CN110412037A - A kind of fabric defects information processing method and device - Google Patents
A kind of fabric defects information processing method and device Download PDFInfo
- Publication number
- CN110412037A CN110412037A CN201910600560.3A CN201910600560A CN110412037A CN 110412037 A CN110412037 A CN 110412037A CN 201910600560 A CN201910600560 A CN 201910600560A CN 110412037 A CN110412037 A CN 110412037A
- Authority
- CN
- China
- Prior art keywords
- information
- detected material
- fault
- processing method
- fabric
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Pathology (AREA)
- Immunology (AREA)
- Biochemistry (AREA)
- Analytical Chemistry (AREA)
- Chemical & Material Sciences (AREA)
- Theoretical Computer Science (AREA)
- Biophysics (AREA)
- General Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Molecular Biology (AREA)
- Evolutionary Computation (AREA)
- Data Mining & Analysis (AREA)
- Computational Linguistics (AREA)
- Biomedical Technology (AREA)
- Artificial Intelligence (AREA)
- General Factory Administration (AREA)
Abstract
A kind of fabric defects information processing method and device.This application discloses a kind of detected material fault information processing method and devices.The detected material fault information processing method includes: from different information source (such as detection systems, production equipment, information management system etc.), by different data transfer modes, (such as INTRANET Intranet is transmitted, INTERNET the Internet transmission, equipment is stored to import, manual entry etc.) obtain detected material status information (such as fault information), the information of detected material manufacturing and processing equipment operating status, personal information etc., to acquired detected material status information (such as fault information), the information of detected material manufacturing and processing equipment operating status, personal information etc. is for statistical analysis, the information provided for the information is fed back.The detected material fault information processing method and device that the embodiment of the present invention proposes, it is for statistical analysis by the information shown to different testing sample, implicit information is therefrom excavated, and then reversely instruct the production link of early period.In an alternative embodiment other than Instructing manufacture link, further follow-up link can also be instructed.
Description
Technical field
This application involves textile technology fields, more particularly to a kind of fabric defects information processing method and device.
Background technique
Fault is to be prevalent in the surface of detected material.By taking detected material is textile material as an example,
Textile material refers to fiber and fibre, is embodied in fiber, yarn, fabric and its compound.According to spinning
The definition of material is knitted, the content of textile material includes fiber and fiber assembly.Textile presses the difference of production method, can broad sense
Ground is divided into the classes such as yarn class, band class, rope class, woven fabric, knitted fabric, braided fabric and non-woven cloth.Not according to fabric texture
It is same to be divided into chemical & blended fabric, cotton spinning fabric, wool spinning fabric, glass fabric etc..
Wherein, chemical & blended fabric refers to the pure spinning being processed by chemical fibre, blended or intertexture, that is to say, that by pure chemical fiber
The fabric being made into, does not include blended, intertexture between natural fiber, and the characteristic of chemical & blended fabric is by being made into its chemical fibre sheet
The characteristic of body determines.Advantage is that bright in luster, soft, pendency is well-pressed, smooth comfortable.They the shortcomings that be then wearability,
Heat resistance, hygroscopicity, gas permeability are poor, and heat is easily deformed, and are easy to produce electrostatic.
Cotton spinning fabric: cotton spinning is all named in all pure cotton weavings.There are knitting, tatting (comprising air-flow etc. without shuttle) two major classes.It
It is mostly used for fashionable dress, easy dress, underwear and shirt.Its advantages are that easily warming, soft fit, hygroscopic, gas permeability be very
It is good.Its advantage is that easily contracting, easily wrinkle, in appearance less well-pressed beauty, must ironing often when wearing.
Wool spinning: being made into using various animal wools, and pure wool shade fabric is naturally soft, good warmth retention effect, is the high-grade west of production
The preferred fabric of clothes and overcoat.
Glass fabric: being made using glass fiber yarn or precursor, there is fiberglass gridding cloth, glass fibre grid
Cloth, glass fiber plain cloth, glass fibre axial direction cloth, glass fibre wallhanging, glass fibre electronics cloth etc., are that one kind is had excellent performance
Inorganic non-metallic material, many kinds of, advantage is good insulating, heat resistance is strong, corrosion resistance is good, high mechanical strength, but lack
Point is that property is crisp, wearability is poor.Glass fibre is typically used as reinforcing material, electrically insulating material and adiabatic heat-insulation in composite material
Material, the national economy every field such as circuit substrate.
Automatic Detection of Fabric Defects is to be controlled fabric quality, realize weaving and perching process automation, is unmanned
Key link.The prior art proposes a variety of for fabric defect detection method and system.But it is examined for fabric
After survey, further processing and excavation step are had no for the result of detection, fails to reversely instruct the fabric of early period to produce
Link.
It is worth noting that correlative technology field, not only there are the above problems for fabric, and there is also above-mentioned for a large amount of non-woven
Problem.
Summary of the invention
In view of the above problems, one embodiment of the invention proposes a kind of fabric defects information processing method and device, to solve
Problem of the existing technology.
To solve the above-mentioned problems, one embodiment of the application discloses a kind of fabric defects information processing method, comprising:
The related information of detected material is obtained, it is described to close the life that information includes the status information of detected material, detected material
Produce the running state information of process equipment, operator's information of the manufacturing and processing equipment of detected material at least one；
It is for statistical analysis to acquired related information, the information feedback for the related information is provided；
Wherein the detected material status information includes fault information.
A kind of terminal device is also disclosed in one embodiment of the application, comprising:
One or more processors；With the one or more machine readable medias for being stored thereon with instruction, when by described one
When a or multiple processors execute, so that the terminal device executes above-mentioned method.
One or more machine readable medias are also disclosed in one embodiment of the application, are stored thereon with instruction, when by one or
When multiple processors execute, so that terminal device executes above-mentioned method.
