Method and system for intelligently controlling thermal load of garbage entering furnace by utilizing garbage crane

Abstract

The invention discloses a method and system for intelligently controlling thermal load of garbage entering a furnace through a garbage crane. The method comprises the steps that the heat value of the corresponding garbage entering the furnace is calculated through boiler thermal load or generating capacity after garbage incineration; according to the combustion residence time of the garbage in the incinerator, the heat value of the garbage entering the incinerator at the moment is reversely deduced; according to the amount of the garbage entering the furnace and the heat value of the garbage entering the furnace, the garbage entering-furnace heat load is calculated; setting the optimal thermal load of the garbage entering the furnace; controlling a garbage crane to feed garbage according to the optimal thermal load of the garbage fed into the furnace, and controlling the thermal load of the garbage fed into the furnace; correcting the combustion attribute of the garbage according to the heat value of the garbage entering the furnace, and recording the original attribute and the combustion attribute of the garbage; according to the method and system for intelligently controlling the heat load of the garbage entering the furnace through the garbage crane, the heat value of the garbage entering the furnace is calculated through the heat load or the generating capacity after garbage incineration, the heat load of the garbage entering the furnace is the product of the garbage entering amount and the garbage heat value, the optimal heat load of the garbage entering the furnace is set, and the heat load of the garbage entering the furnace is intelligently controlled through the garbage crane; and stable combustion of the incinerator is ensured.

Description

Technical Field

[0001] The invention relates to a garbage incineration technology, and in particular to a method and a system for intelligently controlling the heat load of garbage entering a furnace by using a garbage crane. Background Art

[0002] At present, the garbage from the domestic waste incineration plant is sent to the garbage storage of the waste incineration plant by garbage trucks. After 3-4 days of fermentation in the garbage storage in summer and 7-8 days of fermentation in winter, the garbage crane dumps, mixes and feeds the materials to the incinerator feed port for high-temperature incineration. The garbage crane control system is a separate control system and is manually or semi-automatically operated by the garbage crane operator. Due to the complex composition of domestic garbage, high moisture content, and large changes in calorific value, the garbage crane operator can only control the amount of garbage entering the furnace, but cannot control the quality of the garbage entering the furnace according to the changes in the calorific value of the garbage to make the heat load uniform, which directly or indirectly affects the temperature and load stability of the garbage incinerator. Summary of the invention

[0003] Based on this, it is necessary to provide a method for effectively improving the incineration performance by using a garbage crane to intelligently control the heat load of the garbage entering the furnace.

[0004] A system for intelligently controlling the heat load of garbage entering the furnace by utilizing a garbage crane is also provided to effectively improve the incineration performance.

[0005] A method for intelligently controlling the heat load of garbage entering a furnace by using a garbage crane, comprising:

[0006] Calorific value calculation: Calculate the calorific value of the corresponding garbage entering the furnace through the heat load or power generation of the boiler after garbage incineration;

[0007] Reverse calculation: According to the residence time of the garbage in the incinerator, the calorific value of the garbage entering the incinerator can be calculated;

[0008] Estimation of heat load: Estimation of heat load of garbage entering the furnace based on the amount of garbage entering the furnace and the calorific value of the garbage entering the furnace;

[0009] Set the optimal heat load: Set the optimal heat load of the garbage entering the incinerator according to the MCR calorific value and garbage processing volume;

[0010] Heat load control: control the garbage crane feeding garbage according to the optimal heat load of the garbage entering the furnace, and control the heat load of the garbage entering the furnace;

[0011] Record: Correct the combustion properties of the garbage according to the calorific value of the garbage entering the furnace, and record the original properties and combustion properties of the garbage.

[0012] In a preferred embodiment, the calculation of the calorific value of the corresponding waste entering the furnace according to the heat load of the boiler includes: collecting and calculating the weight data of the waste entering the furnace, calculating the mechanical load of the corresponding waste entering the furnace,

[0013] First, in the total time T, each time qn The arithmetic mean L of the feeding weight is calculated cumulatively.

[0014]

[0015] In the above formula, each time q n The feeding weight is some non-continuous discrete data, and the method of averaging multiple values ​​within a set time period is adopted.

[0016] Pushing stroke within time T Calculate the pushing stroke and mechanical load coefficient k based on the total weight of the garbage entering the furnace.

[0017] First, based on the total time T, the push stroke l n The arithmetic mean of the total number of cumulative calculations is used as the denominator to obtain the initial mechanical load coefficient k m

[0018]

[0019]

[0020] The mechanical load coefficient k adopts the gradient iteration method of machine self-learning, and continuously iterates data in the interval from z1 to z2. By continuously adjusting the mechanical load coefficient k parameter, the k value is close to the optimal value, and then the real-time mechanical load L is converted by multiplying the push stroke l by the k coefficient. SL ,

[0021] L SL =k×l (4)

[0022] The boiler heat load is generally characterized by the boiler evaporation capacity, i.e. the main steam flow rate, as the target heat load f, combined with the above-mentioned garbage mechanical load L SL The heat load is converted into the garbage calorific value q, and the calculation formula is as follows:

[0023]

[0024] In the above formula, the calorific value of garbage q is the difference between the total energy produced and the total energy input divided by the mechanical load L SL , that is, boiler heat load f and steam enthalpy H 汽 The product of energy, slag loss Q 潜损 Energy, other boiler steam losses Q 汽损 Equal the total, then subtract the water flow rate F 水 and feed water enthalpy H 水 The product of energy and air flow rate F 风 and air enthalpy H 风 The energy of the product is then divided by the mechanical load L of the garbage sent in. SL .

[0025] In a preferred embodiment, the calculation of the calorific value of the corresponding garbage fed into the furnace according to the power generation includes:

[0026] The benefit analysis of heat energy utilization of waste incineration is characterized by the power generation per ton of waste table, and its relationship with the calorific value of the waste entering the furnace is:

[0027]

[0028] In the above formula, the unit of power generation per ton of garbage is kWh / t garbage, and the calorific value of the garbage entering the furnace is (kj / kg)×1000kg / t; the calorific value of the garbage entering the furnace is calculated as

[0029]

[0030] In a preferred embodiment, the heat load control is as follows: according to the optimal heat load of the garbage entering the furnace, the garbage hanging and mixing materials are controlled to reach the optimal garbage entering the furnace calorific value and feeding amount, and the mixing ratio is carried out according to the calorific value of the garbage entering the furnace, and the garbage is controlled to be incinerated in the normal incineration area. If the calorific value of the garbage in a certain area is low, the garbage in the high calorific value area is grabbed and put into the mixture and then put into the mixture; if the calorific value of the garbage in a certain area is high, the garbage in the low calorific value area is grabbed and put into the mixture and then put into the mixture.

[0031] In a preferred embodiment, the heat load control further comprises: performing weighted averaging on the calorific value of the garbage, including:

[0032] The garbage storage area is divided into m×n grid partitions on the horizontal plane, where m is the number of grids in the x-direction of the moving distance coordinate of the garbage crane, and n is the number of grids in the y-direction of the moving distance coordinate of the garbage crane. Each small square forms a matrix, as shown in the following formula:

[0033]

[0034] In the above formula, the m×n grid A matrix, A ij is one of the elements, i / j are i∈m and j∈n respectively, i / j / m / n are all positive integers, and generally 2 to 5m is a span.

[0035] When the grab is working, the x / y coordinate data of the operating point corresponds to a certain gridded block A. ij , is within the coordinate range of an element in the matrix;

[0036] When the garbage is stored or dumped, a certain A ij The garbage is stored under the grid area for natural fermentation, and then the height z coordinate is located at the h' layer of the height grid. ij-h‘ In the small cube, a new element is formed in the three-dimensional matrix structure of m×n×h, namely, an A ij-h‘Small cubes, where h'∈h, are all positive integers, generally 2 to 5 meters across. It is garbage A ij The height h' layer under the grid area takes the stacking time as the starting point and the natural time advancement as the increasing function of the fermentation degree as the temporal characteristics of the garbage fermentation at this point.

