CN102818809A - Gray cloth defect on-line detecting system based on machine vision and achieving method - Google Patents
Gray cloth defect on-line detecting system based on machine vision and achieving method Download PDFInfo
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Abstract
The invention relates to a gray cloth defect on-line detecting system based on machine vision and an achieving method. The gray cloth defect on-line detecting system comprises a cross beam device, a lighting device, industrial cameras, an industrial control host machine, a display control screen and an alarm indicating module. The cross beam device is installed right above or obliquely above gray cloth detected by a warp knitting machine just now and is used for fixing the lighting device and a round steel pipe, and a group of industrial cameras are fixedly connected to the round steel pipe. The display control screen is connected with the industrial control host machine, diameters of the system are set through the display control screen in a setting state, and defect shapes and regions with defects can be observed in an operating state. The alarm indicating module comprises an alarm indicating lamp and a light-emitting diode (LED) information indicating panel, wherein the alarm indicating lamp can alarm an operator in an acousto-optic signal mode when the defects exist, and the LED information indicating panel indicates whether machine detection is normal or not or the regions and positions where the defects exist. The achieving method has the advantages of overcoming the shortage of the method and being a novel method utilizing a machine vision technology in the field of detection of warp knitting defects.
Description
Technical field
The present invention relates to field of textiles, especially a kind of grey cloth fault on-line detecting system and implementation method based on machine vision.
Background technology
In the process of tricot machine establishment cloth, Fabric Defects Inspection can appear after yarn ruptured, and the fault of the type is to estimate the main parameter of the grade of a warp knitting cloth quality.In the prior art, the auxiliary detection technology is main with zlasing mode and photoelectricity sensing array scan-type mainly.It detects principle: (1) zlasing mode: a pair of laser diode emitters and receiver relatively are installed on loom, are made the horizontal cloth surface of plunderring of laser beam, laser beam is vertical with the trend of cloth.When fault takes place; Correspondence has yarn and ruptures; When yarn was broken, under the air-flow effect of fan blower and the generation of air guide pipeline, thereby yarn can waft into the laser rays disturbance; Produce the subtle disruption of light, photosensitive device and subsequent conditioning circuit are accomplished a defect detection through catching this interference.The verification and measurement ratio of this pattern is generally about 50%-60%, and powerless to the broken string defect detection after knitting.(2) scan pattern: adopt the integrated array of 16-64 photoelectric tubes, this array and cloth surface 8-10cm place that is separated by is moved reciprocatingly perpendicular to the cloth direction, in the motion process, photovoltaic array is from limited regional interior (about 5*8cm
2) obtain the light and shade information of cloth surface light, thus judge through the digital processing unit system whether yarn fracture takes place produce fault.The verification and measurement ratio of this pattern is about 80%-85%, and is lower to the fault recall rate at cloth two ends.Above-mentioned two kinds of patterns equipment power consumption is big, and its utility appliance is installed complicacy, maintenance workload is big.
Summary of the invention
The present invention will solve the shortcoming of above-mentioned prior art, and a kind of grey cloth fault on-line detecting system and implementation method based on machine vision is provided, and refers in particular to NI Vision Builder for Automated Inspection and method that whether the online detection when compiling of a kind of field of textiles grey cloth has fault.
The present invention solves the technical scheme that its technical matters adopts: this grey cloth fault on-line detecting system based on machine vision; Comprise beam device, lighting device and industrial camera, industrial control host, show control screen and warning indicating module; Beam device be installed in grey cloth to be detected that tricot machine just accomplished directly over or oblique upper; Beam device is used for fixing lighting device and fixing round steel pipe, is fixedly connected with one group of industrial camera on the round steel pipe; Round steel pipe also is fixed in combination square steel crossbeam, and round steel pipe is used for fixing the industrial camera anchor clamps to constitute the industrial camera array, and industrial camera array symmetry is placed.Round steel pipe 1-5 is that the short tube of 1m is formed by unit length, and the number of industrial camera 1-6 is confirmed according to the demand of grey cloth width.Said apparent control screen links to each other with industrial control host, when state is set, through showing the parameters that the control screen is provided with system, when running status, can observe the zone of fault form and generation fault; Said warning indicating module comprises alarm lamp and LED information indication panel; Alarm lamp can the form with sound and light signal be warned operating personnel when fault takes place, and whether normally LED information indication panel indication machine detects the regional location of operation or fault generation.
