CN108318506B - Intelligent detection method and detection system for pipeline - Google Patents
Intelligent detection method and detection system for pipeline Download PDFInfo
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- CN108318506B CN108318506B CN201810062322.7A CN201810062322A CN108318506B CN 108318506 B CN108318506 B CN 108318506B CN 201810062322 A CN201810062322 A CN 201810062322A CN 108318506 B CN108318506 B CN 108318506B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
- G01N21/954—Inspecting the inner surface of hollow bodies, e.g. bores
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
- G06V20/42—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items of sport video content
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/222—Studio circuitry; Studio devices; Studio equipment
- H04N5/262—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
- G01N21/954—Inspecting the inner surface of hollow bodies, e.g. bores
- G01N2021/9548—Scanning the interior of a cylinder
Abstract
The invention discloses an intelligent detection method and a detection system for a pipeline, wherein the method comprises the following steps: putting a plurality of detection devices which are connected with a mobile terminal in advance in an inspection well at a starting point of a pipeline to be detected; the detection device moves along with the water flow in the pipeline and collects image data in the pipeline in the moving process; when the detection device moves to a terminal inspection well of a pipeline to be detected, the detection device is recovered, and the mobile terminal acquires the position information of the detection device; the mobile terminal downloads the acquired image data from the detection device and transmits the image data to an intelligent terminal for processing and analyzing the image data; and the intelligent terminal performs image stabilization on the image data, generates a pipeline detection video with a virtual stable view field, and automatically identifies the pipeline diseases from the generated pipeline detection video. The invention effectively realizes the accurate detection and positioning of the pipeline diseases, improves the operation efficiency and reduces the economic cost.
Description
Technical Field
The invention relates to the technical field of pipeline measurement and detection, in particular to an intelligent pipeline detection method and system.
Background
Liquid transmission pipelines (such as water supply pipes, water discharge pipes, oil pipelines and the like) are circulation channels frequently used in modern life and production activities for material transportation and discharge. The safe operation of the pipeline is related to the civil and economic production. With the increase of service life, under the long-term action of working environment and conveying liquid, the pipeline inevitably has diseases such as aging, damage, corrosion and the like, so that potential accidents such as liquid leakage, pipeline burst and the like are caused, and disasters such as pavement rupture, collapse and the like are further caused. Therefore, the pipeline needs to be inspected and maintained regularly, the running state of the pipeline needs to be mastered, and potential risks need to be eliminated and eliminated.
At present, the commonly used pipeline detection methods mainly comprise four methods, namely pipeline periscope, pipeline closed-circuit television monitoring, pipeline sonar detection and personnel entry detection. These existing pipeline inspection methods also have some disadvantages. For example, the pipeline periscope can only be used for single-point detection, and cannot acquire the result of the whole pipeline; the pipeline closed circuit television monitoring is in wired control, the working distance is limited, the efficiency is underground, the quick large-range pipeline inspection cannot be realized, the acquired video data lack accurate position information, and the pipeline is required to be ensured to be in a dry state during working; the pipeline sonar equipment has high cost and more complex operation, and can only be used for detecting the pipe wall covered by liquid; personnel get into the detection mode and need a lot of personnel to participate in, and intensity of labour is big, and is inefficiency, and constructor has certain safety risk simultaneously. Therefore, the prior art has the defects of low working efficiency, high labor intensity, high economic cost and the like.
Accordingly, the prior art is yet to be improved and developed.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide an intelligent pipeline detection method and system, aiming at solving the problems of low operation efficiency, high labor intensity, high economic cost, etc. of the pipeline detection method in the prior art.
The technical scheme adopted by the invention for solving the technical problem is as follows:
an intelligent pipeline detection method, wherein the method comprises the following steps:
step A, putting a plurality of detection devices which are connected with a mobile terminal in advance in an inspection well at a starting point of a pipeline to be detected;
b, the detection device moves along with the water flow in the pipeline and collects image data in the pipeline in the moving process;
c, when the detection device moves to a terminal inspection well of the pipeline to be detected, the detection device is recovered, and the mobile terminal acquires the position information of the detection device;
d, the mobile terminal downloads the acquired image data from the detection device and transmits the image data to an intelligent terminal for processing and analyzing the image data;
and E, the intelligent terminal performs image stabilization on the image data to generate a pipeline detection video with a virtual stable view field, and automatically identifies the pipeline diseases from the generated pipeline detection video.