[0037] The time domain function of garbage fermentation is:

[0038] J(A ij-h‘ ) = k t ×ξ×t k ×F(DT1-DT0) (7)

[0039] In the above formula, garbage A ij-h‘ The fermentation degree of the block J(A ij-h‘ ), with its own garbage properties ξ, storage area ambient temperature t k The natural fermentation time function F(DT1-DT0) is a positive function of the difference between the current time DT1 and the stacking start time DT0. Garbage fermentation is also related to the garbage thickness, storage temperature, and internal bacterial flora. The fermentation coefficient k is used. t To characterize;

[0040] If the internal factors of garbage fermentation cannot be calculated, then ξ*t k =1 as a premise, that is, the comprehensive relationship of related factors is 1, requiring the garbage fermentation degree J(A ik-h‘ )=1 means the fermentation is normal, then we can calculate: in summer, the stacking time is 3 to 4 days, then k t =0.25~0.33; in winter, the stacking time is 7~8 days, then k t =0.125~0.143. When the two-season coefficient k t When the change exceeds 1.8 times, the following method is used;

[0041] The time domain calculation method of natural fermentation of garbage is used for each garbage A ij-h‘ Block fermentation calculation, as the original data of the benchmark, is used to calculate the garbage fermentation coefficient k according to the calorific value in the garbage combustion properties t , using the convolution calculation method and coefficient k in AI calculation t Iterative method, the calculation process is as follows:

[0042] From the surface area of ​​the garbage feeding area, when the grid division is

[0043] matrix

[0044] With the convolution matrix or The average of the products of , B is a matrix of (2N+1) rows multiplied by (2N+1) columns, N = 1, 2, 3..., and the average calorific value formula is obtained:

[0045]

[0046] Among them A ij Garbage fermentation coefficient k at h' height under the grid t is the average value of the convolution of the B matrix centered at (ij). When (ii) is followed by multiple feedings and multiple returns, the calorific value of the garbage is continuously updated, and the calculation process is continuously iterated, so that the garbage fermentation coefficient k t More accurate, the corresponding data is transmitted to the grid management information of the reservoir area for storage, and is calculated based on multiple coefficients every month or every 15-20℃ change in ambient temperature, that is, the garbage fermentation coefficient k t1 , k t2 , k t3 ...respectively represent the fermentation coefficient under the factors of month, external atmospheric environment or internal environment of garbage bin, and are called according to the corresponding database storage location.

[0047] In a preferred embodiment, the heat load control also includes: a comprehensive evaluation of the deviation calculation and comparison based on the calorific value corresponding to the fermentation degree and the calorific value of the garbage returned after incineration, the residence time from the time the garbage is put into the incinerator to the completion of combustion is 1.5-2 hours; when calculating the arithmetic mean value L, the time period used is 3.5-4.5 hours each time q n The feeding weight is averaged over multiple values.

[0048] In a preferred embodiment, in the heat load control, the comprehensive evaluation of the deviation calculation and comparison between the calorific value corresponding to the fermentation degree and the calorific value of the garbage returned after incineration is as follows:

[0049]

[0050] To calculate the same A ij The deviation between the fermentation degree of the garbage in the grid and the heat return value of garbage incineration, that is, the heat return value of garbage incineration is used as the reference value, and the estimated garbage fermentation degree is used as the evaluation object. When the ratio is within the set range, it is normal data, otherwise the fermentation degree coefficient is corrected.

[0051] In a preferred embodiment, setting the optimal heat load also includes: setting the optimal heat load of the garbage entering the furnace through a supervised learning regression algorithm in artificial intelligence machine learning, setting the garbage input weight and the garbage calorific value as input objects, taking the input garbage heat load as the expected output value, analyzing the training data, and generating inferences.

[0052] In a preferred embodiment, the record includes: in the storage area grid management information, the m×n matrix is ​​used as an object to store data, that is, A ij The block is considered as a data storage unit of this matrix, and in the database it is considered as a unit with Aij The data information of the identity tag stores the original properties and combustion properties of the garbage. When the grab bucket of the garbage crane moves, it includes the following states: First, grabbing the material, then the grabbing time, weight, height, and action information are recorded to the relevant A ij In the grid; the second is the interval material pouring work, then A ij The original attributes and action information of the grid garbage are transferred to B i′j′ The corresponding grid of the discharge point, that is, all the information of the garbage at the material grabbing point A is transferred to the information at the discharge point B, that is, the original attributes and action information are transferred accordingly; the third is the feeding work, then A ij The original attributes and action information of the grid garbage are stored in the historical database with time and action tags, that is, the grab material A ij Click on all the information of the garbage + the historical data information of the combustion calorific value returned after the burning time.

[0053] In a preferred embodiment, the original attributes of the garbage include: one or more of the time, source, and type of garbage entering the factory; the combustion attributes of the garbage include: the fermentation degree during natural fermentation, garbage calorific value information, and garbage feeding and collection area point information; the garbage calorific value information includes the calorific value of the garbage returned from combustion, SO2, and HCl; the garbage feeding and collection area point information includes: one or more of time, source point, grabbing warehouse area coordinate system, and feeding amount.

[0054] A system for intelligently controlling the heat load of garbage entering a furnace by using a garbage crane, comprising:

[0055] Calorific value calculation module: calculates the calorific value of the corresponding garbage entering the furnace through the heat load or power generation of the boiler after garbage incineration;

[0056] Reverse calculation module: according to the burning residence time of garbage in the incinerator, the calorific value of the garbage entering the incinerator at that time can be calculated;

[0057] Heat load estimation module: Calculate the heat load of garbage entering the furnace based on the amount of garbage entering the furnace and the calorific value of the garbage entering the furnace;

[0058] Setting the optimal heat load module: Setting the optimal heat load of the garbage entering the incinerator according to the MCR calorific value and garbage processing volume;

[0059] Heat load control module: control the garbage crane feeding garbage according to the optimal heat load of the garbage entering the furnace, and control the heat load of the garbage entering the furnace;

[0060] Recording module: Modify the combustion properties of garbage according to the calorific value of the garbage entering the furnace, and record the original properties and combustion properties of the garbage.

[0061] The above-mentioned method and system for intelligently controlling the heat load of garbage entering the furnace by using a garbage crane, according to thermodynamic calculations, can infer the calorific value of the corresponding garbage entering the furnace through the heat load or power generation after garbage incineration, and the heat load of garbage entering the furnace is the relationship between the amount of garbage entering the furnace and the product of the calorific value of the garbage. If the calorific value of the garbage increases, the amount of garbage entering the furnace decreases, and if the calorific value of the garbage decreases, the amount of garbage entering the furnace increases. The supervised learning regression algorithm in artificial intelligence machine learning is used to set the optimal heat load of the garbage entering the furnace according to the MCR target calorific value of the garbage incinerator and the garbage processing volume, guide the garbage crane to learn operating skills and optimize the calorific value mixing and garbage weight, and intelligently realize the garbage crane to control the heat load of the garbage entering the furnace, ensure stable combustion of the incinerator, and help to increase the heat load of the boiler and the power generation of the whole plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a flow chart of a method for intelligently controlling the heat load of garbage entering a furnace by using a garbage crane according to an embodiment of the present invention;

[0063] Figure 2 This is a principle block diagram of a method for intelligently controlling the heat load of garbage entering a furnace by using a garbage crane according to a preferred embodiment of the present invention;

[0064] Figure 3 This is a garbage combustion property calculation process according to an embodiment of the present invention;

[0065] Figure 4 A coordinate diagram of a garbage crane position according to an embodiment of the present invention;

[0066] Figure 5 A schematic diagram of a gridded garbage storage according to an embodiment of the present invention;

[0067] Figure 6 A three-dimensional schematic diagram of a garbage storage grid according to an embodiment of the present invention;

[0068] Figure 7 This is a combustion load diagram of an incinerator according to an embodiment of the present invention. DETAILED DESCRIPTION

[0069] like Figure 1 to Figure 2 As shown, a method of intelligently controlling the heat load of garbage entering a furnace by using a garbage crane of the present invention comprises:

[0070] Step S101, calorific value calculation: calorific value of the corresponding waste entering the furnace is calculated by the heat load or power generation of the boiler after the waste incineration;

[0071] Step S103, reverse calculation: according to the residence time of the garbage in the incinerator, the calorific value of the garbage entering the incinerator at that time is reversed;

[0072] Step S105, calculating the heat load: calculating the heat load of the garbage entering the furnace according to the amount of garbage entering the furnace and the calorific value of the garbage entering the furnace;

[0073] Step S107, setting the optimal heat load: setting the optimal heat load of the garbage entering the incinerator according to the MCR calorific value and the garbage processing volume;

[0074] Step S109, heat load control: control the garbage crane to feed the garbage according to the optimal heat load of the garbage entering the furnace, and control the heat load of the garbage entering the furnace;

[0075] Step S111, recording: correcting the combustion properties of the garbage according to the calorific value of the garbage entering the furnace, and recording the combustion properties of the garbage.

[0076] The MCR calorific value of this embodiment refers to the calorific value of the waste incinerator under the maximum continuous operation (Maximum Continuous Rating, MCR) state.

[0077] Furthermore, in step S101 of this embodiment, in the calorific value calculation step, the calorific value of the corresponding garbage entering the furnace is calculated according to the boiler thermal load and the mechanical load, including: collecting and calculating the weight data of the garbage entering the furnace, and calculating the mechanical load of the corresponding garbage entering the furnace.

