CN109670250B - Method and system for automatically evaluating accessibility of maintenance equipment - Google Patents
Method and system for automatically evaluating accessibility of maintenance equipment Download PDFInfo
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Abstract
The invention discloses a method and a system for automatically evaluating accessibility of maintenance equipment. The evaluation method comprises the following steps: acquiring virtual arm data and virtual maintenance object data; extracting a first virtual maintenance object feature point based on an adjacent point normal vector included angle feature point extraction algorithm according to the virtual maintenance object data; extracting a second virtual maintenance object feature point based on a vertex saliency feature point extraction algorithm according to the virtual maintenance object data; constructing a virtual arm kinematics model according to the virtual arm data; determining the reachable domain of the tail end of the virtual arm or the tail end of the maintenance tool according to the kinematic model of the virtual arm; performing space subdivision on the reachable domain, and determining a feature point set; and determining the reachability evaluation result of the maintenance equipment according to the first virtual maintenance object characteristic point, the second virtual maintenance object characteristic point and the characteristic point set. According to the evaluation method and the system provided by the invention, the reachability evaluation result of the maintenance equipment can be automatically determined, and the accuracy of the reachability evaluation result is improved.
Description
Technical Field
The invention relates to the field of maintenance operation, in particular to a method and a system for automatically evaluating accessibility of maintenance equipment.
Background
In order to ensure that the equipment has better use reliability and lower full life cycle cost, maintainability design and verification become an indispensable research field in the design process of the equipment. In the virtual maintenance environment, the maintenance process of the equipment can be simulated, meanwhile, a large amount of data generated in the simulation process can provide powerful support for analysis and evaluation of equipment maintenance accessibility, maintenance time, maintenance safety and the like, defects in the aspect of equipment maintainability design are found in advance, improvement suggestions and the like are provided, and potential problems related to the aspect of product maintainability are solved in the early stage of the design. Accessibility refers to whether a maintenance part is within the reach of the virtual human arm or the hand tool after the maintenance station of the maintenance person is determined in the maintenance operation. Accessibility is the most important design criterion in the qualitative requirements for serviceability and is the first element of the design analysis for serviceability.
Virtual repair techniques provide a realistic simulation environment for repair. However, the development of the virtual maintenance technology is still immature, and the maintenance evaluation work based on the virtual maintenance technology is mainly qualitative evaluation at present, so that an objective, quantitative and comprehensive evaluation method is lacked. In the accessibility evaluation, a virtual human arm enveloping sphere is constructed mainly by utilizing an analysis tool provided by DELMIA software, and an evaluator obtains a maintenance accessibility evaluation result by observing the relative position relationship between a maintenance part and the arm enveloping sphere. Many scientific research institutes and colleges at home and abroad make a great deal of research work on maintainability design theory and analysis method, and a lot of quantitative evaluation methods are also provided in accessibility evaluation. However, these evaluation methods also have the problems of subjective qualitative and expert experience dependence, etc., a large number of subjective behaviors exist in the evaluation process, objective data cannot be given to support the evaluation result, and the accessibility evaluation result has low accuracy.
Disclosure of Invention
The invention aims to provide an automatic reachability evaluation method and system for maintenance equipment, and aims to solve the problem that in the existing reachability evaluation process of the maintenance equipment, the reachability evaluation result is low in accuracy due to the fact that objective data cannot be provided due to strong subjective awareness and dependence on expert experience.
In order to achieve the purpose, the invention provides the following scheme:
an automatic reachability evaluation method for maintenance equipment, comprising:
acquiring virtual arm data and virtual maintenance object data;
extracting a first virtual maintenance object feature point based on an adjacent point normal vector included angle feature point extraction algorithm according to the virtual maintenance object data;
extracting a second virtual maintenance object feature point based on a vertex saliency feature point extraction algorithm according to the virtual maintenance object data;
constructing a virtual arm kinematics model according to the virtual arm data;
determining a reachable domain of the tail end of the virtual arm or the tail end of the maintenance tool according to the kinematic model of the virtual arm;
performing space subdivision on the reachable domain, and determining a feature point set;
determining a reachability evaluation result of the maintenance equipment according to the first virtual maintenance object feature point, the second virtual maintenance object feature point and the feature point set; the reachability evaluation result includes that the repair part is within the repair reach and that the repair part is not within the repair reach.
Optionally, the extracting, according to the virtual maintenance object data, a first virtual maintenance object feature point based on an adjacent point normal vector included angle feature point extraction algorithm specifically includes:
describing a virtual maintenance object by adopting a triangular mesh model;
traversing each edge of the triangular network model, and judging whether the edge only has one adjacent point to obtain a first judgment result;
if the first judgment result shows that only one adjacent point exists on the edge, determining two end points of the edge as first virtual maintenance object characteristic points;
if the first judgment result shows that the edge has more than one adjacent point, determining a normal vector included angle between the adjacent points;
judging whether the weight of the normal vector included angle is smaller than a weight threshold value or not to obtain a second judgment result;
and if the second judgment result shows that the weight of the normal vector included angle is smaller than a weight threshold value, determining that the two end points of the edge are first virtual maintenance object characteristic points.
