Earthwork machine operation earthwork amount determination method, device, storage medium, and processor

Abstract

The present application relates to the technical field of engineering machinery, and discloses a method and device for determining earthwork quantity of earthmoving machinery, a storage medium and a processor. The method for determining earthwork quantity comprises: acquiring an electronic map of a working environment, a positioning signal of the earthmoving machinery and actuator movement information, wherein the electronic map of the working environment comprises position information of a range to be worked; determining a working device trajectory of the earthmoving machinery in the electronic map according to the positioning signal of the earthmoving machinery and the actuator movement information; and determining a worked earthwork quantity according to the working device trajectory and the position information of the range to be worked. The worked earthwork quantity of each earthmoving machinery can be counted, so that the overall project construction earthwork quantity can be accurately determined, which helps to determine the overall progress of the project.

Description

Technical Field

[0001] This invention relates to the field of engineering machinery technology, specifically to a method for determining the earthwork volume of earthmoving machinery, a device for determining the earthwork volume of earthmoving machinery, a machine-readable storage medium, and a processor. Background Technology

[0002] With rising labor and material costs and increasing demands for quality and schedule during project construction, intelligent construction, characterized by project decision-making driven by on-site equipment and personnel operational information, is becoming the future development direction. During construction, earthmoving machinery is responsible for completing 65-70% of the earthmoving tasks, and the statistical analysis of its operating conditions, earthmoving volume, fuel consumption, and other operational information is a crucial aspect of intelligent construction.

[0003] Currently, the overall project progress is determined by measuring the workload across the entire construction site. There are three main methods: first, sending personnel to inspect the site; second, using simple equipment to measure the workload; and third, periodically using drones to patrol and compare the results with electronic maps over a period of time to determine the overall earthwork volume. However, none of these methods can accurately calculate the earthwork volume of a single earthmoving machine. Summary of the Invention

[0004] The purpose of this invention is to provide a method for determining the earthwork volume of earthmoving machinery, a device for determining the earthwork volume of earthmoving machinery, a machine-readable storage medium, and a processor. The method for determining the earthwork volume of earthmoving machinery of this invention can calculate the earthwork volume already worked by a single earthmoving machine, which helps in determining the overall progress of a project.

[0005] To achieve the above objectives, the first aspect of this application provides a method for determining the volume of earthwork in earthmoving machinery operations, comprising:

[0006] The system acquires an electronic map of the work environment, the positioning signals of the earthmoving machinery, and the motion information of the actuators. The electronic map of the work environment includes the location information of the work area.

[0007] Based on the positioning signal and actuator motion information of the earthmoving machinery, the trajectory of the working device of the earthmoving machinery in the electronic map is determined;

[0008] Based on the trajectory of the working device and the location information of the area to be worked, the amount of earthwork already worked is determined.

[0009] In this embodiment of the application, determining the amount of earthwork already done based on the location information of the working device trajectory and the work area includes:

[0010] Based on the location information of the work area to be worked, the work area in the electronic map of the work environment is divided into multiple cubes;

[0011] The cube state of each cube is determined, and the cube state indicates the intersection state between the cube and the trajectory of the working device;

[0012] Based on the state and volume of each cube, the amount of earthwork already completed is obtained.

[0013] In this embodiment of the application, it also includes:

[0014] Get the number of earthwork excavation cycles;

[0015] The amount of earthwork excavation work per cycle is calculated based on the amount of earthwork already excavated and the number of earthwork excavation cycles.

[0016] In this embodiment of the application, obtaining the number of earthwork excavation cycles includes:

[0017] Obtain the results of working condition stage identification and working condition type identification;

[0018] Based on the identification results of the working condition stage and the identification results of the working condition type, statistics are performed according to the preset working condition information statistical conditions to obtain the number of earthwork excavation cycles.

[0019] In this embodiment of the application, it also includes:

[0020] Obtain the total operation time for earthwork excavation;

[0021] The earthwork operation efficiency is calculated based on the amount of earthwork already completed and the total operation time of earthwork excavation.

[0022] In this embodiment of the application, the location information of the area to be worked on includes terrain elevation and slope information;

[0023] The acquisition of the electronic map of the working environment includes:

[0024] Obtain terrain elevation and slope information within the area to be worked on;

[0025] An electronic map of the work environment is generated based on the terrain elevation and slope information within the work area.

[0026] In this embodiment of the application, determining the trajectory of the working device of the earthmoving machinery in the electronic map based on the positioning signal and actuator motion information of the earthmoving machinery includes:

[0027] The pose of the earthmoving machinery's base point in the electronic map is determined based on the positioning signal of the earthmoving machinery. The motion trajectory of the working device in the base coordinate system is determined based on the motion information of the actuator and the kinematic model of the earthmoving machinery. The base coordinate system has the base point as the origin of the coordinate system.

[0028] Based on the position of the earthmoving machinery's base point on the electronic map and the movement trajectory of the working device in the base coordinate system, the working device trajectory of the earthmoving machinery's working device on the electronic map is determined.

[0029] The second aspect of this application provides a device for determining the amount of earthwork done by earthmoving machinery, comprising:

[0030] The acquisition module is used to acquire an electronic map of the working environment, the positioning signals of the earthmoving machinery, and the motion information of the actuators. The electronic map of the working environment includes the location information of the area to be worked.

[0031] The first determining module is used to determine the trajectory of the working device of the earthmoving machinery in the electronic map based on the positioning signal and the motion information of the actuator of the earthmoving machinery.

[0032] The second determining module is used to determine the amount of earthwork already done based on the trajectory of the working device and the location information of the work area to be worked.

[0033] A third aspect of this application provides a processor configured to perform the above-described method for determining the volume of earthwork in earthmoving machinery operations.

[0034] A fourth aspect of this application provides a machine-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the above-described method for determining the volume of earthwork in earthmoving machinery operations.

[0035] The above technical solution acquires the positioning signals and actuator motion information of earthmoving machinery; determines the location of the earthmoving machinery in an electronic map of the work environment; and obtains the working device trajectory of the earthmoving machinery based on the actuator motion information. The working device trajectory of the earthmoving machinery is the trajectory formed by the change of the actuator motion information of each earthmoving machinery over time. Based on the electronic map of the work environment and the working device trajectory of the earthmoving machinery, the amount of earthwork already completed is determined. Since the working device trajectory of the earthmoving machinery can be the trajectory of each earthmoving machinery during operation, the amount of earthwork completed by each earthmoving machinery can be accurately counted in the spatial dimension, thereby accurately determining the overall project construction earthwork volume and helping to determine the overall project progress. By determining the earthwork volume based on the electronic map and motion trajectory, the earthwork volume of a single earthmoving machine can be obtained more conveniently, and it helps to further evaluate the efficiency of a single earthmoving machine, saving manpower and material resources.

[0036] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0037] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the following detailed description to explain the invention, but do not constitute a limitation thereof. In the drawings:

[0038] Figure 1 The illustration shows a flowchart of a method for determining the volume of earthwork in earthmoving machinery operations according to an embodiment of this application;

[0039] Figure 2 This illustration schematically shows a flowchart of a multi-level, multi-dimensional hydraulic excavator operation information statistics system according to an embodiment of this application.

