Fuel consumption analysis method for mine vehicle, electronic equipment, medium and system

Abstract

The invention provides a fuel consumption analysis method, electronic equipment, medium and system for a mine vehicle, and the method comprises the steps: obtaining the state information of the vehicle and the road information of a mine, the road information comprising the longitude, the latitude and the elevation; dividing the road into a plurality of line segments according to the road information, removing curve line segments, leaving straight line segments, and storing the longitudes, latitudes and elevations of the plurality of straight line segments as a first sample library; calculating the gradient of each straight-line segment in the first sample library according to the elevation, and correspondingly storing the gradient of each straight-line segment, the longitude, the latitude and the elevation to form a second sample library; classifying samples in a second sample library according to the state information and the gradient of the vehicle to form a plurality of classification groups; and in each classification group, analyzing the relationship among the state information of the vehicle, the gradient and the fuel consumption of the vehicle. The technical problem that systematic, complete and effective oil consumption data of the mining vehicle cannot be accurately obtained in the prior art is solved, and the influence of the speed and load conditions of the mining vehicle and the slope of the road on the oil consumption is clearly and accurately known by adopting the oil consumption analysis method of the mining vehicle, so that the oil consumption analysis accuracy is improved. And the management of the mining vehicles can be refined and accurate.

Description

Technical Field

[0001] The present invention relates to the field of vehicles, and particularly to a fuel consumption analysis method, an electronic device, a medium and a system for mining vehicles. Background Art

[0002] In the prior art, in open-pit mine road transportation, the quality of the road directly affects transportation safety and transportation cost. Fine management and control of the road are the key to improving transportation safety and reducing transportation cost. Obtaining systematic, complete, and effective data is a prerequisite for achieving fine production and management.

[0003] In the existing open-pit mine production and operation management work, only empirical knowledge can often be formed. Due to the lack of support from key data and methods during decision-making, it is difficult to carry out scientific decision-making and accurate implementation. Summary of the Invention

[0004] Based on the above problems, the present invention proposes a fuel consumption analysis method, an electronic device, a medium and a system for mining vehicles. The present invention solves the technical problem in the prior art that it is impossible to accurately obtain systematic, complete, and effective fuel consumption data of mining vehicles. By using the fuel consumption analysis method for mining vehicles proposed by the present invention, the influence of the speed, load condition of the mining vehicle and the slope of the road on the fuel consumption is clearly and accurately understood, enabling the management of mining vehicles to be refined and accurate.

[0005] The present invention proposes a fuel consumption analysis method for mining vehicles, including:

[0006] Obtain the status information of the vehicle and the road information of the mine, where the road information includes longitude, latitude, and elevation;

[0007] Divide the road into multiple line segments according to the road information, remove the curved line segments among them, leave the straight line segments, and store the longitude, latitude, and elevation of the multiple straight line segments as the first sample library;

[0008] Calculate the slope of each straight line segment in the first sample library according to the elevation, and store the slope of each straight line segment corresponding to the longitude, latitude, and elevation to form a second sample library;

[0009] Classify the samples in the second sample library according to the status information of the vehicle and the slope to form multiple classification groups;

[0010] Within each classification group, analyze the relationship between the status information of the vehicle, the slope, and the vehicle fuel consumption.

[0011] In addition, the step of dividing the road into multiple line segments according to the road information and removing the curved line segments among them includes:

[0012] Calculate the curvature of each line segment based on the longitudes and latitudes of the two endpoints of the line segment. If the curvature is greater than the curvature threshold, determine that the line segment is a curved line segment.

