CN106934796B - The high-speed belt conveyor rock slag video analytic system and method that rock tunnel(ling) machine carries - Google Patents
The high-speed belt conveyor rock slag video analytic system and method that rock tunnel(ling) machine carries Download PDFInfo
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30164—Workpiece; Machine component
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Abstract
The high-speed belt conveyor rock slag video analytic system and method carried the invention discloses a kind of rock tunnel(ling) machine, system includes analysis module and the video camera that is set to above belt feeder, the image of rock slag on the cameras capture belt feeder, and it is transferred to analysis module, the analysis module extracts each of these frame, it is converted into grayscale image, and grayscale image is converted into binary map, the morphologic expanding processing of application image, regional connectivity excessively broken in bianry image is got up, determine that each independent communication region is rock slag, oriented bounding box is calculated according to independent communication region, determine rock slag shape.The shape Statistics data for providing rock slag that the present invention can quantify, allow rock tunnel(ling) machine driver to grasp high-speed belt conveyor rock slag situation data in real time.
Description
Technical field
The high-speed belt conveyor rock slag video analytic system and method carried the present invention relates to a kind of rock tunnel(ling) machine.
Background technique
Into after 21 century, the great base such as large quantities of hydraulic and hydroelectric engineerings, Rail Highway traffic engineering, municipal subway engineering
Plinth engineering puts on construction schedule successively, has greatly facilitated the development of the underground engineerings such as tunnel, wherein in terms of municipal pipeline, I
State will build underground pipe gallery as one of 100 large projects of country in " 13 " are planned, our times various countries are increasingly heavy
Depending on the development and utilization of the underground space.Exploitation for the underground space, because rock tunnel(ling) machine construction is fast, quality with speed, takes
It the advantages that with low, construction safety, has generallyd use in the world.However, in rock tunnel(ling) machine work progress, the case where tool wear
Seriously, the expense of cutter changing accounts for operating expenses one third.Too early tool changing will cause money in rock tunnel(ling) machine work progress
Source waste, too late tool changing will lead to cutter eccentric wear or fall off, and the duration is caused to postpone, serious it also occur that accident.How in real time
Detection tool wear situation simultaneously replaces cutter in time, is related to rock tunnel(ling) machine construction efficiency and rock tunnel(ling) machine tunneled
Urgent problem to be solved in journey.
Method currently used for rock tunnel(ling) machine tool wear monitoring mainly has oil pressure detection, peculiar smell detection, boring parameter
Analyze and open a position inspection etc..Wherein, oil pressure detection method is limited by oil circuit quantity, since oil circuit is limited, can only be installed on one
Divide on cutter, the abrasion condition of all cutters cannot be detected, can not also learn the specific abrasion loss of cutter.Peculiar smell detection can be sensitive
Tool wear information is reported on ground, but this method is invalid to shield machine, is only applicable to TBM.Boring parameter analysis method was predicted
Journey is cumbersome, and practical application is difficult, and the accuracy of prediction need to be investigated.It opens a position and checks that working efficiency is low, and danger coefficient is high,
It is likely to result in excavation face collapsing, the serious injures and deaths that will cause personnel.So the real-time hobboing cutter during tunneler construction is ground
Damage detection is a big technological difficulties of rock tunnel(ling) machine and major scientific research institution and manufacturer fall over each other one of project of research.
Under the present art, the detection of rock tunnel(ling) machine hob abrasion still has following problem：(1) since hobboing cutter is direct
It with rock face, causes directly observe hobboing cutter, existing detection mode needs to carry out cutterhead or hobboing cutter more
Transformation on mechanically and structurally, difficulty in engineering realization is big, and higher cost；(2) prior art mostly can only qualitatively detect cutter
Abrasion condition, provides whether cutter has worn out, but is difficult to learn the specific abrasion loss of hobboing cutter；(3) in order to reach quantitative detection
Purpose, some new technologies use more complex method, and some need wireless transport module causes the complexity of entire detection system
Degree is high, difficult in maintenance.For the above problem, studies and propose a kind of high-speed belt conveyor rock slag video that rock tunnel(ling) machine carries
Analysis system, to realize that the Real_time quantitative detection of hob abrasion degree in rock tunnel(ling) machine work progress provides a feasible way
Diameter.
