CN107121063A - The method for detecting workpiece - Google Patents
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- CN107121063A CN107121063A CN201710238445.7A CN201710238445A CN107121063A CN 107121063 A CN107121063 A CN 107121063A CN 201710238445 A CN201710238445 A CN 201710238445A CN 107121063 A CN107121063 A CN 107121063A
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- 238000000034 method Methods 0.000 title claims abstract description 46
- 238000001514 detection method Methods 0.000 claims abstract description 129
- FGUUSXIOTUKUDN-IBGZPJMESA-N C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 Chemical compound C1(=CC=CC=C1)N1C2=C(NC([C@H](C1)NC=1OC(=NN=1)C1=CC=CC=C1)=O)C=CC=C2 FGUUSXIOTUKUDN-IBGZPJMESA-N 0.000 claims abstract description 5
- 238000012545 processing Methods 0.000 claims description 22
- 238000012546 transfer Methods 0.000 claims description 19
- 230000008569 process Effects 0.000 claims description 15
- 238000007689 inspection Methods 0.000 claims description 12
- 238000006073 displacement reaction Methods 0.000 claims description 11
- 230000007547 defect Effects 0.000 claims description 9
- 230000000694 effects Effects 0.000 claims description 6
- 238000003860 storage Methods 0.000 claims description 6
- 238000000605 extraction Methods 0.000 claims description 4
- 238000003672 processing method Methods 0.000 claims description 4
- 241001292396 Cirrhitidae Species 0.000 claims description 3
- 238000003709 image segmentation Methods 0.000 claims description 3
- 230000011218 segmentation Effects 0.000 claims description 3
- 238000012360 testing method Methods 0.000 abstract description 4
- 238000005259 measurement Methods 0.000 abstract 7
- 230000005540 biological transmission Effects 0.000 abstract 2
- 238000004519 manufacturing process Methods 0.000 description 5
- 230000032258 transport Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000008901 benefit Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000003708 edge detection Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
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- 238000004381 surface treatment Methods 0.000 description 2
- 238000004148 unit process Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 1
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- 238000005516 engineering process Methods 0.000 description 1
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- 230000007246 mechanism Effects 0.000 description 1
- 230000002195 synergetic effect Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
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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
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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
- G01B11/22—Measuring arrangements characterised by the use of optical techniques for measuring depth
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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
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/155—Segmentation; Edge detection involving morphological operators
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30164—Workpiece; Machine component
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Theoretical Computer Science (AREA)
- Quality & Reliability (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention discloses a kind of method for detecting workpiece, including：A) workpiece for measurement control execution unit of the central control unit in transhipment memory cell selects corresponding replaceable fixture in frock unit；B) execution unit picks up workpiece for measurement using replaceable fixture and workpiece for measurement is transported into detection unit or depth detection unit；C) workpiece for measurement information is gathered and by gathered information transmission to central control unit by detection unit or depth detection unit；D) workpiece for measurement is transported to relay unit and temporarily put by execution unit；E) central control unit controls execution unit to change replaceable fixture according to workpiece for measurement, and picks up the workpiece for measurement in relay unit and detected；F) by gathered information transmission to central control unit；G) repeat step b and step f；H) data of collection are handled by central control unit.This method detects that testing result is accurate, and efficiency high by way of automation to workpiece.
Description
Technical Field
The invention relates to the field of production and manufacturing, in particular to a method for detecting a workpiece.
Background
At present, under the background that the economy and novel technology of emerging markets continuously rise, the production of high-quality and low-price products is an urgent need for enterprise development. In the traditional device detection, workers are required to be on duty so as to facilitate detection at any time, however, the detection efficiency of the working mode is not high, the production resources are greatly wasted, and reliable automatic production cannot be realized; the more important reason is that most people judge whether the size of the part is qualified or not by subjective consciousness or a rough and shallow testing method for measuring the size precision of the product produced on an industrial production line, the precision detected by the judging method is poor, the misjudgment rate is high, the precision can not meet the requirements of customers at all, and the detection speed is low and the efficiency is low.
Disclosure of Invention
Aiming at the technical problems in the prior art, the invention provides a method for detecting a workpiece, which can realize the automation of product detection and improve the detection precision and efficiency.
