CN113157260B - Automatic part quality detection program generation method for CMM - Google Patents
Automatic part quality detection program generation method for CMM Download PDFInfo
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Abstract
The invention discloses an automatic generation method of a part quality detection program for CMM (machine vision memory), which relates to the technical field of intelligent manufacturing, and is used for combining a CAD (computer-aided design) model constructed by using MBD (mechanical brake system) technology and a probe CAD model of CMM (machine vision memory) to realize automatic generation of the part quality detection program for CMM, and solving the problem of low programming efficiency of the detection program. The automatic generation method of the CMM-oriented part quality detection program can relieve detection personnel from tedious manual extraction detection items, automatically construct the detection items according to the CAD model of the part, reduce the error rate and improve the detection efficiency; the given part automatically plans a detection characteristic sequence and a detection path under the condition of the arrangement pose of the CMM workbench and the probe model information, thereby reducing the service level of detection personnel, improving the detection efficiency and the detection precision and reducing the equipment research and development cost; and automatically generating a DMIS detection program according to the planning result of the detection path, reducing human intervention and improving the development efficiency of the detection program.
Description
Technical Field
The invention relates to the technical field of intelligent manufacturing, in particular to a part quality detection program automatic generation method for a CMM (coordinate measuring machine).
Background
The detection of the manufacturing quality of the parts is a key link in the intelligent manufacturing process. In recent years, with the development of three-dimensional digitization technology, the functions and performances of products are continuously improved. Because enterprises have higher and higher requirements on product quality and processing precision. To meet this trend, modern inspection equipment such as CMM has appeared and has played a great role in product quality control, new product development, mold manufacturing, and the like.
Most enterprises are equipped with CMM and other detection equipment at present, but because a detection system is lack of integration and association with a measurement object (a three-dimensional model and a label of a product), detection work depends on manual work to a great extent, such as manually making a detection procedure, manually writing a CMM detection program, manually reading a detection result, comparing the detection result with the label on a two-dimensional drawing, and judging whether the design requirements are met. The manual participation ensures that the automation and intelligence level of the product quality detection is not high, the detection efficiency is low, and especially the generation of a part manufacturing quality (especially a first part) detection program is a main bottleneck for restricting the improvement of the detection efficiency. The process is time-consuming and labor-consuming, is easy to cause human errors, and has higher requirements on the professional skill level of the detection personnel.
The following three methods are currently mainly used for generating the quality detection program: (1) manual writing based on a two-dimensional drawing. Firstly, a detection worker makes a detection process plan by referring to a drawing, then drives a detection device (such as a coordinate measuring machine) to sample a measurement point of a real object, evaluates the manufacturing quality of a part item by item, and finally stores the process as a detection program for subsequent use. The method has better flexibility, can detect and evaluate the parts according to the technical requirements in the drawing without a CAD model, but has higher requirements on the service level of detection personnel, low detection efficiency, easy omission of detection items and errors and influence on the detection working progress and cost. (2) Based on manual writing of a two-dimensional drawing and a three-dimensional model. Firstly, exporting a three-dimensional model into a neutral file by a detection person, loading the neutral file into a detection system, then sampling and evaluating a measuring point of the CAD model in a virtual environment according to design requirements on a two-dimensional drawing, finally, saving the process into a program, and running the program on real detection equipment to reproduce the detection process. The method is relatively intuitive, and can make full use of models constructed by various CAD software to get rid of the protection of intellectual property rights of various CAD systems. However, in the method, product and Manufacturing Information (PMI) is lost in the process of converting the three-dimensional CAD model into the neutral file, knowledge contained in the model cannot be fully utilized, and the problems of low detection efficiency, easy omission of detection items and the like also exist.
Aiming at the problems in the prior art, the application provides an automatic generation method of a part quality detection program for CMM (machine vision memory), which provides a three-dimensional part CAD (computer aided design) model and a CMM probe sensor parameter model based on model definition, and automatically generates a part manufacturing quality detection program. The requirements on the professional skills of detection technicians can be reduced, the generation of a part quality detection program and the quality evaluation efficiency are improved, and the development of productivity is promoted.