The outside of said beam device, lighting device and industrial camera be equipped be used to prevent dust, the rectangular parallelepiped shell of the shielding of electrostatic prevention, beam device adopts the square steel of hollow, square steel inside is used to walk cable.
Said industrial camera adopts the high precision industrial camera, and the image of camera sensor is to be not less than 1,300,000 pixels above area array CCD or CMOS.Type selecting precision and image fineness according to industrial camera confirm that industrial camera leaves the distance of grey cloth face, through regulating the lens focus that is articulated on the industrial camera, can obtain grey cloth face image clearly.
Said lighting device is made up of one group of linear linearly aligned luminophor; Adjacent tubulose luminophor has lap in the field of illumination of grey cloth to be detected; And all tubulose luminophors cover whole district to be detected in the field of illumination that grey cloth to be detected is spliced to form;, even with the image chiaroscuro effect that guarantees the industrial camera collection.
Said industrial control host comprises system power supply, industrial control mainboard and IO input and output control panel, and said system power supply adopts the electric supply installation of Switching Power Supply as industrial control mainboard, industrial camera and IO input and output control panel; Said industrial control mainboard is carried out software trigger or pulse producer with control panel and is triggered and make the industrial camera images acquired through triggering, industrial camera through USB, 1394 or the transmission mode of GigE kilomega network upload the image of triggering collection to industrial control host.In the industrial control host in IO input/output module and the system industrial camera link to each other and constitute " * " type and trigger and be connected; Light-coupled isolation is adopted in the connectivity port, and arbitrary mode that industrial control host is freely gathered through synchronous triggering, serial triggering or triggerless software according to the configuring condition of software algorithm is controlled the industrial camera images acquired.
The implementation method of this grey cloth fault on-line detecting system based on machine vision of the present invention; May further comprise the steps: industrial control mainboard is handled the image of gathering through fault recognition image Processing Algorithm; When showing the discovery fault in the result; Industrial control host is to IO input and output control panel transmitting order to lower levels, and IO input and output control panel is shut down according to command driven actuating of relay control tricot machine; When tricot machine is in time-out warping state; IO input and output control panel continuous capturing tricot machine running status is also uploaded the tricot machine duty to industrial control mainboard in real time; After the operator handles fault well; When tricot machine restarted, industrial control mainboard was delayed time according to machine state and is restarted fault recognition image Processing Algorithm, and wherein the purpose of time-delay is to skip tricot machine to start the non-full speed non-steady state in preceding 4 seconds.
The detection step of said industrial control mainboard is following: after machine is opened, and the program random start, the program after the startup is carried out initialization earlier, comprises reading in automatically of CONFIG.SYS and opening up of image memory space; After initialization was accomplished, industrial control mainboard detected tricot machine through IO input and output control panel and whether is in running status, if tricot machine is in running status; Then program gets into the time-delay wait, when delay time reaches n empirical value second; N is traditionally arranged to be at 4 o'clock, and fault recognition image Processing Algorithm starts; Flame Image Process and analysis module take out view data in each memory headroom, the original image of collection makes the fault of image strengthen and the background texture obfuscation through the figure image intensifying process of greyscale transformation, mean filter; Adopt the Niblack method to carry out the local threshold binary conversion treatment to image through pre-treatment; According to the image of binary conversion treatment, the disposal route of utilizing advanced form to learn is removed the noise particulate in the image, and whether sreen analysis utilizes the eigenwert leash law to detect fault and exist through particle remaining in the image is screened; For existing, then representing has the fault existence like testing result, and this moment, industrial control mainboard need be sent instruction and the shutdown of control tricot machine to IO input and output control panel, and this process shows that taking turns detection finishes; After the operator carries out the fault reparation, when not quitting a program, detect and get into the foregoing description flow process again in system; For not existing, then carry out new IMAQ and judgement like testing result again.