Optionally, the extracting, according to the virtual maintenance object data, a second virtual maintenance object feature point based on a vertex saliency feature point extraction algorithm specifically includes:
calculating the height difference between adjacent vertexes in the triangular mesh model;
determining the average height difference of each vertex according to the height difference;
and extracting a second virtual maintenance object feature point according to the average height difference.
Optionally, the constructing a virtual arm kinematics model according to the virtual arm data specifically includes:
determining the rotational freedom of the virtual arm according to the virtual arm data; the rotational freedom degree comprises a shoulder joint rotational freedom degree, an elbow joint rotational freedom degree and a wrist joint rotational freedom degree;
determining a relative transformation matrix among all joints according to the rotational freedom; the relative transformation matrix comprises a transformation matrix of the elbow joint relative to the shoulder joint, a transformation matrix of the wrist joint relative to the elbow joint and a transformation matrix of the arm tail end operation point relative to the wrist joint;
and constructing a virtual arm kinematics model according to the relative transformation matrix.
Optionally, the determining a reachability evaluation result of the maintenance device according to the first virtual maintenance object feature point, the second virtual maintenance object feature point, and the feature point set specifically includes:
judging whether each first virtual maintenance object feature point and each second virtual maintenance object feature point belong to the feature point set or not to obtain a third judgment result;
if each first virtual maintenance object feature point and each second virtual maintenance object feature point of the third judgment result all belong to the feature point set, determining that the accessibility evaluation result is that the maintenance component is in a maintenance accessible range;
and if each first virtual maintenance object feature point and each second virtual maintenance object feature point of the third judgment result do not all belong to the feature point set, determining that the accessibility evaluation result is that the maintenance component is not within the maintenance accessibility range.
An automatic reachability evaluation system for maintenance equipment, comprising:
the data acquisition module is used for acquiring virtual arm data and virtual maintenance object data;
the first virtual maintenance object feature point extraction module is used for extracting first virtual maintenance object feature points based on an adjacent point normal vector included angle feature point extraction algorithm according to the virtual maintenance object data;
the second virtual maintenance object feature point extraction module is used for extracting second virtual maintenance object feature points based on a vertex saliency feature point extraction algorithm according to the virtual maintenance object data;
the virtual arm kinematics model building module is used for building a virtual arm kinematics model according to the virtual arm data;
the reachable domain determining module is used for determining the reachable domain of the tail end of the virtual arm or the tail end of the maintenance tool according to the virtual arm kinematics model;
the characteristic point set determining module is used for carrying out space subdivision on the reachable domain and determining a characteristic point set;
a reachability evaluation result determination module configured to determine a reachability evaluation result of the repair apparatus according to the first virtual repair object feature point, the second virtual repair object feature point, and the feature point set; the reachability evaluation result includes that the repair part is within the repair reach and that the repair part is not within the repair reach.
Optionally, the first virtual maintenance object feature point extracting module specifically includes:
the virtual maintenance object description unit is used for describing a virtual maintenance object by adopting a triangular mesh model;
the first judgment unit is used for traversing each edge of the triangular network model and judging whether the edge only has one adjacent point to obtain a first judgment result;
a first virtual maintenance object feature first determining unit, configured to determine two end points of the edge as first virtual maintenance object feature points if the first determination result indicates that only one adjacent point exists on the edge;
a normal vector included angle determining unit, configured to determine a normal vector included angle between adjacent points if the first determination result indicates that the edge has more than one adjacent point;
the second judgment unit is used for judging whether the weight of the normal vector included angle is smaller than a weight threshold value or not to obtain a second judgment result;
and a second determining unit of the first virtual maintenance object feature point, configured to determine two end points of the edge as the first virtual maintenance object feature point if the second determination result indicates that the weight of the normal vector included angle is smaller than a weight threshold.
Optionally, the second virtual maintenance object feature point extracting module specifically includes:
the height difference calculating unit is used for calculating the height difference between adjacent vertexes in the triangular mesh model;
the average height difference determining unit is used for determining the average height difference of each vertex according to the height difference;
and the second virtual maintenance object feature point extraction unit is used for extracting second virtual maintenance object feature points according to the average height difference.
Optionally, the virtual arm kinematics model construction module specifically includes:
the rotational freedom degree determining unit is used for determining the rotational freedom degree of the virtual arm according to the virtual arm data; the rotational freedom degree comprises a shoulder joint rotational freedom degree, an elbow joint rotational freedom degree and a wrist joint rotational freedom degree;
a relative transformation matrix determining unit for determining a relative transformation matrix between each joint according to the rotational degree of freedom; the relative transformation matrix comprises a transformation matrix of the elbow joint relative to the shoulder joint, a transformation matrix of the wrist joint relative to the elbow joint and a transformation matrix of the arm tail end operation point relative to the wrist joint;
and the virtual arm kinematics model building unit is used for building a virtual arm kinematics model according to the relative transformation matrix.
