Intelligent fuel dispatching system and method

Abstract

The invention provides an intelligent fuel dispatching system and method, and belongs to the technical field of comprehensive dispatching, and the system comprises a data collection module which collects basic parameters of a fuel transportation process in real time through a sensor and monitoring equipment, standardizes the basic parameters, and stores the standardized basic parameters in a standard parameter database; the data analysis module is used for acquiring basic parameter information of fuel and real-time position information of a fuel transportation tool in real time through an interface, predicting transportation states of all entities in a supply chain according to a transportation prediction model, and outputting the transportation states to the intelligent allocation and transportation platform; the scheme formulating module is used for dispatching the transportation states of all entities of the intelligent dispatching platform and formulating an optimal fuel dispatching scheme; and the scheme adjusting module is used for dynamically adjusting the optimal fuel dispatching scheme according to the real-time condition of fuel transportation based on the intelligent dispatching platform. The accuracy and efficiency of fuel dispatching are improved, the operation cost is reduced, and energy supply safety is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated dispatching, and in particular to a fuel intelligent dispatching system and method. Background Art

[0002] At present, the business model that relies on manual resource matching and transportation plan formulation and change in each link will result in inaccurate scheduling results when used through human calculations, leading to increased costs. In addition, fuel quality parameters, transportation tool status, environmental data, etc. may come from different systems and departments, and due to the differences in systems and departments, there will be differences in subsequent data analysis, which will in turn affect the transportation speed and efficiency of the fuel and affect the overall operation of the fuel transportation system.

[0003] Therefore, the present invention proposes a fuel intelligent transportation system and method. Summary of the invention

[0004] The present invention provides a fuel intelligent transportation system and method, which is used to obtain fuel storage quantity, quality status, transportation tool information, etc. in real time through an interface, and transmit it to an intelligent transportation platform in real time. After processing and analyzing these data, the intelligent transportation platform can automatically formulate the best fuel transportation plan, as well as when to replenish, which transportation tool to use, and the best route selection. At the same time, the platform can dynamically adjust the plan according to the real-time situation to ensure the stability and efficiency of fuel supply.

[0005] In one aspect, the present invention provides a fuel intelligent transportation system, comprising: Data acquisition module: uses sensors and monitoring equipment to collect basic parameters of the fuel transportation process in real time, and stores the basic parameters in the standard parameter database after standardization; Data analysis module: obtains basic parameter information of fuel and real-time location information of fuel transportation vehicles through the interface, predicts the transportation status of all entities in the supply chain based on the transportation prediction model, and outputs it to the intelligent transportation platform; Plan formulation module: dispatch the transportation status of all entities on the intelligent transportation platform and formulate the optimal fuel transportation plan; Plan adjustment module: Based on the intelligent transportation platform, dynamically adjust the optimal fuel transportation plan according to the real-time situation of fuel transportation.

[0006] On the other hand, the data acquisition module comprises: Parameter determination unit: determines the key fuel transportation parameters of the monitoring target and builds a standard parameter database based on the types of the key fuel transportation parameters; Configuration unit: After configuring the installation parameters to the sensors and monitoring equipment, the original parameters of the fuel transportation process are collected in real time.

[0007] On the other hand, the data acquisition module comprises: Standardization processing unit: after pre-processing the original parameters, the scale is standardized according to the preset standard units and the basic parameters are output; Storage unit: generates standard parameter data from basic parameter data according to the format structure requirements of the standard parameter database and stores it in the standard parameter database.

[0008] On the other hand, the data analysis module comprises: Design interface unit: Based on the target processing data type of the interface, design the interface in combination with the preset data transmission protocol, and match the interface type with the target processing data type; Interface matching unit: sends a request to the interface to obtain data. The encryption system encrypts the request into an API key. The interface receives the API key, verifies the legitimacy, passes the request, and returns the original request data. Data processing unit: after preprocessing the original request data, the corresponding target processing data type is set with a unique tag to generate interface data. On the other hand, the data analysis module includes: Parameter classification unit: used to classify the types of interface data into three categories based on tags: fuel transportation tool parameters, fuel body parameters and environmental parameters; Location unit: Based on the fuel transportation tool parameters of the fuel transportation tool, the starting point and end point of the fuel transportation and the preset transportation route are obtained, and a standard transportation grid map is constructed according to the supply chain where the starting point and end point are located, and all the waypoints between the starting point and end point are marked, where the length and width of the grid unit are proportional to the actual geographical longitude and latitude; Transportation status unit: compares the real-time parameter data of the fuel transportation tool with the basic parameters of the fuel transportation tool. If the absolute value of the deviation of any parameter is greater than a preset error value, it is predicted that the fuel transportation tool is abnormal and the abnormal level of the fuel transportation tool is determined; otherwise, it is determined that the fuel transportation tool is not abnormal; ; in, represents the abnormal level of the fuel transportation vehicle, ( ) represents the level conversion function, represents the absolute value of the deviation of the i-th parameter of the fuel transportation vehicle, It represents the minimum absolute value of all parameter deviations of fuel transportation vehicles. represents the mean of the absolute values ​​of all parameter deviations of fuel transport vehicles, It represents the maximum absolute value of all parameter deviations of fuel transportation vehicles. Indicates the change in estimated deviation n means there are n parameters in total; Output the transportation status of the fuel transportation vehicle, including: the real-time location of the fuel transportation vehicle, the abnormal status and abnormal level of the fuel transportation vehicle; Upload unit: upload the transportation status of all entities in the supply chain to the intelligent dispatching platform.