[0078] First, in the total time T, each time q n The arithmetic mean L of the feeding weight is calculated cumulatively.

[0079]

[0080] In formula (1), for each q n The arithmetic mean L of the cumulative weight of the feed is calculated. n The feeding weight is some non-continuous discrete data, and a method of averaging multiple values ​​within a certain time period, preferably, generally taking 3.5-4.5 hours. Preferably, a method of averaging multiple values ​​collected within 4 hours can be taken.

[0081] Since the time is long, it is not conducive to the continuous calculation of the calorific value of garbage. This embodiment adopts an artificial intelligence data processing method to push the material through a period of time T. The k coefficient of the relationship between the pushing stroke and the mechanical load is calculated based on the total weight of the garbage entering the furnace, so that the machine can self-learn and perform real-time calculations. The details are as follows:

[0082]

[0083] Formula (2) is based on the total time T in formula (1) for the push stroke l n The arithmetic mean of the total number of cumulative calculations is used as the denominator to obtain the initial mechanical load coefficient k m .

[0084]

[0085] The mechanical load k coefficient is a machine self-learning gradient iteration method using formula (3). Data is continuously iterated in the interval from z1 to z2. The k value is made close to the optimal value by continuously adjusting the mechanical load k coefficient parameters, thereby obtaining the optimal formula (4). The push stroke l multiplied by the k coefficient is directly converted into the real-time mechanical load L SL Model.

[0086] L SL =k×l (4)

[0087] The boiler heat load is generally characterized by the boiler evaporation capacity, i.e. the main steam flow rate, as the target heat load f, combined with the above-mentioned garbage mechanical load L SL The heat load is converted into the garbage calorific value q, and the calculation formula is as follows:

[0088]

[0089] The calorific value of the garbage in formula (5) is the difference between the total energy produced and the total energy fed divided by the weight of the garbage, that is, the boiler heat load f and the thermal enthalpy H of the steam. 汽 The product of energy, slag loss Q 潜损 Energy, other boiler steam losses Q 汽损 Equal the total, then subtract the water flow rate F 水 and feed water enthalpy H 水 The product of energy and air flow rate F 风 and air enthalpy H 风 The energy of the product is then divided by the amount of garbage sent in, the mechanical load L SL This calculation process is based on unit time. Based on the above partial data calculation, the garbage incineration control system or this system can directly calculate and output after collecting relevant data during the boiler combustion process.

[0090] Furthermore, in step S101 of this embodiment, in the calorific value calculation step, the calorific value of the corresponding garbage entering the furnace is calculated according to the power generation, including:

[0091] The benefit analysis of heat energy utilization of waste incineration is characterized by the power generation per ton of waste table, and its relationship with the calorific value of the waste entering the furnace is:

[0092]

[0093] In formula (9), the unit of power generation per ton of garbage is kWh / t garbage, and the calorific value of the garbage entering the furnace is (kj / kg)×1000kg / t; the calorific value of the garbage entering the furnace is calculated as

[0094]

[0095] According to formula (10), its real-time calorific value can be calculated by empirical method.

[0096] Furthermore, in step S109 of this embodiment, the heat load control also includes: controlling the garbage hanging and mixing material grabbing to achieve the optimal garbage entering the furnace calorific value and feeding amount according to the optimal heat load of the garbage entering the furnace, mixing the materials according to the calorific value of the garbage entering the furnace, and controlling the garbage to be incinerated in the normal incineration area. If the calorific value of the garbage in a certain area is low, grab the garbage in the high calorific value area and mix it with it before putting it in; if the calorific value of the garbage in a certain area is high, grab the garbage in the low calorific value area and mix it with it before putting it in.

[0097] like Figure 7 As shown, the calorific value grade can be specifically determined by the lines q1 to q3 in the figure. For example, those close to the q1 line have higher calorific value, and those exceeding the q1 line have high calorific value; those close to the q3 line have lower calorific value, and those below the q3 line have poor or low calorific value; those on the q2 line are the best, and those close to the q2 line are all better.

[0098] according to Figure 7 The calorific value after the incineration line can be fitted with this graph, and the area where the calorific value point is located can be used to evaluate the calorific value status of the garbage.

[0099] Garbage calorific value mixing means mixing the garbage calorific value corresponding area of ​​the upper part of q2 with the area below it, so that its line is as close to the q2 line as possible. It is also possible to mix the garbage of the q4 line with the corresponding area close to the q1 line, so that it is in the normal combustion area. It is also possible to mix the garbage of the q4 line with the corresponding area on the q1 line, so that it is in the normal combustion area. Different calorific values ​​correspond to different garbage storage areas, and the garbage mixing of these areas is carried out by grabbing and mixing materials with garbage cranes.

[0100] The garbage storage area can be divided into multiple functional areas, such as Area A for fermentation, Area B for fermented material feeding area, Area C for new garbage stacking area, Area D for other industrial material area, etc. The garbage in these areas has different calorific value qualities.

[0101] When the feeding area of ​​zone B is finished, it will be turned into the stacking area. If it is full, it will be turned into the fermentation area. After the fermentation is completed, it will become the feeding area, and it will run in a cycle. Generally, the area where new garbage and stale garbage are stored is considered to be a low calorific value area; fermented and industrial garbage is considered to be a high calorific value area. When a certain area completes a certain function, its role can be automatically converted or manually changed through the garbage storage management. In the automatic control of the garbage crane, work tasks can be automatically assigned according to the role of a certain area.

[0102] When the calorific value of garbage in a certain area is low, it is necessary to grab garbage from a high calorific value area and mix it with it before adding it. Only after the good and the bad are mixed can the combustion requirements be met. This process is called mixing.

[0103] The ratio of garbage in the mixing material is determined by the combined effect of the calorific value of the fermentation degree and the calorific value returned by combustion.

[0104] Furthermore, in step S109 of this embodiment, the heat load control further includes: performing weighted averaging on the calorific value of the garbage, including:

[0105] The garbage storage area is divided into mm×nn grid partitions on the horizontal plane, where m is the number of grids in the x-direction of the moving distance coordinate of the garbage crane, and n is the number of grids in the y-direction of the moving distance coordinate of the garbage crane. Each small square forms a matrix, as shown in the following formula:

[0106]

[0107] Formula (6), the m×n grid matrix A, A ij is one of the elements, i / j are i∈m and j∈n respectively, i / j / m / n are all positive integers, and the division standard is that each grid is sufficient to define the state of its reservoir area. Generally, a span of 2 to 5m is appropriate for one grid. If it is too small, the amount of data will increase geometrically, and if it is too large, it will not be enough to characterize the local state.

[0108] When the grab is working, the x / y coordinate data of the operating point corresponds to a certain gridded block A. ij , is within the coordinate range of an element in the matrix. Figures 4 to 5 shown.

[0109] In the grid management information of the reservoir area, the m×n matrix is ​​used as the object for data storage, that is, the above-mentioned A ij The block is considered as a data storage unit of this matrix, and in the database it can be considered as a ij The data information strip of the identity tag stores new field information of the original attributes and combustion attributes of the garbage.

[0110] When the grab bucket of the garbage crane moves, there are mainly the following states: one is grabbing material, then the grabbing time, weight, height, action and other action information are recorded to the relevant A ij In the grid; the second is the interval material pouring work, then A ij The original attributes and action information of the grid garbage are transferred to B i′j′ The corresponding grid of the discharge point, that is, all the information of the garbage at the material grabbing point A is transferred to the information at the discharge point B, that is, the original attributes and action information are transferred accordingly; the third is the feeding work, then A ij The original attributes and action information of the grid garbage are stored in the historical database with time and action tags, that is, the grab material A ij Click on all the information of the garbage + historical data information of the calorific value (including SO2 and HCl) returned after a combustion time of 1.5 to 2 hours.

[0111] like Figure 6 As shown, when garbage is stored or dumped, a certain A ijThe garbage stored under the grid area is naturally fermented, and then the A layer of the h' layer of the height grid where the height z coordinate is located is ij-h′ In the small cube, a new element is formed in the three-dimensional matrix structure of m×n×h, namely, an A ij-h′ Small cubes, where h'∈h, are all positive integers, generally 2 to 5 meters across. It is garbage A ij The height h' layer under the grid area takes the stacking time as the starting point and the natural time as the increasing function of the fermentation degree as the time domain characteristics of the garbage fermentation at this point, which can be the expert experience data characteristics. ij-h′ Small cubes such as Figure 6 shown.

