CN114324354A - Textile flaw detection method based on machine vision template - Google Patents
Textile flaw detection method based on machine vision template Download PDFInfo
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- CN114324354A CN114324354A CN202111618425.5A CN202111618425A CN114324354A CN 114324354 A CN114324354 A CN 114324354A CN 202111618425 A CN202111618425 A CN 202111618425A CN 114324354 A CN114324354 A CN 114324354A
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- 239000004753 textile Substances 0.000 title claims abstract description 191
- 238000001514 detection method Methods 0.000 title claims abstract description 87
- 230000000007 visual effect Effects 0.000 claims abstract description 39
- 238000000034 method Methods 0.000 claims abstract description 12
- 230000007547 defect Effects 0.000 claims abstract description 8
- 238000004458 analytical method Methods 0.000 claims abstract description 4
- 238000005259 measurement Methods 0.000 claims description 25
- 238000004088 simulation Methods 0.000 claims description 7
- 238000003860 storage Methods 0.000 claims description 6
- 238000012423 maintenance Methods 0.000 claims description 3
- 230000037303 wrinkles Effects 0.000 claims description 3
- 238000007689 inspection Methods 0.000 claims 3
- 230000009286 beneficial effect Effects 0.000 abstract description 2
- 230000037237 body shape Effects 0.000 description 2
- 239000004744 fabric Substances 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
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- 230000000295 complement effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 229910044991 metal oxide Inorganic materials 0.000 description 1
- 150000004706 metal oxides Chemical class 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
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- 239000002759 woven fabric Substances 0.000 description 1
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Abstract
The invention discloses a textile flaw detection method based on a machine vision template, which comprises the following steps: s1, detecting template data, preparing a visual detection device, placing the qualified textile without defects on a detection table of the visual detection device, detecting various data of the qualified textile, recording S2 template data, obtaining various data of the qualified textile after the step S1 is finished, and recording the data into an analysis comparison computer, and S3, placing the textile. The invention has the beneficial effects that: by adopting the method, the length, the width, the thickness and the textile line gap of the textile are measured and compared respectively, the flaw detection precision can be ensured, the data detection when the textile is not worn and the textile is worn is simulated respectively, the service condition of the textile when people wear the textile can be simulated, the precision of a final detection result is improved, and the flaw detection precision can be ensured.
Description
Technical Field
The invention relates to the technical field of textile detection, in particular to a textile flaw detection method based on a machine vision template.
Background
Textile, i.e. a product made by textile processing. The method comprises the steps of yarn, woven fabric, knitted fabric, braided fabric and the like, flaw sampling detection needs to be carried out on the textile in the production and manufacturing process of the textile, the conventional detection adopts a manual mode, and the mode is time-consuming, labor-consuming and low in efficiency. In the existing textile flaw detection, a visual detection mode is adopted for detection. Visual inspection is to use a robot to replace human eyes for measurement and judgment. The visual detection means that a machine vision product (namely an image shooting device which is divided into a CMOS (complementary metal oxide semiconductor) product and a CCD (charge coupled device) product) converts a shot target into an image signal, transmits the image signal to a special image processing system, and converts the image signal into a digital signal according to information such as pixel distribution, brightness, color and the like; in the existing textile visual detection method, only flaw detection of the textile when the textile is not worn is carried out, the detection result is general in accuracy, and the detection has certain limitation.
Disclosure of Invention
The invention mainly aims to provide a textile flaw detection method based on a machine vision template, which can effectively solve the problems in the background technology.