Disclosure of Invention
The invention aims to provide a method for automatically generating a part quality detection program for CMM (machine vision memory), which provides a three-dimensional part CAD (computer aided design) model and a CMM probe sensor parameter model based on model definition to automatically generate a part manufacturing quality detection program. The requirements on the professional skills of detection technicians can be reduced, the generation of part quality detection programs and the quality evaluation efficiency are improved, and the development of productivity is promoted.
The invention provides a part quality detection program automatic generation method for a CMM (coordinate measuring machine), which comprises the following steps of:
detection feature identification and reconstruction: establishing a three-dimensional part CAD model marked with PMI information, identifying and extracting geometric information of the part, and reconstructing detection characteristics of the model;
and (3) planning distribution of detection points: constructing a detection point sampling rule base according to the detection feature types in the detection feature set, and selecting detection points;
determining a high-layer detection scheme: obtaining a detection feature set under the constraint conditions of given triple-pose, probe and direction configuration by using the placing posture, probe type and probe azimuth angle of the part on the CMM workbench, and planning and determining a high-level detection scheme;
and (3) low-level detection path planning: performing path planning on detection points on each detection surface in the detection characteristics determined in the high-level detection scheme to obtain a shortest detection path set, and simultaneously performing optimal combination on detection sequences of different detection surfaces to obtain an optimal path;
simulation and avoidance processing: carrying out path simulation and avoidance processing on the obtained optimal path; and judging whether the path subjected to the judgment simulation and avoidance processing meets the detection standard, if not, re-planning the low-level detection path, and if so, inputting the detection planning result into a front-end processor for preprocessing to generate the detection method.
More preferably, the PMI information includes a size error, a shape error, a position error, a surface structure, and a reference;
the dimensional errors include length, width, height, included angle, diameter, radius, and other dimensional numerical types between features of the part;
the shape errors comprise straightness, flatness, roundness, cylindricity, conicity, sphericity, line profile, surface profile and other shape numerical value types among the part characteristics;
the position errors comprise parallelism, perpendicularity, inclination, concentricity, coaxiality, position degree, run-out value, symmetry and other position value types among the part features;
the surface texture is a measure of the smoothness of the finished surface of the part.
Preferably, the extraction step of the detection information is as follows:
acquiring a work part WorkPart and a PMI information set of a part, traversing the PMI information, sequentially judging whether the information is a characteristic control frame Fcf, a reference type Datum, a surface structure type SurfaceFinish and a size type Dimension, processing according to a judgment result, acquiring geometric information in the current PMI information, and finishing the extraction of detection information.
Preferably, the selection rule based on the part feature plane detection points is as follows:
firstly, when the structure of a geometric feature surface of a part is incomplete, judging whether a detection point is on the surface of the part, and filtering out points in holes and grooves of the part;
secondly, if the feature surface of the part needs to measure the radius size, at least three detection points need to be selected; if the flatness of the part needs to be measured, at least four detection points need to be selected; when the same feature plane is shared by a plurality of tolerance features, standard sampling is carried out according to the maximum number of sampling points.
Preferably, the detection point sampling rule base automatically plans the number and distribution of the detection points according to the type, geometric elements and precision information of the detection characteristics;
and filtering the detection points, and filtering out points on the edge of the surface of the model, points falling into the hole or the surface of the groove by filtering, thereby obtaining the required detection points.
Preferably, the collision-free detection path planning specifically includes:
high-level detection process planning: determining a detection pose sequence of the part according to the geometric shape of the CAD model, then carrying out testability and accessibility tests according to the detection pose sequence, the geometric parameter model of the probe, the direction of the probe and the distribution of detection points, and finally obtaining a set of the placement pose, the type and the direction of the probe and detectable characteristics of the part;
and (3) low-level detection path planning: an optimization algorithm is adopted to provide a path planning scheme which meets the optimal detection among groups;
simulation and avoidance processing of the detection process: and (3) performing path simulation on the detection scheme by using a collision detection algorithm, and performing avoidance processing if the path is collided.