It can be seen from the above, fabric defects information processing method and device that the embodiment of the present application proposes, include at least following
Advantage:
The fabric defects information processing method and device that the embodiment of the present invention proposes, pass through what is shown to different testing sample
Information is for statistical analysis, therefrom excavates implicit information, and then reversely instructs the production link of early period.
In some optional embodiments, after having known fault information, production link early period can be not only instructed, but also
The links such as dyeing, cutting to the later period instruct, and improve fabric utilization, reduce production loss.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is this hair
Bright some embodiments for those of ordinary skill in the art without creative efforts, can be with root
Other attached drawings are obtained according to these attached drawings.
Fig. 1 is the schematic diagram of the intelligent checking system of one embodiment of the invention.
Fig. 2 is a kind of flow chart of fabric defects information processing method of the application first embodiment.
Fig. 3 A show the schematic diagram of the dirty patch of yarn-dyed fabric.
Fig. 3 B show the schematic diagram of the disconnected warp of yarn-dyed fabric.
Fig. 3 C show the schematic diagram with yarn of yarn-dyed fabric.
Fig. 4 A show the schematic diagram of the cloth dirt of glass.
Fig. 4 B show the schematic diagram of the side damage of glass.
Fig. 4 C show the schematic diagram of the disconnected warp of glass.
Fig. 5 is a kind of block diagram of fabric defects information processing unit of one embodiment of the application.
Fig. 6 schematically shows the block diagram for executing terminal device according to the method for the present invention.
Fig. 7 schematically shows the program code storage unit for keeping or carrying realization the method for the present invention.
Specific embodiment
Below in conjunction with the attached drawing in the embodiment of the present application, technical solutions in the embodiments of the present application carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of embodiments of the present application, instead of all the embodiments.It is based on
Embodiment in the application, those of ordinary skill in the art's every other embodiment obtained belong to the application protection
Range.
The fault information processing method for the detected material (such as fabric) that one embodiment of the invention proposes can pass through fabric
Intelligent checking system realize.Introduce intelligent checking system first herein.The detected material may include fabric or non-knit
Object, fabric for example may include: chemical fibre, cotton spinning, wool spinning, fiberglass products, cord fabric, industrial filter cloth, air bag, safety
Band industrial cloth etc., non-woven for example may include film, copper foil, paper, non-woven cloth etc..
The schematic diagram of the intelligent checking system of first embodiment of the invention shown in Fig. 1, as shown in Figure 1, the intelligent measurement system
System includes smart camera 10 and display 20.
In some embodiments, intelligent checking system can also include bracket 100, and bracket 100 includes but not for setting up
It is limited to smart camera 10, sets up at least one smart camera 10, bracket 100 is used to for smart camera 10 being erected at fabric production and adds
Tooling is set, such as the top of loom, so that smart camera 10 is unhinderedly directed at the need detection fabric surface of loom.It needs to examine
Surveying fabric surface can be plane or curved surface etc., and plane or curved surface include smooth plane or curved surface, because fabric structure is made
At rough plane or curved surface and other kinds of plane or curved surface.Smart camera 10 can be multiple, intelligent phase
The quantity that machine 10 is arranged can produce and process the breadth of the produced and processed fabric of device with fabric, defect detection requires, production adds
The correlations such as speed when tooling sets production and processing, the locational space for installing intelligent checking system, such as single smart camera 10 are clapped
The visual field width taken the photograph is 300mm, and the factor that other may will affect smart camera number is all identical, when fabric width is 2000mm
When, then needing smart camera number is 2000mm/300mm=6.7, then can determine smart camera quantity at least seven of needs；
When fabric width is 1000mm, then needing smart camera number is 1000mm/300mm=3.3, then can determine the intelligence of needs
It can camera quantity at least four.
For the sake of clarity, Fig. 1 does not show that loom, light source to the present invention, however those skilled in the art should know,
The effect of bracket 100 is will to include but is not limited to that the top that fabric produces and processes the fabric of device is arranged in smart camera 10,
Therefore the position that the shape of bracket 100 and smart camera 10 are arranged is adapted to fabric production and processing device.Branch as shown in Figure 1
Frame 100 includes longitudinal support rod 101 and lateral support rod 102, be can be set on lateral support rod 102 multiple longitudinal
Smart camera 10 can be set on longitudinal support rod 101 in support rod 101.
In some embodiments, intelligent checking system can also include mobile terminal 30a perhaps server 30b or two
Person is provided simultaneously with.Mobile terminal 30a or server 30b pass through the modes such as cable network, wireless network, communication network and intelligence
Camera 10 connects, and can be used for issuing the signal for instructing, and acquiring the passback of smart camera 10 to smart camera 10；Or for
Fabric produces and processes device and issues instruction, and acquires the signal of fabric production and processing device passback.
First embodiment of the invention proposes a kind of fault information processing method of detected material (such as fabric).Shown in Fig. 2
For a kind of step flow chart of the fault information processing method of detected material of first embodiment of the invention.As shown in Fig. 2, this hair
A kind of fault information processing method of detected material (such as fabric) of bright embodiment includes the following steps:
S101 obtains the related information of detected material, and the pass information includes the status information of detected material, detected material
The running state information of manufacturing and processing equipment, operator's information of the manufacturing and processing equipment of detected material at least within it
One；
In this step, can from different information sources (such as detection system, production equipment, information management system etc.),
Pass through different data transfer mode (such as transmission of INTRANET Intranet, INTERNET the Internet transmission, storage equipment
Import, manual entry etc.) obtain detected material status information, the information of detected material manufacturing and processing equipment operating status, personnel
Information etc.；Wherein detected material status information may include the fault information of fabric.