Summary of the invention
The present invention to solve the above-mentioned problems, proposes a kind of high-speed belt conveyor rock slag video point that rock tunnel(ling) machine carries
Analysis system and method, the present invention realize the Real_time quantitative detection to hob abrasion degree in rock tunnel(ling) machine work progress.
To achieve the goals above, the present invention adopts the following technical scheme that：
The high-speed belt conveyor rock slag video analytic system that a kind of rock tunnel(ling) machine carries, including analysis module and it is set to skin
With the video camera above machine, the image of rock slag on the cameras capture belt feeder, and it is transferred to analysis module, the analysis mould
Block extracts each of these frame, is converted into grayscale image, and grayscale image is converted to binary map, application image is morphologic swollen
Swollen processing method determines that each independent communication region is rock slag, root so that regional connectivity excessively broken in bianry image is got up
Oriented bounding box is calculated according to independent communication region, determines rock slag shape.
Preferably, protection mechanism is provided with outside the video camera.High-speed camera sensitive electron and optical device are carried out
Water proof and dust proof protection, has Tunnel wall to drip to solve rock tunnel(ling) machine construction environment often, and dust of constructing falls rock slag.It is described
Protection mechanism preferably protects shell, and hull outside is provided with waterproof coating.
The protection mechanism front end is provided with circle dust-proof guard outstanding, to block the drop from hole wall and belt feeder
The interference to camera lens such as water, dust.The video camera benefit is fixed by bolts in the metallic walls above high-speed belt conveyor,
Meanwhile protective device also entirely covers camera body, to protect the precise electronic component damage in video camera.
Certainly, the protection mechanism also can be replaced other forms, such as adds erosion shield, is provided with dust cover,
These simple replacements belong to those skilled in the art on concept of the invention it is conceivable that simple replacement, should belong to
Protection scope of the present invention.
It preferably, further include lighting device.To overcome tunnel to completely enclose, without natural lighting, the darker item of illumination condition
Part.LED light device is placed in individual protective device, with water proof and dust proof.
Working method based on above system, includes the following steps：
(1) for collected rock slag video, each of these frame is extracted, color image is converted into grayscale image, will
To grayscale image be converted to binary map；
(2) to obtained bianry image, the morphologic expanding processing of application image, with being crushed in bianry image
Regional connectivity gets up, and making the corresponding image-region of same rock slag is connection, and image-region corresponding to different rock slags is not connect
Logical；
(3) image connectivity Region detection algorithms are used, determine independent communication region all in bianry image, each connection
Region is rock slag, and is ranked up by the pixel number that each region is included；
(4) to obtained each connected region, oriented bounding box is calculated, to reflect the shape information of rock slag, and records system
Meter.
In the step (1), color image, the specific method for being converted to grayscale image is：
Gray=R × 0.299+G × 0.587+B × 0.114, (1)
In formula, R, G, B are respectively three kinds of color values of red, green, blue of some pixel of color image, and Gray is the ash being converted into
Angle value.
In the step (1), otherwise it is 0 that the binary map respective pixel value that grayscale image is greater than threshold value, which is 1,.
In the step (3), how much the pixel number that each independent communication region is included represents rock slag shooting size.
In the step (4), oriented bounding box is a two-dimensional rectangle, the most narrow place of the corresponding object of its width, its length
The widest part of corresponding object, the ratio of the widest part and most narrow place, to reflect the shape information of rock slag.Common, ratio is greater than
1.5, then rock slag is elongated strip；Ratio is close to 1, then rock slag is round block shape.
In the step (4), by rock slag shape to judge whether hobboing cutter is working properly.If rock slag is mostly elongated strip,
Then hobboing cutter is working properly, and abrasion is smaller, if rock slag is mostly at round block shape, hobboing cutter is not worked normally, and has abrasion condition.
In the step (4), the diameter and rock slag diameter histogram of maximum rock slag are counted, from 0 to maximum rock slag diameter
Length range be divided into multiple sections, statistic diameters falls in the rock slag number in each section, to shooting area be greater than some set
The rock slag of threshold value is divided into two classes, elongated strip and round block shape, and draws histogram.
