CN106379784A - Visual detection method and system for mine reinforcing steel bar inhaul cable - Google Patents
Visual detection method and system for mine reinforcing steel bar inhaul cable Download PDFInfo
- Publication number
- CN106379784A CN106379784A CN201610960252.8A CN201610960252A CN106379784A CN 106379784 A CN106379784 A CN 106379784A CN 201610960252 A CN201610960252 A CN 201610960252A CN 106379784 A CN106379784 A CN 106379784A
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- Prior art keywords
- reinforcing bar
- zip
- mine
- image
- defect
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/0006—Monitoring devices or performance analysers
- B66B5/0037—Performance analysers
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B19/00—Mining-hoist operation
- B66B19/06—Applications of signalling devices
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/0087—Devices facilitating maintenance, repair or inspection tasks
-
- 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
- G01N21/89—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles
- G01N21/8914—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles characterised by the material examined
-
- 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
- G01N21/89—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles
- G01N21/8914—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles characterised by the material examined
- G01N2021/8918—Metal
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- Engineering & Computer Science (AREA)
- Textile Engineering (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
The invention relates to a visual detection method and system for a mine reinforcing steel bar inhaul cable. The visual detection system for the mine reinforcing steel bar inhaul cable comprises a cleaning system, an image information collection system, an intelligent judgment and analysis system and a safety control system. The cleaning system comprises a high-pressure water gun, a cleaning agent sprayer and an air blower for drying. The image information collection system comprises a CCD line-scan digital camera, a rotary encoder, an LED constant light source and an image collection card. The light source way is direct dark field front illumination, and details of the inhaul cable can be highlighted. The intelligent judgment and analysis system comprises an opencv defect detection module and an MYSQL database. In order to solve the problems that manual detection for the reinforcing steel bar inhaul cable is poor in safety, low in precision and the like, detection for the mine reinforcing stele bar inhaul cable is made automatic and visual by means of the image collection and processing technology, and safety coefficients of production and management inside a mine can be improved.
Description
Technical field
The present invention relates to mine zip detection field, particularly to a kind of mine reinforcing bar drag-line visible detection method, system.
Background technology
In the mine manned iron cage course of work, due to the working time can cause long very much reinforcing bar zip aging, rust turbid, tired
The defects such as labor fracture of wire, stripped thread.Therefore, it is necessary to the reinforcing bar zip damage status of traction that iron cage manned in mine is moved up and down are carried out
Detection and early warning, so could improve the safety coefficient of production management in mine, ensure worker's life security.At present, still do not have
The system carrying out real-time detection to mine iron cage reinforcing bar zip is used for putting into practice, and is all by artificial naked eyes routine observation, safety is
Number is very low.Should ensure that miner's life security considers, this functional requirement to zip defect real-time monitoring becomes abnormal urgent.
Content of the invention
The present invention is intended to provide a kind of mine reinforcing bar drag-line visible detection method, system, to solve manual detection zip mill
The deficiency damaged, realizes real-time, the accurate detection to reinforcing bar zip, and can make early warning to the degree difference of abrasion.
Technical scheme is as follows：
A kind of mine reinforcing bar drag-line visible detection method, it has following steps：
S1, reinforcing bar zip to be detected is carried out, removes surface smut；
S2, completed based on artificial intelligence data processing algorithm reinforcing bar drag-line surface defects characteristic extract and masterplate training, build intelligence
Can grader and defect characteristic database；
S3, by the camera that is distributed around reinforcing bar zip to be detected come the image of Real-time Collection standard reinforcing bar zip, and by reinforcing bar
The image of zip passes to and carries out Image semantic classification on computer；
S4, by by process after image and defect characteristic database in template image compare, to realize defect characteristic
Identification；
If S5 is identified as existing defects feature, send a signal to controller, control zip to quit work by controller, and in advance
Alert prompting user；If being identified as not existing defects feature, continue executing with S3；
S6, according to comparison result generate defect data analysis form.
A kind of mine reinforcing bar drag-line vision detection system, its include purging system reinforcing bar zip being carried out,
The image information collecting system of collection reinforcing bar drag-line surface image and judge that reinforcing bar zip is sentenced with the presence or absence of the intelligence of defect characteristic
Disconnected analysis system.
Wherein, purging system has the cleaning agent spraying cleaning agent to the hydraulic giant of reinforcing bar zip water spray and/or to reinforcing bar zip
Sprayer, purging system is additionally provided with the dryer that the reinforcing bar zip after cleaning can be dried.
Image information collecting system include rotary encoder and around reinforcing bar zip to be detected distribution light source and camera；
Image information collecting system controls the acquisition rate of camera according to the zip movement rate that rotary encoder detects.
Intelligent decision analysis system includes defects detection module and defect characteristic database；Defects detection module receives figure
As the reinforcing bar zip image information of information acquisition system collection, and by this reinforcing bar zip image information and defect characteristic database
Template image compare, draw surveyed reinforcing bar zip whether there is defect characteristic analysis result.
