WO2019047338A1 - 港口机械的巡检装置及巡检方法 - Google Patents

港口机械的巡检装置及巡检方法 Download PDF

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Publication number
WO2019047338A1
WO2019047338A1 PCT/CN2017/106796 CN2017106796W WO2019047338A1 WO 2019047338 A1 WO2019047338 A1 WO 2019047338A1 CN 2017106796 W CN2017106796 W CN 2017106796W WO 2019047338 A1 WO2019047338 A1 WO 2019047338A1
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WIPO (PCT)
Prior art keywords
drone
port machinery
data
module
route
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PCT/CN2017/106796
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English (en)
French (fr)
Inventor
李文军
严云福
罗磊
赵子健
俞骏
戴巍
易庆
陆垚
山建国
熊丁根
富茂华
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上海振华重工(集团)股份有限公司
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Priority to EP17924086.6A priority Critical patent/EP3680648B1/en
Publication of WO2019047338A1 publication Critical patent/WO2019047338A1/zh

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/0094—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots involving pointing a payload, e.g. camera, weapon, sensor, towards a fixed or moving target
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G01C11/02—Picture taking arrangements specially adapted for photogrammetry or photographic surveying, e.g. controlling overlapping of pictures
    • 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
    • G01N21/9515—Objects of complex shape, e.g. examined with use of a surface follower device
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U10/00—Type of UAV
    • B64U10/10—Rotorcrafts
    • B64U10/13—Flying platforms
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2101/00—UAVs specially adapted for particular uses or applications
    • B64U2101/30—UAVs specially adapted for particular uses or applications for imaging, photography or videography
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2201/00—UAVs characterised by their flight controls
    • B64U2201/10—UAVs characterised by their flight controls autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS]
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2201/00—UAVs characterised by their flight controls
    • B64U2201/20—Remote controls
    • 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
    • G01N21/9515—Objects of complex shape, e.g. examined with use of a surface follower device
    • G01N2021/9518—Objects of complex shape, e.g. examined with use of a surface follower device using a surface follower, e.g. robot

Definitions

  • the present invention relates to the field of port machinery, and more particularly to the detection and evaluation techniques of port machinery.
  • Port machinery is widely used in the field of logistics. Port machinery mainly includes shore container cranes, track cranes, tire cranes, portal cranes and ship unloaders. Port machinery is very important for the normal operation of the port due to its heavy transportation tasks and long service life.
  • the core of the port machinery safety work is the steel structure. Its working position is at the seaside and it is a corrosive environment. Therefore, it is necessary to conduct regular inspections of the port machinery to check its health.
  • the current port machinery inspections are mainly based on manual inspections.
  • the inspectors climb the port machinery, detect the structure of the port machinery, take manual photographs of the diseased areas, and finally based on the test results and pictures. Record an evaluation report.
  • the size of the existing mainstream port machinery reaches 150m*30m*100m, which is difficult for the inspectors to climb and has a high risk factor.
  • some regional personnel are unable to reach, or due to the artificial viewing angle problem, the image cannot be acquired, and the detection blind zone is formed.
  • the existing manual detection methods have low efficiency, long detection period, poor detection effect, many blind spots, and large safety hazards.
  • the invention provides a patrol inspection technology of a port machinery based on a drone.
  • a patrol device for a port machinery comprising: an unmanned unit, a ground locator group, a ground monitoring processing device, and a data management evaluation device.
  • the unmanned aerial unit includes one or more drones, and the drones inspect the port machinery to obtain images of the port machinery.
  • the ground locator set includes one or more ground locators that position the three-dimensional position of the drone.
  • the ground monitoring processing device communicates with the drone, and the ground monitoring processing device controls the drone to fly, receives the image acquired by the drone, and monitors the state of the drone.
  • the data management evaluation device communicates with the ground monitoring processing device, the data management evaluation device stores the basic data of the port machinery, and the data management evaluation device receives the image acquired by the drone from the ground monitoring processing device, and performs the disease according to the image. Identification and disease analysis, and the results of the assessment based on disease identification and disease analysis.
