CN112883443B - Method for judging similarity of part models based on geometry - Google Patents
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Abstract
The invention provides a method for judging similarity of part models, which comprises the following steps of S1, extracting geometric information of three-dimensional models of historical parts; s2, storing the geometric information of the three-dimensional model of the historical part into a unified data table; s3, extracting geometric information of a current three-dimensional model at a design end, comparing the geometric information of the current three-dimensional model with the geometric information of a historical three-dimensional model in a unified data sheet, and giving a comparison result; s4, respectively solving the maximum value and the minimum value of each field in the geometric information of the current model according to the set checking matching precision P; s5, splicing the maximum value and the minimum value of each field into an inquiry statement; s6, inquiring in the data table obtained in the step S2; and S7, performing similarity calculation on the query results to obtain the similarity of each query result, and displaying. The matching degree only depends on the geometrical characteristic information in the model and does not depend on the information such as parameters of the component level, and the checking result is more in line with the actual service requirement.
Description
Technical Field
The invention relates to the field of similarity judgment, in particular to a method for judging similarity of a part model based on geometry.
Background
A large number of three-dimensional models of parts are often designed by a development type manufacturing enterprise due to production and research and development requirements, and due to the fact that the number of the three-dimensional models is large, on one hand, a good judgment method for the similarity of the three-dimensional models of the parts is not available, and on the other hand, repeated research and development are often caused in the research and development process, so that repeated research and development are caused, and labor waste is caused. Thirdly, for research and development type enterprises, a three-dimensional model usually needs to maintain a purchasing industry chain and a production chain, and for similar three-dimensional models, because the models are unknown to be similar, the mode of the unique model is usually adopted to continuously maintain the purchasing chain and the production chain, and the maintenance workload of the purchasing chain and the production chain is large.
Disclosure of Invention
In order to solve the above technical problem, the present invention provides a method for determining similarity of part models, including the following steps:
s1, extracting geometric information of the three-dimensional model of the historical part to obtain the geometric information of the three-dimensional model of the historical part.
The historical part three-dimensional model refers to an existing part three-dimensional model in an enterprise database;
further, extracting geometric information of the model by using an API (application program interface) development interface of the three-dimensional software, wherein the extracted geometric information comprises: the length x _ len, width y _ len, height z _ len of the model, the amounts of deviation x _ off, y _ off, z _ off of the center of gravity of the model from the center of the model, the volume v _ prt of the model, the surface area a _ prt of the model, and the number n _ srf of curved surfaces of the model.
And S2, storing the extracted geometric information of the three-dimensional model of the historical part into a unified data table.
Further, the extracted length x _ len, width y _ len, height z _ len of the model, the deviation x _ off, y _ off and z _ off of the center of gravity of the model from the center of the model, the volume v _ prt of the model, the surface area a _ prt of the model and the quantity n _ srf of curved surfaces of the model are stored into a unified data table, the data table comprises columns of the length x _ len, width y _ len and height z _ len of the model, the deviation x _ off, y _ off and z _ off of the center of gravity of the model from the center of the model, the volume v _ prt of the model, the surface area a _ prt of the model and the quantity n _ srf 9 of curved surfaces of the model, and each row in the data table represents the geometric information of one model;
length, width, height of the model: the device is used for judging whether the external dimensions of the two models are consistent;
center of gravity of the model and center offset of the model: the device is used for judging whether the material distribution conditions of the two models are consistent or not;
volume of the model: used for judging whether the material wall thicknesses of the two models are consistent or not;
surface area of the model: the method is used for judging whether the detail features of the model surface are consistent or not;
number of curved surfaces of the model: and the method is used for judging whether the appearance characteristics of the model are consistent or not.
And S3, extracting the geometric information of the current three-dimensional model at the design end, and comparing the geometric information of the current three-dimensional model with the geometric information of the historical three-dimensional model in the unified data sheet to give a comparison result.
Furthermore, the geometric information of the current model at the design end is extracted, and comprises the length x _ len, the width y _ len and the height z _ len of the model, the deviation amounts x _ off, y _ off and z _ off of the center of gravity of the model and the center of the model, the volume v _ prt of the model, the surface area a _ prt of the model and the number n _ srf of curved surfaces of the model.
And S4, setting the checking and matching precision, and respectively solving the maximum value and the minimum value of each field in the geometric information of the current model according to the set checking and matching precision P to obtain the maximum value and the minimum value of each field in the geometric information.
