Fuel service digital integrated management system

Abstract

The invention provides a fuel service digital comprehensive management system, and relates to the technical field of digital management, and the system comprises a data obtaining module which is used for obtaining various types of fuel data related to a real-time fuel service, and carrying out the data processing, and obtaining first fuel data; the processing detection module is used for classifying the first fuel data so as to perform data detection of a corresponding type on the fuel data to obtain first detection data; the fuel processing module is used for judging and analyzing the first detection data so as to determine a data optimization scheme for the first fuel data based on a judgment and analysis result; and the analysis display module is used for optimizing the first fuel data based on the data optimization scheme and displaying and outputting based on an optimization result. By classifying the fuel data according to different corresponding businesses, detection of corresponding types is carried out, and detection analysis is carried out by using different detection analysis modes, so that detection analysis of the target fuel business can be more accurate and effective.

Description

Technical Field

[0001] The present invention relates to the technical field of digital management, and in particular to a digital integrated management system for fuel business. Background Art

[0002] At present, with the adjustment of energy structure and the improvement of environmental protection requirements, power generation companies have increasingly stringent requirements on fuel management.

[0003] However, traditional fuel management methods have problems such as cumbersome operations, many human interference factors, and opaque data, which makes it difficult to meet the needs of modern power generation companies.

[0004] Therefore, the present invention provides a digital integrated management system for fuel business. Summary of the invention

[0005] The present invention provides a digital integrated management system for fuel business, which is used to solve the problems in the prior art such as opaque detection data and inability to perform well classified detection.

[0006] The present invention provides a digital integrated management system for fuel business, comprising: Data acquisition module: used to acquire various types of fuel data related to real-time fuel business, and perform data processing to obtain first fuel data; Processing and detection module: used for classifying the first fuel data, thereby performing data detection of corresponding types on the fuel data to obtain first detection data; Fuel processing module: used for judging and analyzing the first detection data, thereby determining a data optimization scheme for the first fuel data based on the judgment and analysis results; Analysis and display module: used to optimize the first fuel data based on the data optimization solution, and display and output based on the optimization result.

[0007] The data acquisition module provided by the present invention includes: A first acquisition unit: used to acquire real-time fuel data related to the real-time fuel business based on a preset sensor and the Internet of Things technology, and to process the real-time fuel data to obtain first fuel data; The second acquisition unit is used to acquire historical fuel data related to the historical fuel business, and process the historical fuel data to obtain first historical fuel data.

[0008] The processing detection module provided according to the present invention includes: A fuel classification unit: used for classifying the first fuel data to obtain a first classification data set, wherein each first classification data subset corresponds to the same fuel data type; A second extraction unit: used for obtaining a fuel data type related to fuel performance, thereby extracting a corresponding first classification data subset to obtain a second classification data set; A third extraction unit is used to obtain a fuel data type related to the fuel ratio, thereby extracting a corresponding first classification data subset to obtain a third classification data set; A first detection unit: used for inputting the second classification data set into a preset virtual machine, thereby determining the real-time fuel performance of the target fuel business, thereby obtaining first initial detection data of the target fuel data; A curve determination unit: used for inputting the fuel data of each first classification data subset in the third classification data set into the same coordinate system, so as to obtain a first proportioning curve corresponding to each fuel data type; A ratio detection unit: used to determine a first ratio performance corresponding to a first ratio curve in combination with historical ratio performance; A second detection unit: used for determining second initial detection data of the target fuel service based on each first proportioning performance of the target fuel service; A fourth extraction unit: used for determining the corresponding fuel data type based on the service management content of the real-time fuel service, thereby extracting the first classification data of the first classification data set to obtain a fourth classification data set; Wherein, each fourth classification data subset in the fourth classification data set corresponds to a business management content; A third detection unit: configured to obtain a data detection scheme for each fourth classification data subset from a preset service detection database, and perform data detection on the corresponding fourth classification data subset based on the data detection scheme to obtain third initial detection data; Comprehensive detection unit: used to integrate the first initial detection data, the second initial detection data, and the third initial detection data to obtain the first detection data of the target fuel business.

