Environmental protection grade assessment method and system based on solid biofuel

Abstract

The present application relates to the field of energy and environmental technology, and provides an environmental protection level assessment method and system based on solid biofuels. The method includes: reading the basic information of the target fuel throughout its life cycle; traversing the information, extracting and integrating effective characteristics, and determining the fuel information system; determining multiple assessment dimensions, single-dimensional parallel training, and building an adaptive assessment model; big data retrieval, determining the verification interval according to the fuel type, including the environmental protection level and difference; combining the adaptive model, analyzing the fuel system in parallel, and mutually verifying with the verification interval, and outputting the environmental protection level. The present application solves the technical problem that the prior art often only focuses on the characteristics of a certain stage of the fuel or only evaluates from a single dimension, ignoring the comprehensive impact of the entire life cycle of the fuel, resulting in insufficient accuracy of the assessment results. It achieves the effect of improving the assessment efficiency and ensuring the accuracy of the assessment results by determining multiple assessment dimensions and building an adaptive assessment model.

Description

Technical Field

[0001] The present application relates to the field of energy and environmental science and technology, specifically to the field of energy and environmental technology, and in particular to a method and system for evaluating an environmental rating based on solid biofuels. Background Art

[0002] With the improvement of environmental awareness and the optimization of energy structure, solid biofuels, as a clean and renewable form of energy, are gradually occupying an important position in the energy field. However, accurately evaluating the environmental protection level of solid biofuels has always been a difficult problem in the technical field. When evaluating the environmental protection level of solid biofuels, existing technologies often only focus on the characteristics of the fuel at a certain stage, or only evaluate from a single dimension. This approach ignores the comprehensive impact of the fuel throughout its life cycle, from raw material collection, production and processing to actual use, resulting in insufficient accuracy of the evaluation results. Due to the failure to fully consider various factors in the fuel throughout its life cycle, the evaluation results are often difficult to truly reflect the environmental performance of the fuel, which to a certain extent hinders the promotion and application of solid biofuels. Summary of the invention

[0003] This application provides an environmental rating assessment method and system based on solid biofuels, aiming to solve the technical problem that the existing technology often only focuses on the characteristics of the fuel at a certain stage or only evaluates from a single dimension, ignoring the comprehensive impact of the entire life cycle of the fuel, resulting in insufficient accuracy of the assessment results.

[0004] In view of the above problems, the present application provides an environmental protection grade assessment method and system based on solid biofuel.

[0005] The first aspect disclosed in the present application provides an environmental protection grade assessment method based on solid biofuel, the method comprising: reading the basic fuel information of the target fuel throughout its life cycle, wherein the entire life cycle includes the raw material stage, the production and processing stage, and the usage stage; traversing the basic fuel information, extracting and associating effective fuel characteristics, and determining the fuel information system of the target fuel; determining multiple assessment dimensions, performing single-dimensional parallel training, and determining an adaptive assessment model, wherein the assessment dimensions include a component analysis dimension, a characteristic analysis dimension, and a periodic stage dimension; performing big data retrieval, and determining a verification interval based on the fuel type of the target fuel, the verification interval including an environmental protection grade interval and a grade difference interval; combining the adaptive assessment model, performing parallel independent analysis on the fuel information system, and performing mutual verification based on the verification interval, and outputting a fuel environmental protection grade, wherein the fuel environmental protection grade is calculated based on the branch mean.

[0006] Another aspect disclosed in the present application provides an environmental protection grade assessment system based on solid biofuel, the system comprising: an information reading module, the information reading module is used to read the basic fuel information of the target fuel throughout its life cycle, wherein the entire life cycle includes the raw material stage, the production and processing stage, and the use stage; an extraction and integration module, the extraction and integration module is used to traverse the basic fuel information, extract and correlate effective fuel characteristics, and determine the fuel information system of the target fuel; a parallel training module, the parallel training module is used to determine multiple evaluation dimensions, perform single-dimensional parallel training, and determine an adaptive evaluation model, wherein the evaluation dimensions include component analysis dimensions, characteristic analysis dimensions, and periodic stage dimensions; a data retrieval module, the data retrieval module is used to perform big data retrieval, and determine a verification interval based on the fuel type of the target fuel, the verification interval includes an environmental protection grade interval and a grade difference interval; a mutual verification module, the mutual verification module is used to combine the adaptive evaluation model, perform parallel independent analysis of the fuel information system, and mutual verification based on the verification interval, and output a fuel environmental protection grade, wherein the fuel environmental protection grade is calculated based on the branch mean.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] The above-mentioned environmental protection grade assessment method based on solid biofuel collects comprehensive information about the fuel from the raw material stage to the production and processing stage and then to the use stage. Subsequently, the key characteristics of the fuel are extracted from this large amount of information and integrated into a complete fuel information system. In order to accurately evaluate the environmental performance of the fuel, multiple evaluation dimensions are determined, including the composition, characteristics and performance of the fuel at each stage of its life cycle. By parallel training on these dimensions, an adaptive assessment model is constructed, which enables flexible assessment according to the characteristics of different fuels. In addition, in order to verify the accuracy of the assessment results, the corresponding verification intervals are determined according to the fuel type using big data retrieval technology. These intervals include the range of environmental protection grades and the difference between grades, which are used for comparison and verification with the assessment results. Finally, the fuel information system is analyzed independently in parallel by combining the adaptive assessment model and the verification interval, and the environmental protection grade of the fuel is determined by mutual verification. This grade is calculated based on the average value of multiple analysis branches, thereby improving the accuracy and reliability of the assessment. This method achieves accurate and efficient assessment of the environmental protection grade of solid biofuels by comprehensively collecting and analyzing fuel information and using adaptive assessment models and big data verification technology.

[0009] 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

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0011] Figure 1 A schematic diagram of a process for evaluating an environmental rating of solid biofuels in one embodiment;

[0012] Figure 2 The present invention is a system architecture diagram for evaluating the environmental protection level based on solid biofuel in one embodiment.

