Solid waste resourceful treatment system and method based on pyrolysis technology

Abstract

The invention discloses a solid waste resourceful treatment system and method based on a pyrolysis technology, and belongs to the technical field of solid waste treatment.The system comprises a solid waste pretreatment module used for obtaining pretreated solid waste; the pyrolysis process parameter identification module is used for obtaining a pyrolysis process parameter threshold value; the pyrolysis process parameter generation module is used for obtaining an initial pyrolysis process parameter set; the influence coefficient determination module is used for determining a resource loss influence coefficient set; and the resourceful treatment module is used for carrying out resourceful treatment on the pretreated solid waste. The technical problem that the pyrolysis treatment efficiency and the recycling effect are affected due to the fact that pyrolysis process parameters are difficult to determine in a unified mode due to the fact that solid waste sources are complex and component differences are large is solved, and the purposes of improving the solid waste recycling treatment efficiency, reducing resource losses and improving the recycling effect are achieved by optimizing the pyrolysis process parameters. And the stable and consistent treatment effect is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of solid waste treatment, and in particular to a solid waste resource treatment system and method based on pyrolysis technology. Background Art

[0002] The treatment and resource utilization of solid waste has always been an important topic in the field of environmental protection and sustainable development. With the advancement of industrialization, the types and quantities of solid waste have increased dramatically. Traditional treatment methods face problems such as low treatment efficiency and severe environmental pollution. New technical means are urgently needed to achieve efficient resource recovery and effective reduction of pollutants. Especially when the waste composition is complex and the physical and chemical properties vary greatly, the existing solid waste treatment technology is often difficult to adapt to the treatment needs of different types of waste.

[0003] As a mature waste treatment technology, pyrolysis technology has the advantage of being able to convert solid waste into useful resources, effectively reducing the volume of waste and producing valuable energy and raw materials. The pyrolysis process heats solid waste in an oxygen-deficient or low-oxygen environment to decompose it into gas, liquid and solid products, thereby achieving waste reduction, resource utilization and harmlessness. However, due to the diverse sources and strong heterogeneity of solid waste, the parameter setting of the pyrolysis process has a huge impact on the treatment effect. Traditional pyrolysis processes are often difficult to optimize for different types of waste, resulting in unsatisfactory treatment efficiency and resource utilization effects. Summary of the invention

[0004] The present application provides a solid waste resource treatment system and method based on pyrolysis technology, aiming to solve the technical problem that the pyrolysis process parameters are difficult to uniformly determine due to the complex sources of solid waste and large differences in composition, which in turn affects the pyrolysis treatment efficiency and resource effect. The application aims to achieve the technical effect of improving the solid waste resource treatment efficiency, reducing resource losses, and ensuring stable and consistent treatment effects by optimizing the pyrolysis process parameters.

[0005] In view of the above problems, the present application provides a solid waste resource treatment system and method based on pyrolysis technology.

[0006] The first aspect disclosed in the present application provides a solid waste resource processing system based on pyrolysis technology, the system comprising: a solid waste pretreatment module, used to obtain a solid waste type set of solid waste to be processed, and to perform crushing and drying pretreatment on the solid waste to be processed to obtain pretreated solid waste; a pyrolysis process parameter identification module, used to traverse the solid waste type set to identify and summarize the pyrolysis process parameters, and obtain a pyrolysis process parameter threshold; a pyrolysis process parameter generation module, used to generate pyrolysis process parameters with the pyrolysis process parameter threshold as a constraint and parameter diversity as a target, and obtain an initial pyrolysis process parameter set; an influence coefficient determination module, used to determine a resource loss influence coefficient set when the pretreated solid waste is pyrolyzed under the initial pyrolysis process parameter set according to a pre-constructed solid waste type processing influence relationship network and a solid waste type set; a resource processing module, used to optimize the initial pyrolysis process parameter set based on the resource loss influence coefficient set, determine the target pyrolysis process parameters, and perform resource processing on the pretreated solid waste based on the target pyrolysis process parameters.

[0007] Another aspect disclosed in the present application provides a method for resource processing of solid waste based on pyrolysis technology, the method comprising: obtaining a set of solid waste types of solid waste to be processed, and pre-processing the solid waste to be processed by crushing and drying to obtain pre-processed solid waste; traversing the solid waste type set to identify and summarize pyrolysis process parameters to obtain pyrolysis process parameter thresholds; using the pyrolysis process parameter thresholds as constraints and parameter diversity as a target to generate pyrolysis process parameters to obtain an initial pyrolysis process parameter set; determining a set of resource loss influence coefficients when pyrolyzing the pre-treated solid waste under the initial pyrolysis process parameter set based on a pre-constructed solid waste type processing influence network and a solid waste type set; optimizing the initial pyrolysis process parameter set based on the resource loss influence coefficient set to determine target pyrolysis process parameters, and resource processing the pre-treated solid waste based on the target pyrolysis process parameters.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] The solid waste pretreatment module is used to obtain a solid waste type set of the solid waste to be treated, and the solid waste to be treated is pretreated by crushing and drying, so as to obtain pretreated solid waste; the pyrolysis process parameter identification module is based on traversing the solid waste type set to identify and summarize the pyrolysis process parameters, so as to obtain the pyrolysis process parameter threshold; the pyrolysis process parameter generation module is based on taking the pyrolysis process parameter threshold as a constraint and parameter diversity as a target to generate pyrolysis process parameters, so as to obtain an initial pyrolysis process parameter set; the influence coefficient determination module is based on the pre-constructed solid waste type processing influence network and the solid waste type set, so as to respectively determine the resource loss influence coefficient set when the pretreated solid waste is pyrolyzed under the initial pyrolysis process parameter set; the resource processing module is based on optimizing the initial pyrolysis process parameter set based on the resource loss influence coefficient set, so as to determine the target pyrolysis process parameters, and the pretreated solid waste is resource processed based on the target pyrolysis process parameters. The technical problem of difficulty in uniformly determining pyrolysis process parameters due to the complex sources of solid waste and large differences in composition, which in turn affects the pyrolysis treatment efficiency and resource utilization effect, has been solved. The technical effect of improving the solid waste resource treatment efficiency, reducing resource losses and ensuring stable and consistent treatment effects has been achieved by optimizing the pyrolysis process parameters.

