer thickness within the ideal range and ensuring the optimal operating state of the grate-type waste incinerator. For easier understanding, please refer to [link / reference]. Figure 5 , Figure 5 This is a schematic diagram showing the thickness of the material layer as a function of the grate position, provided as an embodiment of this application.

[0081] In summary, this application provides a method for determining the bed thickness of a grate-type waste incinerator. The primary air system of the grate-type waste incinerator includes at least a pressure transmitter, an opening transmitter, and a differential pressure sensor. The method includes: acquiring the current primary air preheater outlet pressure of the grate-type waste incinerator using the pressure transmitter; acquiring the current opening degree of the first combustion stage damper of the grate-type waste incinerator using the opening transmitter; and acquiring the current differential pressure of the waste bed in the first combustion stage of the grate-type waste incinerator using the differential pressure sensor; and acquiring... The real-time operating speed and total length of the grate of the grate-type waste incinerator are taken. The current primary air preheater outlet pressure and the current combustion stage damper opening of the grate-type waste incinerator are input into the pre-trained waste bed pressure difference prediction model to obtain the predicted combustion stage waste bed pressure difference of the grate-type waste incinerator. Through the waste bed pressure difference prediction model, the two parameters of the current primary air preheater outlet pressure and the current combustion stage damper opening, which are easy to measure, are converted into the predicted combustion stage waste bed pressure difference. Based on the current combustion stage waste bed pressure difference, the predicted combustion stage waste bed pressure difference, and the preset ratio of the grate-type waste incinerator, the predicted combustion stage material bed thickness of the grate-type waste incinerator is calculated. Based on the real-time operating speed and total length of the grate of the grate-type waste incinerator, as well as the predicted combustion stage material bed thickness, a material transfer algorithm based on the Euler-Lagrange hybrid method is used to dynamically simulate and extrapolate the material bed thickness distribution throughout the grate. This avoids directly using the material bed thickness measured by the differential pressure sensor under high temperature and corrosive environment, and accurately determines the material bed thickness of the grate-type waste incinerator.

[0082] The above describes a method for determining the bed thickness of a grate-type waste incinerator provided by an embodiment of this application. The following will describe a device for determining the bed thickness of a grate-type waste incinerator that performs the above-described method.

[0083] Please see Figure 6 , Figure 6 This is a schematic diagram of a device for determining the bed thickness of a grate-type waste incinerator, provided in an embodiment of this application. The primary air system of the grate-type waste incinerator includes at least a pressure transmitter, an opening transmitter, and a differential pressure sensor, such as... Figure 6 As shown, the device for determining the bed thickness of the grate-type waste incinerator includes:

[0084] The acquisition unit 11 is used to acquire the current primary air preheater outlet pressure of the grate-type waste incinerator using the pressure transmitter, acquire the current combustion stage damper opening of the grate-type waste incinerator using the opening transmitter, acquire the current combustion stage waste layer pressure difference of the grate-type waste incinerator using the differential pressure sensor, and acquire the real-time grate operating speed and total grate length of the grate-type waste incinerator.

[0085] Input unit 12 is used to input the current primary air preheater outlet pressure of the grate-type waste incinerator and the current combustion stage damper opening of the grate-type waste incinerator into the pre-trained waste bed pressure difference prediction model to obtain the predicted combustion stage waste bed pressure difference of the grate-type waste incinerator.

[0086] The first calculation unit 13 is used to calculate the predicted combustion layer thickness of the grate-type waste incinerator based on the predicted combustion layer pressure difference and preset ratio of the waste layer in the first combustion stage.

[0087] The second calculation unit 14 is used to calculate the material layer thickness of the grate-type waste incinerator based on the current combustion stage waste layer pressure difference, the real-time operating speed of the grate and the total length of the grate, and the predicted combustion stage material layer thickness of the grate-type waste incinerator, using a material transport algorithm based on the Euler-Lagrange mixing method.

[0088] In one possible implementation, the device further includes:

[0089] The acquisition unit is used to acquire multiple training samples with labeled information, the labeled information including the historical combustion stage waste layer pressure difference of the grate waste incinerator, and each training sample including the historical primary air preheater outlet pressure of the grate waste incinerator and the historical combustion stage damper opening of the grate waste incinerator.