[0013] In addition, the calculating the curvature of each line segment based on the longitudes and latitudes of the two endpoints of the line segment includes:

[0014] Select three adjacent data points P i 、P i-1 、P i+1 in positive order within the two endpoints of each line segment to form two vectors V i-1 and V i ;

[0015] V i-1 =(x i -x i-1 ,y i -y i-1 )

[0016] V i =(x i+1 -x i ,y i+1 -y i )

[0017] where V i-1 and V i respectively represent the vectors of the line segments formed by connecting the three data points pairwise, x i ,x i-1 ,x i+1 respectively represent the latitudes of the three data points, and y i ,y i-1 ,y i+1 respectively represent the longitudes of the three data points;

[0018] Calculate the lengths of the vectors according to the Euclidean distance formula;

[0019]

[0020] In the formula, |V i-1 | and |V i | respectively represent the moduli of the vectors V i-1 , V i ;

[0021] Calculate the cosine value between the vectors according to the vector dot product formula, then calculate the included angle between the vectors according to the inverse cosine function, and convert it into the included angle of the vectors in degree system;

[0022]

[0023] In the formula, θ degrepresents the included angle of vectors in degree measure, θ represents the included angle of vectors in radian measure, g is the value of gravitational acceleration, and π is the ratio of the circumference of a circle to its diameter;

[0024] θ deg is the curvature of the line segment.

[0025] In addition, before storing the longitude, latitude, and elevation of multiple straight line segments into the first sample library, the following steps are also included:

[0026] Filter and fill the road information of the straight line segment;

[0027] Filter and fill the status information of the vehicle.

[0028] In addition, the filtering and filling process of the road information of the straight line segment includes:

[0029] Determine whether there are abnormal data among the three data of longitude, latitude, and elevation in the road information. If so, determine that the straight line segment is an abnormal segment, and collect the road information of the two straight line segments before and after the abnormal segment to perform mean filling processing on the abnormal segment.

[0030] In addition, the filtering and filling process of the status information of the vehicle includes:

[0031] The status information of the vehicle includes: vehicle speed, load capacity, and fuel consumption;

[0032] If any abnormal data is detected in the vehicle speed, load capacity, or fuel consumption, remove the abnormal data and use the mean filling method to fill the data at the abnormal data location.

[0033] In addition, calculating the slope of each straight line segment in the first sample library according to the elevation includes:

[0034]

[0035] In the formula, i is the slope of the straight line segment, △h is the elevation difference between the starting point and the ending point of each straight line segment, and d is the horizontal distance of each straight line segment.

[0036] The present invention also provides an electronic device, including:

[0037] At least one processor; and,

[0038] A memory communicatively connected to at least one of the processors; wherein,

[0039] The memory stores instructions executable by at least one of the processors, and the instructions are executed by at least one of the processors to enable at least one of the processors to execute the fuel consumption analysis method of the mining vehicle as described in any one of the above.

[0040] The present invention also provides a storage medium storing computer instructions, which are used to execute all steps of the fuel consumption analysis method for mining vehicles described in any one of the above when a computer executes the computer instructions.

[0041] The present invention also provides a system adopting the fuel consumption analysis method for mining vehicles described in any one of the above.

[0042] It includes: a fuel consumption sensor, a weighing sensor, and a positioning sensor.

[0043] The fuel consumption sensor is used to monitor the fuel consumption information during the driving of the mining vehicle, the weighing sensor is used to monitor whether the mining vehicle is in an empty load state or a heavy load state, and the positioning sensor is used to measure the speed information of the mining vehicle during driving and the road information of the mine.

[0044] The present invention solves the technical problem in the prior art that it is impossible to accurately obtain systematic, complete, and effective fuel consumption data of mining vehicles. By adopting the fuel consumption analysis method for mining vehicles proposed by the present invention, the influences of the speed, load condition of the mining vehicle, and the slope of the road on the fuel consumption are clearly and accurately understood, enabling the management of mining vehicles to be refined and accurate.