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A structural schematic diagram of a solid waste resource treatment system based on pyrolysis technology is provided for an embodiment of the present application.

[0012] Figure 2 A flow chart of a solid waste resource treatment method based on pyrolysis technology is provided for the embodiment of the present application.

[0013] Explanation of the reference numerals: solid waste pretreatment module 11 , pyrolysis process parameter identification module 12 , pyrolysis process parameter generation module 13 , influence coefficient determination module 14 , resource recovery processing module 15 . DETAILED DESCRIPTION

[0014] The present application provides a solid waste resource treatment system and method based on pyrolysis technology, which solves the technical problem that the pyrolysis process parameters are difficult to uniformly determine due to the complex sources of solid waste and large differences in composition, thereby affecting the pyrolysis treatment efficiency and resource recovery effect. The application achieves the technical effect of improving the solid waste resource treatment efficiency, reducing resource losses, and ensuring stable and consistent treatment effects by optimizing the pyrolysis process parameters.

[0015] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0016] Embodiment 1, as Figure 1 As shown, the embodiment of the present application provides a solid waste resource treatment system based on pyrolysis technology, the system comprising:

[0017] The solid waste pre-processing module 11 is used to obtain a solid waste type set of solid waste to be processed, and to perform crushing and drying pre-processing on the solid waste to be processed to obtain pre-processed solid waste.

[0018] Specifically, in the solid waste pretreatment module 11, the system terminal first obtains a set of types of solid waste to be treated. This process includes classifying the waste and identifying different types of waste, such as plastic, paper, metal, etc. These solid wastes need to be crushed and dried before treatment. The crushing process can break the waste into smaller particles or fragments to facilitate subsequent pyrolysis treatment, increase its surface area, and improve pyrolysis efficiency. The drying process is to remove moisture from the waste and reduce the interference of moisture on the pyrolysis process, ensuring that the pyrolysis process is carried out under optimal conditions and avoiding poor pyrolysis effect due to excessive moisture content. After pretreatment, the volume and moisture content of the solid waste are effectively controlled, which is convenient for the subsequent pyrolysis treatment stage and ensures that the resource efficiency of the waste is maximized.

[0019] The pyrolysis process parameter identification module 12 is used to traverse the solid waste type set to identify and summarize the pyrolysis process parameters and obtain the pyrolysis process parameter thresholds.

[0020] Specifically, in the solid waste pretreatment module 12, the system terminal traverses all identified solid waste type sets to identify and summarize the pyrolysis process parameters for each waste type. In this process, the system terminal inputs each solid waste type into a pre-built pyrolysis process parameter identification network layer to determine the pyrolysis process parameter range suitable for each type, such as temperature, heating rate, reaction time and pressure, air flow velocity, cooling rate, etc.; then, by summarizing these process parameters, a set of pyrolysis process parameter thresholds are generated, indicating the reasonable range of pyrolysis process parameters under different solid waste types. These thresholds provide a basis for subsequent process optimization, so that the system terminal can adjust the pyrolysis process parameters according to the specific type of waste in actual applications to ensure that each type of waste can be pyrolyzed under optimal conditions, thereby improving the efficiency and effectiveness of resource utilization.

[0021] Furthermore, the solid waste type set is traversed to identify and summarize the pyrolysis process parameters, and the pyrolysis process parameter thresholds are obtained, including:

[0022] Pre-constructing a pyrolysis process parameter identification network layer; using the pyrolysis process parameter identification network layer to respectively identify the solid waste type set to obtain a type pyrolysis process parameter set; performing a union on the type pyrolysis process parameter set to obtain the pyrolysis process parameter threshold.

[0023] In a preferred embodiment, the system terminal extracts the sample solid waste type and the sample pyrolysis process parameters from the style experiment library, and then defines the basic structure of the neural network, including an input layer, a hidden layer, and an output layer. In the input layer, the number of nodes is determined according to the number of characteristics of the solid waste. The hidden layer sets multiple neurons according to the complexity of the problem. The ReLU activation function is used to prevent the gradient from disappearing and speed up the training of the model. The number of nodes in the output layer corresponds to the pyrolysis process parameters that need to be predicted, and the parameters are output through a linear activation function. After the network architecture is determined, the collected sample solid waste types and sample pyrolysis process parameters are used to train the network, and a suitable loss function (such as mean square error) is selected to measure the difference between the predicted pyrolysis process parameters and the actual values. The network is optimized through a back propagation algorithm, and the parameters in the neural network are adjusted using an Adam optimizer to minimize the loss function. Through iterative training, the weights of the network are continuously adjusted until a predetermined optimization effect is achieved (such as the maximum number of iterations and the loss tends to be stable). After the training is completed, cross-validation is used to evaluate the performance of the model to ensure that the neural network can not only perform well on the training data, but also effectively predict the performance on the verification data (data used for training). If the verification is passed, the current neural network is used as the pyrolysis process parameter identification network layer. Otherwise, the prediction accuracy of the model is further improved by adjusting the learning rate, optimizing the network structure or adding training data for retraining. The system terminal traverses the solid waste type set. In each traversal, the solid waste type currently traversed is input into the constructed pyrolysis process parameter identification network layer. The pyrolysis process parameter identification network layer automatically identifies the pyrolysis process parameters of this type of solid waste based on the knowledge obtained during the training process. These parameters usually include temperature, heating rate, reaction time, pressure, air flow velocity and cooling rate, etc. This process continues until the traversal of the solid waste type set is completed. At this time, the system terminal will summarize all the obtained pyrolysis process parameters to generate a type pyrolysis process parameter set. Once the pyrolysis process parameter identification network layer identifies the pyrolysis process parameters of all solid waste types, the system terminal will perform a union operation on these parameter sets to obtain the pyrolysis process parameter thresholds of all solid waste types. This threshold set contains the process parameter ranges required for all types of solid waste in the pyrolysis process, providing a basis for subsequent process optimization. Through this integration process, the system terminal can obtain a widely applicable range of pyrolysis process parameters, ensuring that all types of solid waste can receive reasonable process guarantees during the treatment process.