[0090] The training unit is used to train the initial waste pressure difference prediction model based on multiple training samples to obtain the waste pressure difference prediction model. The input of the waste pressure difference prediction model is the current primary air preheater outlet pressure of the grate waste incinerator and the current combustion stage 1 damper opening of the grate waste incinerator. The output of the waste pressure difference prediction model is the predicted combustion stage 1 waste pressure difference of the grate waste incinerator.

[0091] In one possible implementation, the device further includes:

[0092] The grouping unit is used to obtain multiple initial sets, each including the historical primary air preheater outlet pressure of the grate waste incinerator and the historical waste bed pressure difference of the grate waste incinerator during the first combustion stage, based on the historical combustion stage damper opening of the grate waste incinerator.

[0093] A filtering unit is used to filter each of the initial sets based on the number of historical primary air preheater outlet pressures of the grate-type waste incinerators and the number of historical combustion stage waste pressure differences of the grate-type waste incinerators in each of the acquired initial sets, to obtain at least one candidate set.

[0094] The filtering unit is used to filter each candidate set based on the median pressure, upper quartile pressure, lower quartile pressure, median pressure difference of the landfill layer, upper quartile pressure difference of the landfill layer, and lower quartile pressure difference of the landfill layer, to obtain a target set.

[0095] The construction unit is used to construct new training samples based on the historical primary air preheater outlet pressure of the grate-type waste incinerator in the target set, the historical primary combustion stage waste bed pressure difference of the grate-type waste incinerator in the target set, and the historical combustion stage damper opening of the grate-type waste incinerator corresponding to the historical primary air preheater outlet pressure and the historical primary combustion stage waste bed pressure difference of the grate-type waste incinerator in the target set, and to use the new training samples to replace the training samples.

[0096] In one possible implementation, the second computing unit 14 includes:

[0097] Discrete sub-units are used to discretize the total length of the grate of the grate-type waste incinerator to obtain multiple grate grid units, wherein the multiple grate grid units include the current grate grid unit.

[0098] The first calculation subunit is used to calculate the grate movement distance based on the length of each grate grid unit, the real-time operating speed of the grate in the grate waste incinerator, and a preset time period.

[0099] The sub-unit is determined based on the current grate grid unit and the grate movement distance to determine the target grate grid unit and the target weight corresponding to the target grate grid unit.

[0100] The second calculation subunit is used to calculate the material layer thickness of the grate-type waste incinerator based on the predicted combustion stage thickness of the grate-type waste incinerator, the target grate grid unit, and the target weight corresponding to the target grate grid unit.

[0101] In one possible implementation, the grate-type waste incinerator is connected to client equipment. The apparatus further includes:

[0102] The judgment unit is used to determine whether the thickness of the material layer in the grate-type waste incinerator falls within a preset material layer thickness range.

[0103] The generation unit is used to generate an adjustment command if the material layer thickness of the grate-type waste incinerator does not fall within a preset material layer thickness range, so that the client device can adjust the real-time operating speed of the grate of the grate-type waste incinerator based on the adjustment command.

[0104] This application also provides an electronic device in its embodiments. (See reference...) Figure 7 The diagram illustrates a structural schematic suitable for implementing the electronic device in the embodiments of this application. The electronic device in the embodiments of this application may include, but is not limited to, fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 7 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0105] like Figure 7 As shown, the electronic device may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage device 708 into a random access memory (RAM) 703. When the electronic device is powered on, the RAM 703 also stores various programs and data required for the operation of the electronic device. The processing unit 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0106] Typically, the following devices can be connected to I / O interface 705: input devices 706 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 707 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 708 including, for example, memory cards, hard drives, etc.; and communication devices 709. Communication device 709 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 7 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have alternatively.

[0107] This application also provides a computer program product including computer-readable instructions, which, when executed on an electronic device, cause the electronic device to implement a method for determining the bed thickness of any grate-type waste incinerator provided in this application.

[0108] This application also provides a computer-readable storage medium carrying one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any of the methods for determining the bed thickness of a grate-type waste incinerator provided in this application.