[0009] On the other hand, the program formulation module includes: Quality status unit: Based on the transportation prediction model, the real-time data of fuel body parameters are compared with the basic parameters of the fuel, and the quality status is output; Detention status unit: retrieves the transportation status of the fuel transportation vehicle from the intelligent transportation platform. If the abnormality level of the fuel transportation vehicle is greater than the preset maximum level, the fuel transportation vehicle is detained at the location and waits for subsequent instructions; if the abnormality level is greater than the preset warning level and less than or equal to the preset maximum level, the fuel transportation vehicle is sent to the nearest waypoint to wait for handover; otherwise, it is determined that the fuel transportation vehicle can be transported normally; Time prediction unit: based on the quality status of the fuel and the retention status of the fuel transportation vehicle, predict the time when the fuel transportation vehicle arrives at the destination, assuming that the coordinates of the retention point are o , the predicted arrival time is:

[0010] in, represents the predicted arrival time of the fuel transportation vehicle, Indicates the time the fuel transport vehicle has been transporting. represents the residence time function of the retention point o, M represents the quality state of the fuel, The preset weight coefficient representing the quality status, represents the preset weight coefficient of the residence time, represents the preset weight coefficient of the environmental state, represents the speed-time conversion function, represents the maximum speed within the jth standard distance, represents the minimum speed within the jth standard distance, It represents the estimated maximum time within the standard journey from the stopover point to the destination. represents the logarithmic function symbol, ave represents the average extracted variance value, and n0 represents a total of n0 standard distances. represents the kth environmental parameter within the jth standard distance, and m represents that there are m environmental parameters in the standard distance.

[0011] On the other hand, the program formulation module also includes: Optimal route processing unit: If Greater than the preset arrival time , replan the route of the fuel transportation tool, obtain the time consumption corresponding to the two waypoints m and n from the time consumption degree-waypoint mapping table, obtain the estimated transportation time of the remaining path after the abnormal starting point in the original transportation path, and obtain the initial time consumption degree ; Construct all target transport points that have a connection relationship between all route points and abnormal starting points as a set V, and obtain the point with the minimum time consumption , point Put it into the optimal set S, and find the point in the set V Points with a connection relationship and the minimum time consumption , and point Put it into the optimal set S until the set S contains the endpoint and the iteration ends. If the total time consumption of the optimal set S is greater than , repeatedly iteratively select adjacent points until the total time consumption of the optimal set S is less than , determine that all the waypoints of the optimal set S are the best route waypoints, and upload the optimal set S to the intelligent transportation platform.

[0012] On the other hand, the scheme adjustment module includes: Plan adjustment unit: Based on the intelligent transportation platform, the real-time transportation status of the fuel transportation tool after the plan adjustment is obtained. If anomalies are predicted in the future, the plan is adjusted in real time and the transportation status parameters are detected.

[0013] In another aspect, the present invention provides a method for intelligent fuel transportation, comprising: Step 1: Use sensors and monitoring equipment to collect basic parameters of the fuel transportation process in real time, and store the basic parameters in a standard parameter database after standardization; Step 2: Obtain the basic parameter information of the fuel and the real-time location information of the fuel transportation vehicle in real time through the interface, predict the transportation status of all entities in the supply chain according to the transportation prediction model, and output it to the intelligent transportation platform; Step 3: Dispatch the transportation status of all entities on the intelligent transportation platform and formulate the optimal fuel transportation plan; Step 4: Based on the intelligent transportation platform, dynamically adjust the optimal fuel transportation plan according to the real-time situation of fuel transportation.

