CN109948189B - Material volume and weight measuring system for excavator bucket - Google Patents
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Abstract
The invention relates to a measuring system for the volume and weight of a material of an excavator bucket, which belongs to the technical field of weighing of hydraulic excavator buckets and comprises the following components: laser radar, computing device, preprocessing device, manipulation display device. According to the invention, a laser radar device is used for realizing the measurement of the dynamic volume and weight of materials in the bucket in the operation process of the excavator; the three-dimensional modeling can be effectively performed on the empty bucket, the point cloud registration fusion is performed on the bucket filled with the materials in the subsequent excavation operation process, the problem that the point cloud data acquisition is limited in incomplete point cloud acquisition due to object shielding is solved, the measurement accuracy is improved, and the complexity of the measurement device is reduced.
Description
Technical Field
The invention relates to a bucket material volume and weight measurement system based on laser point cloud, and belongs to the technical field of bucket weighing of hydraulic excavators.
Background
The excavator has wide application fields, and can work differently in cooperation with different devices. In the open-pit mining engineering, the excavator can strip the surface of minerals to finish the excavation and loading and unloading of the minerals. Particularly, when the excavator is matched with a truck for loading, if the weight of the excavated materials can be known, the truck for matched loading and transportation can be prevented from being overloaded or underloaded, and accurate loading can be completed. The data can also be recorded in construction data, and the excavator is reasonably distributed and scheduled according to construction data statistical analysis, so that the production efficiency is improved.
Patent CN106460372a, method and system for actual responsible weight of mining excavation equipment, determining an excavation surface shape based on a scanned excavation surface, identifying an excavation path from the excavation equipment, actually calculating a volume of excavation based on the excavation surface and the excavation path, calculating weight from a density factor. Disadvantages of patent CN106460372 a: the method comprises the steps of scanning an excavation surface around excavation equipment by using a plurality of laser radars, collecting each point in a plurality of scanned images, determining the shape of the excavation surface, enabling materials in an excavation path to be shielded by excavation auxiliary equipment, recording the excavation path by using equipment such as an encoder, removing the points in the excavation path, and calculating and processing are complex.
In the patent CN103900669B, pressure sensors are additionally arranged on an oil cylinder of a movable arm and an oil cylinder of a bucket arm, an inclination angle sensor and a gyroscope are additionally arranged on the movable arm, the bucket arm and the bucket, and the dynamic weighing of bucket materials is realized according to a Kane kinetic equation. Disadvantages of patent CN 103900669B: the sensor of the patent is connected with the data acquisition module through the inclination sensor, the gyroscope and the pressure sensor, the system is complex, the gravity center of the bucket in the dynamic model is not well and accurately measured, and the calculated weight accuracy of the materials has an influence.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a measuring system for the volume and the weight of the material of the bucket of the excavator, which uses a laser radar to scan the bucket containing the material in the process of the excavator operation, thereby realizing the weight measurement of the bucket material with the following characteristics: (1) Weight measurement can be completed in the working process of the excavator; (2) The three-dimensional point cloud modeling can be effectively carried out on the empty bucket, and the point cloud fusion is carried out on the bucket filled with the materials in the later operation process, so that the limitation of incomplete point cloud acquisition caused by the fact that the point cloud data acquisition is shielded by an object is solved; (3) The complexity of the weight measuring device is reduced, and the measuring precision is improved.
In order to achieve the above object, the present invention adopts the following technical scheme: an excavator bucket material volume and weight measurement system, comprising:
the laser radar is used for dynamically scanning the three-dimensional point cloud of the bucket filled with the materials, and transmitting the scanned original three-dimensional point cloud data containing the ground, the movable arm, the bucket rod, the bucket and the material information to the computing device through the communication link;
the computing device is used for receiving the empty bucket three-dimensional point cloud data and the empty bucket volume which are obtained by the processing of the preprocessing device through a communication link; receiving original three-dimensional point cloud data containing a bucket filled with materials, which are obtained by laser radar scanning, through a communication link; processing by a series of algorithms: denoising, clustering, segmentation and ICP iterative fusion to obtain point cloud data of a bucket only containing materials; calculating the volume of a bucket containing the material, calculating the volume of the material by combining the volume of an empty bucket, and calculating the weight of the material according to the density of the material;
the preprocessing device is used for processing the three-dimensional CAD structural model of the empty bucket, generating three-dimensional point cloud data of the empty bucket, calculating the volume of the empty bucket, and transmitting the generated three-dimensional point cloud data of the empty bucket and the calculated volume of the empty bucket to the calculating device through a communication link;
the control display device is used for setting the densities of different materials, and collecting and displaying the results calculated by the calculation device to an operator.