[0013] Explanation of the accompanying drawings: information reading module 1, extraction and integration module 2, parallel training module 3, data retrieval module 4, mutual verification module 5. DETAILED DESCRIPTION

[0014] The embodiments of the present application provide an environmental rating assessment method and system based on solid biofuels to solve the technical problem that the prior art often only focuses on the characteristics of the fuel at a certain stage or only assesses from a single dimension, ignoring the comprehensive impact of the entire life cycle of the fuel, resulting in insufficient accuracy of the assessment results.

[0015] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0016] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or inherent to these processes, methods, products or devices.

[0017] Embodiment 1:

[0018] like Figure 1As shown, the present application provides a method for evaluating the environmental protection level based on solid biofuel, the method comprising:

[0019] Read the fuel basic information of the entire life cycle of the target fuel, wherein the entire life cycle includes the raw material stage - the production and processing stage - the use stage;

[0020] Solid biofuel is a solid fuel made from biomass through a specific process. Its raw materials mainly come from renewable resources such as agricultural and forestry wastes, animal and plant oil residues, etc. It has the characteristics of wide sources, renewable, low-carbon and environmentally friendly. Against the backdrop of global energy structure transformation and increasing attention to environmental protection, solid biofuel, as a renewable, low-carbon and environmentally friendly energy form, has gradually emerged in the energy market. However, how to scientifically and accurately evaluate its environmental protection level and ensure its environmental performance during its use has become an urgent problem to be solved.

[0021] In the embodiment of the present application, when evaluating the environmental protection level of solid biofuel, the system terminal first comprehensively collects the basic information of the fuel in its entire life cycle. This full life cycle covers the entire process from raw material collection to final use, including the raw material stage, the production and processing stage, and the use stage. In the raw material stage, the system terminal focuses on the original source, type and composition of the fuel, which is essential for understanding the essential characteristics of the fuel. The production and processing stage involves the manufacturing process of the fuel, including processing methods, the use of additives, and possible by-products, etc., all of which affect the final quality and environmental performance of the fuel. In the use stage, the system terminal focuses on the types and quantities of pollutants released by the fuel during combustion, as well as key indicators such as combustion efficiency. By collecting these basic information throughout the life cycle, a more comprehensive and in-depth understanding of the overall picture of the fuel can be achieved, providing a solid data foundation for subsequent environmental protection level assessments. This helps to more accurately assess the environmental performance of the fuel, provide a scientific basis for the selection and use of the fuel, and promote the sustainable development of solid biofuels.

[0022] Traversing the basic fuel information, extracting and correlating effective fuel characteristics, and determining the fuel information system of the target fuel;

[0023] In one embodiment, after collecting the basic information of the target fuel throughout its life cycle, the system terminal conducts in-depth analysis and processing of this information. First, these basic information are traversed one by one to extract effective characteristics related to the environmental performance of the fuel. These characteristics include the chemical composition, physical properties, process characteristics, combustion efficiency, types of emissions, etc. of the fuel. After extracting these effective characteristics, the system terminal performs correlation integration. This means that the characteristics of different stages are correlated and the characteristic coefficients are identified to form a complete and coherent fuel information system. In this way, the system terminal can see the performance of the fuel throughout its life cycle more clearly, so as to more accurately evaluate its environmental protection level. Through this series of extraction and correlation integration work, the fuel information system of the target fuel can be finally determined. This system not only contains comprehensive information about the fuel, but also highlights the key characteristics related to environmental performance, providing strong support for subsequent environmental protection level assessment.

[0024] Furthermore, the present application provides a fuel information system for determining the target fuel, including:

[0025] Identify the basic information of the fuel and determine the main characteristic line based on the whole life cycle;

[0026] Setting characteristic dimensions, wherein the characteristic dimensions include direct impact characteristics, indirect impact characteristics, favorable characteristics, and unfavorable characteristics;

[0027] Preferably, when evaluating the environmental protection level of solid biofuel, the system terminal comprehensively sorts out the basic information of the fuel collected, including the type of raw materials, production process, and usage method. Analyze this information and identify the features directly related to environmental protection performance. Subsequently, from the perspective of the entire life cycle, extract the key features that affect the environmental protection performance of the fuel, such as the sustainability of the raw materials, the environmental protection degree of the production process, and the combustion efficiency. After that, analyze the changing trend of the key features throughout the life cycle, such as the characteristic changes from raw materials to products and then to the use stage. Determine which features have the greatest impact on environmental protection performance at a certain stage of the life cycle. Then, based on the characteristic change trend, identify the key factors and key links that affect the environmental protection performance of the fuel. These factors and links may involve the selection of raw materials, optimization of the production process, improvement of the usage method, etc. Finally, based on the above analysis, the system terminal determines a main characteristic line throughout the entire life cycle. This main characteristic line runs through the entire life cycle of the fuel, including the key characteristics of each stage such as raw material collection, production and processing, and use, and can clearly reflect the changes in environmental protection performance and key influencing factors of the fuel throughout the life cycle.

[0028] After determining the main characteristic line, the system terminal sets the characteristic dimensions to further analyze these characteristics. The characteristic dimensions include direct impact characteristics, indirect impact characteristics, favorable characteristics and unfavorable characteristics. These dimensions help to more comprehensively understand the fuel performance and its impact on the environment. Among them, direct impact characteristics refer to characteristics that directly affect the environmental performance of the fuel, such as the sustainability of raw materials. If the raw materials used in the fuel come from renewable resources and the collection process has little impact on the environment, then the sustainability of this raw material will have a positive impact on the environmental protection level of the fuel. Indirect impact characteristics refer to factors that indirectly affect the environmental performance of the fuel, such as production process characteristics. The environmental protection level of the production process, energy consumption, and waste treatment methods will indirectly affect the environmental performance of the fuel. Favorable characteristics refer to characteristics that have a positive contribution to the environmental performance of the fuel, such as efficient combustion and low emissions in combustion characteristics. These characteristics can improve the environmental protection level of the fuel and reduce environmental pollution. Unfavorable characteristics, on the contrary, refer to characteristics that have a negative impact on the environmental performance of the fuel, such as high pollution emissions or low combustion efficiency. These characteristics will reduce the environmental protection level of the fuel and increase the environmental burden. By setting these characteristic dimensions, it is possible to analyze the fuel's full life cycle characteristics more deeply, thereby more accurately assessing its environmental rating. This helps system terminals make more informed energy choices and promote sustainable development.