[0014] The present invention provides a fuel intelligent transportation system and method, which is used to obtain fuel storage quantity, quality status, transportation tool information, etc. in real time through an interface, and transmit it to an intelligent transportation platform in real time. After processing and analyzing these data, the intelligent transportation platform can automatically formulate the best fuel transportation plan, as well as when to replenish, which transportation tool to use, and the best route selection. At the same time, the platform can dynamically adjust the plan according to the real-time situation to ensure the stability and efficiency of fuel supply. 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 schematic diagram of a fuel intelligent transportation system provided by an embodiment of the present invention.

[0017] Figure 2 It is a flow chart of a method for intelligent fuel transportation provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] 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.

[0019] Embodiment 1: like Figure 1 As shown, an embodiment of the present invention provides a fuel intelligent transportation system, including: Data acquisition module: uses sensors and monitoring equipment to collect basic parameters of the fuel transportation process in real time, and stores the basic parameters in the standard parameter database after standardization; Data analysis module: obtains basic parameter information of fuel and real-time location information of fuel transportation vehicles through the interface, predicts the transportation status of all entities in the supply chain based on the transportation prediction model, and outputs it to the intelligent transportation platform; Plan formulation module: dispatch the transportation status of all entities on the intelligent transportation platform and formulate the optimal fuel transportation plan; Plan adjustment module: Based on the intelligent transportation platform, dynamically adjust the optimal fuel transportation plan according to the real-time situation of fuel transportation.

[0020] In this embodiment, the sensor is a device that can sense and measure certain specific physical quantities or environmental parameters, and the types include: temperature sensor, pressure sensor, flow sensor, humidity sensor, etc.

[0021] In this embodiment, the monitoring equipment is used to monitor the status of the transportation tool and the transportation process in real time, including: cameras, GPS devices, on-board computers, sensors and other equipment.

[0022] In this embodiment, the fuel transportation process includes procurement, storage, transportation, processing, and distribution.

[0023] In this embodiment, the basic parameters refer to some key indicators and properties in the fuel transportation process, including: temperature, pressure, flow, vehicle load and other basic information.

[0024] In this embodiment, standardization converts the collected basic parameters of the fuel transportation process into a consistent format, and the steps include: unifying units, data cleaning, format normalization and data unification.

[0025] In this embodiment, the standard parameter database is a database that stores the basic parameters of the standardized fuel transportation process, and the data content includes: basic parameters, standardized data, timestamp and unique identifier.

[0026] In this embodiment, the interface is used to obtain basic parameter information of the fuel and real-time location information of the fuel transportation vehicle in real time, involving: data format, communication protocol, authentication and security, etc.

[0027] In this embodiment, the basic parameter information refers to key parameters of the fuel, including temperature, pressure, liquid level and other parameters.

[0028] In this embodiment, the real-time location information refers to the current geographic location of the fuel transportation vehicle (such as a tanker truck, pipeline, etc.), including: longitude and latitude, timestamp, speed and direction.

[0029] In this embodiment, the transportation prediction model is a model that uses historical data, real-time data and algorithm technology to predict the transportation status and behavior of various entities in the fuel transportation process.

[0030] In this embodiment, the entity refers to various subjects or objects involved in the fuel transportation process, including: transportation tools, transportation routes, fuel, etc.

[0031] In this embodiment, the transportation status refers to the current status of each entity in the fuel transportation process, including: transportation tool status, fuel supply status, transportation route status, etc.

[0032] In this embodiment, the intelligent transportation platform is a system based on information technology that completes the intelligent management and optimization of the fuel transportation process.

[0033] In this embodiment, scheduling refers to the effective arrangement and management of transportation processes and resources, including status detection and plan formulation of each entity.

[0034] In this embodiment, the optimal fuel transportation plan refers to a plan that optimizes the fuel transportation process through an intelligent transportation platform while taking into account multiple factors (such as cost, time, resource utilization, etc.), mainly achieving: minimizing costs, time efficiency, and maximizing resource utilization.

[0035] The working principle and beneficial effects of the above technical solution are: improving data processing efficiency by standardizing parameters, and based on real-time data collection and analysis, using intelligent scheduling to optimize fuel supply chain transportation, improve efficiency and reduce costs, enhance stability, and improve transportation efficiency.

[0036] Embodiment 2: Based on the above embodiment 1, the data acquisition module includes: Parameter determination unit: determines the key fuel transportation parameters of the monitoring target and builds a standard parameter database based on the types of the key fuel transportation parameters; Configuration unit: After configuring the installation parameters to the sensors and monitoring equipment, the original parameters of the fuel transportation process are collected in real time.