[0040] Figure 3 A simplified structural diagram of a backhoe excavator according to an embodiment of this application is shown schematically.

[0041] Figure 4 The DH coordinate system of an excavator working device according to an embodiment of this application is schematically shown;

[0042] Figure 5 This schematic diagram illustrates a structural block diagram of an earthmoving machinery operation earthwork volume determination device according to an embodiment of this application;

[0043] Figure 6 The diagram illustrates the internal structure of a computer device according to an embodiment of this application.

[0044] Explanation of reference numerals in the attached figures

[0045] 1-Unloading; 2-Loading; 3-Boom; 4-Boom hydraulic cylinder; 5-Stick hydraulic cylinder; 6-Stick; 7-Bucket hydraulic cylinder; 8-Rocker arm; 9-Connecting rod; 10-Bucket; 410-Acquisition module; 420-First identification module; 430-Second identification module; A01-Processor; A02-Network interface; A03-Internal memory; A04-Display screen; A05-Input device; A06-Non-volatile storage medium; B01-Operating system; B02-Computer program. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0047] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0048] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0049] Please refer to Figure 1 , Figure 1 The illustration shows a flowchart of a method for determining the volume of earthwork in earthmoving machinery operations according to an embodiment of this application.

[0050] like Figure 1As shown in one embodiment of this application, a method for determining the earthwork volume of earthmoving machinery is provided. It should be noted that this method can be applied to earthmoving machinery such as excavators, shovelers, pushers, or leveling soil and gravel. For ease of explanation, this embodiment primarily uses an excavator as an example. The method for determining the earthwork volume of earthmoving machinery includes the following steps:

[0051] Step 210: Obtain the electronic map of the working environment, the positioning signal of the earthmoving machinery, and the motion information of the actuator. The electronic map of the working environment includes the location information of the area to be worked.

[0052] Step 220: Based on the positioning signal and actuator motion information of the earthmoving machinery, determine the working device trajectory of the earthmoving machinery in the electronic map;

[0053] Step 230: Determine the amount of earthwork already done based on the trajectory of the working device and the location information of the work area to be worked.

[0054] The above technical solution involves acquiring the positioning signals and actuator motion information of earthmoving machinery; determining the location of the earthmoving machinery in an electronic map of the work environment; and obtaining the working device trajectory of the earthmoving machinery based on the actuator motion information. The working device trajectory of the earthmoving machinery is the trajectory formed by the change of the actuator motion information of each earthmoving machinery over time. Based on the electronic map of the work environment and the working device trajectory of the earthmoving machinery, the amount of earthwork already completed can be determined. Since the working device trajectory of the earthmoving machinery can be the working device trajectory of each earthmoving machinery during operation, the amount of earthwork already completed by each earthmoving machinery can be accurately counted in the spatial dimension, thereby accurately determining the total earthwork volume of the project and helping to determine the overall project progress.

[0055] By determining the volume of earthwork based on electronic maps and movement trajectories, it is easier to obtain the earthwork volume of a single earthmoving machine, and it also helps to further evaluate the efficiency of a single earthmoving machine, saving manpower and material resources.

[0056] In step 210, an electronic map of the working environment is acquired. This electronic map includes the location information of the area to be worked on. The electronic map can be constructed by other equipment and sent to the earthmoving machinery, or it can be constructed by the earthmoving machinery itself. The location information can be 3D terrain information. Taking an excavator as an example, the methods for acquiring the 3D terrain information of the excavator's working area include one or more combinations of manual surveying, UAV-borne LiDAR technology, machine vision technology, and millimeter-wave radar technology. The UAV-borne LiDAR completes the terrain point cloud model within the excavator's working area through the flight of the aircraft and the scanning of laser pulses. The vision sensors are installed at the front and rear of the excavator's cab roof, as well as on the left and right sides of the vehicle body. The millimeter-wave radar is installed at the front, rear, left, and right sides of the undercarriage. All of the above technologies are ultimately used to acquire the terrain elevation and slope information within the excavator's working area, i.e., to acquire the terrain elevation and slope information within the area to be worked on, and to form an electronic map of the working environment based on the terrain elevation and slope information within the area to be worked on.

[0057] In this embodiment, taking an excavator as an example of earthmoving machinery, the excavator positioning signal refers to the absolute position of the upper vehicle's rotation center, which can be obtained through a single differential GPS high-precision positioning system, an inertial navigation unit, or a combination of multiple methods.

[0058] In this embodiment, taking an excavator as an example of earthmoving machinery, obtaining the motion information of the actuator refers to acquiring the drive space or joint space coordinates of the actuator by installing displacement, tilt, or position sensors on the actuator structure, and finally converting them into the position space coordinates of the bucket tooth tip using the excavator's kinematic model. The actuator includes multiple joints, which are sequentially hinged and connected by hydraulic cylinders. By acquiring the extension of each hydraulic cylinder and the included angle between adjacent joints, and combining this with the kinematic model, the coordinates of the bucket tooth tip in a coordinate system with the installation position of the positioning system as the origin are obtained, which is the motion information of the actuator.

[0059] Please refer to Figure 3 and Figure 4 , Figure 3 A simplified structural diagram of a backhoe excavator according to an embodiment of this application is shown schematically. Figure 4The diagram schematically illustrates the DH coordinate system of an excavator working device according to an embodiment of this application. When the earthmoving machinery is an excavator, the excavator includes a lower carriage 1, an upper carriage 2, a boom 3, a boom hydraulic cylinder 4, a stick hydraulic cylinder 5, a stick 6, a bucket hydraulic cylinder 7, a rocker arm 8, a connecting rod 9, and a bucket 10. Coordinate systems are established for the lower carriage 1, upper carriage 2, boom 3, stick 6, and bucket 10, respectively, denoted as O0, O1, O2, O3, and O4, where O0 is the base coordinate system, O1 is the upper carriage coordinate system, O2 is the boom coordinate system, O3 is the stick coordinate system, and O4 is the bucket coordinate system. The positional relationship between adjacent coordinate systems is described using offset, rotation angle, stick length, and twist angle, defined as follows:

[0060] Offset s i Along z i Axis from x i axis to x j The distance along the axis is defined relative to z. i A direction consistent with the positive axis is considered positive.

[0061] Angle θ i Along z i Axis from x i axis to x j The rotation angle of the axis is defined as positive in the counterclockwise direction, corresponding to the joint space;

[0062] Rod length h i Along x j Axis from z i axis to z j The distance along the axis is defined relative to x. j A direction consistent with the positive axis is considered positive.

[0063] Twist angle α i Along x j Axis from z i axis to z j The rotation angle of the axis is defined as positive in the counterclockwise direction.

[0064] The excavator's drive space consists of the swing motor rotation angle L0, the boom hydraulic cylinder length L1, the stick hydraulic cylinder length L2, and the bucket hydraulic cylinder length L3, represented as [L0, L1, L2, L3]. T ;

[0065] The excavator joint space is composed of the angle θ0 between the lower carriage 1 and the upper carriage 2, the angle θ1 between the upper carriage 2 and the boom 3, the angle θ2 between the boom 3 and the stick 6, and the angle θ3 between the stick 6 and the bucket 10, and is represented as [θ0, θ1, θ2, θ3]. T ;

[0066] Excavator pose space: Composed of the position and pose angle of the bucket 10 in the base coordinate system (the angle between the stopping surface and the line connecting the hinge point of the bucket 10 and the tip of the bucket 10 tooth), denoted as [x, y, z, ζ]. T .

