CN109540898A - A kind of testing system for content of profiled fibre and method - Google Patents
A kind of testing system for content of profiled fibre and method Download PDFInfo
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- CN109540898A CN109540898A CN201910035306.3A CN201910035306A CN109540898A CN 109540898 A CN109540898 A CN 109540898A CN 201910035306 A CN201910035306 A CN 201910035306A CN 109540898 A CN109540898 A CN 109540898A
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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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N5/00—Analysing materials by weighing, e.g. weighing small particles separated from a gas or liquid
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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
- G01N2021/8444—Fibrous material
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
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Abstract
The present invention provides a kind of testing system for content of profiled fibre and methods, including control module, rejecting module, light source detection module and laying module；Light source detection module includes: transparent cotton flow channel, CCD and backlight；CCD and backlight is corresponding sets up separately in cotton flow channel two sides, backlight includes ultraviolet lamp tube and white fluorescent fluorescent tube；Module is rejected in the connection of cotton flow channel upper end, and rejecting module includes nozzle；Cotton flow channel lower end connects laying module, and laying module includes blower.A kind of testing system for content of profiled fibre of the present invention and method, it is proposed the testing system for content of profiled fibre based on image recognition technology, cooperate fuzzy clustering algorithm, the evaluation index of content of profiled fibre grade in perfect current standard, content rating evaluation method and model are proposed, new content of profiled fibre on-line detecting system and method are given.
Description
Technical field
The invention belongs to cotton foreign fiber detection fields, more particularly, to a kind of testing system for content of profiled fibre and side
Method.
Background technique
Under prior art conditions, there are following main problems for different fine content rating evaluation in production at present:
First is that being inspected by random samples at present using the method for picking by hand.The cost that practical investigation statistics manually rejects one gram of different fibre is several
It is equivalent to the value of one gram of platinum, and when inspection personnel's visual fatigue clearly, it may appear that recall rate is unstable, leads to foreign fiber
For content's index vulnerable to man's activity, testing result fluctuation is big, and cotton textile industry needs to realize different fine detection using automatic detection
The auto upgrading of equipment, the different fine content of scientific accurate detection.
Second is that referring to and being picked from sample at foreskin cotton content of profiled fibre specified in existing foreign fiber evaluation criterion
The weight of foreign fiber out and picked the ratio between example weight.Since content of profiled fibre influences cotton goods quality, cotton products
Fault is the larger impact factor of quality, and the factors such as size, type, area of foreign fiber are all in close relations with fault, so
Content of profiled fibre and its influence of cotton cannot be comprehensively and accurately evaluated using single weight indicator.
Summary of the invention
In view of this, the present invention is directed to propose a kind of testing system for content of profiled fibre and method, propose to know based on image
The testing system for content of profiled fibre of other technology cooperates fuzzy clustering algorithm, content of profiled fibre etc. in perfect current standard
The evaluation index of grade, proposes content rating evaluation method and model, gives new content of profiled fibre on-line detecting system
And method.
In order to achieve the above objectives, the technical scheme of the present invention is realized as follows:
A kind of testing system for content of profiled fibre, including control module, rejecting module, light source detection module and laying mould
Block；Light source detection module includes: transparent cotton flow channel, CCD and backlight；CCD and backlight it is corresponding set up separately it is logical in cotton flow
Road two sides, backlight include ultraviolet lamp tube and white fluorescent fluorescent tube；Module is rejected in the connection of cotton flow channel upper end, is rejected module and is included
Nozzle；Cotton flow channel lower end connects laying module, and laying module includes blower；CCD and nozzle are connect with control module respectively；
Blower sucks in raw cotton to cotton flow channel to be detected, the original to be detected in ultraviolet lamp tube and white fluorescent fluorescent tube irradiation cotton flow channel
Cotton, CCD is acquired the image containing foreign fiber in raw cotton to be detected, and is sent to control module；Control module control
Nozzle, which is opened, sprays foreign fiber contained in raw cotton to be detected.