The working process of the pretreatment device is as follows:
(1) Importing a CAD model of the empty bucket into Meshlab software, and generating three-dimensional point cloud data of the empty bucket by using an algorithm provided by the Meshlab software;
(2) The point cloud is decomposed into a network of geometric figures of triangles using triangulation methods. A point-by-point insertion method is used for establishing a topological structure in a triangular net, new points are continuously inserted to form new triangles, adjacent relations of different triangles are updated, and an empty bucket is divided into a plurality of tetrahedrons. Then, calculating the empty bucket volume according to the tetrahedron;
(3) And sending the result obtained by the pretreatment to a computing device through a communication link.
When the laser radar is arranged at the design installation position, the laser radar is installed at the top of the cab of the excavator by combining the specific structural size of the excavator and laser radar parameters, so that the operation radius interval is covered by the vertical scanning of the laser radar.
Determining an effective scanning range according to the working radius of the excavator and parameters of the laser radar; when the inclination angle AS2 of the excavator movable arm is between A1 and A2 degrees, the angle AS3 between the bucket rod and the movable arm is between A3 and A4 degrees, and the bucket angle is between A5 and A6 degrees, the above angle ranges are the ranges for effectively collecting point cloud data.
In a computing device, the processing is performed by a series of algorithms: removing outliers, super-body clustering, CPC constraint plane segmentation, ICP iteration and fusion matching to obtain point cloud data of a bucket only containing materials; and calculating the volume of the bucket with the material by using a triangular splitting method, subtracting the volume of the bucket with the empty bucket to obtain the volume of the material, and calculating the weight of the material according to the density of the material.
Determining boundaries of an interior surface of the bucket and the payload using the empty bucket point cloud data; matching bucket point cloud data containing materials with empty bucket point cloud data obtained by preprocessing, estimating the pose of the point cloud containing the material bucket relative to the known empty bucket point cloud data by using an ICP iterative nearest point algorithm, obtaining the minimum value of an objective function through iteration, and obtaining two matched point cloud sets of the pose through matrix transformation; two point clouds refer to bucket point cloud data containing material and empty bucket point data obtained by preprocessing.
The bucket volume with materials is calculated by using a triangle splitting method specifically comprises the following steps: triangulating the bucket with the material into tetrahedrons, and calculating the bucket volume with the material.
The process of gathering data using a laser scanner is dynamic and does not require the bucket to be fixed in a particular position.
Specifically, the working flow of the excavator bucket material volume and weight measurement system is as follows:
(1) Importing a bucket CAD model of the excavator into merhlab software to generate a three-dimensional point cloud model of the empty bucket;
(2) Obtaining the volume of the empty bucket by using a triangulation method;
(3) Scanning a bucket filled with materials in an effective range through an installed laser radar to obtain original point cloud data containing ground, a movable arm, a bucket rod, the bucket and the materials;
(4) Filtering the point cloud obtained by scanning in the step (3) to remove outliers;
(5) Dividing the part of the point cloud containing the bucket from the point cloud containing the ground, the movable arm, the bucket rod and the bucket (namely, the point cloud obtained in the step (4)) by adopting a method of super-body clustering and constrained plane segmentation; obtaining a bucket point cloud filled with materials;
(6) Estimating the bucket posture relative to the empty bucket point cloud model by utilizing an ICP algorithm, and carrying out matching fusion on the empty bucket point cloud and the bucket point cloud filled with materials;
(7) Calculating the integral volume of the bucket filled with the materials after fusion by using a triangulation method;
(8) Calculating the volume of the material;
(9) And calculating the weight of the material.