To achieve the above object, the present invention provides a method for inspecting a workpiece, comprising:
a) the central control unit controls the execution unit to select a corresponding replaceable tool in the tool unit according to the workpiece to be tested in the transfer storage unit;
b) the execution unit picks up the workpiece to be detected by using the replaceable tool and conveys the workpiece to be detected to the detection unit or the depth detection unit;
c) the detection unit or the depth detection unit collects the information of the workpiece to be detected and transmits the collected information to the central control unit;
d) the execution unit conveys the workpiece to be detected to the transfer unit and places the workpiece to be detected in the transfer unit;
e) the central control unit controls the execution unit to replace the replaceable tool according to the workpiece to be detected, picks up the workpiece to be detected in the transfer unit and conveys the workpiece to be detected to the detection unit or the depth detection unit;
f) the detection unit or the depth detection unit collects the information of the workpiece to be detected and transmits the collected information to the central control unit;
g) repeating the step b and the step f until the detection information of all the detected workpieces is acquired;
h) the central control unit respectively identifies and processes the acquired image information by using an image identification module for detecting the image information processed by the image processing module and an image processing module for processing the image information so as to determine the shape and the size of the workpiece to be measured.
According to one aspect of the invention, the execution unit comprises a manipulator for carrying workpieces and a quick-change head mounted at the free end of the manipulator for mounting a replaceable tool.
According to one aspect of the invention, the depth detection unit comprises a laser sensor support and a laser displacement sensor supported on the laser sensor support for acquiring depth image information of the workpiece.
According to an aspect of the invention, the detection unit comprises:
the first camera lens is used for acquiring image information of the overall dimension and/or the surface shape of the workpiece;
the second camera lens is used for acquiring image information of the internal size and/or the internal shape of the workpiece;
the third camera lens is used for acquiring the image information of the processed quality of the workpiece;
and the fourth camera lens is used for acquiring the image information of the surface shape of the workpiece.
According to an aspect of the present invention, the first camera lens, the second camera lens, the third camera lens and the fourth camera lens in the detection unit are all a Balser camera using a fixed focus lens.
According to an aspect of the invention, in the step h), the central control unit processes the information of the workpiece to be detected collected by the detection unit or the depth detection unit by using the image recognition module, and distinguishes the information of the detection size and the information of the detection defect.
According to an aspect of the invention, in the step h), the image processing module in the central control unit processes the image information collected in the steps b) and f) as follows:
h1) converting the collected color image into a gray image;
h2) setting the gray value of a pixel point on the image to be 0 or 255, so that the whole image presents an obvious black-and-white effect;
h3) dividing the image into a plurality of non-overlapping areas according to the characteristics of gray scale, color, texture, shape and the like, and enabling the characteristics to present similarity in the same area and obvious difference among different areas;
h4) extracting image information, determining whether the point of each image belongs to an image feature, and dividing the points on the image into different subsets according to a feature extraction result.
According to one aspect of the invention, said step h3) uses a threshold-based segmentation method to calculate one or more gray threshold values by using gray features, and compares the gray value of each pixel in the image with the threshold values, and finally classifies the pixels into proper classes according to the comparison result.
According to one aspect of the invention, the processing method of the image information in the step h) adopts a Halcon algorithm; wherein,
said step h1) is implemented with the operator rgb 1-to-gray;
the step h2) is realized by adopting an operator fast-threshold;
the step h3) adopts an operator threshold to realize the image segmentation of the global threshold;
said step h4) uses the operator select-shape to classify the points with consistent area and radius into a subset.
According to one aspect of the invention, the first camera lens, the second camera lens, the third camera lens and the fourth camera lens in the detection unit transmit the acquired image information to the central control unit through a TCP/IP protocol.
According to one aspect of the invention, the laser displacement sensor transmits the acquired information to the central control unit through a serial port protocol.
According to one scheme of the invention, an automatic detection system is adopted to replace a manual detection mode, so that the labor intensity is reduced, the labor cost is saved, and the working efficiency and the enterprise benefit are improved. Meanwhile, a machine vision detection mode is adopted, and a detection terminal is combined, so that the unification of workpiece detection standards is achieved, the defects of subjective consciousness judgment or rough and shallow test in the manual detection process are overcome, and the product detection accuracy is improved.
According to one aspect of the present invention, a vision inspection system comprising a plurality of cameras and light source systems can meet the requirements of all-around inspection from shape, size, position, to processing defects, surface treatment, and the like. Meanwhile, the laser displacement sensor is additionally arranged to perform supplementary detection on depth sizes and the like which are difficult to detect visually, and the detection is more flexible. The detection difficulty of the grooves and the like of the workpiece with small size is reduced, the effect of being more beneficial is achieved, and the situations of false detection, missing detection and the like in the manual detection process are reduced.