Optionally, the reachability evaluation result determination module specifically includes:
a third determining unit, configured to determine whether each of the first virtual maintenance object feature points and each of the second virtual maintenance object feature points all belong to the feature point set, so as to obtain a third determination result;
a reachability-evaluation-result first determination unit configured to determine that the reachability evaluation result is that the repair part is within a repair reachable range if all of the first virtual repair-object feature points and all of the second virtual repair-object feature points belong to the feature point set as a result of the third determination;
a reachability-evaluation-result second determination unit that determines that the reachability evaluation result is that the repair part is not within the repair reachable range if each of the first virtual repair-object feature points and each of the second virtual repair-object feature points do not all belong to the feature point set as a result of the third determination.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects: the invention provides an automatic reachability evaluation method and system for maintenance equipment, wherein feature points of a first virtual maintenance object and feature points of a second virtual maintenance object are extracted by combining an adjacent point normal vector included angle-based feature point extraction algorithm and a vertex saliency feature point extraction algorithm, and compared with the traditional feature point extraction algorithm, the virtual maintenance object feature points required by reachability evaluation can be extracted more comprehensively and accurately; and constructing a virtual arm kinematics model, determining an reachable domain according to the virtual arm kinematics model, and automatically determining the reachability evaluation result of the maintenance equipment according to the extracted feature points and the feature point set determined by the reachable domain. In the whole evaluation process, the subjective consciousness of workers is removed, and the reachability evaluation result of the maintenance equipment is automatically determined, so that the objectivity and the accuracy of the reachability evaluation result are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a flowchart of an automatic reachability evaluation method for maintenance equipment provided by the present invention;
fig. 2 is a flowchart of an automatic reachability evaluation method for service equipment according to function division provided by the present invention;
FIG. 3 is a schematic view of a normal vector angle of an adjacent point provided by the present invention;
FIG. 4 is a simplified diagram of a three-link seven-degree-of-freedom arm according to the present invention;
FIG. 5 is a schematic view of the hand size provided by the present invention;
FIG. 6 is a schematic diagram of a coordinate system of a master tool tip according to the present invention;
fig. 7 is a diagram showing a configuration of an automatic reachability evaluation system of maintenance equipment provided by the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a method and a system for automatically evaluating the accessibility of maintenance equipment, which can automatically determine the accessibility evaluation result of the maintenance equipment and improve the objectivity and accuracy of the accessibility evaluation result.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Fig. 1 is a flowchart of an automatic reachability evaluation method for a maintenance device according to the present invention, and as shown in fig. 1, the automatic reachability evaluation method for a maintenance device includes:
step 101: and acquiring virtual arm data and virtual maintenance object data.
And building a virtual environment in computer DELMIA software and acquiring virtual human data, virtual maintenance object data and virtual environment component data.
Firstly, a virtual environment is built in computer DELMIA software, a virtual human, a virtual maintenance object and a virtual environment component are loaded into the virtual environment in the DELMIA software, and then the position of a maintenance station and a maintenance tool of the virtual human is adjusted to be in line with the actual maintenance working condition. Virtual human data, virtual maintenance object data, and virtual environment component data in the virtual environment are then collected using the DELMIA interface function.
Step 102: and extracting a first virtual maintenance object characteristic point based on an adjacent point normal vector included angle characteristic point extraction algorithm according to the virtual maintenance object data.
The step 102 specifically includes: describing a virtual maintenance object by adopting a triangular mesh model; traversing each edge of the triangular network model, judging whether the edge only has one adjacent point, and if so, determining two end points of the edge as first virtual maintenance object feature points; if not, determining a normal vector included angle between adjacent points; and judging whether the weight of the normal vector included angle is smaller than a weight threshold value or not, and if so, determining two end points of the edge as first virtual maintenance object characteristic points.
The virtual maintenance object is mainly expressed by using a triangular mesh model, and a three-dimensional model is expressed by a series of space triangular approximations.
The triangular mesh model is a piecewise linear surface formed by connecting space triangular patches through edges and vertices, and is generally denoted as M.
The triangular mesh model M ═ (V, E, T) is a set of three geometric elements of points, edges, and faces in space, and V denotes a geometric element defined in Rk(k is 2, 3); e ═ Ei},e＝(vi，vj) Is represented by vertex vi、vjThe formed triangle side; t ═ TiDenotes a symbol consisting of v not on the same straight lineiAnd vj，vkThe convex hull formed by ∈ V is called triangle t ═ (V)i，vj,vk) And t represents a vertex vi、vjAnd vkAdjacent triangles of (a).
The triangular mesh model of the virtual repair object is typically based on an edge structure. A triangular mesh is described by a vertex array and a triangle array:
V：(double x,y,z)[m](1)
T:(int v0,v1,v2)[n](2)
wherein each vertex has three coordinate components of x, y and z, and each triangle is defined by three vertices. v. of0、v1、v2Respectively representing indexes of three vertexes of the triangle in a vertex array V, wherein m and n respectively indicate the number of the vertexes and the number of the triangle; each vertex may contain, in addition to coordinates, the normal, color, texture coordinates, etc. of the vertex.
The automated evaluation and analysis method of visual accessibility is divided into 3 systems and 7 steps according to the difference of functions. The system comprises a virtual maintenance object feature point extraction system and a virtual human arm tail end or maintenance tool tail end reachable region acquisition system, as shown in figure 2, the system 2 combines a feature point extraction algorithm based on an adjacent point normal vector included angle and vertex significance to extract virtual maintenance object feature points twice, and stores the extracted feature points into a virtual maintenance object feature point set FA。
Firstly, a feature point extraction algorithm based on the size of an adjacent point normal vector included angle is adopted to preliminarily extract surface feature points of a virtual maintenance object, and a normal vector is a normal vector of a curved surface on one point.