[0045] The present invention constructs a sample library capable of accurately identifying fuel consumption under different conditions, providing data support for more accurately analyzing the influence of different conditions on the fuel consumption of mining trucks, and by analyzing the influence law of different conditions on the fuel consumption of mining trucks, providing a scientific basis for supporting the optimization and decision-making of the road transportation link. Compared with the extensive management in the prior art, it can improve the refinement degree of production management in the open-pit mine transportation link and reduce the production cost of the transportation link. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a flowchart of the fuel consumption analysis method for mining vehicles provided by an embodiment of the present invention;

[0047] Figure 2 It is a schematic diagram of a fuel consumption curve provided by an embodiment of the present invention;

[0048] Figure 3 It is a schematic diagram of a fuel consumption curve provided by an embodiment of the present invention;

[0049] Figure 4 It is a schematic diagram of a sample library provided by an embodiment of the present invention;

[0050] Figure 5 It is a schematic diagram of the hardware structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] The present invention will be further described in detail below in conjunction with specific implementation embodiments and the accompanying drawings. It only intends to elaborate on the specific implementation embodiments of the present invention in detail and does not impose any limitations on the present invention. The protection scope of the present invention shall be subject to the claims.

[0052] Referring to Figure 1 , the present invention proposes a fuel consumption analysis method for vehicles used in mines, including:

[0053] Step S001, obtaining the status information of the vehicle and the road information of the mine, where the road information includes longitude, latitude, and elevation;

[0054] Step S002, dividing the road into multiple line segments according to the road information, removing the curved line segments among them, leaving the straight line segments, and storing the longitude, latitude, and elevation of the multiple straight line segments as the first sample library;

[0055] Step S003, calculating the slope of each straight line segment in the first sample library according to the elevation, and storing the slope of each straight line segment corresponding to the longitude, latitude, and elevation to form a second sample library;

[0056] Step S004, classifying the samples in the second sample library according to the status information of the vehicle and the slope to form multiple classification groups;

[0057] Step S005, within each classification group, analyzing the relationship between the status information of the vehicle, the slope, and the vehicle fuel consumption.

[0058] In step S001, the status information of the vehicle and the road information of the mine are obtained, where the road information includes longitude, latitude, and elevation;

[0059] Optionally, the status information of the vehicle includes fuel consumption, load, and driving speed, and the road information includes road longitude, latitude, and elevation. Optionally, the vehicle in this embodiment is a mining truck.

[0060] Specifically, a fuel consumption sensor is used to monitor the fuel consumption information during the driving process of the mining truck, a weighing sensor or a vibration sensor is used to monitor whether the mining truck is in an empty or loaded state, and a positioning sensor is used to measure the speed information of the mining truck during the driving process and the road information of the mine. For example, the road information of the mine includes the elevation, latitude, and longitude of the mine road.

[0061] In step S002, the road is divided into multiple line segments according to the road information, the curved line segments among them are removed, and the straight line segments are left, and the longitude, latitude, and elevation of the multiple straight line segments are stored as the first sample library;

[0062] Identify whether the road is a curve according to the road information of the mine. If it is a curve, the road information of this section is excluded, and finally the first sample library is formed.

[0063] It should be noted that since the research object is a single straight road, the curves of the actual road need to be segmented into straight line segments. However, in a three-dimensional coordinate system, the units of longitude, latitude, and elevation data are different, and large errors are likely to occur in the same coordinate system. Therefore, the xy plane composed of longitude and latitude is first segmented, and the road is segmented into straight line segments in the xy plane.

[0064] The mine road information in the first sample library is the road information of all straight line segments after removing the curves.

[0065] In step S003, according to the elevation, the slope of each straight line segment in the first sample library is calculated, and the slope of each straight line segment is stored corresponding to the longitude, latitude, and elevation to form a second sample library.

[0066] Calculate the slope of the road corresponding to the straight line segment in the first sample library, and store the slope of each straight line segment corresponding to the longitude, latitude, and elevation to form a second sample library.

[0067] Optionally, the elevation parameter in the road information is used to calculate the slope of each straight line segment in the first sample library.

[0068] Specifically, the second sample library is the stored data in the first sample library plus the slope parameter, thus forming a three-dimensional path of xyz.

[0069] In step S004, the samples in the second sample library are classified according to the vehicle status information and the slope to form multiple classification groups.

[0070] The vehicle status information such as speed, load, and fuel consumption; classify the samples in the second sample library. For example, in the case of the same slope and the same load, if the speed is different, then what kind of curve does the fuel consumption present at this time? The samples with the same slope and the same load are grouped into the same category. Or only the samples of mining trucks with the same slope are grouped into one category, and the classification conditions can be combined and matched in various ways.