[0029] The environmental protection related features of the basic fuel information are extracted, and the main feature line and the characteristic dimension are combined to perform cross-correlation and feature coefficient identification to determine the fuel information system.

[0030] Preferably, when evaluating the environmental protection level of solid biofuel, the system terminal extracts features closely related to environmental protection from the basic information of the fuel. These features include the environmental protection of the raw materials, the pollution emissions during the production process, and the combustion efficiency and emission types during the use stage. These environmental protection related features provide the system terminal with a preliminary understanding of the environmental protection performance of the fuel. Subsequently, these environmental protection related features are correlated with the main characteristic line previously determined. The main characteristic line runs through the entire life cycle of the fuel and reveals the key influencing factors of its environmental protection performance. By combining the environmental protection related features with the main characteristic line and then using the characteristic dimension, a deeper understanding of the environmental protection performance of the fuel in each link can be achieved. Specifically, the system terminal checks each environmental protection related feature one by one and accurately matches it with the key nodes on the main characteristic line according to the characteristic dimension. The characteristic dimension plays a vital role here, helping the system terminal to identify and distinguish different aspects involved in the environmental protection related features, such as the sustainability of the raw materials, the energy efficiency of the production process, and the environmental impact of the emissions. For example, when an environmental protection feature closely related to the sustainability of the raw materials is found, the system terminal accurately associates the feature with the feature of the raw material stage on the main characteristic line according to the guidance of the characteristic dimension. This association not only considers the source and acquisition method of raw materials, but also analyzes the utilization efficiency of raw materials and their impact on the environment, thereby comprehensively evaluating the impact of raw material sustainability on the environmental performance of fuels. Similarly, when an environmental feature related to pollution emission control in the production process is found, the system terminal will use the characteristic dimension to associate the feature with the feature of the production and processing stage on the main characteristic line. This association covers multiple aspects such as energy consumption in the production process, the type and amount of emissions, and the effectiveness of pollution control measures, thereby comprehensively evaluating the impact of the production process on the environmental performance of fuels. Through the guidance of the characteristic dimension and the precise matching of the system terminal, the position and role of each environmental-related feature in the entire life cycle can be better understood, so as to more accurately evaluate their impact on the environmental performance of fuels. This not only helps to identify the key factors and potential risks of fuel environmental performance, but also provides strong support for subsequent environmental grade assessment and decision-making. After that, the system terminal determines multiple weighting factors, traverses the environmental-related features according to these weighting factors, and then performs hierarchical weighting configuration based on the traversal results. Then, the weighted operation is performed on the weight distribution results to obtain the characteristic coefficient identification. Finally, through this series of inter-correlations and characteristic coefficient identification work, the system terminal can determine a complete fuel information system. This system not only contains the basic information of the fuel, but also highlights its environmental protection-related characteristics, and integrates and quantifies them through the main characteristic lines and characteristic dimension coefficients. This fuel information system will provide comprehensive and accurate data support for subsequent environmental protection level assessments.

[0031] Furthermore, the present application provides a method for identifying characteristic coefficients, and the method further includes:

[0032] Environmental relevance is used as the first weighting factor, and characteristic strength is used as the second weighting factor;

[0033] Based on the first weighting factor and the second weighting factor, traverse the environmental protection related features to perform hierarchical weighting configuration and determine the hierarchical weight distribution;

[0034] Based on the hierarchical weight distribution, the element weights of each environmental protection related feature are added up to determine the feature coefficient.

[0035] Optionally, in the weight configuration process of environmental protection related features, the system terminal first considers the primary factor of environmental protection relevance, which directly reflects the degree of influence of the feature on environmental protection performance. Secondly, the feature strength is taken as the second factor, which is also an important basis for weighting, and it measures the significance of the feature in environmental protection performance. Subsequently, based on these two weighting factors, the system terminal reviews each environmental protection related feature one by one and sets an initial weight value for each feature. After that, a hierarchical weight configuration model is constructed according to the internal logical relationship and importance of the environmental protection related features. This model should be able to clearly reflect the hierarchical relationship and mutual influence between the features. Then, in each layer, the weight value of each feature is further refined and adjusted according to their performance in environmental protection relevance and feature strength. After the hierarchical weighting configuration, the system terminal obtains a hierarchical weight distribution result. This result reflects the relative importance and contribution of different environmental protection related features in the overall environmental protection performance. After completing the hierarchical weighting configuration, the system terminal sums the weights of each environmental protection related feature, so as to obtain the final coefficient of each feature. This coefficient is a quantitative indicator that can comprehensively reflect the contribution of the feature in environmental protection performance. In summary, this process is a quantitative empowerment process, which helps to more accurately evaluate the environmental performance of the fuel and provide a scientific basis for subsequent environmental rating assessment and decision-making.

[0036] Determine multiple evaluation dimensions, conduct single-dimensional parallel training, and determine an adaptive evaluation model, where the evaluation dimensions include component analysis dimension, characteristic analysis dimension, and cycle phase dimension;

[0037] In one embodiment, in the process of determining the adaptive evaluation model, the system terminal first defines the three main dimensions of the evaluation: the component analysis dimension, the characteristic analysis dimension, and the periodic phase dimension. These dimensions provide a comprehensive and in-depth analysis of the target object from different angles. In the single-dimensional parallel training stage, the system terminal performs independent branch training for each dimension. This means that the system terminal constructs corresponding evaluation branches for the three aspects of component analysis, characteristic analysis, and periodic phase, and performs a large amount of data training and optimization. This enables each branch to focus on a specific evaluation dimension, thereby more accurately capturing the key information and features under the dimension. Finally, by integrating these evaluation branches, the system terminal constructs an adaptive evaluation model. This model can adaptively adjust the weights and parameters between different dimensions according to actual conditions and needs, thereby achieving a comprehensive, objective and accurate evaluation of the target object. This adaptability makes the evaluation model more flexible and practical, and can adapt to evaluation tasks under different scenarios and needs. In summary, by determining multiple evaluation dimensions, conducting single-dimensional parallel training, and constructing an adaptive evaluation model, a comprehensive, in-depth and accurate evaluation of the target object can be achieved, providing strong support for decision-making and optimization.