Preferably, the formula of the time required for the high layer detection process is as follows:
wherein, T i p To detect the time taken for the probe to travel along the path,
the time taken for the probe to rotate is,
in order to change the time taken for the probe,
the time for changing the detection pose of the model and recalibrating the coordinate system is saved.
Preferably, the low-level detection path planning is divided into path planning in a detection characteristic plane and path planning between detection characteristic planes;
path planning in the feature plane: respectively processing according to the characteristics of the characteristic surfaces, and if the characteristic surfaces are planes, solving the planning problem which is classified as a TSP problem; if the characteristic surface is a cylinder, a cone or a sphere, detecting according to the sequence of the rings;
planning paths among the characteristic surfaces: and solving by adopting a genetic algorithm.
Preferably, the avoidance processing comprises surface translation obstacle avoidance and out-of-circle obstacle avoidance;
carrying out surface translation and obstacle avoidance: the detection points A and B are not on the same detection surface, the detection surface where the A is located is translated for a certain rollback distance towards the normal vector direction of the point A to form a safety surface, the normal vector of the point A is upwards intersected with the safety surface at the point C along the point B, the point C is set as an obstacle avoidance point, and according to the spatial relationship, the obstacle avoidance path length is as follows:
calculating that L is shortest when the point C is positioned at the middle point of DE;
keeping away the obstacle outside the circle: the detection points A and B are on the same detection surface, the path between the backspacing points A ' and B ' interferes with the detection surface, an auxiliary point C is taken from the midpoint of the points A and B, the backspacing point C ' is obtained as a safety point, and if a plurality of interference exists, the operation is repeated to iterate until no interference phenomenon exists in the detection process.
Compared with the prior art, the invention has the following remarkable advantages:
the automatic generation method of the CMM-oriented part quality detection program provided by the invention breaks through from three aspects by analyzing the bottleneck problem of low generation efficiency of the detection program.
(1) Automatically constructing detection characteristics: PMI and associated geometric information are extracted from a CAD model constructed by adopting MBD technology, detection characteristics are automatically constructed, manual construction of a detection person for contrasting drawings is omitted, the error rate and the problem of missing items are reduced, and the detection efficiency is improved;
(2) Automatically generating a collision-free detection path: firstly, automatically planning the quantity and distribution of sampling points according to detection characteristics; then, under the constraint conditions of part placement pose, probe sensor information type selection, probe direction selection and the like, the accessibility and testability analysis of the detection items is automatically carried out; and finally, automatically generating a collision-free detection path through intelligent path planning and collision simulation verification. The process can reduce the requirement of professional skills of detection personnel, reduce the blindness of part placement and improve the safety and efficiency of the detection process;
(3) Conversion interface generated by DMIS program: according to the DMIS standard requirement, the detection path planning result is automatically generated into a part manufacturing quality detection and detection evaluation program facing the CMM through a conversion interface, so that the generation efficiency of the detection program is improved.
Drawings
Fig. 1 is a schematic diagram of a generation flow of a detection program according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating the type of detection information provided by an embodiment of the present invention;
FIG. 3 is a flow chart of detection information extraction according to an embodiment of the present invention;
FIG. 4 is a flow chart of a high level inspection process planning operation provided by an embodiment of the present invention;
FIG. 5 is a diagram of simulation and interference check provided by an embodiment of the present invention;
fig. 6 is a plane translation obstacle avoidance diagram provided in the embodiment of the present invention;
fig. 7 is an out-of-circle obstacle avoidance diagram provided by an embodiment of the present invention;
FIG. 8 is a CAD model diagram of a part marked with PMI according to an embodiment of the present invention;
FIG. 9 is a diagram of a model detection item reconstruction provided in an embodiment of the present invention;
FIG. 10 is a diagram of a set of model pose and measurable features for model detection provided by an embodiment of the present invention;
FIG. 11 is a diagram of a detection path provided by an embodiment of the present invention;
FIG. 12 is a diagram illustrating simulation and avoidance of a detection process according to an embodiment of the present invention;
fig. 13 is a diagram illustrating a DMIS detection procedure according to an embodiment of the present invention;
FIG. 14 is a plan view of a planar sampling plan provided by an embodiment of the present invention;
fig. 15 is a cylindrical surface sampling plan provided in the embodiment of the present invention.