[0071] In this way, the samples in the second sample library can form multiple classification groups.

[0072] In step S005, within each classification group, analyze the relationship between the vehicle status information, the slope, and the vehicle fuel consumption.

[0073] Analyze the influence of the samples in multiple classification groups on the fuel consumption of mining trucks.

[0074] Specifically, use data analysis software to draw a relationship curve between the samples in the sample group and the fuel consumption of mining trucks, and analyze the influence law of the samples on the fuel consumption of mining trucks, providing a scientific basis for supporting the optimization of the road transportation link and decision-making.

[0075] For example, it is divided into six gradients according to the slope of the road, and the samples in the second sample library are classified according to the six gradients to form six classification groups.

[0076] For example, the range of the slope of the road is ±10%, and it is divided into 6 levels according to a gradient of 2%, namely, -10 to -2, -2 to 2, 2 to 4, 4 to 6, 6 to 8, 8 to 10.

[0077] It can also be divided into a heavy-load state and an empty-load state according to the load of the mining truck. For example, a classification group of heavy load with a road slope of 2 to 4%, and a classification group of empty load with a road slope of 2 to 4%.

[0078] The samples in the second sample group can also be classified into multiple classification groups according to the driving speeds of different mining trucks. Specifically, the driving speed can be divided into 6 levels, and the samples in the second sample group are classified and summarized according to the 6 levels. For example, a classification group of an empty mining truck with a road slope of 2 to 4% and a driving speed of 5 to 10 km / h.

[0079] Finally, the samples in the second sample library are divided into 72 classification groups, and the samples in the 72 classification groups are analyzed to obtain the fuel consumption laws of mining trucks under different conditions, providing a scientific basis for supporting the optimization of the road transportation link and decision-making. Figure 4 An example of sample division.

[0080] Figure 2 It is the process of the fuel consumption increasing with the increase of the distance when the vehicle is in the heavy-load state and the speed is in the range of 15 to 20 km / h.

[0081] Figure 3 It is the process of the fuel consumption increasing with the increase of the distance when the vehicle is in the empty-load state and the speed is in the range of 15 to 20 km / h.

[0082] This embodiment solves the technical problem in the prior art that it is impossible to accurately obtain the fuel consumption data of mining vehicles that is systematic, complete, and effective. By using the fuel consumption analysis method of mining vehicles proposed in this embodiment, the influence of the speed, load, and slope of the road of mining vehicles on the fuel consumption has been clearly and accurately understood, enabling the management of mining vehicles to be refined and accurate.

[0083] This embodiment constructs a sample library that can accurately identify the fuel consumption under different conditions, provides data support for more accurate analysis of the influence of different conditions on the fuel consumption of mining trucks, and provides a scientific basis for supporting the optimization of the road transportation link and decision-making by analyzing the influence law of different conditions on the fuel consumption of mining trucks. Compared with the extensive management in the prior art, it can improve the refinement degree of production management in the open-pit mine transportation link and reduce the production cost of the transportation link.

[0084] In one embodiment, dividing the road into multiple line segments according to the road information and removing the curved line segments therein includes:

[0085] Calculating the curvature of each line segment based on the longitude and latitude of the two endpoints of the line segment. If the curvature is greater than the curvature threshold, it is determined that the line segment is a curved line segment.

[0086] Removing the curved line segments to make the fuel consumption situation reflected in the sample library more accurate.

