CN108225402A - A kind of injecting products intelligence secondary detection method - Google Patents
A kind of injecting products intelligence secondary detection method Download PDFInfo
- Publication number
- CN108225402A CN108225402A CN201711327370.6A CN201711327370A CN108225402A CN 108225402 A CN108225402 A CN 108225402A CN 201711327370 A CN201711327370 A CN 201711327370A CN 108225402 A CN108225402 A CN 108225402A
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- detection
- injecting products
- injection molding
- molding machine
- machine module
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- 238000001514 detection method Methods 0.000 title claims abstract description 124
- 238000001746 injection moulding Methods 0.000 claims abstract description 71
- 238000012797 qualification Methods 0.000 claims abstract description 20
- 238000004458 analytical method Methods 0.000 claims abstract description 7
- 241001124569 Lycaenidae Species 0.000 claims description 30
- 108010001267 Protein Subunits Proteins 0.000 claims description 10
- 238000009434 installation Methods 0.000 claims description 9
- 230000007547 defect Effects 0.000 claims description 3
- 238000002347 injection Methods 0.000 claims description 3
- 239000007924 injection Substances 0.000 claims description 3
- 238000000465 moulding Methods 0.000 claims description 2
- 238000000034 method Methods 0.000 abstract description 9
- 238000012372 quality testing Methods 0.000 description 5
- 238000007689 inspection Methods 0.000 description 3
- 230000002950 deficient Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000007423 decrease Effects 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000004806 packaging method and process Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
-
- 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
- G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/46—Measurement of colour; Colour measuring devices, e.g. colorimeters
Abstract
The invention discloses a kind of injecting products intelligence secondary detection methods, include the following steps：S1, the n platforms injecting mechanism that is linked in sequence are into n injection molding machine module；S2, acquire j-th of injection molding machine module injecting products image information and be compared with pre-set image information and show whether injecting products qualified ,+1 injection molding machine module of jth is transported to when the injecting products are unqualified and records unqualified reason；S3, the unqualified reason of statistics are simultaneously analyzed, and formulate examination criteria based on analysis result；+ 1 S4, jth injection molding machine module carry out second of qualification detection based on above-mentioned examination criteria to the injecting products that j-th of injection molding machine module conveys.One aspect of the present invention carries out it first time qualification detection according to the image information of itself product, on the other hand second of qualification detection is carried out to the substandard product of a upper injection molding machine module according to the examination criteria that this method is formulated, improves the accuracy of detection to each injecting products comprehensively.
Description
Technical field
The present invention relates to product quality detection technique field more particularly to a kind of injecting products intelligence secondary detection methods.
Background technology
Traditional injecting products quality inspection is to use manually to check repeatedly, will wherein have the defects of lacking material, overlap, stain
Defective products is selected, and to ensure the quality of final injecting products finished product qualification, manually splitting is carried out to certified products again after quality inspection
Packaging.Artificial detection is susceptible to the situation of leakage choosing and wrong choosing, some defective products can come into the market because of leakage choosing, can make product in this way
Qualification rate decline, cannot thoroughly improve again, and artificial detection can generate a large amount of human cost from other links.The present invention
The detection method of proposition not only carries out each injecting products secondary detection to ensure its quality of production, but also realizes note
The automatic detection process of molding product, on the one hand improves accuracy of detection, on the other hand improves detection efficiency.
Invention content
Technical problems based on background technology, the present invention propose a kind of injecting products intelligence secondary detection method.
Injecting products intelligence secondary detection method proposed by the present invention, includes the following steps：
S1, the n platforms injecting mechanism that is linked in sequence are into n injection molding machine module；
S2, acquire j-th of injection molding machine module injecting products image information and be compared with pre-set image information
Whether qualified go out injecting products ,+1 injection molding machine module of jth is transported to when the injecting products are unqualified and record does not conform to
Lattice reason；
S3, the unqualified reason of statistics are simultaneously analyzed, and formulate examination criteria based on analysis result；
S4 ,+1 injection molding machine module of jth based on above-mentioned examination criteria to the injecting products that j-th of injection molding machine module conveys into
Second of qualification detection of row；
Wherein, 1≤j≤n-1.
Preferably, step S3 is specifically included：
It counts the unqualified reason of each injection molding machine module record and analyzes, by above-mentioned multiple unqualified reasons according to knot
Structure flaw, color flaw, flatness flaw are classified and count number, are denoted as A, B, C, are worked as A>During N, structure detection is formulated
For examination criteria, work as B>During N, structure detection is established as examination criteria, works as C>During N, structure detection is established as examination criteria；
Wherein, N is preset value.