A kind of content of profiled fibre detection method, uses above-mentioned testing system for content of profiled fibre:
Step 1: geometrical characteristic and analysis of physical and chemical property being carried out to foreign fiber, extract 10 parameters；
10 parameters include: diameter, length, area, weight, toughness, dyeability, hygroscopicity, acid resistance, alkali resistance and group
At ingredient；
Step 2: using Algorithm for Attribute Reduction, obtain reduction result to 10 parameters are extracted in step 1: including straight
Diameter, length, area, weight, toughness and dyeability；
The Algorithm for Attribute Reduction used includes: genetic algorithm and Johnson algorithm；Take the public of its calculated result
Part is used as reduction result；
Step 3: 6 reduction parameter index section random divisions obtained in step 2 are carried out initial using Maximum entropy method
Interval division adjusts boundary using multifactor optimum seeking method, obtains the contingency table of parameter value and different fine content rating, finally obtains
Different fine content's index system is established in the index section of four grades；
Step 4: being classified using fuzzy clustering algorithm to sample content of profiled fibre, while passing through Validity Function value
Demonstrate the reasonability of different fine content cluster result.
Further, in step 4:
S1: setting clustering parameter: the radius r in fielda、rb, parameter δ, cluster numbers c, Fuzzy Exponential m and minimal error ε, repeatedly
Generation number T, learning parameter α；
The density index of all different fine content sample points is calculated using the following formula of density index, density index is highest
One x pointed out as first cluster centrec1；
S2: further calculating the density index of remaining n-1 data point, finds out highest as second cluster centre
Point xc2, and so on, the c initial cluster center v being used as before choosing0；
S3: degree of membership u is calculated using degree of membership formula:
Cluster centre v is calculated using cluster centre formula:
Feature weight ω is calculated using weight equation:
S4: judge whether to meet termination condition: according to current u, v and ω, using the value of following formula calculating target function,
If the number of iterations is greater than T or adjacent, target function value absolute value of the difference is less than threshold epsilon twice, exports degree of membership u, cluster centre
V and feature weight ω；Otherwise, t=t+1 is enabled, S3 is gone to step and restarts to calculate；
Validity Index function f, is defined as follows:
WhereinReflect total variance in class,Reflect class
Interior total variance；Comprising improved division factor, reflect whether division result is clearly demarcated, value is smaller, then draws
Divide clearly more demarcated；
S5: according to output degree of membership u, cluster centre v and the feature weight ω exported in step S4；Utilize following formula meters
Calculate Validity Index functional value fc, and compare its value size, judge validity；
Compared with the existing technology, a kind of testing system for content of profiled fibre of the present invention and method, have the advantage that
A kind of testing system for content of profiled fibre of the present invention and method, extract different fibre by testing system for content of profiled fibre
Morphological feature, and being identified by image processing algorithm, in conjunction with the different fine weight of ejection, using data processing algorithm to obtaining
The weight indicator in data and target obtained carries out fuzzy classification comparison operation, finally obtains different fine content rating evaluation.It is based on
The content of profiled fibre multi-parameter detection of fuzzy clustering and grade evaluation method, improve content of profiled fibre grade in current standard
Evaluation index, propose content rating evaluation method and model, give new content of profiled fibre online test method, have
Effect improves the detection speed of different fine content and the accuracy of grade evaluation.
Detailed description of the invention
The attached drawing for constituting a part of the invention is used to provide further understanding of the present invention, schematic reality of the invention
It applies example and its explanation is used to explain the present invention, do not constitute improper limitations of the present invention.
In the accompanying drawings:
Fig. 1 is a kind of testing system for content of profiled fibre schematic diagram of the embodiment of the present invention；
Fig. 2 is a kind of content of profiled fibre detection method schematic diagram of the embodiment of the present invention.
Specific embodiment
It should be noted that in the absence of conflict, the feature in embodiment and embodiment in the present invention can phase
Mutually combination.
In the description of the present invention, it is to be understood that, term " center ", " longitudinal direction ", " transverse direction ", "upper", "lower",
The orientation or positional relationship of the instructions such as "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outside" is
It is based on the orientation or positional relationship shown in the drawings, is merely for convenience of description of the present invention and simplification of the description, rather than instruction or dark
Show that signified device or element must have a particular orientation, be constructed and operated in a specific orientation, therefore should not be understood as pair
Limitation of the invention.In addition, term " first ", " second " etc. are used for description purposes only, it is not understood to indicate or imply phase
To importance or implicitly indicate the quantity of indicated technical characteristic.The feature for defining " first ", " second " etc. as a result, can
To explicitly or implicitly include one or more of the features.In the description of the present invention, unless otherwise indicated, " multiple "
It is meant that two or more.