Furthermore, the maximum value and the minimum value of 9 fields in the current model geometric information are respectively solved according to the set checking matching precision P, and 18 fields and values are obtained.
And S5, splicing the maximum value and the minimum value of each field in the geometric information to form an inquiry statement.
Further, according to the obtained 18 fields and values, splicing the query statement, wherein the query statement comprises the obtained 18 fields and values.
And S6, converting the query statement into a query instruction, and querying in the data table obtained in the step S2 to give a query result.
And the query result is a retrieved three-dimensional model of the part, and the retrieved three-dimensional model of the part comprises geometric information.
And S7, performing similarity calculation on the query results, sequentially calculating the percentage value of the offset of each dimension, and obtaining the similarity of each query result through a similarity calculation formula.
And S8, displaying the similarity of each query result in a list or graph mode.
Has the advantages that:
the method for judging the similarity of the part models checks the classification and classification attribute matching degree of the models in the part library, the matching degree only depends on the geometric characteristic information in the models and does not depend on the parameters and other information of the part level, and the checking result is more in line with the actual service requirement. And the inspection efficiency is high, and an additional platform end does not need to be developed.
Drawings
Fig. 1 is a schematic flow chart of the method for determining similarity of part models according to the present invention.
Detailed Description
Example 1: a method for judging similarity of part models comprises the following steps:
s1, extracting geometric information of a three-dimensional model of a historical part;
the historical part three-dimensional model refers to an existing part three-dimensional model in an enterprise database;
extracting geometric information of the model by using an API (application program interface) development interface of the three-dimensional software, wherein the extracted geometric information comprises: the length x _ len, width y _ len and height z _ len of the model, the deviation x _ off, y _ off and z _ off of the center of gravity of the model and the center of the model, the volume v _ prt of the model, the surface area a _ prt of the model and the number n _ srf of curved surfaces of the model.
S2, storing the geometric information into a unified data table;
storing the extracted length x _ len, width y _ len, height z _ len of the model, the deviation x _ off, y _ off and z _ off of the center of gravity of the model from the center of the model, the volume v _ prt of the model, the surface area a _ prt of the model and the number of curved surfaces n _ srf of the model into a unified data table, wherein the data table comprises columns of the length x _ len, width y _ len and height z _ len of the model, the deviation x _ off, y _ off and z _ off of the center of gravity of the model from the center of the model, the volume v _ prt of the model, the surface area a _ prt of the model and the number of curved surfaces n _ srf 9 of the model, and each row in the data table represents the geometric information of one model;
length, width, height of the model: judging whether the external dimensions of the two models are consistent;
center of gravity of the model and center offset of the model: judging whether the material distribution conditions of the two models are consistent;
volume of the model: judging whether the wall thicknesses of the materials of the two models are consistent;
surface area of the model: judging whether the detail features of the model surface are consistent or not;
number of curved surfaces of the model: and judging whether the appearance features of the model are consistent or not.
S3, extracting geometric information of a current model at a design end, comparing the geometric information of the current model with the geometric information of the historical three-dimensional model in the unified data sheet, and giving a comparison result;
the geometric information of the current model at the design end is extracted, wherein the geometric information comprises the length x _ len, the width y _ len and the height z _ len of the model, the deviation amounts x _ off, y _ off and z _ off of the center of gravity of the model and the center of the model, the volume v _ prt of the model, the surface area a _ prt of the model and the number n _ srf of curved surfaces of the model.
S4, respectively solving the maximum value and the minimum value of 9 fields in the geometric information of the current model according to the set checking matching precision P to obtain 18 fields and values;
further, the checking and matching precision P is 80% -100%;
x_len_min＝x_len–x_len/(1-P)；
x_len_max＝x_len+x_len/(1-P)。
y_len_min＝y_len–y_len/(1-P)；
y_len_max＝y_len+y_len/(1-P)。
z_len_min＝z_len–z_len/(1-P)；
z_len_max＝z_len+z_len/(1-P)。
x_off_min＝x_off–x_off/(1-P)；
x_off_max＝x_off+x_off/(1-P)。
y_off_min＝y_off–y_off/(1-P)；
y_off_max＝y_off+y_off/(1-P)。
z_off_min＝z_off–z_off/(1-P)；
z_off_max＝z_off+z_off/(1-P)。
v_prt_min＝v_prt–v_prt/(1-P)；
v_prt_max＝v_prt+v_prt/(1-P)。
a_prt_min＝a_prt–a_prt/(1-P)；
a_prt_max＝a_prt+a_prt/(1-P)。
n_srf_min＝n_srf–n_srf/(1-P)；
n_srf_max＝n_srf+n_srf/(1-P)。
further, P =1-50%, preferably P =20%.