As shown in fig. 3, let e be a certain edge in the triangular mesh,
is v isiThe unit of normal vector of
And
is α.
First, a normal vector angle α of an adjacent point of the edge e is calculated, w (e) is set to cos α, and w (e) can be obtained by calculating the product of the normal vectors:
let βiIf the angle between the normal vectors of any two adjacent vertexes is defined, and n is the number of edges, a threshold value exists:
so that
(3)
When the edge e has only one adjacent point, the edge is a boundary line, and two end points of the edge e are both characteristic points. When the weight of the adjacency point normal vector included angle of the edge e is smaller than the threshold, it is indicated that the adjacency point normal vector included angle of the edge is larger, and then both end points of the edge e are feature points. The initial feature point set F (e) of the surface of the virtual maintenance object can be obtained by the formula (1), and all the extracted feature points are stored in the set FAIn (1).
Step 103: and extracting a second virtual maintenance object characteristic point based on a vertex saliency characteristic point extraction algorithm according to the virtual maintenance object data.
The step 103 specifically includes: calculating the height difference between adjacent vertexes in the triangular mesh model; determining the average height difference of each vertex according to the height difference; and extracting a second virtual maintenance object feature point according to the average height difference.
The saliency of a triangle mesh model vertex is determined by the degree of surface irregularity, and if the degree of irregularity of a certain vertex is higher than the degree of irregularity of other vertices in the neighborhood, the geometric saliency of the vertex is also high. The concave-convex degree of the vertex of the triangular mesh model is measured by the average height difference between the vertex and other vertexes in a certain neighborhood of the vertex, and when the average height difference between a certain vertex and other vertexes in a certain neighborhood of the certain vertex is larger, the concave-convex degree is higher, and the significance of the point is higher.
(1) And sequentially taking each vertex v in the vertex set of the triangular mesh model as a center, and calculating the height difference between the vertex and the adjacent vertex. First, the normal vector NV of each vertex is calculated:
where f (v) is the set of patches associated with vertex v, nf (f) is the normal vector of patch f, and area (f) is the area of patch f.
(2) Next, the average normal vector NE (v, v') for each edge is calculated:
where v, v' are the two vertices of the edge.
(3) The height difference h (v, v') between adjacent vertices is then calculated:
h(v,v')＝||(v-v')·NE(v,v')|| (6)
i.e. the projection height of an edge with two vertices as end points on the average normal vector of the edge.
(4) And finally, calculating the average height difference of each vertex:
where V (v) is the set of vertices connected to vertex v, | V (v) | denotes the size of set V (v).
(5) According to the height difference of all the grid vertexes, extracting the top 10% of vertexes, marking the vertexes as feature points, eliminating the feature points which are repeatedly extracted, and finally storing the feature points into a set FAIn (1).
Step 104: and constructing a virtual arm kinematics model according to the virtual arm data.
The step 104 specifically includes: determining the rotational freedom of the virtual arm according to the virtual arm data; the rotational freedom degree comprises a shoulder joint rotational freedom degree, an elbow joint rotational freedom degree and a wrist joint rotational freedom degree; determining a relative transformation matrix among all joints according to the rotational freedom; the relative transformation matrix comprises a transformation matrix of the elbow joint relative to the shoulder joint, a transformation matrix of the wrist joint relative to the elbow joint and a transformation matrix of the arm tail end operation point relative to the wrist joint; and constructing a virtual arm kinematics model according to the relative transformation matrix.
The arm plays a direct role in the maintenance operation, and the maintenance part can not be touched, which means whether the hand or the handheld maintenance tool can touch the maintenance part. As shown in fig. 4, the arm is wrapped by three parts of an upper arm, a lower arm and a palm, and mainly comprises three joints of a shoulder joint, an elbow joint and a wrist joint, wherein the length of the upper arm is l, the length of the lower arm is m, and the length of the palm is n. After a rational simplification according to the characteristics of the maintenance operation, the shoulder joint has 3 degrees of freedom of rotation, including rotation in the radial plane (parallel to the central plane of the body), in the coronal plane (plane from one shoulder to the other), and around the humerus, the angles of rotation being respectively in theta1，θ2，θ3And (4) showing. The elbow joint has 1 degree of freedom of rotation, including flexion and extension around the elbow joint, and the rotation angle is theta4And (4) showing. The wrist joint has 3 rotational degrees of freedom including abduction, adduction and rotation around the ulna, the rotation angles are respectively theta5，θ6，θ7And (4) showing. The simplified back arm has 7 degrees of freedom, and table 1 is a table of the rotation angle range of each joint of the virtual human arm provided by the invention, and the rotation angle range is shown in table 1.
TABLE 1
The homogeneous coordinates can effectively describe the translation and rotation geometric transformation of each joint of the arm, and the initial state of the arm is shown in fig. 4, wherein the center point O, O is1、O2Respectively representing the shoulder joint, elbow joint and wrist joint, point P representing the end of the palm operating point, respectively establishing the sitting position as shown in the figureThe mark system. In fig. 4, subscript "0" denotes a shoulder joint, "1" denotes an elbow joint, "2" denotes a wrist joint, and "3" denotes an arm end operation point.
