CN106152962A - Oil drilling sleeve pipe deformation detecting method based on pipe crawling device - Google Patents
Oil drilling sleeve pipe deformation detecting method based on pipe crawling device Download PDFInfo
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- CN106152962A CN106152962A CN201510160795.7A CN201510160795A CN106152962A CN 106152962 A CN106152962 A CN 106152962A CN 201510160795 A CN201510160795 A CN 201510160795A CN 106152962 A CN106152962 A CN 106152962A
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- image sequence
- sleeve pipe
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Abstract
The invention discloses a kind of oil drilling sleeve pipe deformation detecting method based on pipe crawling device, including type detection and the deformation location of sleeve pipe deformation.Carried photographic head by pipe crawling device in oil drilling sleeve pipe, gather image sequence, searching image sequence and judge whether deformation, if there is deformation, determining whether Deformation Types and deformation location in sleeve pipe.For the type detection of deformation, by Canny function, Roberts function, Morphological Gradient function or senior contours extract function the image sequence gathered processed thus identify Deformation Types；Position for deformation, by the way of obtaining image key frame, judge deformation position in sleeve pipe, and then propose based on template matching and the method obtaining image key frame based on contours extract two kinds.The present invention can detect the deformation characteristics of oil drilling sleeve pipe exactly, thus gets rid of the potential safety hazard caused in oil well exploration engineering by sleeve pipe deformation.
Description
Technical field
The invention belongs to pipeline deformation field of detecting, a kind of oil drilling sleeve pipe based on pipe crawling device
Deformation detecting method.
Background technology
The deformation of oil drilling sleeve pipe is the key factor affecting oil well exploration engineering safety.Domestic conventional stone
Oil well casing deformation detecting method is jack rabbit detection method, and the method penetrates petroleum drilling by manually pulling jack rabbit
Casing, penetrates process by observation and judges whether sleeve pipe exists deformation.The automaticity of this method is low,
Manual labor expends big, and cannot accurately detect sleeve pipe deformation.
Sun is built up the Army and is proposed to use jack rabbit that subsea manifold is carried out latus rectum in paper " test of subsea manifold clear water "
Test, latus rectum test can measure whether the ovality of pipeline during welding manufacture exists deformation, if deposits
At prominent soldering paste or welding slag, the method for test is after jack rabbit enters pipeline, pulls the rope of one end, logical
Footpath rule can enter from one end, from the other end out in the case of substantially not hindering smoothly；Then commutate from going out
End enters, and pulls out smoothly in the case of not having obvious resistance, then prove that pipeline ovality does not deform, do not have
Prominent soldering paste or welding slag.Although this method can judge that whether unobstructed pipeline is on the whole, but automatization's journey
Spending low, manual labor expends big, and cannot accurately detect sleeve pipe deformation.
Sun Hanjun proposes a kind of oil pipe with pooling feature in paper " development of buffer type oil tube drift diameter gauge "
Jack rabbit, it is possible to reduce the impulsive force that jack rabbit produces when quick penetration pipeline, reduces peace during latus rectum detection
Full hidden danger.Although jack rabbit has structurally been made certain improvement by this method, but still does not solve automatically
Change degree is low, and manual labor expends big, and cannot accurately detect the problems such as sleeve pipe deformation.
Summary of the invention
The present invention proposes a kind of oil drilling sleeve pipe deformation detecting method based on pipe crawling device, solves tradition
Jack rabbit well casing detection method automaticity is low, manual labor expends big and cannot accurately detect sleeve
The problem become.
The technical solution realizing the object of the invention is: a kind of oil drilling sleeve based on pipe crawling device
Become detection method, comprise the following steps:
Step 1, pipe crawling device is arranged on oil drilling sleeved pipe inwall, the afterbody of pipe crawling device with
Oil drilling sleeved pipe mouth is concordant, and pipe crawling device gathers oil drilling sleeved pipe inwall image, by image
By natural number sequential storage, search image sequence in order, it is judged that whether image sequence exists deformation, if existing
Deformation proceeds to step 2；
Step 2, image sequence according to above-mentioned collection, it is judged that the Deformation Types of oil drilling sleeved pipe inwall
And deformation location in sleeve pipe.
In above-mentioned steps 2, Deformation Types detection method, comprise the following steps:
2-1) select Canny function, Roberts function, Morphological Gradient function gradient (), or high step cone
Wide function cvFindContours () that extracts acts on above-mentioned image sequence frame by frame, and the profile extracting image sequence is special
Levy.