[0038] Furthermore, the present application provides an adaptive evaluation model, and the method further includes:

[0039] The adaptive evaluation model includes a first evaluation branch, a second evaluation branch and a third evaluation branch in parallel;

[0040] Preferably, the adaptive evaluation model is a comprehensive and flexible evaluation tool, which consists of three parallel evaluation branches: the first evaluation branch, the second evaluation branch and the third evaluation branch. Each evaluation branch is trained and optimized for a specific evaluation dimension and can independently process and analyze relevant data. The first evaluation branch focuses on the component analysis dimension, extracts key information by deeply analyzing the component ratio and process variables of the target object, and evaluates accordingly. It can help the system terminal understand the basic composition and components of the target object and provide basic data for subsequent evaluation. The second evaluation branch focuses on the characteristic analysis dimension, which focuses on the good and bad state characteristics of the target object, and obtains the corresponding evaluation results by quantitatively analyzing and comparing its characteristics. This branch can reveal the advantages and disadvantages of the target object in specific aspects and provide a more comprehensive evaluation perspective for the system terminal. The third evaluation branch focuses on the periodic stage dimension, which considers the staged summary of the target object, that is, the changes and development trends in different time periods. By analyzing and predicting historical data, this branch can evaluate the performance and potential risks of the target object in different cycles and provide a basis for long-term decision-making. These three evaluation branches run in parallel, independently but complementary to each other, and together constitute the core of the adaptive evaluation model. By integrating the evaluation results of each branch, the adaptive evaluation model can comprehensively consider information from multiple dimensions to form a comprehensive and accurate evaluation conclusion. At the same time, the model is also adaptive and can adjust the weights and parameters of different branches according to actual conditions to adapt to evaluation tasks under different scenarios and requirements. In general, the adaptive evaluation model can achieve a comprehensive evaluation of the target object in multiple dimensions by running three evaluation branches in parallel. It combines flexibility and accuracy, providing strong support for decision-making.

[0041] Among them, the evaluation branch supervision training methods include:

[0042] Based on the ingredient ratio and process variables, supervise the training of the first evaluation branch;

[0043] Based on the principle of finite element analysis, the second evaluation branch is supervised and trained based on the characteristics of good and bad states, in which finite element constraints are performed based on single environmental protection indicators;

[0044] The third evaluation branch is supervised and trained based on the phased aggregate benchmark.

[0045] Preferably, the component ratio refers to various variable factors involved in the production process. The staged assembly refers to a key stage in the production process, such as processing, molding, drying, etc. In the adaptive evaluation model, the supervised training method of each evaluation branch adopts different benchmarks and methods to ensure its accuracy and effectiveness.

[0046] For the first evaluation branch, the system terminal collects data on the composition ratio and process variables of the target object, which covers samples from different batches and under different production conditions to ensure the generalization ability of the first evaluation branch. Subsequently, the collected data is cleaned and sorted, outliers, duplicate data, and incomplete records are removed, and the cleaned data set is divided into a sample set and a test set. Feature extraction is then performed on the cleaned data set, and key features are determined based on historical experience. These key features will serve as the basis for building the first evaluation branch. After that, the formula of the linear regression model is determined based on the extracted key features, where each feature corresponds to a coefficient. Initial values ​​are randomly assigned to the intercept term of the linear regression model and the coefficient of each feature, and the mean square error is defined to measure the difference between the model prediction value and the actual target value. Then, the training set is used to train the linear regression model using gradient descent through multiple iterations, and the parameters of the trained linear regression model are updated until the loss function converges. Finally, the performance of the model is evaluated using the test set, the current mean square error is calculated, and the trained linear regression model is evaluated. If the evaluation result does not meet the requirements, adjust the model parameters or rebuild the linear regression model formula to optimize the model performance, and repeat this process until it meets the expectations. If it meets the requirements, the trained linear regression model is used as the first evaluation branch.

[0047] For the second evaluation branch, the system terminal explicitly evaluates which good and bad characteristics of the target fuel, such as combustion efficiency, emission composition, etc. These characteristics will be used as the output of the evaluation branch. Subsequently, a finite element analysis model is established based on the physical properties and combustion process of the target fuel. The model can simulate the combustion process of the fuel and take into account factors such as fuel composition and combustion conditions. In the finite element model, the system terminal uses a single environmental indicator as a constraint. These constraints include emission limits, fuel consumption limits, etc. By incorporating these constraints into the model, it can be ensured that the simulation results meet environmental requirements. After that, features related to the evaluation of the target fuel are extracted from the finite element model, which include temperature distribution and pressure changes during combustion. Then, according to the good and bad characteristic benchmark, each simulation result is labeled accordingly, that is, good or bad. These labels reflect the performance of the fuel under different conditions. Then, using the extracted features and corresponding labels, the second evaluation branch is supervised through the same training process as described above. The second evaluation branch will learn how to predict the good and bad characteristics of the fuel based on the input features. Finally, an independent test set is used to evaluate the trained second evaluation branch. The performance of the second evaluation branch is evaluated by comparing the consistency between the prediction results of the second evaluation branch and the actual labels. Based on the evaluation results, the second evaluation branch is tuned to improve its prediction accuracy and reliability.