In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, term " installation ", " phase
Even ", " connection " shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or be integrally connected；It can
To be mechanical connection, it is also possible to be electrically connected；It can be directly connected, can also can be indirectly connected through an intermediary
Connection inside two elements.For the ordinary skill in the art, above-mentioned term can be understood by concrete condition
Concrete meaning in the present invention.
The present invention will be described in detail below with reference to the accompanying drawings and embodiments.
As shown in Figure 1, a kind of testing system for content of profiled fibre, including control module, rejecting module, light source detection module
And laying module；Light source detection module includes: transparent cotton flow channel, CCD and backlight；CCD and backlight is corresponding sets up separately
In cotton flow channel two sides, backlight includes ultraviolet lamp tube and white fluorescent fluorescent tube；Module is rejected in the connection of cotton flow channel upper end, is rejected
Module includes nozzle；Cotton flow channel lower end connects laying module, and laying module includes blower；CCD and nozzle respectively with control
Module connection；Blower sucks in raw cotton to cotton flow channel to be detected, in ultraviolet lamp tube and white fluorescent fluorescent tube irradiation cotton flow channel
Raw cotton to be detected, CCD is acquired the image containing foreign fiber in raw cotton to be detected, and is sent to control module；Control
Molding block, which controls nozzle and opens, sprays foreign fiber contained in raw cotton to be detected.
As shown in Fig. 2, a kind of content of profiled fibre detection method, uses above-mentioned testing system for content of profiled fibre:
Step 1: geometrical characteristic and analysis of physical and chemical property being carried out to foreign fiber, extract 10 parameters；
10 parameters include: diameter, length, area, weight, toughness, dyeability, hygroscopicity, acid resistance, alkali resistance and group
At ingredient；
Step 2: using Algorithm for Attribute Reduction, obtain reduction result to 10 parameters are extracted in step 1: including straight
Diameter, length, area, weight, toughness and dyeability；
The Algorithm for Attribute Reduction used includes: genetic algorithm and Johnson algorithm；Take the public of its calculated result
Part is used as reduction result；
Step 3: 6 reduction parameter index section random divisions obtained in step 2 are carried out initial using Maximum entropy method
Interval division adjusts boundary using multifactor optimum seeking method, obtains the contingency table of parameter value and different fine content rating, finally obtains
Different fine content's index system is established in the index section of four grades；
Step 4: being classified using fuzzy clustering algorithm to sample content of profiled fibre, while passing through Validity Function value
Demonstrate the reasonability of different fine content cluster result.
Further, in step 4:
S1: setting clustering parameter: the radius r in fielda、rb, parameter δ, cluster numbers c, Fuzzy Exponential m and minimal error ε, repeatedly
Generation number T, learning parameter α；
The density index that all different fine content sample points are calculated using following formula, by the highest conduct of density index
The x that first cluster centre is pointed outc1；
S2: further calculating the density index of remaining n-1 data point, finds out highest as second cluster centre
Point xc2, and so on, the c initial cluster center v being used as before choosing0；
S3: degree of membership u is calculated using degree of membership formula:
Cluster centre v is calculated using cluster centre formula:
Feature weight ω is calculated using weight equation:
S4: judge whether to meet termination condition: according to current u, v and ω, using the value of following formula calculating target function,
If the number of iterations is greater than T or adjacent, target function value absolute value of the difference is less than threshold epsilon twice, exports degree of membership u, cluster centre
V and feature weight ω；Otherwise, t=t+1 is enabled, S3 is gone to step and restarts to calculate；
Validity Index function f, is defined as follows:
WhereinReflect total variance in class,Reflect class
Interior total variance；Comprising improved division factor, reflect whether division result is clearly demarcated, value is smaller, then
It divides clearly more demarcated；
S5: according to output degree of membership u, cluster centre v and the feature weight ω exported in step S4；Utilize following formula meters
Calculate Validity Index functional value fc, and compare its value size, judge validity；
Content of profiled fibre detection method of the present invention is verified:
Since content of profiled fibre is indicated with weight ratio in national standard, although weight ratio indicates more intuitive,
Be examine cotton products quality be using fault quantity and size as standard, so it cannot comprehensively, accurately reflect it is different in cotton
The number of property fiber content.The features such as foreign fiber length, diameter, area, weight, toughness, dyeability are extracted, analyze 6 kinds
The relationship of feature and fault.The length of foreign fiber, diameter, area, weight, toughness, dyeability parameter is anisotropic as measuring
The characteristic index of fiber content.Typical foreign fiber: hair is had chosen, finishing part data are as follows:
Table 1-1 hair characteristic index parameter
Because being to same different fine content classification, its physicochemical property is roughly the same, and individual difference can be ignored, so
Toughness and dyeability, in same different fine content classification, the influence to classification results can not have to consider, only consider its geometry
Property.Algorithm is used to sample data collected, according to the minimum optimal classification of Validity Function as a result, the hair opposite sex can be obtained
Fiber content is divided into four classes.
