CN104100256A - Method for measuring coal mine underground drilling depth based on image processing technology - Google Patents
Method for measuring coal mine underground drilling depth based on image processing technology Download PDFInfo
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Abstract
The invention discloses an image processing video tracking technology. The technology specifically comprises tracking the movement of drills in a punching video, measuring and analyzing tracking paths to automatically calculate the number of drilling rods, and calculating the depth of drilling holes according to the number of the drilling rods. The measuring error caused by human factors can be avoided, the data can be processed in real time or after the event; the measuring security is excellent, and major hidden danger can be solved. A method for measuring the coal mine underground drilling depth based on an image processing technology is provided, and the technology for automatically tracking and identifying objects in the video with low-quality in the underground complex environment is provided; according to the method, the problems that the underground movement objects are complex, and underground workers block the drilling hole video can be solved; the complex light environment generated by underground mine lamps and head lamps of the workers can be processed; the tracking result automatic quantitative analysis and counting judging result precision is high, and the real-time performance of a system is high.
Description
Technical field
The present invention relates to image processing techniques, be specifically related to the coal mine down-hole drilling depth measurement method based on image processing techniques.
Background technology
Gas is the major hidden danger of Safety of Coal Mine Production always.For gaseous mine, the maximum potential safety hazard in coal production process is gas accident.China's nineteen ninety to 2000, year above major gas accident proportion of once dead 3 people rose year by year, was up to 45.61%, 1996 year and remained on more than 40% later always.Therefore, gas accident is the high principal contradiction of China's coal-mine security incident, and effectively control gas accident is the key that solves China's coal-mine safety problem.Very harmful due to gas accident, eliminate gas accident hidden danger and need to spend more time and expense, to high gas and outburst mine, mechanized extraction equipment is difficult to play effectiveness, coal road driving speed is all difficult to exceed the 100m/ month conventionally, and stope output is difficult to exceed 1,000,000 t/a conventionally.Therefore, the threat of Gas Disaster accident has also greatly limited the raising of coal production scale, production efficiency and economic benefit.Effective control of Gas Disaster is a critical problem that ensures China coal industry sustainable development.
Therefore coal mine gas is carried out to the comprehensive regulation particularly important, application is at present wide, the good technology of effect is gas pumping technology.Gas pumping is the Main Means that colliery prevents Gas Outburst.The method that also rests at present measurement while drilling for the measurement of drilling depth, subsequent supervision cannot be carried out.And still adopt manual method for the measurement after drilling, there is potential safety hazard.
Summary of the invention
In order to solve the deficiencies in the prior art, the present invention adopts image processing techniques, automatically application drilling rod counting algorithm, measurement is drilled and is squeezed into the quantity of drilling rod in process, and calculating drilling depth according to drilling rod quantity, the measuring error of having avoided human factor to cause, can be in real time or deal with data afterwards, and the safety of measuring is good, has solved great potential safety hazard.
Technical scheme of the present invention is: the coal mine down-hole drilling depth measurement method based on image processing techniques, comprises the following steps:
Step 1, automatically calculate frame number FramIn=that drill bit pierces process (s) * video frame rate (frame/s), and the frame number FrameOut=that exits process moves back and bores required time (s) * video frame rate (frame/s) that takes time that takes time of drilling according to the frame per second number of video;
Step 2, selects the drill bit rectangle frame of drilling as To Template, records the position of target rectangle frame and the target image of size and drill bit;
Step 3, adopt the feature histogram of kernel function weighting to describe To Template according to average drifting target tracking algorism, in every frame, To Template model and candidate target model are carried out to similarity measurement, and along the gradient direction iterative search target location of core histogram similarity, realize target is followed the tracks of; Described target following is exactly the drill bit target location y according to previous frame
0, in present frame, find the position y making apart from minimum or likeness coefficient maximum
1. under the definite condition of core window width, obtain target masterplate p and candidate target masterplate q with histogram model after, the matching distance between model is defined as
wherein ρ is Bhattacharyya coefficient, moves to new position until convergence obtains current new position by the gradient direction along similarity measurement constantly;
Step 4, in drilling process, the motion of drill bit is advanced and retreats for constantly jittery, so the distance track to tracking results first adopts median smoothing processing, after level and smooth the offset distance of certain moment t be d ' (t)=med{d (t-k, t+k) }, wherein k is filtering dimensional parameters, judge the division of single drilling rod motion by the remarkable jump of the To Template offset distance after finding smoothly, whole curve movement is rendered as Z-shaped repeatedly, the interior three mean deviations distances of front and back certain limit that the criterion of significantly jumping is defined as judging point are greater than 2/3 of whole movement locus (being run of steel), , meet
need the time difference of satisfied twice vertical jump in succession to meet the time requirement of setting simultaneously, meet T
i+1-T
i> a* (FrameIn+FrameOut), a, between 0 to 1, is a drilling rod quantity,
Step 5, drilling depth can be convenient for measuring and learn according to the drilling well drilling bar quantity of analyzing: Depth=run of steel * drilling well drilling bar quantity.