[0037] In this embodiment, the monitoring target refers to the key parameters that need to be monitored and paid attention to during the fuel transportation process, including: temperature, pressure, flow rate, humidity, etc.

[0038] In this embodiment, key fuel transportation parameters refer to parameters that require special attention and monitoring during the fuel transportation process, including: temperature, pressure, flow rate, humidity, etc.

[0039] In this embodiment, the installation parameters include: sampling frequency, data transmission protocol, data format, sensor calibration parameters and device unique identification, etc.

[0040] In this embodiment, the original parameters refer to the initial parameter data directly obtained from sensors and monitoring equipment, including temperature, pressure, flow rate, humidity, etc.

[0041] The working principle and beneficial effects of the above technical solution are: by determining key parameters and configuring sensors, real-time monitoring and control of the fuel transportation process can be achieved, thereby improving transportation efficiency and safety and reducing losses.

[0042] Embodiment 3: Based on the above embodiment 1, the data acquisition module includes: Standardization processing unit: after pre-processing the original parameters, the scale is standardized according to the preset standard units and the basic parameters are output; Storage unit: generates standard parameter data from basic parameter data according to the format structure requirements of the standard parameter database and stores it in the standard parameter database.

[0043] In this embodiment, the preprocessing is to perform some basic conversion, calibration and adjustment on the original parameters so as to make them conform to the preset standard unit and format requirements.

[0044] In this embodiment, the preset standard unit is a predefined standard measurement unit used in the fuel transportation process, including: Celsius (°C), Pascal (Pa), percentage (%) and other common standard units.

[0045] In this embodiment, scale standardization is to adjust and convert the original data according to the preset standard unit, and the main steps include: unit conversion, value scaling, and precision adjustment.

[0046] In this embodiment, the format structure requirements are determined according to the database design specifications and business needs, including: data organization, field definition, data type, index setting, etc. In this embodiment, the standard parameter data is basic parameter data that has been preprocessed and standardized.

[0047] The working principle and beneficial effects of the above technical solution are: the basic parameters are preprocessed and the units are standardized by the standardization processing unit, and the storage unit then stores the data in the standard parameter database format, thereby improving data consistency and comparability and enhancing management and analysis efficiency.

[0048] Embodiment 4: Based on the above embodiment 1, the data analysis module includes: Design interface unit: Based on the target processing data type of the interface, design the interface in combination with the preset data transmission protocol, and match the interface type with the target processing data type; Interface matching unit: sends a request to the interface to obtain data. The encryption system encrypts the request into an API key. The interface receives the API key, verifies the legitimacy, passes the request, and returns the original request data. Data processing unit: after preprocessing the original request data, the corresponding target processing data type is set with a unique tag to generate interface data. In this embodiment, the processing data type includes: text data, digital data, image data, audio data, video data, etc.

[0049] In this embodiment, the preset data transmission protocol includes HTTP or HTTPS, which is a convention that specifies the format, mode and rules for data transmission in the network.

[0050] In this embodiment, the corresponding relationship refers to matching the corresponding interface according to the data type. For example, if the target processing data type of the interface is text data, the corresponding interface type is a text analysis interface. In this embodiment, the encryption system refers to a system for encrypting and decrypting data, including components such as encryption algorithms, key management systems, and digital certificates.

[0051] In this embodiment, the API key is a credential used to authenticate and authorize API requests, and can be a long string of random characters or a unique identifier generated based on an algorithm.

[0052] In this embodiment, the legitimacy verification means that after receiving the API request, the interface server checks the request to confirm whether the sender of the request has the right to access the requested resources or perform the requested operation.

[0053] In this embodiment, the original request data is the unprocessed data sent to the interface, and the request contains relevant information of the data to be obtained, including: query parameters, identity authentication information, operation instructions, etc.

[0054] In this embodiment, the unique tag refers to an identifier or label generated after processing the original request data, which is usually generated based on characteristics such as data content, type, and processing method.

[0055] In this embodiment, the interface data refers to the original data obtained and returned from the interface, which is structured data organized in a specific format (such as JSON, XML, etc.).

[0056] The working principle and beneficial effects of the above technical solution are: by designing secure interfaces and efficient data processing processes, the security, quality and efficient processing of data are ensured, and the efficiency and value of data utilization are improved.