[0109] It should also be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the device embodiment drawings provided in this application, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines.

[0110] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, training equipment, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0111] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0112] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, training device, or data center to another website, computer, training device, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

Claims

1. A method for determining the bed thickness in a grate-type waste incinerator, characterized in that, The primary air system of the grate-type waste incinerator includes at least a pressure transmitter, an opening transmitter, and a differential pressure sensor, and the method includes: The pressure transmitter is used to obtain the current primary air preheater outlet pressure of the grate-type waste incinerator, the opening degree transmitter is used to obtain the current combustion stage 1 damper opening of the grate-type waste incinerator, the differential pressure sensor is used to obtain the current combustion stage 1 waste layer differential pressure of the grate-type waste incinerator, and the real-time grate operating speed and total grate length of the grate-type waste incinerator are also obtained. The current primary air preheater outlet pressure and the current combustion stage damper opening of the grate-type waste incinerator are input into the pre-trained waste bed pressure difference prediction model to obtain the predicted combustion stage waste bed pressure difference of the grate-type waste incinerator. Based on the current combustion stage waste bed pressure difference of the grate-type waste incinerator, the predicted combustion stage waste bed pressure difference of the grate-type waste incinerator, and the preset ratio, the predicted combustion stage material bed thickness of the grate-type waste incinerator is calculated. Based on the real-time operating speed and total length of the grate of the grate-type waste incinerator, and the predicted thickness of the combustion stage 1 material layer of the grate-type waste incinerator, the material layer thickness of the grate-type waste incinerator is calculated using a material transfer algorithm based on the Euler-Lagrange mixing method.

2. The method for determining the bed thickness of a grate-type waste incinerator according to claim 1, characterized in that, The training process of the landfill pressure difference prediction model includes: Multiple training samples with labeled information are obtained. The labeled information includes the historical combustion stage waste layer pressure difference of the grate waste incinerator. Each training sample includes the historical primary air preheater outlet pressure of the grate waste incinerator and the historical combustion stage damper opening of the grate waste incinerator. The initial waste pressure difference prediction model is trained based on multiple training samples to obtain the waste pressure difference prediction model. The input of the waste pressure difference prediction model is the current primary air preheater outlet pressure of the grate waste incinerator and the current combustion stage 1 damper opening of the grate waste incinerator. The output of the waste pressure difference prediction model is the predicted combustion stage 1 waste pressure difference of the grate waste incinerator.

3. The method for determining the bed thickness of a grate-type waste incinerator according to claim 2, characterized in that, After obtaining multiple training samples with labeled information, the method further includes: Based on the historical combustion stage 1 damper opening of the grate-type waste incinerator, multiple initial sets are obtained, each including the historical primary air preheater outlet pressure of the grate-type waste incinerator and the historical combustion stage 1 waste layer pressure difference of the grate-type waste incinerator. Based on the number of historical primary air preheater outlet pressures of the grate-type waste incinerators and the number of historical combustion stage waste pressure differences of the grate-type waste incinerators in each of the initial sets, each of the initial sets is filtered to obtain at least one candidate set. Based on the median pressure, upper quartile pressure, lower quartile pressure, median pressure difference of the landfill layer, upper quartile pressure difference of the landfill layer, and lower quartile pressure difference of the landfill layer in each of the obtained candidate sets, the candidate sets are filtered to obtain the target set; Based on the historical primary air preheater outlet pressure of the grate-type waste incinerator in the target set, the historical primary combustion stage waste bed pressure difference of the grate-type waste incinerator, and the historical combustion stage damper opening of the grate-type waste incinerator corresponding to the historical primary air preheater outlet pressure and the historical primary combustion stage waste bed pressure difference of the grate-type waste incinerator in the target set, a new training sample is constructed, and the new training sample is used to replace the original training sample.