The intelligent pipeline detection method comprises the following steps before the step A:
s, distinguishing a plurality of detection devices for acquiring image data of different detection sections by different colors in advance, wherein each data acquisition module is configured with a unique identification code; and the mobile terminal is connected with the WIFI communication units of the plurality of detection devices through the APP.
The intelligent pipeline detection method comprises the following steps of:
and M, cleaning sludge of the pipeline to be detected, and putting a testing device for testing the passing performance of the pipeline to be detected.
In the method for intelligently detecting a pipeline, the step C of obtaining the position information of the detection device by the mobile terminal specifically includes:
step C1, the mobile terminal determines the starting point and the end point of the detection device through the GNSS positioning system;
step C2, performing segmentation processing on the motion data through a 9-axis MEMS motion sensor in the detection device, analyzing a key topological position in the pipeline through motion characteristics, and obtaining the moment when the detection device passes through the key topological position to obtain a time topological sequence track;
step C3, matching the obtained time topological sequence track with the layout drawing of the pipeline by combining the starting point position to obtain a specific geographic position corresponding to each key topological position and obtain a sparse space track sequence of the motion of the detection device;
and C4, performing Kalman filtering track combination by using the 9-axis MEMS motion data and the position points of the sparse space track, and combining with the characteristic constraint of uniform motion of the detection device during the motion of the linear pipeline to obtain the fine space track of the motion of the detection device.
The intelligent pipeline detection method comprises the following steps:
step D1, after the mobile terminal finishes downloading the image data, initializing the detection device.
In the method for intelligently detecting a pipeline, the step E of stabilizing the image data by the intelligent terminal to generate a pipeline detection video with a virtual stable view field specifically includes:
e1, the intelligent terminal obtains the relative rotation amount of the detection device between two adjacent frames according to the gyro angular velocity integral between two adjacent frames in the image data;
step E2, rotating the current frame to obtain a spherical imaging video which is de-rotated relative to the previous frame;
e3, obtaining the moving direction of the detection device drifting in the water and the rotation angle of the detection device relative to the moving direction according to the fine space track of the movement of the detection device;
and E4, intercepting the image of the area to be detected from the spherical imaging video which rotates relative to the previous frame according to the rotation angle to obtain the pipeline detection video with the virtual stable view field.
The intelligent pipeline detection method includes the following steps of automatically identifying the pipeline disease defect from the generated pipeline detection video in the step E:
e5, performing image gray correction on the generated pipeline detection video of the virtual stable view field;
e6, dividing the image into a pixel-level image, a unit-level image and a block-level image by using a multi-scale strategy disease detection model, and segmenting the image through two calculation processes;
and E7, performing edge tracking on the detected disease area to obtain an edge vector of the disease, extracting the geometric characteristics of the disease, and identifying the disease in the pipeline.
An intelligent pipeline detection system based on any one of the above items, wherein the system comprises: the system comprises a detection device for collecting image data in the pipeline, a mobile terminal for connecting with the detection device and downloading the image data from the detection device, and an intelligent terminal for automatically identifying the pipeline diseases according to the pipeline detection video.
The intelligent pipeline detection system, wherein, the detection device includes: outside waterproof housing, inside electronic module and balancing weight, the spraying has nanometer coating on the outside waterproof housing, is used for detection device and silt adhesion.
The intelligent pipeline detection system, wherein the internal electronic module comprises: the device comprises a positioning and attitude determining unit, an imaging and photographing unit, an integrated control unit and a power supply unit;
the positioning and qualification unit comprises a nine-axis MEMS motion sensor consisting of an MEMS accelerometer, a gyroscope and a magnetometer;
the imaging photographing unit adopts an ultra-wide angle fisheye lens with a horizontal field angle of 360 degrees and a vertical field angle of more than 180 degrees;
the integrated control unit comprises an ARM circuit board, a memory card and a WIFI communication unit;
the power supply unit comprises a lithium battery and a power management circuit.
The invention has the beneficial effects that: the invention adopts the detection device with unpowered design to acquire image data of the pipeline, realizes position calculation of the detection device through images and 9-axis MEMS inertial navigation, and realizes pipeline diseases and disease analysis by using an image analysis technology, thereby effectively realizing accurate detection and positioning of the pipeline diseases, improving the operation efficiency and reducing the economic cost.
Drawings
FIG. 1 is a flow chart of a preferred embodiment of the intelligent pipeline detection method of the present invention.
Fig. 2 is an imaging schematic diagram of an imaging photographing unit of the intelligent pipeline detection method.
FIG. 3 is a functional block diagram of the intelligent pipeline inspection system of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the defects of the existing pipeline detection method, the invention provides an intelligent pipeline detection method, as shown in fig. 1, fig. 1 is a flow chart of a preferred embodiment of the intelligent pipeline detection method. The intelligent pipeline detection method comprises the following steps:
and S100, putting a plurality of detection devices which are connected with the mobile terminal in advance in a starting point inspection well of the pipeline to be detected.
During specific implementation, in the detection operation, in order to ensure the trafficability characteristic of the pipeline to be detected, before formal operation, the pipeline can be selected to be desilted, and a testing device is put in to test the trafficability characteristic of the pipeline to be detected. In addition, in order to avoid that individual detection devices are stranded by sundries and sludge in the pipeline, a plurality of detection devices are put in an inspection well at the upper starting point of the pipeline to be detected, the detection devices for acquiring image data of different detection sections are distinguished by different colors, each data acquisition module is configured with a unique identification code, and a mobile terminal (such as a mobile phone) is connected with WIFI communication units of the detection devices through an APP (application program) so as to better monitor the detection devices and facilitate the mobile terminal to acquire positioning information of the detection devices.
And S200, the detection device moves along with the water flow in the pipeline and collects image data in the pipeline in the moving process.
The detection device is designed in an unpowered way, can directly move along with water flow in the pipeline, and can be designed according to the fluid mechanics principle in order to enable the detection device to have sufficient time for taking pictures in the pipeline, so that the detection device can be slower than the water flow. Meanwhile, in order to ensure that the detection device can stably acquire image data and ensure the imaging quality, a stabilizing module can be arranged at the lower part of the detection device.
Specifically, the detection device of the present invention includes: outside waterproof housing, inside electronic module and balancing weight, the last spraying of outside waterproof housing has special nanometer coating, is used for detection device and silt adhesion. The whole detection device adopts a waterproof design, and the internal electronic module is protected from being affected by water immersion.
Further, the internal electronics module of the detection device comprises: the device comprises a positioning and attitude determining unit, an imaging and photographing unit, an integrated control unit and a power supply unit. The positioning and qualification unit comprises a nine-axis MEMS motion sensor consisting of sensors such as an MEMS accelerometer, a gyroscope, a magnetometer and the like; the imaging photographing unit comprises an illumination (infrared or visible light) and an ultra-wide angle fisheye lens with a horizontal field angle of 360 degrees and a vertical field angle of more than 180 degrees, so that the photographing stability is ensured. The imaging photographing unit provides visual state data of the inner wall of the pipeline on the one hand, and can assist in motion estimation on the other hand to position and fix the posture of the detection device. The integrated control unit comprises an ARM circuit board, a memory card and a WIFI communication unit; the integrated control unit can realize the functions of connection with a mobile terminal (such as a mobile phone), data acquisition control, data downloading and the like. The power supply unit comprises a lithium battery and a power management circuit.
And S300, when the detection device moves to the terminal inspection well of the pipeline to be detected, the detection device is recovered, and the mobile terminal acquires the position information of the detection device.
The invention combines the existing pipeline layout drawing, when the detection device moves to the terminal inspection well of the pipeline to be detected, the detection device is recovered, and the position information of the detection device is obtained. Because the inside of the pipeline is a closed environment, common wireless positioning methods such as GNSS (global navigation satellite system) and mobile phone base station positioning cannot perform normal positioning. The invention provides a pipeline internal positioning method based on 9-axis MEMS inertial navigation (a three-axis gyroscope, a three-axis accelerometer and a three-axis magnetometer) and visual and pipeline map data combination. Specifically, the mobile terminal is connected with the detection device through the APP, and determines the starting point and the end point of the detection device by utilizing the GNSS positioning system. And then, carrying out sectional processing on the motion data through a 9-axis MEMS motion sensor in the detection device, analyzing key topological positions (such as a drop well and a turning lamp) in the pipeline through motion characteristics, and obtaining the time when the detection device passes through the key topological positions to obtain a time topological sequence track. Further, matching the obtained time topological sequence track with the layout drawing of the pipeline by combining the starting point position to obtain a specific geographic position corresponding to each key topological position, and obtaining a sparse space track sequence of the motion of the detection device. And finally, performing Kalman filtering track combination by using the 9-axis MEMS motion data and the position points of the sparse space track, and combining with the characteristic constraint of uniform motion of the detection device during the motion of the linear pipeline to obtain the fine space track of the motion of the detection device. Through the steps, the position information of the detection device can be accurately acquired.
And S400, downloading the acquired image data from the detection device by the mobile terminal, and transmitting the image data to an intelligent terminal for processing and analyzing the image data.
After the mobile terminal recovers the detection device, the image data is downloaded from the detection device, and after the downloading is completed, the detection device is initialized, so that the next operation is facilitated. The mobile terminal transmits the downloaded image data to an intelligent terminal (such as a computer), and the image data is processed and analyzed through the intelligent terminal.
And S500, the intelligent terminal performs image stabilization on the image data to generate a pipeline detection video with a virtual stable view field, and automatically identifies the pipeline diseases from the generated pipeline detection video.
When drifting in a pipeline, the detection device of the invention is influenced by uncertain turbulence, and generates irregular motions such as rotation around the axial direction of gravity, swing in the horizontal direction and the like. These irregular movements eventually cause the captured detection video to have a severely sloshing field of view and degraded quality. In order to eliminate the negative effects, the invention provides a virtual stable visual field detection video generation method. The invention adopts an ultra-wide angle fish-eye lens with a horizontal field angle of 360 degrees and a vertical field angle of more than 180 degrees to acquire video images, as shown in fig. 2, fig. 2 is an imaging schematic diagram of an imaging photographing unit of the intelligent pipeline detection method, and an imaging surface of the imaging photographing unit is hemispherical. Due to the presence of the rotational or rocking motion, the region of the pipeline wall of interest to the user to be detected does not exist stably in a fixed region of the image. In order to obtain a detection video with a stable visual angle, the intelligent terminal obtains the relative rotation amount of the detection device between two adjacent frames according to the gyro angular velocity integral between two adjacent frames in the image data; and then, rotating the current frame to obtain a spherical imaging video which is deswirl relative to the previous frame. According to the fine space track of the movement of the detection device, the movement direction of the detection device drifting in the water and the rotation angle of the detection device relative to the movement direction are obtained; and then according to the rotation angle, intercepting the image of the area to be detected from the spherical imaging video which rotates relative to the previous frame to obtain the pipeline detection video with the virtual stable view field.
The method comprises the following steps that the intelligent terminal can automatically identify the pipeline diseases according to a pipeline detection video, the common pipeline diseases mainly comprise breakage, dislocation, deformation, siltation and the like, specifically, the image gray level correction is firstly carried out on the generated pipeline detection video with a virtual stable view field, when the pipeline video image is obtained, the requirement of a camera on illumination is high, the illumination nonuniformity causes the formed image to generate strip-shaped stripes, the detection result loses significance due to excessive longitudinal noise, and the auxiliary illumination image I (p) containing cracks mainly comprises ① pipeline background signals Ib (p), ② pipeline crack signals ic (p), ③ random noise signals in (p) and noise signals Ia (p) caused by ④ auxiliary illumination nonuniformity, wherein the components can be expressed as:
. Then, the difference between each pixel of the image line and the average value of the image line is calculated to obtain a difference image line, then least square fitting is carried out on the difference image line by using a sine function to obtain the sine parameter of Ia (p) component, and then Ia (p) gray level difference value of each pixel is calculated to be used as the unit gray level compensation elimination Ia (p) component, and the image after gray level correction is the image
。
Further, a multi-scale strategy disease detection model is used, the image is divided into a pixel level image, a unit level image and a block level image, and the image is divided through two calculation processes, so that diseases such as cracks are detected. The specific calculation process is as follows:
a. the method is based on pixel-level to unit-level image gray scale calculation, and can eliminate the influence of random noise and reduce the time calculation dimension. Selecting a 4 × 4 pixel window as a unit, calculating a unit gray value:
b. Secondly, the image blocks based on the unit level are subjected to differential histogram segmentation. Calculating the statistic value of pixel variation of a certain gray level g in eight fields
Accordingly, a gradation division threshold value is determined
，
Converting the gray image into a binary image according to the threshold,
m and n represent the number of cells in the horizontal and vertical directions of the block image, respectively.
Furthermore, by performing edge tracking on the detected crack region, an edge vector of the crack is obtained, which is a basis for extracting geometric features of the crack, and the geometric features are an important component of crack classification. For a general closed geometric figure, the geometric features thereof are classified into three main categories: point-like features, line-like features, and surface-like features. The three types of characteristics can reflect the types of the cracks in different degrees, so that better basic data are provided for crack classification. And extracting the geometric characteristics of the pipeline diseases so as to identify the diseases in the pipeline.
Based on the above embodiments, the present invention provides an intelligent pipeline detection system, as shown in fig. 3, fig. 3 is a functional schematic block diagram of the intelligent pipeline detection system of the present invention. The system comprises: the system comprises a detection device 310 for collecting image data in the pipeline, a mobile terminal 320 for connecting with the detection device 310 and downloading the image data from the detection device 310, and an intelligent terminal 330 for automatically identifying the pipeline diseases according to a pipeline detection video. Mobile terminal 320 can be connected with the built-in WIFI communication unit in detection device 310 through APP, and mobile terminal 320 and intelligent terminal 330 can carry out data transmission through technologies such as bluetooth and WIFI.
Further, the detecting device 310 includes: outside waterproof housing, inside electronic module and balancing weight, the spraying has nanometer coating on the outside waterproof housing, is used for detection device and silt adhesion.
Further, the internal electronics module comprises: the device comprises a positioning and attitude determining unit, an imaging and photographing unit, an integrated control unit and a power supply unit; the positioning and qualification unit comprises a nine-axis MEMS motion sensor consisting of an MEMS accelerometer, a gyroscope and a magnetometer; the imaging photographing unit adopts an ultra-wide angle fisheye lens with a horizontal field angle of 360 degrees and a vertical field angle of more than 180 degrees; the integrated control unit comprises an ARM circuit board, a memory card and a WIFI communication assembly; the power supply unit comprises a lithium battery and a power management circuit.
In summary, the method and system for intelligently detecting a pipeline provided by the present invention include: putting a plurality of detection devices which are connected with a mobile terminal in advance in an inspection well at a starting point of a pipeline to be detected; the detection device moves along with the water flow in the pipeline and collects image data in the pipeline in the moving process; when the detection device moves to a terminal inspection well of a pipeline to be detected, the detection device is recovered, and the mobile terminal acquires the position information of the detection device; the mobile terminal downloads the acquired image data from the detection device and transmits the image data to an intelligent terminal for processing and analyzing the image data; and the intelligent terminal performs image stabilization on the image data, generates a pipeline detection video with a virtual stable view field, and automatically identifies the pipeline diseases from the generated pipeline detection video. The invention effectively realizes the accurate detection and positioning of the pipeline diseases, improves the operation efficiency and reduces the economic cost.
It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.
Claims (8)
1. An intelligent pipeline detection method is characterized by comprising the following steps:
step A, putting a plurality of detection devices which are connected with a mobile terminal in advance in an inspection well at a starting point of a pipeline to be detected;
b, the detection device moves along with the water flow in the pipeline and collects image data in the pipeline in the moving process;
c, when the detection device moves to a terminal inspection well of the pipeline to be detected, the detection device is recovered, and the mobile terminal acquires the position information of the detection device;
d, the mobile terminal downloads the acquired image data from the detection device and transmits the image data to an intelligent terminal for processing and analyzing the image data;
e, the intelligent terminal performs image stabilization on the image data to generate a pipeline detection video with a virtual stable view field, and automatically identifies the pipeline diseases from the generated pipeline detection video;
the intelligent terminal in the step E performs image stabilization on the image data, and generating a pipeline detection video with a virtual stable view field specifically includes:
e1, the intelligent terminal obtains the relative rotation amount of the detection device between two adjacent frames according to the gyro angular velocity integral between two adjacent frames in the image data;
step E2, rotating the current frame to obtain a spherical imaging video which is de-rotated relative to the previous frame;
e3, obtaining the moving direction of the detection device drifting in the water and the rotation angle of the detection device relative to the moving direction according to the fine space track of the movement of the detection device;
step E4, according to the rotation angle, intercepting an image of a region to be detected from the spherical imaging video which rotates relative to the previous frame to obtain a pipeline detection video with a virtual stable view field;
the step C of the mobile terminal acquiring the position information of the detection device specifically includes:
step C1, the mobile terminal determines the starting point and the end point of the detection device through the GNSS positioning system;
step C2, performing segmentation processing on the motion data through a 9-axis MEMS motion sensor in the detection device, analyzing a key topological position in the pipeline through motion characteristics, and obtaining the moment when the detection device passes through the key topological position to obtain a time topological sequence track;
step C3, matching the obtained time topological sequence track with the layout drawing of the pipeline by combining the starting point position to obtain a specific geographic position corresponding to each key topological position and obtain a sparse space track sequence of the motion of the detection device;
and C4, performing Kalman filtering track combination by using the 9-axis MEMS motion data and the position points of the sparse space track, and combining with the characteristic constraint of uniform motion of the detection device during the motion of the linear pipeline to obtain the fine space track of the motion of the detection device.
2. The intelligent pipeline inspection method of claim 1, wherein step a is preceded by:
s, distinguishing a plurality of detection devices for acquiring image data of different detection sections by different colors in advance, wherein each data acquisition module is configured with a unique identification code; and the mobile terminal is connected with the WIFI communication units of the plurality of detection devices through the APP.
3. The intelligent pipeline inspection method of claim 1, wherein step a is preceded by the steps of:
and M, cleaning sludge of the pipeline to be detected, and putting a testing device for testing the passing performance of the pipeline to be detected.
4. The intelligent pipeline inspection method of claim 1, wherein step D further comprises:
step D1, after the mobile terminal finishes downloading the image data, initializing the detection device.
5. The intelligent pipeline detection method according to claim 1, wherein the step E of automatically identifying the pipeline fault defect from the generated pipeline detection video specifically comprises:
e5, performing image gray correction on the generated pipeline detection video of the virtual stable view field;
e6, dividing the image into a pixel-level image, a unit-level image and a block-level image by using a multi-scale strategy disease detection model, and segmenting the image through two calculation processes;
e7, performing edge tracking on the detected disease area to obtain an edge vector of the disease, extracting the geometric characteristics of the disease, and identifying the disease in the pipeline;
the two calculation processes comprise: the image gray scale calculation from pixel level to unit level and the differential histogram segmentation of the image block based on unit level are carried out.
6. An intelligent pipeline detection system based on the intelligent pipeline detection method of any one of claims 1 to 5, the system comprising: the system comprises a detection device for collecting image data in the pipeline, a mobile terminal for connecting with the detection device and downloading the image data from the detection device, and an intelligent terminal for automatically identifying the pipeline diseases according to the pipeline detection video.
7. The intelligent pipeline inspection system of claim 6, wherein the inspection device comprises: outside waterproof housing, inside electronic module and balancing weight, the spraying has nanometer coating on the outside waterproof housing, is used for preventing detection device and silt adhesion.
8. The intelligent pipeline inspection system of claim 7, wherein the internal electronics module comprises: the device comprises a positioning and attitude determining unit, an imaging and photographing unit, an integrated control unit and a power supply unit;
the positioning and attitude determining unit comprises a nine-axis MEMS motion sensor consisting of an MEMS accelerometer, a gyroscope and a magnetometer;
the imaging and photographing unit adopts an ultra-wide angle fisheye lens with a horizontal field angle of 360 degrees and a vertical field angle of more than 180 degrees;
the integrated control unit comprises an ARM circuit board, a memory card and a WIFI communication unit;
the power supply unit comprises a lithium battery and a power management circuit.
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