CN116071962B - Automatic inspection system of highway unmanned aerial vehicle - Google Patents

Automatic inspection system of highway unmanned aerial vehicle Download PDF

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Publication number
CN116071962B
CN116071962B CN202310165269.4A CN202310165269A CN116071962B CN 116071962 B CN116071962 B CN 116071962B CN 202310165269 A CN202310165269 A CN 202310165269A CN 116071962 B CN116071962 B CN 116071962B
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road section
disease
parameter
highway
module
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CN116071962A (en
Inventor
张强
李永飞
苏志勇
刘奋仁
袁树勇
樊智敏
郭建勋
段志东
王伟
党利军
张跃强
陈丽英
郭靖
童飞
石义
刘中锐
周春雪
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Inner Mongolia Jiaoke Road And Bridge Construction Co ltd
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Inner Mongolia Jiaoke Road And Bridge Construction Co ltd
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0073—Surveillance aids
    • G08G5/0078—Surveillance aids for monitoring traffic from the aircraft
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0047—Navigation or guidance aids for a single aircraft
    • G08G5/0052—Navigation or guidance aids for a single aircraft for cruising
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0047—Navigation or guidance aids for a single aircraft
    • G08G5/0069—Navigation or guidance aids for a single aircraft specially adapted for an unmanned aircraft
    • 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
    • H04N7/183—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a single remote source
    • H04N7/185—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a single remote source from a mobile camera, e.g. for remote control
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/029—Location-based management or tracking services

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Signal Processing (AREA)
  • Multimedia (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention relates to the field of aircraft operation, in particular to an automatic inspection system of a highway unmanned aerial vehicle, which comprises an unmanned airport, an information acquisition module, a highway maintenance operation platform and a task management module, wherein the unmanned airport is used for realizing the take-off operation of the unmanned aerial vehicle and the landing operation of the unmanned aerial vehicle, the information acquisition module is used for acquiring the image information and the position information of a road section to be inspected, the highway maintenance operation platform is used for estimating the maintenance time of a disease road section according to the image information of the road section to be inspected, the task management module is used for matching the position information of the disease road section with the corresponding estimated maintenance time, and the inspection route of the unmanned aerial vehicle is re-planned according to the position information of the disease road section and the corresponding estimated maintenance time information. The invention re-plans the routing inspection route through the combined action of data measurement, parameter calculation and maintenance time estimation of the damaged road section, and can solve the problem of reduced working efficiency and working accuracy of the system caused by repeated working contents.

Description

Automatic inspection system of highway unmanned aerial vehicle
Technical Field
The invention relates to the field of aircraft operation, in particular to an automatic inspection system of a highway unmanned plane.
Background
In daily work and life at present, unmanned aerial vehicle flight technology is mature day by day, and unmanned aerial vehicle inspection technology has been applied to electric power, agriculture and forestry, exploration, movie & TV, law enforcement and rescue specialty field, replaces the manual inspection to specific acquisition target, shows splendid technological application effect, and the manpower sparingly development prospect is big.
The invention discloses an automatic unmanned aerial vehicle inspection system and method, wherein an area to be inspected is divided into a plurality of square areas by an unmanned aerial vehicle management and control platform, an airport body and an airport background command system are arranged in each area, and a plurality of unmanned aerial vehicles in each area are uniformly managed and controlled by the unmanned aerial vehicle management and control platform, so that inspection efficiency is improved;
However, the automatic inspection mode provided by the invention does not need manual operation of the unmanned aerial vehicle for inspection, but because the load equipment of the unmanned aerial vehicle is fixed, real-time multi-type tasks cannot be inspected, and the repetition of inspection paths inevitably leads to the repetition of the working contents of the unmanned aerial vehicle, so that useless workload is increased, and the working efficiency and the working accuracy of the system are reduced.
Disclosure of Invention
Therefore, the invention provides an automatic inspection system for a highway unmanned aerial vehicle, which can solve the problem that the working efficiency and the working precision of the system are reduced due to the repetition of working contents.
In order to achieve the above object, the present invention provides an automatic inspection system for a highway unmanned aerial vehicle, comprising:
the unmanned aerial vehicle airport is arranged on the road section to be inspected and is used for realizing the take-off operation of the unmanned aerial vehicle and the landing operation of the unmanned aerial vehicle;
the information acquisition module is arranged on the unmanned aerial vehicle and used for acquiring image information and position information of a road section to be inspected;
The highway maintenance operation platform is connected with the information acquisition module, internally provided with historical big data information and various calculation parameters of a road section to be inspected, and used for estimating maintenance time of a disease road section according to image information of the road section to be inspected and matching the position information of the disease road section with corresponding estimated maintenance time, and comprises an information extraction module, a measurement module, a disease parameter calculation module, a disease degree judgment module, a maintenance time estimation module and an information arrangement module;
the information extraction module is connected with the information acquisition module and is used for extracting the image information and the position information of the damaged road section from the image information and the position information of the road section to be inspected;
The measuring module is connected with the information extracting module and used for measuring data to be calculated from the image information of the disease road section;
the disease parameter calculation module is connected with the measurement module and used for calculating disease parameters according to the data to be calculated of the measurement of the disease road section;
the disease degree judging module is connected with the disease parameter calculating module and is used for judging the disease degree of the disease road section according to the size of the disease parameter;
The maintenance time estimating module is connected with the disease degree judging module and is used for estimating the maintenance time of the disease road section according to the disease degree;
The information arrangement module is respectively connected with the information extraction module and the maintenance time estimation module and is used for matching the position information of the damaged road section with the corresponding estimated maintenance time;
and the task management module is respectively connected with the unmanned aerial vehicle and the information arrangement module and is used for rescheduling the inspection route of the unmanned aerial vehicle according to the position information of the damaged road section and the corresponding estimated maintenance time information.