According to one scheme of the invention, the execution mechanism can pick up different types of workpieces through different tools, so that the application range of the whole detection method is improved, the detection of different workpieces can be conveniently realized only by inputting related data into the detection terminal, further more products can be detected through the method, the resources of enterprises are saved, and the benefits of the enterprises are improved.
Drawings
FIG. 1 is a schematic representation of a detection apparatus for use in the present invention;
FIG. 2 is a flow chart schematically representing the detection method of the present invention;
fig. 3 is a diagram schematically showing an image processing method in the detection method of the present invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
In describing embodiments of the present invention, the terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in an orientation or positional relationship that is based on the orientation or positional relationship shown in the associated drawings, which is for convenience and simplicity of description only, and does not indicate or imply that the referenced device or element must have a particular orientation, be constructed and operated in a particular orientation, and thus, the above-described terms should not be construed as limiting the present invention.
The present invention is described in detail below with reference to the drawings and the specific embodiments, which are not repeated herein, but the embodiments of the present invention are not limited to the following embodiments.
Figure 1 is a schematic representation of a detection device for use in the present invention. As shown in fig. 1, the inspection apparatus used in the present method of inspecting a workpiece includes: the system comprises a central control unit 1 (not shown in the figure), an execution unit 2, a transfer unit 3, a depth detection unit 4, a detection unit 5, a transfer storage unit 6 and a tooling unit 7. The depth detection unit 4 is used for collecting depth information of workpiece surface depressions, such as grooves, defects, blind holes, and the like of the workpiece surface. The detection unit 5 is used for collecting workpiece size, shape and quality information. The detection unit 5 performs visual identification and acquisition of detection information on the detected workpiece with different characteristics and requirements by adopting different types of camera lenses. The automatic detection equipment can realize the automation of the whole detection equipment through the control of the central control unit 1, operates efficiently and quickly, has accurate detection results, does not need manual participation in the working process of the detection equipment, improves the safety, saves the manpower and reduces the cost.
FIG. 2 is a flow chart schematically illustrating the detection method of the present invention. The detection flow of the method for detecting the workpiece is specifically described with reference to fig. 1 and 2, and the specific steps are as follows:
a) the central control unit 1 controls the execution unit 2 to select a corresponding replaceable tool in the tool unit 7 according to the workpiece to be tested in the transfer storage unit 6.
Referring to fig. 1, the execution unit 2 comprises a manipulator 201 for handling workpieces and a quick-change head 202 mounted at the free end of the manipulator for mounting a replaceable tool. A replaceable tool for picking up a workpiece is carried in the tool unit 7. In this step, the transferring and storing unit 6 conveys the workpiece to be detected to a designated position, the central control unit 1 controls the manipulator 201 to select a corresponding replaceable tool in the tool unit 7, and the quick-change head 202 at the end of the manipulator 201 is matched and locked with the replaceable tool, so that the next step of work is performed. Through the cooperation between manipulator 201 and the replaceable frock of difference, can realize carrying out the centre gripping to the work piece different positions to make the work piece can all-round obtain detecting. Meanwhile, the tool can be replaced in a replaceable manner, so that the detection method is suitable for different types of workpieces, and the application range of the detection method is enlarged.
b) The execution unit 2 picks up the workpiece to be detected by using the replaceable tool and conveys the workpiece to be detected to the detection unit 5 or the depth detection unit 4.
In this step, the central control unit 1 controls the robot 201 to pick up the workpiece transported by the transfer storage unit 6. The robot 201 moves to the position of the transfer storage unit 6 and picks up the workpiece to be inspected by means of the end-connected replaceable tooling. Under the control of the central control unit 1, the robot 201 conveys the picked-up workpiece to the inspection unit 5 or the depth inspection unit 4 for the next inspection.
c) The information of the workpiece to be detected is collected by the detection unit 5 or the depth detection unit 4 and the collected information is transmitted to the central control unit 1.
Referring to fig. 1, according to an embodiment of the present invention, the depth detection unit 4 includes a laser sensor support 401 and a laser displacement sensor 402 supported on the laser sensor support 401 for acquiring depth image information of a workpiece. In this embodiment, the laser displacement sensor 402 is mainly used to collect depth information such as notch depth and hole depth of the workpiece.