[0112] The time domain function of garbage fermentation is:

[0113] J(A ij-h′ ) = k t ×ξ×t k ×F(DT1-DT0) (7)

[0114] In formula (7), A ij-h′ The fermentation degree of garbage in the block J(A ij-h′ ), the garbage properties (such as type) ξ, the ambient temperature of the storage area t k There is a direct relationship between the natural fermentation time function F(DT1-DT0) and the difference between the current time DT1 and the stacking start time DT0. However, garbage fermentation is also directly related to the garbage thickness, storage temperature, internal bacterial flora, etc., so the fermentation coefficient k is used. t Characterization. Fermentation coefficient k t , can be calculated based on empirical values. If the internal factors of garbage fermentation cannot be calculated, then ξ×t k =1 as a premise, that is, the comprehensive relationship of related factors is 1, requiring the garbage fermentation degree J(A ij-h′ )=1 means the fermentation is normal, then we can calculate: in summer, the stacking time is 3 to 4 days, then k t =0.25~0.33; in winter, the stacking time is 7~8 days, then k t =0.125~0.143. When the two-season coefficient k t If the change exceeds 1.8 times and reaches nearly 2 times, this can only be calculated theoretically and cannot meet the requirements of accurate calculation. In this case, the following method is used.

[0115] The time domain calculation method of natural fermentation of garbage is used for each garbage A ij-h′ The block can be used for fermentation calculation and can be used as the original data for calculation. Its accuracy is mainly determined by the fermentation coefficient k tIn this embodiment, the garbage fermentation data is calculated by combining the calorific value in the garbage combustion attribute, and the convolution calculation method and coefficient iteration method in AI calculation are adopted. On the one hand, the balance of calculation is ensured, and on the other hand, the fermentation coefficient is continuously updated and more accurate. The calculation process is as follows:

[0116] It is carried out from the surface area of ​​the garbage feeding area. When the grid partition is the above formula

[0117] matrix

[0118] With the convolution matrix or The average of the products of , B is a matrix of (2N+1) rows multiplied by (2N+1) columns, N = 1, 2, 3..., and the average calorific value formula is obtained:

[0119]

[0120] Among them A ij Garbage fermentation coefficient k at h' height under the grid t is the average value of the convolution of the B matrix centered at (ij). When (ii) is only followed by multiple feedings and multiple returns, the calorific value of the garbage is continuously updated, and the calculation process is continuously iterated, so that the garbage fermentation coefficient k t It is more accurate. AI machine self-learning function can be used. The corresponding data is transmitted to the grid management information of the warehouse area for storage, so that the intelligent garbage crane can automatically control the data guidance of the calorific value.

[0121] In order to prevent the garbage fermentation coefficient k t If it contains iterative data of different seasons, the actual operation is calculated based on multiple coefficients per month or every 15-20℃ change in ambient temperature, that is, the garbage fermentation coefficient k t1 , k t2 , k t3 ...respectively represent the fermentation coefficient under the factors of month, external atmospheric environment or environmental factors in the garbage bin, and can be called according to the corresponding database storage location.

[0122] The fermentation coefficient is a parameter used in digital information systems to measure the trend of natural fermentation of garbage. It is related to the ambient temperature. The degree of garbage fermentation corresponds to the calorific value of garbage. The fermentation coefficient can be corrected according to the calorific value returned after the garbage is burned. tIt is related to the ambient temperature. The natural fermentation time and the temperature of the actual fermentation block are positively correlated. The fermentation coefficient is calculated by returning the calorific value once, and then returning to calculate again. Each calculation is based on the correction of the previous one. The more sample data is calculated, the higher the accuracy. The fermentation coefficient is calculated for the prediction of the calorific value of garbage. The ratio of garbage to the garbage suspension mix is ​​based on the combined effect of the fermented calorific value and the returned calorific value. The higher the accuracy of the fermentation coefficient, the more accurate the prediction of the calorific value of the garbage in the fermentation area. This part is not put into garbage incineration and has no returned calorific value.

[0123] The calorific value of garbage is calculated by weighted average, which mainly solves the problem that the calorific value generated by garbage in each grid block may have large calculation deviation due to factors such as the garbage not being mixed evenly, the weighing error of the garbage crane, and the accidental factors of the combustion process. The convolution matrix can be used To perform secondary calculation on the surrounding blocks and obtain the relevant mean, it is beneficial to the following comprehensive evaluation.

[0124] The comprehensive evaluation is based on the deviation calculation and comparison of the calorific value corresponding to the fermentation degree and the calorific value of the garbage returned after incineration. The specific comparison method is to use the formula

[0125]

[0126] To calculate the same A ij The deviation between the fermentation degree of the garbage in the grid and the heat return value of garbage incineration, that is, the heat return value of garbage incineration is used as the reference value, and the estimated garbage fermentation degree is used as the evaluation object. When the ratio is within a certain range, it is considered to be a reasonable value, generally 0.7 to 1.3 can be used as normal data, otherwise the fermentation coefficient should be corrected. The garbage pile fermentation time can be used to define the combustion properties of garbage, that is, good fermentation, general fermentation, poor fermentation, etc. represent different levels.

[0127] Furthermore, in the present embodiment, the garbage proportioning of the garbage hanging and mixing materials is carried out by referring to the corresponding calorific value of the fermentation degree and the return calorific value.

[0128] Garbage crane control controls the mixing of garbage to achieve the calorific value of the garbage entering the furnace. Generally, there are multiple ratios such as 4:1, 3:1, 2:1, 1:1, etc. For example, grab a portion in the high or low calorific value area, sprinkle it in the feeding area, grab and sprinkle it once or twice, and then grab N+1 portions to enter the furnace. The inventory grid management information controls the garbage crane according to the garbage characteristics in the specific partition, such as letting the crane in B i′j′ Take 1 portion and place it in A ij Mix well, take N+1 portions and put them into the furnace; i′j′ Take 1 portion and put it in A ij Mix well and add the ingredients.

[0129] The garbage ratio can be satisfied in the normal incineration area. It is generally believed that the heat value line q1 to q3 of the intersection area of ​​the mechanical load and heat load frame of 60% to 100% can be between them. The ratio process is fermented garbage → incineration in the furnace to return the heat value → storage at the feeding point → garbage ratio → re-incineration and return → re-ratio → (such a cycle...).

[0130] Furthermore, setting the optimal heat load in this embodiment also includes: setting the optimal heat load of the garbage entering the furnace through the supervised learning regression algorithm in artificial intelligence machine learning, setting the garbage input amount and the garbage calorific value as input objects, taking the input garbage heat load as the expected output value, analyzing the training data, and generating inferences.

[0131] In this embodiment, the calorific value of the garbage entering the furnace can be approximately calculated by the ratio of the boiler heat load (i.e., the boiler evaporation amount, also known as the main steam flow rate) to the amount of garbage entering the furnace. Based on this calorific value, the position of the boiler operating state in the incinerator combustion diagram is calculated according to thermodynamics. The garbage crane is appropriately proportioned according to the actual input calculated garbage calorific value to achieve a stable calorific value of the garbage entering the furnace.

[0132] By using the supervised learning regression algorithm in artificial intelligence machine learning, the optimal heat load value of the garbage entering the furnace is set, which can guide the garbage crane to learn operating skills and optimize the amount of garbage fed, and intelligently realize the garbage crane to control the heat load of the garbage entering the furnace to ensure the stable combustion of the incinerator. Figure 6 shown.

[0133] Furthermore, in step S111 of this embodiment, the recording further includes: correcting the garbage calorific value according to the weighted average garbage calorific value, correcting the combustion property of the garbage, and recording the combustion property of the garbage.

[0134] Further, in step S111 of this embodiment, the recording includes: in the storage area grid management information, the m×n matrix is ​​used as an object to store data, that is, the above-mentioned A ij The block is considered as a data storage unit of this matrix, and in the database it is considered as a unit with A ij The data information of the identity tag stores the original properties and combustion properties of the garbage. When the grab bucket of the garbage crane moves, it includes the following states: First, grabbing the material, then the grabbing time, weight, height, and action information are recorded to the relevant A ij In the grid; the second is the interval material pouring work, then A ij The original attributes and action information of the grid garbage are transferred to B i′j′ The corresponding grid of the discharge point, that is, all the information of the garbage at the material grabbing point A is transferred to the information at the discharge point B, that is, the original attributes and action information are transferred accordingly; the third is the feeding work, then A ij The original attributes and action information of the grid garbage are stored in the historical database with time and action tags, that is,ij Click on all the information of the garbage + the historical data information of the combustion calorific value returned after the burning time.

[0135] The original attributes of the garbage in this embodiment include: one or more of the time, source, and type of garbage entering the factory. The combustion attributes of the garbage in this embodiment include: the fermentation degree during the natural fermentation process, the garbage calorific value information, and the garbage feeding and collection area point information. The garbage feeding and collection area point information includes: time, source point, grabbing warehouse area coordinate system, and feeding amount. The garbage calorific value information includes: the calorific value of the garbage returned by combustion, the SO2 content, and the HCl content.