[0087] In one embodiment, calculating the curvature of each line segment based on the longitude and latitude of the two endpoints of the line segment includes:

[0088] Sequentially selecting three adjacent data points P i , P i-1 , P i+1 in ascending order within the two endpoints of each line segment to form two vectors V i-1 and V i ;

[0089] V i-1 =(x i -x i-1 , y i -y i-1 )

[0090] V i =(x i+1 -x i , y i+1 -y i )

[0091] wherein, V i-1 and V i respectively represent the vectors of the line segments formed by connecting the three data points in pairs, x i , x i-1 , x i+1 respectively represent the latitudes of the three data points, and y i , y i-1 , y i+1 respectively represent the longitudes of the three data points;

[0092] Calculating the vector lengths according to the Euclidean distance formula;

[0093]

[0094] In the formula, |V i-1 | and |V i | respectively represent the moduli of the vectors V i-1 , V i ;

[0095] Calculate the cosine value between vectors according to the vector dot product formula, then calculate the angle between vectors according to the inverse cosine function, and convert it into the vector angle in degree system;

[0096]

[0097] In the formula, θ deg represents the vector angle in degree system, θ represents the vector angle in radian system, g is the value of gravitational acceleration, and π is the pi;

[0098] θ deg is the curvature of the line segment.

[0099] Calculating the curvature of the line segment by calculating the vector angle is more accurate.

[0100] Judge whether the calculated result of the curvature is greater than the second threshold. If it is greater than the second threshold, it is determined that the road is a curve, and the road information of this section is excluded. The second threshold is, for example, 0.2.

[0101] Specifically, after the above steps, the vector angle θ in degree value is finally obtained deg . Compare θ deg with the set second threshold. If the vector angle is greater than the second threshold, it is determined that this section of the road is a curve, and the road information of this section is excluded until the identification and exclusion in the two-dimensional plane of latitude and longitude of all road information are completed.

[0102] In one of the embodiments, before storing the longitude, latitude and elevation of multiple straight line segments into the first sample library, it further includes:

[0103] Filter and fill the road information of the straight line segment;

[0104] Filter and fill the status information of the vehicle.

[0105] The filtering process also includes the preprocessing of the status information and road information. The preprocessing includes:

[0106] Convert the unit of fuel consumption information of the mining truck and road information.

[0107] It should be noted that considering that there are many uncontrollable factors in on-site data collection and transmission, therefore, the collected raw data is transmitted to the server after unit conversion. Therefore, before data processing, the unit of the raw data needs to be converted into the unit format required for analysis. For example, convert the elevation unit into m, convert the fuel consumption unit into L / s, and convert the driving speed into m / s.

[0108] Exclude or fill the abnormal fuel consumption information and / or road information, that is, the filtering process.

[0109] Specifically, affected by the external environment, data missing may occur during the operation of the data acquisition module. For example, when a mining truck is driving normally, its elevation and speed change orderly. At the same time, the truck is on an uphill slope, but the fuel consumption is found to be 0. Therefore, it is determined that the data acquisition module fails to successfully collect data during this period.

[0110] Sometimes, it is also found that data missing may occasionally occur in elevation or longitude and latitude. For example, during the climbing process of a mining truck, the elevation data suddenly becomes 0. In response to such situations, the data of the two seconds before and after this time point are processed by mean filling.

[0111] Filter the fuel consumption information of the mining truck and the road information of the mine:

[0112] For example, speed data is easily affected by the environment. The reasons are that external dust, the vibration of the vehicle body itself, sound, wind speed, etc. will all affect it, and the data ranges of the vertical speed and the speeds in the two side directions of the vehicle body are small, and higher requirements for accuracy are needed. Therefore, it is necessary to clean the data and filter the speed data to improve the effectiveness and accuracy of the data.

[0113] Perform data interpolation processing on the road information.

[0114] Specifically, there are some missing values in the latitude, longitude, and elevation in the road information, resulting in the break of the three-dimensional road trajectory, which to a certain extent affects the rigor, scientificity, and accuracy of the construction of the sample group. The cubic spline interpolation method is used to fill the missing values, that is, the continuity conditions are obtained by using piecewise polynomials, and a set of piecewise cubic polynomials are constructed to approximate the data, so as to perform smooth interpolation between the data and make the road trajectory smoother.

[0115] Optionally, excluding or performing data filling processing on abnormal fuel consumption information and / or road information includes:

[0116] Judge whether the ratio of the number of abnormal fuel consumption information to the total number of fuel consumption information exceeds the first threshold. If it exceeds the first threshold, the data of the two seconds before and after the information collection point are filled with the average fuel consumption. The first threshold is 1 for example.