Further improvement of the present invention comprises:
Described step 2 also comprises selects drilling rod direction as direction of primary motion, to avoid multiple mobile object in complicated subsurface environment as interference and circumstance of occlusion that labour movement etc. produces, to record the parameter of direction line segment.
If the position of target is displaced to a certain distance from the direction of motion of selecting in step 2 in the present frame that mean shift algorithm traces into, think present frame track rejection, this frame result is invalid, taking the predicted value of persistent movement as target location.
Described step 3 also comprises by gray feature, gradient direction feature and Corner Feature and judges the similitude between To Template and candidate family.
Described step 3 also comprises objective definition region, and the region, field of 3 times of target area areas centered by the geometric center of target area is background area, calculates discrimination D and judge the differentiation degree of target and background, calculating principle be defined as
wherein Ha and Hb represent respectively the feature histogram of target area and background area
The present invention adopts image to process video tracking technology, drill bit movement in punching video is followed the tracks of, Measurement and analysis pursuit path calculates the number of drilling rod automatically, and calculate drilling depth according to drilling rod quantity, the measuring error of having avoided human factor to cause, can be in real time or deal with data afterwards, and the safety of measuring is good, has solved great potential safety hazard.Coal mine down-hole drilling depth measurement method based on image processing techniques, to the Automatic Target Tracking recognition technology of low quality video in the complex environment of down-hole, the method not only can solve down-hole moving target complexity, the occlusion issue that underground labour produces hole-drilling video, and can also tackle the complex illumination environment producing in down-hole mine lamp and workman's forehead lamp, tracking results automatically quantitative analysis and counting judged result precision are very high simultaneously, and the real-time of system is high.
Detailed description of the invention
Below the present invention is elaborated.
1. video pre-filtering
The processing of 1.1 videos
Choose and open with a series of pending drilling well video, read video inner parameter.
The automatic acquisition of 1.2 parameters
Automatically calculate frame number FramIn=that drill bit pierces process (s) * video frame rate (frame/s), and the frame number FrameOut=that exits process moves back and bores required time (s) * video frame rate (frame/s) that takes time that takes time of drilling according to the frame per second number of video
2. target following
The selection of 2.1 tracking targets and the direction of motion
Artificial mouse selects the drill bit rectangle frame of drilling as To Template, and selects drilling rod direction as direction of primary motion, to avoid interference and the circumstance of occlusion that in complicated subsurface environment, multiple mobile object produces as labour movement etc.Record the parameter of target rectangle frame and direction line segment.
2.2 average drifting target tracking algorisms based on many features
Average drifting target tracking algorism adopts the feature histogram of kernel function weighting to describe target, in every frame, To Template model and candidate target model are carried out to similarity measurement, and along the gradient direction iterative search target location of core histogram similarity, realize target is followed the tracks of.
A) selection of many features
Downhole video is the serious low resolution gray-scale map of noise, uses single gray feature to be difficult to distinguish tracked drill bit and background, and different features is described and distinguished the ability difference that target and background distributes.Therefore, judge the similitude between To Template and candidate family in conjunction with gray feature, gradient direction feature and Corner Feature.
Objective definition region, the region, field of 3 times of target area areas centered by center, target area is background area, and calculating discrimination D judges the differentiation degree of target and background, and the calculating principle of D is defined as
wherein Ha and Hb represent respectively the feature histogram of target area and background area.
B) tracking of present frame target location
Target following is exactly the drill bit target location y according to previous frame
0, in present frame, find the position y making apart from minimum or likeness coefficient maximum
1. under the definite condition of core window width, obtain target masterplate p and candidate target masterplate q with histogram model after, the matching distance between model is defined as
wherein ρ is Bhattacharyya coefficient.Move to new position until convergence obtains current new position by the gradient direction along similarity measurement constantly.