Table 1-2 hair cluster centre
The corresponding Validity Function of table 1-3 classification number
It can be seen that the Validity Function value corresponding when number of classifying is 4 is minimum, data sample rationally divide
Class simultaneously demonstrates validity.
The classification of table 1-4 hair content of profiled fibre
The above is merely preferred embodiments of the present invention, be not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (3)
1. a kind of testing system for content of profiled fibre, it is characterised in that: including control module, reject module, light source detection module
And laying module；The light source detection module includes: transparent cotton flow channel, CCD and backlight；The CCD and the backlight
Plate is corresponding to be set up separately in cotton flow channel two sides, and the backlight includes ultraviolet lamp tube and white fluorescent fluorescent tube；The cotton flow
Channel upper end connects the rejecting module, and the rejecting module includes nozzle；Cotton flow channel lower end connects the laying mould
Block, the laying module includes blower；The CCD and the nozzle are connect with the control module respectively；The blower is inhaled
Enter in raw cotton to be detected to the cotton flow channel, the ultraviolet lamp tube and the white fluorescent fluorescent tube irradiate in the cotton flow channel
Raw cotton to be detected, the CCD is acquired the image containing foreign fiber in raw cotton to be detected, and is sent to the control
Module；The control module, which controls the nozzle and opens, sprays foreign fiber contained in raw cotton to be detected.
2. a kind of content of profiled fibre detection method, it is characterised in that: contained using a kind of foreign fiber as described in claim 1
Amount detection systems:
Step 1: geometrical characteristic and analysis of physical and chemical property being carried out to foreign fiber, extract 10 parameters；
10 parameters include: diameter, length, area, weight, toughness, dyeability, hygroscopicity, acid resistance, alkali resistance and composition at
Point；
Step 2: use Algorithm for Attribute Reduction, in step 1 extract 10 parameters obtain reduction result: including diameter,
Length, area, weight, toughness and dyeability；
The Algorithm for Attribute Reduction used includes: genetic algorithm and Johnson algorithm；Take the common portion of its calculated result
As reduction result；
Step 3: by 6 reduction parameter index section random divisions obtained in step 2, carrying out initial section using Maximum entropy method
It divides, adjusts boundary using multifactor optimum seeking method, obtain the contingency table of parameter value and different fine content rating, finally obtained four
Different fine content's index system is established in the index section of grade；
Step 4: being classified using fuzzy clustering algorithm to sample content of profiled fibre, while being verified by Validity Function value
The reasonability of different fine content cluster result.