[0057] Embodiment 5: Based on the above embodiment 4, the data analysis module includes: Parameter classification unit: used to classify the types of interface data into three categories based on tags: fuel transportation tool parameters, fuel body parameters and environmental parameters; Location unit: Based on the fuel transportation tool parameters of the fuel transportation tool, the starting point and end point of the fuel transportation and the preset transportation route are obtained, and a standard transportation grid map is constructed according to the supply chain where the starting point and end point are located, and all the waypoints between the starting point and end point are marked, where the length and width of the grid unit are proportional to the actual geographical longitude and latitude; Transportation status unit: compares the real-time parameter data of the fuel transportation tool with the basic parameters of the fuel transportation tool. If the absolute value of the deviation of any parameter is greater than a preset error value, it is predicted that the fuel transportation tool is abnormal and the abnormal level of the fuel transportation tool is determined; otherwise, it is determined that the fuel transportation tool is not abnormal; ; in, represents the abnormal level of the fuel transportation vehicle, ( ) represents the level conversion function, represents the absolute value of the deviation of the i-th parameter of the fuel transportation vehicle, It represents the minimum absolute value of all parameter deviations of fuel transportation vehicles. represents the mean of the absolute values ​​of all parameter deviations of fuel transport vehicles, It represents the maximum absolute value of all parameter deviations of fuel transportation vehicles. Indicates the change in estimated deviation n means there are n parameters in total; Output the transportation status of the fuel transportation vehicle, including: the real-time location of the fuel transportation vehicle, the abnormal status and abnormal level of the fuel transportation vehicle; Upload unit: upload the transportation status of all entities in the supply chain to the intelligent dispatching platform.

[0058] In this embodiment, environmental parameters refer to parameters related to the fuel transportation and fuel use environment, including: air temperature, humidity, atmospheric pressure, wind speed and wind direction, etc.

[0059] In this embodiment, the supply chain is the relationship and operation process between various entities related to fuel transportation.

[0060] In this embodiment, the standard transportation grid map is a diagram that divides the geographical space of the transportation route into regular grid units, and each grid unit represents an area.

[0061] In this embodiment, the waypoint refers to an intermediate station on a preset route for fuel transportation.

[0062] In this embodiment, the actual geographic longitude and latitude are the real longitude and latitude at the geographical level.

[0063] In this embodiment, the real-time parameter data refers to various real-time data generated by the fuel transportation vehicle during the transportation process, including: location information, fuel parameters, movement status, etc.

[0064] In this embodiment, the preset error value is a preset allowable deviation value for abnormality judgment.

[0065] In this embodiment, the abnormality level is a coefficient that quantifies the severity of an abnormality that may exist in the fuel transportation vehicle.

[0066] In this embodiment, the abnormal state is an abnormal situation that occurs in the fuel transportation vehicle or the fuel body, including various faults of the fuel transportation vehicle, deviation from the predetermined route, and parameter deviation exceeding a preset error value.

[0067] In this embodiment, the level conversion function converts various parameters of the fuel transportation vehicle into an abnormal level.

[0068] In this embodiment, the estimated deviation change amount indicates the possible change amount of the deviation absolute value of the fuel transportation tool parameter within a period of time in the future.

[0069] In this embodiment, the quality state refers to the physical and chemical properties of the fuel, including parameters such as temperature, composition, density, water content, and pressure.

[0070] The working principle and beneficial effects of the above technical solution are: monitoring the fuel transportation process, including parameter classification, location acquisition, transportation status monitoring, quality status monitoring and uploading functions, which improves transportation safety and efficiency.

[0071] Embodiment 6: Based on the above embodiment 5, the program formulation module includes: Quality status unit: Based on the transportation prediction model, the real-time data of fuel body parameters are compared with the basic parameters of the fuel, and the quality status is output; Detention status unit: retrieves the transportation status of the fuel transportation vehicle from the intelligent transportation platform. If the abnormality level of the fuel transportation vehicle is greater than the preset maximum level, the fuel transportation vehicle is detained at the location and waits for subsequent instructions; if the abnormality level is greater than the preset warning level and less than or equal to the preset maximum level, the fuel transportation vehicle is sent to the nearest waypoint to wait for handover; otherwise, it is determined that the fuel transportation vehicle can be transported normally; Time prediction unit: based on the quality status of the fuel and the retention status of the fuel transportation vehicle, predict the time when the fuel transportation vehicle arrives at the destination, assuming that the coordinates of the retention point are o , the predicted arrival time is:

[0072] in, represents the predicted arrival time of the fuel transportation vehicle, Indicates the time the fuel transport vehicle has been transporting. represents the residence time function of the retention point o, M represents the quality state of the fuel, The preset weight coefficient representing the quality status, represents the preset weight coefficient of the residence time, represents the preset weight coefficient of the environmental state, represents the speed-time conversion function, represents the maximum speed within the jth standard distance, represents the minimum speed within the jth standard distance, It represents the estimated maximum time within the standard journey from the stopover point to the destination. represents the logarithmic function symbol, ave represents the average extracted variance value, and n0 represents a total of n0 standard distances. represents the kth environmental parameter within the jth standard distance, and m represents that there are m environmental parameters in the standard distance.