[0024] The pyrolysis process parameter generation module 13 is used to generate pyrolysis process parameters with the pyrolysis process parameter threshold as a constraint and parameter diversity as a goal, so as to obtain an initial pyrolysis process parameter set.

[0025] Specifically, in the pyrolysis process parameter generation module 13, the system terminal first uses the obtained pyrolysis process parameter threshold as a constraint condition. The pyrolysis process parameter threshold is a set of parameter ranges obtained by identifying the treatment requirements of different types of solid waste. These parameter ranges limit the process conditions that can be used in the treatment process, such as temperature, heating rate, pressure, etc., to ensure that they are within a reasonable range to prevent the treatment efficiency from decreasing or resources from being wasted due to exceeding the applicable range; the system terminal takes parameter diversity as the goal and generates pyrolysis process parameters by random sampling. Parameter diversity means that the system terminal needs to generate a set of process parameters that are as diverse as possible while meeting the threshold constraint. This diversity ensures that the system terminal can adapt to solid wastes of different types and characteristics, and can flexibly adjust the process conditions to meet different treatment requirements; in this way, the system terminal will randomly generate a set of initial pyrolysis process parameter sets according to the set constraints and goals. These initial parameters have a certain diversity and can provide a variety of options for subsequent pyrolysis treatment, ensuring that the system terminal can efficiently treat various types of solid waste and optimize resource recovery and energy utilization.

[0026] The influence coefficient determination module is used to determine the resource loss influence coefficient set when the pre-treated solid waste is pyrolyzed under the initial pyrolysis process parameter set according to the pre-constructed solid waste type processing influence relationship network and the solid waste type set.

[0027] Specifically, in the impact coefficient determination module 14, the system terminal relies on the pre-constructed solid waste type treatment impact relationship network and the solid waste type set to analyze and determine the impact coefficient of resource loss. The solid waste type treatment impact relationship network is a graphical representation method that describes the mutual influence relationship between different types of waste. The direct or indirect influence of each waste type on other types is reflected by the color of the edge, thereby helping the system terminal understand the interaction in the waste treatment process and the potential risk of resource loss; the system terminal randomly selects a parameter combination from the previously generated initial pyrolysis process parameter set to perform an impact analysis on each waste type in the solid waste type set. In this process, the system terminal calculates the resource loss impact coefficient of the current parameter combination based on the pre-constructed loss function, the waste type with direct and indirect influence, the selected parameter combination, and the selected waste type. After the analysis of all parameter combinations in the initial pyrolysis process parameter set is completed, the system terminal collects and integrates these calculated resource loss impact coefficients to form a complete resource loss impact coefficient set. This set provides a data basis for subsequent process optimization, and can help the system terminal understand which solid waste types will cause greater resource losses under different treatment conditions, thereby providing guidance for further optimizing pyrolysis process parameters.

[0028] Furthermore, a solid waste type treatment impact network is constructed, including:

[0029] Based on the pyrolysis database, Q association label sets of Q solid waste types in the solid waste type set are extracted, wherein the association label is a direct impact label or an indirect impact label, Q is the total number of solid waste types in the solid waste type set, and Q is an integer greater than or equal to 1; based on the Q association label sets, an influence relationship network is constructed for the Q solid waste types to obtain a constructed solid waste type processing influence relationship network, wherein the nodes of the solid waste type processing influence relationship network represent solid waste types, the first color edge represents direct impact, and the second color edge represents indirect impact.

[0030] In a preferred embodiment, the system terminal extracts a solid waste type set from a pyrolysis database, which includes Q different waste types and Q association relationship label sets. Each solid waste type corresponds to an association relationship label set, which records the impact relationship between the solid waste type and other solid waste types. These relationships can be direct (recorded as direct impact labels) or indirect (recorded as indirect impact labels). The direct impact label includes an association strength, which indicates the degree to which one waste type directly affects the pyrolysis of another waste type. For example, the chemical composition of a certain waste may directly accelerate the decomposition rate of another waste. The indirect impact label includes an association strength, which indicates the indirect impact degree between the two waste types through certain intermediate products or reaction processes. degree, which may indirectly affect the pyrolysis effect by producing gas or other by-products; based on these association relationship labels, the system terminal will construct a solid waste type treatment impact network, in which the nodes represent the solid waste types (the quantity is Q), and each node is connected by edges of different colors. The edges of the first color (such as red) represent direct impacts, while the edges of the second color (such as orange) represent indirect impacts. In this way, the system terminal can clearly visualize the direct and indirect impact relationships between the waste types, thereby providing an effective basis for the subsequent pyrolysis process optimization and resource loss impact coefficient calculation; finally, the constructed solid waste type treatment impact network will help the system terminal better understand the interactions between them when treating solid wastes, and ensure the effectiveness of the resource recovery process.