More specifically, the work flow of the excavator bucket material volume and weight measurement system is as follows:
a. importing a CAD model of the empty bucket into Meshlab software, and generating three-dimensional points of the empty bucket by using an algorithm provided by the software;
b. establishing a three-dimensional point cloud data model of the empty bucket;
c. decomposing point-to-empty bucket point cloud data into a network of geometric figures formed by triangles by utilizing a triangle splitting method, establishing a topological structure in the triangle network by utilizing a point-by-point insertion method, continuously inserting new points to form new triangles and updating adjacent relations of different triangles, finally dividing the bucket into a plurality of tetrahedrons, calculating the volumes of the tetrahedrons, obtaining the volumes of the empty bucket, and calculating the volume V of the empty bucket according to the volumes of the tetrahedrons Empty space ；
d. In the dynamic operation process of the excavator, a bucket filled with materials is scanned in an effective range through an installed laser radar, and original point cloud data containing the ground, a movable arm, a bucket rod, the bucket and the materials are obtained;
e. filtering point clouds obtained by laser radar scanning, using the distance from the point to the adjacent point based on input data as a criterion, if the average distance from the point to the adjacent point is out of the range of the global average distance A7, regarding the point as an outlier, removing the outlier from the data set, and generating point cloud data after removing the outlier;
f. clustering the point cloud data with the outlier removed into small blocks with basic characteristic meaning aggregation of the ground, the movable arm, the bucket rod and the bucket by using an ultra-body clustering algorithm; dividing the small blocks in a characteristic sense by adopting a CPC constraint plane dividing method, determining dividing points by utilizing concave-convex relations among different small blocks, and determining a divided plane according to different dividing points;
g. dividing the part of point cloud containing the bucket through the divided plane to obtain bucket point cloud data containing materials;
h. determining boundaries of an inner surface and a payload of a bucket by using empty bucket point cloud data, matching bucket point cloud data containing materials with empty bucket point cloud obtained by preprocessing, wherein the newly obtained bucket point cloud data containing materials is in different coordinate systems with an empty bucket point cloud model and has direction and position changes due to bucket movement in the process of digging, and estimating the pose of the point cloud containing the materials relative to the known empty bucket point cloud data by using an optimal matching ICP iterative nearest point algorithm based on a least square method. And obtaining translation parameters and rotation parameters meeting the requirements of the objective function through an ICP iterative algorithm. In the matching process, the successful point-to-point registration fusion of the control points is ensured. The formula of the point cloud matching objective function of the rotation matrix R and the translation matrix t is as follows:
wherein the two point clouds are respectively point set X= { X needing to be matched in the empty bucket model point cloud 1 ，x 2 ，...，x n Real-time detected point set Y= { Y needing to be matched in point cloud filled with materials 1 ，y 2 ，...，y n Solving a rotation matrix R and a translation matrix t through singular value transformation; and obtaining pose matching by the two point clouds through transformation, and obtaining the fused point cloud.
i. Decomposing the fused point cloud set containing the material bucket into a network of geometric figures formed by triangles by utilizing a triangulation method, establishing a topological structure in the triangle network by utilizing a point-by-point insertion method, continuously inserting new points to form new triangles and updating adjacent relations of different triangles, dividing the bucket containing the material into a plurality of tetrahedrons, and then calculating the bucket volume V containing the material according to the tetrahedron volume Material ；
j. Subtracting the volume of the empty bucket from the bucket volume containing the material calculated in the step i to obtain the volume of the material;
V target volume ＝V Material -V Empty space
k. Multiplying the volume of the material by the density of the material to obtain the weight of the material;
M material ＝ρ*V Target volume
And d-k, namely realizing the dynamic volume and weight measurement in the working process of the excavator.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, a laser radar device is used for realizing the measurement of the dynamic volume and weight of materials in the bucket in the operation process of the excavator; the three-dimensional modeling can be effectively performed on the empty bucket, the point cloud registration fusion is performed on the bucket filled with the materials in the subsequent excavation operation process, the problem that the point cloud data acquisition is limited in incomplete point cloud acquisition due to object shielding is solved, the measurement accuracy is improved, and the complexity of the measurement device is reduced.
Drawings
FIG. 1 is a control block diagram of a system of the present invention;
FIG. 2 is a schematic view of the laser radar installation of the present invention;
FIG. 3 is a schematic diagram of a laser radar scanning acquisition point cloud data within the effective range of the present invention;
FIG. 4 is a flow chart of the volume and weight calculation of the present invention.