Preferably, step S2 is specifically included：
Using detection unit acquire j-th of injection molding machine module injecting products image information and with pre-set image information into
Row relatively show whether injecting products are qualified；
Preferably, the detection unit includes the first detection sub-unit, the second detection sub-unit, third detection sub-unit；
First detection sub-unit is used to acquire the structural images information of the injecting products of j-th of injection molding machine module and with presetting
Image information, which is compared, show whether injection molding product structure is qualified；
Second detection sub-unit is used to acquire the color image information of the injecting products of j-th of injection molding machine module and with presetting
Image information, which is compared, show whether injecting products color is qualified；
Third detection sub-unit for acquire j-th of injection molding machine module injecting products flatness image information and with it is pre-
If image information, which is compared, show whether injecting products flatness is qualified.
Preferably, step S4 is specifically included：
When structure detection is established as examination criteria by step S3 ,+1 injection molding machine mould first detection unit in the block of jth
Start work and second of qualification detection is carried out to the structure of injecting products that j-th of injection molding machine module conveys；
When color detection is established as examination criteria by step S3 ,+1 injection molding machine mould second detection unit in the block of jth
Start work and second of qualification detection is carried out to the color of injecting products that j-th of injection molding machine module conveys；
When flatness detection is established as examination criteria by step S3, the third detection in the block of+1 injection molding machine mould of jth is single
Member starts work and carries out second of qualification detection to the flatness of injecting products that j-th of injection molding machine module conveys.
Preferably, first detection sub-unit includes multiple harvesters, and the installation site of multiple harvesters is not
Identical, multiple harvesters are used to the structural images information of acquisition injecting products；Preferably, multiple harvesters use high definition
Video camera；
Second detection sub-unit includes multiple harvesters, and the installation site of multiple harvesters differs, more
A harvester is used to the color image information of acquisition injecting products；Preferably, multiple harvesters use high-definition camera instrument；
The third detection sub-unit includes multiple harvesters, and the installation site of multiple harvesters differs, more
A harvester is used to the flatness image information of acquisition injecting products；Preferably, multiple harvesters use high-definition camera
Instrument.
Injecting products intelligence secondary detection method proposed by the present invention, the n platforms injecting mechanism that is linked in sequence is into n injection molding machine mould
Block, and establish the information flow channel for having adjacent injection molding machine intermodule so that n platforms injection molding machine can be according to mutual product quality
Quality testing is carried out to the product of itself and other injection molding machine modules, improve to the specific aim of injecting products quality testing and
Validity.On the one hand each injection molding machine module carries out it first time qualification detection according to the image information of itself product,
On the other hand second of qualification is carried out to the substandard product of a upper injection molding machine module according to the examination criteria that this method is formulated
Property detection, the accuracy of detection to each injecting products is improved comprehensively, so as to improve intelligence of this method to injecting products
Detection result realizes the detection of automation comprehensive, accurate to injecting products.
Description of the drawings
Fig. 1 is a kind of step schematic diagram of injecting products intelligence secondary detection method.
Specific embodiment
As shown in FIG. 1, FIG. 1 is a kind of injecting products intelligence secondary detection methods proposed by the present invention.
With reference to Fig. 1, injecting products intelligence secondary detection method proposed by the present invention includes the following steps：
S1, the n platforms injecting mechanism that is linked in sequence are into n injection molding machine module；
S2, acquire j-th of injection molding machine module injecting products image information and be compared with pre-set image information
Whether qualified go out injecting products ,+1 injection molding machine module of jth is transported to when the injecting products are unqualified and record does not conform to
Lattice reason；
S3, the unqualified reason of statistics are simultaneously analyzed, and formulate examination criteria based on analysis result；
S4 ,+1 injection molding machine module of jth based on above-mentioned examination criteria to the injecting products that j-th of injection molding machine module conveys into
Second of qualification detection of row；
Wherein, 1≤j≤n-1.
Each injection molding machine module not only carries out quality testing to the injecting products of this injection molding machine, but also based on formulation
The quality of the injecting products that examination criteria generates adjacent injection molding machine module carries out targetedly secondary detection, improves comprehensively pair
The detection result of each injecting products.Also, when injecting products have shown flaw in first time testing result, second
Secondary detection process further targetedly detects it, is on the one hand conducive to improve the validity of detection, avoids for the first time
There is the situation of flase drop in detection process, is on the one hand conducive to further determine that the flaw type of injecting products, realizes to injection
Comprehensive supervision of product quality.
