CN111948210A - Mechanical visual defect detection method and system - Google Patents
Mechanical visual defect detection method and system Download PDFInfo
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- CN111948210A CN111948210A CN201910413169.2A CN201910413169A CN111948210A CN 111948210 A CN111948210 A CN 111948210A CN 201910413169 A CN201910413169 A CN 201910413169A CN 111948210 A CN111948210 A CN 111948210A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
Abstract
The invention discloses a machine vision defect detection method and a system thereof, which comprises the following steps of providing a part to be detected, acquiring coordinates of each part of the part to be detected, acquiring three-dimensional data and surface characteristic data of the part according to the coordinates of each part of the part to be detected, generating a realistic three-dimensional data model according to the three-dimensional data and the surface characteristic data of the part to be detected, and carrying out high-dimensional data expression and defect detection on the part to be detected; the method comprises the steps of obtaining coordinates of all parts of a part to be detected, obtaining three-dimensional data and surface characteristic data of the part to be detected according to the coordinate data of all the parts of the part to be detected, carrying out data fusion on the three-dimensional data and the surface characteristic data of the part to be detected to obtain a realistic three-dimensional data model, and then carrying out high-dimensional data expression and defect detection on the part according to the realistic three-dimensional data model, so that the problems that the existing defect detection device is difficult to detect complex parts and cannot accurately detect the part during manual detection are solved.
Description
Technical Field
The invention belongs to the field of defect detection, and particularly relates to a mechanical vision defect detection method and a system thereof.
Background
Modern process automation involves a variety of inspection, production monitoring and part identification applications, such as dimensional inspection and integrity inspection of automatic assembly for mass production of automobile parts, automatic positioning of components for electronic transfer lines, character recognition on ICs, etc., and usually such tasks with high repeatability and intelligence are performed by the naked eye, but in some special cases, such as accurate and rapid measurement of minute dimensions, shape matching, and color recognition, etc., cannot be performed stably by the naked eye.
At present, the main defect detection equipment at home and abroad is formed by combining a 2D camera with a customized light source system, the equipment has poor universality, different detection targets and different field working conditions need to be configured with different detection light source systems, and when parts with complex surfaces, size defect shape changes and complex characteristics are surfaced, the existing system is difficult to obtain a better detection effect.
Disclosure of Invention
The invention aims to provide a mechanical vision defect detection method and a system thereof, which are used for solving the problems that the existing system is difficult to obtain better detection effect and cannot accurately detect parts through manual detection when the parts are faced with parts with complex surfaces, size defect shape changes and complex characteristics in the detection process.
The invention is realized in this way, a mechanical visual defect detection method, which is characterized in that: comprises the following steps of (a) carrying out,
step S1: providing a part to be tested;
step S2: obtaining coordinates of each part of the part to be detected;
step S3: acquiring three-dimensional data and surface characteristic data of the part according to the coordinates of each part of the part to be detected;
step S4: and generating a realistic three-dimensional data model according to the three-dimensional data and the surface characteristic data of the part to be detected, and performing high-dimensional data expression and defect detection on the part to be detected.
A machine vision defect detection system, characterized by: comprises a calibration unit, a single-viewpoint measurement unit and a global data fusion unit,
the calibration unit is used for acquiring coordinates of each part of the part to be measured;
the single-viewpoint measurement unit is used for analyzing the coordinates of all parts of the part and generating three-dimensional data and surface characteristic data;
and the global data fusion unit generates a realistic three-dimensional data model through a data fusion formula according to the three-dimensional data and the surface characteristic data of the part and detects the defect of the part.
Preferably, the calibration unit comprises a mechanical arm and an optical sensor, wherein the mechanical arm is used for driving the optical sensor to move, the optical sensor is used for acquiring coordinates of each part of the part, and the mechanical arm is electrically connected with the optical sensor.
Preferably, the single-viewpoint measurement unit includes a structured light three-dimensional scanner and a mechanical vision detection system, the structured light three-dimensional scanner is electrically connected with the mechanical vision detection system, and the mechanical vision detection system is electrically connected with the optical sensor.
Preferably, the structured light three-dimensional scanner projects multi-frequency sinusoidal grating stripes on the surface of the part to be measured.
Preferably, the machine vision inspection system includes 3 different characteristic light sources of low angle, high angle and near-coaxial.
Preferably, the global data fusion unit comprises an industrial personal computer, and the industrial personal computer is electrically connected with the mechanical vision detection system.
Preferably, the fusion formula is IG-St＝RT-GIT-St+TT-G，
Wherein St is a homonymous point under a sensor coordinate system and a global coordinate system; i isG-StIs a three-dimensional coordinate of St in a global coordinate system; i isT-StIs a three-dimensional coordinate of St in a sensor coordinate system; rT-GAnd IT-SRespectively the rotation matrix and translation vector of the sensor coordinate system to the global coordinate system.