In order to achieve the purpose, the invention adopts the technical scheme that:
a textile flaw detection method based on a machine vision template comprises the following steps:
s1, detecting template data, preparing a visual detection device, placing the qualified textile without defects on a detection table of the visual detection device, and detecting each item of data of the qualified textile;
s2, inputting template data, obtaining various data of qualified textiles after the step S1 is completed, and inputting the data into an analysis comparison computer;
s3, placing the textile, and after the step S2 is finished, placing the textile needing visual detection on a detection table of a visual detection device to enable the textile to be consistent with the template in placement position and guarantee the textile to be consistent with the template in placement mode;
s4, measuring the length and width of the textile when the textile is not worn, after the step S3 is completed, measuring the length and width of the textile to be detected respectively by using a visual detection device, and feeding the measurement result back to the computer for storage;
s5, measuring the thickness of the textile when the textile is not worn, changing the orientation of a detection camera in a visual detection device after the step S4 is completed, measuring the thickness of the textile to be detected by using the visual detection device respectively, and feeding the measurement result back to a computer for storage;
s6, measuring the gaps of the textile threads when the textile threads are not worn, measuring the gaps of the textile threads in the textile to be detected by using a visual detection device after the step S5 is finished, and feeding back the measured data to a computer;
s7, comparing the data for the first time, and after the data of the textile is detected when the textile is not worn, transmitting the length and width data detected in the step S3, the thickness data detected in the step S4 and the textile line maintenance data detected in the step S5 to a comparison module of a computer, and comparing the data of the textile to be detected with the data of the qualified textile to obtain a comparison result;
s8, simulating the length and width measurement of the textile when the textile is worn, after the step S7 is completed, performing simulated wearing, placing the textile to be detected during the simulated wearing on a detection table of a visual detection device, measuring the length and width of the textile during the simulated wearing, and feeding the measurement result back to a computer;
s9, thickness measurement of the textile during wearing is simulated, when length and width detection of the textile during wearing is finished, the thickness measurement of the textile during wearing is carried out, and the measurement result is fed back to the computer;
s10, measuring the textile thread gap during the simulated wearing, after the step S9 is finished, measuring the textile thread gap of the textile during the simulated wearing by using a visual detection device, and feeding the measurement result back to the computer;
s11, comparing the data for the second time, namely comparing the data of the textile during the simulated wearing with the data of the qualified textile during the simulated wearing after the data of the textile during the simulated wearing are detected;
s12, comparing comprehensive data, namely after the step S11 is finished, putting the comparison result of the textile when the textile is not worn and the comparison result of the textile when the textile is simulated to be worn together for comparison;
and S13, outputting results, and outputting all comparison results after the step S12 is finished.
In step S1, when detecting the template data, each item of data is detected when the qualified textile is not worn and each item of data is detected when the textile is worn.
In the step S1, when detecting each item of data of the qualified textile, the length, width, thickness, and textile thread gap of the qualified textile in both the unworn state and the worn state are detected.
In step S1, the detection table of the visual detection device is a rotary structure, and rotates with the textile during detection.
In step S3, when the textile is placed, the textile is laid on the detection table of the visual detection device to avoid wrinkles.
In step S8, when wearing the simulation, different wearing simulations can be performed according to different body shapes to ensure that more data can be detected for comparison.
In the step S12, when the comparison of the integrated data is performed, the data of the textile when the textile is not worn and the data of the textile when the textile is simulated to be worn are respectively compared correspondingly.
Compared with the prior art, the invention has the following beneficial effects: by adopting the method, the length, the width, the thickness and the textile line gap of the textile are measured and compared respectively, the flaw detection precision can be ensured, the data detection when the textile is not worn and the textile is worn is simulated respectively, the service condition of the textile when people wear the textile can be simulated, the precision of a final detection result is improved, and the flaw detection precision can be ensured.
