CN118274712B

CN118274712B - Stockpile measuring system and stockpile measuring method

Info

Publication number: CN118274712B
Application number: CN202410419476.2A
Authority: CN
Inventors: 孔繁麟; 吴钰; 胡友德
Original assignee: Gusu Laboratory of Materials
Current assignee: Gusu Laboratory of Materials
Priority date: 2024-04-09
Filing date: 2024-04-09
Publication date: 2025-02-11
Anticipated expiration: 2044-04-09
Also published as: CN118274712A

Abstract

The disclosed embodiments provide a stockpile measurement system and a stockpile measurement method. The stockpile measurement system includes: a guide rail, a rail car, a laser radar, a motion measurement component, and a control processing device; the guide rail is parallel to the stacking surface of the stacked materials, is arranged above the stacked materials and extends along the first direction of the stacked materials; the rail car is used to extend and move along the guide rail; the motion measurement component is arranged on the rail car, and is used to measure the motion information of the rail car; the laser radar is arranged on the rail car, and is used to scan the surface of the stacked materials as the rail car moves to obtain point cloud data; the control processing device is used to determine the volume of the stacked materials based on the motion information and the point cloud data.

Description

Material piling measuring system and material piling measuring method

Technical Field

The invention relates to the field of information technology, in particular to a stacking measurement system and a stacking measurement method.

Background

Some mineral products such as coal and the like are usually stored in a storage yard in a stacking mode, and piles of coal piles and the like are formed in the storage yard. The stacking is usually large in occupied area, large in volume and irregular in shape. Along with the refinement of industrial and mining enterprise management, timely knowledge of the change of the volume and the weight of the stacking becomes an urgent requirement. For example, the requirements of steel plants on cost reduction and efficiency improvement are higher and higher, coal-saving becomes an important link of power generation enterprises, the use condition of coal is directly related to economic indexes of the steel plants, and the real-time performance and high precision of coal pile volume measurement become pursued targets. Therefore, how to determine the volume of the stacking material in time is a problem to be solved.

Disclosure of Invention

In view of this, embodiments of the present disclosure provide a stacking measurement system and a stacking measurement method.

According to a first aspect of an embodiment of the present disclosure, a stacker measurement system is provided, the stacker measurement system includes a guide rail, a railcar, a laser radar, a motion measurement assembly, and a control processing device;

The guide rail is parallel to the stacking surface of the stacking material, is arranged above the stacking material and extends along the first stacking direction of the stacking material;

The rail car is used for extending along the guide rail;

the motion measuring assembly is arranged on the railway car and used for measuring motion information of the railway car;

the laser radar is arranged on the rail car and used for scanning the surface of the stacking material when moving along with the rail car to obtain point cloud data;

and the control processing device is used for determining the volume of the stacking according to the motion information and the point cloud data.

With reference to some embodiments of the first aspect, in some embodiments, the control processing device is specifically configured to:

according to the motion information, determining pose information of the railcar at each scanning moment in the scanning process;

determining three-dimensional contour information for indicating the three-dimensional contour of the stacking according to the pose information of each scanning moment and the point cloud data of each scanning moment;

And determining the volume of the stacking according to the three-dimensional contour information.

determining the cross-sectional areas corresponding to N cross-sections of the three-dimensional profile of the stacking, wherein the N cross-sections are separated by a preset interval distance along the first direction, and N is an integer greater than or equal to 1;

And determining the volume of the stacking material based on the cross-sectional areas corresponding to the N cross sections and the preset interval distance.

With reference to some embodiments of the first aspect, in some embodiments, the three-dimensional profile information is used to indicate coordinates of a point cloud that forms the three-dimensional profile of the stack;

The control processing device is also used for at least one of the following:

Removing point clouds outside a preset coordinate range in the three-dimensional contour information;

Searching the point cloud of the three-dimensional profile of the stacking material by using a searching plane parallel to the stacking surface as a searching unit, determining that a first statistical value of a first coordinate value of the point cloud associated with the current searching plane in a second direction is larger than a first threshold value, and removing the point cloud associated with the current searching plane in the three-dimensional profile information, wherein the second direction is perpendicular to the stacking surface;

filtering the point cloud forming the three-dimensional profile of the stacking material;

And determining the coordinates of the empty defect cloud according to the linear interpolation result of the coordinates of a plurality of point clouds within the preset range of the empty defect cloud in the three-dimensional profile of the stacking.

Searching a point cloud of the three-dimensional profile of the stacking material by adopting a filtering plane parallel to the stacking surface as a filtering unit;

and determining the coordinate value of the point cloud associated with the front filtering plane in the second direction according to the calculation result of the second coordinate value of the point cloud associated with the current filtering plane in the second direction.

The calculation result comprises a second statistical value of second coordinate values of second point clouds remained after the first point cloud is removed in all point clouds associated with the current filtering plane,

The first point cloud includes:

A first duty ratio point cloud with a larger second coordinate value in all point clouds associated with the current filtering plane,

And the second coordinate value of the second ratio in all the point clouds associated with the current filtering plane is smaller.

With reference to some embodiments of the first aspect, in some embodiments, the control processing device includes a control unit disposed on the railcar and a processing unit disposed on the ground;

The control unit is used for at least one of the following:

Controlling movement of the railcar based on control information of the processing unit;

the motion information and the point cloud data are acquired and sent to the processing unit through communication connection between the control unit and the processing unit;

The control unit is used for determining the volume of the stacking material based on the motion information and the point cloud data.

According to a second aspect of embodiments of the present disclosure, there is provided a stacker measurement method, the method including:

The method comprises the steps of obtaining motion information and point cloud data, wherein the point cloud data are obtained by scanning the surface of a stacking material when a laser radar arranged on a railway vehicle moves along a guide rail, and the guide rail is parallel to the stacking surface for stacking the stacking material, is arranged above the stacking material and extends along a first stacking direction of the stacking material;

and determining the volume of the stacking according to the motion information and the point cloud data.