[0048] For the third evaluation branch, the system terminal uses the same process of supervised training for the first evaluation branch as above, and performs supervised training based on the phased total. This means that the system terminal trains and optimizes the third evaluation branch by analyzing the overall performance and development trend of the target object at different stages. This method enables the third evaluation branch to have comprehensive evaluation capabilities in the periodic and phased dimensions, and can accurately capture the changes and risks of the target object in different time periods. Afterwards, the system terminal connects the three constructed evaluation branches in parallel to form an adaptive evaluation model.

[0049] In summary, each evaluation branch in the adaptive evaluation model uses different supervised training methods to ensure its accuracy and effectiveness in its respective dimensions. This diverse training method makes the entire evaluation model more comprehensive and flexible, and can better adapt to evaluation tasks in different scenarios and requirements.

[0050] Performing big data retrieval, and determining a verification interval based on the fuel type of the target fuel, wherein the verification interval includes an environmental protection grade interval and a grade difference interval;

[0051] In one embodiment, the system terminal performs a big data search based on the fuel type of the target fuel, the main purpose of which is to determine the verification interval related to the fuel. This verification interval includes two important aspects, namely the environmental protection grade interval and the grade difference interval. Specifically, the system terminal uses big data tools to perform extensive data retrieval for the fuel type of the target fuel. This includes collecting relevant data from industry reports, data released by scientific research institutions, corporate public information, and various resources on the Internet. The content of the retrieval includes the composition, production process, environmental protection standards, performance test results, etc. of the fuel. Subsequently, the data directly related to the target fuel is screened out from the retrieved data and integrated. This includes removing duplicate data, cleaning erroneous data, filling missing data, etc. to ensure the accuracy and completeness of the data. After that, based on the integrated data, the performance of the target fuel in terms of environmental protection is analyzed. This involves evaluating the environmental protection indicators of the fuel, such as the type and concentration of emissions, energy consumption, etc. According to the evaluation results, combined with the upper and lower limits of the industry environmental protection grade marking, the fuel is divided into different environmental protection grades, and the range of each grade is determined, thereby forming an environmental protection grade interval. In order to determine the grade difference interval, the system terminal compares the specific numerical differences between two adjacent environmental protection grades. These differences include the reduction in emissions, the reduction rate of energy consumption, etc. By calculating these differences, the specific range of the grade difference interval can be obtained. This grade difference interval refers to the range of differences between different environmental protection levels. This interval involves specific values ​​such as differences in emissions, differences in combustion efficiency, etc. Understanding the grade difference interval helps to more deeply understand the differences between different environmental protection levels, as well as the impact of these differences on fuel performance and usage effects. In summary, based on big data retrieval of the fuel type of the target fuel, its environmental protection grade interval and grade difference interval can be determined. These two intervals together constitute the verification interval of the fuel. By understanding this verification interval, you can have a deeper understanding of the environmental performance and differences of the target fuel.

[0052] Furthermore, the present application provides an environmental protection level interval, and the method further includes:

[0053] The environmental protection grade interval is determined based on the upper and lower limits of the environmental protection grade of the fuel type, and the grade difference interval is the evaluation deviation interval range;

[0054] Preferably, the environmental protection grade interval and the grade difference interval are important references for evaluating fuel performance. The environmental protection grade interval is determined based on the upper and lower limits of the environmental protection grade of the fuel, which reflects the possible range of environmental protection performance of this type of fuel. The grade difference interval is the deviation range in the evaluation process, which takes into account the performance differences caused by factors such as different test conditions and sample differences. Specifically, the system terminal finds the best performance or highest standard of this type of fuel in environmental protection from the retrieved data. This involves key indicators such as the lowest concentration of emissions and the lowest value of energy consumption. These best performances or highest standards constitute the upper limit of the environmental protection grade. Similarly, the minimum requirements or worst performance of this type of fuel in environmental protection are found from the data. These minimum requirements or worst performances constitute the lower limit of the environmental protection grade. The determined upper and lower limits are in line with the industry environmental protection grade requirements. By determining the upper and lower limits, the system terminal obtains the environmental protection grade interval of the fuel type. The environmental protection grade interval helps the system terminal understand the environmental protection performance of the fuel. It represents what environmental protection standards this fuel can achieve in the best and worst cases, respectively, and reflects the possible range of environmental protection performance of this type of fuel. Subsequently, the system terminal selects the performance evaluation data for this type of fuel from the retrieved data. The collected evaluation data is then statistically analyzed to calculate the standard deviation of each performance indicator to measure the degree of dispersion between the data. Afterwards, a deviation range is determined based on the results of the statistical analysis. This range covers most of the evaluation data and reflects the uncertainty in the evaluation process. The grade difference interval allows the system terminal to understand the maximum acceptable error range when evaluating the performance of this fuel, which is crucial to accurately understand the actual performance of the fuel. By comprehensively considering the environmental grade interval and the grade difference interval, the performance characteristics of the fuel can be more comprehensively understood, thereby providing an important basis for its selection, production optimization and the formulation of environmental protection policies, which helps to improve the environmental performance of the fuel.

[0055] The verification rules include:

[0056] Based on the environmental protection level interval, the branch parallel output is verified once to determine a first verification result;

[0057] Performing difference calculation on the branch parallel outputs, performing secondary verification based on the level difference interval, and determining a second verification result;

[0058] If both the first verification result and the second verification result are yes, the verification is passed.

[0059] Preferably, the verification rule is an important step to ensure the accuracy of fuel grade assessment. First, the system terminal performs a verification on the branch parallel output according to the environmental protection grade interval, which is mainly to check whether the output result falls within the expected environmental protection performance range, thereby obtaining the first verification result. Subsequently, the branch parallel output is subjected to differential calculation. Specifically, the system terminal collects data of all branch parallel outputs. These data represent the performance indicators of different branches when processing the same fuel type. Subsequently, the collected branch output data are subjected to pairwise difference calculation. That is, for each pair of branches, the difference between their outputs is calculated to obtain a set of differential values. The calculated differential values ​​are then recorded for subsequent verification and analysis. Afterwards, the calculated differential values ​​are compared with the grade differential interval. For each pair of branch differential values, check whether they fall within the grade differential interval. According to the comparison result of the differential value and the grade differential interval, the second verification result is determined. If all differential values ​​fall within the grade differential interval, it means that the performance difference between the branches is within a reasonable range, and the second verification result is correct; if any differential value exceeds the interval, it means that there is an unreasonable performance difference, and the second verification result is abnormal. After obtaining the first verification result and the second verification result, the system terminal judges the two verification results. When both the first verification result and the second verification result are correct, that is, the output result meets the environmental protection level requirements and is within the assessment deviation range, it is judged to be qualified. Such verification rules ensure the accuracy and reliability of the assessment results and provide a strong guarantee for the application of fuel.