Drawings
FIG. 1 is a schematic process flow diagram of a textile defect detection method based on a machine vision template according to the present invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
Example 1
A method for detecting textile defects based on a machine vision template as shown in fig. 1 comprises the following steps:
s1, detecting template data, preparing a visual detection device, placing the qualified textile without defects on a detection table of the visual detection device, and detecting each item of data of the qualified textile;
s2, inputting template data, obtaining various data of qualified textiles after the step S1 is completed, and inputting the data into an analysis comparison computer;
s3, placing the textile, and after the step S2 is finished, placing the textile needing visual detection on a detection table of a visual detection device to enable the textile to be consistent with the template in placement position and guarantee the textile to be consistent with the template in placement mode;
s4, measuring the length and width of the textile when the textile is not worn, after the step S3 is completed, measuring the length and width of the textile to be detected respectively by using a visual detection device, and feeding the measurement result back to the computer for storage;
s5, measuring the thickness of the textile when the textile is not worn, changing the orientation of a detection camera in a visual detection device after the step S4 is completed, measuring the thickness of the textile to be detected by using the visual detection device respectively, and feeding the measurement result back to a computer for storage;
s6, measuring the gaps of the textile threads when the textile threads are not worn, measuring the gaps of the textile threads in the textile to be detected by using a visual detection device after the step S5 is finished, and feeding back the measured data to a computer;
s7, comparing the data for the first time, and after the data of the textile is detected when the textile is not worn, transmitting the length and width data detected in the step S3, the thickness data detected in the step S4 and the textile line maintenance data detected in the step S5 to a comparison module of a computer, and comparing the data of the textile to be detected with the data of the qualified textile to obtain a comparison result;
s8, simulating the length and width measurement of the textile when the textile is worn, after the step S7 is completed, performing simulated wearing, placing the textile to be detected during the simulated wearing on a detection table of a visual detection device, measuring the length and width of the textile during the simulated wearing, and feeding the measurement result back to a computer;
s9, thickness measurement of the textile during wearing is simulated, when length and width detection of the textile during wearing is finished, the thickness measurement of the textile during wearing is carried out, and the measurement result is fed back to the computer;
s10, measuring the textile thread gap during the simulated wearing, after the step S9 is finished, measuring the textile thread gap of the textile during the simulated wearing by using a visual detection device, and feeding the measurement result back to the computer;
s11, comparing the data for the second time, namely comparing the data of the textile during the simulated wearing with the data of the qualified textile during the simulated wearing after the data of the textile during the simulated wearing are detected;
s12, comparing comprehensive data, namely after the step S11 is finished, putting the comparison result of the textile when the textile is not worn and the comparison result of the textile when the textile is simulated to be worn together for comparison;
and S13, outputting results, and outputting all comparison results after the step S12 is finished.
In step S1, when detecting the template data, each item of data is detected when the qualified textile is not worn and each item of data is detected when the textile is worn, and in step S1, when detecting each item of data of the qualified textile, the length, width, thickness and textile line gap of the qualified textile in two states of being not worn and worn are detected, in step S1, the detection table of the visual detection device is a rotary structure, and the textile is driven to rotate during detection, in step S3, during the placement of the textile, the textile is laid on the detection table of the visual detection device to avoid the occurrence of wrinkles, and in step S8, when the simulation wearing is performed, different wearing simulations can be performed according to different body shapes to ensure that more data can be detected for comparison, in step S12, when the comparison of the comprehensive data is carried out, the data of the textile when the textile is not worn and the data of the textile when the textile is worn in a simulation mode are respectively and correspondingly compared.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (7)
1. A textile flaw detection method based on a machine vision template is characterized by comprising the following steps:
s1, detecting template data, preparing a visual detection device, placing the qualified textile without defects on a detection table of the visual detection device, and detecting each item of data of the qualified textile;
s2, inputting template data, obtaining various data of qualified textiles after the step S1 is completed, and inputting the data into an analysis comparison computer;
s3, placing the textile, and after the step S2 is finished, placing the textile needing visual detection on a detection table of a visual detection device to enable the textile to be consistent with the template in placement position and guarantee the textile to be consistent with the template in placement mode;