With reference to some embodiments of the second aspect, in some embodiments, the determining the volume of the heap according to the motion information and the point cloud data includes:

With reference to some embodiments of the second aspect, in some embodiments, the determining the volume of the stack according to the three-dimensional profile information includes:

With reference to some embodiments of the second aspect, in some embodiments, the three-dimensional profile information is used to indicate coordinates of a point cloud that forms the three-dimensional profile of the stack;

The method further comprises at least one of:

With reference to some embodiments of the second aspect, in some embodiments, the filtering the point cloud that forms the three-dimensional contour of the stack includes:

With reference to some embodiments of the second aspect, in some embodiments, the calculation result includes a second statistical value of second coordinate values of second point clouds remaining after the first point cloud is removed from all point clouds associated with the current filtering plane;

The first point cloud includes:

According to a third aspect of embodiments of the present disclosure, there is provided an electronic device, wherein the electronic device includes:

One or more processors;

The processor is used for calling an instruction to enable the electronic equipment to execute the stacking measurement method according to the first aspect.

According to a fourth aspect of embodiments of the present disclosure, a storage medium is provided, where the storage medium stores instructions that, when executed on a communication device, cause the communication device to perform the stacker measurement method of the second aspect.

The stacker measurement system comprises a guide rail, a rail car, a laser radar, a motion measurement assembly and a control processing device, wherein the guide rail is parallel to a stacking surface of a stacker, is arranged above the stacker and extends along a first stacking direction of the stacker, the rail car is used for extending along the guide rail to move, the motion measurement assembly is arranged on the rail car and is used for measuring motion information of the rail car, the laser radar is arranged on the rail car and is used for scanning the surface of the stacker when moving along with the rail car to obtain point cloud data, and the control processing device is used for determining the volume of the stacker according to the motion information and the point cloud data. So, carry on laser radar scanning windrow through the railcar that sets up in windrow top, and then confirm the volume of windrow by control processing device, on the one hand, confirm the windrow volume through laser radar's scan data, and then can confirm windrow weight etc. more convenient nimble through modes such as weighing relatively, need not to carry the windrow. On the other hand, the rail car moves along the rail, the pose is relatively stable, the obtained laser radar data is more accurate, and the measurement accuracy can be improved.

Drawings

FIG. 1 is a schematic diagram of a stacker measurement system according to an example embodiment;

FIG. 2 is a schematic diagram illustrating a structure of a stacker measurement system according to an example embodiment;

FIG. 3 is a schematic diagram illustrating a three-dimensional profile of a stacker according to an example embodiment;

FIG. 4 is a schematic diagram illustrating a three-dimensional profile of a stacker according to an example embodiment;

FIG. 5 is a schematic view of a three-dimensional contour slice of a stack, according to an exemplary embodiment;

FIG. 6 is a flow diagram illustrating a method of stacker measurement according to an example embodiment;

FIG. 7 is a flow chart illustrating a method of stacker measurement according to an example embodiment;

FIG. 8 is a flow chart illustrating a method of stacker measurement according to an example embodiment;

FIG. 9 is a flow chart illustrating a method of stacker measurement according to an example embodiment;

FIG. 10 is a schematic diagram illustrating a coal pile volume detection according to an exemplary embodiment;

Fig. 11 is a schematic diagram of an electronic device according to an exemplary embodiment.

Detailed Description

In order to make the technical scheme and the beneficial effects of the application more obvious and understandable, the following detailed description is given by way of example. Wherein the drawings are not necessarily to scale, and wherein local features may be exaggerated or minimized to more clearly show details of the local features, unless otherwise defined, technical and scientific terms used herein have the same meaning as those in the technical field to which the present application pertains.

The embodiments of the present disclosure are not intended to be exhaustive, but rather are exemplary of some embodiments and are not intended to limit the scope of the disclosure. In the case of no contradiction, each step in an embodiment may be implemented as an independent embodiment, and the steps may be arbitrarily combined, for example, a scheme in which part of the steps are removed in an embodiment may also be implemented as an independent embodiment, the order of the steps may be arbitrarily exchanged in an embodiment, further, alternative implementations in an embodiment may be arbitrarily combined, further, the embodiments may be arbitrarily combined, for example, part or all of the steps of different embodiments may be arbitrarily combined, and an embodiment may be arbitrarily combined with alternative implementations of other embodiments.

In the various embodiments of the disclosure, terms and/or descriptions of the various embodiments are consistent throughout the various embodiments and may be referenced to each other in the absence of any particular explanation or logic conflict, and features from different embodiments may be combined to form new embodiments in accordance with their inherent logic relationships.

The terminology used in the embodiments of the disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure.

In the presently disclosed embodiments, elements that are referred to in the singular, such as "a," "an," "the," "said," etc., may mean "one and only one," or "one or more," "at least one," etc., unless otherwise indicated. For example, where an article (article) is used in translation, such as "a," "an," "the," etc., in english, a noun following the article may be understood as a singular expression or as a plural expression.

In the presently disclosed embodiments, "plurality" refers to two or more.

In some embodiments, terms such as "at least one of (at least one of), at least one of (at least one of)", "one or more of", "multiple of", and the like may be substituted for each other.

In some embodiments, the recitations of "A, B at least one of", "A and/or B", "A in one instance, B in another instance", etc., may include the following technical solutions, A in some embodiments (A being performed independently of B), B in some embodiments (B being performed independently of A), A and B in some embodiments being selected for execution (A and B being selectively executed), A and B in some embodiments (both A and B being executed). Similar to the above when there are more branches such as A, B, C.

In some embodiments, the description modes such as A or B can comprise the following technical scheme, namely A (A is executed independently of B) in some embodiments, B (B is executed independently of A) in some embodiments, and A and B are selected to be executed (A and B are selectively executed) in some embodiments according to the situation. Similar to the above when there are more branches such as A, B, C.