The transformation matrix for each joint angle is as follows:
t (a, b, c) is a translation transformation matrix, wherein a, b and c respectively represent the translation distances of the joint points along the X axis, the Y axis and the Z axis.
The overall transformation matrix for the elbow joint relative to the shoulder joint is then:
the overall transformation matrix for the wrist joint relative to the elbow joint is:
the total transformation matrix of the operation point P at the tail end of the arm relative to the wrist joint is as follows:
the total transformation matrix (i.e. the virtual arm kinematics model) of the arm end operation point P relative to the shoulder joint can be obtained:
0G3＝0G1 1G2 2G3(8)
step 105: and determining the reachable domain of the tail end of the virtual arm or the tail end of the maintenance tool according to the kinematic model of the virtual arm.
(1) Free-hand maintenance
And calculating the reachable domain of the tail end of the arm, substituting the sizes of all parts of the human arm with different percentiles and the rotation angle ranges of all joints of the arm into the virtual arm kinematics model (8) according to the virtual arm kinematics model (8), performing cyclic iteration in the rotation directions of 7 degrees of freedom, and circularly calculating reachable points of all tail end spaces of the arm at the angle change of 5 degrees or 10 degrees. Table 2 is a table of correspondence between the lengths and diameters of the upper arm and forearm of different percentiles provided by the present invention, as shown in table 2, the unit is mm.
TABLE 2
(2) Maintenance using tools
The dimensions of the hand and various parts of the arm of the service person are taken into account in calculating the available space for the hand tool, the parts of the hand being shown in fig. 5. Table 3 is a table of the hand size correspondence for different percentiles provided by the present invention, as shown in table 3, the unit is mm.
TABLE 3
1) Finger-held tool end reach
The finger-gripping tool is a tool, such as a screwdriver, which uses the ball muscle of a finger as a main working surface and assists the palm and other muscles of the forearm to perform actions together. When the finger-gripping tool works, the finger-gripping tool mainly shows the movement of fingers, and the range of limb movement is smaller. When the finger-held tool is held, the tail part of the tool is propped against the palm, the thumb and the forefinger pinch the tool, a section of rigid body is approximately considered to be extended from the wrist, the longitudinal axis of the rigid body is superposed with the vertical center line of the screw, and the rigid body rotates around the vertical center line of the screw to do reciprocating motion. Therefore, when calculating the reachable space of the handheld tool, the palm length is L, the tool length is N, and the operation point at the end of the arm is regarded as the wrist joint is translated by a distance (L/2+ N) along the X-axis.
The overall transformation matrix for the finger-gripping tool tip relative to the wrist joint is:
the overall transformation matrix for the finger-gripping tool tip relative to the shoulder joint can be obtained:
0G3′＝0G1 1G2 2G3′ (9)
and (3) obtaining a kinematic equation of the tail end of the finger-holding tool relative to the shoulder joint according to the formula (9), and calculating all space reachable points of the tail end of the finger-holding tool in a shoulder joint coordinate system O according to the lengths of all parts of the arm of the maintainer and the rotation angle ranges of all joints under different percentiles, thereby calculating the reachable region of the tail end of the finger-holding tool.
2) Reach of master tool end
The palm-held tool refers to a tool which is grasped by muscles of all parts of the palm, such as a cutter, a pliers, various wrenches and the like. The operation of the master tool is generally completed by wrist muscles or upper arm muscles, palm muscles mainly play a role in keeping the posture of the tool, the tool can be approximately regarded as a rigid body which is extended from the wrist, the top end of the rigid body is positioned on the vertical central line of the maintenance part, the longitudinal axis of the rigid body is vertical to the vertical central line of the maintenance part, the rigid body rotates around the vertical central line of the maintenance part to do reciprocating motion, and the rigid body motion drives other parts of the upper limb to move. The distance between the gripping characteristic point of the tool and the tail part of the tool is D/2 according to the maximum moment principle, and D is the width of the palm of the hand.
As shown in FIG. 6, the grasping tool tip-to-wrist coordinate system O2Is converted into: first edge Z3Moved by a distance n1(N-D/2) toO3Second winding Y3The axis rotates 90 DEG along X3The shaft moves a distance n2(L/2) to O2Finally wind Y2Axis of rotation theta6Around Z2Axis of rotation theta7。
The master tool tip to wrist joint total transformation matrix is:
the overall transformation matrix of the master tool tip relative to the shoulder joint is available:
0G3″＝0G1 1G2 2G3″ (10)
the kinematic equation of the tail end of the master tool relative to the shoulder joint can be obtained according to the formula (10), and all space reachable points of the tail end of the master tool in a shoulder joint coordinate system O can be calculated according to the lengths of all parts of the arm of the maintainer and the rotation angle ranges of all joints under different percentiles, so that the reachable region of the tail end of the palm-held tool is calculated.
Step 106: and carrying out space subdivision on the reachable domain, and determining a characteristic point set A.
The reachable points are distributed in a discretization mode and are not suitable for reachability evaluation requirements, so that the reachable domain needs to be spatially subdivided. A space segmentation method is utilized to remove a large number of repeated reachable points and extract the space distribution characteristics of the reachable points, and the method comprises the following specific steps:
1) the known reachable point set E is composed of N reachable points, and is denoted as E ═ ei | i ═ 1, 2, …, N }. the spatial envelope region of the reachable point set E is V, and the region V is equally divided into N × N × N small cubes, each small cube is numbered qj,k,rThe corresponding cube is denoted V (q)j,k,r)。
2) The empty cubes are removed. Initializing a as an empty set.