[0009] The ratio detection unit provided by the present invention includes: Performance extraction subunit: used to obtain the historical proportioning performance under each historical fuel state of the target fuel business, and obtain a first historical proportioning performance set; Performance matching subunit: used to obtain the real-time fuel state of the target fuel business, and compare the real-time fuel state with the historical fuel state corresponding to each historical proportioning performance in the first historical proportioning performance set, so as to extract the historical proportioning performance corresponding to the historical fuel state with the highest degree of consistency with the real-time fuel state as the first proportioning performance of the target fuel business.

[0010] The fuel processing module provided by the present invention comprises: Demand determination unit: used to determine a set of detection and analysis methods for the target fuel business based on the mission requirements of the target fuel business; A data analysis unit: configured to perform data analysis on the first detection data based on each detection analysis method in the detection method set to obtain a first analysis result; Optimization determination unit: used for obtaining the standard fuel state of each fuel business in the target fuel business, and determining the business optimization demand of the target fuel business in combination with the first analysis result, thereby determining the data optimization plan of the first fuel data.

[0011] The data analysis unit provided by the present invention comprises: Initial analysis subunit: used for performing data analysis on the first detection data based on each detection and analysis method in the detection method set to obtain an initial analysis result; Correlation analysis subunit: used to determine the detection correlation of each detection and analysis method; If the detection correlation is higher than the preset standard detection correlation, the detection optimization is performed based on two detection analysis methods related to the current detection correlation; If the detection correlation is not higher than the preset standard detection correlation, there is no need to optimize the current detection analysis method; Comprehensive analysis subunit: Optimize the initial analysis results based on the detection and analysis method after detection optimization to obtain comprehensive analysis results.

[0012] The analysis and display module provided according to the present invention comprises: Display warning unit: used for optimizing the first fuel data based on the data optimization scheme, and determining whether the fuel state of the target fuel business after the data optimization is within the standard fuel state range; If the fuel state of the target fuel business is within the standard fuel state range after data optimization, display output is performed based on the data optimization result; If the fuel state of the target fuel business after data optimization is not within the standard fuel state range, an early warning is issued based on the fuel state of the target fuel business.

[0013] The display warning unit provided according to the present invention comprises: When the fuel state of the target fuel business after data optimization is not within the standard fuel state range, extracting fuel data corresponding to the fuel state exceeding the standard fuel state in the fuel state; The type of fuel data related to the fuel data in the target fuel business is determined, so as to issue a corresponding fuel business warning.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: the digital integrated management system for fuel business provided by the present invention classifies fuel data according to corresponding businesses, thereby performing corresponding types of detection, and using different detection and analysis methods to perform detection and analysis on different detection results, thereby making the detection and analysis of the target fuel business more accurate and effective. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 It is a structural diagram of a digital integrated management system for fuel business provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Embodiment 1: The embodiment of the present invention provides a digital integrated management system for fuel business, such as Figure 1 As shown, including: Data acquisition module: used to acquire various types of fuel data related to real-time fuel business, and perform data processing to obtain first fuel data; Processing and detection module: used for classifying the first fuel data, thereby performing data detection of corresponding types on the fuel data to obtain first detection data; Fuel processing module: used for judging and analyzing the first detection data, thereby determining a data optimization scheme for the first fuel data based on the judgment and analysis results; Analysis and display module: used to optimize the first fuel data based on the data optimization solution, and display and output based on the optimization result.

[0019] In this embodiment, the real-time fuel business is the currently ongoing fuel-related business activities, including the purchase, storage, transportation, use, and sales of fuel.

[0020] In this embodiment, the fuel data includes the type of fuel (such as coal, oil, natural gas, etc.), quantity, quality (such as calorific value, sulfur content, etc.), price, origin, supplier information, etc. Different types of fuel data reflect different aspects of the fuel business.