After intelligent checking system detects fault, relevant fault information can be obtained, and be recorded in camera or
In long-range database.There can be the relevant table of fault information in database, may include detected each in table
The information such as number, fault type, coordinate, area, the size of a fault can also include the information of the fabric where fault, example
The type of such as fabric, the width of fabric, the length of fabric, the grade of fabric, the number of fabric (ID), the specification of yarn letter
Breath；Can also include detected material manufacturing and processing equipment information, such as production equipment number, power consumption, air consumption, water consumption,
The information such as environment temperature, equipment fault reason, production equipment production beginning and ending time, production equipment downtime；It simultaneously can be with
Including information such as personal informations, such as employee number, employee name, shift teams and groups.
These above-mentioned information can by different data transfer mode (such as INTRANET Intranet transmission,
INTERNET the Internet transmission, storage equipment import, manual entry etc.), it is sent to long-range mobile terminal 30a or server
30b is not specially limited herein teach that a variety of data transfer modes transmit data.
Software can be installed in mobile terminal 30a or server 30b, for mobile terminal 30a, can be application
Program (App) can be statistical summary analysis program, for according to detected material status information (such as defect for server
Point information), information, the personal information of detected material manufacturing and processing equipment operating status etc., summary for statistical analysis, subsequent
Obtain various useful information.
Table 1 show the content of the fault information in some embodiments.Table 1 is only a simple example, for illustrating
Explanation.A large amount of fault information can be generated in actual processing, the fault information that each fault includes can have more various dimensions,
Therefore more accurate foundation can be provided for the analysis of user by collecting the fault information generated in processing.
Table 1
After executing step S101, it is as follows that step S102 can be executed:
S102, it is for statistical analysis to acquired related information, the information feedback for the related information is provided；
In this step, information feedback includes feeding back for detected information feedback for the information of processing environment
With the information feedback etc. for personal information.Below by way of multiple examples, illustrate to provide the embodiment of feedback according to fault information.
In the first embodiment, abovementioned steps S102 is for statistical analysis to acquired fault information, provides and is directed to
The fault information information feedback the step of for example may include:
S102a classifies to fault and/or is scored and feed back to display device；
In some embodiments, particularly, the step of being classified to fault and/or being scored and feed back to display device can
To include: that fault is classified and scored using machine learning and deep learning model.
For example, can be classified according to preset type to fault, preset type can there are many, such as color
Woven fabric and glass, each fabric are corresponding with different fault types.
The fault type of Fig. 3 A to Fig. 3 C respectively shown for yarn-dyed fabric.It is respectively dirt as shown in Fig. 3 A to Fig. 3 C
Block, disconnected warp, band yarn.For yarn-dyed fabric, unshowned fault type at least can also include: tieing, flyings, pine hang through,
Disturb damage, Mi Lu, broken end, looped weft, thick warp, cotton point, worm stain, slubbing, greasy dirt, bead, slightly warp, heavy filling/pick, broken end, staplings, slime spots,
Tieing, material stain, Mi Lu, cotton knot, cotton balls, broken hole, color fibre, double weft, hand pick flower, dirty patch, spot, grin, become rusty stain, oil warp, oiled pick,
Palm fiber etc..
The fault type of Fig. 4 A to Fig. 4 C respectively shown for glass.As shown in Fig. 4 A to Fig. 4 C be respectively cloth it is dirty,
Side damage, disconnected warp.For glass, unshowned fault type at least may include: fracture of wire, tight end, loose weft, looped weft, knit,
Circle latitude, refuse yarn are woven into, damage through Xiang Maoyu, strand when yarn falls off, broadwise impression, cloth are dirty, disconnected warp and latitude, white cloth are dirty, big disconnected
Silk, small fracture of wire, flyings are woven into, folding is broken, slurry trace, then yarn, bad start-up, edge damage, elastic warp, staplings, grin, pore, it is dirty,
Fold, tissue collapse.
These above-mentioned fault types can be classified by way of machine learning.For example, can use machine learning
Model judges fault type.Utilization for machine learning model includes training stage and service stage:, can be in the training stage
It using multiple images comprising fault type as input machine learning model, and is fault type to these picture indicias, with this
A little images are that sample is trained machine learning model；In service stage, by the engineering that new image input training is mature
Model is practised, machine learning model can export the fault type for including in image automatically.
In further embodiments, judge that fault type can also be real by way of the deep learning in machine learning
It is existing.Deep learning is using the neural network model comprising multiple hidden layers, is established, the nerve of simulation human brain progress analytic learning
Network imitates the mechanism of human brain to explain data, such as text, image, sound.Deep learning usually requires a greater amount of training numbers
According to neural network model is trained, these training datas are, for example, the image that a large amount of label has type；After training
Service stage, new image is inputted into neural network model, neural network model can export the defect that the image includes automatically
Vertex type, and the accuracy of the information exported increases significantly compared to traditional machine learning model.
It is worth noting that, the above is only citings to be used, judge that the mode of the fault type in image can be not limited to
Above-mentioned a variety of, those skilled in the art can carry out any transformation to determining mode, these transformation are all contained in of the invention
In range.
It is exemplified by Table 1 and is illustrated, after to fault type statistics, can generate in the database as shown in Table 1
Table.It, can be according to the number of the manufacturing and processing equipment when the fault type generated for a certain processing machine is counted
It is retrieved, such as it is all dirty patch that retrieval yarn-dyed fabric, which numbers the fault that the manufacturing and processing equipment for being 100 generates,；Retrieve glass number
Fault for 400 manufacturing and processing equipment generation is all edge damage.
It, can be according to the production and processing people when fault that generates counts in for a certain production and processing personnel operation
The number of member is retrieved, such as it is respectively 004 He of number that retrieval producers, which number the fault that the operator for being A03 generates,
005 disconnected warp and cloth is dirty, and other associated information, such as fault size, process time can be obtained etc..
After obtaining these information, it may be displayed on display device 20 shown in FIG. 1, also may be displayed on other tools
Have on the device of display function, is analyzed for operator.