Referring to fig. 1, according to an embodiment of the present invention, the detecting unit 5 includes: a first camera lens 501 for acquiring information on the overall dimension and/or surface shape of a workpiece; a second camera lens 502 for acquiring information on the internal size and/or internal shape of the workpiece; the third camera lens 503 is used for acquiring the processed quality information of the workpiece; and a fourth camera lens 504 for collecting workpiece surface shape information. In this embodiment, the first camera lens 501, the second camera lens 502, the third camera lens 503, and the fourth camera lens 504 are Balser cameras using fixed focus lenses. The detection unit 5 is also provided with a light source device which can emit uniform white light and assist the lens in the detection unit 4 to obtain high-quality images, so that the detection characteristics of the workpiece are further protruded, and the detection effect of the workpiece characteristics is ensured.
The robot 201 transports the workpiece to below the corresponding lens, and detects the workpiece through the lens. And adjusting a controller of the light source device, initializing uniform white light parameters of the light source device, and controlling the light source to emit uniform white light. When the manipulator 201 transports a workpiece to be detected to the lower part of the lens, the distance between the workpiece and the lens is actively adjusted, so that the lens in the detection unit 5 can be imaged clearly enough and the characteristic information of the workpiece can be accurately acquired, thereby ensuring the accuracy of the detection result in the next detection process.
Alternatively, the robot 201 transports the workpiece to the position of the laser displacement sensor 402, so that the laser displacement sensor 402 can acquire depth information such as the depth of the notch, the depth of the hole, and the like on the workpiece.
d) The execution unit 2 conveys the workpiece to be detected to the transfer unit 3 and places the workpiece to be detected in the transfer unit 3;
e) the central control unit 1 controls the execution unit 2 to replace the replaceable tool according to the workpiece to be detected, picks up the workpiece to be detected in the transfer unit 3 and conveys the workpiece to be detected to the detection unit 5 or the depth detection unit 4;
because the workpiece to be detected has shapes and structures with different complexity, detection steps need to be determined according to the shapes and the structures of the workpiece to be detected, and the manipulator 201 needs to select or replace a replaceable tool to realize the all-dimensional detection of the workpiece to be detected according to different detection steps. When the acquisition information or detection of one process step is completed and the replaceable tool 102 needs to be replaced to continue the detection of the next process step, the mechanical arm 201 is to transfer the workpiece to be detected to the transfer unit 3 for temporary placement, and after the replaceable tool is replaced by the mechanical arm 201, the workpiece to be detected in the transfer unit 3 is transferred to the detection unit 5 or the depth detection unit 4 for detection again.
f) The detection unit 5 or the depth detection unit 4 collects the information of the workpiece to be detected and transmits the collected information to the central control unit 1;
the data collected by the detection unit 5 or the depth detection unit 4 in the above steps are transmitted to the central processing unit 1 for further processing. In the present embodiment, the detection unit 5 transmits the acquired image information to the central control unit 1 through the TCP/IP protocol. The depth detection unit 4 transmits the collected information to the central control unit 1 through a serial port protocol.
g) Repeating the step b and the step f until the detection information of all the detected workpieces is acquired;
h) the central control unit 1 respectively identifies and processes the acquired image information by using an image identification module for detecting the image information processed by the image processing module and an image processing module for processing the image information so as to determine the shape and the size of the workpiece to be measured.
In this step, the central control unit 1 processes the information of the workpiece to be detected collected by the detection unit 5 or the depth detection unit 4 by using the image recognition module, and distinguishes the information of the detection size and the information of the detection defect.
By the aid of the detection unit 5 and the depth detection unit 4, and in combination with flexible operation of the execution unit 2, the shape, the position, the machining defect, the surface treatment and the like of the workpiece can be detected in all directions. The appearance of the workpiece is clearly imaged through the multiple different lenses in the detection unit 5, so that the quality problems such as tiny defects which are difficult to identify by naked eyes in the manual detection process can be detected, the requirement of workpiece detection is improved, and the quality of the workpiece is improved. The laser displacement sensor in the depth detection unit 4 performs supplementary detection on depth sizes and the like which are difficult to detect visually, so that the detection is more convenient and flexible. The method has the beneficial effects of reducing the detection difficulty of the grooves and the like on the workpiece with smaller volume, improving the detection precision and avoiding the occurrence of false detection, missing detection and the like in the manual detection process.