[0067] The joint space coordinates of an excavator can be obtained by using the formula to convert the drive space into the joint space, and then the formula to convert the joint space into the pose space can be used to obtain the pose space coordinates.

[0068] The formula for converting the drive space into the joint space is as follows:

[0069]

[0070] The formula for converting joint space to pose space is:

[0071]

[0072] Where ∠XYZ represents the angle between lines XY and YZ, L XY The distance between hinge points X and Y; similar variables are the angle between two lines or the distance between two hinge points, which can be referred to... Figure 2 The following parameters are used for identification: α is the angle between the line connecting hinge points A and F and the horizontal plane; θ0 is the angle between the lower vehicle 1 and the upper vehicle 2; θ1 is the angle between the upper vehicle 2 and the boom 3; θ2 is the angle between the boom 3 and the stick 6; θ3 is the angle between the stick 6 and the bucket 10; h1 is the length of the boom 3AB; h2 is the length of the stick 6BG; h3 is the length of the bucket 10GJ; the pose space coordinates are represented as: [x,y,z,ζ] T Where x, y, z are the positions of the actuator in the base coordinate system (e.g., the position of bucket 10 in the base coordinate system); ζ is the pose angle, that is, the angle of rotation from the stopping surface to the line connecting the hinge point of bucket 10 and the tip of the bucket 10 tooth.

[0073] Step 220: Based on the positioning signal and actuator motion information of the earthmoving machinery, determine the trajectory of the working device of the earthmoving machinery in the electronic map; wherein, the trajectory of the working device is the trajectory formed by the change of the actuator motion information of the earthmoving machinery over time. In this embodiment, taking an excavator as an example, after obtaining the actuator motion information, combined with the position and pose of the excavator body in the electronic map, the coordinates of the bucket tooth tip are converted into the electronic map, thereby obtaining the trajectory of the working device of the actuator in the electronic map. Specifically, this includes the following steps:

[0074] First, the pose of the earthmoving machinery's base point in the electronic map is determined based on the positioning signal of the earthmoving machinery. Then, the motion trajectory of the working device in the base coordinate system is determined based on the motion information of the actuator and the kinematic model of the earthmoving machinery, with the base point as the origin of the base coordinate system.

[0075] Then, based on the position of the earthmoving machinery's base point on the electronic map and the movement trajectory of the working device in the base coordinate system, the working device trajectory of the earthmoving machinery's working device on the electronic map is determined.

[0076] In this embodiment, the motion information of the actuator changes over time. Taking an excavator as an example, this is reflected in the change of the position of the tip of the bucket 10 teeth over time, thus obtaining a trajectory. This trajectory is used as the working device trajectory of the earthmoving machinery. Each point on the working device trajectory is the positional spatial coordinate of the tip of the bucket 10 teeth at each point in time.

[0077] Step 230: Determine the amount of earthwork already completed based on the location information of the working device trajectory and the work area to be completed. In this embodiment, the amount of earthwork already completed can be obtained by calculating the intersection of the electronic map of the work environment and the working device trajectory of the earthmoving machinery, specifically through the following steps:

[0078] The first step is to divide the work area in the electronic map of the work environment into multiple cubes based on the location information of the work area to be worked. In this embodiment, the work area can be divided into cubes of uniform size, or it can be divided into cubes of different sizes for different areas of the work environment.

[0079] The second step is to determine the cube state of each cube, whereby the cube state indicates the intersection state between the cube and the trajectory of the working device; that is, to determine the intersection state between each cube and the trajectory of the working device to obtain multiple cube states.

[0080] In this embodiment, the state of each cube can be determined based on the trajectory of the working device and a preset cube state determination formula. In this embodiment, the pose space coordinates in the trajectory of the working device are substituted into the cube state determination formula to obtain the state of each cube. The cube state determination formula is as follows:

[0081]

[0082] Where: M j Let M be the state of a certain cube. j =1 indicates that it has been excavated, M j =0 indicates no excavation; V iThe spatial range defined for the cube; [x,y,z,ζ] are the pose space coordinates in the trajectory of the working device, and j is the cube number.

[0083] The third step is to obtain the amount of earthwork already completed based on the state and volume of each cube. In this embodiment, the state and volume of each cube can be substituted into the following formula:

[0084] V=V0×∑M j ;

[0085] In the formula: V0 is the volume of each cube, M j Let V represent the state of each cube, and V represent the amount of earthwork already completed.

[0086] In the above implementation process, the following steps are taken: First, an electronic map of the work environment, the positioning signal of the earthmoving machinery, and the motion information of its actuators are acquired. The electronic map includes the location information of the work area. Then, based on the positioning signal of the earthmoving machinery, its position is determined on the electronic map. Finally, based on the motion information of its actuators, the trajectory of the earthmoving machinery's working device is obtained. Finally, based on the state and volume of each cube, the amount of earthwork already completed is calculated. By statistically analyzing the amount of earthwork completed by the earthmoving machinery in a spatial dimension, and determining the earthwork volume based on the intersection of the electronic map and the motion trajectory, the earthwork volume of a single earthmoving machine can be obtained more conveniently, facilitating the evaluation of the efficiency of a single earthmoving machine.

[0087] As shown above, when dividing the work environment into cubes, different areas can be divided into cubes of different sizes. In some examples, areas with higher flatness can be divided into larger cubes, and areas with lower flatness can be divided into smaller cubes. This reduces the computational workload while ensuring the accuracy of the earthwork volume statistics. The flatness evaluation parameters can be the maximum elevation difference or elevation variance of the aforementioned areas, and the level of flatness can be classified in conjunction with preset thresholds. Specific examples are not provided here.

[0088] After obtaining the volume of earthwork already excavated, the volume of a single earthwork excavation operation can be further calculated, which includes the following steps:

[0089] First, the number of earthwork excavation cycles is obtained. In this embodiment, the number of earthwork excavation cycles can be obtained by on-site staff in real time, or it can be obtained based on the results of working condition identification.

[0090] Among these methods, using statistics based on working condition identification results to determine the number of earthwork excavation cycles is more accurate. The statistical process includes:

[0091] The first step is to obtain the results of the working condition stage identification and the working condition type identification;

[0092] The second step is to perform statistical analysis based on the working condition stage identification results and the working condition type identification results, according to the preset working condition information statistical conditions, to obtain the working condition information statistical results, which include at least the number of earthwork excavation cycles.

[0093] In this embodiment, the statistical results of the working condition information include the statistics of the number of complete cycles for each working condition stage and each working condition type. The statistical process can be carried out using working condition information statistical conditions. In specific implementation, the above statistics can be completed using the IF-AND-THEN conditional form, matching the working condition stage and working condition type identification results with the IF part one by one. If the IF part meets a certain condition, the THEN part is executed to change the statistical result; otherwise, the original statistical result remains unchanged.