  • the ground monitoring processing device includes a master and a handheld remote.
  • the main control unit plans the inspection route of the drone, controls the drone to fly along the inspection route and aerial photography to obtain the image of the port machinery, and monitors the state of the drone.
  • the handheld remote control receives an operation command, and controls the drone flight and aerial photography according to the operation command to obtain an image of the port machinery.
  • the handheld remote control is in an unoperated state, the drone is automatically controlled by the main control machine, the handheld remote control is in an operating state, and the drone exits the automatic operation, and is controlled by the handheld remote controller.
  • the main control machine includes: an interface interaction module, a front end data management module, a route planning module, an aerial photography control module, a monitoring module, and a communication module.
  • the interface interaction module generates an interaction interface, and the interaction interface receives the instructions and displays the information.
  • the front-end data management module acquires basic data of the port machinery from the data management evaluation device or the interface interaction module.
  • the route planning module plans an automatic inspection route according to the basic data of the port machinery acquired by the front-end data management module, or plans a designated inspection route according to the instruction acquired by the interaction interface.
  • the aerial photography control module controls the drone flight and aerial photography according to the automatic patrol route planned by the route planning module or the designated patrol route to obtain the image of the port machinery.
  • the monitoring module monitors the three-dimensional position and status of the drone.
  • the communication module communicates with the data management evaluation device and the handheld remote controller.
  • the handheld remote control includes a handheld operator, a data transmission module, and an image transmission module.
  • the hand-held operator is held by the operator, receives an operation command, and controls the drone to fly according to the operation command.
  • the data transmission module communicates with the drone and the host computer to monitor the status of the drone.
  • the image transmission module performs image communication with the drone and the host computer, and acquires images and videos of the port machinery obtained by the aerial photography of the drone.
  • the data management evaluation device includes a backend data management module, an image disease identification module, an image disease analysis module, and an evaluation module.
  • the back-end data management module processes the basic data of the port machinery, the route data, the state data of the drone, and the image data of the port machinery.
  • the image disease identification module identifies disease areas in the image of the port machinery and marks and classifies the disease areas.
  • the image disease analysis module quantifies the disease area marked and classified by the image disease recognition module, and associates the result of the quantitative calculation with the disease area.
  • the evaluation module generates an evaluation result based on the result of the quantitative calculation and the result of the quantitative calculation and the association with the disease area.
  • the classification of diseased areas includes: rust, cracks, bolt defects, paint stripping, and other diseases.
  • Quantitative calculations for diseased areas include: area of rust area, area of stripping area, length and width of cracks, number and location of bolt defects.
  • the underlying data of the port machinery includes dimensional data and location data for the port machinery.
  • the route data includes planned route data and actual route data, wherein the planned route data includes automatic inspection route data and designated inspection route data.
  • the drone status data includes: time, detection point number, horizontal abscissa, horizontal ordinate, height coordinate, pitch angle, tilt angle, yaw angle, pitch angle of the pan/tilt head, tilt angle, and yaw angle.
  • the processing of port machinery basic data, route data, drone status data, and port machinery image data includes: save, delete, modify, encrypt, decrypt, classify, filter, count, import, and export.
  • the drone includes: a fuselage, a flight module, a flight control module, a data transmission module, an image transmission module, an obstacle avoidance module, a positioning module, an aerial camera, and a tracking camera.
  • a method for inspecting a port machinery which uses the aforementioned inspection device of a port machinery, and the inspection method includes:
  • the route planning step planning the automatic inspection route according to the basic data of the port machinery
  • the drone aerial photography step controls the drone to fly according to the automatic inspection route, and the drone performs aerial photography on the port machinery, monitors the state of the drone and receives the image acquired by the drone;
  • the data processing step is to perform disease identification and disease analysis on the images acquired by the drone, and generate evaluation results based on disease identification and disease analysis.
  • the inspection method further includes:
  • the patrol route is planned according to the instruction obtained by the interface, and the drone performs flight on the designated patrol route to perform aerial photography on the port machinery.