As more excellent scheme, the present invention is additionally provided with safety control system, and safety control system includes controller, controller
Be connected with intelligent decision analysis system signal to receive analysis result, controller be connected with the driving mechanisms control of reinforcing bar zip with
Control the action start-stop of reinforcing bar zip；Controller is receiving the reinforcing bar zip existing defects being sent by intelligent decision analysis system
The drive mechanism automatically controlling reinforcing bar zip after the analysis result of feature quits work.
The invention has the beneficial effects as follows：The present invention is directed to the current peace relying on manual detection mine reinforcing bar zip mode to exist
The problems such as property is poor, accuracy is low, testing result lacks persuasion entirely, is taken through Machine Vision Inspecting System detection process is complete
Portion's real time implementation, the mode of automation, have accomplished real-time detection, automatic early-warning, and each defect problem is generated defect document, side
Just post analysis, the defect situation of inquiry zip, greatly improve the life security of workman.
Brief description
The invention will be further described below in conjunction with the accompanying drawings.
Fig. 1 is the structural representation of purging system；
Fig. 2 is the fundamental diagram of line-scan digital camera；
Fig. 3 is the structured flowchart of the system；
Fig. 4 is the workflow diagram of the system；
In figure, 1 reinforcing bar zip, 2 hydraulic giants, 3 cleaning agent sprayers, 4 dryers, 5 cameras, 6 light sources.
Specific embodiment
With reference to specific embodiment, the present invention is further described.
The step that accompanying drawing 4 shows mine reinforcing bar drag-line visible detection method：
S1, first with hydraulic giant and/or cleaning agent, the dirt on reinforcing bar zip surface is carried out, then steel is removed by dryer
The moisture on muscle zip surface；
S2, the defects such as reinforcing bar drag-line surface corrosion, fatigue breaking, stripped thread and fracture are completed based on artificial intelligence data processing algorithm
Feature extraction and masterplate training, build Intelligence Classifier and defect characteristic database；
S3, by around reinforcing bar zip to be detected distribution two high definitions, at a high speed, horizontal scanning line battle array industrial camera is from zip both sides
Carry out the image of Real-time Collection standard reinforcing bar zip, and using image pick-up card, the image of reinforcing bar zip is passed to and carry out on computer
Image semantic classification；
S4, by by process after image and defect characteristic database in template image compare, to realize defect characteristic
Identification；
If S5 is identified as existing defects feature, send a signal to PLC control system, control zip to stop by PLC control system
Work, and user is reminded in early warning；Otherwise continue executing with S3；
S6, current defect image and its defect characteristic are generated defect data analysis form, manually check for the later stage.
Accompanying drawing 3 shows mine reinforcing bar drag-line vision detection system, and it includes purging system, image information collecting system
System, intelligent decision analysis system and safety control system；Purging system can be carried out to reinforcing bar, and it has as shown in fig. 1
To reinforcing bar zip water spray hydraulic giant and to reinforcing bar zip spray cleaning agent cleaning agent sprayer and to cleaning after reinforcing bar draw
Lock the air blast dried；Image information collecting system includes rotary encoder, image pick-up card and around steel to be detected
Two groups of LED constant light source of muscle zip distribution（Directly details in a play not acted out on stage, but told through dialogues frontlighting, can project the details of zip）, two CCD linear arrays
Camera, image information collecting system controls the acquisition rate of camera according to the zip movement rate that rotary encoder detects；
Intelligent decision analysis system includes opencv defects detection module and MYSQL defect characteristic database；Defects detection module connects
Receive the reinforcing bar zip image information of image information collecting system collection, and by this reinforcing bar zip image information and defect characteristic data
Template image in storehouse is compared, and show that surveyed reinforcing bar zip whether there is the analysis result of defect；Safety control system bag
Include PLC control system, PLC control system is connected to receive analysis result with intelligent decision analysis system signal, and PLC controls
System is connected with the driving mechanisms control of reinforcing bar zip to control the action start-stop of reinforcing bar zip；PLC control system is receiving
Reinforcing bar zip is automatically controlled after the analysis result of the reinforcing bar zip existing defects being sent by defect characteristic intelligent decision analysis system
Drive mechanism quit work.
This system is carried out to reinforcing bar zip by hydraulic giant and cleaning agent sprayer, and by air blast to zip surface
Dried；Its by two cameras from reinforcing bar zip both sides shooting image, and by rotary encoder control acquisition rate, then
Reinforcing bar Damages in Stay Cables situation in mine is analyzed by intelligent decision analysis system, if defect reaches early warning situation, is signaled to
PLC control system stops the work of mine zip, and generates defect database, facilitates subsequent query.