[0060] In combination with the adaptive evaluation model, the fuel information system is analyzed independently in parallel and mutually verified based on the verification interval to output a fuel environmental protection grade, wherein the fuel environmental protection grade is calculated based on the branch mean.

[0061] In one embodiment, the system terminal combines the adaptive evaluation model to analyze the fuel information system in parallel and independently. This means that each branch evaluates the fuel performance independently without being affected by other branches. At the same time, according to the previously determined verification interval and verification rules, the branch outputs are mutually verified to ensure the accuracy and consistency of the evaluation results. Finally, the fuel environmental protection level is calculated based on the mean value and indicator importance of each branch output. This method comprehensively considers the evaluation results of each branch and can more comprehensively reflect the environmental protection performance of the fuel. Through such an analysis and verification process, the environmental protection level of the fuel can be output more accurately, providing strong support for relevant decisions.

[0062] Further, the present application provides the output fuel environmental protection grade, and the method further includes:

[0063] Based on the adaptive evaluation model, performing branch-by-branch parallel analysis of the fuel information system to determine branch evaluation results;

[0064] In combination with the verification rule, performing a qualification verification on the branch evaluation result;

[0065] If the verification is qualified, the branch evaluation results are mapped to the environmental protection index and the average is calculated to determine the environmental protection index level;

[0066] Optionally, based on the adaptive evaluation model, the system terminal performs a branch-by-branch parallel analysis of the fuel information system. This means that each branch is evaluated independently to obtain its own branch evaluation results. This ensures that each branch can give full play to its expertise and conduct a detailed and comprehensive evaluation of fuel performance. Subsequently, these branch evaluation results are verified for environmental protection level and level difference in combination with the set verification rules. This step is crucial because it ensures the accuracy and reliability of the evaluation results. Only branch evaluation results that pass the verification can be further used for subsequent analysis and calculation. If the branch evaluation results are verified, the system terminal will further map these results with environmental protection indicators and calculate their mean. Specifically, the system terminal matches the evaluation results of each branch with the corresponding indicators in the environmental protection indicator system. Ensure that the evaluation results of each branch can find the corresponding environmental protection indicators. If the data formats of the evaluation results of different branches are not uniform, the corresponding data format conversion is required to ensure the accuracy of subsequent calculations. Before calculating the mean, confirm again which branch evaluation results have passed the verification. Only qualified branch results are included in the scope of the mean calculation. For each environmental indicator, the mean of the evaluation results of all qualified branches on that indicator is calculated. This can reflect the overall performance level of the indicator. Subsequently, the calculated mean of the single indicator is compared with the set environmental grade range to determine the grade of each indicator and obtain the environmental indicator grade. In general, this process combines the advantages of the adaptive evaluation model and the rigor of the verification rules, and can more accurately evaluate the environmental performance of the fuel and determine its environmental indicator grade. This is of great significance for guiding the selection and use of fuels.

[0067] Based on the index importance, the environmental index level is weighted and calculated to determine the fuel environmental level.

[0068] Optionally, after determining the environmental index level of the fuel, in order to further accurately evaluate the overall environmental performance of the fuel, the system terminal performs a weighted calculation on the obtained environmental index level according to the importance of each environmental index. This indicator importance is determined based on industry standards, policy requirements and actual application needs. Different environmental indicators are assigned different importance values ​​due to their different impact and priority in fuel performance evaluation. Subsequently, the system terminal assigns weights to the environmental index level based on the indicator importance, and the higher the importance, the higher the weight assigned to the indicator. After that, each environmental index is multiplied by its corresponding importance value to obtain the weighted score of the index. The weighted scores of all environmental indicators are then added together to obtain the comprehensive score of the fuel. Based on the comprehensive score and the environmental grade range, the fuel environmental grade is determined. The fuel environmental grade not only reflects the performance of the fuel on a single indicator, but also comprehensively considers the interaction and overall impact between multiple indicators, providing the system terminal with a more accurate environmental performance evaluation result.

[0069] Furthermore, after the application provides the output fuel environmental protection grade, the method also includes:

[0070] Determining the combustion characteristics of the target fuel, the combustion characteristics at least including combustion efficiency and combustion stability;

[0071] Based on the combustion characteristics, thermal decomposition and analysis are performed on the target fuel to determine the fluctuation trend;

[0072] Preferably, the system terminal determines the combustion characteristics of the target fuel, which mainly include combustion efficiency and combustion stability. Combustion efficiency reflects the ability of the fuel to release energy during the combustion process, while combustion stability describes the stability and controllability of the combustion process. Subsequently, the changes in the precipitates of the fuel during pyrolysis are analyzed in combination with the combustion characteristics and combustion stability of the fuel. Focus on the type, quantity and precipitation rate of the precipitates as a function of temperature. Afterwards, records are made based on the changes in the precipitates, and a fluctuation trend is generated. Then, the system terminal performs an amplitude analysis on the precipitates recorded in the fluctuation trend, that is, calculates the amplitude of the change of the precipitates during the precipitation process. The amplitude can reflect the stability of the precipitates and their potential impact on the environment. In summary, by analyzing the combustion characteristics of the target fuel and combining it with thermal decomposition and analysis, the amplitude of the precipitation of pollutants and harmful substances during the combustion process can be understood, so as to better evaluate its environmental performance and safety of use.

[0073] Based on the fluctuation trend, the fuel environmental protection level is expanded bidirectionally to determine the range of the environmental protection level.