[0094] When the earthmoving machinery is an excavator, the above IF-AND-THEN conditions may include:

[0095] Condition 1: If the result of the current operating condition stage is different from the result of the previous operating condition stage, then the loop count of the corresponding operating condition stage result at the previous time will be increased by 1.

[0096] Condition 2: IF the previous working condition stage result was any of the following: empty bucket return, bucket and stick retraction, boom lowering and stick outward swing, breaking point adjustment, vehicle travel, or idle; AND the current working condition stage result is different from the previous working condition stage result; THEN the working condition type result corresponding to the previous working condition stage structure will have its loop count increased by 1. It should be noted that the above conditions can be set separately for different working condition types.

[0097] By using statistical conditions based on the results of working condition stage identification and working condition type identification, working condition information can be quickly and effectively collected, which helps project managers make reasonable project decisions.

[0098] Then, based on the already completed earthwork volume and the number of earthwork excavation cycles, the volume of a single earthwork excavation operation is calculated. In this embodiment, the already completed earthwork volume and the number of earthwork excavation cycles can be substituted into the following formula:

[0099]

[0100] In the formula, V represents the volume of earthwork already done, V represents the volume of earthwork excavation in a single operation, and N1 represents the number of earthwork excavation cycles. Earthwork excavation has five working stages, and completing one of the five working stages counts as one cycle.

[0101] Accordingly, after obtaining the volume of earthwork already completed, the spatial efficiency of earthwork operations can be further analyzed, specifically including the following steps:

[0102] First, the total operation time of earthwork excavation is obtained. In this embodiment, the total operation time of earthwork excavation is the time that earthwork machinery spends excavating. This time can be obtained by on-site staff in real time or by statistically analyzing the operation information of earthwork machinery in the time dimension.

[0103] Then, based on the amount of earthwork already completed and the total excavation time, the earthwork operation efficiency is calculated. In this embodiment, the amount of earthwork already completed and the total excavation time can be substituted into the following formula:

[0104]

[0105] In the formula, η is the earthwork operation efficiency, V is the earthwork volume already completed, and T21 is the total earthwork excavation operation time.

[0106] In the above process, the earthwork operation efficiency is calculated based on the amount of earthwork already done and the total operation time of earthwork excavation, thereby realizing the evaluation of the operation efficiency of a single earthwork machine, which is conducive to project managers making reasonable project decisions.

[0107] In some embodiments, the operation information of earthmoving machinery can also be statistically analyzed in the time dimension, including the following steps:

[0108] The first step is to obtain the results of the working condition stage identification and the working condition type identification;

[0109] The second step is to perform statistics based on the working condition stage identification results and the working condition type identification results, according to the preset working condition information statistical conditions, to obtain the working condition information statistical results.

[0110] The third step is to obtain fuel consumption rate information. In this embodiment, the fuel consumption rate information can be CAN bus fuel consumption rate information, which can be obtained from the control module of the earthmoving machinery.

[0111] The fourth step involves statistically analyzing the earthmoving machinery's operational information over time based on the operational stage identification results, operational type identification results, operational information statistics results, and fuel consumption rate information. This yields the first operational information statistics result, which includes the total operational time for earthmoving excavation.

[0112] In this embodiment, the time-dimensional operation information statistics include the total duration and time percentage of each operating condition stage, the average fuel consumption rate and fuel consumption rate percentage of each operating condition stage, the total duration of each operating condition type, the duration and time percentage of a single cycle, and the average fuel consumption rate and fuel consumption rate percentage of each operating condition type.

[0113] When the earthmoving machinery is an excavator, the above-mentioned time-dimensional operation information statistics can be calculated using the following formula:

[0114] T1 i =M1 i ×Δt; T2 i =M2 i ×Δt;

[0115] Where Δt is the time interval for identifying the operating condition stage; M1 i T1 represents the number of times each operating condition stage appears in the operating condition stage identification results. i η1 represents the total duration of each operating condition phase. i The time percentage for each operating condition stage; o1 i O1 represents the instantaneous fuel consumption rate under various operating conditions. i η2 represents the average fuel consumption rate under various operating conditions. i M1 represents the percentage of average fuel consumption rate under various operating conditions. i T1 i η1 i o1 i O1 i η2 i In the diagram, i = 1, 2, ..., 13, representing the stages of excavation preparation, excavation, hoisting rotation, unloading, empty bucket return, bucket and stick outward swing, bucket and stick retraction, boom lifting stick retraction, boom lowering stick outward swing, crushing impact, crushing point adjustment, vehicle travel, and idle operation, respectively; M2 i N represents the number of times each operating condition type appears in the operating condition type identification results. i This represents the number of cycles for each operating condition type, and the statistical results of multi-level operating condition information; T2 i The total duration for each operating condition type; t i η3 represents the duration of a single cycle for each operating condition type. i The percentage of single-cycle duration for each operating condition type; o2 i Instantaneous fuel consumption rate for each operating condition; O2 i η4 represents the average fuel consumption rate for each operating condition. i The percentage of average fuel consumption rate for each operating condition; M2 i N i T2i t i η3 i o2 i O2 i η4 i In the inode, i = 1, 2, ..., 6, representing earthwork excavation preparation, leveling, slope repair, crushing, vehicle travel, and idle operation, respectively.

[0116] In the above implementation process, by identifying the working condition stage and type, as well as the fuel consumption rate information of the CAN bus, multi-level excavator working condition information statistics and time-dimensional operation information statistics are completed. The statistics cover information on working conditions and energy consumption, revealing detailed information on the working condition type and stage during excavator operation, which is conducive to project managers making reasonable project decisions.

[0117] In the above implementation process, by statistically analyzing the trajectory of the working device, the working condition information, and the first operational information, the operational information of the earthmoving machinery is statistically analyzed in the spatial dimension to obtain the amount of earthwork already completed, earthmoving efficiency, and the amount of earthwork excavation per cycle, thereby achieving an evaluation of the operational efficiency of a single earthmoving machine. This enables the statistical analysis of operational information from a spatial dimension, providing a data foundation for host machine health evaluation and intelligent construction. Simultaneously, it allows for the acquisition of statistical information on earthmoving volume and the operational efficiency of a single machine, which is beneficial for project managers to make reasonable project decisions.

[0118] The process described above, which uses statistical analysis based on working condition identification results to determine the number of earthwork excavation cycles, involves obtaining working condition stage identification results and working condition type identification results. In this embodiment, to obtain more accurate working condition stage identification results and working condition type identification results, these results can be obtained through steps 310-330.

[0119] Step 310: Obtain the main pump pressure signal of the earthmoving machinery; In this embodiment, the main pump pressure signal of the earthmoving machinery can be acquired by a pressure sensor on the earthmoving machinery. The main pump pressure signal can be the main pump pressure data acquired at the current moment, or it can be the main pump pressure data within a certain time range. For example, when the earthmoving machinery is an excavator, the pressure sensor is used to acquire the main pump pressure signal of the excavator within 0.5 seconds of the current moment. For different types of earthmoving machinery, the main pump pressure signal can be one or more sets. For example, for small excavators, there is only one set of main pump pressure signals; for large and medium-sized excavators, there are two sets of main pump pressure signals.