Further, the unmanned airports include a starting unmanned airport, a finishing unmanned airport and a plurality of intermediate unmanned airports;
The first starting point unmanned aerial vehicle airport is arranged at the starting point of the road section to be inspected and used for realizing the take-off operation in the course of going out of the unmanned aerial vehicle and the landing operation in the course of returning back of the unmanned aerial vehicle;
the terminal unmanned aerial vehicle airport is arranged at the terminal of the road section to be inspected and used for realizing take-off operation in the process of returning the unmanned aerial vehicle and landing operation in the process of going the unmanned aerial vehicle;
The middle unmanned aerial vehicle takes the starting point unmanned aerial vehicle as a starting point, and is equidistantly arranged on the section to be inspected along the section to be inspected by taking a preset distance L0 as a distance, so as to realize the take-off and landing work in the round trip process of the unmanned aerial vehicle, wherein the preset distance L0 is the maximum diameter of the signal receiving range of the unmanned aerial vehicle.
Further, the total length L of the road sections to be inspected and the preset distance L0 are calculated according to a formula [ L/L0] -1 to obtain the number N of the intermediate unmanned airports, the road sections from the starting unmanned airport to the first intermediate unmanned airport are set as a first road section, the (N-1) th road section from the intermediate unmanned airport to the N th intermediate unmanned airport is set as an N-th road section, and the N-th road section from the intermediate unmanned airport to the end unmanned airport is set as an (N+1) th road section, wherein N is a positive integer.
Further, the information acquisition module comprises an image acquisition unit, a laser imaging unit and a GPS positioning unit, wherein the image acquisition unit, the laser imaging unit and the GPS positioning unit are all arranged on the unmanned aerial vehicle and are mutually independent;
the image acquisition unit is connected with the information extraction module and is used for acquiring image information of a road section to be inspected through the camera device;
The laser imaging unit is connected with the information extraction module and is used for returning and filtering vegetation through laser multiple reflection to obtain a real topography image of a diseased road section;
The GPS positioning unit is connected with the information extraction module and used for determining the real-time position of the unmanned aerial vehicle and acquiring the position information of the diseased road section.
Further, the information extraction module is used for extracting image information and position information of the damaged road section from the image information and the position information of the road section to be inspected;
The image information of the damaged road section comprises image information of a road crack section, image information of a road pit slot section and image information of a road sand accumulation section, the image information of the road crack section is set to be first image information, the image information of the road pit slot section is set to be second image information, and the image information of the road sand accumulation section is set to be third image information;
The position information of the damaged road section comprises position information of a road crack section, position information of a road pit slot section and position information of a road sand accumulation section, the position information of the road crack section is set to be first position information, the image information of the road pit slot section is set to be second position information, the image information of the road sand accumulation section is set to be third position information, and the first position information, the second position information and the third position information are sent to the information arrangement module.
Further, the measurement module is configured to measure a length L1 of the highway crack and a depth H1 of the highway crack in the first image information, set the length L1 of the highway crack as a first length, set the depth H1 of the highway crack as a first height, and send the first length L1 and the first height H1 to the disease parameter calculation module for calculating a disease parameter of the first image information;
The measuring module is used for measuring the length L2 of the highway pit slot, the width W1 of the highway pit slot and the depth H2 of the highway pit slot in the second image information, setting the length L2 of the highway pit slot as a second length, setting the width W1 of the highway pit slot as a first width, setting the depth H2 of the highway pit slot as a second height, and sending the second length L2, the first width W1 and the second height H2 to the disease parameter calculating module for calculating the disease parameters of the second image information;
the measurement module is configured to measure a length L3 of the highway deposited sand, a width W2 of the highway deposited sand, and a thickness H3 of the highway deposited sand in the third image information, set the length L3 of the highway deposited sand as a third length, set the width W2 of the highway deposited sand as a second width, set the thickness H3 of the highway deposited sand as a third height, and send the third length L3, the second width W2, and the third height H3 to the disease parameter calculation module for calculating a disease parameter of the third image information.
Further, the disease parameter calculation module presets that an influence parameter of the first length L1 is a first parameter k1, an influence parameter of the first height H1 is a second parameter k2, an influence parameter of the second length L1 is a third parameter k3, an influence parameter of the first width W1 is a fourth parameter k4, an influence parameter of the second height H2 is a fifth parameter k5, an influence parameter of the third length L3 is a sixth parameter k6, an influence parameter of the second width W2 is a seventh parameter k7, and an influence parameter of the third height H3 is an eighth parameter k8 according to big data provided by a platform;
The disease parameter calculation module is configured to calculate the first length L1, the first height H1, the first parameter k1, and the second parameter k2 according to a formula (l1×k1) + (h1×k2) =p1 to obtain a disease parameter of the first image information, and set the disease parameter as a first disease parameter P1;
the disease parameter calculation module is configured to calculate the second length L2, the first width W1, the second height H2, the third parameter k3, the fourth parameter k4, and the fifth parameter k5 according to a formula (l2×k3) + (w1×k4) + (h2×k5) =p2) to obtain a disease parameter of the second image information, and set the disease parameter as a second disease parameter P2;
The disease parameter calculation module is configured to calculate a disease parameter of the third image information according to a formula (l3×k6) + (w2×k7) + (h3×k8) =p3) from the third length L3, the second width W2, the third height H3, the sixth parameter k6, the seventh parameter k7, and the eighth parameter k8, and set the disease parameter as a third disease parameter P3;
The disease degree judging module is further used for judging the disease degree of the disease road section according to the size of the disease parameter, presetting PA as a first preset parameter of a highway crack, PB as a second preset parameter of the highway crack, PC as a first preset parameter of a highway pit slot, PD as a second preset parameter of the highway pit slot, PE as a preset parameter of a highway product Sha Di, PF as a second preset parameter of a highway product Sha Di, wherein the second preset parameter PB of the highway crack is larger than the first preset parameter PA of the highway crack, the second preset parameter PD of the highway pit slot is larger than the first preset parameter PC of the highway pit slot, and the second preset parameter PF of the highway product Sha Di is larger than the first preset parameter PE of the highway product Sha Di;
When P1 is less than or equal to PA, the damaged road section is a first-stage crack damage, when PA is less than P1 and less than PB, the damaged road section is a second-stage crack damage, and when P1 is more than or equal to PB, the damaged road section is a third-stage crack damage;
When P2 is less than or equal to PC, the disease road section is primary pit groove disease, when PC is less than P2 and less than PD, the disease road section is secondary pit groove disease, and when P2 is more than or equal to PD, the disease road section is tertiary pit groove disease;
when P3 is less than or equal to PE, the disease road section is a first product Sha Binghai, when PE is less than P3 and less than PF, the disease road section is a second product Sha Binghai, and when P3 is more than or equal to PF, the disease road section is a third product sand disease.