3. a kind of content of profiled fibre detection method according to claim 2, it is characterised in that: in step 4:
S1: setting clustering parameter: the radius r in fielda、rb, parameter δ, cluster numbers c, Fuzzy Exponential m and minimal error ε, iteration are secondary
Number T, learning parameter α；
The density index that all different fine content sample points are calculated using density index formula, by the highest conduct of density index
The x that first cluster centre is pointed outc1；
S2: further calculating the density index of remaining n-1 data point, finds out highest as second cluster centre point
xc2, and so on, the c initial cluster center v being used as before choosing0；
S3: degree of membership u is calculated using degree of membership formula:
Cluster centre v is calculated using cluster centre formula:
Feature weight ω is calculated using weight equation:
S4: judge whether to meet termination condition: according to current u, v and ω, using the value of following formula calculating target function, if repeatedly
Generation number be greater than T or adjacent twice target function value absolute value of the difference be less than threshold epsilon, then export degree of membership u, cluster centre v and
Feature weight ω；Otherwise, t=t+1 is enabled, S3 is gone to step and restarts to calculate；
Validity Index function f, is defined as follows:
Wherein Reflect total variance in class,Always become in reflection class
Difference；Comprising improved division factor, reflect whether division result is clearly demarcated, value is smaller, then divides and get over
Clearly；
S5: according to output degree of membership u, cluster centre v and the feature weight ω exported in step S4；Have using the calculating of following formula
Effect property target function value fc, and compare its value size, judge validity；
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112184615A (en) * | 2020-07-04 | 2021-01-05 | 浙江省常山纺织有限责任公司 | Fabric colored fiber detection system based on image processing |
| CN113063928A (en) * | 2021-03-24 | 2021-07-02 | 江阴市纤维检验所 | Quantitative test method for foreign fiber of raw cotton |
| CN114693680A (en) * | 2022-05-31 | 2022-07-01 | 季华实验室 | Method for detecting textile fibers, electronic device and computer-readable storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050033139A1 (en) * | 2002-07-09 | 2005-02-10 | Deus Technologies, Llc | Adaptive segmentation of anatomic regions in medical images with fuzzy clustering |
| CN1963473A (en) * | 2006-12-06 | 2007-05-16 | 北京中棉机械成套设备有限公司 | Testing system for content of profiled fibre of cotton |
| CN101393139A (en) * | 2008-10-22 | 2009-03-25 | 北京中棉机械成套设备有限公司 | Isomerism fibre detection and measurement method and device in lint |
| CN103234975A (en) * | 2013-03-29 | 2013-08-07 | 西安理工大学 | Detecting and positioning method of cotton foreign fibers |
| US20170161606A1 (en) * | 2015-12-06 | 2017-06-08 | Beijing University Of Technology | Clustering method based on iterations of neural networks |
-
2019
- 2019-01-15 CN CN201910035306.3A patent/CN109540898B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050033139A1 (en) * | 2002-07-09 | 2005-02-10 | Deus Technologies, Llc | Adaptive segmentation of anatomic regions in medical images with fuzzy clustering |
| CN1963473A (en) * | 2006-12-06 | 2007-05-16 | 北京中棉机械成套设备有限公司 | Testing system for content of profiled fibre of cotton |
| CN101393139A (en) * | 2008-10-22 | 2009-03-25 | 北京中棉机械成套设备有限公司 | Isomerism fibre detection and measurement method and device in lint |
| CN103234975A (en) * | 2013-03-29 | 2013-08-07 | 西安理工大学 | Detecting and positioning method of cotton foreign fibers |
| US20170161606A1 (en) * | 2015-12-06 | 2017-06-08 | Beijing University Of Technology | Clustering method based on iterations of neural networks |
Non-Patent Citations (2)
| Title |
|---|
| ZHOU ZHICHAO ET AL.: "A Simulated Annealing White Balance Algorithm for Foreign Fiber Detection", 《ICBEB》 * |
| 周志超: "异性纤维含量等级评价模型的构建", 《中国优秀硕士学位论文全文数据库工程科技Ⅰ辑》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112184615A (en) * | 2020-07-04 | 2021-01-05 | 浙江省常山纺织有限责任公司 | Fabric colored fiber detection system based on image processing |
| CN113063928A (en) * | 2021-03-24 | 2021-07-02 | 江阴市纤维检验所 | Quantitative test method for foreign fiber of raw cotton |
| CN114693680A (en) * | 2022-05-31 | 2022-07-01 | 季华实验室 | Method for detecting textile fibers, electronic device and computer-readable storage medium |
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