[0117] For example, the fuel consumption data shows a '0' value for about 40 minutes. By screening all the data of the current month, it is found that the number of days with this problem in each month does not exceed two days. The ratio of the abnormal fuel consumption data to all the data in this month is about 1%. The amount of abnormal value data is small, and the impact on the comprehensiveness of the sample group is small. Therefore, the corresponding data with abnormal values is removed. In other words, the first threshold is 1%. When the first threshold is less than 1%, the abnormal fuel consumption information is removed.

[0118] Determine whether the ratio of the number of abnormal road information to the total amount of road information data exceeds the first threshold. If it exceeds the first threshold, fill in the position mean value for the data two seconds before and after the information collection point.

[0119] For example, the elevation information shows a '0' value for about 10 minutes. By screening all the data of the current month, it is found that the number of days with this problem in each month does not exceed two days. The ratio of abnormal fuel consumption data to all data in this month is about 1%. The amount of abnormal data is small, and the impact on the comprehensiveness of the sample group is small. Therefore, the corresponding data with abnormal values is removed. In other words, the first threshold is 1%. When the first threshold is less than 1%, the abnormal elevation information is removed.

[0120] In some embodiments, interpolation processing is performed on the road information according to the speed of the mining truck.

[0121] For example, if the speed at this moment is 5 m / s, then 4 rows of uniformly and monotonically changing data are inserted at this moment.

[0122] By filtering and filling the road information of the straight section, and filtering and filling the vehicle status information, the data in the sample library becomes more reliable and continuous.

[0123] In one of the embodiments, the filtering and filling processing of the road information of the straight section includes:

[0124] Determine whether there is abnormal data in the three data of longitude, latitude, and elevation in the road information. If so, determine that the straight section is an abnormal section, and collect the road information of the two straight sections before and after the abnormal section to perform mean filling processing on the abnormal section.

[0125] By filtering and filling the road information of the straight section, and filtering and filling the vehicle status information, the data in the sample library becomes more reliable and continuous.

[0126] In one of the embodiments, the filtering and filling processing of the vehicle status information includes:

[0127] The vehicle status information includes: vehicle speed, load weight, and fuel consumption;

[0128] If any data among the vehicle speed, load weight, or fuel consumption is detected to be abnormal, the abnormal data is removed, and the mean filling method is used to fill the data at the abnormal data location.

[0129] By filtering and filling the road information of the straight section, and filtering and filling the vehicle status information, the data in the sample library becomes more reliable and continuous.

[0130] In one of the embodiments, calculating the slope of each straight line segment in the first sample library according to the elevation includes:

[0131]

[0132] In the formula, i is the slope of the straight line segment, △h is the elevation difference between the starting point and the ending point of each straight line segment, and d is the horizontal distance of each straight line segment.

[0133] By calculating the ground slope, the data of the straight line segment on the z-axis is filled.

[0134] Referring to Figure 5 , the present invention also provides a schematic diagram of the hardware structure of an electronic device, including:

[0135] At least one processor 301; and,

[0136] A memory 302 communicatively connected to at least one of the processors 301; wherein,

[0137] The memory 302 stores instructions executable by at least one processor. The instructions are executed by at least one processor so that at least one processor can execute the fuel consumption analysis method of the mining vehicle as described above.

[0138] Figure 5 Taking one processor 301 as an example in

[0139] The electronic device is preferably a controller of a vehicle. The electronic device may further include: an input device 303 and a display device 304.

[0140] The processor 301, the memory 302, the input device 303 and the display device 304 may be connected by a bus or other means. In the figure, the connection by a bus is taken as an example.

[0141] The memory 302, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs and modules, such as the program instructions / modules corresponding to the fuel consumption analysis method of the mining vehicle in the embodiments of the present application. For example, Figure 1 The method flow shown. The processor 301 executes various functional applications and data processing by running the non-volatile software programs, instructions and modules stored in the memory 302, that is, implements the fuel consumption analysis method of the mining vehicle in the above embodiments.