Compared with prior art, beneficial effects of the present invention are：
High-speed belt conveyor rock slag video analysis method proposed by the present invention suitable under rock tunnel(ling) machine environment, realizes
The automated analysis of rock slag video, and the shape Statistics data for providing rock slag that can be quantitative, make rock tunnel(ling) machine driver can
To grasp high-speed belt conveyor rock slag situation data in real time.
The high-speed belt conveyor rock slag video analytic system that rock tunnel(ling) machine proposed by the present invention carries, effective solution are existing
There is the design of hob abrasion detection device to realize deficiency that is complicated and being difficult to quantitative detection hob abrasion situation.By to high-speed belt
The analysis of machine rock slag shape counts, and provides the degree of wear estimation of hobboing cutter, overcomes the difficult point of the prior art, and simple and convenient.
Detailed description of the invention
The accompanying drawings constituting a part of this application is used to provide further understanding of the present application, and the application's shows
Meaning property embodiment and its explanation are not constituted an undue limitation on the present application for explaining the application.
Fig. 1 is schematic diagram side view of the invention.
Fig. 2 is schematic diagram top view of the invention.
Fig. 3 design flow diagram of the present invention.
Wherein：1,8 high-speed camera is indicated, 2 indicate LED light device, and 3 indicate high-speed belt conveyor, and 4,6 indicate high speed skin
Band, 5,7 indicate rock slag.
Specific embodiment：
The invention will be further described with embodiment with reference to the accompanying drawing.
It is noted that following detailed description is all illustrative, it is intended to provide further instruction to the application.Unless another
It indicates, all technical and scientific terms used herein has usual with the application person of an ordinary skill in the technical field
The identical meanings of understanding.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root
According to the illustrative embodiments of the application.As used herein, unless the context clearly indicates otherwise, otherwise singular
Also it is intended to include plural form, additionally, it should be understood that, when in the present specification using term "comprising" and/or " packet
Include " when, indicate existing characteristics, step, operation, device, component and/or their combination.
As shown in Figure 1, high-speed belt conveyor 3 operates and 4 one superhigh speed of belt is driven to transport in rock tunnel(ling) machine work progress
It is dynamic, rock slag 5 is transported to outside tunnel from cutterhead.High-speed camera 1 and its water proof and dust proof protective device are fixed using bolt
In the metallic walls above belt, the camera lens of video camera is towards belt centre.Further, due in tunnel illumination it is darker,
In order to taking the clear image of rock slag on belt feeder, needs to illuminate using LED light device 2 and be photographed on high-speed belt
Region.
As shown in Fig. 2, cutterhead cuts lower rock slag 7 constantly from face, and rock slag is with skin with the construction of rock tunnel(ling) machine
Operating with 6 is transported out tunnel.At the same time, start high-speed camera 8 and LED light device, to the rock slag on belt feeder
High-speed capture is carried out, the clear video of rock slag is obtained.
Further, the video that high-speed camera takes transfers back to the meter in rock tunnel(ling) machine driver's cabin by data line
On calculation machine.
Further, the computer vision analysis software developed of the operation present invention gets and is passed back by data line
Rock slag video data, and extract single-frame images therein and handled.Since the degree of wear of hobboing cutter in tunneling process will not
It mutates in a short time, so video analysis processing need not all be carried out to each frame image of high-speed camera.Only every
The computer vision analysis that first frame image carries out next step is individually extracted in the video that second obtains.
Further, in the computer vision analysis software that the present invention is developed, for the single frames rock slag figure extracted
Picture, operation cromogram turn gray scale nomography, are converted to gray level image.
Further, it for grayscale image obtained in previous step, runs grayscale image and turns two-value nomography, be converted to two-value
Image.
Further, it for bianry image obtained in previous step, runs the processing of computer picture morphological dilations and calculates
Method, the broken region that rock slag same in bianry image is divided into due to illumination, color, is connected to as a complete rock slag
Region.
Further, to the bianry image after Morphological scale-space, operation image connected region detection algorithm detects image
In each connected region be considered as a rock slag.
As shown in figure 3, specific step is as follows：
For collected rock slag video, each of these frame is extracted, single-frame images is handled for next step.By
The degree of wear of hobboing cutter will not occur to change greatly in a short time in tunneling process, it is not necessary to use excessively high image sampling frequency
Rate, one frame rock slag image of extraction per second are analyzed.