In a second embodiment, abovementioned steps S102 is for statistical analysis to acquired related information, provides and is directed to
The related information information feedback the step of for example may include:
S102b, when fault size, quantity, type at least one be greater than preset threshold value when, issue prompt information it is anti-
It is fed to display device.
In this step, in conjunction with shown in table 1, preset threshold value is, for example, 4mm2, when the size of fault is greater than preset
When threshold value, it is believed that the fault is more serious problem, then can issue prompt information and show to display device.Such as
The dirty patch that number is 002, due to judging that its area has exceeded 4mm2Threshold value, can issue prompt information and be shown in display dress
It sets.
In some embodiments, prompt information may include when prompt degrades, prompt final finishing is processed using suitable work
Skill, prompt board likelihood of failure, prompt the workmanship etc. for checking operator, and those skilled in the art can know presence
The mode and content of a variety of prompts, do not repeat herein.
In the third embodiment, abovementioned steps S102 is for statistical analysis to acquired related information, provides and is directed to
The related information information feedback the step of for example may include:
S102c is determined according to the information of the fault information or detected material manufacturing and processing equipment operating status and is detected
The problem of object manufacturing and processing equipment.
In this step, it can be produced for type, coordinate and quantity and equipment fault reason, the production equipment of fault
The information such as beginning and ending time, production equipment downtime determine the problem of manufacturing and processing equipment of processing detected material.
For example, as above-mentioned, it can be according to the number of manufacturing and processing equipment, to the defect for the fault that the manufacturing and processing equipment generates
Point information is analyzed.The manufacturing and processing equipment for being 100 for number, the production can be not only gone out by fault information analysis and is added
Construction equipment is easy to produce dirty patch, but also can further obtain information according to fault coordinate.For example, if fault coordinate is aobvious
Show, the x-axis coordinate difference of each fault is little, and the increased of y-axis coordinate is regular, it may be considered that the production and processing
Equipment passes periodically through the point of a generation spot during cloth rewinder roll rotates, therefore can be directed to this problem, prompts
Operator, so that operator is handled in time.
The problem of above in relation to manufacturing and processing equipment is only that citing is used, and those skilled in the art can pass through fault information
Know it is more manufacturing and processing equipment aiming at the problem that, such as when detecting the continuous broken yarn of y-axis coordinate, it is believed that production adds
The equipment of work fabric is problematic (such as: reed abrasion), these information can feed back to operator, be handled in time.
The mode of prompt operator can be to be prompted using display device above-mentioned；Or the volume according to operator
Number, the terminal device for being sent directly to operator's carrying is medium, and the present invention is not specially limited.
In the fourth embodiment, abovementioned steps S102 is for statistical analysis to acquired related information, provides and is directed to
The related information information feedback the step of for example may include:
S102d is determined according to the information of the fault information or detected material manufacturing and processing equipment operating status and is detected
Object produces and processes the problem of personnel.
In this step, the problem of processing staff being confirmed according to the type and quantity of fault.For example, when some adds
When the number that the manufacturing and processing equipment of worker person's operation generates fault is significantly more than other processing staff, it is believed that processing people
The operative skill of member needs further to be trained.Therefore it can further be trained for the processing staff.
In the 5th embodiment, abovementioned steps S102, i.e., it is for statistical analysis to acquired related information, it provides and is directed to
The related information information feedback the step of for example may include:
S102e runs shape according to the detected material status information (such as fault information), detected material manufacturing and processing equipment
Information, personal information of state etc. determine the problem of detected material raw material.
In this step, the problem of raw material being reflected according to the type and quantity of fault.Such as it is raw in factory
When production, raw material all obtain from raw material supplier in batch.The raw material number of every a batch product can reflect out
Its source.Table 2 show a kind of illustrative table of fault information comprising rule of origin:
Table 2
According to table 2, the raw material work in-process that raw material number is 070 is easy to appear the fault of palm fiber and color fibre,
This illustrates that it is necessary to further be promoted, therefore in subsequent processing, it is pre- can be directed to the raw material for the quality inspection requirement of the raw material
Incoming Quality Control or sampling observation are first carried out, or the foundation when purchasing raw material as guidance purchase.
Further, other than raw material number, the producer for producing the raw material can also be associated with out.Believed using fault
Breath assesses the production level of manufacturer.
Those skilled in the art are it is ensured that determine processing detected material for according to the type and coordinate of fault
The problem of raw material, can have a variety of judgment modes, not list one by one herein.
In the sixth embodiment, abovementioned steps S102, that is, described for statistical analysis to acquired related information, provides
For the related information information feedback the step of for example may include:
S102f runs shape according to the detected material status information (such as fault information), detected material manufacturing and processing equipment
Information, personal information of state etc. determine the problem of detected material production and processing environment.
It in this step, can be according to the temperature, wet in the current environment for including in fault information in conjunction with shown in table 2
The information such as degree, judge whether the environment of processing material web is qualified.
Such as yarn-dyed fabric, with the raising of temperature and humidity, the fault of generation does not have significant change；And with production
The increase of dust concentration in environment, the fault of generation obviously increase, it is believed that are that environmental problem affects processing, therefore
Adjustable production environment, such as reduce dust concentration.
Such as glass, when other conditions are constant, temperature is increased to 26 DEG C, and the disconnected of generation increased significantly, then recognizes
Production is affected for temperature, produces more fault；When other conditions are constant, when humidity is increased to 40%, generation is broken
Through increased significantly, then it is assumed that humidity affects production, produces more fault.Therefore it can be controlled in the processing for glass
Temperature and humidity processed reduces the generation of defect rate.
In the seventh embodiment, abovementioned steps S102, that is, described for statistical analysis to acquired related information, provides
For the related information information feedback the step of for example may include:
S102g determines the cutting method to detected material according to the fault information.