[0031] Further, according to the pre-constructed solid waste type treatment impact relationship network and the solid waste type set, a set of resource loss impact coefficients when the pre-treated solid waste is pyrolyzed under the initial pyrolysis process parameter set is determined respectively, including:

[0032] A first initial pyrolysis process parameter is randomly extracted from the initial pyrolysis process parameter set; a first solid waste type is randomly extracted from the solid waste type set, and the solid waste types connected to the first solid waste type with a first color edge in the solid waste type treatment impact relationship network are extracted to obtain a first directly affected solid waste type set; solid waste types connected to the first solid waste type with a second color edge in the solid waste type treatment impact relationship network are extracted to obtain a first indirectly affected solid waste type set; a first sub-resource loss influence coefficient of the first solid waste type under the first initial pyrolysis process parameter is determined according to the first directly affected solid waste type set, the first indirectly affected solid waste type set and the loss function; a sub-resource loss influence coefficient set of the solid waste type set under the first initial pyrolysis process parameter is determined, and the sub-resource loss influence coefficient set is weightedly calculated to obtain a first resource loss influence coefficient; and a resource loss influence coefficient set when the pre-treated solid waste is pyrolyzed under the initial pyrolysis process parameter set is determined in combination with the solid waste type treatment impact relationship network and the solid waste type set.

[0033] In a feasible implementation, the system terminal randomly selects a set of initial pyrolysis process parameters from the initial pyrolysis process parameter set as the first initial pyrolysis process parameters, which parameters include temperature, heating rate, reaction time, pressure, air flow velocity, cooling rate, etc. The system terminal performs simulation and evaluation under different pyrolysis conditions through random selection; then, a solid waste type is randomly selected from the solid waste type set and marked as the first solid waste type, and then the relationship between the first solid waste type and other waste types is analyzed based on the previously constructed solid waste type treatment impact relationship network, that is, the first solid waste type is located in the solid waste type treatment impact relationship network. , extract the waste types connected to the first solid waste type through the first color edge. These waste types have a direct impact relationship with the first solid waste type, forming a first set of directly impacted solid waste types. These direct impacts may be manifested as the existence or treatment conditions of one waste directly accelerating or slowing down the decomposition process of another waste. Then extract the waste types connected to the first solid waste type through the second color edge. The impact between these waste types and the first solid waste type is an indirect impact, forming a first set of indirect impacted solid waste types. These indirect impacts usually indirectly affect the pyrolysis process through the side effects of intermediate products or other reactions. Afterwards, the system terminal utilizes The pre-constructed loss function calculates the first sub-resource loss impact coefficient of the first solid waste type under the first initial pyrolysis process parameters according to the first directly affected solid waste type set and the first indirectly affected solid waste type set. The loss function is used to quantify the degree of resource loss and calculate the resource loss of each waste type during the pyrolysis process. On this basis, the system terminal will further determine the sub-resource loss impact coefficient set of the solid waste type set under the initial pyrolysis process parameters, and through weighted calculation, synthesize the resource loss impact coefficient of each waste type under the initial pyrolysis process parameters into an overall first resource loss impact coefficient, wherein each sub-resource loss impact coefficient The weight is determined according to the association relationship label. The first resource loss impact coefficient reflects the resource loss impact of all waste types under given pyrolysis process parameters. Then, the system terminal combines the solid waste type treatment impact network and the solid waste type set, and determines the resource loss impact coefficients of all pre-treated solid wastes under other pyrolysis process parameter groups in the initial pyrolysis process parameter set in the same way, and integrates these resource loss impact coefficients into a resource loss impact coefficient set. Through this process, the system terminal can accurately evaluate the resource loss of solid waste treatment under different pyrolysis process parameters, and provide support for subsequent pyrolysis process optimization.

[0034] Furthermore, the loss function is:

[0035] In a feasible implementation, the pre-constructed loss function aims to quantify the extent of resource loss during the solid waste pyrolysis process, and calculates the total resource loss by considering both direct and indirect impacts. The core goal of the loss function is to evaluate the resource loss based on the relationship between various process parameters and waste types during the pyrolysis process, thereby providing a basis for optimizing the pyrolysis process parameters; the loss function formula is as follows: Among them, LOSS is the first sub-resource loss impact coefficient output by the loss function, which is the total value of resource loss and represents the resource loss caused by different influencing factors in the solid waste treatment process. is the direct impact degree of the mth first directly impacting solid waste type in the first directly impacting solid waste type set on the first solid waste type under the first initial pyrolysis process parameters, which is obtained through model calculation. α is the attenuation coefficient, which is an empirical coefficient used to indicate the attenuation effect of the intensity of direct and indirect impacts due to environmental disturbances, operational errors or other uncertain factors. This coefficient is derived through historical experience and expert decision-making and is used to correct the impact degree. is the indirect impact degree of the tth first indirect impact solid waste type in the first indirect impact solid waste type set on the first solid waste type under the first initial pyrolysis process parameters, which is also obtained through model calculation. Δδ is the empirical error parameter of environmental random disturbance in the pyrolysis process, which is used to correct the error caused by environmental random disturbance or other external factors to ensure that the loss function can reflect the error of the actual situation. M is the total number of first direct impact solid waste types in the first direct impact solid waste type set, and T is the total number of first indirect impact solid waste types in the first indirect impact solid waste type set. The loss function evaluates the total amount of resource loss in the solid waste treatment process under specific pyrolysis process parameters by calculating the direct and indirect impacts between solid waste types. The direct impact and indirect impact coefficients in the formula respectively reflect the contribution of the interaction between different waste types to resource loss, while the attenuation coefficient and empirical error parameter correct the impact due to environmental disturbance and uncertainty factors. Finally, this loss function can provide a reference for optimizing pyrolysis process parameters, help reduce resource loss and improve treatment efficiency.