And S5, splicing query statements according to the obtained 18 fields and values, wherein the query statements comprise the obtained 18 fields and values.
The sql statement is as follows:
SELECT*FROM PART_INFO WHERE
x_len>＝x_len_min and x_len<＝x_len_max and
y_len>＝y_len_min and y_len<＝y_len_max and
z_len>＝y_len_min and y_len<＝y_len_max and
x_off>＝x_off_min and x_off<＝x_off_max and
y_off>＝y_off_min and y_off<＝y_off_max and
z_off>＝z_off_min and z_off<＝z_off_max and
v_prt>＝v_prt_min and v_prt<＝v_prt_max and
a_prt>＝a_prt_min and a_prt<＝a_prt_max and
n_srf>＝n_srf_min and n_srf<＝n_srf_max
and S6, converting the query statement into a query instruction, and querying in the data table obtained in the step S2 to give a query result.
And the query result is a retrieved three-dimensional model of the part, and the retrieved three-dimensional model of the part comprises geometric information.
And S7, performing similarity calculation on the query results, sequentially calculating the percentage value of the offset of each dimension, and subtracting the percentage value of the offset of each dimension by 1 to obtain the similarity of each query result.
The percentage value of the offset of each dimension is formulated as
(1.0–abs(x_len_des–x_len_src)/x_len_src
–abs(y_len_des–y_len_src)/y_len_src
–abs(z_len_des–z_len_src)/z_len_src
–abs(x_off_des–x_off_src)/x_off_src
–abs(y_off_des–y_off_src)/y_off_src
–abs(z_off_des–z_off_src)/z_off_src
–abs(v_prt_des–v_prt_src)/v_prt_src
–abs(a_prt_des–a_prt_src)/a_prt_src
–abs(n_srf_des–n_srf_src)/n_srf_src)*100％
Wherein:
abs means the determination of absolute values
x _ len _ des refers to the length of the geometric information of the three-dimensional model of the part in the query result;
x _ len _ src refers to the length in the geometric information of the current model at the design end;
y _ len _ des refers to the width of geometric information of the three-dimensional model of the part in the query result
y _ len _ src refers to the width in the geometric information of the current model at the design end;
z _ len _ des refers to the height in the geometric information of the three-dimensional model of the part in the query result;
z _ len _ src refers to the height in the geometric information of the current model at the design end;
x _ off _ des refers to the deviation x _ off between the center of gravity of the model and the center of the model in the geometric information of the part three-dimensional model in the query result;
x _ off _ src refers to the deviation x _ off between the center of gravity of the model and the center of the model in the geometric information of the current model at the design end;
y _ off _ des refers to the deviation y _ off of the center of gravity of the model and the center of the model in the geometric information of the part three-dimensional model in the query result;
y _ off _ src refers to a deviation y _ off between the center of gravity of the model and the center of the model in the geometric information of the current model at the design end;
z _ off _ des refers to the deviation z _ off between the center of gravity of the model and the center of the model in the geometric information of the three-dimensional model of the part in the query result;
z _ off _ src refers to the deviation z _ off between the center of gravity of the model and the center of the model in the geometric information of the current model at the design end;
v _ prt _ des refers to the volume v _ prt of a model in the geometric information of the part three-dimensional model in the query result;
v _ prt _ src refers to the volume v _ prt of the model in the geometric information of the current model at the design end;
a _ prt _ des refers to the surface area a _ prt of the model in the geometric information of the three-dimensional model of the part in the query result;
a _ prt _ src refers to the surface area a _ prt of the model in the geometric information of the current model at the design end;
n _ srf _ des refers to the number n _ srf of curved surfaces of a model in the geometric information of the three-dimensional model of the part in the query result;
n _ srf _ src refers to the number n _ srf of curved surfaces of the model in the geometric information of the current model at the design end.
And S8, displaying the similarity of each query result in a list or graph mode.