In this step, when determined the size of the kind of detected material, type, breadth, length and fault, coordinate,
It when scoring and quantity, can be cut automatically according to the coordinate of fault, the foundation of cutting is to avoid realization while fault
The maximization of detected material usable area.In specific implementation, can be by the way of linear programming, optimization object function (is cut out
Cut product below), the extreme value of objective function is acquired, is calculated automatically and automatic cutting.
In the eighth embodiment, abovementioned steps S102 i.e. to acquired detected material status information (such as fault information),
Information, the personal information of detected material manufacturing and processing equipment operating status etc. are for statistical analysis, provide for the information
Information feed back the step of for example may include:
S102h determines the scoring of detected material according to the fault information.
In this step, it can score first fault, the scoring further according to fault determines commenting for detected material
Point.The scoring of fault is in the field of business known marking mode and grade, can be tested according to this after fault scoring has been determined
The scoring for surveying all faults on object, utilizes the scoring in the way of weighting, determining entire detected material.The scoring of detected material
With direct ratio or the scoring of fault can be inversely proportional to.Corresponding formula can be set to be calculated automatically.
After determining the scoring of detected material, corresponding grade and price can be arranged according to scoring, it is no longer superfluous herein
It states.
To sum up, the step S102, for statistical analysis to acquired fault information, provide for the fault
The information of information is fed back, and at least may include the production link or following process link according to fault information to the detected material
Information feedback is provided.
It can be seen from the above, the embodiment of the present invention propose a kind of detected material fault information processing method at least have it is as follows
Technical effect:
The present invention utilizes the detected material status information (such as fault information), detected material manufacturing and processing equipment got
Information, operator's information of detected material manufacturing and processing equipment of operating status etc. provide information feedback.Detected material state
Information includes but is not limited to the type of fault, the position of fault, time, the frequency of fault of fault appearance etc.；Detected material is raw
Produce process equipment running state information include but is not limited to production equipment number, power consumption, air consumption, water consumption, environment temperature,
The information such as equipment fault reason, production equipment production beginning and ending time, production equipment downtime；Personal information includes but is not limited to
The information such as employee number, employee name, shift teams and groups.Information feedback includes but is not limited to the manufacturing and processing equipment of detected material
The problem of the problem of problem, raw material, the operational issue of the production and processing personnel of manufacturing and processing equipment, environment, detected material production
The problem of processing method.It after providing information feedback, can be adjusted, be changed in production environment according to the information of feedback
The factor for easily causing detected flaw improves the qualification rate of detected material.
The fault information processing method and device for the detected material that the embodiment of the present invention proposes, by different testing sample table
The information revealed is for statistical analysis, therefrom excavates implicit information, and then reversely instructs the production link of early period.
In some optional embodiments, after having known fault information, production link early period can be not only instructed, but also
The links such as dyeing, cutting to the later period instruct, and improve fabric utilization, reduce production loss.
3rd embodiment
Third embodiment of the invention proposes a kind of fault information processing unit of detected material (such as fabric), such as Fig. 5 institute
Show, which includes:
Data obtaining module 501 leads to from different information sources (such as detection system, production equipment, information management system etc.)
Crossing different data transfer modes, (such as the transmission of INTRANET Intranet, INTERNET the Internet transmission, storage equipment are led
Enter, manual entry etc.) obtain detected material status information (such as fault information), detected material manufacturing and processing equipment operating status
Information, personal information etc.；
Statistical analysis module 502 adds acquired detected material status information (such as fault information), detected material production
Information, the personal information of construction equipment operating status etc. are for statistical analysis, provide the information feedback for the information.
In conclusion a kind of fault information processing unit for detected material (such as fabric) that the present embodiment proposes at least has
It has the following advantages:
The present invention is transported using detected material status information (such as fault information), the detected material manufacturing and processing equipment got
Information, personal information of row state etc. provide information feedback.Detected material status information includes but is not limited to the type of fault, defect
Time, the frequency of fault etc. that the position of point, fault occur；Detected material manufacturing and processing equipment running state information includes but not
It is limited to production equipment number, power consumption, air consumption, water consumption, environment temperature, equipment fault reason, production equipment production start-stop
The information such as time, production equipment downtime；Personal information includes but is not limited to employee number, employee name, shift teams and groups etc.
Information.The problem of the problem of information feedback includes but is not limited to the manufacturing and processing equipment of detected material, raw material, manufacturing and processing equipment
Production and processing personnel operational issue, environment the problem of, detected material production and processing method the problem of.It is anti-providing information
It after feedback, can be adjusted according to the information of feedback, change the factor for easily causing detected flaw in production environment, improved
The qualification rate of detected material.
The fault information processing method and device for the detected material (such as fabric) that the embodiment of the present invention proposes, by not
The information shown with detectable substance is for statistical analysis, therefrom excavates implicit information, and then reversely instructs the production ring of early period
Section.
In some optional embodiments, after having known fault information, production link early period can be not only instructed, but also
The links such as dyeing, cutting to the later period instruct, and improve fabric utilization, reduce production loss.
For device embodiment, since it is basically similar to the method embodiment, related so describing fairly simple
Place illustrates referring to the part of embodiment of the method.
Fig. 6 is the hardware structural diagram for the terminal device that one embodiment of the application provides.As shown in fig. 6, the terminal is set
Standby may include input equipment 90, processor 91, output equipment 92, memory 93 and at least one communication bus 94.Communication is total
Line 94 is for realizing the communication connection between element.Memory 93 may include high speed RAM memory, it is also possible to further include non-easy
The property lost storage NVM, for example, at least a magnetic disk storage can store various programs in memory 93, for completing various places
It manages function and realizes the method and step of the present embodiment.
Optionally, above-mentioned processor 91 can be for example central processing unit (Central Processing Unit, abbreviation
CPU), application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing appts (DSPD), programmable
Logical device (PLD), field programmable gate array (FPGA), controller, microcontroller, microprocessor or other electronic components are real
Existing, which is coupled to above-mentioned input equipment 90 and output equipment 92 by wired or wireless connection.