[0021] In this embodiment, data processing refers to a series of operations performed on the collected raw data to extract useful information, convert data formats, clean data (remove erroneous or duplicate data), integrate data (combine data from different sources into one data set), etc.

[0022] In this embodiment, the first fuel data is a fuel data set obtained after preliminary data processing and used for subsequent analysis or decision-making.

[0023] In this embodiment, classification is to classify the fuel data based on the type of fuel (such as oil, natural gas, coal, etc.), use (such as industrial fuel, transportation fuel, etc.) or other relevant characteristics.

[0024] In this embodiment, data detection includes detecting the integrity, accuracy, quality, etc. of the fuel data.

[0025] In this embodiment, the first detection data is test data obtained through data detection. For example, for fuel data, the detection data may include actual calorific value, water content, ash content, etc. of the fuel.

[0026] In this embodiment, the judgment analysis refers to an in-depth analysis and evaluation of the first detection data.

[0027] In this embodiment, the data optimization scheme is a plan or strategy for improving or optimizing the first fuel data based on the results of the judgment analysis. The data optimization scheme may involve multiple aspects, such as improving data accuracy, reducing data redundancy, optimizing data storage and retrieval methods, etc.

[0028] In this embodiment, the display output is to display the optimization result in a visual manner.

[0029] The beneficial effect of the above technical solution is: by classifying the fuel data according to the corresponding business, corresponding types of detection are performed, and different detection and analysis methods are used to perform detection and analysis on different detection results, so that the detection and analysis of the target fuel business can be more accurate and effective.

[0030] Embodiment 2: Based on Example 1, the data acquisition module includes: A first acquisition unit: used to acquire real-time fuel data related to the real-time fuel business based on a preset sensor and the Internet of Things technology, and to process the real-time fuel data to obtain first fuel data; The second acquisition unit is used to acquire historical fuel data related to the historical fuel business, and process the historical fuel data to obtain first historical fuel data.

[0031] In this embodiment, the real-time fuel business is the currently ongoing fuel-related business activities, including the purchase, storage, transportation, use, and sales of fuel.

[0032] In this embodiment, real-time fuel data refers to various types of fuel data corresponding to real-time fuel business, for example, including fuel type (such as coal, oil, natural gas, etc.), quantity, quality (such as calorific value, sulfur content, etc.), price, origin, supplier information and other data information. Different types of fuel data reflect different aspects of the fuel business.

[0033] In this embodiment, data processing refers to a series of operations performed on the collected raw data to extract useful information, convert data formats, clean data (remove erroneous or duplicate data), integrate data (combine data from different sources into one data set), etc.

[0034] In this embodiment, the first fuel data is a fuel data set that has been processed by data cleaning and data standardization.

[0035] In this embodiment, the historical fuel data refers to fuel data related to historical fuel services.

[0036] In this embodiment, the first historical fuel data refers to the historical fuel data obtained after data cleaning and data standardization processing.

[0037] The beneficial effect of the above technical solution is that by processing the real-time fuel data, the determined first fuel data can be made more concise and effective, and easy to analyze, thereby improving the efficiency of fuel detection and analysis.

[0038] Embodiment 3: Based on Example 2, the processing detection module includes: A fuel classification unit: used for classifying the first fuel data to obtain a first classification data set, wherein each first classification data subset corresponds to the same fuel data type; A second extraction unit: used for obtaining a fuel data type related to fuel performance, thereby extracting a corresponding first classification data subset to obtain a second classification data set; A third extraction unit is used to obtain a fuel data type related to the fuel ratio, thereby extracting a corresponding first classification data subset to obtain a third classification data set; A first detection unit: used for inputting the second classification data set into a preset virtual machine, thereby determining the real-time fuel performance of the target fuel business, thereby obtaining first initial detection data of the target fuel data; A curve determination unit: used for inputting the fuel data of each first classification data subset in the third classification data set into the same coordinate system, so as to obtain a first proportioning curve corresponding to each fuel data type; A ratio detection unit: used to determine a first ratio performance corresponding to a first ratio curve in combination with historical ratio performance; A second detection unit: used for determining second initial detection data of the target fuel service based on each first proportioning performance of the target fuel service; A fourth extraction unit: used for determining the corresponding fuel data type based on the service management content of the real-time fuel service, thereby extracting the first classification data of the first classification data set to obtain a fourth classification data set; Wherein, each fourth classification data subset in the fourth classification data set corresponds to a business management content; A third detection unit: configured to obtain a data detection scheme for each fourth classification data subset from a preset service detection database, and perform data detection on the corresponding fourth classification data subset based on the data detection scheme to obtain third initial detection data; Comprehensive detection unit: used to integrate the first initial detection data, the second initial detection data, and the third initial detection data to obtain the first detection data of the target fuel business.