Detailed Description
In order to achieve the above objective, referring to fig. 1, a system for measuring the volume and weight of a bucket of an excavator at least comprises a multi-line laser radar, a computing device, an operation display device and a preprocessing device.
The multi-line laser radar is used for scanning three-dimensional point clouds of the bucket filled with materials, and transmitting scanned original three-dimensional point cloud data containing information such as ground, movable arms, bucket and the like to the computing device through a communication link (such as Ethernet).
The computing device is used for receiving the empty bucket three-dimensional point cloud data and the empty bucket volume which are obtained by the pretreatment device through a communication link (such as USB or Ethernet); receiving original three-dimensional point cloud data containing a bucket filled with materials, which are obtained by multi-line laser radar scanning, through a communication link (such as Ethernet); processing by a series of algorithms: denoising, clustering, segmentation and ICP iterative fusion to obtain point cloud data of a bucket only containing materials; calculating the volume of the bucket containing the material, calculating the volume of the material by combining the volume of the empty bucket, and calculating the weight of the material according to the density of the material.
The preprocessing device is used for processing the three-dimensional CAD structural model of the empty bucket, generating three-dimensional point cloud data of the empty bucket, calculating the volume of the empty bucket, and sending the generated three-dimensional point cloud data of the empty bucket and the calculated volume of the empty bucket to the calculating device through a communication link. The communication link may be one or more of usb can network cables, but is not limited thereto, and the communication link adapted to the vehicle environment may be used.
The control display device is used for setting the densities of different materials, and collecting and displaying the results calculated by the calculation device to an operator.
In order to obtain a point cloud of a bucket filled with material, the lidar needs to be mounted in an advantageous scanning position. According to the invention, the laser radar is arranged at the front part of the top of the cab of the excavator by combining the structural size of the excavator and the laser radar parameters, so that the vertical scanning range of the laser radar can cover an effective excavation operation interval, and meanwhile, the laser radar and the bucket are positioned on the rotary platform, thereby reducing the influence of the rotation of the vehicle body on the scanning point cloud.
In order to obtain effective scanning data of a bucket containing materials, the invention determines an effective scanning range through experiments according to the working radius of the excavator and parameters of a laser radar; when the excavator boom inclination angle AS2 is between A1 and A2 degrees, the angle AS3 between the arm and the boom is between A3 and A4 degrees, and the bucket angle is between A5 and A6 degrees, effective bucket point cloud data can be obtained (A1 … A6 is determined by experiments according to specific boom, arm and bucket sizes).
In order to calculate the volume and weight of material in an excavator bucket, the calculation process of the invention is as follows:
firstly, importing a bucket CAD model of an excavator into merhlab software to generate a three-dimensional point cloud model of an empty bucket; splitting the three-dimensional point cloud model of the empty bucket by utilizing a triangulation method to generate a tetrahedron; and calculating the volume of the tetrahedron, and further obtaining the volume of the empty bucket.
Secondly, scanning a bucket filled with materials in an effective range by using a laser radar in the process of excavating operation of the excavator; filtering the point cloud obtained by scanning to remove outliers; the point cloud data after the filtering process includes not only the bucket but also information such as the boom, the arm, the ground, and the like. Thus, in order to obtain a point cloud containing only a bucket, the point cloud of the bucket needs to be separated from the point cloud of other excavating arms, backgrounds and the like, and the point cloud containing information such as the ground, the bucket, the movable arms and the like is segmented by using an ultra-body clustering algorithm, so that the point cloud is segmented into a plurality of small blocks with adjacent relations; and carrying out semantic segmentation on the point cloud small blocks subjected to the ultra-volume clustering by using a CPC algorithm, judging the concave-convex relation among the small blocks by connecting a central line vector and a normal vector between adjacent small blocks and whether the adjacent small blocks are communicated, and determining a segmented plane by concave-convex information of the point cloud so as to obtain bucket point cloud data only containing materials.