Detailed Description
The technical solutions of the embodiments of the present invention are clearly and completely described below with reference to the drawings in the present invention, and it is obvious that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
The invention is used for solving the problem of low generation efficiency of a part (especially a first part) manufacturing quality detection program for CMM. The CAD model built by the MBD technology is combined with the probe CAD model of the CMM, so that the automatic generation of a part quality detection program for the CMM is realized, and the problem of low programming efficiency of the detection program is solved. By applying the method, (1) detection personnel can be freed from tedious manual extraction of detection items, and the detection items are automatically constructed according to the CAD model of the part, so that the error rate is reduced, and the detection efficiency is improved; (2) the method has the advantages that a given part automatically plans a detection characteristic sequence and a detection path under the condition of the arrangement pose of the CMM workbench and the probe model information, so that the service level of detection personnel is reduced, the detection efficiency and the detection precision are improved, and the equipment research and development cost is reduced; (3) and automatically generating a DMIS detection program according to the planning result of the detection path, reducing human intervention and improving the development efficiency of the detection program.
The application of the MBD technology enables the three-dimensional CAD model to bear rich knowledge. In the design stage, designers mark the information on the CAD model according to the design intentions of the designers through a PMI module of commercialized CAD software. In the detection stage, the marked PMI and the associated geometric information are extracted, so that the information of the part can be reused in the design and detection stages.
Referring to fig. 1-13, the present invention provides a method for automatically generating a CMM-oriented part quality inspection program, comprising the steps of:
detection feature identification and reconstruction: establishing a three-dimensional part CAD model marked with PMI information, identifying and extracting geometric information of the part, and reconstructing detection characteristics of the model;
and (3) planning distribution of detection points: constructing a detection point sampling rule base according to the detection feature types in the detection feature set, and selecting detection points;
determining a high-layer detection scheme: the method comprises the following steps of obtaining a detection feature set under the constraint conditions of given triple-pose, probe and direction configuration by using the placing posture, probe type and probe azimuth angle of a part on a CMM workbench, and planning and determining a high-level detection scheme;
and (3) low-level detection path planning: performing path planning on detection points on each detection surface in the detection characteristics determined in the high-level detection scheme to obtain a shortest detection path set, and simultaneously performing optimal combination on detection sequences of different detection surfaces to obtain an optimal path;
simulation and avoidance processing: carrying out path simulation and avoidance processing on the obtained optimal path; and judging whether the path subjected to the judgment simulation and avoidance processing meets the detection standard, if not, re-planning the low-level detection path, and if so, inputting the detection planning result into a front processor for pretreatment to generate the detection method.
Wherein the PMI information includes a size error, a shape error, a position error, a surface structure, and a reference;
the dimensional errors include length, width, height, included angle, diameter, radius, and other dimensional numerical types between features of the part;
the shape error comprises straightness, flatness, roundness, cylindricity, conicity, sphericity, line profile, surface profile and other shape numerical value types among the part characteristics, the shape error is evaluated as the error between the actual shape and the ideal shape of the geometric characteristic, and is irrelevant to the size and the position of the evaluated characteristic, and the shape error is compared with the theoretical shape of the characteristic per se, so that the reference characteristic is not needed, the evaluation method of the shape error has minimum conditions, a least square method and the like, and the normal and reliable work of the geometric shape deformation and the error of the machined part in the practical application can be ensured by controlling the shape error;
the position errors comprise parallelism, verticality, inclination, concentricity, coaxiality, position degree, run-out value, symmetry and other position value types among the part characteristics, and the position errors are evaluated by processing deviation of actual positions and theoretical positions of the part geometric shapes, need reference characteristics and influence the assembly precision among the parts which are matched with each other;
the surface structure is a measure of the smoothness of the machined surface of the part, and the benchmark is a reference for error assessment, which is an ideal state. The type of detection information is shown in fig. 2.