[0036] For the direct impact It is calculated by inputting the first initial pyrolysis process parameters, the mth first directly affected solid waste type and the first solid waste type into the direct impact analysis model. This model is built based on a neural network. The data used are sample pyrolysis process parameters, sample directly affected solid waste types, sample solid waste types and sample direct impact levels. These data are extracted from the style experiment library. The training method is the same as the aforementioned construction of the pyrolysis process parameter recognition network layer, and is also carried out through forward propagation, loss calculation, back propagation, parameter optimization and other steps; for the indirect impact level It is calculated through the indirect impact analysis model. The data involved in the training process are sample pyrolysis process parameters, sample indirectly affected solid waste type, sample solid waste type and sample indirect impact degree. The training steps remain the same.

[0037] The resource recovery processing module 15 is used to optimize the initial pyrolysis process parameter set based on the resource loss influence coefficient set, determine the target pyrolysis process parameters, and perform resource recovery processing on the pre-treated solid waste based on the target pyrolysis process parameters.

[0038] Specifically, in the resource processing module 15, the system terminal optimizes the initial pyrolysis process parameter set based on the calculated resource loss influence coefficient set. The resource loss influence coefficient set reflects the resource loss that may occur in the solid waste treatment process under different pyrolysis process parameters. By analyzing these coefficients, the system terminal can identify which parameter combinations will lead to less resource loss, thereby selecting the optimization direction and reducing resource loss; the goal of the optimization process is to minimize resource loss and improve the resource efficiency of solid waste by adjusting the pyrolysis process parameters (such as temperature, heating rate, pressure, etc.). The system terminal will gradually adjust the initial pyrolysis process parameters according to the resource loss influence coefficient to find the best process parameter combination to achieve the best resource recovery effect and the lowest resource loss; after determining the target pyrolysis process parameters, the system terminal will use these parameters to treat the pre-treated solid waste for resource recovery. The target pyrolysis process parameters are the process conditions that are optimized to best meet the current waste type and treatment requirements. These parameters ensure that the resource recovery efficiency in the pyrolysis process is the highest and the treatment effect is the most stable. In this way, solid waste can be converted into valuable resources under the best process conditions while reducing environmental impact and resource waste.

[0039] Further, obtaining the target pyrolysis process parameters includes:

[0040] Extract the initial pyrolysis process parameters corresponding to the minimum value in the resource loss influence coefficient set as the directional pyrolysis process parameters, and use the pyrolysis process parameters corresponding to the remaining resource loss influence coefficients in the resource loss influence coefficient set as the pyrolysis process parameter set to be optimized; take the directional pyrolysis process parameters as the optimization direction, adjust the pyrolysis process parameter set to be optimized according to the preset adjustment step, and obtain the adjusted pyrolysis process parameter set; obtain the adjusted resource loss influence coefficient set when the pretreated solid waste is pyrolyzed under the adjusted pyrolysis process parameter set; optimize the directional pyrolysis process parameters according to the size of the adjusted resource loss influence coefficient in the adjusted resource loss influence coefficient set and the adjusted pyrolysis process parameter set, and obtain the target pyrolysis process parameters.

[0041] In a preferred embodiment, the system terminal extracts the minimum resource loss influence coefficient from the resource loss influence coefficient set, and this minimum value represents the minimum resource loss generated under the initial pyrolysis process parameters. The system terminal uses the pyrolysis process parameters corresponding to the minimum resource loss as the directional pyrolysis process parameters, that is, as the starting point of optimization, the directional pyrolysis process parameters represent the preliminary process conditions for optimal resource recovery. At the same time, the pyrolysis process parameters corresponding to other influence coefficients in the resource loss influence coefficient set are classified as the pyrolysis process parameter set to be optimized, and these parameters will be the parts that need to be further adjusted and optimized; then, the system terminal uses the directional pyrolysis process parameters as the optimization direction, and adjusts the pyrolysis process parameter set to be optimized according to the preset adjustment step size. The preset adjustment step size is set according to business needs and is used to control the amplitude of parameter adjustment to ensure that the parameter adjustment during the optimization process will not be too large or too small, thereby achieving a smooth optimization process. Through this adjustment, the system terminal generates a new set of adjusted pyrolysis process parameters; for the adjusted pyrolysis process parameter set The system terminal performs the same impact analysis on the pre-treated solid waste according to the new parameter values, and calculates the corresponding set of adjusted resource loss impact coefficients. These new resource loss impact coefficients reflect the changes in resource loss in the solid waste treatment process under the adjusted pyrolysis process parameters. After that, the system terminal compares the various coefficients in the set of adjusted resource loss impact coefficients, evaluates the resource loss caused by different adjusted pyrolysis process parameters, and then compares the minimum adjusted resource loss impact coefficient with the resource loss impact coefficient corresponding to the current directional pyrolysis process parameters to further optimize the directional pyrolysis process parameters. By optimizing the directional pyrolysis process parameters, the system terminal can more accurately determine the final process conditions to minimize resource losses. Finally, after multiple rounds of adjustment and optimization, the system terminal will obtain the target pyrolysis process parameters. These target parameters are the best process conditions after full optimization, which can achieve the best resource recovery efficiency, while minimizing resource losses, ensuring the best solid waste treatment efficiency, and optimizing resource recovery effects.

