Mine transport vehicle data integration method and system based on big data

Abstract

The invention discloses a big data-based mine transport vehicle data integration method and system. The big data-based mine transport vehicle data integration method comprises the steps of obtaining vehicle operation data and environment data generated in a vehicle transport process; analyzing the obtained vehicle operation data and environment data, and matching the vehicle operation data and the environment data according to time and position by using a real-time processing framework of big data; and sending the matched vehicle operation data and environment data to a distributed database. According to the invention, the environment data of the environment sensor at the fixed position and the vehicle operation data are effectively integrated and synchronized, and the consistency and accuracy of the data are ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of data integration, and in particular relates to a method and system for integrating mining transportation vehicle data based on big data. Background Art

[0002] In the operation of traditional transport vehicles, the vehicle's operating parameters (such as engine speed, gear, etc.) are mainly controlled by the driver's experience. These parameters have a significant impact on the vehicle's fuel consumption. Under the requirements of efficient and energy-saving mining, how to achieve fuel economy has become a key issue for all mining parties.

[0003] Studies have shown that there is a significant correlation between engine speed and environmental factors. For example, in a high temperature environment, the load on the engine cooling system increases, resulting in a decrease in fuel efficiency. By appropriately reducing the engine speed, the burden on the cooling system can be reduced and fuel efficiency can be improved. In a high humidity environment, the air density increases and the combustion efficiency decreases. By properly adjusting the engine speed, the combustion process can be optimized and fuel consumption can be reduced.

[0004] When mines are located in mountainous areas at high altitudes, the climate and environment vary greatly. Therefore, obtaining environmental information during vehicle transportation is a key challenge in optimizing vehicle operating parameters. Due to cost constraints, vehicles are usually not equipped with environmental monitoring sensors, but are installed independently in fixed locations. This brings up an important technical issue: how to effectively integrate environmental data with vehicle status data so that analysts can optimize vehicle operating parameters based on real-time environmental information, thereby improving vehicle fuel economy.

[0005] In the Chinese invention patent application with publication number CN118708585A, a multi-source heterogeneous data integration system based on distributed computing is proposed. The multi-source heterogeneous data is formatted in a unified manner through a distributed formatting processing network. After feature extraction and calculation, a fusion subset is created, and finally the integrated data is realized.

[0006] In the Chinese invention patent application with publication number CN118426915A, a vehicle data integration method is proposed, which uses a long connection method to realize asynchronous, non-blocking, decoding and classification integration of vehicle data, focusing on solving data transmission efficiency, making full use of machine performance, and thus improving the timeliness of data transmission.

[0007] The above two patents solve the problems of efficiency and flexibility of data integration through distributed computing and long connections respectively, but they need to build a model to extract data features. The process is complicated and cannot realize the need to merge different data sources. In addition, insufficient attention is paid to the timeliness of data integration and it cannot meet the real-time integration requirements of vehicle operation data and environmental data. Summary of the invention

[0008] In response to the above problems, the present invention proposes a mine transportation vehicle data integration method and system based on big data, which realizes the effective integration and synchronization of environmental data from environmental sensors at fixed locations with vehicle operation data, ensuring the consistency and accuracy of the data.

[0009] In order to achieve the above technical objectives and the above technical effects, the present invention is implemented through the following technical solutions: In a first aspect, the present invention provides a method for integrating mine transportation vehicle data based on big data, comprising: Acquire vehicle operation data and environmental data generated during vehicle transportation; Analyze the acquired vehicle operation data and environmental data; Using the real-time processing framework of big data, the parsed vehicle operation data and environmental data are matched according to time and location; The matched vehicle operation data and environmental data are sent to the distributed database.

[0010] In combination with the first aspect, optionally, the vehicle operation data includes vehicle position coordinates and vehicle operation time information, and the environmental data includes position coordinates of environmental sensors and time information when the environmental data is generated.