[0073] In this embodiment, the fuel body parameters refer to parameters related to the characteristics and quality of the fuel itself, such as the density, viscosity, sulfur content, carbon content and oxygen content of the fuel.

[0074] In this embodiment, the transportation prediction model refers to a model that combines the real-time data of the fuel body parameters and the basic parameters of the fuel to judge the quality of fuel transportation. For example, the current real-time parameter group of the fuel is: , the basic parameter group of fuel is: , then the model determines the quality state of the fuel as ;.

[0075] In this embodiment, the transport status refers to the current transport status of the tool, including information such as its position, speed, and load status.

[0076] In this embodiment, the preset maximum level refers to the highest threshold of the abnormal level set in the intelligent transportation platform.

[0077] In this embodiment, detention means that the fuel transportation vehicle stays at a certain location for some reason and does not continue to move forward or transport, including: equipment failure, traffic congestion, safety considerations and other factors.

[0078] In this embodiment, the preset warning level refers to an indicator of the degree of abnormality set during the monitoring and evaluation of the transportation of the fuel transportation vehicle.

[0079] In this embodiment, the retention point refers to a stop position that may occur during the fuel transportation process.

[0080] In this embodiment, the detention state refers to different stopping states that may occur in the fuel transportation vehicle during the transportation process, including: equipment failure, traffic congestion, safety considerations and other factors.

[0081] In this embodiment, the retention time function is a function that comprehensively predicts the retention time based on the retention points.

[0082] In this embodiment, the preset weight coefficient is a pre-set coefficient representing the degree of influence of different entity transportation states on the retention time.

[0083] The working principle and beneficial effects of the above technical solution are: combining the intelligent dispatching platform to monitor the status of fuel transportation tools, improving transportation safety and efficiency through detention status evaluation and time prediction, and ensuring that the fuel arrives at the destination smoothly.

[0084] Embodiment 7: Based on the above embodiment 6, the plan formulation module further includes: Optimal route processing unit: If Greater than the preset arrival time , replan the route of the fuel transportation tool, obtain the time consumption corresponding to the two waypoints m and n from the time consumption degree-waypoint mapping table, obtain the estimated transportation time of the remaining path after the abnormal starting point in the original transportation path, and obtain the initial time consumption degree ; Construct all target transport points that have a connection relationship between all route points and abnormal starting points as a set V, and obtain the point with the minimum time consumption , point Put it into the optimal set S, and find the point in the set V Points with a connection relationship and the minimum time consumption , and point Put it into the optimal set S until the set S contains the endpoint and the iteration ends. If the total time consumption of the optimal set S is greater than , repeatedly iteratively select adjacent points until the total time consumption of the optimal set S is less than , determine that all the waypoints of the optimal set S are the best route waypoints, and upload the optimal set S to the intelligent transportation platform.

[0085] In this embodiment, re-planning refers to re-planning a new plan path when the original plan or path is no longer applicable.

[0086] In this embodiment, the time consumption degree-way point mapping table is a table indicating the mapping relationship between way points and time consumption degrees.

[0087] In this embodiment, the time consumption refers to the time cost consumption in route planning or path selection, and a higher value indicates a greater cost consumption.

[0088] In this embodiment, the remaining path is the path that has not been traversed from the current position to the destination after excluding the traversed part of the path.

[0089] In this embodiment, the estimated transportation time refers to an estimate of the time required for the entire path from the current location to the destination based on the current route planning and known road conditions and other information.

[0090] In this embodiment, the connection relationship refers to the accessibility and connectivity between various waypoints in the route.

[0091] In this embodiment, the target transportation point refers to the final destination.

[0092] In this embodiment, the optimal set refers to a set of best route waypoints selected during the route planning process.

[0093] In this embodiment, the best route waypoints refer to all waypoints on the optimal path selected during the route planning process.

[0094] The working principle and beneficial effects of the above technical solution are: through dynamic planning, iterative selection of optimal path points, route replanning of fuel transportation vehicles can be achieved, transportation efficiency and intelligent scheduling management can be improved, and logistics transportation can be made more flexible and efficient.