Described equalization is handled and is adopted [0,255] interval broadening; Filtering Processing adopts the effect nuclear matrix of 3x3 or 5x5; Adopt the NiBlack algorithm during analysis of threshold, its effect nuclear should adopt the big minor matrix of 16x8, and deviation factors is set to 0.6; When choosing Background Correction and carrying out analysis of threshold, the nuclear matrix parameter is provided with Niblack; Advanced form is learned and is handled the corrosion operation that the anistree data matrix of checking Hexa that adopts 3x3 carries out 8 connections; Morphology is handled and is adopted conventional open and close computing and expansion, corrosion to operate; Nuclear is the 3x3 matrix; The mode of action be
sreen analysis adopt fault height, angle and length ratio characteristic as basis for estimation; When the doubtful fault after the algorithm process satisfies the parameter setting of sreen analysis, then carry out fault identification and record.
Further, be false alarm and the manually-operated of avoiding detecting, set warning/shutdown sensitivity in the program; Promptly confirm the number of times adjusting; And the functionality buttons of manual switching, can set manual mode or automatic mode, help tackling the numerous uncertain factors in the actual engineering.Only report to the police when detecting fault during manual mode and do not shut down, can whether shut down, at the next generation above-mentioned condition of automatic mode hard stop then by manually-operated decision.
The effect that the present invention is useful is: the present invention has then overcome the deficiency of said method, is that machine vision technique is at a kind of novel method through volume defect detection field.
Description of drawings
Fig. 1 is through compiling the defect detection system schematic;
Fig. 2 industrial control host modular structure synoptic diagram;
Fig. 3 software program core algorithm process flow diagram;
Fig. 4 is the overall flow synoptic diagram.
Embodiment
Below in conjunction with accompanying drawing the present invention is described further:
As shown in the figure; This grey cloth fault on-line detecting system based on machine vision; Comprise beam device 1-3, lighting device 1-2 and industrial camera 1-6, industrial control host 2-2, show control screen 1-1 and warning indicating module; Beam device 1-3 be installed in grey cloth 1-7 to be detected that tricot machine just accomplished directly over or oblique upper, beam device 1-3 is used for fixing lighting device 1-2 and fixing round steel pipe 1-5, is fixedly connected with one group of industrial camera 1-6 on the round steel pipe 1-5; Said apparent control screen 1-1 links to each other with industrial control host 1-2, when state is set, through showing the parameters that the control screen is provided with system, when running status, can observe the zone of fault form and generation fault; Said warning indicating module comprises alarm lamp and LED information indication panel; Alarm lamp can the form with sound and light signal be warned operating personnel when fault takes place, and whether normally LED information indication panel indication machine detects the regional location of operation or fault generation.The outside of beam device 1-3, lighting device 1-2 and industrial camera 1-6 be equipped be used to prevent dust, the rectangular parallelepiped shell of the shielding of electrostatic prevention; Beam device 1-3 adopts the square steel of hollow; Square steel inside is used to walk cable, and its data line is imbedded the crossbeam of hollow to keep the succinct of equipment.Said industrial control host 2-2 comprises system power supply 2-1, industrial control mainboard 2-3 and IO input and output control panel 2-6, and said system power supply 2-1 adopts the electric supply installation of Switching Power Supply as industrial control mainboard 2-3, industrial camera 2-8 and IO input and output control panel 2-6; Said industrial control mainboard 2-3 carries out software trigger or pulse producer with control panel 2-5 and triggers and make industrial camera 2-8 images acquired through triggering, industrial camera 2-8 through USB, 1394 or the transmission mode of GigE kilomega network upload the image of triggering collection to industrial control host 2-2.Embed fault recognition image Processing Algorithm in the said industrial control host, identify going out the cloth place whether fault takes place in the current weaving process of tricot machine, utilize recognition result to confirm that whether tricot machine shut down because of fault through image processing algorithm; Said tricot machine control panel can be controlled tricot machine and shut down when fault takes place, and when tricot machine starts, sends tricot machine starting state signal to industrial control host, to support launching once more of decision algorithm; Said touch shows the control screen and links to each other with industrial control host, when state is set, controls the parameters that screen is provided with system through showing, the zone that when running status, can observe the fault form and fault takes place; Said warning indicating module comprises alarm lamp and LED information indication panel; Alarm lamp can the form with sound and light signal be warned operating personnel when fault takes place, and whether normally LED information indication panel indication machine detects the regional location of operation or fault generation.