Further, the maintenance time estimating module is used for estimating the maintenance time of the damaged road section according to the damage degree;
when the damaged road section is the primary crack damage, the maintenance time of the damaged road section is estimated to be a days, when the damaged road section is the secondary crack damage, the maintenance time of the damaged road section is estimated to be b days, and when the damaged road section is the tertiary crack damage, the maintenance time of the damaged road section is estimated to be c days, wherein c is larger than b is larger than a;
When the damaged road section is the primary pit slot damage, the maintenance time of the damaged road section is estimated to be d days, when the damaged road section is the secondary pit slot damage, the maintenance time of the damaged road section is estimated to be e days, and when the damaged road section is the tertiary pit slot damage, the maintenance time of the damaged road section is estimated to be f days, wherein f is more than e and more than d;
and when the damaged road section is the first-stage sand accumulation damage, the maintenance time of the damaged road section is estimated to be g days, when the damaged road section is the second-stage sand accumulation damage, the maintenance time of the damaged road section is estimated to be h days, and when the damaged road section is the third-stage sand accumulation damage, the maintenance time of the damaged road section is estimated to be i days, wherein i is more than h and more than g.
Further, the information arrangement module is used for matching the position information of the damaged road section with the corresponding estimated maintenance time;
the information arrangement module is used for judging a road section where the first position information, the second position information and the third position information are located, and setting a data pair obtained by matching the estimated maintenance time corresponding to the road section with the middle unmanned airport corresponding to the road section as a target data pair;
Obtaining X target data pairs according to the number X of the damaged road sections in the road sections to be inspected, uploading the obtained X target data pairs to the road maintenance operation platform and carrying out maintenance work;
When the same road section comprises a plurality of target data pairs, comparing the size relation of the estimated maintenance time in each target data pair, only reserving a group of target data pairs with the maximum estimated maintenance time, and sending all the reserved target data pairs to the task management module for rescheduling the inspection route of the unmanned aerial vehicle according to the target data.
Further, the task management module is used for rescheduling a routing inspection route of the unmanned aerial vehicle according to the target data;
And after receiving the target data pair, the task management module eliminates the intermediate unmanned aerial vehicle corresponding to the disease road section in the target data pair from the preset path of the unmanned aerial vehicle within the estimated maintenance time corresponding to the target data pair, and re-plans the inspection route of the unmanned aerial vehicle.
Compared with the prior art, the system has the advantages that the system runs along the road section to be inspected for the first time completely and simultaneously acquires the road section information along the road section by the information acquisition module, extracts the road section with the disease therein for further feature extraction and data calculation, thereby evaluating the disease severity of the road section with the disease according to the parameter magnitude relation obtained by calculation, then estimating the maintenance time of the road section with the disease according to the disease severity, reasonably skipping some road sections to be inspected by the regulation and control of the task management module in the subsequent inspection, re-planning the inspection route of the unmanned aerial vehicle, storing mass data about the road section to be inspected by the highway maintenance operation platform based on the large data in the prior art, enabling the calculation result of the system to be more accurate based on the parameters obtained by the correction of the data, effectively avoiding repeated inspection of the road section by the unmanned aerial vehicle re-planned by the system, effectively improving the working efficiency of the system on the premise of not affecting the work, and solving the problem of the reduction of the working efficiency and working precision of the system due to the repetition of the working content.
In particular, the disease conditions facing the highway to be inspected have diversity and can not be mixed together at work, the image information is finely classified into a highway crack section, a highway pit slot section and a highway sand accumulation section in the extraction process, the disease section is subdivided, so that more accurate estimated maintenance time is facilitated, the working efficiency of the system is improved, different disease conditions are greatly different in specific maintenance construction methods, and the classification and the separate treatment can further improve the working efficiency of the system.
In particular, the first disease parameter P1, the first disease parameter P2 and the first disease parameter P3 are obtained through calculation according to measured data, the disease degree of the highway crack is judged according to the magnitude relation between the first disease parameter P1 and the first preset parameter PA of the highway crack and the second preset parameter PB of the highway crack, the disease degree of the highway pit is judged according to the magnitude relation between the second disease parameter P2 and the first preset parameter PC of the highway pit and the second preset parameter PD of the highway pit, the disease degree of the highway sand is judged according to the magnitude relation between the third disease parameter P3 and the first preset parameter PE of the highway product Sha Di and the second preset parameter PF of the highway product Sha Di, and the classification judgment of the disease degree severity refines the working process from shallow to deep, so that the obtained result is more accurate, and the working precision of the system is further improved.