[0095] Embodiment 8: Based on the above embodiment 1, the scheme adjustment module includes: Plan adjustment unit: Based on the intelligent transportation platform, the real-time transportation status of the fuel transportation tool after the plan adjustment is obtained. If anomalies are predicted in the future, the plan is adjusted in real time and the transportation status parameters are detected.

[0096] In this embodiment, the real-time transportation status refers to real-time data of parameters such as the current position, speed, fuel consumption rate, and estimated arrival time of the fuel transportation vehicle.

[0097] The working principle and beneficial effects of the above technical solution are: real-time acquisition of the status of fuel transportation vehicles, prediction of abnormalities and adjustment of plans, and improvement of transportation reliability, efficiency and economy.

[0098] Embodiment 9: like Figure 2 As shown, an embodiment of the present invention provides a method for intelligent fuel transportation, comprising: Step 1: Use sensors and monitoring equipment to collect basic parameters of the fuel transportation process in real time, and store the basic parameters in a standard parameter database after standardization; Step 2: Obtain the basic parameter information of the fuel and the real-time location information of the fuel transportation vehicle in real time through the interface, predict the transportation status of all entities in the supply chain according to the transportation prediction model, and output it to the intelligent transportation platform; Step 3: Dispatch the transportation status of all entities on the intelligent transportation platform and formulate the optimal fuel transportation plan; Step 4: Based on the intelligent transportation platform, dynamically adjust the optimal fuel transportation plan according to the real-time situation of fuel transportation.

[0099] The working principle and beneficial effects of the above technical solution are: based on real-time data collection and analysis, intelligent scheduling is used to optimize fuel supply chain transportation, improve efficiency and reduce costs, enhance stability, and improve transportation efficiency.

[0100] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. 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 fuel intelligent transportation system, characterized in that: include: Data acquisition module: uses sensors and monitoring equipment to collect basic parameters of the fuel transportation process in real time, and stores the basic parameters in the standard parameter database after standardization; Data analysis module: obtains basic parameter information of fuel and real-time location information of fuel transportation vehicles through the interface, predicts the transportation status of all entities in the supply chain based on the transportation prediction model, and outputs it to the intelligent transportation platform; Plan formulation module: dispatch the transportation status of all entities on the intelligent transportation platform and formulate the optimal fuel transportation plan; Plan adjustment module: Based on the intelligent transportation platform, dynamically adjust the optimal fuel transportation plan according to the real-time situation of fuel transportation.

2. The intelligent fuel transportation system according to claim 1, characterized in that: The data acquisition module comprises: Parameter determination unit: determines the key fuel transportation parameters of the monitoring target and builds a standard parameter database based on the types of the key fuel transportation parameters; Configuration unit: After configuring the installation parameters to the sensors and monitoring equipment, the original parameters of the fuel transportation process are collected in real time.

3. The intelligent fuel transportation system according to claim 1, characterized in that: The data acquisition module comprises: Standardization processing unit: after pre-processing the original parameters, the scale is standardized according to the preset standard units and the basic parameters are output; Storage unit: generates standard parameter data from basic parameter data according to the format structure requirements of the standard parameter database and stores it in the standard parameter database.

4. The intelligent fuel transportation system according to claim 1, characterized in that: The data analysis module comprises: Design interface unit: Based on the target processing data type of the interface, design the interface in combination with the preset data transmission protocol, and match the interface type with the target processing data type; Interface matching unit: sends a request to the interface to obtain data. The encryption system encrypts the request into an API key. The interface receives the API key, verifies the legitimacy, passes the request, and returns the original request data. Data processing unit: After preprocessing the original request data, the corresponding target processing data type sets a unique tag to generate interface data.