Optionally, above-mentioned input equipment 90 may include a variety of input equipments, such as may include user oriented user
At least one of interface, device oriented equipment interface, the programmable interface of software, camera, sensor.Optionally, the face
It can be wireline interface for carrying out data transmission between equipment and equipment to the equipment interface of equipment, can also be for setting
Standby hardware the insertion interface, such as USB interface, serial ports etc. carried out data transmission between equipment；Optionally, this is user oriented
User interface for example can be user oriented control button, the voice-input device for receiving voice input and user and connect
Receive the touch awareness apparatus, such as the touch screen with touch sensing function, Trackpad etc. of touch input；Optionally, above-mentioned soft
The programmable interface of part for example can be the entrance for editing or modifying program for user, for example, chip input pin interface or
Person's input interface etc.；The audio input device such as microphone can receive voice data.Output equipment 92 may include display, sound
The output equipments such as sound.
In the present embodiment, the processor of the terminal device includes for executing each module of data processing equipment in each equipment
Function, concrete function and technical effect are referring to above-described embodiment, and details are not described herein again.
Fig. 7 is the hardware structural diagram for the terminal device that another embodiment of the application provides.Fig. 7 is being realized to Fig. 6
A specific embodiment in the process.As shown in fig. 7, the terminal device of the present embodiment includes processor 101 and memory
102。
Processor 101 executes the computer program code that memory 102 is stored, and realizes Fig. 1 to Fig. 5 in above-described embodiment
A kind of detected material (such as fabric) fault information processing method.
Memory 102 is configured as storing various types of data to support the operation in terminal device.These data
Example includes the instruction of any application or method for operating on the terminal device, such as message, picture, video etc..
Memory 102 may include random access memory (random access memory, abbreviation RAM), it is also possible to further include non-
Volatile memory (non-volatile memory), for example, at least a magnetic disk storage.
Optionally, processor 101 is arranged in processing component 100.The terminal device can also include: communication component 103,
Power supply module 104, multimedia component 105, audio component 106, input/output interface 107 and sensor module 108.Terminal is set
Standby component for specifically being included etc. is set according to actual demand, and the present embodiment is not construed as limiting this.
The integrated operation of the usual controlling terminal equipment of processing component 100.Processing component 100 may include one or more places
Device 101 is managed to execute instruction, to complete all or part of the steps of above-mentioned Fig. 1 to Fig. 7 method.In addition, processing component 100 can be with
Including one or more modules, convenient for the interaction between processing component 100 and other assemblies.For example, processing component 100 can wrap
Multi-media module is included, to facilitate the interaction between multimedia component 105 and processing component 100.
Power supply module 104 provides electric power for the various assemblies of terminal device.Power supply module 104 may include power management system
System, one or more power supplys and other with for terminal device generate, manage, and distribute the associated component of electric power.
Multimedia component 105 includes that the display screen of an output interface is provided between terminal device and user.Some
In embodiment, display screen may include liquid crystal display (LCD) and touch panel (TP).If display screen includes touch panel,
Display screen may be implemented as touch screen, to receive input signal from the user.Touch panel includes one or more touches
Sensor is to sense the gesture on touch, slide, and touch panel.The touch sensor can not only sense touch or sliding
The boundary of movement, but also detect duration and pressure associated with the touch or slide operation.
Audio component 106 is configured as output and/or input audio signal.For example, audio component 106 includes a Mike
Wind (MIC), when terminal device is in operation mode, when such as speech recognition mode, microphone is configured as receiving external audio letter
Number.The received audio signal can be further stored in memory 102 or send via communication component 103.In some realities
It applies in example, audio component 106 further includes a loudspeaker, is used for output audio signal.
Input/output interface 107 provides interface, above-mentioned peripheral interface between processing component 100 and peripheral interface module
Module can be click wheel, button etc..These buttons may include, but are not limited to: volume button, start button and locking press button.
Sensor module 108 includes one or more sensors, and the state for providing various aspects for terminal device is commented
Estimate.For example, sensor module 108 can detecte the state that opens/closes of terminal device, the relative positioning of component, Yong Huyu
The existence or non-existence of terminal device contact.Sensor module 108 may include proximity sensor, be configured to do not appointing
Detected the presence of nearby objects when what physical contact, including detection user between terminal device at a distance from.In some embodiments
In, which can also be including camera etc..
Communication component 103 is configured to facilitate the communication of wired or wireless way between terminal device and other equipment.Eventually
End equipment can access the wireless network based on communication standard, such as WiFi, 2G, 3G, 4G, 5G or their combination.In a reality
It applies in example, may include SIM card slot in the terminal device, the SIM card slot is for being inserted into SIM card, so that terminal device can
To log in GPRS network, communicated by internet with server-side foundation.
From the foregoing, it will be observed that communication component 103, audio component 106 involved in Fig. 7 embodiment and input/output connect
Mouth 107, sensor module 108 can be used as the implementation of the input equipment in Fig. 6 embodiment.
The embodiment of the present application provides a kind of terminal device, comprising: one or more processors；It is instructed with being stored thereon with
One or more machine readable medias, when by one or more of processors execute when so that the terminal device execute
Method as described in one or more in the embodiment of the present application.
All the embodiments in this specification are described in a progressive manner, the highlights of each of the examples are with
The difference of other embodiments, the same or similar parts between the embodiments can be referred to each other.
Although preferred embodiments of the embodiments of the present application have been described, once a person skilled in the art knows bases
This creative concept, then additional changes and modifications can be made to these embodiments.So the following claims are intended to be interpreted as
Including preferred embodiment and all change and modification within the scope of the embodiments of the present application.