[0142] The memory 302 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the fuel consumption analysis method for mining vehicles, etc. In addition, the memory 302 may include high-speed random access memory and may also include non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the memory 302 optionally includes a memory remotely set relative to the processor 301, and these remote memories can be connected to the device executing the fuel consumption analysis method for mining vehicles through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0143] The input device 303 can receive input user clicks and generate signal inputs related to user settings and function controls of the fuel consumption analysis method for mining vehicles. The display device 304 may include display devices such as a display screen.

[0144] When one or more modules are stored in the memory 302 and run by one or more processors 301, the fuel consumption analysis method for mining vehicles in any of the above method embodiments is executed.

[0145] This embodiment constructs a sample library that can accurately identify fuel consumption under different conditions, provides data support for more accurate analysis of the impact of different conditions on the fuel consumption of mining trucks, and provides a scientific basis for supporting the optimization and decision-making of the road transportation link by analyzing the influence law of different conditions on the fuel consumption of mining trucks. Compared with the extensive management in the prior art, it can improve the refinement degree of production management in the open-pit mine transportation link and reduce the production cost of the transportation link.

[0146] An embodiment of the present invention provides a storage medium that stores computer instructions, and when the computer executes the computer instructions, it is used to execute all steps of the fuel consumption analysis method for mining vehicles as described above.

[0147] In the context of the present disclosure, the storage medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. The storage medium can be a machine-readable signal medium or a machine-readable storage medium. Optionally, the storage medium can be a non-transitory computer-readable storage medium. For example, the non-transitory computer-readable storage medium can be ROM, random access memory (Random Access Memory, RAM), compact disc read-only memory (Compact Disc ROM, CD-ROM), magnetic tape, floppy disk, and optical data storage devices, etc.

[0148] In this embodiment, a sample library capable of accurately identifying fuel consumption under different conditions is constructed, providing data support for more accurate analysis of the impact of different conditions on the fuel consumption of mining trucks. By analyzing the influence law of different conditions on the fuel consumption of mining trucks, it provides a scientific basis for supporting the optimization of the road transportation link and decision-making. Compared with the extensive management in the prior art, it can improve the refinement degree of production management in the open-pit mine transportation link and reduce the production cost of the transportation link.

[0149] The present invention also proposes an analysis system adopting the fuel consumption analysis method of the mining vehicle as described in any one of the above.

[0150] It includes: a fuel consumption sensor, a weighing sensor, and a positioning sensor;

[0151] The fuel consumption sensor is used to monitor the fuel consumption information during the driving of the mining vehicle, the weighing sensor is used to monitor whether the mining vehicle is in an empty load state or a heavy load state, and the positioning sensor is used to measure the speed information of the mining vehicle during driving and the road information of the mine.

[0152] In this embodiment, a sample library capable of accurately identifying fuel consumption under different conditions is constructed, providing data support for more accurate analysis of the impact of different conditions on the fuel consumption of mining trucks. By analyzing the influence law of different conditions on the fuel consumption of mining trucks, it provides a scientific basis for supporting the optimization of the road transportation link and decision-making. Compared with the extensive management in the prior art, it can improve the refinement degree of production management in the open-pit mine transportation link and reduce the production cost of the transportation link.

[0153] The above are only the principles and preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, based on the principles of the present invention, several other variations can also be made, which should also be regarded as the protection scope of the present invention.

Claims

1. A fuel consumption analysis method for a vehicle used in a mine, characterized in that, including: Obtain the status information of the vehicle and the road information of the mine, where the road information includes longitude, latitude, and elevation; Divide the road into multiple line segments according to the road information, remove the curved line segments among them, leave the straight line segments, and store the longitude, latitude, and elevation of the multiple straight line segments as the first sample library; Calculate the slope of each straight line segment in the first sample library according to the elevation, and store the slope of each straight line segment corresponding to the longitude, latitude, and elevation to form the second sample library; Classify the samples in the second sample library according to the status information of the vehicle and the slope to form multiple classification groups; Within each classification group, analyze the relationship between the status information of the vehicle, the slope, and the vehicle fuel consumption.