5. The intelligent fuel transportation system according to claim 4, characterized in that: The data analysis module comprises: Parameter classification unit: used to classify the types of interface data into three categories based on tags: fuel transportation tool parameters, fuel body parameters and environmental parameters; Location unit: Based on the fuel transportation tool parameters of the fuel transportation tool, the starting point and end point of the fuel transportation and the preset transportation route are obtained, and a standard transportation grid map is constructed according to the supply chain where the starting point and end point are located, and all the waypoints between the starting point and end point are marked, where the length and width of the grid unit are proportional to the actual geographical longitude and latitude; Transportation status unit: compares the real-time parameter data of the fuel transportation tool with the basic parameters of the fuel transportation tool. If the absolute value of the deviation of any parameter is greater than a preset error value, it is predicted that the fuel transportation tool is abnormal and the abnormal level of the fuel transportation tool is determined; otherwise, it is determined that the fuel transportation tool is not abnormal; ;in, represents the abnormal level of the fuel transportation vehicle, ( ) represents the level conversion function, represents the absolute value of the deviation of the i-th parameter of the fuel transportation vehicle, It represents the minimum absolute value of all parameter deviations of fuel transportation vehicles. represents the mean of the absolute values ​​of all parameter deviations of fuel transport vehicles, It represents the maximum absolute value of all parameter deviations of fuel transportation vehicles. It indicates the change of estimated deviation, and n indicates that there are n parameters in total; Output the transportation status of the fuel transportation vehicle, including: the real-time location of the fuel transportation vehicle, the abnormal status and abnormal level of the fuel transportation vehicle; Upload unit: upload the transportation status of all entities in the supply chain to the intelligent dispatching platform.

6. The intelligent fuel transportation system according to claim 5, characterized in that: The program formulation module includes: Quality status unit: Based on the transportation prediction model, the real-time data of the fuel body parameters are compared with the basic parameters of the fuel, and the quality status is output; Detention status unit: retrieves the transportation status of the fuel transportation vehicle from the intelligent transportation platform. If the abnormality level of the fuel transportation vehicle is greater than the preset maximum level, the fuel transportation vehicle is detained at the location and waits for subsequent instructions; if the abnormality level is greater than the preset warning level and less than or equal to the preset maximum level, the fuel transportation vehicle is sent to the nearest waypoint to wait for handover; otherwise, it is determined that the fuel transportation vehicle can be transported normally; Time prediction unit: based on the quality status of the fuel and the retention status of the fuel transportation vehicle, predict the time when the fuel transportation vehicle arrives at the destination, assuming that the coordinates of the retention point are o , the predicted arrival time is: ;in, represents the predicted arrival time of the fuel transportation vehicle, Indicates the time the fuel transport vehicle has been transporting. represents the residence time function of the retention point o, M represents the quality state of the fuel, The preset weight coefficient representing the quality status, represents the preset weight coefficient of the residence time, represents the preset weight coefficient of the environmental state, represents the speed-time conversion function, represents the maximum speed within the jth standard distance, represents the minimum speed within the jth standard distance, It represents the estimated maximum time within the standard journey from the stopover point to the destination. represents the logarithmic function symbol, ave represents the average extracted variance value, It means there are n0 standard distances in total. represents the kth environmental parameter within the jth standard distance, and m represents that there are m environmental parameters in the standard distance.

7. The intelligent fuel transportation system according to claim 6, characterized in that: The program formulation module also includes: Optimal route processing unit: If Greater than the preset arrival time , replan the route of the fuel transportation tool, obtain the time consumption corresponding to the two waypoints m and n from the time consumption degree-waypoint mapping table, obtain the estimated transportation time of the remaining path after the abnormal starting point in the original transportation path, and obtain the initial time consumption degree ; Construct all target transport points that have a connection relationship between all route points and abnormal starting points as a set V, and obtain the point with the minimum time consumption , point Put it into the optimal set S, and find the point in the set V Points with a connection relationship and minimum time consumption , and point Put it into the optimal set S until the set S contains the endpoint and the iteration ends. If the total time consumption of the optimal set S is greater than , repeatedly iteratively select adjacent points until the total time consumption of the optimal set S is less than , determine that all the waypoints of the optimal set S are the best route waypoints, and upload the optimal set S to the intelligent transportation platform.

8. The intelligent fuel transportation system according to claim 1, characterized in that: The scheme adjustment module includes: Plan adjustment unit: Based on the intelligent transportation platform, the real-time transportation status of the fuel transportation tool after the plan adjustment is obtained. If anomalies are predicted in the future, the plan is adjusted in real time and the transportation status parameters are detected.

9. A method for intelligent fuel transportation, characterized in that: include: Step 1: Use sensors and monitoring equipment to collect basic parameters of the fuel transportation process in real time, and store the basic parameters in a standard parameter database after standardization; Step 2: Obtain the basic parameter information of the fuel and the real-time location information of the fuel transportation vehicle in real time through the interface, predict the transportation status of all entities in the supply chain according to the transportation prediction model, and output it to the intelligent transportation platform; Step 3: Dispatch the transportation status of all entities on the intelligent transportation platform and formulate the optimal fuel transportation plan; Step 4: Based on the intelligent transportation platform, dynamically adjust the optimal fuel transportation plan according to the real-time situation of fuel transportation.

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