s4, measuring the length and width of the textile when the textile is not worn, after the step S3 is completed, measuring the length and width of the textile to be detected respectively by using a visual detection device, and feeding the measurement result back to the computer for storage;
s5, measuring the thickness of the textile when the textile is not worn, changing the orientation of a detection camera in a visual detection device after the step S4 is completed, measuring the thickness of the textile to be detected by using the visual detection device respectively, and feeding the measurement result back to a computer for storage;
s6, measuring the gaps of the textile threads when the textile threads are not worn, measuring the gaps of the textile threads in the textile to be detected by using a visual detection device after the step S5 is finished, and feeding back the measured data to a computer;
s7, comparing the data for the first time, and after the data of the textile is detected when the textile is not worn, transmitting the length and width data detected in the step S3, the thickness data detected in the step S4 and the textile line maintenance data detected in the step S5 to a comparison module of a computer, and comparing the data of the textile to be detected with the data of the qualified textile to obtain a comparison result;
s8, simulating the length and width measurement of the textile when the textile is worn, after the step S7 is completed, performing simulated wearing, placing the textile to be detected during the simulated wearing on a detection table of a visual detection device, measuring the length and width of the textile during the simulated wearing, and feeding the measurement result back to a computer;
s9, thickness measurement of the textile during wearing is simulated, when length and width detection of the textile during wearing is finished, the thickness measurement of the textile during wearing is carried out, and the measurement result is fed back to the computer;
s10, measuring the textile thread gap during the simulated wearing, after the step S9 is finished, measuring the textile thread gap of the textile during the simulated wearing by using a visual detection device, and feeding the measurement result back to the computer;
s11, comparing the data for the second time, namely comparing the data of the textile during the simulated wearing with the data of the qualified textile during the simulated wearing after the data of the textile during the simulated wearing are detected;
s12, comparing comprehensive data, namely after the step S11 is finished, putting the comparison result of the textile when the textile is not worn and the comparison result of the textile when the textile is simulated to be worn together for comparison;
and S13, outputting results, and outputting all comparison results after the step S12 is finished.
2. The method of claim 1, wherein in step S1, when detecting the template data, the method detects the data of the qualified textile when the textile is not worn and the data of the qualified textile when the textile is worn.
3. The method for detecting textile defects based on machine vision template as claimed in claim 2, wherein in step S1, the length, width, thickness and textile thread gap of the qualified textile are detected when the data of the qualified textile is detected.
4. The method of claim 1, wherein in step S1, the inspection table of the vision inspection apparatus is a rotary structure, and the textile is rotated during inspection.
5. The method for detecting textile defects based on machine vision template as claimed in claim 1, wherein in step S3, the textile is laid on the detection table of the vision detection device to avoid wrinkles when placing the textile.
6. The method of claim 1, wherein in step S8, when the wearing simulation is performed, different wearing simulations can be performed according to different shapes, so as to ensure that more data can be detected for comparison.
7. The method of claim 1, wherein in step S12, when comparing the integrated data, each item of data of the textile when the textile is not worn is compared with each item of data of the textile when the textile is simulated to be worn.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6369896B1 (en) * | 1997-11-03 | 2002-04-09 | Cognivision Research, S.L. | Method for visually inspecting textile garments, and a system for implementing said method |
| CN102967606A (en) * | 2012-11-02 | 2013-03-13 | 海宁市科威工业电子科技有限公司 | Textile machine fabric defect visual inspection system |
| CN109174694A (en) * | 2018-08-22 | 2019-01-11 | 杰克缝纫机股份有限公司 | Cut-parts Defect Detection system, method, electric terminal and storage medium |
| CN111177929A (en) * | 2019-12-31 | 2020-05-19 | 江西服装学院 | Textile fabric physical characteristic digital attribute simulation system and measuring method |
| CN111784691A (en) * | 2020-07-27 | 2020-10-16 | 泉州迈斯特新材料科技有限公司 | Textile flaw detection method |
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- 2021-12-29 CN CN202111618425.5A patent/CN114324354A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6369896B1 (en) * | 1997-11-03 | 2002-04-09 | Cognivision Research, S.L. | Method for visually inspecting textile garments, and a system for implementing said method |
| CN102967606A (en) * | 2012-11-02 | 2013-03-13 | 海宁市科威工业电子科技有限公司 | Textile machine fabric defect visual inspection system |
| CN109174694A (en) * | 2018-08-22 | 2019-01-11 | 杰克缝纫机股份有限公司 | Cut-parts Defect Detection system, method, electric terminal and storage medium |
| CN111177929A (en) * | 2019-12-31 | 2020-05-19 | 江西服装学院 | Textile fabric physical characteristic digital attribute simulation system and measuring method |
| CN111784691A (en) * | 2020-07-27 | 2020-10-16 | 泉州迈斯特新材料科技有限公司 | Textile flaw detection method |
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