Drawings
Fig. 1 is a simple block diagram of an automatic inspection system for an unmanned aerial vehicle according to an embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1, an automatic inspection system for a highway unmanned aerial vehicle according to an embodiment of the present invention includes:
The Unmanned Aerial Vehicle (UAV) 1 is arranged on a road section to be inspected and is used for realizing take-off operation of the UAV and landing operation of the UAV;
The information acquisition module 2 is arranged on the unmanned aerial vehicle and is used for acquiring image information and position information of a road section to be inspected;
The highway maintenance operation platform 10 is connected with the information acquisition module 2, is internally provided with historical big data information and various calculation parameters of a road section to be inspected, and is used for estimating maintenance time of a disease road section according to image information of the road section to be inspected and matching the position information of the disease road section with corresponding estimated maintenance time, and comprises an information extraction module 101, a measurement module 102, a disease parameter calculation module 103, a disease degree judgment module 104, a maintenance time estimation module 105 and an information arrangement module 106;
The information extraction module 101 is connected with the information acquisition module 2, and is used for extracting image information and position information of a disease road section from the image information and the position information of the road section to be inspected;
The measuring module 102 is connected with the information extracting module 101 and is used for measuring data to be calculated from the image information of the disease road section;
the disease parameter calculation module 103 is connected with the measurement module 102 and is used for calculating disease parameters according to the measured data to be calculated of the disease road section;
The disease degree judging module 104 is connected with the disease parameter calculating module 103 and is used for judging the disease degree of the disease road section according to the size of the disease parameter;
the maintenance time estimating module 105 is connected to the disease degree judging module 104, and is configured to estimate maintenance time of the disease road section according to the disease degree;
The information sorting module 106 is respectively connected with the information extraction module 101 and the maintenance time estimation module 105, and is used for matching the position information of the damaged road section with the corresponding estimated maintenance time;
and the task management module 3 is respectively connected with the unmanned aerial vehicle and the information arrangement module and is used for rescheduling the inspection route of the unmanned aerial vehicle according to the position information of the damaged road section and the corresponding estimated maintenance time information.
Specifically, the system runs along the road section to be inspected completely and simultaneously the information acquisition module acquires the road section information along the road section when running for the first time, and extracts the road section with the disease to perform further feature extraction and data calculation, so that the disease severity of the road section with the disease is estimated according to the parameter size relationship obtained by calculation, the maintenance time of the road section with the disease is estimated according to the disease severity, and in the subsequent inspection, some road sections to be inspected are reasonably skipped through the regulation and control of the task management module, and the inspection route of the unmanned aerial vehicle is re-planned.
Specifically, the highway maintenance operation platform can store mass data about a road section to be inspected based on big data in the prior art, and parameters obtained based on data correction can enable a calculation result of a system to be more accurate.
Specifically, the unmanned airport 1 includes a starting unmanned airport, a finishing unmanned airport, and a plurality of intermediate unmanned airports;
The first starting point unmanned aerial vehicle airport is arranged at the starting point of the road section to be inspected and used for realizing the take-off operation in the course of going out of the unmanned aerial vehicle and the landing operation in the course of returning back of the unmanned aerial vehicle;
the terminal unmanned aerial vehicle airport is arranged at the terminal of the road section to be inspected and used for realizing take-off operation in the process of returning the unmanned aerial vehicle and landing operation in the process of going the unmanned aerial vehicle;
The middle unmanned aerial vehicle takes the starting point unmanned aerial vehicle as a starting point, and is equidistantly arranged on the section to be inspected along the section to be inspected by taking a preset distance L0 as a distance, so as to realize the take-off and landing work in the round trip process of the unmanned aerial vehicle, wherein the preset distance L0 is the maximum diameter of the signal receiving range of the unmanned aerial vehicle.
Specifically, the unmanned aerial vehicle airport can also play a role in monitoring and maintaining the working state of the unmanned aerial vehicle, and ensure that the electric quantity is sufficient when the unmanned aerial vehicle works.
Specifically, setting up a plurality of unmanned aerial vehicle field on waiting to patrol and examine the highway section and can improving the efficiency of patrolling and examining of system, increased the stability of system implementation scheme, wherein middle unmanned aerial vehicle field regard as the starting point along waiting to patrol and examine the highway section and regard preset distance L0 as the equidistant purpose that sets up in waiting to patrol and examine the highway section as the interval, the furthest reduce cost under the prerequisite that satisfies system job stabilization nature accords with the thought of green development.
Specifically, the total length L of the road sections to be patrolled and examined and the preset distance L0 are calculated according to a formula [ L/L0] -1 to obtain the number N of the intermediate unmanned airports, the road sections from the starting unmanned airport to the first intermediate unmanned airport are set as a first road section, the (N-1) th road section from the intermediate unmanned airport to the N th intermediate unmanned airport is set as an N-th road section, and the road sections from the N-th intermediate unmanned airport to the end unmanned airport are set as an (N+1) th road section, wherein N is a positive integer.
Specifically, the [ L/L0] in the calculation formula [ L/L0] -1 is a rounding function used for cutting and quantizing the path to be patrolled and examined into a plurality of road sections.