System equipment along through compiling grey cloth travel direction crossbearer above grey cloth that tricot machine has just been accomplished or oblique upper; Crossbeam is vertical with grey cloth direction of motion; As the installation carrier of lighting device and industrial camera, lighting device and industrial camera are installed in corresponding zone.Said lighting device 1-2 is common fluorescent light or the direct supply that drives through direct supply; Be the tubulose luminophor; The tubulose luminophor has lap in the field of illumination of grey cloth to be detected, and all tubulose luminophors cover whole district to be detected in the field of illumination that grey cloth to be detected is spliced to form, and is used to provide comparatively constant, even, the sufficient lighting source in zone to be detected; The width that this light source is weaved cotton cloth according to different tricot machine and difference, the quantity of setting is also different.The brightness that needs the adjacent lighting source of assurance to engage the district to be detected image that is illuminated that forms has consistance, and guarantees that the chiaroscuro effect of the image that industrial camera is gathered is even.
Simultaneously; Said industrial camera 1-6 adopts the high precision industrial camera, and the image of camera sensor is to be not less than 1,300,000 pixels above area array CCD or CMOS, the size of ccd sensor target surface in the choose reasonable camera; The imaging precision of camera lens and the visual angle of camera lens; The height and position of adjustment beam device 1-3 is set the reasonable object distance of industrial camera 1-6, the suitable imaging area that the assurance system is required, and the precision of desired image was a starting point when selection of this area was discerned with fault; The Width that on the camera length direction is grey cloth guarantees the precision of images; Be direction that grey cloth weaving the is walked about length that institute can definitely discern when guaranteeing that fault occurs on the camera Width, generally value is at 5cm, and district to be detected is the target of the industrial camera 1-6 of this system IMAQ among Fig. 1.
After fixing crossbeam and carrying out camera adjustments, link to each other the start and stop relay of the IO input and output control panel of industrial control host and tricot machine governor circuit, the control of tricot machine is reached the detection to the tricot machine running status to guarantee detection system through cable.
When system gets into running status; Program is carried out initialization; Comprise and read in reading in automatically of CONFIG.SYS and opening up of image memory space; Under the driving of the soft triggering of trigger action or the free acquisition software of software, the image that each industrial camera is gathered will be imported into the correspondence memory space of being opened up.Then whether program is in operation to tricot machine and once judges; As for otherwise quit a program; As for being then after the time-delay that was generally second 4 seconds through n is waited for, to begin images acquired; The grey cloth face image that collects is transferred to industrial control host, is handled by the fault recognition image Processing Algorithm that embeds in the industrial control host, and algorithm makes the fault of image strengthen and the background texture obfuscation to the figure image intensifying process that the image that collects carries out greyscale transformation, mean filter; Adopt the Niblack method to carry out the local threshold binary conversion treatment to image through pre-treatment.According to the image of binary conversion treatment, the disposal route of utilizing advanced form to learn is removed the noise particulate in the image, and whether sreen analysis utilizes the eigenwert leash law to detect fault and exist through particle remaining in the image is screened.For existing, then representing has the fault existence like testing result, and this moment, industrial control mainboard 2-3 need send instruction and the shutdown of control tricot machine to IO input and output control panel 2-6, and this process shows that taking turns detection finishes.After the operator carries out the fault reparation, when not quitting a program, detect and get into the foregoing description flow process again in system.For not existing, then carry out new IMAQ and judgement like testing result again.