[0011] In combination with the first aspect, optionally, parsing the acquired vehicle operation data and environmental data, and matching the vehicle operation data and environmental data according to time and location, includes: Matching environmental data corresponding to the vehicle operation data according to the vehicle position coordinates in the vehicle operation data and the position coordinates of the environmental sensor in the environmental data; By utilizing the real-time data processing framework of big data, based on the time information generated by vehicle operation time information and environmental data, the water level update mechanism is used to determine the match and calculate the trigger, so as to obtain the environmental data corresponding to the vehicle operation data at different times and locations.

[0012] In combination with the first aspect, optionally, the mine transportation vehicle data integration method based on big data further includes: With the goal of achieving minimum fuel consumption, the engine speed and gear are optimized based on the matched vehicle operating data and environmental data.

[0013] In combination with the first aspect, optionally, in the process of optimizing the engine speed and gear position, an optimized neural network and genetic algorithm are used to achieve it.

[0014] In combination with the first aspect, optionally, after parsing the acquired vehicle operation data and environmental data, the method further includes: Add labels to vehicle operation data and environmental data, and merge data with the same labels; The step of adding labels to the vehicle operation data and the environmental data includes: Extracting the vehicle VIN code and the sending time from the vehicle operation data to form a vehicle label; A sensor number and a transmission time are extracted from the environmental data to form a tag of the environmental data.

[0015] In a second aspect, the present invention provides a mine transportation vehicle data integration system based on big data, comprising: A data acquisition module is used to obtain vehicle operation data and environmental data generated during vehicle transportation; A data analysis module, used to analyze the acquired vehicle operation data and environmental data; Data integration module, which is used to match the parsed vehicle operation data and environmental data according to time and location using the real-time processing framework of big data; The data storage module is used to send the matched vehicle operation data and environmental data to the distributed database.

[0016] In combination with the second aspect, optionally, the mine transportation vehicle data integration system based on big data further includes: The data application module is used to optimize the engine speed and gear position according to the matched vehicle operation data and environmental data with the goal of achieving minimum fuel consumption.

[0017] In a third aspect, the present invention provides a mine transportation vehicle data integration system based on big data, including a vehicle end, an environmental sensor and a server end; The vehicle end includes a position sensor and a controller arranged on the vehicle, wherein the position sensor is used to collect the position data of the vehicle in real time; the controller sends the vehicle operation information and the real-time position data of the vehicle to the service end through the base station; The environmental sensor collects environmental data in real time and sends it to the server through the base station; The server is configured to execute any one of the methods described in the first aspect.

[0018] In a fourth aspect, the present invention provides a mine transportation vehicle data integration system based on big data, comprising a storage medium and a processor; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the method according to any one of the first aspects.

[0019] Compared with the prior art, the present invention has the following beneficial effects: The present invention utilizes a real-time processing framework of big data to achieve matching of vehicle operation data with environmental data, thus avoiding the problem that traditional methods cannot match the environmental status at the time of vehicle operation.

[0020] The present invention utilizes a wireless base station to transmit vehicle operation data and environmental data to a server side in real time, and the server side receives and processes the data from the wireless base station.

[0021] The present invention utilizes a neural network to extract key features of integrated data and predict an optimization scheme for vehicle operating parameters; and utilizes a genetic algorithm model to perform multi-objective optimization based on the prediction results to maximize fuel economy. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative labor, among which: Figure 1 This is a schematic structural diagram of a mining transportation vehicle data integration system based on big data according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0024] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention. Example 1

[0025] An embodiment of the present invention provides a method for integrating mining transportation vehicle data based on big data, which is applied to a server and includes the following steps: (1) Obtain vehicle operation data and environmental data generated during vehicle transportation; (2) Analyze the acquired vehicle operation data and environmental data; (3) Using the real-time processing framework of big data, the parsed vehicle operation data and environmental data are matched according to time and location; (4) The matched vehicle operation data and environmental data are sent to the distributed database. With the help of the horizontal expansion, high fault tolerance, and automatic load balancing characteristics of the distributed database components, the needs for large data storage in mining construction scenarios can be met.