2-2) according to the contour feature of image sequence, it is judged that the Deformation Types of image sequence.
The Deformation Types of above-mentioned image sequence is crack, empty or protruding.
Above-mentioned deformation position detection method, comprises the following steps:
The first step, first start image acquisition due to crawl device, then start to creep, therefore before creeping, first can gather
To one section of static image, search the image sequence of collection in order, in the image sequence that record gathers, first
The frame ordinal number of secondary two two field pictures image change occur, i.e. becomes, from rest image, the frame sequence that moving image is corresponding
Number.
Second step, according to Deformation Types, obtains deformation and occurs in image sequence to just disappearing to image sequence
The frame ordinal number of critical part image key frame.
3rd step, determine crawl device from setting in motion until closest to distance d at sleeve pipe deformation,
D=(i-startframe) f v, wherein i represents the frame ordinal number of image key frame, startframe table
Showing the frame ordinal number of the previous frame image obtained in the first step, f represents the time between adjacent two two field pictures of collection
Interval, v represents the movement velocity of pipe crawling device.
4th step, by the length of wagon of pipe crawling device and crawl device from setting in motion until closest to sleeve pipe deformation
The distance d summation at place, it is thus achieved that deformation is present position in sleeve pipe.
In above-mentioned second step, if the Deformation Types of image sequence is crack, empty or protruding, then extracts deformation and go out
Now to the frame ordinal number of two continuous frames image of the critical part just disappearing to image sequence, method in image sequence
As follows:
1st step, from gather image sequence intercept one piece of rectangular area comprising deformation as deformable templates.
2nd step, deformable templates is mated with the image sequence frame by frame of collection, obtain in every two field picture with deformation mould
The position that plate mates most, and draw rectangle frame.
3rd step, basis carry out pixel to the deformation all images from occurring to disappearing in the image sequence of collection and divide
Analysis, limits the rectangle frame upper left corner point coordinates of the deformation all images from occurring to disappearing, it is thus achieved that upper left angle point is sat
Mark scope, and judge whether the rectangle frame upper left corner point coordinates of all image sequences is positioned at above-mentioned scope, by position
Rectangle frame upper left corner point coordinates in the range of in is averaged value computing, if meansigma methods is in above-mentioned scope, records shape
Become the frame ordinal number of the previous frame image just disappearing to image sequence, i.e. image key frame.
In above-mentioned second step, if the Deformation Types of image sequence is crack, then extracts deformation and occur in image sequence
In to the frame ordinal number of two continuous frames image of the critical part just disappearing to image sequence, method is as follows:
A walks, and extracts image sequence contour feature frame by frame, adds rectangle frame around the contour feature extracted,
Record comprises the contour feature information of deformation simultaneously.
B walks, the deformation all images from occurring to disappearing in the image sequence gathered is carried out pixel analysis,
Calculate the rectangle comprised around the contour feature of deformation that the deformation all images from occurring to disappearing are corresponding respectively
The elemental area of frame and the ratio of width to height, using elemental area and the maximum of the ratio of width to height and minima as the scope of restriction,
In the range of judging whether the area of image sequence rectangle frame and the ratio of width to height are in above-mentioned restriction frame by frame, if limiting model
In enclosing, record is positioned at the frame ordinal number of the last frame image in the range of restriction, i.e. image key frame.
The present invention compared with prior art, its remarkable advantage: 1) present invention uses the mode of image sequence processing
The deformation of detection oil drilling sleeve pipe, automaticity is higher, saves cost of labor；2) can be to oil
Deformation in well casing positions, and positioning precision is high.
Accompanying drawing explanation
Fig. 1 is present invention oil drilling based on pipe crawling device sleeve pipe deformation type detection method flow diagram.
Fig. 2 is that in oil drilling sleeve pipe deformation position based on pipe crawling device detection, Deformation Types is crack, sky
Method flow diagram when hole or projection.
When Fig. 3 is that in oil drilling sleeve pipe deformation position based on pipe crawling device detection, Deformation Types is crack
Method flow diagram.
Detailed description of the invention
Below in conjunction with the accompanying drawings the present invention is described in further detail.