In present embodiment, step S3 is specifically included：
It counts the unqualified reason of each injection molding machine module record and analyzes, by above-mentioned multiple unqualified reasons according to knot
Structure flaw, color flaw, flatness flaw are classified and count number, are denoted as A, B, C, are worked as A>During N, show with the structure flaw
The quantity of the injecting products of defect is more than preset value, and structure detection is established as examination criteria at this time, works as B>During N, show with face
The quantity of the injecting products of color flaw is more than preset value, and structure detection is established as examination criteria at this time, works as C>During N, show have
The quantity for having the injecting products of flatness flaw is more than preset value, and structure detection is established as examination criteria at this time；
Wherein, N is preset value.
In example is further carried out, step S2 is specifically included：
Using detection unit acquire j-th of injection molding machine module injecting products image information and with pre-set image information into
Row relatively show whether injecting products are qualified；
Preferably, the detection unit includes the first detection sub-unit, the second detection sub-unit, third detection sub-unit；
First detection sub-unit is used to acquire the structural images information of the injecting products of j-th of injection molding machine module and with presetting
Image information, which is compared, show whether injection molding product structure is qualified；
Second detection sub-unit is used to acquire the color image information of the injecting products of j-th of injection molding machine module and with presetting
Image information, which is compared, show whether injecting products color is qualified；
Third detection sub-unit for acquire j-th of injection molding machine module injecting products flatness image information and with it is pre-
If image information, which is compared, show whether injecting products flatness is qualified；
By setting the first detection sub-unit, the second detection sub-unit, third detection sub-unit respectively to injecting products
Structure, color, flatness targetedly acquire and analyze, be conducive to improve to the validity of injecting products quality analysis and
Correctness.
Step S4 is specifically included：
When structure detection is established as examination criteria by step S3 ,+1 injection molding machine mould first detection unit in the block of jth
Start work and second of qualification detection is carried out to the structure of injecting products that j-th of injection molding machine module conveys；
When color detection is established as examination criteria by step S3 ,+1 injection molding machine mould second detection unit in the block of jth
Start work and second of qualification detection is carried out to the color of injecting products that j-th of injection molding machine module conveys；
When flatness detection is established as examination criteria by step S3, the third detection in the block of+1 injection molding machine mould of jth is single
Member starts work and carries out second of qualification detection to the flatness of injecting products that j-th of injection molding machine module conveys；
By the way that the first detection sub-unit, the second detection sub-unit, third detection sub-unit is respectively started further to injection
Structure, color, the flatness of product carry out targetedly secondary detection, are conducive to further improve to injecting products quality analysis
Validity and correctness.
In example is further carried out, first detection sub-unit includes multiple harvesters, multiple harvesters
Installation site differs, and multiple harvesters are used to the structural images information of acquisition injecting products；Preferably, multiple acquisitions
Device uses high-definition camera instrument；
Second detection sub-unit includes multiple harvesters, and the installation site of multiple harvesters differs, more
A harvester is used to the color image information of acquisition injecting products；Preferably, multiple harvesters use high-definition camera instrument；
The third detection sub-unit includes multiple harvesters, and the installation site of multiple harvesters differs, more
A harvester is used to the flatness image information of acquisition injecting products；Preferably, multiple harvesters use high-definition camera
Instrument；
It, can be from different location different angle to structural images information, the color diagram of injecting products using multiple harvesters
Picture information, flatness image information comprehensively and accurately acquire, and are conducive to the first detection sub-unit of raising, the second detection
Unit, third detection sub-unit Image Acquisition validity, so as to improve detection supply unit precision of analysis.
The injecting products intelligence secondary detection method that present embodiment proposes, the n platforms injecting mechanism that is linked in sequence are molded into n
Machine module, and establish the information flow channel for having adjacent injection molding machine intermodule so that n platforms injection molding machine can be according to mutual product
Quality carries out quality testing to the product of itself and other injection molding machine modules, improves and injecting products quality testing is directed to
Property and validity.On the one hand each injection molding machine module carries out it first time qualification inspection according to the image information of itself product
It surveys, on the other hand carrying out second to the substandard product of a upper injection molding machine module according to the examination criteria that this method is formulated closes
Lattice detect, and the accuracy of detection to each injecting products are improved comprehensively, so as to improve intelligence of this method to injecting products
Change detection result, realize the detection of automation comprehensive, accurate to injecting products.