Decision point eiWhether it belongs to a small cube in V, if it belongs to V (q)j,k,r) Then the cube is stored in set a.
Step 107: determining a reachability evaluation result of the maintenance equipment according to the first virtual maintenance object feature point, the second virtual maintenance object feature point and the feature point set; the reachability evaluation result includes that the repair part is within the repair reach and that the repair part is not within the repair reach.
The step 107 specifically includes: judging whether each first virtual maintenance object feature point and each second virtual maintenance object feature point belong to the feature point set or not, and if so, determining that the accessibility evaluation result is that the maintenance component is in a maintenance reachable range; if not, determining that the accessibility evaluation result is that the maintenance part is not in the maintenance accessibility range.
Sequentially judging the set FAWhether each feature point in the set M is located in a certain small cube in the set M or not, and if all the feature points are located in the cubes, the fact that the maintenance component can be contacted is indicated; if the characteristic points which do not belong to any small cube exist, the accessibility of the repair part is poor and the repair part cannot be contacted. And feeding the evaluation result back to a designer, and providing reference for balancing and optimizing the maintainability design scheme.
Fig. 7 is a structural view of an automatic reachability evaluation system for maintenance equipment provided by the present invention, and as shown in fig. 7, the automatic reachability evaluation system for maintenance equipment includes:
the data obtaining module 701 is configured to obtain virtual arm data and virtual maintenance object data.
A first virtual maintenance object feature point extracting module 702, configured to extract, according to the virtual maintenance object data, a first virtual maintenance object feature point based on an adjacent point normal vector included angle feature point extracting algorithm.
The first virtual maintenance object feature point extraction module 702 specifically includes: the virtual maintenance object description unit is used for describing a virtual maintenance object by adopting a triangular mesh model; the first judgment unit is used for traversing each edge of the triangular network model and judging whether the edge only has one adjacent point to obtain a first judgment result; a first virtual maintenance object feature first determining unit, configured to determine two end points of the edge as first virtual maintenance object feature points if the first determination result indicates that only one adjacent point exists on the edge; a normal vector included angle determining unit, configured to determine a normal vector included angle between adjacent points if the first determination result indicates that the edge has more than one adjacent point; the second judgment unit is used for judging whether the weight of the normal vector included angle is smaller than a weight threshold value or not to obtain a second judgment result; and a second determining unit of the first virtual maintenance object feature point, configured to determine two end points of the edge as the first virtual maintenance object feature point if the second determination result indicates that the weight of the normal vector included angle is smaller than a weight threshold.
The second virtual maintenance object feature point extraction module 703 is configured to extract a second virtual maintenance object feature point based on a vertex saliency feature point extraction algorithm according to the virtual maintenance object data.
The second virtual maintenance object feature point extraction module 703 specifically includes: the height difference calculating unit is used for calculating the height difference between adjacent vertexes in the triangular mesh model; the average height difference determining unit is used for determining the average height difference of each vertex according to the height difference; and the second virtual maintenance object feature point extraction unit is used for extracting second virtual maintenance object feature points according to the average height difference.
And a virtual arm kinematics model construction module 704, configured to construct a virtual arm kinematics model according to the virtual arm data.
The virtual arm kinematics model construction module 704 specifically includes: the rotational freedom degree determining unit is used for determining the rotational freedom degree of the virtual arm according to the virtual arm data; the rotational freedom degree comprises a shoulder joint rotational freedom degree, an elbow joint rotational freedom degree and a wrist joint rotational freedom degree; a relative transformation matrix determining unit for determining a relative transformation matrix between each joint according to the rotational degree of freedom; the relative transformation matrix comprises a transformation matrix of the elbow joint relative to the shoulder joint, a transformation matrix of the wrist joint relative to the elbow joint and a transformation matrix of the arm tail end operation point relative to the wrist joint; and the virtual arm kinematics model building unit is used for building a virtual arm kinematics model according to the relative transformation matrix.
A reachable domain determining module 705, configured to determine, according to the virtual arm kinematics model, a reachable domain of the virtual arm end or the maintenance tool end.
A characteristic point set determining module 706, configured to perform spatial subdivision on the reachable domain, and determine a characteristic point set.
A reachability evaluation result determination module 707 configured to determine a reachability evaluation result of the repair apparatus from the first virtual repair object feature point, the second virtual repair object feature point, and the feature point set; the reachability evaluation result includes that the repair part is within the repair reach and that the repair part is not within the repair reach.
The reachability-evaluation-result determination module 707 specifically includes: a third determining unit, configured to determine whether each of the first virtual maintenance object feature points and each of the second virtual maintenance object feature points all belong to the feature point set, so as to obtain a third determination result; a reachability-evaluation-result first determination unit configured to determine that the reachability evaluation result is that the repair part is within a repair reachable range if all of the first virtual repair-object feature points and all of the second virtual repair-object feature points belong to the feature point set as a result of the third determination; a reachability-evaluation-result second determination unit that determines that the reachability evaluation result is that the repair part is not within the repair reachable range if each of the first virtual repair-object feature points and each of the second virtual repair-object feature points do not all belong to the feature point set as a result of the third determination.
