Milling operation amount detection method, milling operation amount detection system, and milling machine

Abstract

The present application belongs to the technical field of milling and planing machines, and particularly relates to a milling and planing operation amount detection method, a detection system and a milling and planing machine. The milling and planing operation amount detection method comprises: collecting image information of a construction road surface in a preset time period through an image collector; determining a down-cut working condition of the milling and planing operation by identifying whether a boundary line of a milled area and a to-be-milled area exists in the image information; and determining a milling and planing cubic amount of the milling and planing machine in the preset time period according to the down-cut working condition, size parameters of the milling and planing machine, operation parameters and state information of the boundary line. The present application can detect the milling and planing cubic amount through image recognition, and can calculate in different ways according to different down-cut working conditions of the milling and planing machine. Compared with the existing way, the present application can effectively prevent operation amount deviation, and the detection and calculation results are more accurate, which is beneficial to reducing the rental fee of the milling and planing machine user.

Description

Technical Field

[0001] This invention belongs to the field of milling machine technology, specifically relating to a method for detecting milling workload, a system for detecting milling workload, and a milling machine. Background Technology

[0002] Milling machines are commonly used in road construction, primarily for milling and cutting road surfaces. In practice, milling machines are mostly operated on a rental basis, and rental fees are typically settled based on the amount of milling work completed. Therefore, the accuracy of the milling work volume is crucial to the rental cost. In actual milling operations, the width of the road surface is usually greater than the milling width of the milling machine, generally requiring multiple milling operations in the same direction. Initially, the milling width is roughly the same as the width of the milling rotor. However, when the milling machine cuts again, there is some overlap between the area to be milled and the adjacent already milled area. Therefore, the amount of milling work completed in the initial and subsequent cuts differs. Current methods for calculating milling work volume are simplistic, directly using the width of the milling rotor as the milling width. This calculation results in discrepancies between the actual work volume and the calculated volume, and these discrepancies vary depending on the construction process, making effective correction difficult. This leads to the calculated volume being significantly higher than the actual work volume, increasing rental costs for the user. Summary of the Invention

[0003] In view of the above, in order to improve at least one of the above-mentioned problems existing in the prior art, the present invention provides a milling operation quantity detection method, a milling operation quantity detection system, and a milling machine.

[0004] The first aspect of the present invention provides a method for detecting milling work volume, applied to a milling machine equipped with an image acquisition device, the method comprising:

[0005] Step S100: Collect image information of the construction road surface within a preset time period using an image acquisition device;

[0006] Step S200: By identifying whether there is a boundary line between the milled area and the area to be milled in the image information, the cutting condition of the milling operation is determined; wherein, the cutting condition includes the initial cutting condition and the second cutting condition;

[0007] Step S300: Determine the milling volume of the milling machine within a preset time period based on the cutting conditions, the milling machine's dimensional parameters, operating parameters, and boundary line status information.

[0008] In one feasible implementation, when the current cutting condition is a re-cutting condition, step S300: based on the cutting condition, the boundary line status information, and the milling machine's dimensional and operational parameters, determine the milling volume of the milling machine within a preset time period, including:

[0009] Step S310: In the images corresponding to different times within a preset time period, identify the first coordinate information of the reference point on the boundary line relative to the viewpoint of the image acquisition device and the heading angle information of the boundary line.

[0010] Step S320: Calculate the milling volume of the milling machine within a preset time period based on the first coordinate information, heading angle information, and the size and operation parameters of the milling machine at different times.

[0011] In one feasible implementation, step S310: In the images corresponding to different times within a preset time period, identify the first coordinate information of the reference point on the boundary line relative to the viewpoint of the image acquisition device and the heading angle information of the boundary line, including:

[0012] Step S311: Establish a viewpoint coordinate system with the viewpoint of the image acquisition device as the origin, and establish a rotor center coordinate system with the center point of the milling rotor of the milling machine as the origin;

[0013] Step S312: In the images corresponding to different times, select any point on the boundary line between the milled area and the area to be milled in the image as a reference point;

[0014] Step S313: Determine the second coordinate information of the reference point in the rotor center coordinate system based on the image information;

[0015] Step S314: Perform perspective transformation based on the second coordinate information to determine the first coordinate information of the reference point in the viewpoint coordinate system;

[0016] Step S315: Determine the heading angle of the boundary line in the viewpoint coordinate system based on the first coordinate information.

[0017] In one feasible implementation, step S315: determining the heading angle of the boundary line in the viewpoint coordinate system based on the first coordinate information, including:

[0018] Step S3151: Determine the equation of the boundary line in the viewpoint coordinate system based on the first coordinate information;

[0019] Step S3152: Determine the angle between the boundary line and the positive direction of the horizontal coordinate axis of the viewpoint coordinate system according to the straight line equation of the boundary line, and use the angle as the heading angle of the boundary line.