The prefix words "first", "second", etc. in the embodiments of the present disclosure are only for distinguishing different description objects, and do not limit the location, order, priority, numerical value, content, etc. of the description objects, and the statement of the description object refers to the claims or the description of the embodiment context, and should not constitute unnecessary limitations due to the use of the prefix words. For example, if the description object is a "field", the ordinal words before the "field" in the "first field" and the "second field" do not limit the position or the order between the "fields", and the "first" and the "second" do not limit whether the "fields" modified by the "first" and the "second" are in the same message or not. For another example, describing an object as "level", ordinal words preceding "level" in "first level" and "second level" do not limit priority between "levels". For another example, the numerical value describing the object is not limited by ordinal words, and may be one or more, taking "first device" as an example, where the numerical value of "device" may be one or more. Further, the objects modified by different prefix words may be the same or different, for example, the description object is a "device", the "first device" and the "second device" may be the same device or different devices, the types of which may be the same or different, and, further, the description object is an "information", the "first information" and the "second information" may be the same information or different information, and the contents thereof may be the same or different.

In some embodiments, "comprising a", "containing a", "for indicating a", "carrying a", may be interpreted as carrying a directly, or as indicating a indirectly.

In some embodiments, the terms "a.m.", "determine a.m.", "in the case of a.m.", "when in a.m.", "if a.m." and "if a.m." can be replaced with each other.

In some embodiments, terms "greater than", "greater than or equal to", "not less than", "more than or equal to", "not less than", "above" and the like may be interchanged, and terms "less than", "less than or equal to", "not greater than", "less than or equal to", "not more than", "below", "lower than or equal to", "no higher than", "below" and the like may be interchanged.

In some embodiments, an apparatus or the like may be interpreted as an entity, or may be interpreted as a virtual, and the names thereof are not limited to the names described in the embodiments, "apparatus," "device," "circuit," "function," "unit," "component," "system," "network," "chip system," "entity," "body," and the like may be replaced with each other.

Furthermore, each element, each row, or each column in the tables of the embodiments of the present disclosure may be implemented as a separate embodiment, and any combination of elements, any rows, or any columns may also be implemented as a separate embodiment.

Fig. 1 is a diagram illustrating a stacker measurement system 10 according to an embodiment of the present disclosure, the stacker measurement system 10 comprising:

Rail 110, rail car 120, lidar 130, motion measurement assembly 140, control processing device 150;

The guide rail 110 is parallel to the stacking surface of the stacking material, is arranged above the stacking material and extends along the first stacking direction of the stacking material;

the rail car 120 is used for extending along the guide rail 110;

The motion measurement component 140 is disposed on the railcar 120 and is used for measuring motion information of the railcar 120;

the laser radar 130 is disposed on the railcar 120, and is configured to scan the surface of the stacker as the railcar 120 moves, so as to obtain point cloud data;

The control processing device 150 is configured to determine a volume of the stack according to the motion information and the point cloud data.

Here, the guide rail 110 may be installed in a stacking direction of a stacker (e.g., a coal pile), and the guide rail 110 may cover the entire stacker such that a travel range of the rail car 120 installed on the guide rail 110 may cover the entire stacker.

In one possible implementation, the rail car 120 may be powered by an external power source, or the rail car 120 may be powered by a power supply device, such as a battery, disposed on the rail car 120.

In one possible implementation, the motion measurement component 140 may be an inertial measurement device such as a gyroscope and/or accelerometer.

In one possible implementation, the motion information of the railcar 120 is used to indicate at least one of speed, acceleration, swing angle.

In one possible implementation, control processing device 150 may be located on railcar 120 or on the ground.

In one possible implementation, the control processing device 150 may also be used to at least one of obtain control information for a user and control movement of the railcar 120.

In one possible implementation, lidar 130 is fixedly coupled to railcar 120.

In one possible implementation, lidar 130 may include a single-wire lidar 130 capable of producing a single laser beam, or a multi-wire lidar 130 capable of producing multiple laser beams.

In one possible implementation, lidar 130 may scan the stack back and forth in a third direction during movement in the first direction and determine the coordinates of the different scan points in the first, second, and/or third directions based on the reflected laser light. Here, the coordinates of the scanning point may include coordinates with respect to the lidar 130.

The first direction, the second direction and the third direction are perpendicular to each other, the first direction is the direction of the guide rail 110, the third direction is the scanning direction of the laser radar 130, and the second direction can be the height direction of the stacking. The elevation information of the scanning points obtained by lidar 130 at different times and/or different locations constitutes point cloud data. For example, the point cloud data may include coordinates of different point clouds, and the like.

In one possible implementation, the coordinates of different point clouds in the point cloud data are associated with a timestamp. The point cloud data includes time stamps corresponding to the coordinates of different point clouds, and is used for determining the coordinates of different point clouds in the three-dimensional space in combination with the positions of the lidar 130 under the different time stamps.

Control processing device 150 may be in communication with lidar 130 for controlling the scanning of lidar 130 and obtaining point cloud data from lidar 130.

The control processing means 150 may be in communication with the motion measurement component 140 for obtaining motion information. For example, the control processing device 150 may be coupled to the motion measurement component 140 via I2C, serial communication, or the like.

The control processing device 150 may determine the pose of the railcar 120 at different times based on the motion information, and may determine the three-dimensional profile of the stockpile in combination with the point cloud data of the lidar 130, thereby determining the volume of the stockpile.

In this way, the laser radar 130 is carried on the railcar 120 above the stacking, so that the control processing device 150 can determine the volume of the stacking, on the one hand, the volume of the stacking can be determined according to the scanning data of the laser radar 130, and the weight of the stacking can be determined, so that the method is more convenient and flexible relative to the method of weighing, and the stacking is not required to be carried. On the other hand, the rail car 120 moves along the rail, the pose is relatively stable, the acquired laser radar 130 data is more accurate, and the measurement accuracy can be improved.

In some embodiments, as shown in fig. 2, the control processing device 150 includes a control unit 151 disposed on the railcar 120 and a processing unit 152 disposed on the ground;

the control unit 151 is configured to at least one of:

Controlling movement of the rail car 120 based on control information of the processing unit 152;

transmitting the acquired motion information and the point cloud data to the processing unit 152 through a communication connection between the control unit 151 and the processing unit 152;

the control unit 151 is configured to determine a volume of the stack based on the motion information and the point cloud data.

In one possible implementation, the control unit 151 may include an industrial personal computer or the like.

In one possible implementation, processing unit 152 may include an electronic device with data processing capabilities, such as a server.