[0039] In this embodiment, the first classified data set is a set obtained by classifying the first fuel data. In the first classified data set, each first classified data subset corresponds to fuel data of the same fuel data type.

[0040] In this embodiment, the fuel data type refers to a label for classifying fuel data according to the characteristics or uses of the fuel, for example, fuel type (such as gasoline, diesel), fuel quality, fuel performance parameters, etc.

[0041] In this embodiment, the second classification data set is a data set obtained by integrating subsets corresponding to fuel data types related to fuel performance extracted from the first classification data set.

[0042] In this embodiment, the third classification data set is a data set obtained by integrating subsets corresponding to fuel data types related to fuel ratios extracted from the first classification data set.

[0043] In this embodiment, the real-time fuel performance covers multiple aspects of the fuel, including but not limited to calorific value, combustion characteristics, stability, storage characteristics, and physical properties.

[0044] In this embodiment, the first initial detection data is data on the real-time fuel performance of the target fuel business obtained after the second classification data set is processed by a preset virtual machine.

[0045] In this embodiment, the first proportioning curve refers to a curve drawn in a coordinate system according to data points of a certain fuel data type in the third classification data set.

[0046] In this embodiment, the first ratio performance is obtained by interpreting and analyzing the first ratio curve in combination with the historical ratio performance.

[0047] In this embodiment, the second initial detection data is data on the target fuel service proportioning performance obtained after comprehensive evaluation based on each first proportioning performance of the target fuel service.

[0048] In this embodiment, the business management content refers to various management activities or tasks related to the target fuel business, such as fuel procurement, storage, transportation, sales, etc.

[0049] In this embodiment, the fourth classified data set is a data set obtained by integrating corresponding data subsets extracted from the first classified data set according to the business management content.

[0050] In this embodiment, each fourth classification data subset in the fourth classification data set corresponds to a business management content.

[0051] In this embodiment, the data detection scheme is a data detection method for each business management content based on what is stored in a preset business detection database.

[0052] In this embodiment, the third initial detection data is result data obtained after performing data detection on the fourth classification data set based on the data detection scheme.

[0053] In this embodiment, data detection includes detecting the integrity, accuracy, quality, etc. of the fuel data.

[0054] In this embodiment, the first detection data is obtained by integrating the first initial detection data, the second initial detection data, and the third initial detection data of the target fuel business.

[0055] The beneficial effect of the above technical solution is that by classifying the fuel data according to the corresponding business, and thus performing corresponding types of detection, the detection and analysis of the target fuel business can be made more accurate and effective.

[0056] Embodiment 4: Based on Example 3, the ratio detection unit includes: Performance extraction subunit: used to obtain the historical proportioning performance under each historical fuel state of the target fuel business, and obtain a first historical proportioning performance set; Performance matching subunit: used to obtain the real-time fuel state of the target fuel business, and compare the real-time fuel state with the historical fuel state corresponding to each historical proportioning performance in the first historical proportioning performance set, so as to extract the historical proportioning performance corresponding to the historical fuel state with the highest degree of consistency with the real-time fuel state as the first proportioning performance of the target fuel business.