The color image that previous step is obtained using following formula, is converted to grayscale image：
Gray=R × 0.299+G × 0.587+B × 0.114, (1)
In formula, R, G, B are respectively three kinds of color values of red, green, blue of some pixel of color image, and Gray is the ash being converted into
Angle value.The formula is applied to each pixel of color image, corresponding grayscale image can be obtained.
Further, using following formula, the grayscale image that previous step is obtained is converted to binary map：
In formula, Gray is the value of some pixel of grayscale image, and Binary is the value of respective pixel in the binary map being converted into.By
In illumination and color change, same rock slag may be divided into multiple disconnected regions in binary map, need to make in next step
It is handled with morphological method.
For obtained bianry image, the morphologic expanding processing of application image, excessively broken in bianry image
Broken regional connectivity gets up, and making the corresponding image-region of same rock slag is connection, and image-region corresponding to different rock slags is
It is disconnected.
Further, using image connectivity Region detection algorithms, independent communication region all in bianry image is found out, often
A connected region is rock slag, and how much i.e. rock slag shooting size is ranked up the pixel number for being included by each region.
To each connected region obtained in previous step, oriented bounding box (Oriented bounding Box) is calculated.
Oriented bounding box is a two-dimensional rectangle, the most narrow place of the corresponding object of its width, the widest part of its long corresponding object.The widest part
The ratio at most narrow place, can reflect the shape information of rock slag：Ratio is greater than 1.5, then rock slag is elongated strip；Ratio close to
1, then rock slag is round block shape.
Count the shape information of rock slag.By construction experience it is found that hobboing cutter is working properly if rock slag is mostly elongated strip,
Abrasion is smaller, if rock slag is mostly at round block shape, hobboing cutter is not worked normally, and has abrasion condition.Accordingly, we count several letters
Breath：1. the diameter of maximum rock slag；2. rock slag diameter histogram.Count two analogous column diagram data：1, from 0 to maximum rock slag diameter
Length range be divided into 10 sections, statistic diameters falls in the rock slag number in each section；2, shooting area is set greater than some
The rock slag for determining threshold value is divided into two classes, elongated strip and round block shape, and draws histogram.
Further, the shape information of all rock slags in single-frame images is counted.If the widest part of a rock slag and most narrow place
Ratio close to 1, then the rock slag be round block shape, if ratio be greater than 1.5, the rock slag be elongated strip.
Further, two kinds of rock slag Information Statistics histograms are provided.The first be rock slag diameter 0 into the frame image most
Distribution histogram on big rock slag diameter section is for second the comparison histogram of round block shape Yu elongated strip rock slag number.It is logical
The broken situation that first histogram provides rock slag is crossed, two kinds of rock slag numbers comparison of second histogram can provide hobboing cutter
The degree of wear estimation.Elongated strip rock slag is more, then hobboing cutter is working properly, wears smaller；Circle massive rock slag is more, then hobboing cutter
The degree of wear is larger, needs replacing hobboing cutter.
The foregoing is merely preferred embodiment of the present application, are not intended to limit this application, for the skill of this field
For art personnel, various changes and changes are possible in this application.Within the spirit and principles of this application, made any to repair
Change, equivalent replacement, improvement etc., should be included within the scope of protection of this application.
Above-mentioned, although the foregoing specific embodiments of the present invention is described with reference to the accompanying drawings, not protects model to the present invention
The limitation enclosed, those skilled in the art should understand that, based on the technical solutions of the present invention, those skilled in the art are not
Need to make the creative labor the various modifications or changes that can be made still within protection scope of the present invention.
Claims (8)
1. the high-speed belt conveyor rock slag video analytic system that a kind of rock tunnel(ling) machine carries, it is characterized in that：Including analysis module and
Video camera, the lighting device being set to above belt feeder, the image of rock slag on the cameras capture belt feeder, and be transferred to point
Module is analysed, the analysis module extracts each of these frame, is converted into grayscale image, and grayscale image is converted to binary map,
The morphologic expanding processing of application image is determined each only so that regional connectivity excessively broken in bianry image is got up
Vertical connected region is rock slag, calculates oriented bounding box according to independent communication region, determines rock slag shape.