Example 1
Acquiring a work part WorkPart and a PMI information set of a part, traversing the PMI information, sequentially judging whether the information is a characteristic control frame Fcf, a reference type Datum, a surface structure type SurfaceFinish and a size type Dimension, processing according to a judgment result, acquiring geometric information in the current PMI information, and finishing the extraction of detection information.
The extraction process of the detection information comprises the following steps:
s101: acquiring WorkPart, and further acquiring a PMI set;
s102: taking out a PMI in the set, judging whether the PMI is a characteristic control frame Fcf, if the judgment result is the characteristic control frame Fcf, acquiring a numerical value, an upper deviation, a lower deviation and a type, further acquiring geometric information to finish extraction, and if not, further judging whether the PMI is a reference type Datum; if the judgment result is the standard type Datum, obtaining the annotation information and the geometric information, further obtaining the geometric information to finish extraction, and if not, further judging whether the surface structure type is surface finish; if the judgment result is the surface structure type SurfaceFinish, acquiring the type and the numerical value, further acquiring geometric information to finish extraction, and if not, further judging whether the Dimension type Dimension is adopted; and if the judgment result is the Dimension type Dimension, acquiring a numerical value and an upper and lower deviation value, further acquiring geometric information to finish extraction, and if not, processing according to other types to finish extraction.
The basic flow of the detection information extraction is shown in fig. 3. Firstly, acquiring a working component and further acquiring a PMI set; then, the PMI in the set is traversed, the system judges and processes the Fcf (Feature control Frame, mainly referred to as a position tolerance type), the Datum (reference type), the surface finish (surface structure type) and the Dimension (size type), the annotated semantics and the associated geometric information are extracted, and the detection features of the model are reconstructed.
Example 2
Through the summary of a large number of tests and detection experiences, a detection point sampling rule base is constructed in advance, and the number and distribution of detection points are automatically planned according to the types (such as planeness and roundness) of detection features, geometric elements (such as planes, cylinders and cones) and precision information;
and filtering and selecting the detection points, and filtering out points too close to the edge of the surface of the model, points falling into the hole or the surface of the groove, so as to obtain the required detection points.
Point sampling of the CMM on the surface of the workpiece is based on the feature plane of the part. The geometric features of the part are generally composed of flat, cylindrical, conical, spherical, free-form surfaces and incomplete forms of these surfaces. Through a large number of examples and experimental empirical summaries, table 1 lists common plan schemes for detecting points on planar and cylindrical surfaces, and sampling rules for conical and spherical surfaces, similar to cylindrical surfaces.
The selection rule based on the detection points of the part feature surface is as follows:
firstly, when the structure of a geometric feature surface of a part is incomplete, judging whether a detection point is on the surface of the part, and filtering out points in holes and grooves of the part;
secondly, if the feature surface of the part needs to measure the radius size, at least three detection points need to be selected; if the flatness of the part needs to be measured, at least four detection points need to be selected; when the same feature plane is shared by multiple tolerance features, standard sampling is performed according to the maximum number of sampling points.
The detection point sampling rule base automatically plans the number and distribution of detection points according to the type, geometric elements and precision information of detection features;
and filtering the detection points, and filtering out points on the edge of the surface of the model, points falling into the hole or the surface of the groove by filtering, thereby obtaining the required detection points.
TABLE 1 sampling plan for partial feature planes
The planning of the collision-free detection path is a precondition for the generation of the part quality detection program. The method consists of three sub-processes: planning a high-level detection process, planning a bottom-level detection path and simulating and interference avoiding processing in a detection process. The non-collision detection path planning specifically comprises the following steps:
1. high-level detection process planning: determining a detection pose sequence of the part according to the geometric shape of a CAD model, then testing the testability and accessibility according to the detection pose sequence, a geometric parameter model of the probe, the direction of the probe and the distribution of detection points, and finally obtaining a set of the placing pose, the type and the direction of the probe and detectable features of the part, wherein the aim of the process is to determine how the part is placed on a CMM workbench, select which type of probe, which azimuth angle is adopted by the probe and which detection features can detect grouped information in the state, and the working flow is shown in FIG. 4;
the process shown in fig. 4 consists of two upper and lower areas, identified by the numbers (1), (2), respectively. The identification area of the sequence number (2) is a detection feature identification and reconstruction and detection point planning description part. The sequence number (1) marking area is a detection configuration tree structure formed by parts, poses, probes, probe orientations and the like. The formula of the time required in the detection process is:
wherein, T i p To detect the time taken for the probe to travel along the path,
the time taken for the probe to rotate is,
in order to change the time taken for the measuring head,
the time for changing the detection pose of the model and recalibrating the coordinate system is saved. Considering that the adjustment of the pose of the part placement is a time-consuming process which affects the detection precision and the detection efficiency, the pose is arranged at the top layer of the detection configuration tree structure. To improve the detection efficiency, the replacement of a measuring head and the change of direction and angle thereof should be reduced, and especially the adjustment of the position and pose of a part should be reduced.