The control unit 151 and the communication connection between the control units 151 may include at least one of a wired communication connection and a wireless communication connection. The wireless communication connection may include cellular wireless communication, wi-Fi, etc.

The railcar 120 moves back and forth along the guide rail 110, the laser radar 130 scans the material stack below to obtain point cloud data, the control unit 151 performs preliminary processing on the point cloud data, and then transmits the point cloud data to the processing unit 152 through communication connection, and the processing unit 152 establishes and determines the volume of the material stack according to the point cloud data.

The control unit 151 is disposed on the railcar 120, and may facilitate control of the railcar 120, the lidar 130, and the motion-measurement assembly 140 by the control unit 151. The processing unit 152 is arranged on the ground, so that the load of the rail car 120 can be reduced, the running stability of the rail car 120 can be improved, and the measurement accuracy can be further improved.

In some embodiments, the control processing device 150 is specifically configured to:

Determining pose information of the railcar 120 at each scanning moment in the scanning process according to the motion information;

In one possible implementation, the motion information is associated with a timestamp. I.e. the movement information is used to indicate the movement states, such as speed, etc., corresponding to the different time stamps. Thus, control processing device 150 may determine pose information for railcar 120 at different scanning moments based on the motion information. The pose information is used to indicate at least one of a position, a pose (e.g., yaw angle, pitch angle, etc.) of the railcar 120. Since lidar 130 is disposed on railcar 120, pose information of lidar 130 may be determined based on pose information of railcar 120.

In one possible implementation, the pose information of railcar 120 is the same as the pose information of lidar 130.

Based on pose information of the laser radar 130 at different moments and point cloud data of the laser radar 130 at different moments, point cloud coordinates of the whole stacking can be determined.

Here, the point cloud coordinates of the stacker may have a position fixed to the stacker relative position as the origin of the coordinate system.

In one possible implementation, the origin of the coordinate system may be the departure location of the railcar 120 during the measurement of the stockpile.

In one possible implementation, one end of the rail 110 may be used as the origin of the coordinate system.

In one possible implementation, the first direction may be an X-axis direction, the second direction may be a Z-axis direction, and the third direction may be a Y-axis direction.

Illustratively, with the direction of the guide rail 110 as the X axis, one end of the guide rail 110 is set as the origin (0, 0) of the coordinate system, and the position of the railcar 120 at the time t is calculated as (Xt, 0) according to the time stamp and the pose information of the railcar 120.

And calculating the stacking point cloud coordinates scanned at the moment t as (Xt+xi, yi, zi) according to the original point cloud data (Xi, yi, zi) of the laser radar 130.

In one possible implementation, the point cloud coordinates of the surface of the stacking profile may be determined, and the coordinates of the stacking surface may be used as the stacking bottom coordinates.

In this way, the point cloud coordinates of the three-dimensional profile of the stack can be determined, and the volume of the stack can be calculated based on the three-dimensional profile of the stack.

In some embodiments, the three-dimensional profile information is used to indicate coordinates of a point cloud constituting the stacker three-dimensional profile.

In some embodiments, the control processing device 150 is further configured to remove a point cloud outside a predetermined coordinate range in the three-dimensional profile information.

The point cloud obtained by lidar 130 is related to the angle at which lidar 130 scans.

As shown in fig. 3, the lidar 130 may obtain point cloud data of the external environment such as the wall, ceiling, etc. of the warehouse where the stacker is located. Therefore, in the stacker three-dimensional profile information, there may be point cloud coordinates of the external environment such as a wall, a ceiling, and the like.

Therefore, the boundary range of the stacking, that is, the preset coordinate range of the boundary of the stacking, can be preset, and the point cloud exceeding the preset coordinate range is removed from the three-dimensional contour information.

As shown in fig. 3, the Z-axis coordinate of the guide rail 110 is 0, and it can be considered that the point cloud with the Z-axis coordinate higher than the guide rail 110 is not the stacking point cloud, so that the point cloud data points with Zi >0 can be removed from the three-dimensional contour information, that is, invalid data above the guide rail 110 and on the ceiling are removed.

By removing the point cloud outside the preset coordinate range, the interference of the surrounding environment of the stacking to the three-dimensional profile of the stacking is reduced, and the accuracy of determining the stacking volume is improved.

In some embodiments, the control processing device 150 is further configured to search the point cloud of the three-dimensional profile of the stacking using a search plane parallel to the stacking surface as a search unit, determine that a first statistical value of a first coordinate value of the point cloud associated with the current search plane in a second direction is greater than a first threshold, and remove the point cloud associated with the current search plane in the three-dimensional profile information, where the second direction is perpendicular to the stacking surface.

The second direction is the stacking height direction. In some scenarios, posts, walls, etc. supporting the ceiling are provided in the stockyard, which posts, walls, etc. may be above the surface of the stockpile. Here, the three-dimensional profile of the stacker may be searched one by one in units of search planes.

For example, the search may be performed with Δx, Δy as search steps in the first direction (X-axis direction) and the third direction (Y-axis direction), that is, the Z-axis coordinate values of the point clouds within the rectangles having the length and width of Δx and Δy, respectively, are calculated. The point cloud associated with the current search plane includes point clouds with X-axis and Y-axis coordinates within the current search plane. Because the pillars, walls, etc. will be higher than the surface of the stacker, if the first statistic value of the first coordinate value of the point cloud associated with the current search plane in the second direction is greater than the first threshold value, it is indicated that the point cloud associated with the search plane is a pillar, wall, etc. with a high probability, and therefore the point cloud associated with the current search plane can be removed from the three-dimensional profile of the stacker.

In one possible implementation, the first threshold may be set based on a highest elevation of the stockpile, etc.

In one possible implementation, the first statistical value may include one of an average value, a median value, and the like.

For example, the contour boundary of the pile is searched, the search step size is set to be (Δx and Δy), the single-step search area is square, the diagonal vertices are (0, 0) and (Δx and Δy), all the point cloud coordinates Zi values falling within this range are found to be Z1, Z2,..zn, and the average value thereof is found to be (z1+z2.+zn)/n, and if the point cloud data where Zi is greater than the average value exceeds the set threshold P, the wall or the column is determined. Searching the whole XY plane, and removing the point clouds of the walls and the columns to obtain the contour point cloud data of the pure stacking.