Example 2: as shown in fig. 1, the present invention provides a method for determining similarity of part models, including the following steps:
extracting geometric information of the model when the parts are put in storage;
when a warehousing request is received, storing the model classification and other component-level information into a part library, and storing geometric information into a geometric information library;
when similarity checking is carried out, the maximum and minimum values of model geometric information items of the checked model are given;
when an inspection request is received, splicing the maximum and minimum values into an sql statement conditional constraint statement to execute query, and returning a result; for example:
SELECT*FROM PART_INFO WHERE val1>＝v1Min and val1<＝v2Max and val2>＝v2Min and val2<＝v2Max；
after the result set is obtained, calculating the similarity of the models in the result set according to a similarity algorithm in sequence, and displaying the similarity to a report;
the invention judges whether the models are consistent and judges from the following dimensions:
length, width, height of the model: judging whether the external dimensions of the two models are consistent;
center of gravity of the model and center offset of the model: judging whether the material distribution conditions of the two models are consistent;
volume of the model: judging whether the wall thicknesses of the materials of the two models are consistent;
additional dimensions:
the surface area of the model;
the number of curved surfaces of the model;
the information extracted by the geometric information extraction algorithm is packaged into the following fields:
-x_len、y_len、z_len、x_off、y_off、z_off、v_prt、a_prt、n_sr；
the geometric similarity checking algorithm of the invention is described as follows:
extracting geometric information (x _ len, y _ len, z _ len, x _ off, y _ off, z _ off, v _ prt, a _ prt, n _ srf) of a model to be inspected
According to the checking matching precision P (80% -100%) set by user in checking interface respectively finding out maximum and minimum values of 9 fields in the geometric information group, as follows:
x_len_min＝x_len–x_len/(1-P)；
x_len_max＝x_len+x_len/(1-P)。
y_len_min＝y_len–y_len/(1-P)；
y_len_max＝y_len+y_len/(1-P)。
z_len_min＝z_len–z_len/(1-P)；
z_len_max＝z_len+z_len/(1-P)。
x_off_min＝x_off–x_off/(1-P)；
x_off_max＝x_off+x_off/(1-P)。
y_off_min＝y_off–y_off/(1-P)；
y_off_max＝y_off+y_off/(1-P)。
z_off_min＝z_off–z_off/(1-P)；
z_off_max＝z_off+z_off/(1-P)。
v_prt_min＝v_prt–v_prt/(1-P)；
v_prt_max＝v_prt+v_prt/(1-P)。
a_prt_min＝a_prt–a_prt/(1-P)；
a_prt_max＝a_prt+a_prt/(1-P)。
n_srf_min＝n_srf–n_srf/(1-P)；
n_srf_max＝n_srf+n_srf/(1-P)。
submitting the calculated result (18 fields and values) to a server;
the server side splices Sql query sentences for query; the result set is returned directly to CREO, sql statement as follows:
SELECT*FROM PART_INFO WHERE x_len>＝x_len_min and x_len<＝x_len_max and....
and after obtaining the result, the CREO end executes similarity calculation, and calculates the percentage value of the offset of each dimension in turn to obtain the final similarity, wherein the algorithm is as follows:
(1.0–abs(x_len_des–x_len_src)/x_len_src-abs(y_len_des–y_len_src)/y_len_src-...)*100
the results are displayed into the front-end interface.
Example 3: the invention also provides a system for judging the similarity of the part models, which comprises a design end and a Server end.
1. (design end) extracting geometric information of the model when the parts are put in storage;
2. when receiving a storage request, the Server stores the model classification and other component-level information into a part library, and stores the geometric information into a geometric information library;
3. when similarity check is executed, the maximum and minimum values of model geometric information items of a model needing to be checked are transmitted to a server;
4. when receiving the check request, the SERVER side splices the maximum and minimum values into the sql statement conditional constraint statement to execute the query, and returns the result, for example:
SELECT*FROM PART_INFO WHERE val1>＝v1Min and val1<＝v2Max and val2>＝v2Min and val2<＝v2Max
5. after the result set is obtained, (the design end) calculates the similarity of the models in the result set according to a similarity algorithm in sequence and displays the similarity in a report.