Compared with the prior art, the method has the beneficial effects that: the method comprises the steps of driving an optical sensor to move through a mechanical arm, obtaining each angle coordinate of a part to be detected, obtaining three-dimensional data of the part to be detected through a structured light three-dimensional scanner, obtaining surface characteristic data of the part to be detected through a mechanical vision detection system, fusing each angle coordinate, the three-dimensional data and the surface characteristic data through an industrial personal computer, obtaining a realistic three-dimensional data model of the part, and carrying out defect detection on the part through the industrial personal computer according to the realistic three-dimensional data model of the part so as to solve the problem that the existing system is difficult to obtain a good detection effect when the part faces the part with a complex surface, a complex size, a defect shape and a complex characteristic in the detection process, and further solve the problem that manual detection cannot carry out accurate detection on the part.
Drawings
FIG. 1 is a schematic flow diagram of the present invention;
FIG. 2 is a fusion diagram of the present invention;
FIG. 3 is a schematic diagram of the system of 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.
Example 1
Referring to fig. 1, the present invention provides a method for detecting machine vision defects, comprising the following steps,
step S1: providing a part to be tested;
step S2: obtaining coordinates of each part of the part to be detected;
step S3: acquiring three-dimensional data and surface characteristic data of the part according to the coordinates of each part of the part to be detected;
step S4: and generating a realistic three-dimensional data model according to the three-dimensional data and the surface characteristic data of the part to be detected, and performing high-dimensional data expression and defect detection on the part to be detected.
In the embodiment, each part coordinate of the part is acquired, each part coordinate of the part is analyzed, three-dimensional data and surface characteristic data of the part are obtained according to each part coordinate of the part, and a realistic three-dimensional data model of the part to be detected is acquired by performing data fusion on the three-dimensional data and the surface characteristic data of the part number, so that high-dimensional data expression and defect detection are performed on the part according to the realistic three-dimensional data model.
Example 2
Referring to fig. 2-3, the present invention provides a mechanical visual defect detecting system, which comprises a calibration unit, a single-viewpoint measurement unit and a global data fusion unit,
the calibration unit is used for acquiring coordinates of each part of the part to be measured;
the single-viewpoint measuring unit is used for analyzing the coordinates of all parts of the part and generating three-dimensional data and surface characteristic data;
and the global data fusion unit generates a realistic three-dimensional data model according to the three-dimensional data and the surface characteristic data of the part through a data fusion formula, and detects the defect of the part.
In the embodiment, the calibration unit is arranged to acquire coordinates of each part of the part to be detected, and transmit coordinate data of each part of the part to be detected to the single-view measuring unit, the single-view measuring unit analyzes the received coordinate data of each part of the part to be detected, generates three-dimensional data and surface characteristic data of the part to be detected, and transmits the three-dimensional data and the surface characteristic data of the part to be detected to the global data unit, and the global data unit generates a realistic three-dimensional data model for the three-dimensional data and the surface characteristic data through a data fusion formula, so that defect detection is performed on the part to be detected.
Furthermore, the calibration unit comprises a mechanical arm and an optical sensor, wherein the mechanical arm is used for driving the optical sensor to move, the optical sensor acquires coordinates of each part of the part, and the mechanical arm is electrically connected with the optical sensor.
In this embodiment, the mechanical arm drives the optical sensor to move, so that the optical sensor can measure the part to be measured at multiple angles, and the angular coordinates of the part to be measured are obtained.
Furthermore, the single-viewpoint measurement unit comprises a structured light three-dimensional scanner and a mechanical vision detection system, the structured light three-dimensional scanner is electrically connected with the mechanical vision detection system, and the mechanical vision detection system is electrically connected with the optical sensor.
In this embodiment, the structured light three-dimensional scanner scans the part and simultaneously acquires three-dimensional data of the part according to each angular coordinate of the part to be measured in the optical sensor, and the machine vision detection system scans the part to be measured and simultaneously acquires surface feature data of the part to be measured according to each angular coordinate of the part to be measured in the optical sensor.
Further, the structured light three-dimensional scanner projects multi-frequency sinusoidal grating stripes on the surface of the part to be measured.
In this embodiment, the structured light three-dimensional scanner modulates the sinusoidal grating stripes on the surface of the to-be-measured part, where the sinusoidal grating stripes form a stripe image carrying surface information of the to-be-measured part, so as to generate three-dimensional data of the to-be-measured part.
Further, the machine vision detection system comprises 3 different characteristic light sources of low angle, high angle and near-coaxial.
In the embodiment, the mechanical vision detection system acquires surface characteristic data of the part to be detected by combining different characteristic light sources in the low-angle, high-angle and near-coaxial 3.
Further, the global data fusion unit comprises an industrial personal computer, and the industrial personal computer is electrically connected with the mechanical vision detection system.