Finally, when the bucket is filled with materials, the data such as the inner surface of the bucket cannot be scanned, and in order to determine the effective boundary of the bucket and the complete three-dimensional point cloud data of the bucket containing the materials, an iterative closest point ICP algorithm is used for matching the three-dimensional point cloud data, and the point cloud data of the bucket containing the materials and the point cloud data of the empty bucket are fused. The fused point cloud is the complete point cloud with the bucket information of the materials; the triangulation method is also used for dividing and calculating the fused point cloud, so that the bucket volume (comprising the bucket volume and the volume of the material) containing the material is obtained. Subtracting the volume of the empty bucket from the bucket volume with the material to obtain the volume of the material; the material weight was then further determined by the density of the different materials.
In combination with fig. 2, the laser radar is installed at the front part of the top of the cab of the excavator by combining the structural size of the excavator and the laser radar parameters, so that the laser radar and the bucket are positioned on the rotary platform while the vertical scanning range of the laser radar can cover an effective excavation operation interval, and the influence of the rotation of the vehicle body on the scanning point cloud is reduced.
Referring to fig. 3, an effective scanning range is determined according to parameters of an excavator working radius and a laser radar; when the inclination angle AS2 of the excavator boom is between A1 and A2 degrees, the angle AS3 between the bucket rod and the boom is between A3 and A4 degrees, and the bucket angle is between A5 and A6 degrees, the range is the range of effectively collecting point cloud data (A1 … A6 is determined by experiments according to specific boom, bucket rod and bucket sizes). In one embodiment, the laser radar is used for scanning the materials in the bucket AS an effective range, the inclination angle AS2 of the movable arm is 30-60 degrees, the angle AS3 between the bucket rod and the movable arm is 45-90 degrees, and the bucket angle AS4 is 90-180 degrees, so that the laser radar is an effective point cloud data scanning range.
Meanwhile, as can be seen from fig. 3, even in the effective scanning range, the point cloud data scanned by the laser radar contains the point cloud information of the ground, the movable arm, the bucket rod and the bucket in a complex manner.
Referring to fig. 4, the volume and weight calculation of the present invention is divided into two major parts, wherein steps 1 to 3 are pretreatment parts, and only one treatment is needed for different buckets; step 4 to 10, calculating the volume and weight of the material, and circularly and dynamically measuring the material in the process of excavation operation; the whole flow is detailed as follows:
(1) Firstly, a designated CAD model of the empty bucket of the excavator is imported into Meshlab software, and the CAD model is used for generating three-dimensional point cloud data of the empty bucket by using an algorithm provided by the software;
(2) Using triangle splitting method to emptyThe bucket point cloud is decomposed into a network of geometric figures consisting of triangles, a topological structure is established in the triangle network by using a point-by-point insertion algorithm, and the bucket is finally divided into a plurality of tetrahedrons. We find the volume on tetrahedrons formed every four points to obtain the volume of the whole bucket, there may be shared points and shared faces between different tetrahedrons, but there is no overlapping area (referring to the area that can be used to calculate the volume), thus making the volume calculation of the whole bucket accurate. Calculating the empty bucket volume V according to the tetrahedral volume formula Empty space ；
(3) In the dynamic operation process of the excavator, a bucket filled with materials is scanned in an effective range through an installed laser radar, and original point cloud data containing a plurality of targets such as ground, movable arms, bucket arms, buckets and materials are obtained.
(4) Filtering the original point cloud data obtained by scanning, filtering the point cloud obtained by scanning, obtaining the average distance between each point and the point in the neighborhood of the point, forming a sample by the average distance of each point in the neighborhood, and obtaining the mean value and the variance according to the data of the sample. And if the average distance of a certain point is out of the average value, the point cloud data is considered as an outlier and is removed from the data set, and finally the point cloud data with the outlier removed is generated.
(5) And clustering the point cloud data with the outlier removed into a plurality of small blocks by using a super-body clustering algorithm, and calculating the concave-convex relation among different small blocks by adopting an extended convex quasi-measurement and perfecting criterion algorithm after performing super-body segmentation on the point cloud data. After the concave-convex relation is obtained, a weight is given to each point cloud by the CPC constraint plane segmentation method, and the concave block is assigned with 1 and the other points are assigned with 0. Points perpendicular to the concave edge surface have higher weights and finally plane cuts are made by random sample consensus algorithm (RanSaC).
(6) The part of the point cloud of the bucket can be segmented from the whole point cloud data through the segmentation plane, and bucket point cloud data containing materials are obtained.