Fig. 3 is a diagram schematically showing an image processing method in the detection method of the present invention. Referring to fig. 2 and 3, after acquiring the information of the workpiece to be detected transmitted by the detection unit 5 or the depth detection unit 4, the central control unit 1 needs to perform further processing and determine the quality of the workpiece, and the central control unit 1 performs information processing through the image processing module and the image recognition module by using a Halcon algorithm. The method comprises the following steps:
h1) and converting the collected color image into a gray image.
As shown in fig. 2 and 3, the central control unit 1 acquires the color image transmitted by the detection unit 5, and converts the color image into a gray image through the image processing module. In this embodiment, the process operator rgb1-to-gray is used to realize this function when converting a color image into a grayscale image.
h2) The gray value of the pixel point on the image is set to be 0 or 255, so that the whole image presents obvious black and white effect.
And the image processing module converts the color image into a gray image and then performs binarization processing on the image. That is, the gray value of the pixel point on the image is set to 0 or 255, so that the whole image has an obvious black and white effect. The processing of the pixel points on the image needs to be completed by the fast-threshold operator.
h3) Dividing the image into a plurality of non-overlapping areas according to the characteristics of gray scale, color, texture, shape and the like, and enabling the characteristics to present similarity in the same area and obvious difference among different areas;
and further segmenting the image after binarization processing according to the step, segmenting the image by an operator threshold global value in the process of segmenting the image to realize image segmentation, calculating one or more gray threshold values by a threshold-based segmentation method through gray features, comparing the gray value of each pixel in the image with the threshold value, and finally classifying the pixels into proper categories according to the comparison result.
h4) Extracting image information, determining whether the point of each image belongs to an image feature, and dividing the points on the image into different subsets according to a feature extraction result.
In this step, different subsets of the feature extraction results may be divided into isolated points, continuous curves, or continuous regions. In the method, the operator select-shape can be used for grouping the points with consistent area and radius into a subset.
And further carrying out image pixel edge detection and image sub-pixel edge detection on the extracted image information, and outputting edge characteristics. And the image identification module performs size detection and defect detection according to the edge characteristics of the output image. The central control unit 1 simultaneously determines the quality of the workpiece in combination with the data collected by the laser displacement sensor 402.
The central control unit 1 identifies and detects the collected workpiece information through the synergistic effect of the image processing module and the image identification module, so that the workpiece detection can be efficient and high in precision, the detection standard is unified, the workpiece detection result is more accurate, and the problems that whether the sizes of parts are qualified or not is judged by a subjective consciousness or shallow and subjective testing method in the manual detection process, the detection precision is low, the misjudgment rate is high and the like are solved.
The foregoing is illustrative of specific embodiments of the present invention and reference should be made to the implementation of apparatus and structures not specifically described herein, which are understood to be generic to the means and methods available in the art.
The above description is only one embodiment of the present invention, and is not intended to limit the present invention, and it is apparent to those skilled in the art that various modifications and variations can be made in the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (11)
1. A method of inspecting a workpiece, comprising:
a) the central control unit (1) controls the execution unit (2) to select a corresponding replaceable tool in the tool unit (7) according to the workpiece to be tested in the transfer storage unit (6);
b) the execution unit (2) picks up the workpiece to be detected by using the replaceable tool and conveys the workpiece to be detected to the detection unit (5) or the depth detection unit (4);
c) the detection unit (5) or the depth detection unit (4) collects the information of the workpiece to be detected and transmits the collected information to the central control unit (1);
d) the execution unit (2) conveys the workpiece to be detected to the transfer unit (3) and places the workpiece to be detected in the transfer unit (3);
e) the central control unit (1) controls the execution unit (2) to replace the replaceable tool according to the workpiece to be detected, picks up the workpiece to be detected in the transfer unit (3) and conveys the workpiece to be detected to the detection unit (5) or the depth detection unit (4);
f) the detection unit (5) or the depth detection unit (4) collects the information of the workpiece to be detected and transmits the collected information to the central control unit (1);
g) repeating the step b and the step f until the detection information of all the detected workpieces is acquired;
h) the central control unit (1) respectively identifies and processes the acquired image information by using an image identification module for detecting the image information processed by the image processing module and an image processing module for processing the image information so as to determine the shape and the size of the workpiece to be measured.
2. The method of inspecting a workpiece according to claim 1, characterised in that the execution unit (2) comprises a robot (201) for handling workpieces and a fast-changing head (202) mounted at the free end of the robot for mounting a replaceable tool.
3. The method of inspecting a workpiece according to claim 2, characterized in that the depth detection unit (4) comprises a laser sensor holder (401) and a laser displacement sensor (402) supported on the laser sensor holder (401) for acquiring depth image information of the workpiece.