Compared with the prior art, the invention can achieve the following beneficial effects:
(1) the method realizes the automatic analysis and evaluation of the accessibility, and compared with the prior accessibility analysis and evaluation method under the virtual environment which needs the subjective qualitative judgment of maintenance personnel and the assistance of expert opinions, the method helps the designers to realize the objective and automatic accessibility analysis and evaluation, thereby effectively reducing the working time of the designers.
(2) The virtual maintenance object feature point extraction method based on the neighbor point normal vector included angle combines the feature point extraction algorithm based on the neighbor point normal vector included angle and the vertex saliency feature point extraction algorithm to extract the virtual maintenance object feature point, and compared with the traditional feature point extraction algorithm, the virtual maintenance object feature point required by reachability evaluation can be extracted more comprehensively and more accurately.
(3) The method and the device consider two maintenance modes of bare-handed maintenance and tool maintenance, respectively calculate the reachable domain of the tail end of the arm, the reachable domain of the tail end of the finger-holding tool and the reachable domain of the tail end of the master tool, and are suitable for most maintenance operation modes in actual maintenance operation compared with the mode of only considering bare-handed maintenance.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (10)
1. An automatic accessibility evaluation method for a maintenance device, comprising:
acquiring virtual arm data and virtual maintenance object data;
extracting a first virtual maintenance object feature point based on an adjacent point normal vector included angle feature point extraction algorithm according to the virtual maintenance object data;
extracting a second virtual maintenance object feature point based on a vertex saliency feature point extraction algorithm according to the virtual maintenance object data;
constructing a virtual arm kinematics model according to the virtual arm data;
the homogeneous coordinate can effectively describe the translation and rotation geometric transformation of each joint of the arm;
the transformation matrix for each joint angle is as follows:
t (a, b, c) is a translation transformation matrix, wherein a, b and c respectively represent the translation distances of the joint points along the X axis, the Y axis and the Z axis;
the overall transformation matrix for the elbow joint relative to the shoulder joint is then:
the overall transformation matrix for the wrist joint relative to the elbow joint is:
the total transformation matrix of the operation point P at the tail end of the arm relative to the wrist joint is as follows:
the total transformation matrix of the arm end operation point P relative to the shoulder joint can be obtained, namely: virtual arm kinematics model:
0G3＝0G1 1G2 2G3(8)
determining a reachable domain of the tail end of the virtual arm or the tail end of the maintenance tool according to the kinematic model of the virtual arm;
performing space subdivision on the reachable domain, and determining a feature point set;
determining a reachability evaluation result of the maintenance equipment according to the first virtual maintenance object feature point, the second virtual maintenance object feature point and the feature point set; the reachability evaluation result includes that the repair part is within the repair reach and that the repair part is not within the repair reach.
2. The method for automatically evaluating reachability of maintenance equipment according to claim 1, wherein the extracting, according to the virtual maintenance object data, a first virtual maintenance object feature point based on an adjacent point normal vector included angle feature point extraction algorithm specifically comprises:
describing a virtual maintenance object by adopting a triangular mesh model;
traversing each edge of the triangular network model, and judging whether the edge only has one adjacent point to obtain a first judgment result;
if the first judgment result shows that only one adjacent point exists on the edge, determining two end points of the edge as first virtual maintenance object characteristic points;
if the first judgment result shows that the edge has more than one adjacent point, determining a normal vector included angle between the adjacent points;
judging whether the weight of the normal vector included angle is smaller than a weight threshold value or not to obtain a second judgment result;
and if the second judgment result shows that the weight of the normal vector included angle is smaller than a weight threshold value, determining that the two end points of the edge are first virtual maintenance object characteristic points.
3. The method for automatically evaluating reachability of maintenance device according to claim 2, wherein extracting a second virtual maintenance object feature point based on a vertex saliency feature point extraction algorithm according to the virtual maintenance object data specifically comprises:
calculating the height difference between adjacent vertexes in the triangular mesh model;
determining the average height difference of each vertex according to the height difference;
and extracting a second virtual maintenance object feature point according to the average height difference.
4. The method for automatically evaluating reachability of maintenance device according to claim 1, wherein the constructing a virtual arm kinematics model according to the virtual arm data specifically comprises:
determining the rotational freedom of the virtual arm according to the virtual arm data; the rotational freedom degree comprises a shoulder joint rotational freedom degree, an elbow joint rotational freedom degree and a wrist joint rotational freedom degree;
determining a relative transformation matrix among all joints according to the rotational freedom; the relative transformation matrix comprises a transformation matrix of the elbow joint relative to the shoulder joint, a transformation matrix of the wrist joint relative to the elbow joint and a transformation matrix of the arm tail end operation point relative to the wrist joint;
and constructing a virtual arm kinematics model according to the relative transformation matrix.