  • the inspection method further includes:
  • the manual control step is operated by the handheld remote control, and the drone exits the automatic operation, and the flight is controlled by the hand-held remote controller to perform aerial photography on the port machinery.
  • the inspection device and the inspection method of the port machinery of the invention can automatically plan the route of the drone according to the basic data of the port machinery, and the drone automatically flies and performs aerial photography according to the planned route to complete the inspection work, and collect the image of the port machinery.
  • Data and video data The image data and video data are transmitted to a data management evaluation device for disease identification and disease analysis, and an evaluation result is generated based on disease identification and disease analysis. If necessary, you can manually modify the drone's route or switch the drone to manual mode.
  • the inspection device and the inspection method have high automation degree, high detection efficiency, wide application range and high safety factor.
  • FIG. 1 discloses a schematic structural view of a patrol device of a port machinery according to an embodiment of the present invention.
  • FIG. 2 is a block diagram showing the structure of a patrol device of a port machinery according to an embodiment of the present invention.
  • FIG. 3 is a block diagram showing the structure of a ground monitoring processing device in a patrol device of a port machinery according to an embodiment of the present invention.
  • FIG. 4a and 4b illustrate an example flow of a method of inspection of a port machinery in accordance with an embodiment of the present invention.
  • FIG. 1 discloses a schematic structural view of a patrol inspection apparatus for a port machinery according to an embodiment of the present invention.
  • the inspection device of the port machinery includes an unmanned aerial unit 101, a ground locator group 102, a ground monitoring processing device 103, and a data management evaluation device 104.
  • the unmanned aerial vehicle 101 includes one or more drones, and the drones inspect the port machinery to obtain images of the port machinery.
  • the ground locator set 102 includes one or more ground locators that position the three-dimensional position of the drone.
  • the ground monitoring processing device 103 communicates with the drone, and the ground monitoring processing device controls the drone to fly, receives the image acquired by the drone, and monitors the state of the drone.
  • the data management evaluation device 104 communicates with the ground monitoring processing device, the data management evaluation device stores basic data of the port machinery, and the data management evaluation device receives the image acquired by the drone from the ground monitoring processing device, and performs disease identification and disease analysis according to the image. The results of the assessment are generated based on disease identification and disease analysis.
  • FIG. 2 discloses a structural block diagram of a patrol device of a port machinery according to an embodiment of the present invention, and discloses a more detailed structure of the patrol device of the port machinery.
  • the unmanned aerial unit 101 includes one or more drones, and each of the unmanned aerial vehicles 101 in Fig. 2 is labeled as 101.1 to 101.n.
  • the drone used herein is a drone with automatic tracking flight and aerial photography functions.
  • the drone includes: a fuselage, a flight module, a flight control module, a data transmission module, and an image transmission module. , obstacle avoidance module, positioning module, aerial camera and tracking camera.
  • the ground locator set 102 includes one or more ground locators, each of which is labeled 102.1 - 102. m in Figure 2 in the ground locator 102.
  • the ground positioner positions the three-dimensional position of the drone.
  • the ground locator locates the three-dimensional position of the drone based on the wireless pulse signal or satellite signal.
  • the positioning method of the ground positioner to the three-dimensional position of the drone is not limited to the above-mentioned wireless pulse signal or satellite signal.
  • the ground monitoring processing device 103 includes a main control unit 131 and a handheld remote control 132.
  • the main control unit 131 plans the inspection route of the drone, controls the drone to fly along the planned inspection route and aerial photography to obtain the image of the port machinery, and monitors the state of the drone.
  • the hand-held remote control 132 receives an operation command, and controls the drone flight and aerial photography according to the operation command to acquire an image of the port machinery.
  • the hand-held remote control 132 is in an inoperative state, the drone is controlled to operate automatically by the host computer 131.
  • the hand-held remote control 132 is in an operational state, the drone exits the automatic operation and is controlled by the hand-held remote control 132.
  • the main control unit 131 includes an interface interaction module 301, a front end data management module 302, a route planning module 303, an aerial photography control module 304, a monitoring module 305, and a communication module 306.