In conjunction with Fig. 1, Fig. 2 and Fig. 3, the present invention provides a kind of oil drilling sleeve based on pipe crawling device
Become detection method, including to the detection of Deformation Types and deformation detection of present position in sleeve pipe, including following
Step:
Step 1, by pipe crawling device (" petroleum pipeline detection crawl device design and image processing techniques research ")
Being arranged on oil drilling sleeved pipe inwall, the afterbody of pipe crawling device is concordant with oil drilling sleeved pipe mouth,
Pipe crawling device gathers oil drilling sleeved pipe inwall image, image is pressed natural number sequential storage, in order
Search image sequence, it is judged that whether image sequence exists deformation, if there is deformation to proceed to step 2.
Step 2, image sequence according to above-mentioned collection, it is judged that the Deformation Types of oil drilling sleeved pipe inwall
And deformation location in sleeve pipe.
The Deformation Types detection method of above-mentioned oil drilling sleeved pipe inwall is as follows:
2-1) select Canny function, Roberts function, Morphological Gradient function gradient (), or high step cone
Wide function cvFindContours () that extracts acts on above-mentioned image sequence frame by frame, and the profile extracting image sequence is special
Levy:
By the Canny operator in OpenCV tool storage room, or Roberts operator, or Morphological Gradient function
Gradient (), or senior contours extract function cvFindContours () acts on above-mentioned image frame by frame, extracts figure
Contour feature as sequence.
2-2) according to the contour feature of image sequence, it is judged that the Deformation Types of image sequence, Deformation Types is for splitting
Seam, empty or protruding.
Above-mentioned deformation position detection method is as follows, comprises the following steps:
The first step, search the image sequence of collection in order, first start image acquisition due to crawl device, then start
Creep, therefore before creeping, first can collect one section of static image, in the image sequence that record gathers, first
There is the frame ordinal number of image change in secondary two continuous frames image, i.e. becomes, from rest image, the frame sequence that moving image is corresponding
Number.
Second step, according to Deformation Types, obtains deformation and occurs in image sequence to just disappearing to image sequence
The frame ordinal number of critical part image key frame.
3rd step, determine crawl device from setting in motion until closest to distance d at sleeve pipe deformation,
D=(i-startframe) f v, wherein i represents the frame ordinal number of image key frame, startframe table
Showing the frame ordinal number of the previous frame image obtained in the first step, f represents the time between adjacent two two field pictures of collection
Interval, v represents the movement velocity of pipe crawling device.
4th step, by the length of wagon of pipe crawling device and crawl device from setting in motion until closest to sleeve pipe deformation
The distance d summation at place, it is thus achieved that deformation is present position in sleeve pipe.
In above-mentioned second step, if the Deformation Types of image sequence is crack, empty or protruding, then extracts deformation and go out
Now to the frame ordinal number of two continuous frames image of the critical part just disappearing to image sequence, method in image sequence
As follows:
1st step, from gather image sequence intercept one piece of rectangular area comprising deformation as deformable templates；
2nd step, deformable templates is mated with the image sequence frame by frame of collection, obtain in every two field picture with deformation mould
The position that plate mates most, and draw rectangle frame:
Defining matrix source images by function copyTo () in OpenCV tool storage room, function create () creates
Output matrix of consequence, deformable templates and collection image are mated fortune by function matchtemplate () frame by frame
Calculate, matching operation result is normalized by function normalize (), according to function minMaxLoc () with
The position that the matching operation method location selected is mated most, last function rectangle () is in the position mated most
Draw rectangle frame；
3rd step, basis carry out pixel to the deformation all images from occurring to disappearing in the image sequence of collection and divide
Analysis, limits the rectangle frame upper left corner point coordinates of the deformation all images from occurring to disappearing, it is thus achieved that upper left angle point is sat
Mark scope, and judge whether the rectangle frame upper left corner point coordinates of all image sequences is positioned at above-mentioned scope, by position
Rectangle frame upper left corner point coordinates in the range of in is averaged value computing, if meansigma methods is in above-mentioned scope, records shape
Become the frame ordinal number of the previous frame image just disappearing to image sequence, i.e. image key frame.
Embodiment 1
Using said method, if the Deformation Types of image sequence is cavity, related data is: image becomes for the first time
The frame ordinal number changed is 130, and the image key frame ordinal number of acquisition is 341, and the movement velocity of crawl device is 20mm/s,
Time interval between adjacent two two field pictures gathered is 0.13s, the physical location in crack and the distance of pipeline opening
For 592.6mm.
Through test, the deformation position percentage error using the present invention to calculate is 7.42%.