[0020] In one feasible implementation, the operating parameters of the milling machine include milling thickness and milling speed;

[0021] Step S320: Based on the first coordinate information and heading angle information of the reference points at different times, as well as the dimensional parameters and operating parameters of the milling machine, calculate the milling volume of the milling machine within the preset time period, including:

[0022] Step S321: Calculate the actual milling width of the milling machine at each moment based on the first coordinate information, heading angle information, and size parameters of the milling machine at different times;

[0023] Step S322: Calculate the milling area of ​​the milling machine within the preset time period by integrating the milling speed and the actual milling width of the milling machine at each moment according to the formula S=∫Li×Vi; where Li is the actual milling width and Vi is the milling speed.

[0024] Step S323: Calculate the milling thickness and milling area according to the formula V=S×Hi, and calculate the milling volume of the milling machine within the preset time period; where V is the milling volume and Hi is the milling thickness.

[0025] In one feasible implementation, the dimensional parameters of the milling machine include the dimensional parameters of the milling rotor and the positional parameters of the image acquisition device relative to the milling rotor.

[0026] Step S321: Based on the first coordinate information of the reference point at different times, the heading angle information, and the size parameters of the milling machine, calculate the actual milling width of the milling machine at each time, including:

[0027] Step S3211: Determine the width of the milling rotor and the third coordinate information of the two ends of the milling rotor in the rotor center coordinate system according to the dimensional parameters of the milling rotor; wherein, the third coordinate information includes the coordinate of the left end of the milling rotor (Xl0,0) and the coordinate of the right end of the milling rotor (Xr0,0).

[0028] Step S3212: Based on the position parameters of the image acquisition device relative to the milling rotor, determine the fourth coordinate information of the viewpoint of the image acquisition device in the rotor center coordinate system; wherein, image acquisition devices are provided on both the left and right sides of the milling machine, and the fourth coordinate information includes the coordinates (Xl, Yl) of the left image acquisition device and the coordinates (Xr, Yr) of the right image acquisition device.

[0029] Step S3213: When the milled area is located on the right side of the milling machine, calculate the actual milling width of the milling machine at each moment according to the formula Li=L0+(Xr-Xr0)+X0-(Y0+Yl)×tan(π / 2-θ); when the milled area is located on the left side of the milling machine, calculate the actual milling width of the milling machine at each moment according to the formula Li=L0+(Xl-Xl0)+X0-(Y0+Yr)×tan(π / 2-θ); where L0 is the width of the milling rotor, (X0,Y0) is the first coordinate information of the reference point, and θ is the heading angle of the boundary line.

[0030] In one feasible implementation, the dimensional parameters of the milling machine include the dimensional parameters of the milling rotor;

[0031] The operating parameters of a milling machine include milling thickness and milling speed;

[0032] When the current cutting condition is the initial cutting condition, step S300: Based on the cutting condition, the boundary line status information, and the milling machine's dimensional and operational parameters, determine the milling volume of the milling machine within a preset time period, including:

[0033] Step S351: Determine the width of the milling rotor based on the dimensional parameters of the milling rotor, and use the width of the milling rotor of the milling machine as the actual milling width;

[0034] Step S352: Calculate the milling volume of the milling machine within a preset time period based on the milling rotor width, milling thickness, and milling speed.

[0035] In one feasible implementation, the operating parameters of the milling machine also include the material density of the milled road surface;

[0036] Milling operation quantity detection methods also include:

[0037] Step S400: Calculate the weight of material produced by the milling machine during the preset time period based on the material density and milling volume.

[0038] The second aspect of the present invention also provides a milling work volume detection system, comprising: an image acquisition device disposed on the side of a milling machine, the image acquisition device being used to acquire image information of the construction road surface in front of the milling machine; a controller being communicatively connected to the image acquisition device, the controller being adapted to execute the milling work volume detection method in any of the first aspects above to determine the milling work volume of the milling machine; and a display device being communicatively connected to the controller and capable of outputting corresponding milling work volume information according to the control instructions of the controller.

[0039] The third aspect of the present invention also provides a milling machine, including the milling work volume detection system described in any of the second aspects above.

[0040] A fourth aspect of the present invention also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program suitable for execution in the processor. When the processor executes the computer program in the memory, it can implement the milling work quantity detection method of any of the first aspects described above.

[0041] The fifth aspect of the present invention also provides a readable storage medium storing a computer program that, when executed by a processor, implements the milling work quantity detection method of any of the first aspects described above.

[0042] The beneficial effects of the above-mentioned technical solution of the present invention are as follows:

[0043] The milling volume is detected by image recognition, and different calculation methods are used according to different milling machine cutting conditions. Compared with existing methods, it can effectively prevent deviations in the workload, and the detection and calculation results are more accurate, which helps to reduce the rental costs for milling machine users. Attached image description:

[0044] Figure 1 The diagram shown is a flowchart of a milling operation quantity detection method provided in an embodiment of the present invention.

[0045] Figure 2 The diagram shown is a top view of a milling machine according to an embodiment of the present invention.

[0046] Figure 3 The diagram shown is a top-down view of a milling machine provided in an embodiment of the present invention at a construction site.

[0047] Figure 4 As shown Figure 1 A schematic diagram of a specific step in step S300.

[0048] Figure 5 The image shown is a schematic diagram of a frame provided in an embodiment of the present invention.