(7) Determining boundaries of an inner surface and a payload of a bucket by using empty bucket point cloud data, matching bucket point cloud data containing materials with empty bucket point cloud obtained by preprocessing, wherein the newly obtained bucket point cloud data containing materials is in different coordinate systems with an empty bucket point cloud model and has direction and position changes due to bucket movement in the process of digging, and estimating the pose of the point cloud containing the materials relative to the known empty bucket point cloud data by using an optimal matching ICP iterative nearest point algorithm based on a least square method. And obtaining translation parameters and rotation parameters meeting the requirements of the objective function through an ICP iterative algorithm. In the matching process, the successful point-to-point registration fusion of the control points is ensured. The formula of the point cloud matching objective function of the rotation matrix R and the translation matrix t is as follows:
wherein the two point clouds are respectively point set X= { X needing to be matched in the empty bucket model point cloud 1 ，x 2 ，...，x n Real-time detected point set Y= { Y needing to be matched in point cloud filled with materials 1 ，y 2 ，...，y n Solving a rotation matrix R and a translation matrix t through singular value transformation; and obtaining pose matching by the two point clouds through transformation, and obtaining the fused point cloud.
(8) Obtaining the fused bucket point cloud in the step (7), solving the volume of the fused bucket point cloud, and calculating the bucket volume V containing the materials according to the tetrahedron volume in the same step (2) Material ；
(9) The calculated bucket volume containing the material is subtracted from the previous empty bucket volume to obtain the volume of the material;
V target volume ＝V Material -V Empty space
(10) Multiplying the volume of the material by the density of the material to obtain the weight of the material;
M material ＝ρ*V Target volume
And (3) circulating the steps 3-10 to realize the dynamic volume and weight measurement in the working process of the excavator.
The invention uses a laser radar device to realize dynamic material weight calculation in the process of excavator operation; the three-dimensional modeling can be effectively performed on the empty bucket, and the point cloud registration fusion is performed on the bucket filled with the materials in the later operation, so that the incomplete limitation that the point cloud data acquisition is blocked by objects and the like is solved; the complexity of the weight calculation device is reduced, and the measurement accuracy is improved.
Abbreviation and key term definitions
Bucket material-the material loaded in the bucket after an excavator uses its bucket to excavate material to be excavated.
Point cloud-a data set of points of the product's apparent surface obtained by measuring instruments in reverse engineering.
Triangle splitting- -the curved surface is split into curved-sided triangles, and any two such curved-sided triangles either do not intersect or intersect exactly on a common side.
An outlier-is a data object that is significantly different from other data objects in that the proximity between an outlier object and its nearest neighbors in the feature space significantly deviates from the proximity between other objects in the dataset and their own nearest neighbors.
Super-body clustering-implementing over-segmentation on point cloud, clouding scene points into a plurality of small blocks, and researching the relation among each small block. Essentially, the method is to summarize the local part, the texture, the material and the similar color part can be automatically divided into one piece, and the super-body clustering is beneficial to the subsequent recognition work.
CPC constrained planar segmentation-the method of determining segmentation points using the concave-convex relationship between different patches and then determining the segmented plane from the different segmentation points can divide an object into meaningful patches.
ICP algorithm-optimal registration fusion method based on least square method, the algorithm repeatedly selects corresponding relation point pairs, and calculates optimal rigid transformation until meeting convergence accuracy requirement of correct registration fusion.
Registration fusion-carrying out coordinate system transformation on point cloud data measured in different coordinate systems so as to obtain an integral data model.
It should be noted that the foregoing embodiments of the present invention are merely examples, and are not intended to limit the scope of the present invention, and all equivalent structures or equivalent processes using the content of the present invention or direct or indirect application in other related technical fields are included in the scope of the present invention.