In above-mentioned second step, if the Deformation Types of image sequence is crack, then extracts deformation and occur in image sequence
In to the frame ordinal number of two continuous frames image of the critical part just disappearing to image sequence, method is as follows:
A walks, and extracts image sequence contour feature frame by frame, adds rectangle frame around the contour feature extracted,
Record comprises the contour feature information of deformation simultaneously:
The figure of collection is searched frame by frame by contours extract function cvFindContours () in OpenCV tool storage room
As sequence, and around the profile extracted, add rectangle frame.
B walks, the deformation all images from occurring to disappearing in the image sequence gathered is carried out pixel analysis,
Calculate the rectangle comprised around the contour feature of deformation that the deformation all images from occurring to disappearing are corresponding respectively
The elemental area of frame and the ratio of width to height, using elemental area and the maximum of the ratio of width to height and minima as the scope of restriction,
In the range of judging whether the area of image sequence rectangle frame and the ratio of width to height are in above-mentioned restriction frame by frame, if limiting model
In enclosing, record is positioned at the frame ordinal number of the last frame image in the range of restriction, i.e. image key frame.
Embodiment 2
Using said method, if the Deformation Types of image sequence is crack, related data is: image becomes for the first time
The frame ordinal number changed is 130, and the image key frame ordinal number of acquisition is 339, and the movement velocity of crawl device is 20mm/s,
Time interval between adjacent two two field pictures gathered is 0.13s, the physical location in crack and the distance of pipeline opening
For 592.6mm.
Through test, the deformation position percentage error using this method to calculate is 8.30%.
The oil drilling sleeve pipe deformation detecting method based on pipe crawling device provided according to the present invention, can be more
Accurately detect the position of oil drilling sleeve pipe deformation.
Claims (6)
1. an oil drilling sleeve pipe deformation detecting method based on pipe crawling device, it is characterised in that include
Following steps:
Step 1, pipe crawling device is arranged on oil drilling sleeved pipe inwall, the afterbody of pipe crawling device with
Oil drilling sleeved pipe mouth is concordant, and pipe crawling device gathers oil drilling sleeved pipe inwall image, by image
By natural number sequential storage, search image sequence in order, it is judged that whether image sequence exists deformation, if existing
Deformation proceeds to step 2；
Step 2, image sequence according to above-mentioned collection, it is judged that the Deformation Types of oil drilling sleeved pipe inwall
And deformation location in sleeve pipe.
Oil drilling sleeve pipe deformation detecting method based on pipe crawling device the most according to claim 1,
It is characterized in that: in step 2 that Deformation Types detection method comprises the following steps:
2-1) select Canny function, Roberts function, Morphological Gradient function gradient (), or high step cone
Wide function cvFindContours () that extracts acts on above-mentioned image sequence frame by frame, and the profile extracting image sequence is special
Levy；
2-2) according to the contour feature of image sequence, it is judged that the Deformation Types of image sequence.
Oil drilling sleeve pipe deformation detecting method based on pipe crawling device the most according to claim 2,
It is characterized in that: the Deformation Types of above-mentioned image sequence is crack, empty or protruding.
4. according to the oil drilling sleeve pipe shape changing detection side based on pipe crawling device described in claim 1 or 3
Method, it is characterised in that: above-mentioned deformation position detection method, comprise the following steps:
The first step, first start image acquisition due to crawl device, then start to creep, therefore before creeping, first can gather
To one section of static image, search the image sequence of collection in order, in the image sequence that record gathers, first
The frame ordinal number of secondary two two field pictures image change occur, i.e. becomes, from rest image, the frame sequence that moving image is corresponding
Number；
Second step, according to Deformation Types, obtains deformation and occurs in image sequence to just disappearing to image sequence
The frame ordinal number of critical part image key frame；
3rd step, determine crawl device from setting in motion until closest to distance d at sleeve pipe deformation,
D=(i-startframe) f v, wherein i represents the frame ordinal number of image key frame, startframe table
Showing the frame ordinal number of the previous frame image obtained in the first step, f represents the time between adjacent two two field pictures of collection
Interval, v represents the movement velocity of pipe crawling device；
4th step, by the length of wagon of pipe crawling device and crawl device from setting in motion until closest to sleeve pipe deformation
The distance d summation at place, it is thus achieved that deformation is present position in sleeve pipe.