Specifically, according to the unmanned aerial vehicle, the path to be patrolled and examined is cut and quantized into a plurality of sections, on one hand, the real-time position of the unmanned aerial vehicle is convenient to determine, safety guarantee is provided for the working process of the unmanned aerial vehicle, on the other hand, each quantized section and the unmanned aerial vehicle are respectively made in one-to-one correspondence, the planning of the path to be patrolled and examined is convenient to adjust, and the working efficiency is improved.
Specifically, the information acquisition module 2 comprises an image acquisition unit, a laser imaging unit and a GPS positioning unit, wherein the image acquisition unit, the laser imaging unit and the GPS positioning unit are all arranged on the unmanned aerial vehicle and are mutually independent;
The image acquisition unit is connected with the information extraction module 101 and is used for acquiring image information of a road section to be inspected through the camera device;
the laser imaging unit is connected with the information extraction module 101 and is used for filtering vegetation through repeated laser reflection and returning to obtain a real topography image of a diseased road section;
the GPS positioning unit is connected to the information extraction module 101, and is configured to determine a real-time position of the unmanned aerial vehicle, and to obtain position information of the diseased road section.
Specifically, the image acquisition unit and the laser imaging unit acquire image information for presuming maintenance time, the GPS positioning unit acquires position information of a disease road section for rescheduling a routing inspection route, and the image acquisition unit, the laser imaging unit and the GPS positioning unit are respectively arranged on the unmanned aerial vehicle and do not interfere with each other, so that work division is facilitated, detected data are clear, and the working accuracy of the system is improved.
Specifically, the information extraction module 101 is configured to extract image information and position information of a damaged road section from the image information and the position information of the road section to be inspected;
The image information of the damaged road section comprises image information of a road crack section, image information of a road pit slot section and image information of a road sand accumulation section, the image information of the road crack section is set to be first image information, the image information of the road pit slot section is set to be second image information, and the image information of the road sand accumulation section is set to be third image information;
The position information of the damaged road section comprises position information of a road crack section, position information of a road pit slot section and position information of a road sand accumulation section, the position information of the road crack section is set to be first position information, the image information of the road pit slot section is set to be second position information, the image information of the road sand accumulation section is set to be third position information, and the first position information, the second position information and the third position information are sent to the information arrangement module.
Specifically, the disease conditions of the roads to be inspected have diversity and can not be mixed together at work, and the image information is finely classified into road crack sections, road pit slot sections and road sand accumulation sections in the extraction process.
Particularly, the disease road sections are subdivided, so that more accurate estimation of maintenance time is facilitated, the working efficiency of the system is improved, different disease conditions are greatly different in specific maintenance construction methods, and the system working efficiency can be further improved by classifying and respectively processing the disease road sections.
Specifically, the measurement module 102 is configured to measure a length L1 of the highway crack and a depth H1 of the highway crack in the first image information, set the length L1 of the highway crack as a first length, set the depth H1 of the highway crack as a first height, and send the first length L1 and the first height H1 to the disease parameter calculation module for calculating a disease parameter of the first image information;
The measurement module 102 is configured to measure a length L2 of the highway pit slot, a width W1 of the highway pit slot, and a depth H2 of the highway pit slot in the second image information, set the length L2 of the highway pit slot as a second length, set the width W1 of the highway pit slot as a first width, set the depth H2 of the highway pit slot as a second height, and send the second length L2, the first width W1, and the second height H2 to the disease parameter calculation module for calculating a disease parameter of the second image information;
the measurement module 102 is configured to measure a length L3 of the highway deposited sand, a width W2 of the highway deposited sand, and a thickness H3 of the highway deposited sand in the third image information, set the length L3 of the highway deposited sand as a third length, set the width W2 of the highway deposited sand as a second width, set the thickness H3 of the highway deposited sand as a third height, and send the third length L3, the second width W2, and the third height H3 to the disease parameter calculation module for calculating a disease parameter of the third image information.
Specifically, the first length L1, the second length L2, the first width W1, the third length L3 and the second width W2 are measured according to the image data collected by the image collecting unit, the first height H1, the second height H2 and the third height H3 are measured according to the image data collected by the laser imaging unit, and the same length data are measured respectively in different manners, so that the accuracy of data acquisition is improved, and the accuracy of a system is further improved.
Specifically, the disease parameter calculation module 103 presets, according to big data provided by a platform, that an influence parameter of the first length L1 is a first parameter k1, an influence parameter of the first height H1 is a second parameter k2, an influence parameter of the second length L1 is a third parameter k3, an influence parameter of the first width W1 is a fourth parameter k4, an influence parameter of the second height H2 is a fifth parameter k5, an influence parameter of the third length L3 is a sixth parameter k6, an influence parameter of the second width W2 is a seventh parameter k7, and an influence parameter of the third height H3 is an eighth parameter k8;
The disease parameter calculating module is configured to calculate the first length L1, the first height H1, the first parameter k1, and the second parameter k2 according to a formula (l1×k1) + (h1×k2) =p1) to obtain a disease parameter of the first image information and set the disease parameter as a first disease parameter P1;
the disease parameter calculation module 103 is configured to calculate the second length L2, the first width W1, the second height H2, the third parameter k3, the fourth parameter k4, and the fifth parameter k5 according to a formula (l2×k3) + (w1×k4) + (h2×k5) =p2) to obtain a disease parameter of the second image information and set the disease parameter as a second disease parameter P2;
the disease parameter calculation module 103 is configured to calculate the third length L3, the second width W2, the third height H3, the sixth parameter k6, the seventh parameter k7, and the eighth parameter k8 according to a formula (l3×k6) + (w2×k7) + (h3×k8) =p3 to obtain a disease parameter of the third image information and set the disease parameter as a third disease parameter P3;
The disease degree judging module 104 is further configured to judge the disease degree of the disease road section according to the magnitude of the disease parameter, preset PA as a first preset parameter of the highway crack, PB as a second preset parameter of the highway crack, PC as a first preset parameter of the highway pit slot, PD as a second preset parameter of the highway pit slot, PE as a preset parameter of the highway product Sha Di, PF as a second preset parameter of the highway product Sha Di, wherein the second preset parameter PB of the highway crack is greater than the first preset parameter PA of the highway crack, the second preset parameter PD of the highway pit slot is greater than the first preset parameter PC of the highway pit slot, and the second preset parameter PF of the highway product Sha Di is greater than the first preset parameter PE of the highway product Sha Di;
When P1 is less than or equal to PA, the damaged road section is a first-stage crack damage, when PA is less than P1 and less than PB, the damaged road section is a second-stage crack damage, and when P1 is more than or equal to PB, the damaged road section is a third-stage crack damage;
When P2 is less than or equal to PC, the disease road section is primary pit groove disease, when PC is less than P2 and less than PD, the disease road section is secondary pit groove disease, and when P2 is more than or equal to PD, the disease road section is tertiary pit groove disease;
when P3 is less than or equal to PE, the disease road section is a first product Sha Binghai, when PE is less than P3 and less than PF, the disease road section is a second product Sha Binghai, and when P3 is more than or equal to PF, the disease road section is a third product sand disease.