  • the interface interaction module 301 generates an interaction interface that receives instructions and displays information.
  • the front end data management module 302 acquires basic data of the port machinery from the data management evaluation device 104 or the interface interaction module 301.
  • the underlying data of the port machinery includes dimensional data and location data for the port machinery.
  • the route planning module 303 plans an automatic inspection route according to the basic data of the port machinery acquired by the front-end data management module 302, that is, automatically patrols the route according to the size and location of the port machinery. Alternatively, the route planning module 303 plans to specify a patrol route according to the instruction acquired by the interaction interface. In some cases, the automatic patrol route needs to be modified. At this time, an instruction may be input through the interactive interface generated by the interface interaction module 301 to manually modify the patrol route to generate a designated patrol route. After the specified patrol route is generated, the drone flies and performs aerial photography according to the newly modified designated patrol route.
  • the aerial photography control module 304 controls the drone flight and aerial photography according to the automatic patrol route planned by the route planning module or the designated patrol route to obtain an image of the port machinery.
  • the monitoring module 305 monitors the three-dimensional position and status of the drone.
  • the communication module 306 communicates with the data management evaluation device 104 and the handheld remote control 132.
  • the front end data management module 302 also processes the basic data of the port machinery, the route data, the drone status data, and the image data of the port machinery. The processing includes: saving, deleting, modifying, encrypting, decrypting, sorting, filtering, counting, importing, exporting, and the like.
  • the handheld remote control 132 includes a handheld operator 307 and a data transmission module 308. And image transmission module 309. The hand-held operator 307 is held by the operator, receives an operation command, and controls the drone to fly according to the operation command.
  • the handheld operator 307 includes a rocker, a button, and a scroll wheel.
  • the data transmission module 308 performs data communication with the drone and the host computer to monitor the state of the drone.
  • the data transmission module 308 is mainly used for transmission of basic data, route data, and drone status data of the port machinery.
  • the image transmission module 309 performs image communication with the drone and the host computer to acquire images and videos of the port machinery obtained by the aerial photography of the drone.
  • the image transmission module 309 is mainly used for transmission of image data or video data of a port machine.
  • the data management evaluation device 104 includes a backend data management module 141, an image disease identification module 142, an image disease analysis module 143, and an evaluation module 144.
  • the backend data management module 141 processes the basic data of the port machinery, the route data, the drone state data, and the image data of the port machinery.
  • the underlying data of the port machinery includes dimensional data and location data for the port machinery.
  • the route data includes planned route data and actual route data.
  • UAV status data includes: time, detection point number, horizontal abscissa (or longitude coordinate), horizontal ordinate (or latitude coordinate), altitude coordinate, pitch angle, tilt angle, yaw angle, pitch angle of the pan/tilt , tilt angle, yaw angle.
  • the processing of port machinery basic data, route data, drone status data, port machinery image data includes: save, delete, modify, encrypt, decrypt, sort, filter, statistics, import, export and so on.
  • the image disease identification module 142 identifies diseased areas in the image of the port machinery and marks and classifies the diseased areas. In one embodiment, the classification of diseased areas includes: rust, cracks, bolt defects, paint stripping, and other diseases.
  • the image disease analysis module 143 performs a quantitative calculation on the diseased area marked and classified by the image disease recognition module, and associates the result of the quantitative calculation with the diseased area.
  • the quantitative calculation of the diseased area includes: area of the rusted area, area of the stripping area, length and width of the crack, number and location of the bolt defect.
  • the evaluation module 144 generates an evaluation result based on the result of the quantitative calculation and the result of the quantitative calculation and the association with the disease area.
  • the invention also provides a method for inspecting a port machinery, which uses the aforementioned inspection device of the port machinery, and the inspection method comprises:
  • the route planning step is to automatically patrol the route according to the basic data of the port machinery.
  • the drone aerial photography step controls the drone to fly according to the automatic inspection route.
  • the drone performs aerial photography on the port machinery, monitors the state of the drone and receives the image acquired by the drone.