Oil drilling sleeve pipe deformation detecting method based on pipe crawling device the most according to claim 4,
It is characterized in that: in above-mentioned second step, if the Deformation Types of image sequence is crack, empty or protruding, then carry
Take the frame of two continuous frames image that deformation occurs in image sequence to the critical part just disappearing to image sequence
Ordinal number, method is as follows:
1st step, from gather image sequence intercept one piece of rectangular area comprising deformation as deformable templates；
2nd step, deformable templates is mated with the image sequence frame by frame of collection, obtain in every two field picture with deformation mould
The position that plate mates most, and draw rectangle frame；
3rd step, basis carry out pixel to the deformation all images from occurring to disappearing in the image sequence of collection and divide
Analysis, limits the rectangle frame upper left corner point coordinates of the deformation all images from occurring to disappearing, it is thus achieved that upper left angle point is sat
Mark scope, and judge whether the rectangle frame upper left corner point coordinates of all image sequences is positioned at above-mentioned scope, by position
Rectangle frame upper left corner point coordinates in the range of in is averaged value computing, if meansigma methods is in above-mentioned scope, records shape
Become the frame ordinal number of the previous frame image just disappearing to image sequence, i.e. image key frame.
Oil drilling sleeve pipe deformation detecting method based on pipe crawling device the most according to claim 4,
It is characterized in that: in above-mentioned second step, if the Deformation Types of image sequence is crack, then extracts deformation and occur in
To the frame ordinal number of two continuous frames image of the critical part just disappearing to image sequence in image sequence, method is such as
Under:
A walks, and extracts image sequence contour feature frame by frame, adds rectangle frame around the contour feature extracted,
Record comprises the contour feature information of deformation simultaneously；
B walks, the deformation all images from occurring to disappearing in the image sequence gathered is carried out pixel analysis,
Calculate the rectangle comprised around the contour feature of deformation that the deformation all images from occurring to disappearing are corresponding respectively
The elemental area of frame and the ratio of width to height, using elemental area and the maximum of the ratio of width to height and minima as the scope of restriction,
In the range of judging whether the area of image sequence rectangle frame and the ratio of width to height are in above-mentioned restriction frame by frame, if limiting model
In enclosing, record is positioned at the frame ordinal number of the last frame image in the range of restriction, i.e. image key frame.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201510160795.7A CN106152962B (en) | 2015-04-07 | 2015-04-07 | Oil drilling casing deformation detecting method based on pipe crawling device |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510160795.7A CN106152962B (en) | 2015-04-07 | 2015-04-07 | Oil drilling casing deformation detecting method based on pipe crawling device |
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| CN106152962A true CN106152962A (en) | 2016-11-23 |
| CN106152962B CN106152962B (en) | 2018-12-14 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110136381A (en) * | 2018-02-07 | 2019-08-16 | 中国石油化工股份有限公司 | A kind of well drilling operation site personnel standing monitoring and warning system |
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| CN1563891A (en) * | 2004-04-20 | 2005-01-12 | 长安大学 | System and method for discriminating road gap |
| CN101169380A (en) * | 2007-10-31 | 2008-04-30 | 重庆大学 | Bridge cable surface damage dynamic detection method and device |
| CN102355569A (en) * | 2011-05-30 | 2012-02-15 | 南京航空航天大学 | Aircraft skin structure monitoring method based on wireless machine vision |
| CN103279765A (en) * | 2013-06-14 | 2013-09-04 | 重庆大学 | Steel wire rope surface damage detection method based on image matching |
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2015
- 2015-04-07 CN CN201510160795.7A patent/CN106152962B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5243542A (en) * | 1987-12-29 | 1993-09-07 | Asahi Kogaku Kogyo Kabushiki Kaisha | Interferometer employing reference images |
| US20030098426A1 (en) * | 2001-11-27 | 2003-05-29 | Kabushiki Kaisha Shinkawa | Wire bonding method and apparatus |
| CN1563891A (en) * | 2004-04-20 | 2005-01-12 | 长安大学 | System and method for discriminating road gap |
| CN101169380A (en) * | 2007-10-31 | 2008-04-30 | 重庆大学 | Bridge cable surface damage dynamic detection method and device |
| CN102355569A (en) * | 2011-05-30 | 2012-02-15 | 南京航空航天大学 | Aircraft skin structure monitoring method based on wireless machine vision |
| CN103279765A (en) * | 2013-06-14 | 2013-09-04 | 重庆大学 | Steel wire rope surface damage detection method based on image matching |
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| CN110136381A (en) * | 2018-02-07 | 2019-08-16 | 中国石油化工股份有限公司 | A kind of well drilling operation site personnel standing monitoring and warning system |
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