[0074] Preferably, the system terminal obtains the fluctuation trend of the precipitate by analyzing the pyrolysis characteristics of the fuel. This trend reflects the changes in the precipitate under different temperatures and conditions during the pyrolysis process of the fuel, including the fluctuations in the type, quantity and precipitation rate. In order to more comprehensively consider the environmental performance of the fuel, the system terminal performs a two-way expansion of the obtained fuel environmental protection level. Specifically, the system terminal first analyzes the maximum or most unfavorable situation of the number or type of precipitates in the fluctuation trend to determine the range in which the environmental protection level may decrease. This range reflects the environmental performance of the fuel under unfavorable conditions. Subsequently, the minimum or most favorable situation of the number or type of precipitates in the fluctuation trend is analyzed to determine the range in which the environmental protection level may increase. This range reflects the environmental performance of the fuel under ideal conditions. Afterwards, the fluctuation range of the fuel environmental protection level of the target fuel, i.e., the environmental protection level range, is determined by combining the environmental protection level interval and the results of the two-way expansion. In summary, the two-way expansion of the fuel environmental protection level based on the fluctuation trend can help to more comprehensively evaluate the environmental performance of the fuel and determine a reasonable environmental protection level range.

[0075] In summary, the embodiments of the present application have at least the following technical effects:

[0076] The embodiment of the present application reads the full life cycle information of the fuel, extracts the effective characteristics of the fuel and integrates them into a fuel information system. Then determine multiple evaluation dimensions, and establish an adaptive evaluation model through single-dimensional parallel training. At the same time, perform big data retrieval to determine the verification interval, including the environmental protection level interval and the level difference interval. Combined with the adaptive evaluation model, the fuel information system is analyzed in parallel and independently, and mutually verified with the verification interval, and the fuel environmental protection level is finally output. After outputting the fuel environmental protection level, the combustion characteristics of the fuel are further determined, the thermal decomposition and analysis are performed, and the environmental protection level is bidirectionally expanded based on the fluctuation trend to determine the environmental protection level range. This method combines full life cycle information, multi-dimensional evaluation and big data verification, and provides a comprehensive and accurate method for the environmental protection level evaluation of solid biofuels. These technical effects jointly solve the technical problem that the prior art often only focuses on the characteristics of a certain stage of the fuel or only evaluates from a single dimension, ignoring the comprehensive impact of the entire life cycle of the fuel, resulting in insufficient accuracy of the evaluation results, and achieves the effect of improving the evaluation efficiency and ensuring the accuracy of the evaluation results by determining multiple evaluation dimensions and constructing an adaptive evaluation model.

[0077] Embodiment 2:

[0078] Based on the same inventive concept as the environmental protection level assessment method based on solid biofuel in the aforementioned embodiment, Figure 2 As shown, the present application provides an environmental rating assessment system based on solid biofuels, the system comprising:

[0079] Information reading module 1: the information reading module 1 is used to read the basic fuel information of the entire life cycle of the target fuel, wherein the entire life cycle includes the raw material stage - the production and processing stage - the use stage;

[0080] Extraction and integration module 2: the extraction and integration module 2 is used to traverse the basic fuel information, extract and integrate the effective characteristics of the fuel, and determine the fuel information system of the target fuel;

[0081] Parallel training module 3: the parallel training module 3 is used to determine multiple evaluation dimensions, perform single-dimensional parallel training, and determine an adaptive evaluation model, wherein the evaluation dimensions include component analysis dimensions, characteristic analysis dimensions, and periodic stage dimensions;

[0082] Data retrieval module 4: the data retrieval module 4 is used to perform large data retrieval, and determine the verification interval based on the fuel type of the target fuel, the verification interval including the environmental protection grade interval and the grade difference interval;

[0083] Mutual verification module 5: The mutual verification module 5 is used to combine the adaptive evaluation model, perform parallel independent analysis on the fuel information system, and mutual verification based on the verification interval to output the fuel environmental protection level, and the fuel environmental protection level is calculated based on the branch mean.

[0084] Furthermore, the extraction and integration module 2 is also used to perform the following method:

[0085] Identify the basic information of the fuel and determine the main characteristic line based on the whole life cycle;

[0086] Setting characteristic dimensions, wherein the characteristic dimensions include direct impact characteristics, indirect impact characteristics, favorable characteristics, and unfavorable characteristics;

[0087] The environmental protection related features of the basic fuel information are extracted, and the main feature line and the characteristic dimension are combined to perform cross-correlation and feature coefficient identification to determine the fuel information system.

[0088] Furthermore, the extraction and integration module 2 is also used to perform the following method:

[0089] Environmental relevance is used as the first weighting factor, and characteristic strength is used as the second weighting factor;

[0090] Based on the first weighting factor and the second weighting factor, traverse the environmental protection related features to perform hierarchical weighting configuration and determine the hierarchical weight distribution;

[0091] Based on the hierarchical weight distribution, the element weights of each environmental protection related feature are added up to determine the feature coefficient.

[0092] Furthermore, the parallel training module 3 is also used to execute the following method:

[0093] The adaptive evaluation model includes a first evaluation branch, a second evaluation branch and a third evaluation branch in parallel;

[0094] Among them, the evaluation branch supervision training methods include:

[0095] Based on the ingredient ratio and process variables, supervise the training of the first evaluation branch;

[0096] Based on the principle of finite element analysis, the second evaluation branch is supervised and trained based on the characteristics of good and bad states, in which finite element constraints are performed based on single environmental protection indicators;

[0097] The third evaluation branch is supervised and trained based on the phased aggregate benchmark.

[0098] Furthermore, the data retrieval module 4 is also used to execute the following method:

[0099] The environmental protection grade interval is determined based on the upper and lower limits of the environmental protection grade of the fuel type, and the grade difference interval is the evaluation deviation interval range;

[0100] The verification rules include:

[0101] Based on the environmental protection level interval, the branch parallel output is verified once to determine a first verification result;

[0102] Performing difference calculation on the branch parallel outputs, performing secondary verification based on the level difference interval, and determining a second verification result;

[0103] If both the first verification result and the second verification result are yes, the verification is passed.