[0136] The acquisition of SO2 and HCl can be measured and returned by the online flue gas monitoring device CEMS after incineration. On the one hand, the flue gas emission characteristics of the garbage in this area can be obtained, and the original characteristics of the garbage can be inferred through historical tracing; on the other hand, the correlation of these data can be used to guide the advance control of the flue gas control system.

[0137] Source point information generally refers to where the garbage comes from (such as XX Street, XX Factory, etc.), the type of garbage (such as domestic garbage, industrial garbage, office garbage, etc.), the weight of the garbage (for convenient calculation of volume), etc.

[0138] The combustion properties of the garbage in this embodiment are mainly composed of the information of the garbage feeding collection area, and then the information combination associated with the calorific value of the garbage after it is loaded into the furnace for combustion. Figure 3 As shown in the figure, field 1 is the garbage feeding collection area point information obtained from the intelligent garbage crane control system. After time recursion t, it is combined with field 2 to return the calorific value of garbage combustion, forming a new field containing complete information such as time, source point, grabbing warehouse area coordinate system, feeding amount, calorific value (also SO2, HCl), etc. This new field will be stored in the corresponding garbage grabbing point data information in the grid partition management of the garbage warehouse.

[0139] The recording steps of the present invention can be corrected as long as the calorific value of the garbage is obtained. The order of the steps is not limited and can be performed after the calorific value is estimated. The order of description is only for convenience of description and is not intended to be limiting.

[0140] The calorific value of the corresponding garbage can be calculated through the boiler heat load or power generation. Since the residence time of garbage from the time it is put into the incinerator to the completion of combustion is about 1.5 to 2 hours, the calorific value of the garbage entering the furnace at that time can be deduced accordingly. The database records of the grid area where the garbage crane is pushed forward 1.5 to 2 hours before feeding can be used to obtain the calorific value of the garbage in the feeding area of ​​the garbage storage.

[0141] When the data of the grid partitions are combined, a data group covering the surface of the garbage storage area is formed, and the calorific value distribution curve or functional color change display diagram of each pile area of ​​the garbage storage is mapped. According to the combustion diagram of the garbage incinerator, the calorific value of the normal incineration area between the calorific value q1-q3 lines is guaranteed to ensure stable and efficient combustion of garbage incineration. The operating condition around the calorific value q2 line is the best state. When the heat load of garbage entering the furnace is constant, the amount of garbage entering the furnace is inversely proportional to the calorific value of the garbage. By collecting and analyzing the operating parameters of the garbage crane operation, the amount of garbage entering the furnace, the boiler heat load, the power generation and the combustion conditions of the garbage incinerator, around the optimal operating condition calorific value q2 line of the combustion diagram, and establishing a garbage crane intelligent control mode model, after a large amount of data training, comparison correction and model optimization, the relationship and change trend of each variable are found, and the garbage crane can control the heat load of the garbage entering the furnace to achieve the best control condition. Intelligent control mode.

[0142] The quality of combustion conditions is mainly reflected in the inappropriateness of heat load, furnace temperature, oxygen content, etc. These parameters can be directly measured online. Poor working conditions generally include low heat load, furnace temperature drop or low point, high oxygen content, etc., which is the operating condition of the boiler. The calorific value of garbage directly affects the working condition of the incinerator. It is generally believed that poor or low calorific value of garbage can be used as the direct cause of poor working conditions, that is, it is often said that "garbage is not easy to burn."

[0143] The entire system of the present invention integrates the garbage incineration process with the garbage storage management into a digital intelligent management method, and applies an artificial intelligence supervised learning algorithm, which is an innovative technology in the industry; it utilizes the powerful computing power and data storage advantages of modern computers to improve the predictability, efficiency and accuracy of control, and simplifies the system's hardware requirements; according to the calculation and prediction of the calorific value of garbage incineration, the garbage crane can be used to control the garbage feeding amount, so as to achieve the stability of the calorific value of the garbage entering the furnace to assist the stability of combustion, which is more conducive to improving the garbage incineration efficiency and power generation.

[0144] The present invention proposes a system for intelligently controlling the heat load of garbage entering a furnace by using a garbage crane, comprising:

[0145] Calorific value calculation module: calculates the calorific value of the corresponding garbage entering the furnace through the heat load or power generation of the boiler after garbage incineration;

[0146] Reverse calculation module: according to the burning residence time of garbage in the incinerator, the calorific value of the garbage entering the incinerator at that time can be calculated;

[0147] Heat load estimation module: Calculate the heat load of garbage entering the furnace based on the amount of garbage entering the furnace and the calorific value of the garbage entering the furnace;

[0148] Setting the optimal heat load module: Setting the optimal heat load of the garbage entering the incinerator according to the MCR calorific value and garbage processing volume;

[0149] Heat load control module: control the garbage crane feeding garbage according to the optimal heat load of the garbage entering the furnace, and control the heat load of the garbage entering the furnace;

[0150] Recording module: Correct the combustion properties of garbage according to the calorific value of the garbage entering the furnace and record the combustion properties of the garbage.

[0151] The MCR calorific value of this embodiment refers to the calorific value of the waste incinerator under the maximum continuous operation (Maximum Continuous Rating, MCR) state; controlling the heat load of the garbage entering the furnace means automatically mixing the garbage by hanging the garbage in the fermented garbage storage area, and controlling the calorific value of the garbage entering the furnace to control the stability of the boiler's heat load.

[0152] Furthermore, in the calorific value calculation module of this embodiment, calculating the calorific value of the corresponding garbage entering the furnace according to the thermal load of the boiler includes: collecting and calculating the weight data of the garbage entering the furnace, and calculating the mechanical load of the corresponding garbage entering the furnace.

[0153] First, in the total time T, each time q n The arithmetic mean L of the feeding weight is calculated cumulatively.

[0154]

[0155] In formula (1), for each q n The arithmetic mean L of the cumulative weight of the feed is calculated. n The feeding weight is some non-continuous discrete data, and a method of averaging multiple values ​​within a certain time period, preferably, generally taking 3.5-4.5 hours. Preferably, a method of averaging multiple values ​​collected within 4 hours can be taken.

[0156] Since the time is long, it is not conducive to the continuous calculation of the calorific value of garbage. This embodiment adopts an artificial intelligence data processing method to push the material through a period of time T. The k coefficient of the relationship between the pushing stroke and the mechanical load is calculated based on the total weight of the garbage entering the furnace, so that the machine can self-learn and perform real-time calculations. The details are as follows:

[0157]

[0158] Formula (2) is based on the total time T in formula (1) for the push stroke l n The arithmetic mean of the total number of cumulative calculations is used as the denominator to obtain the initial mechanical load coefficient k m .

[0159]

[0160] The mechanical load k coefficient is a machine self-learning gradient iteration method using formula (3). Data is continuously iterated in the interval from z1 to z2. The k value is made close to the optimal value by continuously adjusting the mechanical load k coefficient parameters, thereby obtaining the optimal formula (4). The push stroke l multiplied by the k coefficient is directly converted into the real-time mechanical load L SL Model.

[0161] L SL =k×l (4)

[0162] The boiler heat load is generally characterized by the boiler evaporation capacity, i.e. the main steam flow rate, as the target heat load f, combined with the above-mentioned garbage mechanical load L SL The heat load is converted into the garbage calorific value q, and the calculation formula is as follows:

[0163]

[0164] The calorific value of the garbage in formula (5) is the difference between the total energy produced and the total energy fed divided by the weight of the garbage, that is, the boiler heat load f and the thermal enthalpy H of the steam. 汽 The product of energy, slag loss Q 潜损 Energy, other boiler steam losses Q 汽损 Equal the total, then subtract the water flow rate F 水 and feed water enthalpy H 水 The product of energy and air flow rate F 风 and air enthalpy H 风 The energy of the product is then divided by the amount of garbage sent in, the mechanical load L SL This calculation process is based on unit time. Based on the above partial data calculation, the garbage incineration control system or this system can directly calculate and output after collecting relevant data during the boiler combustion process.

[0165] Furthermore, in the calorific value calculation module of this embodiment, the calorific value of the corresponding garbage entering the furnace is calculated according to the power generation, including:

[0166] The benefit analysis of heat energy utilization of waste incineration is characterized by the power generation per ton of waste table, and its relationship with the calorific value of the waste entering the furnace is:

[0167]

[0168] In formula (9), the unit of power generation per ton of garbage is kWh / t garbage, and the calorific value of the garbage entering the furnace is (kj / kg)×1000kg / t; the calorific value of the garbage entering the furnace is calculated as

[0169]

[0170] According to formula (10), its real-time calorific value can be calculated by empirical method.