System disposition has the control of showing operating terminal; The user can the zone of fault occur and parameter is set in operating terminal observation when running status; Like sensitivity adjusting; Number of times etc. is confirmed in warning/shutdown, and shuts down and confirm that being provided with of number of times and shutdown sensitivity coefficient can guarantee being not less than report to the police affirmation number of times and warning sensitivity coefficient automatically.Method to set up needs password to operate for selecting the keeper district in the interface control hurdle.Simultaneously for preventing when employee cleaning, the maintenance system etc. to occur the mistakenly stop machine; The terminal is equipped with automatic, manual switchover button, when manual state, if there is fault to be detected; The alarm lamp of system can have been found fault with the form caution operating personnel of sound and light signal but not shut down; And when auto state, system not only provides sound and light alarm, also can automatically stop the operation of fine works machine in real time.When fine works machine and native system time-out, industrial control host can be caught the enabling signal of tricot machine, and after predetermined time-delay, native system can restart according to the signal that industrial control host captures once more.
Except that the foregoing description, the present invention can also have other embodiments.All employings are equal to the technical scheme of replacement or equivalent transformation formation, all drop on the protection domain of requirement of the present invention.
Claims (9)
1. grey cloth fault on-line detecting system based on machine vision; It is characterized in that: comprise beam device (1-3), lighting device (1-2) and industrial camera (1-6), industrial control host (2-2), show control screen (1-1) and warning indicating module; Beam device (1-3) be installed in grey cloth to be detected (1-7) that tricot machine just accomplished directly over or oblique upper; Beam device (1-3) is used for fixing lighting device (1-2) and fixing round steel pipe (1-5), is fixedly connected with one group of industrial camera (1-6) on the round steel pipe (1-5); Said apparent control screen (1-1) links to each other with industrial control host (1-2), when state is set, through showing the parameters that the control screen is provided with system, when running status, can observe the zone of fault form and generation fault; Said warning indicating module comprises alarm lamp and LED information indication panel; Alarm lamp can the form with sound and light signal be warned operating personnel when fault takes place, and whether normally LED information indication panel indication machine detects the regional location of operation or fault generation.
2. the grey cloth fault on-line detecting system based on machine vision according to claim 1; It is characterized in that: the outside of beam device (1-3), lighting device (1-2) and industrial camera (1-6) be equipped be used to prevent dust, the rectangular parallelepiped shell of the shielding of electrostatic prevention; Beam device (1-3) adopts the square steel of hollow, and square steel inside is used to walk cable.
3. the grey cloth fault on-line detecting system based on machine vision according to claim 1 is characterized in that: said industrial camera (1-6) adopts the high precision industrial camera, and the image of camera sensor is to be not less than 1,300,000 pixels above area array CCD or CMOS.
4. the grey cloth fault on-line detecting system based on machine vision according to claim 1; It is characterized in that: said lighting device (1-2) is made up of one group of linear linearly aligned luminophor; Adjacent tubulose luminophor has lap in the field of illumination of grey cloth to be detected, and all tubulose luminophors cover whole district to be detected in the field of illumination that grey cloth to be detected is spliced to form.
5. the grey cloth fault on-line detecting system based on machine vision according to claim 1; It is characterized in that: said industrial control host (2-2) comprises system power supply (2-1), industrial control mainboard (2-3) and IO input and output control panel (2-6), and said system power supply (2-1) adopts the electric supply installation of Switching Power Supply as industrial control mainboard (2-3), industrial camera (2-8) and IO input and output control panel (2-6); Said industrial control mainboard (2-3) is carried out software trigger or pulse producer with control panel (2-5) and is triggered and make industrial camera (2-8) images acquired through triggering, industrial camera (2-8) through USB, 1394 or the transmission mode of GigE kilomega network upload the image of triggering collection to industrial control host (2-2).