  • the data processing step is to perform disease identification and disease analysis on the images acquired by the drone, and generate evaluation results based on disease identification and disease analysis.
  • the inspection method of the port machinery further includes: a route adjustment step, planning a designated inspection route according to an instruction acquired by the interaction interface, and the drone is inspected according to the designated inspection. Flight on the route, aerial photography of the port machinery.
  • the inspection method of the port machinery further includes: a manual control step, the drone is operated by the handheld remote controller, and the drone is controlled to fly, and the handheld remote control controls the flight. , aerial photography of the port machinery.
  • FIG. 4a and 4b illustrate an example flow of a method of inspection of a port machinery in accordance with an embodiment of the present invention.
  • the example process includes the following steps:
  • Step S1 The ground monitoring processing device 103 is activated to check that both the main control unit 131 and the handheld remote control 132 are in a normal state.
  • Step S2 The port size data to be inspected is input through the interface interaction module 301 of the main control unit 131, or the port machine size data to be inspected is downloaded from the back end data management module 141 through the communication module 306 of the main control unit 131.
  • Step S3 The drone 101 and the ground locator 102 are respectively placed in an initial position, and the initial position of the drone 101 is a pre-defined relative position of the position of the port machine to be inspected, and the ground locator 102 is a drone.
  • the positioning accuracy is required to be placed at an appropriate position on the ground.
  • Step S4 The drone 101 and the ground locator 102 are activated, and it is checked that both the drone and the ground locator are in a normal state.
  • Step S5 Record the initial position coordinates of the drone 101 in the main control unit 131, including its horizontal abscissa (or longitude coordinate), horizontal ordinate (or latitude coordinate), and height coordinate.
  • Step S6 According to the port machine size data that has been imported into the master machine 131, the route planning module 303 executes the route planning program to automatically generate an automatic patrol route matching the port machine to be inspected. When required, the inspector can manually modify the automatic inspection route through the interface interaction module 301 according to actual needs, modify the designated inspection route and save the designated inspection route as the latest planned route.
  • Step S7 Automatically control the aerial drone 101 to perform an aerial photography task according to the latest planned route.
  • Step S8 The ground monitoring processing system 103 receives the mission state of the drone 101 and determines whether the aerial mission is completed. If it is determined that the aerial photography task has not been completed, the process proceeds to step S9; if it is determined that the aerial photography task is completed, the process proceeds to step S15.
  • Step S9 The main control unit 131 detects the manipulation command of the handheld remote controller 132 in real time to determine whether an instruction is received. If the determination is yes, the process proceeds to step S10, and if the determination is no, the process returns to step S7.
  • Step S10 The ground monitoring processing system 103 sends an instruction to the drone 101 to control the drone. 101 Pause aerial photography and hover.
  • Step S11 The main control unit 131 displays three options through the interactive interface: modifying the route, manual control and misoperation, waiting for the detection personnel to make a selection; if selecting to modify the route, proceeding to step S12; if manual control is selected, proceeding to step S14 If the error operation is selected, the process returns to step S7.
  • Step S12 The detecting personnel manually modify the route parameters in the main control unit 131 according to actual needs, specify the inspection route and save the designated inspection route as the latest planned route.
  • Step S13 The main control unit 131 queries the detecting person whether to continue the automatic control through the interactive interface; if the detecting person selects No, the process goes to step S14, and if the detecting person selects Yes, the process returns to step S7.
  • Step S14 The detecting person manually operates the hand-held remote controller 132, and controls the drone 101 to execute the aerial shooting task according to the manual control command.
  • Step S15 In the automatic control mode, the ground monitoring processing system 103 automatically controls the drone 101 to end the flight mission and return to the ground.
  • the detecting personnel operate the handheld remote controller 132 to manually control the drone 101 to end the flight task. Return to the ground.
  • Step S16 The inspector introduces the picture and video data collected by the drone 101 to the main control unit 131.
  • Step S17 The detecting personnel manually inspect and filter the pictures that have been imported into the main control unit 131 according to actual needs.
  • Step S18 The inspector transmits the route data, all or the filtered picture and the video data in the master machine 131 to the backend data management module 141 in the data management evaluation device 104.