[0049] Figure 6 As shown Figure 4 A schematic diagram of a specific step in step S310.

[0050] Figure 7 As shown Figure 6 A schematic diagram of a specific step in step S315.

[0051] Figure 8 As shown Figure 4 A schematic diagram of a specific step in step S320.

[0052] Figure 9 As shown Figure 8 A schematic diagram of a specific step in step S321.

[0053] Figure 10 As shown Figure 1 A schematic diagram of another specific step in step S300.

[0054] Figure 11 The diagram shown is a flowchart of another milling operation quantity detection method provided in an embodiment of the present invention.

[0055] Figure 12 The figure shown is a schematic block diagram of a milling operation quantity detection system provided in an embodiment of the present invention.

[0056] Figure 13 The diagram shown is a schematic block diagram of a milling machine provided in one embodiment of the present invention. Detailed Implementation

[0057] In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, top, bottom, etc.) in the embodiments of this application are only used to explain the relative positional relationships and movement of the components in a specific posture (as shown in the figures). If the specific posture changes, the directional indication will also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0058] Furthermore, the reference to "embodiment" herein means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0059] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0060] Application Overview

[0061] Currently, most large-scale construction machinery is operated through leasing, and the calculation method for leasing fees varies depending on the specific characteristics of the machinery. Taking milling machines, a common type of road construction machinery, as an example, milling machines are mainly used for milling and cutting road surfaces. Rental fees are typically calculated based on the amount of milling work (e.g., the volume of milled material). During construction, the width of the road surface is usually greater than the milling width of the milling machine, generally requiring multiple milling operations in the same direction. During the initial cut, the milling width is roughly the same as the width of the milling rotor; however, during subsequent cuts, there is some overlap between the area to be milled and the adjacent already milled area. Therefore, the amount of milling work done during the initial cut and subsequent cuts is not the same. Current methods for calculating milling machine workload are relatively simple, directly using the width of the milling rotor as the milling width. This results in a discrepancy between the calculated result and the actual workload, and this discrepancy varies depending on the construction process, making effective correction difficult. This leads to calculated results that are significantly higher than the actual workload, increasing costs for the user.

[0062] The following provides some embodiments of the milling work volume detection method, milling work volume detection system, milling machine, electronic device and readable storage medium in the technical solution of the present invention.

[0063] An embodiment of the first aspect of the present invention provides a method for detecting milling work volume, such as... Figure 1 As shown, the methods for detecting milling work volume include:

[0064] Step S100: Collect image information of the construction road surface within a preset time period using an image acquisition device;

[0065] Step S200: By identifying whether there is a boundary line between the milled area and the area to be milled in the image information, the cutting condition of the milling operation is determined; wherein, the cutting condition includes the initial cutting condition and the second cutting condition;

[0066] Step S300: Based on the cutting conditions, boundary line status information, and the milling machine's dimensional and operational parameters, determine the milling volume of the milling machine within a preset time period.

[0067] The milling work volume detection method in this embodiment is applied to a milling machine, such as... Figure 2As shown, the milling machine 200 is equipped with at least one image acquisition device 11 for acquiring image information of the construction road surface. The image acquisition device 11 is positioned to the side and slightly forward of the milling machine 200 to prevent the image acquisition range 350 in front of the milling machine from being obstructed by the material conveying mechanism 230, thus facilitating the acquisition of image information of the construction road surface in front of the milling machine 200. When multiple image acquisition devices 11 are installed, for example... Figure 2 The two shown can be located on the left and right sides of the milling machine 200, respectively. The image acquisition device 11 includes, but is not limited to, a camera, video camera, or webcam. The condition of the construction road surface is as follows... Figure 3 As shown, when the milling machine 200 is in the process of cutting again, the construction road surface includes the milled area 310 and the area to be milled 320.

[0068] In this embodiment, step S100 involves using an image acquisition device to collect image information of the construction road surface within a preset time period, which serves as the basis for subsequent identification of the cutting condition and calculation of the milling workload. The preset time period can be set according to specific construction requirements. Step S200 involves identifying the image information, determining whether the milling operation's cutting condition is an initial cutting condition or a subsequent cutting condition based on the presence of a boundary line between the milled area and the area to be milled. This determination serves as the basis for selecting the workload calculation method. Step S300 involves using corresponding calculation methods based on different cutting conditions, and performing corresponding calculations based on the boundary line status information, the milling machine's dimensions, and operating parameters to determine the milling volume within the preset time period. It is understood that in practical applications, the milling workload is usually expressed in milling volume. The boundary line status information includes the presence or absence of a boundary line and the position information of any point on the boundary line.

[0069] It should be noted that when the milling machine initially makes its first cut, the milling rotor width is the milling width, so the milling workload can be directly determined; however, when the milling machine makes its second cut, such as Figure 3 In the example above, since a milled area 310 already exists next to the area to be milled 320, there is usually a partial overlap 330 between the two areas during the next milling operation to ensure proper alignment. Therefore, the milling width during this next operation is typically smaller than the width of the milling rotor. Furthermore, deviations are inevitable during milling machine operation, and the actual milling width changes as the machine travels, making it difficult to determine directly. Therefore, the calculation method for milling work volume varies depending on the milling operation condition. Correspondingly, the milling operation condition can be determined by identifying the presence of a boundary line between the milled area and the area to be milled in the image. The presence of a boundary line indicates a re-entry operation, while the absence of a boundary line indicates an initial entry operation.

[0070] The milling workload detection method in this embodiment detects the milling volume through image recognition. Moreover, it can use different calculation methods to calculate the volume according to different milling machine cutting conditions. Compared with existing methods, it can effectively prevent workload deviations, and the detection and calculation results are more accurate, which helps to reduce the rental costs for milling machine users.

[0071] The milling operation quantity detection method provided in a further embodiment of the present invention, such as Figures 1 to 4 As shown, when the milling machine is detected to be cutting again during the current milling operation, step S300 includes:

[0072] Step S310: In the images corresponding to different times within a preset time period, identify the first coordinate information of the reference point on the boundary line relative to the viewpoint of the image acquisition device and the heading angle information of the boundary line.

[0073] Step S320: Calculate the milling volume of the milling machine within a preset time period based on the first coordinate information, heading angle information, and the size and operation parameters of the milling machine at different times.

[0074] In this embodiment, based on the previous embodiments, the specific method steps of step S300 under the condition of re-cutting are further described. Through step S310, multiple different times are selected within a preset time period, and the first coordinate information of the reference point on the boundary line between the milled area and the area to be milled, relative to the viewpoint of the image acquisition device, and the heading angle information of the boundary line are identified in the images corresponding to different times. Then, through step S320, the milling volume of the milling machine within the preset actual section is obtained by performing corresponding calculations using the first coordinate information of the reference point, the heading angle information of the boundary line, and the size parameters and operating parameters of the milling machine.

[0075] It is understandable that in the images captured by the image acquisition device, the shape of the boundary lines relative to the viewpoint differs from their shape in the coordinate plane of the actual road surface due to the perspective issue. For example, Figure 3 The image shows a top view of the milling machine and the road surface it is working on. Figure 3 In the coordinate system, the boundary line 340 between the milled area 310 and the area to be milled 320 is a straight line parallel to the Y-axis; Figure 5 The image displayed is a frame of a certain image. Figure 5 In the coordinate system, boundary line 340 appears as a straight line tilted to the Y-axis due to the perspective. There is a certain heading angle between boundary line 340 and the coordinate axes, for example... Figure 5 The angle θ in the equation.

[0076] This embodiment utilizes reference points on the boundary line (e.g. Figure 5By performing corresponding calculations on point P in the diagram and the heading angle of the boundary line, the actual milling width of the milling machine can be accurately obtained. Then, by combining the size parameters and operating parameters of the milling machine, the actual milling volume can be calculated. This not only eliminates the overlapping area between the area to be milled and the area that has already been milled, but also effectively identifies the difference in the actual milling width of the milling machine at different times, further improving the accuracy of the detection results.

[0077] Furthermore, such as Figure 6 As shown, step S310 specifically includes the following steps:

[0078] Step S311: Establish a viewpoint coordinate system with the viewpoint of the image acquisition device as the origin, and establish a rotor center coordinate system with the center point of the milling rotor of the milling machine as the origin;

[0079] Step S312: In the images corresponding to different times, select any point on the boundary line between the milled area and the area to be milled in the image as a reference point;

[0080] Step S313: Determine the second coordinate information of the reference point in the rotor center coordinate system based on the image information;

[0081] Step S314: Perform perspective transformation based on the second coordinate information to determine the first coordinate information of the reference point in the viewpoint coordinate system;

[0082] Step S315: Determine the heading angle of the boundary line in the viewpoint coordinate system based on the first coordinate information.

[0083] In this embodiment, the specific process of determining the first coordinate information and the heading angle is further explained based on the aforementioned embodiments. Through step S311, a viewpoint coordinate system is established with the viewpoint of the image acquisition device as the origin (e.g., ...). Figure 5 In addition to the coordinate system in the image, a rotor center coordinate system is also established with the center point of the milling rotor of the milling machine as the origin (e.g., ...). Figure 3 (Coordinate system in the text); through step S312, select any point on the boundary line as a reference point, for example... Figure 3 and Figure 5 Point P in the coordinate system is used, and through step S313, the second coordinate information of the reference point in the rotor center coordinate system is determined. For example, point P is located at... Figure 3 The coordinates (x0, y0) in the image can be obtained through the image acquisition process of the image acquisition device. In step S314, a perspective transformation is performed based on the second coordinate information to calculate the first coordinate information of the reference point in the viewpoint coordinate system. For example... Figure 5The coordinates (X0, Y0) of point P can be calculated using a corresponding perspective transformation algorithm, such as homography algorithm; then, through step S315, the heading angle of the boundary line in the viewpoint coordinate system is determined by performing corresponding calculations based on the first coordinate information of the reference point.

[0084] Furthermore, such as Figure 7 As shown, step S315 specifically includes the following steps:

[0085] Step S3151: Determine the equation of the boundary line in the viewpoint coordinate system based on the first coordinate information;

[0086] Step S3152: Determine the angle between the boundary line and the positive direction of the horizontal coordinate axis of the viewpoint coordinate system according to the straight line equation of the boundary line, and use the angle as the heading angle of the boundary line.

[0087] In step S3151, the equation of the boundary line in the viewpoint coordinate system can be determined by the coordinates of the reference point on the boundary line, thus determining the position and direction of the boundary line. Furthermore, through step S3151, in the viewpoint coordinate system, the boundary line must intersect with the coordinate axes. The angle formed by the boundary line and the positive direction of the horizontal coordinate axis of the viewpoint coordinate system is taken as the heading angle of the boundary line. Then, the magnitude of the heading angle can be calculated through geometric operations, thereby determining the heading angle information of the boundary line.

[0088] In this embodiment, a perspective transformation method is used to establish the connection between the reference point and the two coordinate systems, thereby obtaining the first coordinate information of the reference point in the viewpoint coordinate system and the heading angle of the boundary line, providing a data basis and basis for subsequent calculation of milling volume.

[0089] In a further embodiment of the present invention, a method for detecting milling output is provided, wherein the operating parameters of the milling machine include milling thickness and milling speed. For example... Figure 1 , Figure 4 and Figure 8 As shown, step S320 of the milling operation quantity detection method specifically includes the following steps:

[0090] Step S321: Calculate the actual milling width of the milling machine at each moment based on the first coordinate information, heading angle information, and size parameters of the milling machine at different times;

[0091] Step S322: Calculate the milling area of ​​the milling machine within the preset time period by integrating the milling speed and the actual milling width of the milling machine at each moment according to the formula S=∫Li×Vi; where Li is the actual milling width and Vi is the milling speed.

[0092] Step S323: Calculate the milling thickness and milling area according to the formula V=S×Hi, and calculate the milling volume of the milling machine within the preset time period; where V is the milling volume and Hi is the milling thickness.

[0093] In this embodiment, step S320 is further improved based on the aforementioned embodiment. In step S321, the actual milling width of the milling machine at each moment is calculated based on the first coordinate information of the reference point in the image corresponding to different times, the heading angle information of the boundary line, and the size parameters of the milling machine. In step S322, the actual milling width Li at each moment within the preset time period is integrated with the milling speed Vi to obtain the milling area S of this milling operation. Then, in step S323, the milling volume V of the milling machine within the preset time period is calculated by combining the milling thickness Hi and the milling area S, which is used to characterize the milling workload of the milling machine.

[0094] Furthermore, the dimensional parameters of the milling machine specifically include the dimensional parameters of the milling rotor and the positional parameters of the image acquisition device relative to the milling rotor. For example... Figure 9 As shown, step S321 specifically includes:

[0095] Step S3211: Determine the width of the milling rotor and the third coordinate information of the two ends of the milling rotor in the rotor center coordinate system according to the dimensional parameters of the milling rotor; wherein, the third coordinate information includes the coordinate of the left end of the milling rotor (Xl0,0) and the coordinate of the right end of the milling rotor (Xr0,0).

[0096] Step S3212: Based on the position parameters of the image acquisition device relative to the milling rotor, determine the fourth coordinate information of the viewpoint of the image acquisition device in the rotor center coordinate system; wherein, image acquisition devices are provided on both the left and right sides of the milling machine, and the fourth coordinate information includes the coordinates (Xl, Yl) of the left image acquisition device and the coordinates (Xr, Yr) of the right image acquisition device.

[0097] Step S3213: When the milled area is located on the right side of the milling machine, calculate the actual milling width of the milling machine at each moment according to the formula Li=L0+(Xr-Xr0)+X0-(Y0+Yl)×tan(π / 2-θ); when the milled area is located on the left side of the milling machine, calculate the actual milling width of the milling machine at each moment according to the formula Li=L0+(Xl-Xl0)+X0-(Y0+Yr)×tan(π / 2-θ); where L0 is the width of the milling rotor, (X0,Y0) is the first coordinate information of the reference point, and θ is the heading angle of the boundary line.

[0098] Specifically, such as Figure 3 and Figure 5In the example, the milling rotor 220 has a width of L0, an actual milling width of Li, a milling thickness of Hi, and a milling speed of Vi. The milled area 310 is located to the right of the milling machine 200. The coordinates of the right end of the milling rotor 220 in the rotor center coordinate system are (Xr0,0), and the coordinates of the left end of the milling rotor 220 in the rotor center coordinate system are (Xl0,0), serving as the third coordinate information. The coordinates of the left image acquisition device in the rotor center coordinate system are (Xl,Yl), and the coordinates of the right image acquisition device in the rotor center coordinate system are (Xr,Yr), serving as the fourth coordinate information. The coordinates of the reference point P in the viewpoint coordinate system are (X0,Y0), and the heading angle of the boundary line 340 in the viewpoint coordinate system is θ.

[0099] Since the milled area 310 is located to the right of the milling machine 200, the actual milling width is calculated according to the following formula:

[0100] Li=L0+(Xr-Xr0)+X0-(Y0+Yl)×tan(π / 2-θ);

[0101] Then, calculate the milling area S = ∫Li × Vi according to the following formula 2;

[0102] Then, calculate the milling volume V = S × Hi according to the following formula:

[0103] If the milled area 310 is located to the left of the milling machine 200, the actual milling width is calculated according to the following formula four:

[0104] Li=L0+(Xl-Xl0)+X0-(Y0+Yr)×tan(π / 2-θ);

[0105] Then, calculate the milling area S and milling volume V according to Formula 2 and Formula 3 above.

[0106] It is understandable that during actual operation, the milling machine's travel path cannot be guaranteed to be perfectly straight, and lateral deviation is inevitable. Therefore, the actual milling width varies at different times, resulting in an irregularly shaped milling area for a single operation. In this embodiment, by integrating the milling width at different times within a preset time period, the lateral deviation of the milling machine can be corrected, avoiding the resulting deviation and accurately calculating the actual area and volume of the irregular milling area.

[0107] It should be noted that the rotor center coordinate system and the viewpoint coordinate system in the above embodiments are preferred implementations, but other similar coordinate systems can also be used for calculation. Additionally, relative position values ​​can be used for calculation as needed.

[0108] In a further embodiment of the present invention, the milling output detection method includes the dimensional parameters of the milling machine, including the dimensional parameters of the milling rotor, and the operating parameters of the milling machine, including the milling thickness and milling speed. When the milling machine is in its initial cutting condition, such as... Figure 1 and Figure 10 As shown, step S300 specifically includes:

[0109] Step S351: Determine the width of the milling rotor based on the dimensional parameters of the milling rotor, and use the width of the milling rotor of the milling machine as the actual milling width;

[0110] Step S352: Calculate the milling volume of the milling machine within a preset time period based on the milling rotor width, milling thickness, and milling speed.

[0111] In this embodiment, since the milling rotor width is equal to the actual milling width at the initial cut, after determining the milling rotor width, milling speed, and milling thickness in the aforementioned steps S351 and S352, the milling volume of the milling machine within a preset time period can be calculated directly through mathematical operations. Specifically, the volume of the milling area obtained by multiplying the milling rotor width, milling speed, and milling thickness is the milling volume.

[0112] The milling operation quantity detection method provided in a further embodiment of the present invention, such as Figure 11 As shown, it includes:

[0113] Step S100: Collect image information of the construction road surface within a preset time period using an image acquisition device;

[0114] Step S200: Determine the cutting condition for this milling operation by identifying whether there is a boundary line between the milled area and the area to be milled in the image information;

[0115] Step S300: Determine the milling volume of the milling machine within a preset time period based on the cutting conditions, the milling machine's dimensional parameters, operating parameters, and boundary line status information;

[0116] Step S400: Calculate the weight of material produced by the milling machine during the preset time period based on the material density and milling volume.

[0117] In this embodiment, based on the aforementioned embodiment, a further step S400 is added after step S300. Specifically, the operating parameters of the milling machine also include the material density of the milled road surface. After determining the milling volume, the weight of material generated by the milling operation within a preset time period can be calculated based on the milling volume and the material density of the milled road surface, thus providing auxiliary guidance for the material transportation process.

[0118] It is understandable that materials generated from milling operations need to be transported away from the construction site by material transport vehicles, and the transportation process must comply with relevant transportation regulations to prevent overloading. However, drivers of material transport vehicles cannot determine whether there is overloading by simply measuring the milling volume at the milling construction site. They need to weigh the materials at a designated weighing point. If overloading is found, the excess material must be unloaded, which seriously affects the normal construction operation process and construction and transportation efficiency.

[0119] In this embodiment, the milling volume and corresponding material weight are directly obtained through the detection process, which can provide auxiliary guidance for the material transport vehicle driver. The driver can know the weight of the milling material being carried at the receiving site, which can effectively avoid overloading and repeated unloading, and is conducive to improving construction efficiency and transportation efficiency.

[0120] It should be noted that in the above embodiments, the dimensional and operational parameters of the milling machine are preset information and can be pre-stored in the milling machine's controller. Furthermore, image information can be retrieved at different times within the preset time period based on varying detection accuracy requirements. For example, image information can be retrieved at preset intervals, or it can be retrieved after the milling machine has traveled a preset distance. It is understood that the shorter the time interval for retrieving image information, the greater the computational load, and the higher the accuracy of the detection results. In practical applications, appropriate time points can be selected to retrieve image information based on the required detection accuracy.

[0121] In addition, the method steps in the above embodiments can also be combined and applied according to actual needs, which will not be elaborated here.

[0122] In an embodiment of the second aspect of the present invention, a milling work volume detection system 100 is also provided, such as Figure 2 and Figure 12 As shown, the milling work volume detection system 100 includes an image acquisition unit 11, a controller 12, and a display device 13. When applied to a milling machine 200, the image acquisition unit 11 is positioned to the side of the milling machine 200 to acquire image information of the construction road surface in front of the milling machine 200. The controller 12 is communicatively connected to the image acquisition unit 11. The controller 12 can acquire the image information acquired by the image acquisition unit 11 and execute the milling work volume detection method in any embodiment of the first aspect described above, determining the milling work volume of the milling machine 200 through the image information. The display device 13 is communicatively connected to the controller 12. The controller 12 can control the display device 13 to display the corresponding milling work volume information to show the detection results to the operator.