Finally, it is to be noted that, herein, relational terms such as first and second and the like be used merely to by
One entity or operation are distinguished with another entity or operation, without necessarily requiring or implying these entities or operation
Between there are any actual relationship or orders.Moreover, the terms "include", "comprise" or its any other variant meaning
Covering non-exclusive inclusion, so that process, method, article or terminal device including a series of elements not only wrap
Those elements are included, but also including other elements that are not explicitly listed, or further includes for this process, method, article
Or the element that terminal device is intrinsic.In the absence of more restrictions, being wanted by what sentence "including a ..." limited
Element, it is not excluded that there is also other identical elements in process, method, article or the terminal device for including the element.
Above to the fault information processing method and device of a kind of detected material (such as fabric) provided herein, into
It has gone and has been discussed in detail, specific examples are used herein to illustrate the principle and implementation manner of the present application, the above implementation
The explanation of example is merely used to help understand the present processes and its core concept；Meanwhile for the general technology people of this field
Member, according to the thought of the application, there will be changes in the specific implementation manner and application range, in conclusion this explanation
Book content should not be construed as the limitation to the application.
Claims (14)
1. a kind of fabric defects information processing method characterized by comprising
The related information of detected material is obtained, the related information includes the production of the status information of detected material, detected material
The running state information of process equipment, operator's information of the manufacturing and processing equipment of detected material at least one；
It is for statistical analysis to acquired related information, the information feedback for the related information is provided；
Wherein the detected material status information includes fault information.
Wherein the detected material includes fabric.
2. fabric defects information processing method according to claim 1, which is characterized in that described to believe acquired association
Cease it is for statistical analysis, provide for the related information information feedback, comprising:
Classified to fault and/or is scored and feed back to display device.
3. fabric defects information processing method according to claim 1, which is characterized in that described to classify to fault
And/or it scores and includes: the step of feeding back to display device
Fault is classified and scored using machine learning or deep learning model.
4. fabric defects information processing method according to claim 1, which is characterized in that described to believe acquired association
Cease it is for statistical analysis, provide for the related information information feedback, comprising:
When fault size, quantity, type at least one be greater than preset threshold value when, issue prompt information feed back to display dress
It sets.
5. fabric defects information processing method according to claim 1, which is characterized in that the detected material type includes
Following at least one: chemical fibre, cotton spinning, wool spinning, fiberglass products, cord fabric or industrial filter cloth.
6. fabric defects information processing method according to claim 1, which is characterized in that described to believe acquired association
Cease it is for statistical analysis, provide for the related information information feedback, comprising:
The production of detected material is determined according to the information of the fault information and/or detected material manufacturing and processing equipment operating status
The problem of process equipment.
7. fabric defects information processing method according to claim 1, which is characterized in that described to believe acquired association
Cease it is for statistical analysis, provide for the related information information feedback, comprising:
According to the detected material status information, the information of detected material manufacturing and processing equipment operating status, detected material production
Operator's information of processing determines the problem of production and processing personnel of detected material.
8. fabric defects information processing method according to claim 1, which is characterized in that described to believe acquired association
Cease it is for statistical analysis, provide for the related information information feedback, comprising:
According to the detected material status information, the information of the operating status of the manufacturing and processing equipment of detected material, detected material
Operator's information of manufacturing and processing equipment the problem of determining detected material raw material.
9. fabric defects information processing method according to claim 1, which is characterized in that described to believe acquired association
Cease it is for statistical analysis, provide for the related information information feedback, comprising:
According to the detected material status information, the information of the operating status of the manufacturing and processing equipment of detected material, detected material
Operator's information of manufacturing and processing equipment the problem of determining the production and processing environment of detected material.
10. fabric defects information processing method according to claim 1, which is characterized in that described to acquired association
Information is for statistical analysis, provide for the related information information feedback, including it is following at least one:
The cutting method to detected material is determined according to the fault information；
The scoring of detected material is determined according to the fault information.
11. fabric defects information processing method according to claim 1, which is characterized in that described to acquired association
Information is for statistical analysis, provides the information feedback for the related information, comprising:
It is anti-to the production link of the detected material, printing and dyeing link, cutting link, at least one offer information of sales section
Feedback.
12. fabric defects information processing method according to claim 1, which is characterized in that described to acquired association
Information is for statistical analysis, provides the information feedback for the related information, comprising:
According to the detected material status information, the information of the operating status of the manufacturing and processing equipment of detected material, detected material
Operator's information of manufacturing and processing equipment the problem of determining detected material production and processing method.
13. a kind of terminal device characterized by comprising
One or more processors；With the one or more machine readable medias for being stored thereon with instruction, when by one or
When multiple processors execute, so that the terminal device executes the method as described in one or more in claim 1-12.