  • Step S19 The image disease identification module 142 in the data management evaluation device 104 automatically recognizes the structural surface diseases in the picture, classifies the surface diseases into rust, cracks, bolt defects, paint stripping and other types, and labels the pictures identifying the diseases.
  • the diseased area and type are saved to the backend data management module 141.
  • Step S20 The image disease analysis module 143 performs automatic quantitative calculation on the pictures that have been identified as rust, crack, bolt defect and paint stripping disease, and calculates the area of the rust or stripping area, the length of the crack length, the position of the bolt defect, and then calculates The result is associated with the disease picture.
  • Step S21 The evaluation module 144 automatically writes the structural disease picture and the analysis result as the evaluation result into the pre-stored evaluation report template document to form a basic evaluation report.
  • Step S22 The professional evaluator checks the basic evaluation report in the evaluation module 144, and writes maintenance and other suggestions in the basic evaluation report, and saves it as a complete evaluation report.
  • the inspection device and the inspection method of the port machinery of the invention can be based on the basic data of the port machinery.
  • the route of the drone is planned, and the drone automatically flies and performs aerial photography according to the planned route to complete the inspection work, and collect image data and video data of the port machinery.
  • the image data and video data are transmitted to a data management evaluation device for disease identification and disease analysis, and an evaluation result is generated based on disease identification and disease analysis. If necessary, you can manually modify the drone's route or switch the drone to manual mode.
  • the inspection device and the inspection method have high automation degree, high detection efficiency, wide application range and high safety factor.

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Abstract

一种港口机械的巡检装置及巡检方法，具有无人机组（101）、地面定位器组（102）、地面监控处理装置（103）和数据管理评估装置（104）。无人机对港口机械进行巡检，获取港口机械的图像。地面定位器对无人机的三维位置进行定位。地面监控处理装置（103）与无人机以及地面定位器通信，控制无人机飞行，接收无人机获取的图像，并监测无人机的状态。数据管理评估装置（104）与地面监控处理装置（103）通信，数据管理评估装置（104）保存有港口机械的基础数据，从地面监控处理装置（103）接收无人机获取的图像，根据图像进行病害识别和病害分析，并基于病害识别和病害分析生成评估结果。