Specifically, the embodiment of the invention calculates the first disease parameter P1, the first disease parameter P2 and the first disease parameter P3 through measured data, judges the disease degree of the highway crack according to the magnitude relation between the first disease parameter P1 and the first preset parameter PA of the highway crack and the second preset parameter PB of the highway crack, judges the disease degree of the highway pit according to the magnitude relation between the second disease parameter P2 and the first preset parameter PC of the highway pit and the second preset parameter PD of the highway pit, and judges the disease degree of the highway sand according to the magnitude relation between the third disease parameter P3 and the first preset parameter PE of the highway product Sha Di and the second preset parameter PF of the highway product Sha Di.
Specifically, the classification judgment of the severity of the disease degree refines the working process from shallow to deep, so that the obtained result is more accurate, and the working accuracy of the system is further improved.
Specifically, the maintenance time estimation module 105 is configured to estimate a maintenance time of the damaged road section according to the damaged degree;
when the damaged road section is the primary crack damage, the maintenance time of the damaged road section is estimated to be a days, when the damaged road section is the secondary crack damage, the maintenance time of the damaged road section is estimated to be b days, and when the damaged road section is the tertiary crack damage, the maintenance time of the damaged road section is estimated to be c days, wherein c is larger than b is larger than a;
When the damaged road section is the primary pit slot damage, the maintenance time of the damaged road section is estimated to be d days, when the damaged road section is the secondary pit slot damage, the maintenance time of the damaged road section is estimated to be e days, and when the damaged road section is the tertiary pit slot damage, the maintenance time of the damaged road section is estimated to be f days, wherein f is more than e and more than d;
and when the damaged road section is the first-stage sand accumulation damage, the maintenance time of the damaged road section is estimated to be g days, when the damaged road section is the second-stage sand accumulation damage, the maintenance time of the damaged road section is estimated to be h days, and when the damaged road section is the third-stage sand accumulation damage, the maintenance time of the damaged road section is estimated to be i days, wherein i is more than h and more than g.
Specifically, the estimated time increases the reliability of the system operation to ensure that the damaged road segment can be repaired within the estimated time.
Specifically, the information sorting module 106 is configured to match the location information of the damaged road section with the corresponding estimated maintenance time;
The information sorting module 106 is configured to determine a road segment where the first location information, the second location information, and the third location information are located, and set a data pair obtained by matching the estimated maintenance time corresponding to the road segment with the intermediate unmanned airport corresponding to the road segment as a target data pair;
Obtaining X target data pairs according to the number X of the damaged road sections in the road sections to be inspected, uploading the obtained X target data pairs to the road maintenance operation platform and carrying out maintenance work;
When the same road section comprises a plurality of target data pairs, comparing the size relation of the estimated maintenance time in each target data pair, only reserving a group of target data pairs with the maximum estimated maintenance time, and sending all the reserved target data pairs to the task management module for rescheduling the inspection route of the unmanned aerial vehicle according to the target data.
Specifically, the road sections of the first position information, the second position information and the third position information are determined, the middle unmanned air station corresponding to the road section can be positioned fundamentally, and the purpose of rescheduling the routing inspection route of the unmanned air vehicle can be achieved by regulating and controlling the route of the unmanned air vehicle to reach each unmanned air station.
Specifically, the data pair obtained by matching the estimated maintenance time corresponding to the road section with the intermediate unmanned airport corresponding to the road section is set as target data pair for rescheduling the routing inspection, so that the working efficiency of the system is further improved.
Specifically, the task management module 3 is configured to reschedule an inspection route of the unmanned aerial vehicle according to the target data;
And after receiving the target data pair, the task management module eliminates the intermediate unmanned aerial vehicle corresponding to the disease road section in the target data pair from the preset path of the unmanned aerial vehicle within the estimated maintenance time corresponding to the target data pair, and re-plans the inspection route of the unmanned aerial vehicle.