[0057] In this embodiment, the historical fuel state refers to the fuel status or condition of the target fuel business during the historical working process, wherein the historical fuel state includes state parameters such as the type, quality, reserves, temperature, and pressure of the fuel.

[0058] In this embodiment, the historical fuel ratio performance refers to the performance exhibited by the fuel ratio under each specific historical fuel state, such as combustion efficiency, emission level, cost-effectiveness, etc.

[0059] In this embodiment, the first historical matching performance set refers to a performance set including each historical matching performance.

[0060] In this embodiment, the real-time fuel status is the fuel status or condition of the target fuel business at the current moment.

[0061] In this embodiment, the first proportioning performance refers to the historical proportioning performance that is found to have the highest degree of consistency with the real-time fuel state after comparing the real-time fuel state with the historical proportioning performance in the first historical proportioning performance set.

[0062] The beneficial effect of the above technical solution is that by classifying the fuel data according to the corresponding business, and thus performing corresponding types of detection, the detection and analysis of the target fuel business can be made more accurate and effective.

[0063] Embodiment 5: Based on Example 3, the fuel processing module includes: Demand determination unit: used to determine a set of detection and analysis methods for the target fuel business based on the mission requirements of the target fuel business; A data analysis unit: configured to perform data analysis on the first detection data based on each detection analysis method in the detection method set to obtain a first analysis result; Optimization determination unit: used for obtaining the standard fuel state of each fuel business in the target fuel business, and determining the business optimization demand of the target fuel business in combination with the first analysis result, thereby determining the data optimization plan of the first fuel data.

[0064] In this embodiment, the mission requirement refers to a specific goal or requirement that needs to be solved or achieved in the target fuel business. The mission requirement involves requirements such as improving fuel efficiency, reducing fuel costs, and ensuring fuel quality.

[0065] In this embodiment, the detection and analysis method set includes statistical analysis, data mining, machine learning algorithms, etc.

[0066] In this embodiment, data analysis refers to performing data analysis on the first detection data based on each detection analysis method in the detection method set.

[0067] In this embodiment, the first analysis result is a result obtained by analyzing the first detection data using a method in the detection analysis method set. For example, the first analysis result may include statistical characteristics, trends, patterns, etc. of the data.

[0068] In this embodiment, the business optimization requirements may involve adjusting fuel procurement strategies, improving fuel efficiency, strengthening fuel safety management, etc.

[0069] In this embodiment, the data optimization scheme is a plan or strategy for improving or optimizing the first fuel data based on the results of the judgment analysis. The data optimization scheme may involve multiple aspects, such as improving data accuracy, reducing data redundancy, optimizing data storage and retrieval methods, etc.

[0070] The beneficial effect of the above technical solution is that by using different detection and analysis methods to detect and analyze a variety of detection results, the detection and analysis of the target fuel business can be made more accurate and effective.

[0071] Embodiment 6: Based on Example 5, the data analysis unit includes: Initial analysis subunit: used for performing data analysis on the first detection data based on each detection and analysis method in the detection method set to obtain an initial analysis result; Correlation analysis subunit: used to determine the detection correlation of each detection and analysis method; If the detection correlation is higher than the preset standard detection correlation, the detection optimization is performed based on two detection analysis methods related to the current detection correlation; If the detection correlation is not higher than the preset standard detection correlation, there is no need to optimize the current detection analysis method; Comprehensive analysis subunit: Optimize the initial analysis results based on the detection and analysis method after detection optimization to obtain comprehensive analysis results.

[0072] In this embodiment, the initial analysis result is a result obtained after performing a preliminary analysis on the first detection data using each detection analysis method in the detection method set.

[0073] In this embodiment, the detection correlation is the similarity or consistency in the results between different detection and analysis methods. For example, if the detection results of two detection and analysis methods are very close or similar, then their detection correlation is high. The detection correlation is used to evaluate the complementarity or redundancy between different detection and analysis methods.