Claims (7)
1. a kind of mine reinforcing bar drag-line visible detection method, is characterized in that thering is following steps：
S1, reinforcing bar zip to be detected is carried out, removes surface smut；
S2, completed based on artificial intelligence data processing algorithm reinforcing bar drag-line surface defects characteristic extract and masterplate training, build intelligence
Can grader and defect characteristic database；
S3, by the camera that is distributed around reinforcing bar zip to be detected come the image of Real-time Collection standard reinforcing bar zip, and by reinforcing bar
The image of zip passes to and carries out Image semantic classification on computer；
S4, by by process after image and defect characteristic database in template image compare, to realize defect characteristic
Identification；
If S5 is identified as existing defects feature, send a signal to controller, control zip to quit work by controller, and in advance
Alert prompting user；If being identified as not existing defects feature, continue executing with S3；
S6, according to comparison result generate defect data analysis form.
2. mine reinforcing bar drag-line visible detection method according to claim 1, is characterised by：In S1, first with hydraulic giant and/or
Cleaning agent is carried out to the dirt on reinforcing bar zip surface, then removes the moisture on reinforcing bar zip surface by dryer.
3. mine reinforcing bar drag-line visible detection method according to claim 1, is characterized in that：In S2, described reinforcing bar draws
Rope surface defects characteristic includes corrosion, fatigue breaking, stripped thread and fracture.
4. mine reinforcing bar drag-line visible detection method according to claim 1, is characterized in that：In S6, by current defect figure
Picture and its defect characteristic generate defect data analysis form, manually check for the later stage.
5. a kind of mine reinforcing bar drag-line vision detection system, is characterized in that：Include image information collecting system and intelligent decision
Analysis system, described image information acquisition system include rotary encoder and around reinforcing bar zip to be detected distribution light source,
Camera, described image information acquisition system controls the collection speed of camera according to the zip movement rate that rotary encoder detects
Rate；Described intelligent decision analysis system includes defects detection module and defect characteristic database；Described defects detection module connects
Receive the reinforcing bar zip image information of image information collecting system collection, and by this reinforcing bar zip image information and defect characteristic data
Template image in storehouse is compared, and show that surveyed reinforcing bar zip whether there is the analysis result of defect.
6. mine reinforcing bar drag-line vision detection system according to claim 5, is characterized in that：It is additionally provided with safety control system,
Described safety control system includes controller, and described controller is connected with intelligent decision analysis system signal to receive analysis knot
Really, described controller is connected with the driving mechanisms control of reinforcing bar zip to control the action start-stop of reinforcing bar zip；Described controller
Automatically control after the analysis result receiving the reinforcing bar zip existing defects being sent by defect characteristic intelligent decision analysis system
The drive mechanism of reinforcing bar zip quits work.
7. mine reinforcing bar drag-line vision detection system according to claim 1, is characterized in that：It is additionally provided with and reinforcing bar can be carried out clearly
The purging system washed, described purging system has to the hydraulic giant of reinforcing bar zip water spray and/or sprays the clear of cleaning agent to reinforcing bar zip
Lotion sprayer, described purging system is additionally provided with the dryer that the reinforcing bar zip after cleaning can be dried.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610960252.8A CN106379784A (en) | 2016-10-28 | 2016-10-28 | Visual detection method and system for mine reinforcing steel bar inhaul cable |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610960252.8A CN106379784A (en) | 2016-10-28 | 2016-10-28 | Visual detection method and system for mine reinforcing steel bar inhaul cable |
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| Publication Number | Publication Date |
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| CN106379784A true CN106379784A (en) | 2017-02-08 |
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| CN201610960252.8A Pending CN106379784A (en) | 2016-10-28 | 2016-10-28 | Visual detection method and system for mine reinforcing steel bar inhaul cable |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107941803A (en) * | 2017-11-15 | 2018-04-20 | 广西大学 | A kind of measurement device and analysis method of reinforcing bar full angle corrosion character parameter |
| CN108760739A (en) * | 2018-05-30 | 2018-11-06 | 天仁民防建筑工程设计有限公司 | A kind of closed guard gate's corrosion state detecting system and method |
| CN108821047A (en) * | 2018-06-22 | 2018-11-16 | 潘丽娜 | A kind of detection system of mine elevator drag-line |
| CN111339220A (en) * | 2020-05-21 | 2020-06-26 | 深圳新视智科技术有限公司 | Defect mapping method |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107941803A (en) * | 2017-11-15 | 2018-04-20 | 广西大学 | A kind of measurement device and analysis method of reinforcing bar full angle corrosion character parameter |
| CN108760739A (en) * | 2018-05-30 | 2018-11-06 | 天仁民防建筑工程设计有限公司 | A kind of closed guard gate's corrosion state detecting system and method |
| CN108821047A (en) * | 2018-06-22 | 2018-11-16 | 潘丽娜 | A kind of detection system of mine elevator drag-line |
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| CN111339220B (en) * | 2020-05-21 | 2020-08-28 | 深圳新视智科技术有限公司 | Defect mapping method |
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Application publication date: 20170208 |