C) correction of tracking position of object and model modification
If the position of the present frame that mean shift algorithm traces into is displaced to the direction of motion of selecting with a certain distance from 2.1 steps, think present frame track rejection, this frame result is invalid, taking the predicted value of persistent movement as target location.
3. automatic drilling rod method of counting
The movement locus of 3.1 level and smooth target followings
In drilling process, the motion of drill bit is advanced and retreats for constantly jittery, so the distance track to tracking results first adopts median smoothing processing, after level and smooth the offset distance of certain moment t be d ' (t)=med{d (t-k, t+k), wherein k is filtering dimensional parameters.
3.2 drilling rods move back the judgement in bar cycle
Boring procedure for show as into-move back-...-cycle movement of entering-moving back, on movement locus figure, show as offset distance and present periodic jump, judge the division of single drilling rod motion by the remarkable jump of the offset distance after finding smoothly, whole curve movement is rendered as Z-shaped repeatedly, the interior three mean deviations distances of front and back certain limit that the criterion of significantly jumping is defined as judging point are greater than 2/3 of whole movement locus (being run of steel),, meet
need the satisfied time difference of twice vertical jump in succession simultaneously to meet the time requirement of setting simultaneously, meet T
i+1-T
i> a* (FrameIn+FrameOut), a is between 0 to 1.
4. drilling depth is measured and is proofreaied and correct
Drilling depth can be convenient for measuring and learn according to the drilling well drilling bar quantity of analyzing: Depth=run of steel * drilling well drilling bar quantity.Due to down-hole complex illumination and movement environment, or workman's irregular operation etc. may cause following the tracks of loses, or the movement locus of drill bit is not entirely drills and moves back brill process, therefore provide track following figure in system, can find out brightly to follow the tracks of and lose and irregular drilling the cycle, administrative staff can verify and correction calculation result partial video section according to track following figure.
More than show and described general principle of the present invention and principal character and advantage of the present invention.The technician of the industry should understand; the present invention is not restricted to the described embodiments; that in above-described embodiment and manual, describes just illustrates principle of the present invention; without departing from the spirit and scope of the present invention; the present invention also has various changes and modifications, and these changes and improvements clans enter in the claimed scope of the invention.The claimed scope of the present invention is defined by appending claims and equivalent thereof.
Claims (5)
1. the coal mine down-hole drilling depth measurement method based on image processing techniques, is characterized in that, comprises the following steps:
Step 1, automatically calculate frame number FramIn=that drill bit pierces process (s) * video frame rate (frame/s), and the frame number FrameOut=that exits process moves back and bores required time (s) * video frame rate (frame/s) that takes time that takes time of drilling according to the frame per second number of video;
Step 2, selects the drill bit rectangle frame of drilling as To Template, records the position of target rectangle frame and the target image of size and drill bit;
Step 3, adopt the feature histogram of kernel function weighting to describe To Template according to average drifting target tracking algorism, in every frame, To Template model and candidate target model are carried out to similarity measurement, and along the gradient direction iterative search target location of core histogram similarity, realize target is followed the tracks of; Described target following is exactly the drill bit target location y according to previous frame
0, in present frame, find the position y making apart from minimum or likeness coefficient maximum
1. under the definite condition of core window width, obtain target masterplate p and candidate target masterplate q with histogram model after, the matching distance between model is defined as
wherein ρ is Bhattacharyya coefficient, moves to new position until convergence obtains current new position by the gradient direction along similarity measurement constantly;
Step 4, in drilling process, the motion of drill bit is advanced and retreats for constantly jittery, so the distance track to tracking results first adopts median smoothing processing, after level and smooth the offset distance of certain moment t be d ' (f)=med{d (t-k, t+k) }, wherein k is filtering dimensional parameters, judge the division of single drilling rod motion by the remarkable jump of the tracking results offset distance after finding smoothly, need the time difference of satisfied twice vertical jump in succession to meet the time requirement of setting simultaneously, meet T
i+1-T
i> a* (FrameIn+FrameOut), a, between 0 to 1, is a drilling rod quantity;
Step 5, drilling depth can be convenient for measuring and learn according to the drilling well drilling bar quantity of analyzing: Depth=run of steel * drilling well drilling bar quantity.
2. the coal mine down-hole drilling depth measurement method based on image processing techniques according to claim 1, it is characterized in that, described step 2 also comprises selects drilling rod direction as direction of primary motion, to avoid multiple mobile object in complicated subsurface environment as interference and circumstance of occlusion that labour movement etc. produces, to record the parameter of direction line segment.