6. implementation method based on the grey cloth fault on-line detecting system of machine vision; It is characterized in that: may further comprise the steps: industrial control mainboard (2-3) is handled the image of gathering through fault recognition image Processing Algorithm; When showing the discovery fault in the result; Industrial control host (2-2) is to IO input and output control panel (2-6) transmitting order to lower levels, and IO input and output control panel (2-6) is shut down according to command driven actuating of relay control tricot machine (2-7); When tricot machine (2-7) is in time-out warping state; IO input and output control panel (2-6) continuous capturing tricot machine (2-7) running status is also uploaded tricot machine (2-7) duty to industrial control mainboard (2-3) in real time; After the operator handles fault well; When tricot machine restarted, industrial control mainboard (2-3) was delayed time according to machine state and is restarted fault recognition image Processing Algorithm.
7. the implementation method of the grey cloth fault on-line detecting system based on machine vision according to claim 6; It is characterized in that: the detection step of said industrial control mainboard (2-3) is following: after machine is opened; The program random start; Program after the startup is carried out initialization earlier, comprises reading in automatically of CONFIG.SYS and opening up of image memory space; After initialization is accomplished; Industrial control mainboard (2-3) detects tricot machine through IO input and output control panel (2-6) and whether is in running status, if tricot machine is in running status, then program gets into the time-delay wait; When delay time reaches n during second, fault recognition image Processing Algorithm starts; Flame Image Process and analysis module take out view data in each memory headroom, the original image of collection makes the fault of image strengthen and the background texture obfuscation through the figure image intensifying process of greyscale transformation, mean filter; Adopt the Niblack method to carry out the local threshold binary conversion treatment to image through pre-treatment; According to the image of binary conversion treatment, the disposal route of utilizing advanced form to learn is removed the noise particulate in the image, and whether sreen analysis utilizes the eigenwert leash law to detect fault and exist through particle remaining in the image is screened; For existing, then representing has the fault existence like testing result, and industrial control mainboard this moment (2-3) need be sent instruction and the shutdown of control tricot machine to IO input and output control panel (2-6), and this process shows that taking turns detection finishes; After the operator carries out the fault reparation, when not quitting a program, detect and get into the foregoing description flow process again in system; For not existing, then carry out new IMAQ and judgement like testing result again.
8. the implementation method of the grey cloth fault on-line detecting system based on machine vision according to claim 7 is characterized in that: equalization is handled and is adopted [0,255] interval broadening; Filtering Processing adopts the effect nuclear matrix of 3x3 or 5x5; Adopt the NiBlack algorithm during analysis of threshold, its effect nuclear should adopt the big minor matrix of 16x8, and deviation factors is set to 0.6; When choosing Background Correction and carrying out analysis of threshold, the nuclear matrix parameter is provided with Niblack; Advanced form is learned and is handled the corrosion operation that the anistree data matrix of checking Hexa that adopts 3x3 carries out 8 connections; Morphology is handled and is adopted conventional open and close computing and expansion, corrosion to operate, and examines the matrix into 3x3, and the mode of action does
Sreen analysis adopts the characteristic of fault height, angle and length ratio as basis for estimation, when the doubtful fault after the algorithm process satisfies the parameter setting of sreen analysis, then carries out fault identification and record.
9. the implementation method of the grey cloth fault on-line detecting system based on machine vision according to claim 6; It is characterized in that: in program, set warning/shutdown sensitivity, promptly confirm the number of times adjusting, and the functionality buttons of manual switching; Can set manual mode or automatic mode; Only report to the police when detecting fault during manual mode and do not shut down, can whether shut down, at the next generation above-mentioned condition of automatic mode hard stop then by manually-operated decision.
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