[0123] The milling work volume detection system in this embodiment can detect the milling volume through image recognition. Moreover, it can use different calculation methods to calculate the volume according to different milling machine cutting conditions, which can effectively prevent work volume deviations and make the detection and calculation results more accurate, thus helping to reduce the rental costs for milling machine users.

[0124] Furthermore, the image acquisition device 11 includes, but is not limited to, cameras, video cameras, and webcams. Depending on actual usage needs, one or more image acquisition devices 11 can be configured, for example... Figure 2 and Figure 3 The two shown are respectively set on the left and right sides of the milling machine 200; preferably, the image acquisition device 11 is set on the side of the milling machine 200 near the front end, which can be close to the construction road surface in front of the milling machine 200 and the milled area 310 on the side, and can also avoid the view being blocked by the material conveying mechanism 230 at the front of the vehicle body.

[0125] Furthermore, the display device 13 can specifically be a dashboard, monitor, mobile terminal (phone, tablet computer), or other such device.

[0126] Furthermore, the milling work volume detection system in this embodiment also has all the beneficial effects of the milling work volume detection method in any of the above embodiments, which will not be repeated here.

[0127] In one embodiment of the third aspect of the present invention, a milling machine 200 is provided, such as... Figure 2 and Figure 13 As shown, the milling machine 200 includes the milling work volume detection system 100 in any of the above embodiments, which can detect the milling volume through image recognition and can use different calculation methods to calculate according to different milling machine cutting conditions, so that the detection and calculation results are more accurate.

[0128] Furthermore, the milling machine 200 in this embodiment also has all the beneficial effects of the milling work volume detection system 100 in any of the above embodiments, which will not be repeated here.

[0129] In one embodiment of the present invention, an electronic device is also provided. The electronic device includes a processor and a memory, wherein the memory stores a computer program suitable for execution on the processor. When the processor executes the computer program in the memory, it can implement the milling workload detection method of any of the above embodiments. Furthermore, the electronic device may also be provided with a communication interface and a communication bus, and the processor, communication interface, and memory communicate with each other through the communication bus. The electronic device in this embodiment has all the beneficial effects of the milling workload detection method of any of the above embodiments, and will not be elaborated further here.

[0130] In addition, one embodiment of the present invention provides a readable storage medium storing a computer program that, when executed by a processor, implements the milling workload detection method of any of the above embodiments. Therefore, the readable storage medium in this embodiment possesses all the beneficial effects of the milling workload detection method of any of the above embodiments, and will not be elaborated further here.

[0131] It should be noted that the computer program in the memory of the above embodiments can be implemented in the form of software functional units. When implemented in the form of software functional units and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the milling work quantity detection method of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0132] The basic principles of the present invention have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in the present invention are merely examples and not limitations, and should not be considered as essential features of each embodiment of the present invention. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the present invention to the necessity of employing the aforementioned specific details.

[0133] The block diagrams of the devices, apparatuses, devices, and systems involved in this invention are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it. It should also be noted that in the apparatuses and devices of this invention, the components can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered equivalents of the invention.

[0134] The computer program product of this invention can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on a user's computing device, partially on a user's device, as a standalone software package, partially on a user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. The above description has been given for illustrative and descriptive purposes. Furthermore, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although several exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

[0135] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the invention. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the invention. Therefore, the invention is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features of the invention herein.

[0136] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for detecting milling output, applied to a milling machine equipped with an image acquisition device, characterized in that, Milling operation quantity detection methods include: Step S100: Acquire image information of the construction road surface within a preset time period using the image acquisition device; Step S200: By identifying whether there is a boundary line between the milled area and the area to be milled in the image information, the cutting condition of the milling operation is determined; wherein, the cutting condition includes the initial cutting condition and the second cutting condition; Step S300: Determine the milling volume of the milling machine within the preset time period based on the cutting condition, the size parameters of the milling machine, the operating parameters, and the state information of the boundary line; When the cutting condition is a re-cutting condition, step S300: based on the cutting condition, the state information of the boundary line, and the dimensional parameters and operating parameters of the milling machine, determine the milling volume of the milling machine within the preset time period, including: Step S310: In the images corresponding to different times within the preset time period, identify the first coordinate information of the reference point on the boundary line relative to the viewpoint of the image acquisition device and the heading angle information of the boundary line. Step S320: Based on the first coordinate information of the reference point at different times, the heading angle information, and the size parameters and operating parameters of the milling machine, calculate the milling volume of the milling machine within the preset time period.

2. The milling operation quantity detection method according to claim 1, characterized in that, Step S310: In the images corresponding to different times within the preset time period, identify the first coordinate information of the reference point on the boundary line relative to the viewpoint of the image acquisition device and the heading angle information of the boundary line, including: Step S311: Establish a viewpoint coordinate system with the viewpoint of the image acquisition device as the origin, and establish a rotor center coordinate system with the center point of the milling rotor of the milling machine as the origin; Step S312: In the images corresponding to different times, select any point on the boundary line between the milled area and the area to be milled in the image as the reference point; Step S313: Determine the second coordinate information of the reference point in the rotor center coordinate system based on the image information; Step S314: Perform perspective transformation based on the second coordinate information to determine the first coordinate information of the reference point in the viewpoint coordinate system; Step S315: Determine the heading angle of the boundary line in the viewpoint coordinate system based on the first coordinate information.

3. The milling operation quantity detection method according to claim 2, characterized in that, Step S315: Determining the heading angle of the boundary line in the viewpoint coordinate system based on the first coordinate information includes: Step S3151: Determine the equation of the boundary line in the viewpoint coordinate system based on the first coordinate information; Step S3152: Determine the angle formed by the boundary line and the positive direction of the horizontal coordinate axis of the viewpoint coordinate system according to the straight line equation of the boundary line, and take the angle as the heading angle of the boundary line.

4. The milling operation quantity detection method according to claim 2, characterized in that, The operating parameters of the milling machine include milling thickness and milling speed; Step S320: Based on the first coordinate information of the reference point at different times, the heading angle information, and the size parameters and operating parameters of the milling machine, calculate the milling volume of the milling machine within the preset time period, including: Step S321: Calculate the actual milling width of the milling machine at each time based on the first coordinate information of the reference point at different times, the heading angle information, and the size parameters of the milling machine; Step S322: Calculate the milling area of ​​the milling machine within the preset time period by integrating the milling speed and the actual milling width of the milling machine at each moment according to the formula S=∫Li×Vi; where Li is the actual milling width and Vi is the milling speed. Step S323: Calculate the milling thickness and the milling area according to the formula V=S×Hi to calculate the milling volume of the milling machine within the preset time period; where V is the milling volume and Hi is the milling thickness.

5. The milling operation quantity detection method according to claim 4, characterized in that, The dimensional parameters of the milling machine include the dimensional parameters of the milling rotor and the position parameters of the image acquisition device relative to the milling rotor; Step S321: Based on the first coordinate information of the reference point at different times, the heading angle information, and the size parameters of the milling machine, calculate the actual milling width of the milling machine at each time, including: Step S3211: Determine the width of the milling rotor and the third coordinate information of the two ends of the milling rotor in the rotor center coordinate system according to the size parameters of the milling rotor; wherein, the third coordinate information includes the left end coordinate (Xl0,0) and the right end coordinate (Xr0,0) of the milling rotor. Step S3212: Based on the position parameters of the image acquisition device relative to the milling rotor, determine the fourth coordinate information of the viewpoint of the image acquisition device in the rotor center coordinate system; wherein, the image acquisition devices are provided on both the left and right sides of the milling machine, and the fourth coordinate information includes the coordinates (Xl, Yl) of the left image acquisition device and the coordinates (Xr, Yr) of the right image acquisition device. Step S3213: When the milled area is located on the right side of the milling machine, the actual milling width of the milling machine at each moment is calculated according to the formula Li=L0+(Xr-Xr0)+X0-(Y0+Yl)×tan(π / 2-θ); when the milled area is located on the left side of the milling machine, the actual milling width of the milling machine at each moment is calculated according to the formula Li=L0+(Xl-Xl0)+X0-(Y0+Yr)×tan(π / 2-θ); where L0 is the width of the milling rotor, (X0,Y0) is the first coordinate information of the reference point, and θ is the heading angle of the boundary line.

6. The milling operation quantity detection method according to claim 1, characterized in that, The dimensional parameters of the milling machine include the dimensional parameters of the milling rotor; The operating parameters of the milling machine include milling thickness and milling speed; When the cutting condition is the initial cutting condition, step S300: Based on the cutting condition, the state information of the boundary line, and the dimensional parameters and operating parameters of the milling machine, determine the milling volume of the milling machine within the preset time period, including: Step S351: Determine the width of the milling rotor according to the dimensional parameters of the milling rotor, and use the width of the milling rotor of the milling machine as the actual milling width; Step S352: Calculate the milling volume of the milling machine within the preset time period based on the milling rotor width, the milling thickness, and the milling speed.

7. The method for detecting milling output according to any one of claims 1 to 6, characterized in that, The operating parameters of the milling machine also include the material density of the milled road surface; The method for detecting milling work volume also includes: Step S400: Calculate the weight of material produced by the milling machine during the preset time period based on the material density and the milling volume.

8. A milling operation quantity detection system, characterized in that, include: An image acquisition device is located on the side of the milling machine, and the image acquisition device is used to acquire image information of the construction road surface in front of the milling machine; A controller, communicatively connected to the image acquisition unit, is adapted to perform the milling workload detection method as described in any one of claims 1 to 7, to determine the milling workload of the milling machine; The display device is communicatively connected to the controller and can output corresponding milling operation quantity information according to the control instructions of the controller.

9. A milling machine, characterized in that, include: The milling operation quantity detection system as described in claim 8.

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