3. the coal mine down-hole drilling depth measurement method based on image processing techniques according to claim 1, it is characterized in that, if the position of the present frame that mean shift algorithm traces into is displaced to a certain distance from the direction of motion of selecting in step 2, think present frame track rejection, this frame result is invalid, taking the predicted value of persistent movement as target location.
4. the coal mine down-hole drilling depth measurement method based on image processing techniques according to claim 1, it is characterized in that, described step 3 also comprises by gray feature, gradient direction feature and Corner Feature and judges the similitude between To Template and candidate family.
5. the coal mine down-hole drilling depth measurement method based on image processing techniques according to claim 1, it is characterized in that, described step 3 also comprises objective definition region, the region, field of 3 times of target area areas centered by the geometric center of target area is background area, calculate the differentiation degree that discrimination D judges target and background, the calculating principle of D is defined as
wherein Ha and Hb represent respectively the feature histogram of target area and background area.
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| CN105649607A (en) * | 2015-12-31 | 2016-06-08 | 郑州光力科技股份有限公司 | Mining while-drilling type borehole track detection method and system and drill rod |
| CN107833240A (en) * | 2017-11-09 | 2018-03-23 | 华南农业大学 | The target trajectory extraction of multi-track clue guiding and analysis method |
| CN107871114A (en) * | 2016-09-23 | 2018-04-03 | 杭州海康威视数字技术股份有限公司 | A kind of method, apparatus and system for pushing target person tracking information |
| CN109267995A (en) * | 2018-10-16 | 2019-01-25 | 安徽理工大学 | A kind of geologic drilling rod feeding depth measuring system based on Aberration Analysis drilling rod node |
| CN109598710A (en) * | 2018-11-29 | 2019-04-09 | 中国科学院重庆绿色智能技术研究院 | A kind of coal mine drill pipe automatic counting method and system |
| CN109800848A (en) * | 2019-01-23 | 2019-05-24 | 中国科学院重庆绿色智能技术研究院 | A kind of underground coal mine is drilled the automatic counting method of quantity |
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| CN105649607A (en) * | 2015-12-31 | 2016-06-08 | 郑州光力科技股份有限公司 | Mining while-drilling type borehole track detection method and system and drill rod |
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| CN109267995A (en) * | 2018-10-16 | 2019-01-25 | 安徽理工大学 | A kind of geologic drilling rod feeding depth measuring system based on Aberration Analysis drilling rod node |
| CN109267995B (en) * | 2018-10-16 | 2022-02-11 | 安徽理工大学 | Geological drill rod feeding depth measuring system based on aberration analysis drill rod node |
| CN109598710A (en) * | 2018-11-29 | 2019-04-09 | 中国科学院重庆绿色智能技术研究院 | A kind of coal mine drill pipe automatic counting method and system |
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| CN112001420B (en) * | 2020-07-24 | 2022-09-09 | 武汉安视感知科技有限公司 | Intelligent timing and counting method and device for drill pipe of mine worker and storage device |
| CN112001420A (en) * | 2020-07-24 | 2020-11-27 | 武汉安视感知科技有限公司 | Intelligent timing and counting method and device for drill pipe of mine worker and storage device |
| CN112883830B (en) * | 2021-01-29 | 2022-03-15 | 南京北路智控科技股份有限公司 | Real-time automatic counting method for drill rods |
| CN112883830A (en) * | 2021-01-29 | 2021-06-01 | 南京北路智控科技股份有限公司 | Real-time automatic counting method for drill rods |
| CN113188465A (en) * | 2021-04-21 | 2021-07-30 | 中铁第四勘察设计院集团有限公司 | Drilling hole depth identification method and device based on video learning |
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| CN114821453B (en) * | 2022-06-30 | 2022-09-20 | 广州英码信息科技有限公司 | Coal mine drill rod counting method based on target detection and computer readable medium |
| CN116778532A (en) * | 2023-08-24 | 2023-09-19 | 汶上义桥煤矿有限责任公司 | Underground coal mine personnel target tracking method |
| CN116778532B (en) * | 2023-08-24 | 2023-11-07 | 汶上义桥煤矿有限责任公司 | Underground coal mine personnel target tracking method |
| CN117557401A (en) * | 2024-01-12 | 2024-02-13 | 东华理工大学南昌校区 | Geological big data-based uranium ore prospecting target area intelligent demarcating method |
| CN117557401B (en) * | 2024-01-12 | 2024-04-02 | 东华理工大学南昌校区 | Geological big data-based uranium ore prospecting target area intelligent demarcating method |
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