By adopting the search plane to search the three-dimensional profile of the stacking, objects outside the stacking are removed, the interference of the objects outside the stacking on the three-dimensional profile of the stacking is reduced, and the accuracy of determining the stacking volume is improved.

In some embodiments, the control processing device 150 is further configured to filter the point cloud that forms the three-dimensional contour of the stack.

The three-dimensional profile of the stack is typically not smooth, increasing the complexity and computational effort of determining the volume based on the three-dimensional profile of the stack, etc. Therefore, the point cloud of the three-dimensional profile of the stacking material can be filtered, so that the complexity of the three-dimensional profile of the stacking material is reduced.

Here, filtering includes smoothing the three-dimensional profile of the stack, reducing abrupt changes in point cloud coordinates in one direction (e.g., the second direction).

The second direction is the stacking height direction. The three-dimensional profile of the stack can be searched one by one in units of a filtering plane.

For example, the search may be performed with Δx, Δy as the search step length in the first direction (X-axis direction) and the third direction (Y-axis direction), that is, the Z-axis coordinate values of the point clouds within the rectangles with the length and width of Δx and Δy, respectively, are counted, and the Z-axis counted result is used as the Z-axis coordinates of all the point clouds within the filtering plane. The point cloud associated with the current filtering plane includes point clouds with X-axis and Y-axis coordinates within the current filtering plane. Therefore, the point cloud of the filtering plane can be smoothed, and the complexity of the three-dimensional profile of the stacking is reduced.

The first point cloud includes:

For example, the Z-axis coordinate values of all the point clouds associated with the current filtering plane may be arranged in order of magnitude, a first proportion of the point clouds having larger Z-axis coordinate values in all the point clouds and a second proportion of the point clouds having smaller Z-axis coordinate values in all the point clouds may be removed, and the second statistical value of the Z-axis coordinate values of the remaining point clouds may be determined as the Z-axis coordinate values of all the point clouds associated with the current filtering plane.

In one possible implementation, the second statistical value comprises one of an average value, a median value.

For example, the single-step filtering area is a square with diagonal vertices (0, 0) and (Δx and Δy), all the point cloud coordinates Zi falling within the range are ranked with Z1, Z2,..zn, the minimum value of 10% and the maximum value of 10% are removed to obtain an average value Zp, only one point cloud data (Xi, zp) is reserved within the range, and the whole stacking area is filtered to obtain filtered stacking point cloud data.

In some embodiments, the control processing device 150 is further configured to determine coordinates of the empty defect cloud according to a linear interpolation result of coordinates of a plurality of point clouds within a predetermined range of the empty defect cloud in the three-dimensional profile of the stack.

In some scenes, the point clouds in the three-dimensional profile of the stockpile are not coherent due to the conditions of reflecting light, removing the point clouds and the like of the stockpile, and the condition of empty point clouds exists. Here, the difference processing may be performed on the space point cloud. And taking the linear interpolation result of the coordinates of a plurality of point clouds within a preset range of the empty point cloud as the coordinates of the empty point cloud.

Illustratively, at positions of three point clouds in succession along the Y-axis direction, the first point cloud coordinate is (X1, Y1, Z1), the third point cloud coordinate is (X3, Y1, Z3), the second point cloud is empty, which is located between the first point cloud and the third point cloud, interpolation calculation is performed based on the first point cloud coordinate and the third point cloud coordinate, and the interpolation result is taken as the coordinate of the second point cloud. For example, an average of the first point cloud coordinate and the third point cloud coordinate may be used as the coordinates of the second point cloud.

In practical applications, a linear interpolation result of coordinates of the null point cloud in a plurality of axis directions (X axis, Y axis and Z axis) may be used as the coordinates of the null point cloud. The principle is similar to the above example and will not be described here again.

By filling the empty point cloud of the three-dimensional profile of the stacking, the integrity of the three-dimensional profile of the stacking is improved, and the accuracy of determining the stacking volume is improved.

Exemplary, the three-dimensional profile of the stack after completion of point cloud removal, filtering, and void point cloud difference is shown in fig. 4.

As shown in fig. 5, the cross-sectional areas of N cross-sections spaced apart by a predetermined spacing distance in the first direction (X-axis direction) may be determined, and the sum of products of each cross-sectional area multiplied by the predetermined spacing distance, respectively, may be taken as the volume of the stack.

In one possible implementation, the predetermined separation distance may be determined based on a scan interval of lidar 130.

For example, if lidar 130 is a single-line lidar 130, the predetermined separation distance may be determined based on a scanning separation of the single-line laser in a third direction (Y-axis direction). If the lidar 130 is a single-line lidar 130, the predetermined separation distance may be determined based on the separation of the two laser beams in the third direction (Y-axis direction) onto the stack.

For example, as shown in fig. 5, the point cloud data is sequentially sliced in the direction of the third direction (Y-axis direction) along the first direction (X-axis direction) of the guide rail 110, the thickness is X0, n slices are obtained, the area of each slice is S (Yi, zi) by gridding, and the further stacking volume can be expressed by expression (1).

Thus, the volume of the stacking is determined according to the three-dimensional profile of the stacking.

Fig. 6 is a diagram illustrating a stacker measurement method according to an embodiment of the present disclosure, as shown in fig. 6, the method including:

step 601, acquiring motion information and point cloud data, wherein the point cloud data is obtained by scanning a stacking surface of a rail car 120 along with a laser radar 130 arranged on the rail car 120 when the rail car 120 moves along a guide rail 110, wherein the guide rail 110 is parallel to a stacking surface for stacking the stacks and is arranged above the stacks and extends along a first stacking direction;

And step 602, determining the volume of the stacking according to the motion information and the point cloud data.

The stacker measuring method of the embodiment of the present disclosure may be applied to the control processing device 150 in the stacker measuring system as shown in fig. 1 and/or fig. 2.

Here, the guide rail 110 may be erected in the stacking direction of the stacker, and the guide rail 110 may cover the entire stacker so that the travel range of the rail car 120 erected on the guide rail 110 may cover the entire stacker.

In one possible implementation, lidar 130 is fixedly coupled to railcar 120.

In some embodiments, the step 602 includes:

FIG. 7 is a diagram illustrating a method of stacking measurement, three-dimensional profile information indicating coordinates of a point cloud constituting the three-dimensional profile of the stack, according to an embodiment of the present disclosure;

The stacking measurement method as shown in fig. 7 may include at least one of:

Step 701, removing point clouds outside a preset coordinate range in the three-dimensional contour information;

Step 702, searching point clouds of the three-dimensional profile of the stacking by using a searching plane parallel to the stacking surface as a searching unit, determining that a first statistical value of a first coordinate value of the point clouds associated with the current searching plane in a second direction is larger than a first threshold value, and removing the point clouds associated with the current searching plane in the three-dimensional profile information, wherein the second direction is perpendicular to the stacking surface;

step 703, filtering the point cloud forming the three-dimensional profile of the stacking material;

And step 704, determining coordinates of the empty defect cloud according to linear interpolation results of the coordinates of a plurality of point clouds within a preset range of the empty defect cloud in the three-dimensional profile of the stacking material.

In some embodiments, the filtering the point cloud that forms the three-dimensional profile of the heap includes:

In some embodiments, the calculation result comprises a second statistical value of second coordinate values of second point clouds remaining after the first point cloud is removed in all point clouds associated with the current filtering plane;

The first point cloud includes:

In some embodiments, the determining the volume of the stack from the three-dimensional profile information comprises:

For example, as shown in fig. 5, the point cloud data is sequentially sliced in the direction of the third direction (Y-axis direction) along the first direction (X-axis direction) of the guide rail 110, the thickness is X0, n slices are obtained, the area of each slice is S (Yi, zi) by gridding, and the further stacking volume can be expressed by expression (1). Thus, the volume of the stacking is determined according to the three-dimensional profile of the stacking.

A number of specific examples are provided below in connection with any of the embodiments described above:

as shown in fig. 1 or 2, the stacker measuring system is composed of a guide rail 110, a rail car 120, an industrial personal computer (i.e., a control unit 151), an inertial measurement unit (i.e., a motion measuring assembly 140), a laser radar 130, and a server (i.e., a processing unit 152).

The guide rail 110 is a steel rail and is erected above a pile (coal pile) along a straight line, and is kept level with the ground.

The rail car 120 is hung on the guide rail 110 and can move along the guide rail 110 in a linear manner, and the rail car 120 can be provided with a power supply for supplying power to vehicle-mounted instruments.

The industrial personal computer is installed on the railcar 120, has data processing capability, wired communication capability and wireless communication capability, and the wireless communication mode is 5G or WIFI, and can also receive a server instruction to control the railcar 120 to advance or retreat.

The inertial measurement unit may provide speed and acceleration information, and may be mounted on the rail car 120 to communicate with the industrial personal computer via an I2C bus or serial port.

The laser radar 130 may provide the original data of the scanning point cloud, and the model may be a single-line laser radar 130 or a multi-line laser radar 130, which is installed on the railcar 120 and is in wired communication with the industrial personal computer.

The server is installed on the ground, has wireless communication capability, and can send control commands such as start, stop and the like to the controller.

The railcar 120 moves back and forth along the guide rail 110, the laser radar 130 scans the coal pile below to obtain point cloud data, the industrial personal computer performs preliminary processing on the point cloud data and then transmits the point cloud data to the server through wireless transmission (5G or Wifi), the server builds a three-dimensional model according to the point cloud data, an envelope map of the coal pile is formed, and the volume of the coal pile is calculated, wherein the schematic diagram is as follows. If there is a vehicle in the room, the arrangement of the guide rail 110 and the rail car 120 can be omitted, the industrial personal computer, the inertial measurement unit and the laser radar 130 can be installed on the vehicle, and the vehicle can be equivalent to the rail car 120.

As shown in fig. 8, the measurement procedure of the specific stacker measurement system is as follows:

step 801, a server sends a start command to an industrial personal computer.

Step 802, after the industrial personal computer receives the starting instruction, the railway vehicle runs to one end of the railway.

803, The railcar uniformly advances to the other end of the track, and the laser radar starts scanning. The industrial personal computer records data of the inertial measurement unit at each moment and original point cloud data of the laser radar, and sends the data to the server.

And 804, stopping sending data by the industrial personal computer when the rail car runs to the other end of the rail, and informing the server that the data acquisition is completed.

Step 805, the server calculates the total volume of the coal pile. The server converts the original point cloud data into point cloud data under a Cartesian coordinate system, a 3-dimensional model is formed through methods of filtering, interpolation and the like, and a coal pile envelope surface is drawn. Slicing the data of the coal pile along the vertical direction of the guide rail, calculating the area of each slice, multiplying the area of each slice by the thickness of each slice to obtain the volume of each slice, and accumulating to obtain the total volume of the coal pile.

As shown in fig. 9, the specific flow of the data processing performed by the server in step 805 is as follows:

And step 8051, determining the positions of the rail cars at all moments. And taking the track direction as an X axis, setting one end of the track as an origin (0, 0) of a coordinate system, and calculating the position of the track car at the time t as (Xt, 0) according to the time stamp and the inertial navigation unit data.

Step 8052, determining three-dimensional point cloud coordinates, and removing invalid data. According to laser radar original point cloud data (Xi, yi, zi), calculating original contour three-dimensional point cloud coordinates scanned at the moment t as (Xt+xi, yi, zi), removing point cloud data points with Zi >0, namely removing invalid data above a track and a ceiling, and obtaining point cloud data of a coal pile mixed wall and a pillar.

Step 8053, searching point cloud data which do not belong to the coal pile in the three-dimensional profile. Searching the contour boundary of the coal pile, setting the searching step length as delta x and delta y, setting the single-step searching area as square, setting the diagonal vertex as (0, 0) and delta x and delta y, finding all the point cloud coordinate Zi values falling in the range as Z1, Z2, and calculating the average value of Zn as (Z1+Z2+).

+Zn)/n, and if the point cloud data where Zi is greater than the average value exceeds the set threshold value P, the wall or column is determined. Searching the whole XY plane, and removing the point clouds of the wall and the column to obtain the contour point cloud data of the pure coal pile.

Step 8054, filtering the three-dimensional contour. Further carrying out average value filtering on the coal pile profile point cloud, wherein a single-step filtering area is square with diagonal peaks (0, 0) and (delta x and delta y), and coordinates of all the point clouds falling in the range are obtained

The Zi values are Z1, Z2,. Zn is sequenced, 10% of the minimum value and 10% of the maximum value are removed, an average value Zp is obtained, only one point cloud data (Xi, zp) is reserved in the range, and the whole coal pile area is filtered, so that filtered coal pile point cloud data are obtained.

Step 8055, compensating the missing point cloud in the three-dimensional contour point cloud. Further processing a coal pile point cloud data hole (missing point cloud) caused by coal pile reflection, performing linear interpolation by using effective point cloud data adjacent to the hole, and calculating to obtain approximate point cloud data at the hole.

Step 8056, slicing the three-dimensional contour points, and calculating the volume piece by piece to obtain the total volume. Slicing the point cloud data along the vertical direction of the guide rail, wherein the thickness is X0, obtaining n slices, and obtaining the area of each slice by gridding to obtain S (Yi, zi), wherein the volume of the coal pile is further as shown in the expression (1).

Step 806, the server continues to send a start command to the industrial personal computer, and the steps 801 to 805 are repeated unless a stop command is sent to the server.

Step 807, the server draws a graph of the real-time dynamic coal pile volume according to the coal pile volume measured each time (as shown in fig. 10), and can draw the graph in hours on a daily basis.

If the space is available in the room, the technical scheme of the embodiment can save the arrangement of the guide rail and the rail car, and has higher economical efficiency.

The calculation of the coal pile profile point cloud coordinates depends on the data of the inertial navigation unit, and the airlines or the rail cars are allowed to stop, pause and change speed during the running process. The guide rail is linearly erected, the pose of the railway car is relatively stable, the obtained laser radar data are more accurate, the method has more advantages with manual scanning or unmanned aerial vehicle scanning, and the accuracy is higher.

WIFI and 5G can be selected to the communication mode, to less space, can use the WIFI signal to improve economic nature, to great space, can use 5G signal to improve stability.

Judgment on the ceiling, the wall and the pillars above the track is added in the data processing of the coal pile profile point cloud coordinates, a large amount of invalid data is removed, and the calculation of the pillar volume into the coal pile is avoided.

The average value filtering of the coal pile profile point cloud eliminates invalid data caused by the influence of the laser radar or the environment, and greatly reduces the processing amount of the point cloud data.

The linear interpolation of the coal pile profile point cloud eliminates the point cloud data cavity caused by the reflection of the coal pile surface.

The server is the brain of the whole system, can control the operation of the system 24 hours after starting, draw the volume graph of the coal pile, have realized unmanned on duty.

Fig. 11 is a schematic structural diagram of an electronic device 9100 provided by an embodiment of the present disclosure. The electronic device 9100 may be a computer device, a terminal, a chip system, a processor or the like that supports a network device to implement any of the above methods, or a chip, a chip system, a processor or the like that supports a terminal to implement any of the above stacker measurement methods. The electronic device 9100 may be used to implement the stacking measurement method described in the above method embodiment, and specifically, reference may be made to the description in the above method embodiment.

As shown in fig. 11, the electronic device 9100 includes one or more processors 9101. The processor 9101 may be a general-purpose processor or a special-purpose processor, and may be a central processing unit, for example. The processor 9101 is configured to invoke instructions to cause the electronic device 9100 to perform any of the above methods of stacker measurement. The specific implementation steps of the stacking measurement method are as in the above embodiments, and are not described herein.

It will be understood by those of ordinary skill in the art that the names of processors are not limited to those described in the embodiments, and that terms such as "processor", "controller", "central processor (Central Processing Unit, CPU)", "micro-control unit (Microcontroller Unit, MCU)", "sensor processor (Microcontroller Unit, MCU)", "micro-processing unit (Micro Processing Unit, MCU)", "microprocessor (Micro Processing Unit, MCU)", etc. may be replaced with each other.

The computing power of the processor 9101 may be configured based on the actual requirements in performing the steps of stacking measurement, filtering, and the like. For example, a processor of X86 architecture (e.g., dual core, 1.5G primary CPU) may be employed, and ARM, MIPS architecture may be employed, but is not limited thereto.

In some embodiments, electronic device 9100 further comprises one or more memories 9102 for storing instructions. Alternatively, all or a portion of memory 9102 may be external to electronic device 9100.

In one possible implementation, the data stored by the memory 9102 further includes, but is not limited to, at least one of:

Data generated by the processor in the process of executing the stacking measurement method;

data generated by the lidar.

The capacity of the memory 9102 may be determined based on the stored data, and the duration of the stored data (e.g., the duration of the stored three-dimensional point cloud data). For example, the memory storage capacity may be greater than or equal to 500 gigabytes.

In some embodiments, the electronic device 9100 further comprises one or more transceivers 9103. Where the electronic device 9100 includes one or more transceivers 9103, the steps of transmitting, receiving, and/or acquiring of the methods described above are performed by the transceivers 9103, and the other steps are performed by the processors 9101.

The transceiver 9103 may transmit data directly from the control unit 151 and the processing unit 152 when the stacker measuring method is performed, but is not limited thereto. The transceiver 9103 may include a wired transceiver and a wireless transceiver. The bandwidth of the transceiver 9103 may be greater than or equal to 100Mbps.

For example, the wired transceiver may include an Ethernet transceiver, may include a 100M Ethernet transceiver, a 1000M Ethernet transceiver, etc., but is not limited thereto. The wireless transceiver may include a Wi-Fi transceiver, may include a 2.5Gwi-Fi transceiver, a 5Gwi-Fi transceiver, and the like, but is not limited thereto.