14. one or more machine readable medias, are stored thereon with instruction, when executed by one or more processors, so that
Terminal device executes the method as described in one or more in claim 1-12.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910600560.3A CN110412037A (en) | 2019-07-04 | 2019-07-04 | A kind of fabric defects information processing method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910600560.3A CN110412037A (en) | 2019-07-04 | 2019-07-04 | A kind of fabric defects information processing method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110412037A true CN110412037A (en) | 2019-11-05 |
Family
ID=68360191
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910600560.3A Pending CN110412037A (en) | 2019-07-04 | 2019-07-04 | A kind of fabric defects information processing method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110412037A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110954548A (en) * | 2019-11-28 | 2020-04-03 | 西安获德图像技术有限公司 | Cloth inspecting machine based on machine vision and method for detecting cloth defects by adopting cloth inspecting machine |
| CN111024720A (en) * | 2019-12-13 | 2020-04-17 | 东华大学 | Visual and tactile integrated detection device for protruding defects on surface of fabric |
| CN111595237A (en) * | 2020-05-13 | 2020-08-28 | 广西大学 | Machine vision-based fabric size measurement distributed system and method |
| CN112115287A (en) * | 2020-08-17 | 2020-12-22 | 联通(广东)产业互联网有限公司 | Method, system and medium based on AI quality inspection and industrial big data analysis |
| CN113249982A (en) * | 2021-06-18 | 2021-08-13 | 南通宝硕纺织品有限公司 | Method and device for improving printing stability of fabric |
| CN116008289A (en) * | 2023-02-07 | 2023-04-25 | 浙江聚优非织造材料科技有限公司 | Nonwoven product surface defect detection method and system |
| TWI818876B (en) * | 2023-03-06 | 2023-10-11 | 適着三維科技股份有限公司 | Fabric simulation device and method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3841761A (en) * | 1973-10-24 | 1974-10-15 | Neotec Corp | Method and apparatus for detecting faults in fabric |
| JP2004117229A (en) * | 2002-09-27 | 2004-04-15 | Hitachi Ltd | Defect data analytic method, apparatus for the same and review system |
| CN101598677A (en) * | 2009-07-03 | 2009-12-09 | 天津工业大学 | Online three-dimensional recognition method of fabric defects |
| CN201778193U (en) * | 2010-07-14 | 2011-03-30 | 陈明泽 | Monitoring system with far infrared wireless remote controller for detecting looms and cloth inspecting machines |
| CN107907548A (en) * | 2017-11-23 | 2018-04-13 | 南通大学 | A kind of raw silk shade detection device |
| CN108268892A (en) * | 2017-12-29 | 2018-07-10 | 英特尔产品（成都）有限公司 | Fault in production management analysis method |
-
2019
- 2019-07-04 CN CN201910600560.3A patent/CN110412037A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3841761A (en) * | 1973-10-24 | 1974-10-15 | Neotec Corp | Method and apparatus for detecting faults in fabric |
| JP2004117229A (en) * | 2002-09-27 | 2004-04-15 | Hitachi Ltd | Defect data analytic method, apparatus for the same and review system |
| CN101598677A (en) * | 2009-07-03 | 2009-12-09 | 天津工业大学 | Online three-dimensional recognition method of fabric defects |
| CN201778193U (en) * | 2010-07-14 | 2011-03-30 | 陈明泽 | Monitoring system with far infrared wireless remote controller for detecting looms and cloth inspecting machines |
| CN107907548A (en) * | 2017-11-23 | 2018-04-13 | 南通大学 | A kind of raw silk shade detection device |
| CN108268892A (en) * | 2017-12-29 | 2018-07-10 | 英特尔产品（成都）有限公司 | Fault in production management analysis method |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110954548A (en) * | 2019-11-28 | 2020-04-03 | 西安获德图像技术有限公司 | Cloth inspecting machine based on machine vision and method for detecting cloth defects by adopting cloth inspecting machine |
| CN111024720A (en) * | 2019-12-13 | 2020-04-17 | 东华大学 | Visual and tactile integrated detection device for protruding defects on surface of fabric |
| CN111595237A (en) * | 2020-05-13 | 2020-08-28 | 广西大学 | Machine vision-based fabric size measurement distributed system and method |
| CN112115287A (en) * | 2020-08-17 | 2020-12-22 | 联通(广东)产业互联网有限公司 | Method, system and medium based on AI quality inspection and industrial big data analysis |
| CN113249982A (en) * | 2021-06-18 | 2021-08-13 | 南通宝硕纺织品有限公司 | Method and device for improving printing stability of fabric |
| CN113249982B (en) * | 2021-06-18 | 2021-09-10 | 南通宝硕纺织品有限公司 | Method and device for improving printing stability of fabric |
| CN116008289A (en) * | 2023-02-07 | 2023-04-25 | 浙江聚优非织造材料科技有限公司 | Nonwoven product surface defect detection method and system |
| CN116008289B (en) * | 2023-02-07 | 2024-06-07 | 浙江聚优非织造材料科技有限公司 | Nonwoven product surface defect detection method and system |
| TWI818876B (en) * | 2023-03-06 | 2023-10-11 | 適着三維科技股份有限公司 | Fabric simulation device and method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110412037A (en) | A kind of fabric defects information processing method and device | |
| Nayak et al. | Automation in garment manufacturing | |
| US20040133297A1 (en) | Method for optimizing a textile production process and devices applying this method | |
| Simonis et al. | INDUSTRIE 4.0-Automation in weft knitting technology | |
| Rasheed et al. | Geometrical model to calculate the consumption of sewing thread for 301 lockstitch | |
| CN104375491B (en) | Spinning workshop environment monitoring and alarming system | |
| CN115201211A (en) | Quality control method and system for intelligent visual textile product | |
| CN104360669B (en) | A kind of spinning and weaving workshop environment control method | |
| CN106087154A (en) | A kind of problem spindle alignment system for spinning frame and method | |
| CN203096481U (en) | Cloth inspecting and rolling machine | |
| CN106556604B (en) | Cloth inspection machine capable of inspecting and marking flaws and use method thereof | |
| CN108491904A (en) | Clothing production management system based on Internet of things | |
| CN206033962U (en) | A problem spindle positioning system for spinning frame | |
| CN112760831A (en) | Intelligent piece counting method and system based on sewing equipment | |
| TWM595133U (en) | Information management monitoring and early warning integration system for cloud real-time textile intelligent production | |
| CN103440523B (en) | Labor standard labor time equipment system in vest production and method of work thereof | |
| CN107130326A (en) | Ring-traveller quality online test method | |
| CN205821660U (en) | A kind of full-automatic high head sewing machine | |
| CN115508282A (en) | Online intelligent cloth inspection detection system | |
| CN114004819A (en) | Cloth inspection processing method, device, equipment, system and medium | |
| CN204203758U (en) | Spinning and weaving workshop environmental monitoring warning system | |
| CN205347714U (en) | Novel special sewing machine of suit | |
| Singha et al. | Use of AI and machine learning techniques in knitting | |
| Arikan | Developing an intelligent automation and reporting system for fabric inspection machines | |
| CN205644632U (en) | Embroidery equipment standard work force system in ready -made clothe production |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |