CN111521279B - Pipeline leakage inspection method - Google Patents
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- 238000007689 inspection Methods 0.000 title claims abstract description 14
- 238000012545 processing Methods 0.000 claims abstract description 7
- 230000008859 change Effects 0.000 claims description 43
- 230000014509 gene expression Effects 0.000 claims description 28
- 230000001186 cumulative effect Effects 0.000 claims description 15
- 238000005259 measurement Methods 0.000 claims description 14
- 230000002159 abnormal effect Effects 0.000 claims description 10
- 238000012937 correction Methods 0.000 claims description 4
- 238000012544 monitoring process Methods 0.000 claims description 3
- 230000004075 alteration Effects 0.000 abstract description 3
- 238000001931 thermography Methods 0.000 abstract description 3
- 238000004458 analytical method Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 210000000416 exudates and transudate Anatomy 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J5/48—Thermography; Techniques using wholly visual means
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J5/80—Calibration
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M3/00—Investigating fluid-tightness of structures
- G01M3/002—Investigating fluid-tightness of structures by using thermal means
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M3/00—Investigating fluid-tightness of structures
- G01M3/02—Investigating fluid-tightness of structures by using fluid or vacuum
- G01M3/04—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
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- G06V10/40—Extraction of image or video features
- G06V10/46—Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
- G06V10/462—Salient features, e.g. scale invariant feature transforms [SIFT]
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- G06V20/10—Terrestrial scenes
- G06V20/182—Network patterns, e.g. roads or rivers
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J2005/0077—Imaging
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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- G06V20/194—Terrestrial scenes using hyperspectral data, i.e. more or other wavelengths than RGB
Abstract
The invention provides a pipeline leakage inspection method. The method comprises the following steps: initializing; determining pipeline paths, and acquiring image information and thermal image information of each position area of the pipeline in a normal state; acquiring patrol data; obtaining image information and thermal image information of each position area in a real-time state; comparing image information; comparing the thermal image information; weighting the images and the thermal images; local comparison; eliminating external interference and determining the possible position of the leakage accident; and (5) manually confirming. The unmanned aerial vehicle is provided with the digital camera, the thermal infrared imager and the external thermometer, the unmanned aerial vehicle needs to have a real-time positioning function, and the unmanned aerial vehicle is also provided with the searchlight so as to facilitate night patrol; acquiring a digital color photo and an infrared thermography by adopting unmanned aerial vehicle inspection; the image chromatic aberration is combined with the temperature difference, and weighting processing is carried out, so that the recognition rate is greatly improved; through local comparison, external interference is further eliminated, and accuracy of confirming the leakage occurrence position is improved.
Description
Technical Field
The invention relates to the technical field of information, numerical control, mapping and mathematics, in particular to a pipeline leakage inspection method.
Background
In order to ensure high-efficiency production and safety requirements, the real-time inspection and accident troubleshooting of pipelines for outdoor production and other purposes are time-consuming and labor-consuming work, problems are found and solved mainly through manual on-site inspection at present, time and labor are wasted, efficiency is low, and certain potential safety hazards are formed for the safety of personnel in special areas, such as mountainous areas and other areas where people are inconvenient to walk. In order to find and treat pipeline accidents as soon as possible and avoid or reduce the influence on production and the damage to the surrounding environment caused by the pipeline accidents, an efficient automatic inspection system is needed.
With the development of the unmanned aerial vehicle aerial photography technology, an unmanned aerial vehicle aerial photography measurement technology can be adopted, and an image and infrared thermal image identification technology is combined to provide a pipeline inspection method based on unmanned aerial vehicle photography.
In view of the above, there is a need for a method for inspecting a pipeline leakage to solve the problems in the prior art.
Disclosure of Invention
According to the invention, on the basis of aerial photography measurement of an unmanned aerial vehicle, pictures along a pipeline are acquired by the unmanned aerial vehicle and uploaded to a data center; the data center processes the pictures; and comparing and analyzing the image and the thermal image to judge pipeline accidents and risks. Forming a set of pipeline inspection methods.
In order to achieve the above object, the present invention provides a pipeline leakage inspection method, comprising the following steps;
the method comprises the following steps: initializing; determining pipeline paths, and acquiring image information and thermal image information of each position area of the pipeline in a normal state;
step two: acquiring patrol data; obtaining image information and thermal image information of each position area in a real-time state;
step three: comparing image information;
step four: comparing the thermal image information;
step five: weighting the images and the thermal images;
step six: local comparison; and eliminating external interference and determining the position where the leakage accident can occur.
Preferably, the first step is specifically: acquiring image range and precision according to a camera and a thermal imager, and performing initialization information acquisition in sections along the pipeline path; and then splicing the acquired images and the thermograph, and fitting the images into a fixed coordinate system through a fixed reference object.
Preferably, step two is specifically: and (3) the unmanned aerial vehicle patrols the pipeline path of the pipeline, acquires image information and thermal image information of each position area of the pipeline, and performs positioning correction and denoising treatment.
Preferably, the unmanned aerial vehicle is equipped with digital camera, thermal infrared imager and external thermometer, and the unmanned aerial vehicle needs to possess real-time positioning function. The unmanned aerial vehicle is also provided with a searchlight so as to facilitate night patrol.
Preferably, step three is specifically: graying image information, graying the acquired n times of aerial pictures to obtain a grayscale image, accumulating the grayscale values at the position a in the grayscale image of the previous n-1 times to obtain a cumulative number of grayscale values, and comparing the grayscale value at the position a in the grayscale image of the nth time with the cumulative number of grayscale values to obtain an image change ratio at the position a;
the cumulative number of gray values is calculated by adopting an expression (1):
the image change ratio of the a position is calculated by using the expression (2):
in the expressions (1) and (2),
obtaining the gray value of the nth time at the position a in the gray map;
the cumulative number of gray values of the a position is n-1 times; u image current trust weight factor;
the a position image change ratio is obtained; n is any natural number.
Preferably, the fourth step is specifically: performing difference processing on the obtained nth thermal image information and the real-time temperature measured by the external thermometer to obtain the thermal difference value of the a position obtained by nth measurement, accumulating the thermal difference values of the a position for n-1 times to obtain the accumulated thermal difference value number, and then comparing the thermal difference value of the a position obtained by nth measurement with the accumulated thermal difference value number to obtain the temperature change ratio of the a position;
the thermal image information of the position a obtained by the nth measurement is calculated by adopting an expression (3) to obtain:
the accumulated number of the heat difference values is calculated by adopting an expression (4):
the temperature change ratio is calculated by adopting an expression (5):
in expressions (3) to (5), W is the real-time temperature measured by the external thermometer;
acquiring thermal image information of a position a for the nth measurement;
is the thermal difference of the a position;
the cumulative number of the heat difference values of the a positions at the previous n-1 times is obtained; v thermal imagery forward trust weight factors;
is a position temperature change ratio; n is any natural number.
Preferably, step five is specifically: setting a threshold value for judgment, and if the threshold value is w, calculating the change rate of the position a by adopting an expression (6):
in the expression (6) above, the first,
is the rate of change of the a position; m is an image change weight, and l is a thermal image change weight, wherein m + l is 1;
when in use
When the position a is abnormal, the position a is judged to be abnormal.
Preferably, the sixth step is specifically: let a be the abnormal change position, and average change rate of the position and each position in the peripheral change region
Comparing, setting the judgment threshold value as beta when
The a position is considered as a position where the leakage accident may occur.
Further, the invention also comprises the seventh step: manually confirming; and pushing related pictures of the positions where the leakage accidents possibly occur to related responsible persons for manual determination.
The technical scheme of the invention has the following beneficial effects:
the unmanned aerial vehicle is provided with the digital camera, the thermal infrared imager and the external thermometer, the unmanned aerial vehicle needs to have a real-time positioning function, and the unmanned aerial vehicle is also provided with the searchlight so as to facilitate night patrol; acquiring a digital color photo and an infrared thermography by adopting unmanned aerial vehicle inspection; the image chromatic aberration is combined with the temperature difference, and weighting processing is carried out, so that the recognition rate is greatly improved; through local comparison, external interference is further eliminated, and accuracy of confirming the leakage occurrence position is improved.
In addition to the objects, features and advantages described above, there are other objects, features and advantages of the present invention. The present invention will be described in further detail below with reference to the drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic illustration of a partial alignment;
FIG. 2 is a flow chart of the operation of a pipeline leak patrol method;
Detailed Description
Embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be implemented in many different ways, which are defined and covered by the claims.
Example 1:
analysis principle of pipeline leakage accident: after the pipeline leaks, substances in the pipeline seep out to pollute the surrounding environment, so that the color of the surrounding environment changes; the exudate will affect changes in the ambient temperature. According to the two points, the color difference change and the temperature difference change of the periphery of the pipeline are combined respectively, comparison and analysis are carried out, and the accident position area information is obtained.
Referring to fig. 1 and 2, a pipeline leakage patrol method includes the steps of:
the method comprises the following steps: initializing; determining pipeline paths, acquiring image range and precision according to a camera and a thermal imager, and performing initialization information acquisition along the pipeline paths in a segmented manner; splicing the collected images and the thermograph, and fitting the images into a fixed coordinate system through a fixed reference object; and acquiring image information and thermal image information of each position area of the pipeline in a normal state.
Step two: acquiring patrol data; and (3) the unmanned aerial vehicle patrols the pipeline path of the pipeline, acquires image information and thermal image information of each position area of the pipeline, and performs positioning correction and denoising treatment. The unmanned aerial vehicle is provided with a digital camera, a thermal infrared imager and an external thermometer, and the unmanned aerial vehicle needs to have a real-time positioning function. The unmanned aerial vehicle is also provided with a searchlight so as to facilitate night patrol. The localization correction and denoising process can be solved by the prior art means.
Step three: comparing image information; graying image information, graying the acquired n times of aerial pictures to obtain a grayscale image, accumulating the grayscale values at the position a in the grayscale image of the previous n-1 times to obtain a cumulative number of grayscale values, and comparing the grayscale value at the position a in the grayscale image of the nth time with the cumulative number of grayscale values to obtain an image change ratio at the position a;
the cumulative number of gray values is calculated by adopting an expression (1):
the image change ratio of the a position is calculated by using the expression (2):
in the expressions (1) and (2),
obtaining the gray value of the nth time at the position a in the gray map;
the cumulative number of gray values of the a position is n-1 times; u image current trust weight factor;
the a position image change ratio is obtained; n is any natural number. The a position represents a minimum monitoring area.
Step four: comparing the thermal image information; performing difference processing on the obtained nth thermal image information and the real-time temperature measured by the external thermometer to obtain the thermal difference value of the a position obtained by nth measurement, accumulating the thermal difference values of the a position for n-1 times to obtain the accumulated thermal difference value number, and then comparing the thermal difference value of the a position obtained by nth measurement with the accumulated thermal difference value number to obtain the temperature change ratio of the a position;
the thermal image information of the position a obtained by the nth measurement is calculated by adopting an expression (3) to obtain:
the accumulated number of the heat difference values is calculated by adopting an expression (4):
the temperature change ratio is calculated by adopting an expression (5):
in expressions (3) to (5), W is the real-time temperature measured by the external thermometer;
acquiring thermal image information of a position a for the nth measurement;
is the thermal difference of the a position;
is front n-1 cumulative number of thermal difference values of a position; v thermal imagery forward trust weight factors;
is a position temperature change ratio; n is any natural number.
Step five: weighting the images and the thermal images; performing weighted analysis, setting a threshold value for judgment, and calculating the change rate of the position a by adopting an expression (6) if the threshold value is w:
in the expression (6) above, the first,
is the rate of change of the a position; m is an image change weight, and l is a thermal image change weight, wherein m + l is 1;
when in use
When the position a is abnormal, the position a is judged to be abnormal.
Step six: local comparison; in order to determine that the abnormal change excludes the external interference as much as possible, the abnormal change needs to be further compared with an adjacent area, as shown in fig. 1, each letter a, b, c, d, e, f, g, h, i in the graph represents a minimum monitoring area, and the size of the area is obtained by taking a common multiple of the resolution of the camera and the resolution of the thermal imager (averaging processing of each point in the area).
Assuming that the position a is the position with abnormal change, the positions b, c, d, e, f, g, h and i are the positions on the adjacent area of the position a, and the average change rate of the positions b, c, d, e, f, g, h and i is taken as
Can be calculated according to expressions (1) to (6)
Setting the determination threshold value as beta when
And a is considered as a possible occurrence position of the leakage accident.
Step seven: manually confirming; and pushing related pictures of the positions where the leakage accidents possibly occur to related responsible persons for manual determination. The manual confirmation can adopt the prior art means to judge whether the leakage accident exists at the position where the leakage accident possibly occurs.
The unmanned aerial vehicle is provided with the digital camera, the thermal infrared imager and the external thermometer, the unmanned aerial vehicle needs to have a real-time positioning function, and the unmanned aerial vehicle is also provided with the searchlight so as to facilitate night patrol; acquiring a digital color photo and an infrared thermography by adopting unmanned aerial vehicle inspection; the image chromatic aberration is combined with the temperature difference, and weighting processing is carried out, so that the recognition rate is greatly improved; through local comparison, external interference is further eliminated, and accuracy of confirming the leakage occurrence position is improved.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A method for inspecting a pipeline for leaks, comprising the steps of:
the method comprises the following steps: initializing; determining pipeline paths, and acquiring image information and thermal image information of each position area of the pipeline in a normal state;
step two: acquiring patrol data; obtaining image information and thermal image information of each position area in a real-time state;
step three: comparing image information; the method comprises the following steps: graying image information, graying the acquired n times of aerial pictures to obtain a grayscale image, accumulating the grayscale values at the position a in the grayscale image of the previous n-1 times to obtain a cumulative number of grayscale values, and comparing the grayscale value at the position a in the grayscale image of the nth time with the cumulative number of grayscale values to obtain an image change ratio at the position a;
the cumulative number of gray values is calculated by adopting an expression (1):
the image change ratio of the a position is calculated by using the expression (2):
in the expressions (1) and (2),
obtaining the gray value of the nth time at the position a in the gray map;
the cumulative number of gray values of the a position is n-1 times; u image current trust weight factor;
the a position image change ratio is obtained; n is any natural number, and the position a represents a minimum monitoring area;
step four: comparing the thermal image information; the method comprises the following steps: performing difference processing on the obtained nth thermal image information and the real-time temperature measured by the external thermometer to obtain the thermal difference value of the a position obtained by nth measurement, accumulating the thermal difference values of the a position for n-1 times to obtain the accumulated thermal difference value number, and then comparing the thermal difference value of the a position obtained by nth measurement with the accumulated thermal difference value number to obtain the temperature change ratio of the a position;
the thermal image information of the position a obtained by the nth measurement is calculated by adopting an expression (3) to obtain:
the accumulated number of the heat difference values is calculated by adopting an expression (4):
the temperature change ratio is calculated by adopting an expression (5):
in expressions (3) to (5), W is the real-time temperature measured by the external thermometer;
acquiring thermal image information of a position a for the nth measurement;
is the thermal difference of the a position;
the cumulative number of the heat difference values of the a positions at the previous n-1 times is obtained; v thermal imagery forward trust weight factors;
is a position temperature change ratio; n is any natural number;
step five: weighting the images and the thermal images; the method comprises the following steps: setting a threshold value for judgment, and if the threshold value is w, calculating the change rate of the position a by adopting an expression (6):
in the expression (6) above, the first,
is the rate of change of the a position; m is an image change weight, and l is a thermal image change weight, wherein m + l is 1;
when in use
Judging that the position a has abnormal change;
step six: local comparison; and eliminating external interference and determining the position where the leakage accident can occur.
2. The pipeline leakage patrol method according to claim 1, wherein the first step is specifically: acquiring image range and precision according to a camera and a thermal imager, and performing initialization information acquisition in sections along the pipeline path; and then splicing the acquired images and the thermograph, and fitting the images into a fixed coordinate system through a fixed reference object.
3. The pipeline leakage patrol method according to claim 2, wherein the second step is specifically: and (3) the unmanned aerial vehicle patrols the pipeline path of the pipeline, acquires image information and thermal image information of each position area of the pipeline, and performs positioning correction and denoising treatment.
4. The pipeline leakage inspection method according to claim 3, wherein the unmanned aerial vehicle is provided with a digital camera, a thermal infrared imager and an external thermometer, and the unmanned aerial vehicle needs to have a real-time positioning function.
5. The pipeline leakage patrol method according to claim 4, wherein the sixth step is specifically: let a be the abnormal change position, and average change rate of a position and each position in the change area around the position
Comparing, setting the judgment threshold value as beta when
The a position is considered as a position where the leakage accident may occur.
6. The pipeline leakage patrol method according to any one of claims 1 to 5, further comprising a seventh step of: manually confirming; and pushing related pictures of the positions where the leakage accidents possibly occur to related responsible persons for manual determination.
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| CN113781513B (en) * | 2021-08-19 | 2023-11-28 | 广东能源集团科学技术研究院有限公司 | Leakage detection method and system for water supply pipeline of power plant |
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