[0042] Further, according to the size of the adjusted resource loss influence coefficient in the adjusted resource loss influence coefficient set and the adjusted pyrolysis process parameter set, the directional pyrolysis process parameters are optimized to obtain the target pyrolysis process parameters, including:

[0043] Determine whether there is an adjusted resource loss influence coefficient in the adjusted resource loss influence coefficient set that is less than or equal to the resource loss influence coefficient corresponding to the directional pyrolysis process parameter. If so, update the directional pyrolysis process parameter with the adjusted pyrolysis process parameter corresponding to the minimum value in the adjusted resource loss influence coefficient set to obtain the updated directional pyrolysis process parameter, and continue to optimize the adjusted pyrolysis process parameter set until the preset maximum number of optimization times is met, and use the last updated directional pyrolysis process parameter as the target pyrolysis process parameter.

[0044] In a feasible implementation, the system terminal checks whether there is a value less than or equal to the resource loss impact coefficient corresponding to the directional pyrolysis process parameter in the adjusted resource loss impact coefficient set. That is to say, the system terminal compares each adjusted resource loss impact coefficient with the resource loss impact coefficient corresponding to the current directional pyrolysis process parameter to determine whether there is room for improvement. If there is a resource loss coefficient smaller than the resource loss impact coefficient corresponding to the current directional pyrolysis process parameter, it means that some adjusted process parameter combinations can effectively reduce resource loss. At this time, the adjusted pyrolysis process parameter corresponding to the minimum value in the resource loss impact coefficient set will be extracted. This minimum value represents the optimal adjustment result, which can minimize resource loss. The system terminal Update the corresponding adjusted pyrolysis process parameters to new directional pyrolysis process parameters; then, continue to optimize the remaining adjusted pyrolysis process parameter sets, and further optimize and adjust the new directional pyrolysis process parameters in the same way as mentioned above. This process will be repeated until the preset maximum number of optimizations is reached. This preset maximum number of optimizations is a limit for controlling the optimization process to prevent excessive iterations and ensure that the optimization process is not too long or too complicated; finally, when the optimization process is completed, the system terminal will use the last updated directional pyrolysis process parameters as the final target pyrolysis process parameters, that is, after multiple adjustments and optimizations, the process parameters that are most suitable for the current type of solid waste. These parameters can ensure minimal resource loss and maximize resource recovery efficiency.

[0045] In summary, the solid waste resource treatment system based on pyrolysis technology provided in the embodiment of the present application has the following technical effects:

[0046] The solid waste pretreatment module 11 is used to obtain a solid waste type set of solid waste to be treated, and to perform crushing and drying pretreatment on the solid waste to be treated to obtain pretreated solid waste; the pyrolysis process parameter identification module 12 is used to traverse the solid waste type set to identify and summarize the pyrolysis process parameters to obtain the pyrolysis process parameter threshold; the pyrolysis process parameter generation module 13 is used to generate pyrolysis process parameters with the pyrolysis process parameter threshold as a constraint and parameter diversity as a goal to obtain an initial pyrolysis process parameter set; the influence coefficient determination module 14 is used to determine the resource loss influence coefficient set when the pretreated solid waste is pyrolyzed under the initial pyrolysis process parameter set according to the pre-constructed solid waste type treatment influence relationship network and the solid waste type set; the resource processing module 15 is used to optimize the initial pyrolysis process parameter set based on the resource loss influence coefficient set, determine the target pyrolysis process parameters, and perform resource processing on the pretreated solid waste based on the target pyrolysis process parameters. Through the above steps, the technical problem of difficulty in uniformly determining pyrolysis process parameters due to the complex sources of solid waste and large differences in composition, which in turn affects the pyrolysis treatment efficiency and resource utilization effect, is solved. The technical effect of improving the solid waste resource treatment efficiency, reducing resource losses and ensuring stable and consistent treatment effects is achieved by optimizing the pyrolysis process parameters.

[0047] Embodiment 2 is based on the same inventive concept as the solid waste resource treatment system based on pyrolysis technology in the previous embodiment. Figure 2 As shown, the embodiment of the present application provides a solid waste resource treatment method based on pyrolysis technology, the method comprising:

[0048] A solid waste type set of solid waste to be treated is obtained, and the solid waste to be treated is pre-treated by crushing and drying to obtain pre-treated solid waste; the solid waste type set is traversed to identify and summarize pyrolysis process parameters to obtain pyrolysis process parameter thresholds; pyrolysis process parameters are generated with the pyrolysis process parameter thresholds as constraints and parameter diversity as a goal to obtain an initial pyrolysis process parameter set; according to a pre-constructed solid waste type treatment influence network and a solid waste type set, a resource loss influence coefficient set when the pre-treated solid waste is pyrolyzed under the initial pyrolysis process parameter set is determined respectively; based on the resource loss influence coefficient set, the initial pyrolysis process parameter set is optimized to determine the target pyrolysis process parameters, and the pre-treated solid waste is resource-processed based on the target pyrolysis process parameters.

[0049] Furthermore, the method comprises:

[0050] Pre-constructing a pyrolysis process parameter identification network layer; using the pyrolysis process parameter identification network layer to respectively identify the solid waste type set to obtain a type pyrolysis process parameter set; performing a union on the type pyrolysis process parameter set to obtain the pyrolysis process parameter threshold.

[0051] Furthermore, the method comprises:

[0052] Based on the pyrolysis database, Q association label sets of Q solid waste types in the solid waste type set are extracted, wherein the association label is a direct impact label or an indirect impact label, Q is the total number of solid waste types in the solid waste type set, and Q is an integer greater than or equal to 1; based on the Q association label sets, an influence relationship network is constructed for the Q solid waste types to obtain a constructed solid waste type processing influence relationship network, wherein the nodes of the solid waste type processing influence relationship network represent solid waste types, the first color edge represents direct impact, and the second color edge represents indirect impact.

[0053] Furthermore, the method comprises:

[0054] A first initial pyrolysis process parameter is randomly extracted from the initial pyrolysis process parameter set; a first solid waste type is randomly extracted from the solid waste type set, and the solid waste types connected to the first solid waste type with a first color edge in the solid waste type treatment impact relationship network are extracted to obtain a first directly affected solid waste type set; solid waste types connected to the first solid waste type with a second color edge in the solid waste type treatment impact relationship network are extracted to obtain a first indirectly affected solid waste type set; a first sub-resource loss influence coefficient of the first solid waste type under the first initial pyrolysis process parameter is determined according to the first directly affected solid waste type set, the first indirectly affected solid waste type set and the loss function; a sub-resource loss influence coefficient set of the solid waste type set under the first initial pyrolysis process parameter is determined, and the sub-resource loss influence coefficient set is weightedly calculated to obtain a first resource loss influence coefficient; and a resource loss influence coefficient set when the pre-treated solid waste is pyrolyzed under the initial pyrolysis process parameter set is determined in combination with the solid waste type treatment impact relationship network and the solid waste type set.

[0055] Furthermore, the method comprises:

[0056] The loss function is: Among them, LOSS is the first sub-resource loss impact coefficient output by the loss function, is the direct impact degree of the mth first directly affecting solid waste type in the first directly affecting solid waste type set on the first solid waste type under the first initial pyrolysis process parameters, α is the attenuation coefficient, is the indirect impact degree of the tth first indirectly affected solid waste type in the set of first indirectly affected solid waste types on the first solid waste type under the first initial pyrolysis process parameters, Δδ is the empirical error parameter of the random disturbance of the environment during the pyrolysis process, M is the total number of the first directly affected solid waste types in the set of first directly affected solid waste types, and T is the total number of the first indirectly affected solid waste types in the set of first indirect affected solid waste types.

[0057] Furthermore, the method comprises:

[0058] Extract the initial pyrolysis process parameters corresponding to the minimum value in the resource loss influence coefficient set as the directional pyrolysis process parameters, and use the pyrolysis process parameters corresponding to the remaining resource loss influence coefficients in the resource loss influence coefficient set as the pyrolysis process parameter set to be optimized; take the directional pyrolysis process parameters as the optimization direction, adjust the pyrolysis process parameter set to be optimized according to the preset adjustment step, and obtain the adjusted pyrolysis process parameter set; obtain the adjusted resource loss influence coefficient set when the pretreated solid waste is pyrolyzed under the adjusted pyrolysis process parameter set; optimize the directional pyrolysis process parameters according to the size of the adjusted resource loss influence coefficient in the adjusted resource loss influence coefficient set and the adjusted pyrolysis process parameter set, and obtain the target pyrolysis process parameters.

[0059] Furthermore, the method comprises:

[0060] Determine whether there is an adjusted resource loss influence coefficient in the adjusted resource loss influence coefficient set that is less than or equal to the resource loss influence coefficient corresponding to the directional pyrolysis process parameter. If so, update the directional pyrolysis process parameter with the adjusted pyrolysis process parameter corresponding to the minimum value in the adjusted resource loss influence coefficient set to obtain the updated directional pyrolysis process parameter, and continue to optimize the adjusted pyrolysis process parameter set until the preset maximum number of optimization times is met, and use the last updated directional pyrolysis process parameter as the target pyrolysis process parameter.

[0061] Any step of the method described above can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor to implement any method in the embodiments of the present application, without any unnecessary restrictions.

[0062] Furthermore, the first or second mentioned above may not only represent an order relationship, but may also represent a specific concept, and / or refer to the selection of multiple elements individually or in whole. Obviously, those skilled in the art may make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application intends to include these modifications and variations.

Claims

1. A solid waste resource treatment system based on pyrolysis technology, characterized in that: The system includes: A solid waste pretreatment module, used to obtain a solid waste type set of solid waste to be treated, and to perform crushing and drying pretreatment on the solid waste to be treated to obtain pretreated solid waste; A pyrolysis process parameter identification module is used to traverse the solid waste type set to identify and summarize the pyrolysis process parameters and obtain a pyrolysis process parameter threshold; A pyrolysis process parameter generation module, used to generate pyrolysis process parameters with the pyrolysis process parameter threshold as a constraint and parameter diversity as a goal, to obtain an initial pyrolysis process parameter set; An influence coefficient determination module, for determining a set of resource loss influence coefficients when the pre-treated solid waste is pyrolyzed under the initial pyrolysis process parameter set, respectively, based on a pre-constructed solid waste type processing influence relationship network and a solid waste type set; The resource recovery processing module is used to optimize the initial pyrolysis process parameter set based on the resource loss influence coefficient set, determine the target pyrolysis process parameters, and perform resource recovery processing on the pre-treated solid waste based on the target pyrolysis process parameters.

2. The solid waste resource treatment system based on pyrolysis technology according to claim 1, characterized in that: include: Extracting Q association relationship label sets of Q solid waste types in the solid waste type set based on the pyrolysis database, wherein the association relationship label is a direct impact label or an indirect impact label, Q is the total number of solid waste types in the solid waste type set, and Q is an integer greater than or equal to 1; An influence relationship network is constructed for the Q solid waste types based on the Q association relationship tag sets to obtain a constructed solid waste type processing influence relationship network, wherein the nodes of the solid waste type processing influence relationship network represent the solid waste types, the first color edge represents the direct influence, and the second color edge represents the indirect influence.