[0171] Furthermore, the heat load control module of this embodiment also includes: controlling the garbage hanging and mixing materials to achieve the optimal garbage entering the furnace calorific value and feeding amount according to the optimal heat load of the garbage entering the furnace, mixing materials according to the calorific value of the garbage entering the furnace, and controlling the garbage to be incinerated in the normal incineration area. If the calorific value of the garbage in a certain area is low, the garbage in the high calorific value area is grabbed and put in to mix with it before being put in; if the calorific value of the garbage in a certain area is high, the garbage in the low calorific value area is grabbed and put in to mix with it before being put in.

[0172] like Figure 7 As shown, the calorific value grade can be specifically represented by the lines q1 to q3 in the figure. For example, those close to the q1 line have higher calorific value, and those exceeding it are high; those close to the q3 line have lower calorific value, and those below it are poor or low; those on the q2 line are the best, and those close to them are all better.

[0173] according to Figure 7 The calorific value after the incineration line can be fitted with this graph, and the area where the calorific value point is located can be used to evaluate the calorific value status of the garbage.

[0174] Garbage calorific value mixing means mixing the garbage calorific value corresponding area of ​​the upper part of q2 with the area below it, so that its line is as close to the q2 line as possible. It is also possible to mix the garbage of the q4 line with the corresponding area close to the q1 line, so that it is in the normal combustion area. It is also possible to mix the garbage of the q4 line with the corresponding area on the q1 line, so that it is in the normal combustion area. Different calorific values ​​correspond to different garbage storage areas, and the garbage mixing of these areas is carried out by grabbing and mixing materials with garbage cranes.

[0175] The garbage storage area can be divided into multiple functional areas, such as Area A for fermentation, Area B for fermented material feeding area, Area C for new garbage stacking area, Area D for other industrial material area, etc. The garbage in these areas has different calorific value qualities.

[0176] When the feeding area of ​​zone B is finished, it will be turned into the stacking area. If it is full, it will be turned into the fermentation area. After the fermentation is completed, it will become the feeding area, and it will run in a cycle. Generally, the area where new garbage and stale garbage are stored is considered to be a low calorific value area; fermented and industrial garbage is considered to be a high calorific value area. When a certain area completes a certain function, its role can be automatically converted or manually changed through the garbage storage management. In the automatic control of the garbage crane, work tasks can be automatically assigned according to the role of a certain area.

[0177] When the calorific value of garbage in a certain area is low, it is necessary to grab garbage from a high calorific value area and mix it with it before adding it. Only after the good and the bad are mixed can the combustion requirements be met. This process is called mixing.

[0178] The ratio of garbage in the mixing material is determined by the combined effect of the calorific value of the fermentation degree and the calorific value returned by combustion.

[0179] Furthermore, the heat load control module of this embodiment further includes: performing weighted averaging on the heat value of the garbage, including:

[0180] The garbage storage area is divided into m×n grid partitions on the horizontal plane, where m is the number of grids in the x-direction of the moving distance coordinate of the garbage crane, and n is the number of grids in the y-direction of the moving distance coordinate of the garbage crane. Each small square forms a matrix, as shown in the following formula:

[0181]

[0182] Formula (6), the m×n grid matrix A, A ij is one of the elements, i / j are i∈m and j∈n respectively, i / j / m / n are all positive integers, and the division standard is that each grid is sufficient to define the state of its reservoir area. Generally, a span of 2 to 5m is appropriate for one grid. If it is too small, the amount of data will increase geometrically, and if it is too large, it will not be enough to characterize the local state.

[0183] When the grab is working, the x / y coordinate data of the operating point corresponds to a certain gridded block A. ij , is within the coordinate range of an element in the matrix. Figures 4 to 5 shown.

[0184] In the grid management information of the reservoir area, the m×n matrix is ​​used as the object for data storage, that is, the above-mentioned A ij The block is considered as a data storage unit of this matrix, and in the database it can be considered as a ij The data information strip of the identity tag stores new field information of the original attributes and combustion attributes of the garbage.

[0185] When the grab bucket of the garbage crane moves, there are mainly the following states: one is grabbing material, then the grabbing time, weight, height, action and other action information are recorded to the relevant A ij In the grid; the second is the interval material pouring work, then A ij The original attributes and action information of the grid garbage are transferred to the corresponding grid of the discharge point, that is, all the information of the garbage at the material picking point A is transferred to the information at the discharge point B, that is, the original attributes and action information are transferred accordingly; the third is the feeding work, then A ij The original attributes and action information of the grid garbage are stored in the historical database with time and action tags, that is, the grab material A ij Click on all the information of the garbage + historical data information of the calorific value (including SO2 and HCl) returned after a combustion time of 1.5 to 2 hours.

[0186] like Figure 6 As shown, when garbage is stored or dumped, a certain A ijThe garbage stored under the grid area is naturally fermented, and then the A layer of the h' layer of the height grid where the height z coordinate is located is ij-h′ In the small cube, a new element is formed in the three-dimensional matrix structure of m×n×h, namely, an A ij-h′ Small cubes, where h'∈h, are all positive integers, and the grid division is generally 2 to 5m span. It is garbage A ij The height h' layer under the grid area takes the stacking time as the starting point and the natural time as the increasing function of the fermentation degree as the time domain characteristics of the garbage fermentation at this point, which can be the expert experience data characteristics. ij-h′ Small cubes such as Figure 6 shown.

[0187] The time domain function of garbage fermentation is:

[0188] J(A ij-h′ ) = k t ×ξ×t k ×F(DT1-DT0) (7)

[0189] In formula (7), A ij-h′ The fermentation degree of garbage in the block J(A ij-h′ ), the garbage properties (such as type) ξ, the ambient temperature of the storage area t k There is a direct relationship between the natural fermentation time function F(DT1-DT0) and the difference between the current time DT1 and the stacking start time DT0. However, garbage fermentation is also directly related to the garbage thickness, storage temperature, internal bacterial flora, etc., so the fermentation coefficient k is used. t Characterization. Fermentation coefficient k t , can be calculated based on empirical values. If the internal factors of garbage fermentation cannot be calculated, then ξ×t k =1 as a premise, that is, the comprehensive relationship of related factors is 1, requiring the garbage fermentation degree J(A ij-h′ )=1 means the fermentation is normal, then we can calculate: in summer, the stacking time is 3 to 4 days, then k t =0.25~0.33; in winter, the stacking time is 7~8 days, then k t =0.125~0.143. When the two-season coefficient k t If the change exceeds 1.8 times and reaches nearly 2 times, this can only be calculated theoretically and cannot meet the requirements of accurate calculation. In this case, the following method is used.

[0190] The time domain calculation method of natural fermentation of garbage is used for each garbage A ij-h′ The block can be used for fermentation calculation and can be used as the original data for calculation. Its accuracy is mainly determined by the fermentation coefficient k tIn this embodiment, the garbage fermentation data is calculated by combining the calorific value in the garbage combustion attribute, and the convolution calculation method and coefficient iteration method in AI calculation are adopted. On the one hand, the balance of calculation is ensured, and on the other hand, the fermentation coefficient is continuously updated and more accurate. The calculation process is as follows:

[0191] It is carried out from the surface area of ​​the garbage feeding area. When the grid partition is the above formula

[0192] matrix

[0193] With the convolution matrix or The average of the products of , B is a matrix of (2N+1) rows multiplied by (2N+1) columns, N = 1, 2, 3..., and the average calorific value formula is obtained:

[0194]

[0195] Among them A ij Garbage fermentation coefficient k at h' height under the grid t is the average value of the convolution of the B matrix centered at (ij). When (jj) is only updated with multiple feedings and multiple returns of garbage calorific value, the calculation process is continuously iterated, so that the garbage fermentation coefficient k t It is more accurate. AI machine self-learning function can be used. The corresponding data is transmitted to the grid management information of the warehouse area for storage, so that the intelligent garbage crane can automatically control the data guidance of the calorific value.

[0196] In order to prevent the garbage fermentation coefficient k t If it contains iterative data of different seasons, the actual operation is calculated based on multiple coefficients per month or every 15-20℃ change in ambient temperature, that is, the garbage fermentation coefficient k t1 , k t2 , k t3 ...respectively represent the fermentation coefficient under the factors of month, external atmospheric environment or environmental factors in the garbage bin, and can be called according to the corresponding database storage location.