[0120] Step 320: Based on the main pump pressure signal, the working condition stage of the earthmoving machinery is identified using a preset working condition stage identification model to obtain the working condition stage identification result.

[0121] When the earthmoving machinery is an excavator, the excavator's operating conditions can include earthmoving, leveling, slope trimming, breaking, vehicle travel, and idling. Specifically, the earthmoving operating condition includes five stages: excavation preparation, excavation, lifting and slewing, unloading, and empty bucket return. The leveling operating condition includes two stages: bucket and stick outward swing and bucket and stick inward retraction. The slope trimming operating condition includes two stages: boom lifting and stick inward retraction and boom lowering and stick outward swing. The breaking operating condition includes two stages: breaking impact and breaking point adjustment. Vehicle travel and idling are both independent operating condition types and stages, and will not be further subdivided. The operating condition types and stages for other earthmoving machinery can be determined according to the actual situation, and will not be elaborated here.

[0122] Prior to step 320, a working condition stage identification model can be pre-built and trained using a neural network. This model can be pre-installed within the earthmoving machinery. In some embodiments, the construction process of the pre-installed working condition stage identification model includes the following steps:

[0123] First, first sample data is acquired. This first sample data includes main pump pressure data for each working condition stage under each working condition type, and the corresponding working condition stage label for the main pump pressure data. In this embodiment, the first sample data contains multiple sets of data, each set including a main pump pressure data and the corresponding working condition stage label. The division of the aforementioned working condition stages can be based on the main pump pressure waveform corresponding to each working condition stage as the working condition stage division marker. For example, when the earthmoving machinery is an excavator, since the main pump pressure signal is different under different working condition stages, the main pump pressure waveform corresponding to each working condition stage under different working condition types can be used as the working condition stage division marker to segment the excavator's work cycle. The segmentation result is the corresponding working condition stage. Taking the earthmoving excavation working condition type as an example, after the work cycle is segmented, there are five working condition stages: excavation preparation, excavation, hoisting and rotation, unloading, and empty bucket return. It should be noted that the main pump pressure waveform here refers to the main pump pressure signal.

[0124] Then, the main pump pressure data for each operating condition stage are input into the first neural network to obtain the predicted operating condition stage.

[0125] Then, the predicted operating condition stage is compared with the operating condition stage label corresponding to the main pump pressure data in the first sample data to obtain the operating condition stage comparison result.

[0126] Finally, the parameters of the first neural network are adjusted based on the comparison results of the working condition stages to obtain the working condition stage recognition model.

[0127] In this embodiment, the first neural network can be a linear neural network, a feedback neural network, or a multilayer feedforward neural network (BP neural network), among which the BP neural network has strong nonlinear mapping ability and flexible network structure. The number of intermediate layers and the number of neurons in each layer can be arbitrarily set according to specific circumstances, and it has strong generalization ability and fault tolerance. Using the BP neural network can obtain a more stable and reliable working condition stage recognition model. When the earthmoving machinery is an excavator, a working condition stage recognition model for the excavator can be established based on the BP neural network. The main pump pressure data of each working condition stage under each working condition type is used as the model input to obtain the predicted working condition stage. The predicted working condition stage and the working condition stage label corresponding to the main pump pressure data are input into a preset loss function to obtain the corresponding loss value. The model parameters are adjusted according to the loss value so that the predicted working condition stage is the same as the working condition stage label corresponding to the main pump pressure data, so that the model has a sufficient recognition accuracy. Finally, the working condition stage recognition model is trained.

[0128] Step 330: Based on the working condition stage identification results, the working condition type of the earthmoving machinery is identified using a preset working condition type identification model to obtain the working condition type identification results.

[0129] Correspondingly, the working condition type identification model can also be pre-built. The construction process of the pre-built working condition type identification model includes the following steps:

[0130] First, second sample data is acquired. This second sample data includes feature data for each working condition stage under each working condition type, and the working condition type label corresponding to the feature data. In this embodiment, the second sample data contains multiple sets of data, each set including feature data for a working condition stage and the working condition type label corresponding to the feature data. The division of the above-mentioned working condition types can be based on the waveform features corresponding to each working condition stage as the working condition type division mark. For example, when the earthmoving machinery is an excavator, the waveform features of the corresponding working condition stage under the working condition type are used as the identification mark of the working condition type to divide the excavator's working type. The division result is the working condition type corresponding to the current moment. Taking the earthmoving excavation working condition type as an example, if the working condition stage at the current moment is any one of the stages of excavation preparation, excavation, hoisting rotation, unloading, and empty bucket return, the working condition type at the current moment is earthmoving excavation.

[0131] Then, the feature data of each working condition stage are input into the second neural network to obtain the predicted working condition type;

[0132] Then, the predicted working condition type is compared with the working condition type label corresponding to the feature data in the second sample data to obtain the working condition type comparison result;

[0133] Finally, the parameters of the second neural network are adjusted based on the comparison results of the working condition types to obtain the working condition type recognition model.

[0134] In this embodiment, the second neural network can be a linear neural network, a feedback neural network, or a multilayer feedforward neural network (BP neural network), among which the BP neural network has strong nonlinear mapping ability and a flexible network structure. The number of intermediate layers and the number of neurons in each layer can be arbitrarily set according to specific circumstances, and it has strong generalization ability and fault tolerance. Using a BP neural network can obtain a more stable and reliable working condition type recognition model. When the earthmoving machinery is an excavator, an excavator working condition type recognition model can be established based on a BP neural network. The waveform features of the working condition stages under all working condition types are used as model input to obtain the predicted working condition type. The predicted working condition type and the working condition type label corresponding to the feature data are input into a preset loss function to obtain the corresponding loss value. The model parameters are adjusted according to the loss value to make the predicted working condition type the same as the working condition type label corresponding to the feature data, so that the model has a sufficient recognition accuracy. Finally, the working condition type recognition model is trained.

[0135] In the above implementation process, the use of neural network training to obtain the working condition stage identification model and the working condition type identification model helps to improve the reliability of the working condition identification results. Choosing a BP neural network model can reduce the cost of working condition identification and makes it easier to integrate into construction machinery.

[0136] When identifying the working stages of the earthmoving machinery using a preset working stage identification model, the main pump pressure signal can be input into the preset working stage identification model to obtain the working stage identification result. To make the obtained working stage identification result more accurate, main pump pressure data within a certain time range can be used as the data source for working stage identification. That is, the main pump pressure signal includes multiple main pump pressure data points within a first preset time range from the current time; for example, in the above example, the main pump pressure signal within 0.5 seconds of the current time.

[0137] In one embodiment, the working condition stage results can be obtained in real time. The step of identifying the working condition stage of the earthmoving machinery based on the main pump pressure signal using a preset working condition stage identification model to obtain the working condition stage identification result includes the following steps:

[0138] Step A1: Feature extraction is performed on the main pump pressure signal to obtain a feature vector. In this embodiment, the feature extraction includes using mean filtering to reduce noise and transient interference in the main pump pressure signal; then, based on the computing power of the host controller, the frequency of the main pump pressure signal is reduced by system sampling; finally, the time-domain feature values ​​of the frequency-reduced main pump pressure signal are extracted to obtain the feature vector. The above-mentioned extraction of the time-domain feature values ​​of the frequency-reduced main pump pressure signal can be obtained by calculating the mean and variance of the main pump pressure signal. By using system sampling to reduce the data sampling frequency, the low cost and low computing power requirements for working condition identification are ensured, making it easier to integrate with earthmoving machinery.

[0139] Taking excavators as an example of earthmoving machinery, for a small excavator with only one main pump, the feature vector is composed of the mean and variance of the pressure signal of main pump No. 1, and can be expressed as: X = [x1, x2], where X is the feature vector constructed from time-domain feature values; x1 is the mean of the pressure signal of main pump No. 1; and x2 is the variance of the pressure signal of main pump No. 1. For large and medium-sized excavators with two main pumps, the feature vector is composed of the mean and variance of the pressure signal of main pump No. 1 and the mean and variance of the pressure signal of main pump No. 2. The mean and variance of the pressure signal difference between main pumps 1 and 2 can be represented as: X = [x1, x2, x3, x4, x5, x6], where X is the eigenvector constructed from time-domain eigenvalues; x1 is the mean pressure signal of main pump 1; x2 is the variance of the pressure signal of main pump 1; x3 is the mean pressure signal of main pump 2; x4 is the variance of the pressure signal of main pump 2; x5 is the mean of the pressure signal difference between main pumps 1 and 2; and x6 is the variance of the pressure signal difference between main pumps 1 and 2.

[0140] Step A2: Normalize the feature vector to obtain a normalized feature vector. In this embodiment, the normalization process can be achieved by substituting the feature values ​​of the feature vector into the normalization formula to calculate the normalized feature values, thereby obtaining the normalized feature vector. The normalization formula can be:

[0141] Where, x new x represents the normalized eigenvalues; x represents the eigenvalues ​​before normalization; x max x represents the maximum value of the category feature corresponding to x in the feature vector; min In the feature vector x The minimum value of the corresponding category's characteristic value. In practical applications, other normalization methods such as nonlinear normalization can also be used.

[0142] Step A3: Input the normalized feature vector into the preset working condition stage identification model to identify the working condition stage and obtain the working condition stage identification result;

[0143] When the earthmoving machinery is an excavator, the normalized feature vector is input into the working condition stage identification model. The working condition stage of the excavator can be determined based on the sequence number with the highest output probability value in the working condition stage identification model output results. For example: when the maximum probability value is 1-5, the excavator's current working stage is respectively the excavation preparation, excavation, lifting and slewing, unloading, and empty bucket return stages under the earthmoving excavation working condition; when the maximum probability value is 6-7, the excavator's current working stage is respectively the bucket and stick outward swing and bucket and stick inward retraction stages under the leveling working condition; when the maximum probability value is 8-9, the excavator's current working stage is respectively the boom lifting stick inward swing and boom lowering stick outward swing stages under the slope trimming working condition; when the maximum probability value is 10-11, the excavator's current working stage is respectively the crushing impact and crushing point adjustment stages under the breaking working condition; when the maximum probability value is 12-13, the excavator's current working stage is respectively the vehicle travel and idling stages. It should be noted that the above sequence numbers can be set during the pre-training of the working condition stage recognition model, and the sequence number with the highest output probability value can be set as the output result.

[0144] In one embodiment, the obtained operating condition stage identification result may be stored in hardware devices such as processors and caches.

[0145] In one embodiment, the obtained operating condition stage identification results can also be output from the aforementioned hardware device to an output device in real time. The output device can be a memory, display device, terminal, communication module, etc., so that users can obtain the operating condition stage identification results in a timely manner. For example, the operating condition stage identification results stored in the processor can be output to the display device.

[0146] In one embodiment, to further improve the accuracy of operating condition stage identification, the operating condition stage identification can be performed cyclically until an end signal is received, at which point the operating condition stage identification result is output. Specifically, after executing step A3, step A4 can be executed: determining whether the operating condition stage identification process has ended. In this embodiment, determining whether the operating condition stage identification process has ended can be done by checking for an end signal. This end signal can be a switch that is activated by the operator according to the actual situation to obtain the end signal. Alternatively, it can be determined whether the operating condition stage identification process has ended by checking whether the power has been cut off.

[0147] Step A5: After the working condition stage identification process is completed, output the working condition stage identification result;

[0148] In this real-time example, the obtained operating condition stage identification results can be output from the aforementioned hardware devices to an output device, which can be a memory, display device, terminal, communication module, etc., so that users can obtain the operating condition stage identification results in a timely manner. For example, the operating condition stage identification results stored in the processor can be output to the display device.

[0149] Step A6: If the working condition identification process is not completed, remove the main pump pressure data that is furthest from the current time in the main pump pressure signal, and obtain the main pump pressure data at the next time to update the main pump pressure signal, obtain a new main pump pressure signal, and execute A1-A4.

[0150] In this embodiment, since the main pump pressure signal includes main pump pressure data within a certain time range, when the working condition identification process is not finished, as time changes, the main pump pressure data furthest from the current time can be removed, and then the main pump pressure data of the next time moment can be added to form a new main pump pressure signal. Then, steps A1-A4 are repeated until the identification is finished, thereby ensuring the accuracy and real-time performance of the working condition identification results.

[0151] Accordingly, to make the obtained operating condition type identification results more accurate, the operating condition stage identification results within a certain time range can be used as the data source for operating condition type identification.

[0152] In one embodiment, the working condition type identification result is a real-time output working condition type identification result. The step of identifying the working condition type of the earthmoving machinery using a preset working condition type identification model based on the working condition stage identification result to obtain the working condition type identification result includes:

[0153] Step B1: Obtain multiple working condition stage identification results within a second preset time range from the current time, and combine the multiple working condition stage identification results into a working condition stage vector; for example, taking earthmoving machinery as an excavator as an example, receive the identification results within 0.5s from the current time output by the excavator working condition stage identification model, and combine these working condition stage identification results into a vector to obtain the working condition stage vector.

[0154] It should be noted that the first preset time and the second preset time in this embodiment can be the same or different, and can be set according to actual needs.

[0155] Step B2: Input the working condition stage vector into the preset working condition type recognition model to identify the working condition type and obtain the working condition type recognition result;

[0156] When the earthmoving machinery is an excavator, the working condition stage vector is input into the working condition type recognition model. The working condition type of the excavator is determined based on the sequence number of the highest probability value in the model's output. For example: when the highest probability value is 1, the excavator's current working condition type is earthmoving; when the highest probability value is 2, the excavator's current working condition type is leveling; when the highest probability value is 3, the excavator's current working condition type is slope repair; when the highest probability value is 4, the excavator's current working condition type is breaking; and when the highest probability values ​​are 5-6, the excavator's current working condition types are vehicle travel and idling, respectively. It should be noted that the above sequence numbers can be set in advance when training the working condition stage recognition model, and the sequence number with the highest output probability value can be set as the output result.

[0157] In one embodiment, the obtained operating condition type identification result may be stored in hardware devices such as processors and caches.

[0158] In one embodiment, the obtained operating condition type identification result can also be output from the aforementioned hardware device to an output device in real time. The output device can be a memory, display device, terminal, communication module, etc., so that the user can obtain the operating condition type identification result in a timely manner. For example, the operating condition type identification result stored in the processor can be output to the display device.

[0159] In one embodiment, to further improve the accuracy of operating condition type identification, the operating condition type identification can be performed cyclically until an end signal is received, at which point the operating condition type identification result is output. Specifically, after executing step B2, step B3 can be continued: determining whether the operating condition type identification process has ended. In this embodiment, determining whether the operating condition type identification process has ended is similar to determining whether the operating condition stage identification process has ended in step A4 above. Both are determined by whether there is an end signal, so it will not be described in detail here.

[0160] Step B4: After the working condition type identification process is completed, output the working condition type identification result;

[0161] In this real-time example, the obtained operating condition type identification result can be output from the aforementioned hardware device to an output device, such as a memory, display device, terminal, or communication module, so that the user can obtain the operating condition type identification result in a timely manner. For example, the operating condition type identification result stored in the processor can be output to the display device.

[0162] Step B5: If the working condition type identification process is not completed, remove the working condition stage identification result that is furthest from the current time from the multiple working condition stage identification results, and obtain the working condition stage identification result of the next time moment to update the working condition stage vector, obtain a new working condition stage vector, and execute B2.

[0163] In this embodiment, since the working condition stage vector is composed of the working condition stage identification results at multiple time points, when the working condition type identification process is not finished, as time changes, the working condition stage identification result furthest from the current time can be removed, and then the working condition stage identification result at the next time point can be added to form a new working condition stage vector. Then, steps B2-B3 are repeated until the identification is finished, thereby ensuring the accuracy and real-time performance of the working condition type identification result.

[0164] In the above implementation process, the main pump pressure signal of the earthmoving machinery is acquired; then, based on the main pump pressure signal, a pre-set working condition stage identification model is used to identify the working condition stage of the earthmoving machinery, obtaining the working condition stage identification result; based on the working condition stage identification result, a pre-set working condition type identification model is used to identify the working condition type of the earthmoving machinery, obtaining the working condition type identification result. Based on the main pump pressure signal, the working condition stage identification model and the working condition type identification model are used sequentially to obtain the working condition stage identification result and the working condition type identification result. Using the main pump pressure generated by the basic actions of the actuator as the data source, the working condition identification of the earthmoving machinery is completed in a multi-step manner of working condition stage-working condition type, thus realizing a multi-level working condition identification method. Compared with the single-step working condition identification method, it reduces the complexity of the working condition identification model and the computational power requirements, which is beneficial for actual vehicle installation, and improves the accuracy and stability of the identification results. Meanwhile, the working condition stage identification model and the working condition type identification model can cover more working condition stages and types, broadening the coverage of the identification model, thus making it applicable to a variety of scenarios and improving the environmental adaptability of the working condition identification method.

[0165] By dividing the excavator operation process into six working conditions—earth excavation, leveling, slope repair, breaking, vehicle travel, and idling—and further defining the working condition stages covered by each working condition type, the model identifies the working condition stages and types sequentially from bottom to top based on the mapping relationship between the basic actions of the actuators and the main pump pressure waveform under each working condition stage. This multi-level identification method can effectively improve the reliability of the model. Furthermore, by using the main pump pressure signal as the original signal source and establishing the identification model using a BP neural network, the model has low cost and low computing power requirements, making it more suitable for the configuration of construction machinery mainframes.

[0166] By employing a working condition stage identification model and a working condition type identification model to identify the working condition stage and working condition type respectively, and using the output of the working condition stage identification model as the input of the working condition type identification model, a multi-level working condition identification method is realized, which reduces the amount of computation and facilitates the rapid acquisition of working condition identification results.

[0167] Please refer to Figure 2 , Figure 2This diagram illustrates a multi-level, multi-dimensional statistical flowchart of hydraulic excavator operation information according to an embodiment of this application. The amount of earthwork already completed, earthwork efficiency, and the amount of earthwork excavated in a single operation can be used as the second statistical result of the operation information. After obtaining the first and second statistical results of the operation information, multi-level, multi-dimensional operation information statistics can be achieved. The operation information statistics cover three aspects: working conditions, energy consumption, and earthwork volume, thus providing more comprehensive information on the main machine's operation process and supporting project managers in making reasonable project decisions. Furthermore, the first and second statistical results of the operation information can be uploaded to an IoT platform via an external controller to achieve remote monitoring of the main machine's operation information.

[0168] Figure 1 This is a flowchart illustrating the method for determining the earthwork volume using earthmoving machinery in this embodiment. It should be understood that, although... Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0169] In one embodiment, such as Figure 5 As shown, Figure 5 This schematically illustrates a structural block diagram of an earthmoving machinery operation earthwork volume determination device according to an embodiment of this application. An earthmoving machinery operation earthwork volume determination device is provided, including an acquisition module 410, a first determination module 420, and a second determination module 430, wherein:

[0170] The acquisition module 410 is used to acquire an electronic map of the working environment, the positioning signal of the earthmoving machinery, and the motion information of the actuator. The electronic map of the working environment includes the location information of the area to be worked.

[0171] The first determining module 420 is used to determine the working device trajectory of the earthmoving machinery in the electronic map based on the positioning signal and actuator motion information of the earthmoving machinery.

[0172] The second determining module 430 is used to determine the amount of earthwork already done based on the trajectory of the working device and the location information of the work area to be worked.

[0173] The earthmoving machinery operation earthmoving volume determination device includes a processor and a memory. The aforementioned acquisition module 410, first determination module 420, and second determination module 430 are all stored in the memory as program units. The processor executes the aforementioned program modules stored in the memory to realize the corresponding functions.

[0174] The processor contains a kernel, which retrieves the corresponding program unit from memory. One or more kernels can be configured, and the amount of earthwork completed by each earthmoving machine can be calculated by adjusting the kernel parameters.

[0175] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0176] This application provides a storage medium storing a program that, when executed by a processor, implements the above-described method for determining the volume of earthwork in earthmoving machinery operations.

[0177] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown in the figure, the computer device includes a processor A01, a network interface A02, a display screen A04, an input device A05, and a memory (not shown) connected via a system bus. The processor A01 provides computing and control capabilities. The memory includes internal memory A03 and a non-volatile storage medium A06. The non-volatile storage medium A06 stores an operating system B01 and a computer program B02. The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 stored in the non-volatile storage medium A06. The network interface A02 is used for communication with external terminals via a network connection. When the computer program is executed by the processor A01, it implements a method for determining the earthwork volume of earthmoving machinery. The display screen A04 can be an LCD screen or an e-ink display screen. The input device A05 can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0178] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0179] In one embodiment, the earthmoving machinery operation earthmoving volume determination device provided in this application can be implemented as a computer program, and the computer program can be implemented as follows: Figure 6 The computer device shown runs the program. The computer device's memory can store the various program modules that make up the earthmoving machinery operation earthmoving volume determination device, for example, Figure 5 The acquisition module 410, the first determination module 420, and the second determination module 430 are shown. The computer program, comprised of these modules, causes the processor to execute the steps in the earthmoving machinery operation earthwork volume determination method described in the various embodiments of this application.

[0180] Figure 6 The computer device shown can be used as follows Figure 5 The acquisition module 410 in the earthmoving machinery operation earthmoving volume determination device shown executes step 210. The computer equipment can execute step 220 through the first determination module 420 and step 230 through the second determination module 430.

[0181] This application provides a device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs the following steps:

[0182] The system acquires an electronic map of the work environment, the positioning signals of the earthmoving machinery, and the motion information of the actuators. The electronic map of the work environment includes the location information of the work area.

[0183] Based on the positioning signal and actuator motion information of the earthmoving machinery, the trajectory of the working device of the earthmoving machinery in the electronic map is determined;

[0184] Based on the trajectory of the working device and the location information of the area to be worked, the amount of earthwork already worked is determined.

[0185] In one embodiment, determining the amount of earthwork already completed based on the location information of the working device trajectory and the work area includes:

[0186] Based on the location information of the work area to be worked, the work area in the electronic map of the work environment is divided into multiple cubes;

[0187] The cube state of each cube is determined, and the cube state indicates the intersection state between the cube and the trajectory of the working device;

[0188] Based on the state and volume of each cube, the amount of earthwork already completed is obtained.

[0189] In one embodiment, it also includes:

[0190] Get the number of earthwork excavation cycles;

[0191] The amount of earthwork excavation work per cycle is calculated based on the amount of earthwork already excavated and the number of earthwork excavation cycles.

[0192] In one embodiment, obtaining the number of earthwork excavation cycles includes:

[0193] Obtain the results of working condition stage identification and working condition type identification;

[0194] Based on the identification results of the working condition stage and the identification results of the working condition type, statistics are performed according to the preset working condition information statistical conditions to obtain the number of earthwork excavation cycles.

[0195] In one embodiment, it also includes:

[0196] Obtain the total operation time for earthwork excavation;

[0197] The earthwork operation efficiency is calculated based on the amount of earthwork already completed and the total operation time of earthwork excavation.

[0198] In one embodiment, the location information of the area to be worked on includes terrain elevation and slope information;

[0199] The acquisition of the electronic map of the working environment includes:

[0200] Obtain terrain elevation and slope information within the area to be worked on;

[0201] An electronic map of the work environment is generated based on the terrain elevation and slope information within the work area.

[0202] In one embodiment, determining the trajectory of the earthmoving machinery's working device on the electronic map based on the positioning signal and actuator motion information of the earthmoving machinery includes:

[0203] The pose of the earthmoving machinery's base point in the electronic map is determined based on the positioning signal of the earthmoving machinery. The motion trajectory of the working device in the base coordinate system is determined based on the motion information of the actuator and the kinematic model of the earthmoving machinery. The base coordinate system has the base point as the origin of the coordinate system.

[0204] Based on the position of the earthmoving machinery's base point on the electronic map and the movement trajectory of the working device in the base coordinate system, the working device trajectory of the earthmoving machinery's working device on the electronic map is determined.

[0205] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0206] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0207] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0208] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0209] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0210] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0211] Computer-readable media include both permanent and non-permanent, removable and non-removable media, which can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0212] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0213] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for determining the volume of earthwork in earthmoving machinery operations, characterized in that, include: The system acquires an electronic map of the work environment, the positioning signals of the earthmoving machinery, and the motion information of the actuators. The electronic map of the work environment includes the location information of the work area. Based on the positioning signal and actuator motion information of the earthmoving machinery, the trajectory of the working device of the earthmoving machinery in the electronic map is determined; Based on the trajectory of the working device and the location information of the work area, the amount of earthwork already completed is determined; The step of determining the amount of earthwork already done based on the trajectory of the working device and the location information of the work area includes: Based on the location information of the work area to be worked, the work area in the electronic map of the work environment is divided into multiple cubes; The cube state of each cube is determined, and the cube state indicates the intersection state between the cube and the trajectory of the working device; Based on the state and volume of each cube, the amount of earthwork already completed is obtained.

2. The method for determining the earthwork volume of earthmoving machinery operations according to claim 1, characterized in that, Also includes: Get the number of earthwork excavation cycles; The amount of earthwork excavation work per cycle is calculated based on the amount of earthwork already excavated and the number of earthwork excavation cycles.

3. The method for determining the earthwork volume of earthmoving machinery operations according to claim 2, characterized in that, The process of obtaining the number of earthwork excavation cycles includes: Obtain the results of working condition stage identification and working condition type identification; Based on the identification results of the working condition stage and the identification results of the working condition type, statistics are performed according to the preset working condition information statistical conditions to obtain the number of earthwork excavation cycles.

4. The method for determining the earthwork volume of earthmoving machinery operations according to claim 1, characterized in that, Also includes: Obtain the total operation time for earthwork excavation; The earthwork operation efficiency is calculated based on the amount of earthwork already completed and the total operation time of earthwork excavation.

5. The method for determining the earthwork volume of earthmoving machinery operations according to claim 1, characterized in that, The location information of the area to be worked on includes terrain elevation and slope information; The acquisition of the electronic map of the working environment includes: Obtain terrain elevation and slope information within the area to be worked on; An electronic map of the work environment is generated based on the terrain elevation and slope information within the work area.

6. The method for determining the earthwork volume of earthmoving machinery operations according to claim 1, characterized in that, The step of determining the trajectory of the earthmoving machinery's working device on the electronic map based on the positioning signal and actuator motion information of the earthmoving machinery includes: The pose of the earthmoving machinery's base point in the electronic map is determined based on the positioning signal of the earthmoving machinery. The motion trajectory of the working device in the base coordinate system is determined based on the motion information of the actuator and the kinematic model of the earthmoving machinery. The base coordinate system has the base point as the origin of the coordinate system. Based on the position of the earthmoving machinery's base point on the electronic map and the movement trajectory of the working device in the base coordinate system, the working device trajectory of the earthmoving machinery's working device on the electronic map is determined.

7. A device for determining the volume of earthwork in earthmoving machinery operations, characterized in that, include: The acquisition module is used to acquire an electronic map of the working environment, the positioning signals of the earthmoving machinery, and the motion information of the actuators. The electronic map of the working environment includes the location information of the area to be worked. The first determining module is used to determine the trajectory of the working device of the earthmoving machinery in the electronic map based on the positioning signal and the motion information of the actuator of the earthmoving machinery. The second determining module is used to determine the amount of earthwork already done based on the location information of the working device trajectory and the work area to be worked; wherein, determining the amount of earthwork already done based on the location information of the working device trajectory and the work area to be worked includes: dividing the work area in the electronic map of the work environment into multiple cubes based on the location information of the work area to be worked; determining the cube state of each cube, wherein the cube state indicates the intersection state of the cube with the working device trajectory; and obtaining the amount of earthwork already done based on the cube state and the volume of each cube.

8. A processor, characterized in that, Configured to perform the earthwork volume determination method for earthmoving machinery operations according to any one of claims 1 to 6.

9. A machine-readable storage medium storing instructions thereon, characterized in that, When executed by a processor, this instruction causes the processor to be configured to perform the method for determining the earthwork volume of earthmoving machinery operations according to any one of claims 1 to 6.

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