The positions and postures of the probes, the orientations of the probes and the like are enumerable quantities, and the configured triad item set can be obtained by performing depth-first traversal on the detection configuration tree structure. The triple format is shown as { pose 1, probe 1, azimuth angle (0 degrees ) }, and the meaning is that in the state of the pose 1, the azimuth angle (0 degrees ) of the probe 1 is adopted to detect the detection point of the feature plane. And finally, obtaining the grouping information of the collision-free detectable characteristics in each pose state by adopting a collision interference algorithm.
2. And (3) low-level detection path planning: providing a path planning scheme meeting the optimal detection among groups through an optimization algorithm; and (4) after the high-level detection process planning treatment, obtaining a detection feature set under the configuration constraint condition of a given triple (pose, probe and direction). The low-level detection path planning aims at performing path planning on detection points on each detection surface of the detection features to obtain the shortest detection path so as to improve the detection efficiency; and simultaneously, the detection sequences of different detection surfaces are optimized and combined to achieve optimal path.
The low-level detection path plan can be divided into a path plan in a detection feature plane and a path plan between the detection feature planes. The path planning in the feature plane can be processed according to the characteristics of the feature plane. If the characteristic surface is a plane, the planning problem can be classified as a TSP problem, and a plurality of corresponding algorithms are used for solving the problem; when the characteristic surfaces are cylindrical, conical and spherical surfaces, detection is carried out according to the sequence of the rings. The path planning between the characteristic surfaces can be solved by adopting various optimization algorithms, and the genetic algorithm is adopted for solving the problem.
3. Simulation and avoidance processing of the detection process: and (3) performing path simulation on the detection scheme by using a collision detection algorithm, and performing avoidance processing if the path is collided. Through simulation, the interference condition of the probe and the part can be detected in advance. The flow chart of path subdivision, simulation and interference check between detection points by inserting a plurality of nodes is shown in fig. 5. And detecting whether the probe is interfered with the part model when passing through the node, and if so, carrying out obstacle avoidance operation.
1) Carrying out surface translation to avoid obstacles: as shown in fig. 6, the detection points a and B are not on the same detection surface, the detection surface where a is located is translated by a certain rollback distance toward the normal vector direction of the point a to form a safety surface, the detection point B intersects the safety surface at a point C upward along the normal vector of the point a as an obstacle avoidance point, and according to the spatial relationship, the obstacle avoidance path length is:
calculated, L is shortest when point C is at the midpoint of DE.
2) Obstacle avoidance outside the circle: as shown in fig. 7, the detection points a and B are on the same detection surface, the path between the back-off points a ' and B ' interferes with the detection surface, an auxiliary point C is taken from the midpoint of the points a and B on the surface, the back-off point C ' is obtained as a safety point, and if there are a plurality of interferences, the operations are repeated until there is no interference in the detection process.
Example 3
DMIS (Dimensional measurement Interface Specification) defines a set of bidirectional interaction standards between a computer system and a measurement device, that is, provides a data format to implement transmission of detection programs and measurement results between different detection devices. Currently, the CMM software system provides a DMIS interface, which provides an environment for an operator to execute DMIS commands or files by means of post-processing or command interpretation. The DMIS preprocessor is responsible for converting the result of the detection plan into a DMIS file for use by the measuring machine software.
The program structure in the DMIS file mainly consists of the following parts: the method comprises the following steps of defining parameters of a measuring machine, defining a measuring head, defining a coordinate system, defining detection characteristics, and defining a measuring process and measuring result output. For convenient conversion, an object-oriented technology is adopted to respectively carry out design conversion on all components in the DMIS file structure, and finally all converted program segments are combined to be connected into a complete file.
The technical effect that this application realized has:
(1) Extraction and reconstruction of detection item information
A CAD model of a part constructed using MBD techniques is shown in fig. 8. In the model, 12 items are the detection items (including size, shape and position tolerance and surface structure) concerned by the designer, and fig. 9 is the model detection item constructed by the method, which comprises 2 pieces of benchmark information, and 14 items. The method requires that the geometric elements associated with the detection items are geometric surface features, but designers may select some points and lines of the model as starting points or end points of dimension and form and position tolerance labeling when performing dimension and form and position tolerance labeling, so that the associated geometric elements such as the points and the lines are converted to the associated geometric surfaces according to information such as labeling planes and labeling line directions by developing an intelligent algorithm in the process of reconstructing the detection items, so as to facilitate the subsequent work; similarly, the inspection items such as surface structure and the like are also checked on the relevant geometric surface.
If the extraction and reconstruction process of the detection items is carried out in a manual mode by detection personnel, particularly when the number of the detection items is large, the detection items are very tedious work, errors and detection item omission easily occur, and by adopting the method, the detection efficiency of the product is improved, and the research and development period is shortened.
(2) Collision-free detection path planning
By giving the placing pose, the probe and the measuring angle of the part during detection, the method can automatically give the detectable characteristics, the detection path and the simulation avoidance result in the pose, and give the collision-free detection path as shown in fig. 10, fig. 11 and fig. 12.
(3) Generation of DMIS detection program
After the test plan is generated, a test program conforming to the DMIS standard is automatically generated for CMM test by developing a dedicated conversion program, and the result is shown in fig. 13.
The above disclosure is only for a few specific embodiments of the present invention, however, the present invention is not limited to the above embodiments, and any modifications that can be made by those skilled in the art are intended to fall within the scope of the present invention.
Claims (9)
1. A method for automatically generating a part quality inspection program for CMMs, comprising the steps of:
detection feature identification and reconstruction: establishing a three-dimensional part CAD model marked with PMI information, identifying and extracting geometric information of parts, completing extraction of detection information, and reconstructing detection characteristics of the model;
the PMI information comprises a size error, a shape error, a position error, a surface structure and a reference;
and (3) planning distribution of detection points: constructing a detection point sampling rule base according to the detection feature types in the detection feature set, and selecting detection points;
the planning of collision-free detection paths consists of three sub-processes:
determining a high-layer detection scheme: obtaining a detection feature set under the constraint conditions of given triple-pose, probe and direction configuration by using the placing posture, probe type and probe azimuth angle of the part on the CMM workbench, and planning and determining a high-level detection scheme;
and (3) low-level detection path planning: performing path planning on detection points based on a part feature plane in detection features determined in a high-level detection scheme, selecting the detection points based on a detection point selection rule of the part feature plane to obtain a shortest detection path set, and simultaneously performing optimal combination on detection sequences of different detection planes to obtain an optimal path;
simulation and avoidance processing: carrying out path simulation and avoidance processing on the obtained optimal path; and judging whether the optimal path subjected to path simulation and avoidance meets the detection standard, if not, re-planning the low-level detection path, and if so, inputting the detection planning result into a pre-processor for pre-processing to generate the detection method.
2. The method of claim 1 wherein the dimensional errors include length, width, height, included angle, diameter, radius, and other dimensional value types between part features;
the shape errors comprise straightness, flatness, roundness, cylindricity, conicity, sphericity, line profile, surface profile and other shape numerical value types among the part characteristics;
the position errors comprise parallelism, perpendicularity, inclination, concentricity, coaxiality, position degree, run-out value, symmetry and other position numerical value types among the part characteristics;
the surface texture is a measure of the smoothness of the finished surface of the part.