[0197] The fermentation coefficient is a parameter used in digital information systems to measure the trend of natural fermentation of garbage. It is related to the ambient temperature. The degree of garbage fermentation corresponds to the calorific value of garbage. The fermentation coefficient can be corrected according to the calorific value returned after the garbage is burned. tIt is related to the ambient temperature. The natural fermentation time and the temperature of the actual fermentation block are positively correlated. The fermentation coefficient is calculated by returning the calorific value once, and then returning to calculate again. Each calculation is based on the correction of the previous one. The more sample data is calculated, the higher the accuracy. The fermentation coefficient is calculated for the prediction of the calorific value of garbage. The ratio of garbage to the garbage suspension mix is ​​based on the combined effect of the fermented calorific value and the returned calorific value. The higher the accuracy of the fermentation coefficient, the more accurate the prediction of the calorific value of the garbage in the fermentation area. This part is not put into garbage incineration and has no returned calorific value.

[0198] The calorific value of garbage is calculated by weighted average, which mainly solves the problem that the calorific value generated by garbage in each grid block may have large calculation deviation due to factors such as the garbage not being mixed evenly, the weighing error of the garbage crane, and the accidental factors of the combustion process. The convolution matrix can be used To perform secondary calculation on the surrounding blocks and obtain the relevant mean, it is beneficial to the following comprehensive evaluation.

[0199] The comprehensive evaluation is based on the deviation calculation and comparison of the calorific value corresponding to the fermentation degree and the calorific value of the garbage returned after incineration. The specific comparison method is to use the formula

[0200]

[0201] To calculate the same A ij The deviation between the fermentation degree of garbage in the grid and the calorific value returned by garbage incineration, that is, the calorific value returned by garbage incineration is used as the reference value, and the estimated garbage fermentation degree is used as the evaluation object. When the ratio is within a certain range, it is considered to be a reasonable value, generally 0.7 to 1.3 can be used as normal data, otherwise the fermentation degree coefficient should be corrected.

[0202] The garbage fermentation time can be used to define the combustion properties of garbage, that is, good, average, poor fermentation, etc. represent different levels.

[0203] Furthermore, in the present embodiment, the garbage proportioning of the garbage hanging and mixing materials is carried out by referring to the corresponding calorific value of the fermentation degree and the return calorific value.

[0204] Garbage crane control controls the mixing of garbage to achieve the calorific value of the garbage entering the furnace. Generally, there are multiple ratios such as 4:1, 3:1, 2:1, 1:1, etc. For example, grab a portion in the high or low calorific value area, sprinkle it in the feeding area, grab and sprinkle it once or twice, and then grab N+1 portions to enter the furnace. The inventory grid management information controls the garbage crane according to the garbage characteristics in the specific partition, such as letting the crane in B i′j′ Take 1 portion from Aij, put it in Aij, then take N+1 portions and put them into the furnace; then take i′j′ Take 1 portion and put it in A ij Mix well and add the ingredients.

[0205] The garbage ratio can be satisfied in the normal incineration area. It is generally believed that the heat value line q1 to q3 of the intersection area of ​​the mechanical load and heat load frame of 60% to 100% can be between them. The ratio process is fermented garbage → incineration in the furnace to return the heat value → storage at the feeding point → garbage ratio → re-incineration and return → re-ratio → (such a cycle...).

[0206] Furthermore, the module for setting the optimal heat load of the present embodiment also includes: setting the optimal heat load of the garbage entering the furnace through the supervised learning regression algorithm in the artificial intelligence machine learning, setting the garbage input amount and the garbage calorific value as input objects, taking the input garbage heat load as the expected output value, analyzing the training data, and generating an inference function.

[0207] Furthermore, the recording module of this embodiment further includes: correcting the garbage calorific value according to the weighted average garbage calorific value, correcting the combustion property of the garbage, and recording the combustion property of the garbage.

[0208] Furthermore, the recording module of this embodiment also includes: in the storage area grid management information, using m×n matrix as an object to store data, that is, the above-mentioned A ij The block is considered as a data storage unit of this matrix, and in the database it is considered as a unit with A ij The data information of the identity tag stores the original properties and combustion properties of the garbage. When the grab bucket of the garbage crane moves, it includes the following states: First, grabbing the material, then the grabbing time, weight, height, and action information are recorded to the relevant A ij In the grid; the second is the interval material pouring work, then A ij The original attributes and action information of the grid garbage are transferred to B i′j′ The corresponding grid of the discharge point, that is, all the information of the garbage at the material grabbing point A is transferred to the information at the discharge point B, that is, the original attributes and action information are transferred accordingly; the third is the feeding work, then A ij The original attributes and action information of the grid garbage are stored in the historical database with time and action tags, that is, ij Click on all the information of the garbage + the historical data information of the combustion calorific value returned after the burning time.

[0209] The original attributes of the garbage in this embodiment include: one or more of the time, source, and type of garbage entering the factory. The combustion attributes of the garbage in this embodiment include: the fermentation degree during the natural fermentation process, the garbage calorific value information, and the garbage feeding and collection area point information. The garbage feeding and collection area point information includes: time, source point, grabbing warehouse area coordinate system, and feeding amount. The garbage calorific value information includes: the calorific value of the garbage returned by combustion, the SO2 content, and the HCl content.

[0210] The present invention uses a garbage crane to intelligently control the calorific value of the garbage entering the furnace to meet the algorithm of thermal load stability of garbage incineration. It is mainly based on the process of garbage incineration, using the garbage crane as the execution device, and controlling the amount and calorific value of the garbage entering the furnace through the intelligent control system of the garbage crane to achieve the stability of the thermal load of garbage incineration. Then the mechanical load and boiler heat load are returned and the calorific value of the garbage is calculated; the calorific value calculation result and the feeding data are integrated to form the combustion properties of the garbage; the combustion properties of the garbage are combined with the time domain calculation method of the natural fermentation of the garbage in the garbage bin and continuously self-learn and iterate, and then sent to the garbage storage area grid management information system to realize the revision and correction of the combustion properties of the garbage at the garbage crane grabbing material in advance, and then push the combustion information to the garbage crane in the storage area to select or mix the ingredients to achieve the closed-loop control of the optimal calorific value of the garbage entering the furnace.

[0211] In the description of the present invention, it is necessary to understand that terms such as "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are orientations or positional relationships based on the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0212] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0213] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be directly connected or indirectly connected through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0214] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for intelligently controlling the heat load of garbage entering a furnace by using a garbage crane, characterized in that: include: Calorific value calculation: Calculate the calorific value of the corresponding garbage entering the furnace through the heat load or power generation of the boiler after garbage incineration; Reverse calculation: According to the combustion residence time in the waste incinerator, the calorific value of the waste entering the incinerator at that time can be reversed; Estimation of heat load: Estimation of heat load of garbage entering the furnace based on the amount of garbage entering the furnace and the calorific value of the garbage entering the furnace; Set the optimal heat load: Set the optimal heat load of the garbage entering the incinerator according to the MCR calorific value and garbage processing volume; Heat load control: control the garbage crane feeding garbage according to the optimal heat load of the garbage entering the furnace, and control the heat load of the garbage entering the furnace; Record: Correct the combustion properties of the garbage according to the calorific value of the garbage entering the furnace, and record the original properties and combustion properties of the garbage.

2. The method for intelligently controlling the heat load of garbage entering the furnace by using a garbage crane according to claim 1 is characterized in that: The method of calculating the calorific value of the corresponding waste entering the furnace according to the heat load of the boiler includes: collecting and calculating the weight data of the waste entering the furnace, calculating the mechanical load of the corresponding waste entering the furnace, First, in the total time T, each time q n The arithmetic mean L of the feeding weight is calculated cumulatively. In the above formula, each time q n The feeding weight is some non-continuous discrete data, and the method of averaging multiple values ​​within a set time period is adopted. Pushing stroke within time T Calculate the pusher stroke and mechanical load coefficient k based on the total weight of the garbage entering the furnace. First, based on the total time T, the push stroke l n The arithmetic mean of the total number of cumulative calculations is used as the denominator to obtain the initial mechanical load coefficient k m The mechanical load coefficient k adopts the gradient iteration method of machine self-learning, and continuously iterates data in the interval from z1 to z2. By continuously adjusting the mechanical load coefficient k parameter, the k value is close to the optimal value, and then the real-time mechanical load L is converted by multiplying the push stroke l by the k coefficient. SL , L SL =k×l (4) The boiler heat load is characterized by the boiler evaporation rate, i.e. the main steam flow rate, as the target heat load f, combined with the above-mentioned garbage mechanical load L SL The heat load is converted into the garbage calorific value q, and the calculation formula is as follows: In the above formula, the calorific value of garbage q is the difference between the total energy produced and the total energy input divided by the mechanical load L SL , that is, boiler heat load f and steam enthalpy H 汽 The product of energy, slag loss Q 渣损 Energy, other boiler steam losses Q 汽损 Total, minus the water flow F 水 and feed water enthalpy H 水 The product of energy and air flow rate F 风 and air enthalpy H 风 The energy of the product is then divided by the mechanical load L of the garbage sent in. SL .