Claims (10)
1. An excavator bucket material volume and weight measurement system, comprising:
the laser radar is used for dynamically scanning the three-dimensional point cloud of the bucket filled with the materials, and transmitting the scanned original three-dimensional point cloud data containing the ground, the movable arm, the bucket rod, the bucket and the material information to the computing device through the communication link;
the computing device is used for receiving the empty bucket three-dimensional point cloud data and the empty bucket volume which are obtained by the processing of the preprocessing device through a communication link; receiving original three-dimensional point cloud data containing a bucket filled with materials, which are obtained by laser radar scanning, through a communication link; processing by a series of algorithms: denoising, clustering, segmentation and ICP iterative fusion to obtain point cloud data of a bucket only containing materials; calculating the volume of a bucket containing the material, calculating the volume of the material by combining the volume of an empty bucket, and calculating the weight of the material according to the density of the material;
the preprocessing device is used for processing the three-dimensional CAD structural model of the empty bucket, generating three-dimensional point cloud data of the empty bucket, calculating the volume of the empty bucket, and transmitting the generated three-dimensional point cloud data of the empty bucket and the calculated volume of the empty bucket to the calculating device through a communication link;
the control display device is used for setting the densities of different materials, and collecting and displaying the results calculated by the calculation device to an operator.
2. The system for measuring the volume and weight of the material in the bucket of the excavator according to claim 1, wherein the pretreatment device comprises the following working procedures:
(1) Importing a CAD model of the empty bucket into Meshlab software, and generating three-dimensional point cloud data of the empty bucket by using an algorithm provided by the Meshlab software;
(2) Decomposing the point cloud set into a network of geometric figures consisting of triangles by using a triangulation method; a topological structure is built in a triangular net by using a point-by-point insertion method, new points are continuously inserted to form new triangles, adjacent relations of different triangles are updated, and an empty bucket is divided into a plurality of tetrahedrons; then, calculating the empty bucket volume according to the tetrahedron;
(3) And sending the result obtained by the pretreatment to a computing device through a communication link.
3. The excavator bucket material volume and weight measurement system of claim 1 wherein the lidar is mounted on top of the excavator cab in combination with specific structural dimensions of the excavator and lidar parameters such that the vertical sweep of the lidar covers the working radius interval.
4. An excavator bucket material volume and weight measurement system as defined in claim 1 wherein the effective scan range is determined based on excavator work radius and laser radar parameters; when the inclination angle AS2 of the excavator movable arm is between A1 and A2 degrees, the angle AS3 between the bucket rod and the movable arm is between A3 and A4 degrees, and the bucket angle is between A5 and A6 degrees, the above angle ranges are the ranges for effectively collecting point cloud data.
5. An excavator bucket material volume and weight measurement system as defined in claim 1 wherein the computing device processes by a series of algorithms: removing outliers, super-body clustering, CPC constraint plane segmentation, ICP iteration and fusion matching to obtain point cloud data of a bucket containing materials; and calculating the volume of the bucket with the material by using a triangular splitting method, subtracting the volume of the bucket with the empty volume to obtain the volume of the material, and calculating the weight of the material according to the density of the material.
6. The excavator bucket material volume and weight measurement system of claim 5 wherein the computing device uses the empty bucket point cloud data to determine the boundaries of the bucket's interior surface and the payload; matching bucket point cloud data containing materials with empty bucket point cloud data obtained by preprocessing, estimating the pose of the point cloud containing the materials relative to the known empty bucket point cloud data by using an ICP iterative nearest point algorithm, obtaining the minimum value of an objective function through iteration, and obtaining two matched point clouds of the pose through matrix transformation; two point clouds refer to bucket point cloud data containing material and empty bucket point data obtained by preprocessing.
7. The system for measuring the volume and weight of the material in the bucket of the excavator according to claim 5, wherein the calculation of the volume of the bucket with the material by using the triangle splitting method is specifically as follows: triangulating the bucket with the material into tetrahedrons, and calculating the bucket volume with the material.
8. An excavator bucket material volume and weight measurement system as defined in claim 5 wherein the process of collecting data using the laser scanner is dynamic without the need to fix the bucket in a particular position.