3. The method for automatically generating the part quality inspection program for the CMM as claimed in claim 1, wherein the step of extracting the inspection information comprises:
acquiring a work part WorkPart and a PMI information set of a part, traversing the PMI information, sequentially judging whether the information is a characteristic control frame Fcf, a reference type Datum, a surface structure type SurfaceFinish and a size type Dimension, processing according to a judgment result, acquiring geometric information in the current PMI information, and finishing the extraction of detection information.
4. The method for automatically generating the part quality inspection program for the CMM as claimed in claim 1, wherein the inspection point selection rule based on the feature plane of the part is:
firstly, when the structure of a geometric feature surface of a part is incomplete, judging whether a detection point is on the surface of the part, and filtering out points in holes and grooves of the part;
secondly, if the feature surface of the part needs to measure the radius size, at least three detection points need to be selected; if the part needs to measure the flatness, at least four detection points need to be selected; when the same feature plane is shared by multiple tolerance features, standard sampling is performed according to the maximum number of sampling points.
5. The automatic generation method of the CMM-oriented part quality inspection program as claimed in claim 1, wherein the inspection point sampling rule base automatically plans the number and distribution of inspection points according to the type, geometric elements and precision information of the inspection features;
and filtering and selecting the detection points, and filtering out points at the edge of the surface of the model and points falling into the hole or the groove surface, so as to obtain the required detection points.
6. A method for automatically generating a CMM-oriented part quality inspection program as defined by claim 1, wherein the collision-free inspection path plan is specifically:
high-level detection process planning: determining a detection pose sequence of the part according to the geometric shape of the CAD model, then carrying out testability and accessibility tests according to the detection pose sequence, the geometric parameter model of the probe, the direction of the probe and the distribution of detection points, and finally obtaining a set of the placement pose, the type and the direction of the probe and detectable characteristics of the part;
and (3) low-level detection path planning: an optimization algorithm is adopted to provide a path planning scheme which meets the best detection among groups;
simulation and avoidance processing of the detection process: and (3) performing path simulation on the detection scheme by using a collision detection algorithm, and performing avoidance processing if the path is collided.
7. A method for automatically generating a CMM-oriented part quality inspection process as defined by claim 6 wherein the time required for the high-level inspection process is formulated as:
wherein, T i p To detect the time taken for the probe to travel along the path,
in order to measure the time taken for the probe to rotate,
in order to change the time taken for the measuring head,
the time for changing the detection pose of the model and recalibrating the coordinate system is saved.
8. The method for automatically generating the CMM-oriented part quality inspection program as claimed in claim 6, wherein the low-level inspection path plan is divided into a path plan in the inspection feature plane and a path plan between the inspection feature planes;
path planning in the feature plane: respectively processing according to the characteristics of the characteristic surfaces, and if the characteristic surfaces are planes, solving the planning problem which is classified as a TSP problem; if the characteristic surface is a cylinder, a cone or a spherical surface, detecting according to the sequence of the rings;
planning the path between the characteristic surfaces: and solving by adopting a genetic algorithm.
9. The method for automatically generating the part quality inspection program for the CMM as claimed in claim 6, wherein the avoidance process comprises a plane translation obstacle avoidance and an out-of-circle obstacle avoidance;
carrying out surface translation to avoid obstacles: the detection points A and B are not on the same detection surface, the detection surface where the A is located is translated for a certain backspacing distance in the direction of the normal vector of the point A to form a safety surface, the detection surface is intersected with the safety surface in the B position along the normal vector of the point A at a point C, the point C is set as an obstacle avoidance point, and according to the space relation, the obstacle avoidance path length is as follows:
calculating that L is shortest when the point C is positioned at the middle point of DE;
obstacle avoidance outside the circle: the detection points A and B are on the same detection surface, the path between the backspacing points A ' and B ' interferes with the detection surface, an auxiliary point C is taken from the midpoint of the points A and B, the backspacing point C ' is obtained as a safety point, and if a plurality of interference exists, the operation is repeated to iterate until no interference phenomenon exists in the detection process.
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