[0026] The present invention utilizes a real-time processing framework of big data to match vehicle operation data with environmental data based on time and location information, thus avoiding the problem that traditional methods cannot match the environmental status at the time of vehicle operation.

[0027] In a specific implementation of the embodiment of the present invention, the vehicle operation data includes the vehicle position coordinates and the vehicle operation time information, and the environmental data includes the position coordinates of the environmental sensor and the time information when the environmental data is generated. In the specific implementation process, there are several environmental sensors, and each environmental sensor is connected to the server end through a base station, and the collected environmental data is sent to the server end through the base station. The vehicle is equipped with a position sensor and a controller, and the position sensor is used to collect the vehicle's position data in real time; the controller sends the vehicle operation information and the vehicle's real-time position data to the server end through the base station.

[0028] In a specific implementation of an embodiment of the present invention, the parsing of the acquired vehicle operation data and environmental data includes: processing the collected vehicle operation data and environmental data, parsing the vehicle operation data and environmental data according to the metadata definition of the data source, realizing data structuring, and filtering out data that does not meet the specifications.

[0029] In a specific implementation of the embodiment of the present invention, parsing the acquired vehicle operation data and environmental data, and matching the vehicle operation data and environmental data according to time and location, includes: Matching environmental data corresponding to the vehicle operation data according to the vehicle position coordinates in the vehicle operation data and the position coordinates of the environmental sensor in the environmental data; By utilizing the real-time data processing framework of big data, based on the time information generated by vehicle operation time information and environmental data, the water level update mechanism is used to determine the match and calculate the trigger, so as to obtain the environmental data corresponding to the vehicle operation data at different times and locations.

[0030] In a specific implementation of the embodiment of the present invention, the mine transportation vehicle data integration method based on big data also includes: With the goal of achieving minimum fuel consumption, the engine speed and gear are optimized based on the matched vehicle operating data and environmental data.

[0031] In a specific implementation of the embodiment of the present invention, in the process of optimizing the engine speed and gear position, an optimized neural network and genetic algorithm are used to achieve it. In the specific implementation process, the neural network is used to use all the integrated data columns as the features of the input layer, add hidden layers and activation functions to support complex mapping, and the output layer selects the mileage under unit fuel consumption to calculate the optimized operating parameters. The genetic algorithm uses real number coding, combined with the prediction results of the neural network, to design the fitness function, and uses genetic operations to output the optimal operating parameters when the stop condition is reached.

[0032] In a specific implementation of the embodiment of the present invention, after parsing the acquired vehicle operation data and environmental data, the method further includes: Add tags to vehicle operation data and environmental data, and merge data with the same tags to facilitate users to transparently access required data; The step of adding labels to the vehicle operation data and the environmental data includes: Extracting the vehicle VIN code and the sending time from the vehicle operation data to form a vehicle label; A sensor number and a transmission time are extracted from the environmental data to form a tag of the environmental data. Example 2

[0033] In an embodiment of the present invention, a mine transportation vehicle data integration system based on big data is provided. Figure 1 As shown, including: A data acquisition module is used to obtain vehicle operation data and environmental data generated during vehicle transportation; A data analysis module, used to analyze the acquired vehicle operation data and environmental data; Data integration module, which is used to match the parsed vehicle operation data and environmental data according to time and location using the real-time processing framework of big data; The data storage module is used to send the matched vehicle operation data and environmental data to the distributed database.

[0034] In a specific implementation of the embodiment of the present invention, the mine transportation vehicle data integration system based on big data further includes: The data application module is used to optimize the engine speed and gear position according to the matched vehicle operation data and environmental data with the goal of achieving minimum fuel consumption. Example 3

[0035] The embodiment of the present invention provides a mine transportation vehicle data integration system based on big data, including a vehicle end, an environmental sensor and a server end; The vehicle end includes a position sensor and a controller arranged on the vehicle, wherein the position sensor is used to collect the position data of the vehicle in real time; the controller sends the vehicle operation information and the real-time position data of the vehicle to the service end through the base station; The environmental sensor collects environmental data in real time and sends it to the server through the base station; The server is configured to execute the method described in any one of Embodiment 1.