2. the high-speed belt conveyor rock slag video analytic system that a kind of rock tunnel(ling) machine as described in claim 1 carries, feature
It is：Protection mechanism is provided with outside the video camera.
3. the high-speed belt conveyor rock slag video analytic system that a kind of rock tunnel(ling) machine as claimed in claim 2 carries, feature
It is：The protection mechanism front end is provided with circle dust-proof guard outstanding.
4. based on the working method of system as claimed in any one of claims 1-3, it is characterized in that：Include the following steps：
(1) for collected rock slag video, each of these frame is extracted, color image is converted into grayscale image, by what is obtained
Grayscale image is converted to binary map；
(2) to obtained bianry image, the morphologic expanding processing of application image, the region being crushed in bianry image
Connection is got up, and making the corresponding image-region of same rock slag is connection, and image-region corresponding to different rock slags is disconnected；
(3) image connectivity Region detection algorithms are used, determine independent communication region all in bianry image, each connected region
As rock slag, and be ranked up by the pixel number that each region is included；
(4) to obtained each connected region, oriented bounding box is calculated, to reflect the shape information of rock slag, and records statistics；It is logical
Rock slag shape is crossed to judge whether hobboing cutter is working properly, if rock slag is mostly elongated strip, hobboing cutter is working properly, wears small；If
Rock slag is mostly at round block shape, then hobboing cutter does not work normally, and has abrasion condition；Count the diameter and rock slag diameter histogram of maximum rock slag
Figure, multiple sections are divided into from 0 to the length range of maximum rock slag diameter, statistic diameters falls in the rock slag number in each section,
The rock slag for being greater than some given threshold to shooting area is divided into two classes, elongated strip and round block shape, and draws histogram.
5. working method as claimed in claim 4, it is characterized in that：In the step (1), color image is converted to grayscale image
Specific method be：
Gray=R × 0.299+G × 0.587+B × 0.114, (1)
In formula, R, G, B are respectively three kinds of color values of red, green, blue of some pixel of color image, and Gray is the gray scale being converted into
Value.
6. working method as claimed in claim 4, it is characterized in that：In the step (1), grayscale image is greater than the binary map of threshold value
Respective pixel value is 1, is otherwise 0.
7. working method as claimed in claim 4, it is characterized in that：In the step (3), each independent communication region is included
Pixel number how much represent rock slag shooting size.
8. working method as claimed in claim 4, it is characterized in that：In the step (4), oriented bounding box is a Two-Dimensional Moment
The ratio at shape, the most narrow place of the corresponding object of its width, the widest part of its long corresponding object, the widest part and most narrow place reflects rock slag
Shape information.
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| CN109977944B (en) * | 2019-02-21 | 2023-08-01 | 杭州朗阳科技有限公司 | Digital water meter reading identification method |
| CN110568448B (en) * | 2019-07-29 | 2021-04-27 | 浙江大学 | Device and method for identifying accumulated slag at bottom of tunnel of hard rock tunnel boring machine |
| CN110308169A (en) * | 2019-08-09 | 2019-10-08 | 山东大学 | A kind of TBM slag piece ray back scattering real time scan imaging device and method |
| CN110954452B (en) * | 2019-12-10 | 2021-04-06 | 山东交通学院 | TBM (tunnel boring machine) carrying type test device and method for automatically obtaining particle size and strength characteristics of rock slag |
| CN112127896B (en) * | 2020-09-18 | 2021-12-21 | 武汉大学 | Automatic acquisition and analysis system and method for TBM excavation rock slag information |
| CN117147552A (en) * | 2023-10-30 | 2023-12-01 | 北京交通大学 | Rock slag grading analysis method for TBM tunnel |
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| CN103093456A (en) * | 2012-12-25 | 2013-05-08 | 北京农业信息技术研究中心 | Corn ear character index computing method based on images |
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| EP2273449A3 (en) * | 2004-06-11 | 2012-07-25 | Lyyn Ab | Method and Apparatus for Image Processing using Histogram Equalization |
| WO2013044345A1 (en) * | 2011-09-30 | 2013-04-04 | Tesman Inc. | Systems and methods for motion capture in an underground environment |
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| CN103020970A (en) * | 2012-12-25 | 2013-04-03 | 北京农业信息技术研究中心 | Corn ear image grain segmentation method |
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