Claims (2)
1. A method for judging similarity of part models is characterized by comprising the following steps:
s1, extracting geometric information of a three-dimensional model of a historical part to obtain the geometric information of the three-dimensional model of the historical part; extracting geometric information of the model by using an API (application program interface) development interface of the three-dimensional software, wherein the extracted geometric information comprises: the length x _ len, the width y _ len and the height z _ len of the model, the deviation x _ off, y _ off and z _ off of the center of gravity of the model and the center of the model, the volume v _ prt of the model, the surface area a _ prt of the model and the number n _ srf of curved surfaces of the model;
the historical part three-dimensional model refers to a part three-dimensional model existing in an enterprise database;
s2, storing the extracted geometric information of the three-dimensional model of the historical part into a unified data table;
storing the extracted length x _ len, width y _ len, height z _ len, deviation x _ off, y _ off and z _ off of the center of gravity of the model and the center of the model, volume v _ prt, surface area a _ prt and curved surface number n _ srf of the model into a unified data table, wherein the data table comprises columns of length x _ len, width y _ len and height z _ len of the model, deviation x _ off, y _ off and z _ off of the center of gravity of the model and the center of the model, volume v _ prt, surface area a _ prt and curved surface number n _ srf 9 of the model, and each row in the data table represents geometric information of one model;
length, width, height of the model: the device is used for judging whether the external dimensions of the two models are consistent;
center of gravity of the model and center offset of the model: the device is used for judging whether the material distribution conditions of the two models are consistent or not;
volume of the model: used for judging whether the material wall thicknesses of the two models are consistent or not;
surface area of the model: the method is used for judging whether the detail features of the model surface are consistent or not;
number of curved surfaces of the model: used for judging whether the appearance features of the model conform to each other;
s3, extracting geometric information of the current three-dimensional model of the design end, comparing the geometric information of the current three-dimensional model with the geometric information of the historical three-dimensional model in the unified data sheet, and giving a comparison result;
extracting geometric information of a current model at a design end, wherein the geometric information comprises a length x _ len, a width y _ len and a height z _ len of the model, deviation amounts x _ off, y _ off and z _ off of the center of gravity of the model and the center of the model, a volume v _ prt of the model, a surface area a _ prt of the model and the number n _ srf of curved surfaces of the model;
s4, checking and matching precision is set, and the maximum value and the minimum value of each field in the geometric information of the current model are respectively solved according to the set checking and matching precision P to obtain the maximum value and the minimum value of each field in the geometric information;
respectively solving the maximum value and the minimum value of 9 fields in the geometric information of the current model according to the set checking matching precision P to obtain 18 fields and values;
s5, splicing the maximum value and the minimum value of each field in the geometric information to form an inquiry statement;
splicing query statements according to the obtained 18 fields and values, wherein the query statements comprise the obtained 18 fields and values;
s6, converting the query statement into a query instruction, and querying in the data table obtained in the step S2 to give a query result;
the query result is a retrieved three-dimensional model of the part, and the retrieved three-dimensional model of the part comprises geometric information;
s7, performing similarity calculation on the query results, sequentially calculating the percentage value of the offset of each dimension, and summing the percentage values of the offsets of each dimension to obtain the similarity of each query result;
and S8, displaying the similarity of each query result in a list or graph mode.
2. The method for determining similarity of part models according to claim 1, characterized in that: the checking and matching precision P is 80-100%.
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Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001166789A (en) * | 1999-12-10 | 2001-06-22 | Matsushita Electric Ind Co Ltd | Method and device for voice recognition of chinese using phoneme similarity vector at beginning or end |
| CN101697174B (en) * | 2009-11-06 | 2012-05-09 | 合肥工业大学 | Automatic simplifying and evaluating method of part model facing to steady-state thermal analysis |
| US8489499B2 (en) * | 2010-01-13 | 2013-07-16 | Corelogic Solutions, Llc | System and method of detecting and assessing multiple types of risks related to mortgage lending |
| US20130066601A1 (en) * | 2011-09-13 | 2013-03-14 | CGN & Associates, Inc. | Product attribute visualizer |
| US8908918B2 (en) * | 2012-11-08 | 2014-12-09 | Navigate Surgical Technologies, Inc. | System and method for determining the three-dimensional location and orientation of identification markers |
| KR101460313B1 (en) * | 2013-05-24 | 2014-11-14 | 중앙대학교 산학협력단 | Apparatus and method for robot localization using visual feature and geometric constraints |
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| CN110555219A (en) * | 2018-05-31 | 2019-12-10 | 首都航天机械公司 | Three-dimensional CAD model similarity retrieval system and method based on image recognition |
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