9. The excavator bucket material volume and weight measurement system of claim 1 wherein the excavator bucket material volume and weight measurement system workflow is:
(1) Importing a bucket CAD model of the excavator into merhlab software to generate a three-dimensional point cloud model of the empty bucket;
(2) Obtaining the volume of the empty bucket by using a triangulation method;
(3) Scanning a bucket filled with materials in an effective range through an installed laser radar to obtain original point cloud data containing ground, a movable arm, a bucket rod, the bucket and the materials;
(4) Filtering the point cloud obtained by scanning in the step (3) to remove outliers;
(5) Dividing the part of the point cloud containing the bucket from the point cloud containing the ground, the movable arm, the bucket rod and the bucket by adopting a super-body clustering and constraint plane dividing method; obtaining a bucket point cloud filled with materials;
(6) Estimating the bucket posture relative to the empty bucket point cloud model by utilizing an ICP algorithm, and carrying out matching fusion on the empty bucket point cloud and the bucket point cloud filled with materials;
(7) Calculating the integral volume of the bucket filled with the materials after fusion by using a triangulation method;
(8) Calculating the volume of the material;
(9) And calculating the weight of the material.
10. The excavator bucket material volume and weight measurement system of claim 1 wherein the excavator bucket material volume and weight measurement system workflow is:
a. importing a CAD model of the empty bucket into Meshlab software, and generating three-dimensional point cloud data of the empty bucket by using an algorithm provided by the software;
b. decomposing point-to-empty bucket point cloud data into a network of geometric figures formed by triangles by utilizing a triangle splitting method, establishing a topological structure in the triangle network by utilizing a point-by-point insertion method, continuously inserting new points to form new triangles and updating adjacent relations of different triangles, finally dividing the bucket into a plurality of tetrahedrons, calculating the volumes of the tetrahedrons, obtaining the volumes of the empty bucket, and calculating the volume V of the empty bucket according to the volumes of the tetrahedrons Empty space ；
c. In the dynamic operation process of the excavator, a bucket filled with materials is scanned in an effective range through an installed laser radar, and original point cloud data containing the ground, a movable arm, a bucket rod, the bucket and the materials are obtained;
d. filtering point clouds obtained by laser radar scanning, using the distance from the point to the adjacent point based on input data as a criterion, and if the average distance from the point to the adjacent point is out of the global average distance range, regarding as an outlier and removing the outlier from the data set to generate point cloud data after the outlier is removed;
e. clustering the point cloud data with the outlier removed into small blocks with basic characteristic meaning aggregation of the ground, the movable arm, the bucket rod and the bucket by using an ultra-body clustering algorithm; determining a dividing point by adopting a CPC constraint plane dividing method and utilizing concave-convex relations among different small blocks, and then determining a divided plane according to different dividing points;
f. dividing the part of point cloud containing the bucket through the divided plane to obtain bucket point cloud data containing materials;
g. determining boundaries of the inner surface and the payload of the bucket by using empty bucket point cloud data, matching bucket point cloud data containing materials with empty bucket point cloud obtained by preprocessing, wherein the newly obtained bucket point cloud data containing materials and an empty bucket point cloud model are in different coordinate systems and have direction and position changes due to bucket movement in the process of digging, and estimating the attitude of the point cloud containing the material bucket relative to the known empty bucket point cloud data by using an optimal matching ICP iterative nearest point algorithm based on a least square method; obtaining translation parameters and rotation parameters meeting the requirements of an objective function through an ICP iterative algorithm; in the matching process, the successful point-to-point registration fusion of the control points is ensured; the formula of the point cloud matching objective function of the rotation matrix R and the translation matrix t is as follows:
wherein the two point clouds are respectively point set X= { X needing to be matched in the empty bucket model point cloud 1 ，x 2 ，…，x n Point set Y= { Y needing to be matched in point cloud with materials detected in real time 1 ，y 2 ，…，y n Solving a rotation matrix R and a translation matrix t through singular value transformation; obtaining pose matching by the two point clouds through transformation, and obtaining fused point clouds;
i. decomposing the fused point cloud set containing the material bucket into a network of geometric figures formed by triangles by using a triangulation method, establishing a topological structure in the triangle network by using a point-by-point insertion method, continuously inserting new points to form new triangles and updating adjacent relations of different triangles, and dividing the bucket containing the material into a plurality of four sidesThe volume of the bucket containing the material is then calculated from the tetrahedral volume Material ；
j. Subtracting the volume of the empty bucket from the bucket volume containing the material calculated in the step i to obtain the volume of the material;
V target volume ＝V Material -V Empty space
k. Multiplying the volume of the material by the density of the material to obtain the weight of the material;
M material ＝ρ*V Target volume
And d-k, namely realizing the dynamic volume and weight measurement in the working process of the excavator.
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