Specifically, when the same road section has multiple diseases at the same time in the working process, the size relation corresponding to the estimated maintenance time is compared, and the maximum estimated maintenance time is selected for reservation, so that the situation that the damaged road section is completely repaired after the estimated maintenance time passes can be effectively ensured, and the reliability of equipment is further improved.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
The foregoing description is only of the preferred embodiments of the invention and is not intended to limit the invention; various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (8)

1. The utility model provides a highway unmanned aerial vehicle automatic inspection system which characterized in that includes:
the unmanned aerial vehicle airport is arranged on the road section to be inspected and is used for realizing the take-off operation of the unmanned aerial vehicle and the landing operation of the unmanned aerial vehicle;
the information acquisition module is arranged on the unmanned aerial vehicle and used for acquiring image information and position information of a road section to be inspected;
The highway maintenance operation platform is connected with the information acquisition module, internally provided with historical big data information and various calculation parameters of a road section to be inspected, and used for estimating maintenance time of a disease road section according to image information of the road section to be inspected and matching the position information of the disease road section with corresponding estimated maintenance time, and comprises an information extraction module, a measurement module, a disease parameter calculation module, a disease degree judgment module, a maintenance time estimation module and an information arrangement module;
the information extraction module is connected with the information acquisition module and is used for extracting the image information and the position information of the damaged road section from the image information and the position information of the road section to be inspected;
The measuring module is connected with the information extracting module and used for measuring data to be calculated from the image information of the disease road section;
the disease parameter calculation module is connected with the measurement module and used for calculating disease parameters according to the data to be calculated of the measurement of the disease road section;
the disease degree judging module is connected with the disease parameter calculating module and is used for judging the disease degree of the disease road section according to the size of the disease parameter;
The maintenance time estimating module is connected with the disease degree judging module and is used for estimating the maintenance time of the disease road section according to the disease degree;
The information arrangement module is respectively connected with the information extraction module and the maintenance time estimation module and is used for matching the position information of the damaged road section with the corresponding estimated maintenance time;
The task management module is respectively connected with the unmanned aerial vehicle and the information arrangement module and is used for rescheduling a routing inspection route of the unmanned aerial vehicle according to the position information of the diseased road section and the corresponding estimated maintenance time information;
The position information of the damaged road section comprises position information of a road crack road section, position information of a road pit slot road section and position information of a road sand accumulation road section, the position information of the road crack road section is set to be first position information, the image information of the road pit slot road section is set to be second position information, the image information of the road sand accumulation road section is set to be third position information, and the first position information, the second position information and the third position information are sent to the information arrangement module;
The middle unmanned aerial vehicle takes the starting point unmanned aerial vehicle as an starting point, and is equidistantly arranged on the section to be inspected along the section to be inspected by taking a preset distance L0 as a distance, so as to realize the take-off and landing work in the round trip process of the unmanned aerial vehicle, wherein the preset distance L0 is the maximum diameter of the signal receiving range of the unmanned aerial vehicle;
The information arrangement module is used for judging road sections where the first position information, the second position information and the third position information are located, and respectively setting the estimated maintenance time corresponding to the road sections corresponding to each position information and the data pair obtained by matching the corresponding middle unmanned air station as a target data pair;
Obtaining X target data pairs according to the number X of the damaged road sections in the road sections to be inspected, uploading the obtained X target data pairs to the road maintenance operation platform and carrying out maintenance work;
When the same road section comprises a plurality of target data pairs, comparing the size relation of the estimated maintenance time in each target data pair, only reserving a group of target data pairs with the maximum estimated maintenance time, and transmitting all the reserved target data pairs to the task management module, wherein the task management module is used for rescheduling a patrol route of the unmanned aerial vehicle according to the target data;
And after receiving the target data pair, the task management module eliminates the intermediate unmanned aerial vehicle corresponding to the disease road section in the target data pair from the preset path of the unmanned aerial vehicle within the estimated maintenance time corresponding to the target data pair, and re-plans the inspection route of the unmanned aerial vehicle.
2. The automated inspection system of claim 1, wherein the unmanned airports include a starting unmanned airport, a finishing unmanned airport, and a plurality of intermediate unmanned airports;
the starting unmanned aerial vehicle airport is arranged at the starting point of the road section to be inspected and used for realizing the take-off operation in the course of going out of the unmanned aerial vehicle and the landing operation in the course of returning back of the unmanned aerial vehicle;
The terminal unmanned aerial vehicle airport is arranged at the terminal of the road section to be inspected and used for realizing take-off operation in the return process of the unmanned aerial vehicle and landing operation in the going process of the unmanned aerial vehicle.
3. The automatic inspection system of a highway unmanned aerial vehicle according to claim 2, wherein the total length L of the road segments to be inspected and the preset distance L0 are calculated according to a formula [ L/L0] -1 to obtain the number N of the intermediate unmanned airports, the road segments from the starting unmanned airport to the first one of the intermediate unmanned airports are set as a first road segment, the (N-1) th road segment from the intermediate unmanned airport to the nth intermediate unmanned airport is set as an nth road segment, and the N-th road segment from the intermediate unmanned airport to the destination unmanned airport is set as an (n+1) th road segment, where N is a positive integer.
4. The automatic inspection system of a highway unmanned aerial vehicle according to claim 3, wherein the information acquisition module comprises an image acquisition unit, a laser imaging unit and a GPS positioning unit, and the image acquisition unit, the laser imaging unit and the GPS positioning unit are all arranged on the unmanned aerial vehicle and are mutually independent;
the image acquisition unit is connected with the information extraction module and is used for acquiring image information of a road section to be inspected through the camera device;
The laser imaging unit is connected with the information extraction module and is used for returning and filtering vegetation through laser multiple reflection to obtain a real topography image of a diseased road section;
The GPS positioning unit is connected with the information extraction module and used for determining the real-time position of the unmanned aerial vehicle and acquiring the position information of the diseased road section.