[0074] In this embodiment, the standard detection correlation is a pre-set detection threshold used to determine whether the detection correlation is high enough to determine whether detection optimization is needed. For example, the standard detection correlation can be determined based on expert experience, professional knowledge or some statistical method.

[0075] In this embodiment, detection optimization refers to optimizing the corresponding detection and analysis methods based on detection correlation, thereby reducing the redundancy of detection and analysis.

[0076] In this embodiment, the comprehensive analysis result is the result obtained after further processing the initial analysis result using the optimized detection and analysis method after detection optimization.

[0077] The beneficial effect of the above technical solution is that by using different detection and analysis methods to detect and analyze a variety of detection results, the detection and analysis of the target fuel business can be made more accurate and effective.

[0078] Embodiment 7: Based on Example 6, the analysis and display module includes: Display warning unit: used for optimizing the first fuel data based on the data optimization scheme, and determining whether the fuel state of the target fuel business after the data optimization is within the standard fuel state range; If the fuel state of the target fuel business is within the standard fuel state range after data optimization, display output is performed based on the data optimization result; If the fuel state of the target fuel business after data optimization is not within the standard fuel state range, an early warning is issued based on the fuel state of the target fuel business.

[0079] In this embodiment, the fuel state refers to the condition or property of the fuel at a specific time point or under certain conditions, such as the temperature, pressure, composition, quality, etc. of the fuel.

[0080] In this embodiment, the standard fuel state range is a pre-set range. If the fuel state is within this range, it is considered that the fuel meets the standard or expectations.

[0081] In this embodiment, the display output is to display the data optimization result that the fuel state of the target fuel business after data optimization is within the standard fuel state range in a visual manner.

[0082] In this embodiment, the early warning means that if the fuel state of the target fuel business after data optimization is not within the standard fuel state range, a fuel early warning is issued based on the real-time fuel state of the target fuel business.

[0083] The beneficial effect of the above technical solution is that by providing timely feedback on the data optimization results, faults can be discovered more promptly and effectively, so that faults can be solved in a timely manner, thereby improving the efficiency of detection and analysis.

[0084] Embodiment 8: Based on the embodiment 7, the warning unit is displayed, including: When the fuel state of the target fuel business after data optimization is not within the standard fuel state range, extracting fuel data corresponding to the fuel state exceeding the standard fuel state in the fuel state; The type of fuel data related to the fuel data in the target fuel business is determined, so as to issue a corresponding fuel business warning.

[0085] The beneficial effect of the above technical solution is that by providing timely feedback on the data optimization results, faults can be discovered more promptly and effectively, so that faults can be solved in a timely manner, thereby improving the efficiency of detection and analysis.

[0086] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A digital integrated management system for fuel business, characterized in that: include: Data acquisition module: used to acquire various types of fuel data related to real-time fuel business, and perform data processing to obtain first fuel data; Processing and detection module: used for classifying the first fuel data, thereby performing data detection of corresponding types on the fuel data to obtain first detection data; Fuel processing module: used for judging and analyzing the first detection data, thereby determining a data optimization scheme for the first fuel data based on the judgment and analysis results; Analysis and display module: used to optimize the first fuel data based on the data optimization solution, and display and output based on the optimization result.

2. A digital integrated management system for fuel business according to claim 1, characterized in that: Data acquisition module, including: A first acquisition unit: used to acquire real-time fuel data related to the real-time fuel business based on a preset sensor and the Internet of Things technology, and to process the real-time fuel data to obtain first fuel data; The second acquisition unit is used to acquire historical fuel data related to the historical fuel business, and process the historical fuel data to obtain first historical fuel data.