2. The fuel consumption analysis method for a mine vehicle according to claim 1, characterized in that The step of dividing the road into multiple line segments according to the road information and removing the curved line segments among them includes: Calculate the curvature of the line segment according to the longitude and latitude of the two endpoints of each line segment. If the curvature is greater than the curvature threshold, determine that the line segment is a curved line segment.

3. The fuel consumption analysis method for a mine vehicle according to claim 2, characterized in that The step of calculating the curvature of the line segment according to the longitude and latitude of the two endpoints of each line segment includes: Select three adjacent data points P in positive order within the two endpoints of each line segment i , P i-1 , P i+1 to form two vectors V i-1 and V i ; V i-1 =(x i -x i-1 ,y i -y i-1 ) V i = (x i+1 - x i , y i+1 - y i ) Among them, V i-1 and V i respectively represent the vectors of the line segments formed by connecting two by two of the three data points, x i , x i-1 , x i+1 respectively represent the latitudes of the three data points, y i , y i-1 , y i+1 respectively represent the longitudes of the three data points; Calculate the vector length according to the Euclidean distance formula; where, ∣V i-1 ∣ and ∣V i ∣ respectively represent the magnitudes of vectors V i-1 , V i ; Calculate the cosine value between vectors according to the vector dot product formula, then calculate the angle between vectors according to the inverse cosine function, and convert it into an angular vector angle; where θ deg represents the included angle of vectors in degree measure, θ represents the included angle of vectors in radian measure, g is the value of gravitational acceleration, and π is the ratio of a circle's circumference to its diameter; θ deg That is, the curvature of the line segment.

4. The fuel consumption analysis method for a mine vehicle according to claim 3, characterized in that Before storing the longitude, latitude, and elevation of the multiple straight line segments as the first sample library, it further includes: Perform filtering processing and filling processing on the road information of the straight line segment; Perform filtering processing and filling processing on the status information of the vehicle.

5. The fuel consumption analysis method for a mine vehicle according to claim 4, characterized in that The step of performing filtering processing and filling processing on the road information of the straight line segment includes: Judge whether there are abnormal data in the three data of longitude, latitude, and elevation in the road information. If so, determine that the straight line segment is an abnormal line segment, and collect the road information of the two straight line segments before and after the abnormal line segment to perform mean filling processing on the abnormal line segment.

6. The fuel consumption analysis method for a mine vehicle according to claim 4, characterized in that The step of performing filtering processing and filling processing on the status information of the vehicle includes: The status information of the vehicle includes: vehicle speed, load weight, and fuel consumption; If any abnormal data is detected in the vehicle speed, load weight, or fuel consumption, remove the abnormal data and perform data filling on the abnormal data using the mean filling method.

7. The fuel consumption analysis method for a mine vehicle according to any one of claims 1-6, characterized in that The step of calculating the slope of each straight line segment in the first sample library according to the elevation includes: In the formula, i is the slope of the straight line segment, △h is the elevation difference between the starting point and the ending point of each straight line segment, and d is the horizontal distance of each straight line segment.

8. An electronic device, characterized in that, including: At least one processor; and, A memory communicatively connected to at least one of the processors; wherein, The memory stores instructions executable by at least one of the processors, and the instructions are executed by at least one of the processors to enable at least one of the processors to execute the fuel consumption analysis method for a mining vehicle according to any one of claims 1 to 7.

9. A storage medium, characterized in that, The storage medium stores computer instructions, which are used to execute all steps of the fuel consumption analysis method for a mining vehicle according to any one of claims 1 to 7 when the computer executes the computer instructions.

10. A system adopting the fuel consumption analysis method of the mining vehicle according to any one of claims 1-7, Characterized in that Comprising: A fuel consumption sensor, a weighing sensor and a positioning sensor; The fuel consumption sensor is used to monitor the fuel consumption information during the driving of the mining vehicle, the weighing sensor is used to monitor whether the mining vehicle is in an empty load state or a heavy load state, and the positioning sensor is used to measure the speed information of the mining vehicle during driving and the road information of the mine.

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