In some embodiments, the steps of obtaining and the like in the above method may also be performed by the processor 9101, for example, obtaining information from the memory 9102 and the like.

Optionally, the electronic device 9100 further includes one or more interface circuits 9104, where the interface circuits 9104 are connected to the memory 9102, and the interface circuits 9104 can be used to receive signals from the memory 9102 or other apparatus, and can be used to send signals to the memory 9102 or other apparatus. For example, the interface circuit 9104 may read instructions stored in the memory 9102 and send the instructions to the processor 9101.

The electronic device 9100 in the above embodiment description may be a network device or a terminal, but the scope of the electronic device 9100 described in the present disclosure is not limited thereto, and the structure of the electronic device 9100 may not be limited by fig. 11. The electronic device may be a stand-alone device or may be part of a larger device. The electronic device may be, for example, (1) a stand-alone integrated circuit IC, or chip, or a system or subsystem of chips, (2) a set of one or more ICs, which may optionally also include storage means for storing data, programs, (3) an ASIC, such as a Modem, (4) a module that may be embedded in other devices, (5) a receiver, terminal device, smart terminal device, cellular telephone, wireless device, handset, mobile unit, vehicle-mounted device, network device, cloud device, artificial smart device, etc., (6) and so forth.

It will be appreciated by those of ordinary skill in the art that implementing all or part of the steps of the above method embodiments may be accomplished by hardware associated with program commands, and that the above program may be stored in a storage medium, including a removable Memory device, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic or optical disk, or other various media that can store program code.

Or the above-described integrated units of the application may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium, comprising several commands for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present application. The storage medium includes various media capable of storing program codes such as a removable storage device, a ROM, a RAM, a magnetic disk or an optical disk.

It should be understood that the above examples are illustrative and are not intended to encompass all possible implementations encompassed by the claims. Various modifications and changes may be made in the above embodiments without departing from the scope of the disclosure. Likewise, the individual features of the above embodiments can also be combined arbitrarily to form further embodiments of the invention which may not be explicitly described. Therefore, the above examples merely represent several embodiments of the present invention and do not limit the scope of protection of the patent of the present invention.

Claims

1. The system for measuring the stacking material is characterized by comprising a guide rail, a rail car, a laser radar, a motion measuring assembly and a control processing device;

The guide rail is parallel to the stacking surface of the stacking material, is arranged above the stacking material and linearly extends along a first stacking direction of the stacking material, wherein the first direction is the guide rail direction, and the second direction is the stacking height direction;

The rail car is used for extending along the guide rail;

The laser radar is arranged on the railway vehicle and used for scanning the surface of the stacking material along a third direction when moving along with the railway vehicle to obtain point cloud data, wherein the first direction, the second direction and the third direction are mutually perpendicular;

the control processing device is used for determining the volume of the stacking according to the motion information and the point cloud data;

the control processing device is specifically configured to:

determining the volume of the stacking according to the three-dimensional contour information;

the three-dimensional contour information is used for indicating coordinates of point clouds forming the three-dimensional contour of the stacking material;

The control processing device is further used for searching the point cloud of the three-dimensional profile of the stacking by using a searching plane parallel to the stacking surface as a searching unit, determining that a first statistical value of a first coordinate value of the point cloud associated with the current searching plane in the second direction is larger than a first threshold value, and removing the point cloud associated with the current searching plane in the three-dimensional profile information, wherein the second direction is perpendicular to the stacking surface, the searching plane is square with a side length being a searching step length, and the searching plane searches the point cloud of the three-dimensional profile of the stacking by using the searching step length;

The control processing device is also used for filtering the point cloud forming the three-dimensional profile of the stacking;

the control processing device is specifically configured to:

Determining the coordinate value of the point cloud associated with the current filtering plane in the second direction according to the calculation result of the second coordinate value of the point cloud associated with the current filtering plane in the second direction;

The calculation result comprises a second statistical value of second coordinate values of second point clouds remaining after the first point cloud is removed in all point clouds associated with the current filtering plane;

The first point cloud includes:

2. The system according to claim 1, characterized in that said control processing means are specifically adapted to:

3. The system of claim 1, wherein the three-dimensional profile information is used to indicate coordinates of a point cloud constituting the three-dimensional profile of the stack;

The control processing device is also used for at least one of the following:

4. A system according to any one of claims 1 to 3, wherein the control processing means comprises a control unit provided on the railcar and a processing unit provided on the ground;

The control unit is used for at least one of the following:

5. A method of stacking measurements, the method comprising

The method comprises the steps of obtaining motion information and point cloud data, wherein the point cloud data are obtained by scanning a stacking surface along a third direction when a laser radar arranged on a railway vehicle moves along a guide rail, the guide rail is parallel to a stacking surface for stacking the stacks and is arranged above the stacks and linearly extends along a first direction for stacking the stacks, the motion information is obtained by measuring the motion of the railway vehicle through a motion measuring assembly arranged on the railway vehicle, the first direction is a guide rail direction, the second direction is a stacking height direction, and the first direction, the second direction and the third direction are mutually perpendicular;

determining the volume of the stacker according to the motion information and the point cloud data;

The determining the volume of the stacking according to the motion information and the point cloud data comprises the following steps:

searching the point cloud of the three-dimensional profile of the stacking material by using a searching plane parallel to the stacking surface as a searching unit, determining that a first statistical value of a first coordinate value of the point cloud associated with the current searching plane in the second direction is larger than a first threshold value, and removing the point cloud associated with the current searching plane in the three-dimensional profile information, wherein the second direction is perpendicular to the stacking surface, the searching plane is a square with a side length being a searching step length, and the searching plane searches the point cloud of the three-dimensional profile of the stacking material by using the searching step length;

the method further includes filtering a point cloud constituting the three-dimensional profile of the stack;

the filtering the point cloud forming the three-dimensional profile of the stacking material comprises the following steps:

The first point cloud includes:

6. An electronic device, wherein the electronic device comprises:

One or more processors;

wherein the processor is configured to invoke instructions to cause the electronic device to perform the method of claim 5.

7. A storage medium storing instructions that, when executed on a communication device, cause the communication device to perform the method of claim 5.