4. The method for determining the bed thickness of a grate-type waste incinerator according to claim 1, characterized in that, The material bed thickness of the grate-type waste incinerator is calculated using a material transport algorithm based on the Euler-Lagrange mixing method, based on the real-time operating speed and total length of the grate, and the predicted thickness of the combustion stage 1 material bed of the grate-type waste incinerator. This includes: The total length of the grate in the grate incinerator is discretized to obtain multiple grate grid units, including the current grate grid unit; Based on the length of each grate grid unit, the real-time operating speed of the grate in the grate-type waste incinerator, and the preset time period, the grate movement distance is calculated. Based on the current grate grid cell and the grate movement distance, determine the target grate grid cell and the target weight corresponding to the target grate grid cell; Based on the predicted combustion layer thickness of the grate-type waste incinerator, the target grate grid unit, and the target weight corresponding to the target grate grid unit, the layer thickness of the grate-type waste incinerator is calculated.

5. The method for determining the bed thickness of a grate-type waste incinerator according to claim 1, characterized in that, The grate-type waste incinerator is connected to the client equipment; After calculating the bed thickness of the grate-type waste incinerator using a material transport algorithm based on the real-time operating speed and total length of the grate, and the predicted bed thickness of the combustion stage of the grate-type waste incinerator, the method further includes: Determine whether the material layer thickness of the grate-type waste incinerator falls within the preset material layer thickness range; If the bed thickness of the grate-type waste incinerator does not fall within the preset bed thickness range, an adjustment command is generated so that the client device can adjust the real-time operating speed of the grate of the grate-type waste incinerator based on the adjustment command.

6. A device for determining the bed thickness of a grate-type waste incinerator, characterized in that, The primary air system of the grate-type waste incinerator includes at least a pressure transmitter, an opening transmitter, and a differential pressure sensor, and the device includes: The acquisition unit is used to acquire the current primary air preheater outlet pressure of the grate-type waste incinerator using the pressure transmitter, acquire the current combustion stage damper opening of the grate-type waste incinerator using the opening transmitter, acquire the current combustion stage waste layer pressure difference of the grate-type waste incinerator using the differential pressure sensor, and acquire the real-time grate operating speed and total grate length of the grate-type waste incinerator. The input unit is used to input the current primary air preheater outlet pressure of the grate waste incinerator and the current combustion stage damper opening of the grate waste incinerator into the pre-trained waste bed pressure difference prediction model to obtain the predicted combustion stage waste bed pressure difference of the grate waste incinerator. The first calculation unit is used to calculate the predicted combustion stage thickness of the grate-type waste incinerator based on the predicted combustion stage waste layer pressure difference and preset ratio. The second calculation unit is used to calculate the material layer thickness of the grate-type waste incinerator based on the current combustion stage waste layer pressure difference, the real-time operating speed of the grate and the total length of the grate, and the predicted combustion stage material layer thickness of the grate-type waste incinerator, using a material transport algorithm based on the Euler-Lagrange mixing method.

7. The device for determining the bed thickness of a grate-type waste incinerator according to claim 6, characterized in that, The device further includes: The acquisition unit is used to acquire multiple training samples with labeled information. The labeled information includes the historical combustion stage waste layer pressure difference of the grate waste incinerator. Each training sample includes the historical primary air preheater outlet pressure of the grate waste incinerator and the historical combustion stage damper opening of the grate waste incinerator. The training unit is used to train the initial waste pressure difference prediction model based on multiple training samples to obtain the waste pressure difference prediction model. The input of the waste pressure difference prediction model is the current primary air preheater outlet pressure of the grate waste incinerator and the current combustion stage 1 damper opening of the grate waste incinerator. The output of the waste pressure difference prediction model is the predicted combustion stage 1 waste pressure difference of the grate waste incinerator.

8. A computer program product, characterized in that, Includes computer-readable instructions that, when executed on an electronic device, cause the electronic device to implement the method for determining the bed thickness of a grate-type waste incinerator as described in any one of claims 1 to 5.

9. An electronic device, characterized in that, It includes at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program so that the electronic device can implement the method for determining the bed thickness of the grate-type waste incinerator as described in any one of claims 1 to 5.

10. A computer storage medium, characterized in that, The storage medium carries one or more computer programs that, when executed by an electronic device, enable the electronic device to implement the method for determining the bed thickness of a grate-type waste incinerator as described in any one of claims 1 to 5.

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