3. A digital integrated management system for fuel business according to claim 2, characterized in that: Processing detection module, including: A fuel classification unit: used for classifying the first fuel data to obtain a first classification data set, wherein each first classification data subset corresponds to the same fuel data type; A second extraction unit: used for obtaining a fuel data type related to fuel performance, thereby extracting a corresponding first classification data subset to obtain a second classification data set; A third extraction unit is used to obtain a fuel data type related to the fuel ratio, thereby extracting a corresponding first classification data subset to obtain a third classification data set; A first detection unit: used for inputting the second classification data set into a preset virtual machine, thereby determining the real-time fuel performance of the target fuel business, thereby obtaining first initial detection data of the target fuel data; A curve determination unit: used for inputting the fuel data of each first classification data subset in the third classification data set into the same coordinate system, so as to obtain a first proportioning curve corresponding to each fuel data type; A ratio detection unit: used to determine a first ratio performance corresponding to a first ratio curve in combination with historical ratio performance; A second detection unit: used for determining second initial detection data of the target fuel service based on each first proportioning performance of the target fuel service; A fourth extraction unit: used for determining the corresponding fuel data type based on the service management content of the real-time fuel service, thereby extracting the first classification data of the first classification data set to obtain a fourth classification data set; Wherein, each fourth classification data subset in the fourth classification data set corresponds to a business management content; A third detection unit: configured to obtain a data detection scheme for each fourth classification data subset from a preset service detection database, and perform data detection on the corresponding fourth classification data subset based on the data detection scheme to obtain third initial detection data; Comprehensive detection unit: used to integrate the first initial detection data, the second initial detection data, and the third initial detection data to obtain the first detection data of the target fuel business.

4. A digital integrated management system for fuel business according to claim 3, characterized in that: Ratio detection unit, including: Performance extraction subunit: used to obtain the historical proportioning performance under each historical fuel state of the target fuel business, and obtain a first historical proportioning performance set; Performance matching subunit: used to obtain the real-time fuel state of the target fuel business, and compare the real-time fuel state with the historical fuel state corresponding to each historical proportioning performance in the first historical proportioning performance set, so as to extract the historical proportioning performance corresponding to the historical fuel state with the highest degree of consistency with the real-time fuel state as the first proportioning performance of the target fuel business.

5. A digital integrated management system for fuel business according to claim 3, characterized in that: Fuel processing module, including: Demand determination unit: used to determine a set of detection and analysis methods for the target fuel business based on the mission requirements of the target fuel business; A data analysis unit: configured to perform data analysis on the first detection data based on each detection analysis method in the detection method set to obtain a first analysis result; Optimization determination unit: used for obtaining the standard fuel state of each fuel business in the target fuel business, and determining the business optimization demand of the target fuel business in combination with the first analysis result, thereby determining the data optimization plan of the first fuel data.

6. A digital integrated management system for fuel business according to claim 5, characterized in that: Data Analysis Unit, including: Initial analysis subunit: used for performing data analysis on the first detection data based on each detection and analysis method in the detection method set to obtain an initial analysis result; Correlation analysis subunit: used to determine the detection correlation of each detection and analysis method; If the detection correlation is higher than the preset standard detection correlation, the detection optimization is performed based on two detection analysis methods related to the current detection correlation; If the detection correlation is not higher than the preset standard detection correlation, there is no need to optimize the current detection analysis method; Comprehensive analysis subunit: Optimize the initial analysis results based on the detection and analysis method after detection optimization to obtain comprehensive analysis results.

7. A digital integrated management system for fuel business according to claim 5, characterized in that: Analysis and display module, including: Display warning unit: used for optimizing the first fuel data based on the data optimization scheme, and determining whether the fuel state of the target fuel business after the data optimization is within the standard fuel state range; If the fuel state of the target fuel business is within the standard fuel state range after data optimization, display output is performed based on the data optimization result; If the fuel state of the target fuel business after data optimization is not within the standard fuel state range, an early warning is issued based on the fuel state of the target fuel business.

8. A digital integrated management system for fuel business according to claim 6, characterized in that: Display warning unit, including: When the fuel state of the target fuel business after data optimization is not within the standard fuel state range, extracting fuel data corresponding to the fuel state exceeding the standard fuel state in the fuel state; The type of fuel data related to the fuel data in the target fuel business is determined, so as to issue a corresponding fuel business warning.

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