5. The method according to claim 1, wherein the determining the reachability evaluation result of the maintenance device from the first virtual maintenance object feature point, the second virtual maintenance object feature point, and the feature point set specifically includes:
judging whether each first virtual maintenance object feature point and each second virtual maintenance object feature point belong to the feature point set or not to obtain a third judgment result;
if each first virtual maintenance object feature point and each second virtual maintenance object feature point of the third judgment result all belong to the feature point set, determining that the accessibility evaluation result is that the maintenance component is within the maintenance accessibility range;
and if each first virtual maintenance object feature point and each second virtual maintenance object feature point of the third judgment result do not all belong to the feature point set, determining that the accessibility evaluation result is that the maintenance component is not within the maintenance accessibility range.
6. An automatic reachability evaluation system for maintenance equipment, comprising:
the data acquisition module is used for acquiring virtual arm data and virtual maintenance object data;
the first virtual maintenance object feature point extraction module is used for extracting first virtual maintenance object feature points based on an adjacent point normal vector included angle feature point extraction algorithm according to the virtual maintenance object data;
the second virtual maintenance object feature point extraction module is used for extracting second virtual maintenance object feature points based on a vertex saliency feature point extraction algorithm according to the virtual maintenance object data;
the virtual arm kinematics model building module is used for building a virtual arm kinematics model according to the virtual arm data;
the homogeneous coordinate can effectively describe the translation and rotation geometric transformation of each joint of the arm;
the transformation matrix for each joint angle is as follows:
t (a, b, c) is a translation transformation matrix, wherein a, b and c respectively represent the translation distances of the joint points along the X axis, the Y axis and the Z axis;
the overall transformation matrix for the elbow joint relative to the shoulder joint is then:
the overall transformation matrix for the wrist joint relative to the elbow joint is:
the total transformation matrix of the operation point P at the tail end of the arm relative to the wrist joint is as follows:
the total transformation matrix of the arm end operation point P relative to the shoulder joint can be obtained, namely: virtual arm kinematics model:
0G3＝0G1 1G2 2G3(8)
the reachable domain determining module is used for determining the reachable domain of the tail end of the virtual arm or the tail end of the maintenance tool according to the virtual arm kinematics model;
the characteristic point set determining module is used for carrying out space subdivision on the reachable domain and determining a characteristic point set;
a reachability evaluation result determination module configured to determine a reachability evaluation result of the repair apparatus according to the first virtual repair object feature point, the second virtual repair object feature point, and the feature point set; the reachability evaluation result includes that the repair part is within the repair reach and that the repair part is not within the repair reach.
7. The system for automatically evaluating reachability of maintenance device according to claim 6, wherein the first virtual maintenance object feature point extraction module specifically includes:
the virtual maintenance object description unit is used for describing a virtual maintenance object by adopting a triangular mesh model;
the first judgment unit is used for traversing each edge of the triangular network model and judging whether the edge only has one adjacent point to obtain a first judgment result;
a first virtual maintenance object feature first determining unit, configured to determine two end points of the edge as first virtual maintenance object feature points if the first determination result indicates that only one adjacent point exists on the edge;
a normal vector included angle determining unit, configured to determine a normal vector included angle between adjacent points if the first determination result indicates that the edge has more than one adjacent point;
the second judgment unit is used for judging whether the weight of the normal vector included angle is smaller than a weight threshold value or not to obtain a second judgment result;
and a second determining unit of the first virtual maintenance object feature point, configured to determine two end points of the edge as the first virtual maintenance object feature point if the second determination result indicates that the weight of the normal vector included angle is smaller than a weight threshold.
8. The system for automatically evaluating reachability of maintenance device according to claim 7, wherein the second virtual maintenance object feature point extraction module specifically includes:
the height difference calculating unit is used for calculating the height difference between adjacent vertexes in the triangular mesh model;
the average height difference determining unit is used for determining the average height difference of each vertex according to the height difference;
and the second virtual maintenance object feature point extraction unit is used for extracting second virtual maintenance object feature points according to the average height difference.
9. The system for automatically assessing reachability of maintenance device according to claim 6, wherein said virtual arm kinematics model building module specifically comprises:
the rotational freedom degree determining unit is used for determining the rotational freedom degree of the virtual arm according to the virtual arm data; the rotational freedom degree comprises a shoulder joint rotational freedom degree, an elbow joint rotational freedom degree and a wrist joint rotational freedom degree;
a relative transformation matrix determining unit for determining a relative transformation matrix between each joint according to the rotational degree of freedom; the relative transformation matrix comprises a transformation matrix of the elbow joint relative to the shoulder joint, a transformation matrix of the wrist joint relative to the elbow joint and a transformation matrix of the arm tail end operation point relative to the wrist joint;
and the virtual arm kinematics model building unit is used for building a virtual arm kinematics model according to the relative transformation matrix.
10. The system for automatically evaluating reachability of maintenance device according to claim 6, wherein the reachability-evaluation-result determination module specifically includes:
a third determining unit, configured to determine whether each of the first virtual maintenance object feature points and each of the second virtual maintenance object feature points all belong to the feature point set, so as to obtain a third determination result;
a reachability-evaluation-result first determination unit configured to determine that the reachability evaluation result is that the repair part is within a repair reachable range if all of the first virtual repair-object feature points and all of the second virtual repair-object feature points belong to the feature point set as a result of the third determination;
a reachability-evaluation-result second determination unit that determines that the reachability evaluation result is that the repair part is not within the repair reachable range if each of the first virtual repair-object feature points and each of the second virtual repair-object feature points do not all belong to the feature point set as a result of the third determination.
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