3. The method of intelligently controlling the heat load of garbage entering the furnace by using a garbage crane according to claim 1 is characterized in that: The calculation of the calorific value of the corresponding garbage entering the furnace based on the power generation includes: The benefit analysis of heat energy utilization of waste incineration is characterized by the power generation per ton of waste table, and its relationship with the calorific value of the waste entering the furnace is: In the above formula, the unit of power generation per ton of garbage is kWh / t garbage, and the calorific value of the garbage entering the furnace is (kj / kg)×1000kg / t; the calorific value of the garbage entering the furnace is calculated as 4. The method for intelligently controlling the heat load of garbage entering the furnace by using a garbage crane as claimed in claim 1, characterized in that: The heat load control is as follows: according to the optimal heat load of the garbage entering the furnace, the garbage hanging and mixing material grabbing are controlled to achieve the optimal garbage entering the furnace calorific value and feeding amount, the material mixing ratio is carried out according to the calorific value of the garbage entering the furnace, and the garbage is controlled to be incinerated in the normal incineration area. If the calorific value of the garbage in a certain area is low, the garbage in the high calorific value area is grabbed and put in, mixed with it, and then put in; if the calorific value of the garbage in a certain area is high, the garbage in the low calorific value area is grabbed and put in, mixed with it, and then put in.

5. The method for intelligently controlling the heat load of garbage entering the furnace by using a garbage crane according to claim 2 is characterized in that: The heat load control also includes: performing weighted averaging on the heat value of the garbage, including: The garbage storage area is divided into m×n grid partitions on the horizontal plane, where m is the number of grids in the x-direction of the moving distance coordinate of the garbage crane, and n is the number of grids in the y-direction of the moving distance coordinate of the garbage crane. Each small square forms a matrix, as shown in the following formula: In the above formula, the m×n grid A matrix, A ij is one of the elements, i / j are i∈m and j∈n respectively, i / j / m / n are all positive integers, and the span is 2 to 5m. When the grab bucket is working, the x / y coordinate data of the operating point corresponds to a certain gridded block A. ij , is the coordinate range of an element in the matrix; When the garbage is stored or dumped, a certain A ij The garbage is stored under the grid area for natural fermentation, and then the height z coordinate is located at the h' layer of the height grid A ij-h‘ In the small cube, a new element is formed in the three-dimensional matrix structure of m×n×h, namely, an A ij-h‘ Small cubes, where h'∈h, are all positive integers, with a span of 2 to 5m. It is garbage A ij The height h' layer under the grid area takes the stockpiling time as the starting point and the natural time advancement as the increasing function of the fermentation degree as the time domain characteristics of the garbage fermentation at this point. The time domain function of the garbage fermentation is: J(A ij-h‘ )=k t ×ξ×t k ×F(DT1-DT0) (7) In the above formula, garbage A ij-h‘ The fermentation degree of the block J(A ij-h‘ ), with its own garbage properties ξ, storage area ambient temperature t k The natural fermentation time function F(DT1-DT0) is a positive function of the difference between the current time DT1 and the stacking start time DT0. Garbage fermentation is also related to the garbage thickness, storage temperature, and internal bacterial flora. The fermentation coefficient k is used. t To characterize; If the internal factors of garbage fermentation cannot be calculated, then ξ×t k =1 as a premise, that is, the comprehensive relationship of related factors is 1, requiring the garbage fermentation degree J(A ij-h‘ )=1 means the fermentation is normal, then we can calculate: in summer, the stacking time is 3 to 4 days, then k t =0.25~0.33; in winter, the stacking time is 7~8 days, then k t =0.125~0.143, when the two-season coefficient k t When the change exceeds 1.8 times, the following method is used; The time domain calculation method of natural fermentation of garbage is used for each garbage A ij-h‘ Block fermentation calculation, as the original data of the benchmark, is used to calculate the garbage fermentation coefficient k according to the calorific value in the garbage combustion properties t , using the convolution calculation method and coefficient k in AI calculation t Iterative method, the calculation process is as follows: The surface area of ​​the garbage feeding area is divided into a matrix With the convolution matrix or The average of the products of , B is a matrix of (2N+1) rows multiplied by (2N+1) columns, N = 1,2,3..., the average calorific value formula is obtained: Among them A ij Garbage fermentation coefficient k at h' height under the grid t is the average value of the convolution of the B matrix centered on (ij). When (ij) is continuously updated with multiple feedings and multiple returns of garbage calorific value, the calculation process is continuously iterated, making the garbage fermentation coefficient k t More accurate, the corresponding data is transmitted to the grid management information of the reservoir area for storage, and is calculated based on multiple coefficients every month or every 15-20℃ change in ambient temperature, that is, the garbage fermentation coefficient k t1 , k t2 , k t3 ...respectively represent the fermentation coefficient under the factors of month, external atmospheric environment or internal environment of garbage bin, and are called according to the corresponding database storage location.

6. The method for intelligently controlling the heat load of garbage entering the furnace by using a garbage crane as claimed in claim 5, characterized in that: The heat load control also includes: a comprehensive evaluation based on the calculation and comparison of the deviation between the calorific value corresponding to the fermentation degree and the calorific value of the garbage returned after incineration, the residence time of the garbage from the time of input to the completion of combustion in the incinerator is 1.5-2 hours; when calculating the arithmetic mean value L, the time period used is 3.5-4.5 hours each time q n The feeding weight is averaged over multiple values.

7. The method of intelligently controlling the heat load of garbage entering the furnace by using a garbage crane as claimed in claim 6, characterized in that: The setting of the optimal heat load also includes: setting the optimal heat load of the garbage entering the furnace through a supervised learning regression algorithm in artificial intelligence machine learning, setting the garbage input weight and the garbage calorific value as input objects, taking the input garbage heat load as the expected output value, analyzing the training data, and generating inferences; In the heat load control, the comprehensive evaluation of the deviation calculation and comparison between the calorific value corresponding to the fermentation degree and the calorific value of the garbage returned after incineration is as follows: To calculate the same A ij The deviation between the fermentation degree of the garbage in the grid and the heat return value of garbage incineration, that is, the heat return value of garbage incineration is used as the reference value, and the estimated garbage fermentation degree is used as the evaluation object. When the ratio is within the set range, it is normal data, otherwise the fermentation degree coefficient is corrected.

8. The method for intelligently controlling the heat load of garbage entering the furnace by using a garbage crane according to claim 5 is characterized in that: The record includes: in the reservoir area grid management information, the m×n matrix is ​​used as the object for data storage, that is, A ij The block is considered as a data storage unit of this matrix, and in the database it is considered as a ij The data information of the identity tag stores the original properties and combustion properties of the garbage. When the grab bucket of the garbage crane moves, it includes the following states: First, grabbing the material, then the grabbing time, weight, height, and action information are recorded to the relevant A ij In the grid; the second is the interval material pouring work, then A ij The original attributes and action information of the grid garbage are transferred to B i′j′ The corresponding grid of the discharge point, that is, all the information of the garbage at the material grabbing point A is transferred to the information at the discharge point B, that is, the original attributes and action information are transferred accordingly; the third is the feeding work, then A ij The original attributes and action information of the grid garbage are stored in the historical database with time and action tags, that is, the grab material A ij Click on all the information of the garbage + the historical data information of the combustion calorific value returned after the burning time.

9. The method for intelligently controlling the heat load of garbage entering the furnace by using a garbage crane according to any one of claims 1 to 8, characterized in that: The original attributes of the garbage include: one or more of the time, source, and type of garbage entering the factory; the combustion attributes of the garbage include: the fermentation degree during natural fermentation, the calorific value information of the garbage, and the garbage feeding and collection area point information; the garbage calorific value information includes the calorific value of the garbage returned from combustion, SO2, and HCl; the garbage feeding and collection area point information includes: one or more of the time, source point, grabbing warehouse area coordinate system, and feeding amount.

10. A system for intelligently controlling the heat load of garbage entering a furnace using a garbage crane, characterized in that: include: Calorific value calculation module: calculates the calorific value of the corresponding garbage entering the furnace through the heat load or power generation of the boiler after garbage incineration; Reverse calculation module: according to the burning residence time of garbage in the incinerator, the calorific value of the garbage entering the incinerator at that time can be calculated; Heat load estimation module: Calculate the heat load of garbage entering the furnace based on the amount of garbage entering the furnace and the calorific value of the garbage entering the furnace; Setting the optimal heat load module: Setting the optimal heat load of the garbage entering the incinerator according to the MCR calorific value and garbage processing volume; Heat load control module: control the garbage crane feeding garbage according to the optimal heat load of the garbage entering the furnace, and control the heat load of the garbage entering the furnace; Recording module: Modify the combustion properties of garbage according to the calorific value of the garbage entering the furnace, and record the original properties and combustion properties of the garbage.

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