4. A method of inspecting a workpiece according to claim 3, characterized in that the inspection unit (5) comprises:
the first camera lens (501) is used for acquiring image information of the overall dimension and/or the surface shape of the workpiece;
a second camera lens (502) for acquiring image information of the internal size and/or internal shape of the workpiece;
the third camera lens (503) is used for acquiring the image information of the processed quality of the workpiece;
and the fourth camera lens (504) is used for acquiring image information of the surface shape of the workpiece.
5. The method of inspecting a workpiece according to claim 4, characterized in that the first camera lens (501), the second camera lens (502), the third camera lens (503) and the fourth camera lens (504) in the inspection unit (5) are all Balser cameras employing fixed focus lenses.
6. The method of inspecting a workpiece according to claim 5, characterized in that in step h), the central control unit (1) processes the workpiece information to be inspected, collected by the inspection unit (5) or the depth inspection unit (4), by means of an image recognition module, distinguishing between information of inspection size and information of inspection defects.
7. Method for inspecting workpieces according to one of claims 1 to 6, characterized in that in step h), the image processing module in the central control unit (1) processes the image information acquired in step b) and step f) as follows:
h1) converting the collected color image into a gray image;
h2) setting the gray value of a pixel point on the image to be 0 or 255, so that the whole image presents an obvious black-and-white effect;
h3) dividing the image into a plurality of non-overlapping areas according to the characteristics of gray scale, color, texture, shape and the like, and enabling the characteristics to present similarity in the same area and obvious difference among different areas;
h4) extracting image information, determining whether the point of each image belongs to an image feature, and dividing the points on the image into different subsets according to a feature extraction result.
8. The method of claim 7, wherein said step h3) is implemented by using a threshold-based segmentation method, calculating one or more gray threshold values from the gray features, comparing the gray value of each pixel in the image with the threshold values, and classifying the pixels into appropriate classes according to the comparison result.
9. The method of inspecting a workpiece according to claim 8, wherein the processing method of the image information in the step h) adopts a Halcon algorithm; wherein,
said step h1) is implemented with the operator rgb 1-to-gray;
the step h2) is realized by adopting an operator fast-threshold;
the step h3) adopts an operator threshold to realize the image segmentation of the global threshold;
said step h4) uses the operator select-shape to classify the points with consistent area and radius into a subset.
10. The method of claim 6, wherein the first camera lens (501), the second camera lens (502), the third camera lens (503) and the fourth camera lens (504) in the detection unit (5) transmit the collected image information to the central control unit through a TCP/IP protocol.
11. The method of inspecting a workpiece of claim 10, wherein the laser displacement sensor (402) transmits the collected information to a central control unit via a serial protocol.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710238445.7A CN107121063A (en) | 2017-04-13 | 2017-04-13 | The method for detecting workpiece |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710238445.7A CN107121063A (en) | 2017-04-13 | 2017-04-13 | The method for detecting workpiece |
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| CN107121063A true CN107121063A (en) | 2017-09-01 |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108168600A (en) * | 2017-12-13 | 2018-06-15 | 全椒祥瑞塑胶有限公司 | A kind of injecting products Intelligentized control method based on secondary detection |
| CN108663382A (en) * | 2018-05-10 | 2018-10-16 | 苏州大学 | The method and device of the paper surface defects detection of view-based access control model conspicuousness |
| CN113189009A (en) * | 2021-05-17 | 2021-07-30 | 石家庄格力电器小家电有限公司 | System for detecting surface treatment quality of smoke collecting hood |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106546173A (en) * | 2016-11-01 | 2017-03-29 | 宁波舜宇智能科技有限公司 | For detecting the equipment and its detection method of components and parts |
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| CN106546173A (en) * | 2016-11-01 | 2017-03-29 | 宁波舜宇智能科技有限公司 | For detecting the equipment and its detection method of components and parts |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108168600A (en) * | 2017-12-13 | 2018-06-15 | 全椒祥瑞塑胶有限公司 | A kind of injecting products Intelligentized control method based on secondary detection |
| CN108663382A (en) * | 2018-05-10 | 2018-10-16 | 苏州大学 | The method and device of the paper surface defects detection of view-based access control model conspicuousness |
| CN113189009A (en) * | 2021-05-17 | 2021-07-30 | 石家庄格力电器小家电有限公司 | System for detecting surface treatment quality of smoke collecting hood |
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