3. The solid waste resource treatment system based on pyrolysis technology according to claim 2 is characterized in that: According to the pre-constructed solid waste type treatment impact relationship network and the solid waste type set, a resource loss impact coefficient set when the pre-treated solid waste is pyrolyzed under the initial pyrolysis process parameter set is determined respectively, including: Randomly extracting a first initial pyrolysis process parameter from the initial pyrolysis process parameter set; Randomly extract a first solid waste type from the solid waste type set, extract the solid waste types connected to the first solid waste type by a first color edge in the solid waste type treatment impact relationship network, and obtain a first directly impacted solid waste type set; Extracting the solid waste types connected to the first solid waste type by a second color edge in the solid waste type treatment impact relationship network to obtain a first indirect impact solid waste type set; Determine a first sub-resource loss impact coefficient of the first solid waste type under the first initial pyrolysis process parameters according to the first directly affected solid waste type set, the first indirectly affected solid waste type set and the loss function; Determine a set of sub-resource loss influence coefficients of the solid waste type set under the first initial pyrolysis process parameters, and perform weighted calculation on the set of sub-resource loss influence coefficients to obtain a first resource loss influence coefficient; In combination with the solid waste type treatment impact relationship network and the solid waste type set, a set of resource loss impact coefficients when the pre-treated solid waste is pyrolyzed under the initial pyrolysis process parameter set is determined respectively.

4. The solid waste resource treatment system based on pyrolysis technology according to claim 3 is characterized in that: The loss function is: Among them, LOSS is the first sub-resource loss impact coefficient output by the loss function, is the direct impact degree of the mth first directly affecting solid waste type in the first directly affecting solid waste type set on the first solid waste type under the first initial pyrolysis process parameters, α is the attenuation coefficient, is the indirect impact degree of the tth first indirectly affected solid waste type in the set of first indirectly affected solid waste types on the first solid waste type under the first initial pyrolysis process parameters, Δδ is the empirical error parameter of the random disturbance of the environment during the pyrolysis process, M is the total number of the first directly affected solid waste types in the set of first directly affected solid waste types, and T is the total number of the first indirectly affected solid waste types in the set of first indirect affected solid waste types.

5. The solid waste resource treatment system based on pyrolysis technology according to claim 1, characterized in that: include: Extracting the initial pyrolysis process parameter corresponding to the minimum value in the resource loss influence coefficient set as the directional pyrolysis process parameter, and taking the pyrolysis process parameters corresponding to the remaining resource loss influence coefficients in the resource loss influence coefficient set as the pyrolysis process parameter set to be optimized; Taking the directional pyrolysis process parameter as the optimization direction, adjusting the set of pyrolysis process parameters to be optimized according to the preset adjustment step length to obtain the adjusted pyrolysis process parameter set; Obtaining a set of adjusted resource loss influence coefficients when pyrolyzing the pretreated solid waste under the set of adjusted pyrolysis process parameters; According to the size of the adjusted resource loss influence coefficient in the adjusted resource loss influence coefficient set and the adjusted pyrolysis process parameter set, the directional pyrolysis process parameters are optimized to obtain the target pyrolysis process parameters.

6. The solid waste resource treatment system based on pyrolysis technology according to claim 5, characterized in that: According to the size of the adjusted resource loss influence coefficient in the adjusted resource loss influence coefficient set and the adjusted pyrolysis process parameter set, the directional pyrolysis process parameters are optimized to obtain the target pyrolysis process parameters, including: Determine whether there is an adjusted resource loss influence coefficient in the adjusted resource loss influence coefficient set that is less than or equal to the resource loss influence coefficient corresponding to the directional pyrolysis process parameter. If so, update the directional pyrolysis process parameter with the adjusted pyrolysis process parameter corresponding to the minimum value in the adjusted resource loss influence coefficient set to obtain the updated directional pyrolysis process parameter, and continue to optimize the adjusted pyrolysis process parameter set until the preset maximum number of optimization times is met, and use the last updated directional pyrolysis process parameter as the target pyrolysis process parameter.

7. The solid waste resource treatment system based on pyrolysis technology according to claim 1 is characterized in that: Traverse the solid waste type set to identify and summarize the pyrolysis process parameters, and obtain the pyrolysis process parameter thresholds, including: Pre-constructed pyrolysis process parameter identification network layer; Using the pyrolysis process parameter identification network layer to identify the solid waste type set respectively, to obtain a type pyrolysis process parameter set; The pyrolysis process parameter set of the type is unioned to obtain the pyrolysis process parameter threshold.

8. A method for recycling solid waste based on pyrolysis technology, characterized in that: The method is performed by a solid waste resource treatment system based on pyrolysis technology according to any one of claims 1 to 7, comprising: Obtaining a set of solid waste types of solid waste to be processed, and performing crushing and drying pretreatment on the solid waste to be processed to obtain pretreated solid waste; Traversing the solid waste type set to identify and summarize pyrolysis process parameters, and obtaining pyrolysis process parameter thresholds; Taking the pyrolysis process parameter threshold as a constraint and parameter diversity as a goal, pyrolysis process parameter generation is performed to obtain an initial pyrolysis process parameter set; Determine, based on the pre-constructed solid waste type treatment impact relationship network and the solid waste type set, a set of resource loss impact coefficients when the pre-treated solid waste is pyrolyzed under the initial pyrolysis process parameter set; The initial pyrolysis process parameter set is optimized based on the resource loss influence coefficient set, the target pyrolysis process parameters are determined, and the pre-treated solid waste is processed for resource recovery based on the target pyrolysis process parameters.

Images