5. The automatic inspection system of a highway unmanned aerial vehicle according to claim 4, wherein the information extraction module is configured to extract image information and position information of a damaged road section from the image information and the position information of the road section to be inspected;
The image information of the damaged road section comprises image information of a road crack section, image information of a road pit slot section and image information of a road sand accumulation section, the image information of the road crack section is set to be first image information, the image information of the road pit slot section is set to be second image information, and the image information of the road sand accumulation section is set to be third image information.
6. The system according to claim 5, wherein the measurement module is configured to measure a length L1 of the highway crack and a depth H1 of the highway crack in the first image information, set the length L1 of the highway crack as a first length, set the depth H1 of the highway crack as a first height, and send the first length L1 and the first height H1 to the disease parameter calculation module for calculating a disease parameter of the first image information;
The measuring module is used for measuring the length L2 of the highway pit slot, the width W1 of the highway pit slot and the depth H2 of the highway pit slot in the second image information, setting the length L2 of the highway pit slot as a second length, setting the width W1 of the highway pit slot as a first width, setting the depth H2 of the highway pit slot as a second height, and sending the second length L2, the first width W1 and the second height H2 to the disease parameter calculating module for calculating the disease parameters of the second image information;
the measurement module is configured to measure a length L3 of the highway deposited sand, a width W2 of the highway deposited sand, and a thickness H3 of the highway deposited sand in the third image information, set the length L3 of the highway deposited sand as a third length, set the width W2 of the highway deposited sand as a second width, set the thickness H3 of the highway deposited sand as a third height, and send the third length L3, the second width W2, and the third height H3 to the disease parameter calculation module for calculating a disease parameter of the third image information.
7. The automatic inspection system of a highway unmanned aerial vehicle according to claim 6, wherein the disease parameter calculation module presets an influence parameter of the first length L1 as a first parameter k1, an influence parameter of the first height H1 as a second parameter k2, an influence parameter of the second length L1 as a third parameter k3, an influence parameter of the first width W1 as a fourth parameter k4, an influence parameter of the second height H2 as a fifth parameter k5, an influence parameter of the third length L3 as a sixth parameter k6, an influence parameter of the second width W2 as a seventh parameter k7, and an influence parameter of the third height H3 as an eighth parameter k8 according to big data provided by a platform;
The disease parameter calculation module is configured to calculate the first length L1, the first height H1, the first parameter k1, and the second parameter k2 according to a formula (l1×k1) + (h1×k2) =p1 to obtain a disease parameter of the first image information, and set the disease parameter as a first disease parameter P1;
the disease parameter calculation module is configured to calculate the second length L2, the first width W1, the second height H2, the third parameter k3, the fourth parameter k4, and the fifth parameter k5 according to a formula (l2×k3) + (w1×k4) + (h2×k5) =p2) to obtain a disease parameter of the second image information, and set the disease parameter as a second disease parameter P2;
The disease parameter calculation module is configured to calculate a disease parameter of the third image information according to a formula (l3×k6) + (w2×k7) + (h3×k8) =p3) from the third length L3, the second width W2, the third height H3, the sixth parameter k6, the seventh parameter k7, and the eighth parameter k8, and set the disease parameter as a third disease parameter P3;
The disease degree judging module is used for judging the disease degree of the disease road section according to the size of the disease parameter, presetting PA as a first preset parameter of a highway crack, PB as a second preset parameter of the highway crack, PC as a first preset parameter of a highway pit slot, PD as a second preset parameter of the highway pit slot, PE as a preset parameter of a highway product Sha Di, PF as a second preset parameter of a highway product Sha Di, wherein the second preset parameter PB of the highway crack is larger than the first preset parameter PA of the highway crack, the second preset parameter PD of the highway pit slot is larger than the first preset parameter PC of the highway pit slot, and the second preset parameter PF of the highway product Sha Di is larger than the first preset parameter PE of the highway product Sha Di;
When P1 is less than or equal to PA, the damaged road section is a first-stage crack damage, when PA is less than P1 and less than PB, the damaged road section is a second-stage crack damage, and when P1 is more than or equal to PB, the damaged road section is a third-stage crack damage;
When P2 is less than or equal to PC, the disease road section is primary pit groove disease, when PC is less than P2 and less than PD, the disease road section is secondary pit groove disease, and when P2 is more than or equal to PD, the disease road section is tertiary pit groove disease;
when P3 is less than or equal to PE, the disease road section is a first product Sha Binghai, when PE is less than P3 and less than PF, the disease road section is a second product Sha Binghai, and when P3 is more than or equal to PF, the disease road section is a third product sand disease.
8. The automated inspection system of claim 7, wherein the repair time estimation module is configured to estimate a repair time of the damaged road segment based on a degree of damage;
when the damaged road section is the primary crack damage, the maintenance time of the damaged road section is estimated to be a days, when the damaged road section is the secondary crack damage, the maintenance time of the damaged road section is estimated to be b days, and when the damaged road section is the tertiary crack damage, the maintenance time of the damaged road section is estimated to be c days, wherein c is larger than b is larger than a;
When the damaged road section is the primary pit slot damage, the maintenance time of the damaged road section is estimated to be d days, when the damaged road section is the secondary pit slot damage, the maintenance time of the damaged road section is estimated to be e days, and when the damaged road section is the tertiary pit slot damage, the maintenance time of the damaged road section is estimated to be f days, wherein f is more than e and more than d;
and when the damaged road section is the first-stage sand accumulation damage, the maintenance time of the damaged road section is estimated to be g days, when the damaged road section is the second-stage sand accumulation damage, the maintenance time of the damaged road section is estimated to be h days, and when the damaged road section is the third-stage sand accumulation damage, the maintenance time of the damaged road section is estimated to be i days, wherein i is more than h and more than g.
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