[0036] In the specific implementation process, the environmental sensor needs to have a two-way communication capability so as to communicate with the base station and thus realize time correction. Example 4

[0037] An embodiment of the present invention provides a mine transportation vehicle data integration system based on big data, including a storage medium and a processor; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the method according to any one of the embodiments 1.

[0038] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0039] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0040] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0041] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0042] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which all fall within the protection of the present invention.

[0043] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A mine transportation vehicle data integration method based on big data, characterized in that: include: Acquire vehicle operation data and environmental data generated during vehicle transportation; Analyze the acquired vehicle operation data and environmental data; Using the real-time processing framework of big data, the parsed vehicle operation data and environmental data are matched according to time and location; The matched vehicle operation data and environmental data are sent to the distributed database.

2. The method for integrating mining transportation vehicle data based on big data according to claim 1, characterized in that: The vehicle operation data includes the vehicle position coordinates and vehicle operation time information, and the environmental data includes the position coordinates of the environmental sensor and the time information of the environmental data generation.

3. The method for integrating mining transportation vehicle data based on big data according to claim 2 is characterized in that: The step of parsing the acquired vehicle operation data and environmental data and matching the vehicle operation data and environmental data according to time and location includes: Matching environmental data corresponding to the vehicle operation data according to the vehicle position coordinates in the vehicle operation data and the position coordinates of the environmental sensor in the environmental data; By utilizing the real-time data processing framework of big data, based on the time information generated by vehicle operation time information and environmental data, the water level update mechanism is used to determine the match and calculate the trigger, so as to obtain the environmental data corresponding to the vehicle operation data at different times and locations.

4. The method for integrating mining transportation vehicle data based on big data according to claim 1, characterized in that: The mine transportation vehicle data integration method based on big data also includes: With the goal of achieving minimum fuel consumption, the engine speed and gear are optimized based on the matched vehicle operating data and environmental data.

5. The method for integrating mining transportation vehicle data based on big data according to claim 4 is characterized in that: In the process of optimizing the engine speed and gear, the optimized neural network and genetic algorithm are used to achieve it.

6. The method for integrating mining transportation vehicle data based on big data according to claim 1, characterized in that: After parsing the acquired vehicle operation data and environmental data, the method further includes: Add labels to vehicle operation data and environmental data, and merge data with the same labels; The step of adding labels to the vehicle operation data and the environmental data includes: Extracting the vehicle VIN code and the sending time from the vehicle operation data to form a vehicle label; A sensor number and a transmission time are extracted from the environmental data to form a tag of the environmental data.

7. A mine transportation vehicle data integration system based on big data, characterized in that: include: A data acquisition module is used to obtain vehicle operation data and environmental data generated during vehicle transportation; A data analysis module, used to analyze the acquired vehicle operation data and environmental data; Data integration module, which is used to match the parsed vehicle operation data and environmental data according to time and location using the real-time processing framework of big data; The data storage module is used to send the matched vehicle operation data and environmental data to the distributed database.

8. The mine transportation vehicle data integration system based on big data according to claim 7 is characterized in that: The mine transportation vehicle data integration system based on big data also includes: The data application module is used to optimize the engine speed and gear position according to the matched vehicle operation data and environmental data with the goal of achieving minimum fuel consumption.

9. A mine transportation vehicle data integration system based on big data, characterized in that: Including vehicle side, environmental sensor and server side; The vehicle end includes a position sensor and a controller arranged on the vehicle, wherein the position sensor is used to collect the position data of the vehicle in real time; the controller sends the vehicle operation information and the real-time position data of the vehicle to the service end through the base station; The environmental sensor collects environmental data in real time and sends it to the server through the base station; The server is configured to execute the method according to any one of claims 1 to 6.

10. A mine transportation vehicle data integration system based on big data, characterized in that: including storage media and processors; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the method according to any one of claims 1-6.

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