The foregoing is only a preferred embodiment of the present invention, but protection scope of the present invention be not limited thereto,
Any one skilled in the art in the technical scope disclosed by the present invention, according to the technique and scheme of the present invention and its
Inventive concept is subject to equivalent substitution or change, should be covered by the protection scope of the present invention.
Claims (5)
- A kind of 1. injecting products intelligence secondary detection method, which is characterized in that include the following steps：S1, the n platforms injecting mechanism that is linked in sequence are into n injection molding machine module；S2, acquire j-th of injection molding machine module injecting products image information and be compared with pre-set image information and obtain note Whether molding product is qualified, and+1 injection molding machine module of jth is transported to when the injecting products are unqualified and records unqualified original Cause；S3, the unqualified reason of statistics are simultaneously analyzed, and formulate examination criteria based on analysis result；The injecting products that+1 S4, jth injection molding machine module convey j-th of injection molding machine module based on above-mentioned examination criteria carry out the Secondary qualification detection；Wherein, 1≤j≤n-1.
- 2. injecting products intelligence secondary detection method according to claim 1, which is characterized in that step S3 is specifically included：It counts the unqualified reason of each injection molding machine module record and analyzes, by above-mentioned multiple unqualified reasons according to the structure flaw Defect, color flaw, flatness flaw are classified and count number, are denoted as A, B, C, are worked as A>During N, structure detection is established as examining Mark is accurate, works as B>During N, structure detection is established as examination criteria, works as C>During N, structure detection is established as examination criteria；Wherein, N is preset value.
- 3. injecting products intelligence secondary detection method according to claim 2, which is characterized in that step S2 is specifically included：The image information of the injecting products of j-th of injection molding machine module is acquired using detection unit and is compared with pre-set image information Relatively show whether injecting products are qualified；Preferably, the detection unit includes the first detection sub-unit, the second detection sub-unit, third detection sub-unit；First detection sub-unit is used to acquire the structural images information and and pre-set image of the injecting products of j-th of injection molding machine module Information, which is compared, show whether injection molding product structure is qualified；Second detection sub-unit is used to acquire the color image information and and pre-set image of the injecting products of j-th of injection molding machine module Information, which is compared, show whether injecting products color is qualified；Third detection sub-unit for acquire j-th of injection molding machine module injecting products flatness image information and with default figure Show whether injecting products flatness is qualified as information is compared.
- 4. injecting products intelligence secondary detection method according to claim 3, which is characterized in that step S4 is specifically included：When structure detection is established as examination criteria by step S3 ,+1 injection molding machine mould of jth first detection unit in the block starts It works and second of qualification detection is carried out to the structure of the injecting products of j-th of injection molding machine module conveying；When color detection is established as examination criteria by step S3 ,+1 injection molding machine mould of jth second detection unit in the block starts It works and second of qualification detection is carried out to the color of the injecting products of j-th of injection molding machine module conveying；When flatness detection is established as examination criteria by step S3 ,+1 injection molding machine mould of jth third detection unit in the block opens The flatness of injecting products of j-th of injection molding machine module conveying of starting building to oppose carries out second of qualification detection.
- 5. injecting products intelligence secondary detection method according to claim 3, which is characterized in that the first detection is single Member includes multiple harvesters, and the installation site of multiple harvesters differs, and multiple harvesters are used to acquisition injection The structural images information of product；Preferably, multiple harvesters use high-definition camera instrument；Second detection sub-unit includes multiple harvesters, and the installation site of multiple harvesters differs, multiple to adopt Acquisition means are used to the color image information of acquisition injecting products；Preferably, multiple harvesters use high-definition camera instrument；The third detection sub-unit includes multiple harvesters, and the installation site of multiple harvesters differs, multiple to adopt Acquisition means are used to the flatness image information of acquisition injecting products；Preferably, multiple harvesters use high-definition camera instrument.
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| CN201711327370.6A CN108225402A (en) | 2017-12-13 | 2017-12-13 | A kind of injecting products intelligence secondary detection method |
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| CN201711327370.6A CN108225402A (en) | 2017-12-13 | 2017-12-13 | A kind of injecting products intelligence secondary detection method |
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|---|---|---|---|---|
| EP1275772A2 (en) * | 2001-07-13 | 2003-01-15 | Voith Paper Patent GmbH | Process and apparatus for monitoring the condition of felts or screens |
| CN103196917A (en) * | 2013-03-13 | 2013-07-10 | 同济大学 | CCD linear array camera-based online rolled sheet material surface flaw detection system and detection method thereof |
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Application publication date: 20180629 |