In the embodiment, the industrial personal computer performs data fusion on the surface characteristic data and the three-dimensional data characteristic of the part to be detected to generate a third dimension data model, and performs high dimension data expression on the part to be detected by using the third dimension data model of the part to be detected, so as to realize defect detection on the part to be detected.
Further, the data fusion formula is IG-St＝RT-GIT-St+TT-G，
Where St is the local coordinate systemAnd the same-name point under the global coordinate system; i isG-StIs a three-dimensional coordinate of St in a global coordinate system; i isT-StIs a three-dimensional coordinate of St under a local coordinate system; rT-GAnd IT-SRespectively a rotation matrix and a translation vector from the local coordinate system to the global coordinate system.
In this embodiment, the global coordinate system is a coordinate system where the three-dimensional space object is located, the fixed point of the model is expressed based on the global coordinate system, the local coordinate system is an imaginary coordinate system, the relative position of the coordinate system and the object is unchanged from beginning to end, when the local coordinate system is used for understanding the model transformation, all the transformation operations directly act on the local coordinate system, and since the relative positions of the local coordinate system and the object are not aligned, when the local coordinate system is translated, rotated, and scaled, the position and shape of the object in the scene are correspondingly changed, so as to realize the fusion of the three-dimensional data and the surface feature data to generate the realistic three-dimensional data model.
The working principle and the using process of the invention are as follows: the mechanical arm drives the optical sensor to measure coordinates of each part of a part to be measured, the optical sensor transmits coordinate measurement data to the structured light three-dimensional scanner and the mechanical vision detection system, the structured light three-dimensional scanner projects multi-frequency sinusoidal grating stripes to the part to be measured, the sinusoidal grating stripes are modulated by the surface of the part to form stripe images carrying surface information of the part, so that the structured light three-dimensional scanner obtains three-dimensional data of the part to be measured, the mechanical vision detection system scans the part through three different characteristic light sources to obtain surface characteristic data of the part, the structured light three-dimensional scanner and the mechanical vision detection system transmit the three-dimensional data and the surface characteristic data of the part to be measured to the industrial personal computer, and the industrial personal computer transmits the three-dimensional data and the surface characteristic dataG-St＝RT-GIT-St+TT-GAnd performing data fusion on the three-dimensional data and the surface characteristic data of the part to be detected to generate a realistic three-dimensional data model, and realizing high-dimensional data expression and defect three-dimensional data expression of the part to be detected so as to perform defect detection on the part to be detected.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. A machine vision defect detection method is characterized in that: comprises the following steps of (a) carrying out,
step S1: providing a part to be tested;
step S2: obtaining coordinates of each part of the part to be detected;
step S3: acquiring three-dimensional data and surface characteristic data of the part according to the coordinates of each part of the part to be detected;
step S4: and generating a realistic three-dimensional data model according to the three-dimensional data and the surface characteristic data of the part to be detected, and performing high-dimensional data expression and defect detection on the part to be detected.
2. A machine vision defect detection system, characterized by: comprises a calibration unit, a single-viewpoint measurement unit and a global data fusion unit,
the calibration unit is used for acquiring coordinates of each part of the part to be measured;
the single-viewpoint measurement unit is used for analyzing the coordinates of all parts of the part and generating three-dimensional data and surface characteristic data;
and the global data fusion unit generates a realistic three-dimensional data model through a data fusion formula according to the three-dimensional data and the surface characteristic data of the part and detects the defect of the part.
3. The machine vision defect detection system of claim 2, characterized by: the calibration unit comprises a mechanical arm and an optical sensor, wherein the mechanical arm is used for driving the optical sensor to move, the optical sensor acquires coordinates of each part of the part, and the mechanical arm is electrically connected with the optical sensor.
4. The system of claim 2, wherein the single vision measurement unit comprises a structured light three-dimensional scanner and a mechanical vision detection system, the structured light three-dimensional scanner is electrically connected with the mechanical vision detection system, and the mechanical vision detection system is electrically connected with the optical sensor.
5. The system of claim 4, wherein: the structured light three-dimensional scanner projects multi-frequency sinusoidal grating stripes on the surface of the part to be measured.
6. The system of claim 4, wherein: the mechanical vision detection system comprises 3 different characteristic light sources of low angle, high angle and near coaxiality.
7. The system of claim 2, wherein: the global data fusion unit comprises an industrial personal computer which is electrically connected with the mechanical vision detection system.
8. The system of claim 2, wherein: the fusion formula is IG-St＝RT-GIT-St+TT-G，
Wherein St is a homonymous point under a sensor coordinate system and a global coordinate system; i isG-StIs a three-dimensional coordinate of St in a global coordinate system; i isT-StIs a three-dimensional coordinate of St in a sensor coordinate system; rT-GAnd IT-SRespectively the rotation matrix and translation vector of the sensor coordinate system to the global coordinate system.
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