[0104] Furthermore, the data retrieval module 4 is also used to execute the following method:

[0105] Based on the adaptive evaluation model, performing branch-by-branch parallel analysis of the fuel information system to determine branch evaluation results;

[0106] In combination with the verification rule, performing a qualification verification on the branch evaluation result;

[0107] If the verification is qualified, the branch evaluation results are mapped to the environmental protection index and the average is calculated to determine the environmental protection index level;

[0108] Based on the index importance, the environmental index level is weighted and calculated to determine the fuel environmental level.

[0109] Furthermore, the mutual verification module 5 is also used to perform the following method:

[0110] Determining the combustion characteristics of the target fuel, the combustion characteristics at least including combustion efficiency and combustion stability;

[0111] Based on the combustion characteristics, thermal decomposition and analysis are performed on the target fuel to determine the fluctuation trend;

[0112] Based on the fluctuation trend, the fuel environmental protection level is expanded bidirectionally to determine the range of the environmental protection level.

[0113] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. Other embodiments are within the scope of the attached claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0114] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0115] This specification and the drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various modifications and variations 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 equivalents, the present application intends to include these modifications and variations.

Claims

1. A method for evaluating the environmental protection level of solid biofuels, characterized in that: The method comprises: Read the fuel basic information of the entire life cycle of the target fuel, wherein the entire life cycle includes the raw material stage - the production and processing stage - the use stage; Traversing the basic fuel information, extracting and correlating effective fuel characteristics, and determining the fuel information system of the target fuel; Determine multiple evaluation dimensions, conduct single-dimensional parallel training, and determine an adaptive evaluation model, where the evaluation dimensions include component analysis dimension, characteristic analysis dimension, and cycle phase dimension; Performing big data retrieval, and determining a verification interval based on the fuel type of the target fuel, wherein the verification interval includes an environmental protection grade interval and a grade difference interval; In combination with the adaptive evaluation model, the fuel information system is analyzed independently in parallel, and the fuel environmental protection grade is outputted based on the mutual verification of the verification interval, and the fuel environmental protection grade is calculated based on the branch mean; Wherein, the fuel information system for determining the target fuel includes: Identify the basic information of the fuel and determine the main characteristic line based on the whole life cycle; Setting characteristic dimensions, wherein the characteristic dimensions include direct impact characteristics, indirect impact characteristics, favorable characteristics, and unfavorable characteristics; Extracting environmental protection related features of the basic fuel information, combining the main feature line with the characteristic dimension, performing cross-correlation and feature coefficient identification, and determining the fuel information system; Among them, the characteristic coefficient identification includes: Environmental relevance is used as the first weighting factor, and characteristic strength is used as the second weighting factor; Based on the first weighting factor and the second weighting factor, traverse the environmental protection related features to perform hierarchical weighting configuration and determine the hierarchical weight distribution; Based on the hierarchical weight distribution, the element weights of each environmental protection related feature are added up to determine the feature coefficient.

2. The method according to claim 1, characterized in that The environmental protection grade interval is determined based on the upper and lower limits of the environmental protection grade of the fuel type, and the grade difference interval is the evaluation deviation interval range; The verification rules include: Based on the environmental protection level interval, the branch parallel output is verified once to determine a first verification result; Performing difference calculation on the branch parallel outputs, performing secondary verification based on the level difference interval, and determining a second verification result; If both the first verification result and the second verification result are yes, the verification is passed.

3. The method according to claim 1, characterized in that The adaptive evaluation model includes a first evaluation branch, a second evaluation branch and a third evaluation branch in parallel; Among them, the evaluation branch supervision training methods include: Based on the ingredient ratio and process variables, supervise the training of the first evaluation branch; Based on the principle of finite element analysis, the second evaluation branch is supervised and trained based on the characteristics of good and bad states, in which finite element constraints are performed based on single environmental protection indicators; The third evaluation branch is supervised and trained based on the phased aggregate benchmark.

4. The method according to claim 2, characterized in that The environmental protection level of the output fuel includes: Based on the adaptive evaluation model, performing branch-by-branch parallel analysis of the fuel information system to determine branch evaluation results; In combination with the verification rule, performing a qualification verification on the branch evaluation result; If the verification is qualified, the branch evaluation results are mapped to the environmental protection index and the average is calculated to determine the environmental protection index level; Based on the index importance, the environmental index level is weighted and calculated to determine the fuel environmental level.

5. The method according to claim 1, characterized in that Output fuel environmental rating, including: Determining the combustion characteristics of the target fuel, wherein the combustion characteristics at least include combustion efficiency and combustion stability; Based on the combustion characteristics, thermal decomposition and analysis are performed on the target fuel to determine the fluctuation trend; Based on the fluctuation trend, the fuel environmental protection level is expanded bidirectionally to determine the range of the environmental protection level.

6. An environmental rating assessment system based on solid biofuels, characterized in that: The method for implementing any one of the solid biofuel-based environmental protection level assessment methods 1-5 comprises: Information reading module: reads the basic fuel information of the entire life cycle of the target fuel, wherein the entire life cycle includes the raw material stage - production and processing stage - use stage; Extraction and integration module: traverses the basic fuel information, extracts and integrates the effective characteristics of the fuel, and determines the fuel information system of the target fuel; Parallel training module: determine multiple evaluation dimensions, conduct single-dimensional parallel training, and determine the adaptive evaluation model. The evaluation dimensions include component analysis dimension, characteristic analysis dimension, and periodic stage dimension. Data retrieval module: performs big data retrieval, and determines the verification interval based on the fuel type of the target fuel, wherein the verification interval includes an environmental protection grade interval and a grade difference interval; Mutual verification module: Combined with the adaptive evaluation model, the fuel information system is analyzed independently in parallel, and the mutual verification based on the verification interval is performed to output the fuel environmental protection level, and the fuel environmental protection level is calculated based on the branch mean.

Images