Description

港口机械的巡检装置及巡检方法 技术领域
本发明涉及港口机械领域，更具体地说，涉及港口机械的检测和评估技术。
背景技术
港口机械在物流领域应用广泛，港口机械主要包括岸边集装箱起重机、轨道吊、轮胎吊、门座起重机和卸船机等。港口机械由于运输任务繁重，服役时间长，因此港机结构的健康检测对于港口的正常运营来说至关重要。港口机械安全工作的核心是钢机构，其工作位置处于海边，是易腐蚀的环境，因此需要定期对港口机械进行巡检，检查其健康状况。
目前的港口机械巡检主要是以人工巡检为主，由巡检员攀爬港口机械，对港口机械的各处结构进行检测、对出现病害的区域进行人工拍照，最后再根据检测结果和图片记录得出评估报告。随着港口机械的大型化，现有的主流港口机械的尺寸达到150m*30m*100m，对于巡检员来说攀爬困难，且危险系数较高。并且，由于港口机械的结构特殊性，有些区域人员无法到达，或者由于人工视角问题，无法获取图像，形成检测盲区。总体而言，现有的人工检测的方式效率低下、检测周期长、检测效果差、盲区多、且存在较大的安全隐患。
发明内容
本发明提出一种基于无人机的港口机械的巡检技术。
根据本发明的一实施例，提出一种港口机械的巡检装置，包括：无人机组、地面定位器组、地面监控处理装置和数据管理评估装置。无人机组包括一个或多个无人机，无人机对港口机械进行巡检，获取港口机械的图像。地面定位器组包括一个或多个地面定位器，地面定位器对无人机的三维位置进行定位。地面监控处理装置与无人机通信，地面监控处理装置控制无人机飞行，接收无人机获取的图像，并监测无人机的状态。数据管理评估装置与地面监控处理装置通信，数据管理评估装置保存有港口机械的基础数据，数据管理评估装置从地面监控处理装置接收无人机获取的图像，根据图像进行病 害识别和病害分析，并基于病害识别和病害分析生成评估结果。
在一个实施例中，地面监控处理装置包括：主控机和手持遥控器。主控机规划无人机的巡检航线，控制无人机沿巡检航线飞行和航拍以获取港口机械的图像，监测无人机的状态。手持遥控器接收操作指令，根据操作指令控制无人机飞行和航拍以获取港口机械的图像。其中，手持遥控器处于未操作状态，无人机由主控机控制自动运行，手持遥控器处于操作状态，无人机退出自动运行，由手持遥控器控制。
在一个实施例中，主控机包括：界面交互模块、前端数据管理模块、航线规划模块、航拍控制模块、监视模块和通信模块。界面交互模块产生交互界面，交互界面接收指令并显示信息。前端数据管理模块从数据管理评估装置或界面交互模块获取港口机械的基础数据。航线规划模块根据前端数据管理模块获取的港口机械的基础数据规划自动巡检航线，或者根据交互界面获取的指令规划指定巡检航线。航拍控制模块根据航线规划模块规划的自动巡检航线或者指定巡检航线控制无人机飞行和航拍，以获取港口机械的图像。监视模块监测无人机的三维位置和状态。通信模块与数据管理评估装置、手持遥控器进行通信。
在一个实施例中，手持遥控器包括：手持操作器、数据传输模块和图像传输模块。手持操作器由操作人员手持，接收操作指令，根据操作指令控制无人机飞行。数据传输模块与无人机和主控机进行数据通信，监测无人机的状态。图像传输模块与无人机和主控机进行图像通信，获取无人机航拍获得的港口机械的图像和视频。
在一个实施例中，数据管理评估装置包括：后端数据管理模块、图像病害识别模块、图像病害分析模块和评估模块。后端数据管理模块对港口机械的基础数据、航线数据、无人机状态数据、港口机械的图像数据进行处理。图像病害识别模块识别港口机械的图像中的病害区域，对病害区域进行标记和分类。图像病害分析模块对图像病害识别模块所标记和分类的病害区域进行量化计算，并将量化计算的结果与病害区域相关联。评估模块基于量化计算的结果以及量化计算的结果与病害区域的关联生成评估结果。
在一个实施例中，病害区域的分类包括：锈蚀、裂纹、螺栓缺损、脱漆和其他病害。对病害区域的量化计算包括：锈蚀区域面积、脱漆区域面积、裂纹长度和宽度、螺栓缺损数量和位置。
在一个实施例中，港口机械的基础数据包括港口机械的尺寸数据和位置数据。航线数据包括规划航线数据和实际航线数据，其中规划航线数据包括自动巡检航线数据和指定巡检航线数据。无人机状态数据包括：时间、检测点编号、水平横坐标、水平纵坐标、高度坐标、俯仰角、倾斜角、偏航角、拍摄云台的俯仰角、倾斜角、偏航角。对港口机械的基础数据、航线数据、无人机状态数据、港口机械的图像数据的处理包括：保存、删除、修改、加密、解密、分类、筛选、统计、导入、导出。
在一个实施例中，无人机包括：机身、飞行模块、飞行控制模块、数据传输模块、图像传输模块、障碍规避模块、定位模块、航拍摄像机和循迹摄像机。
根据本发明的一实施例，提出一种港口机械的巡检方法，使用前述的港口机械的巡检装置，该巡检方法包括：
航线规划步骤，根据港口机械的基础数据规划自动巡检航线；
无人机航拍步骤，控制无人机按照自动巡检航线飞行，无人机对港口机械进行航拍，监测无人机的状态并接收无人机获取的图像；
数据处理步骤，对无人机获取的图像进行病害识别和病害分析，并基于病害识别和病害分析生成评估结果。
在一个实施例中，该巡检方法还包括：
航线调整步骤，根据交互界面获取的指令规划指定巡检航线，无人机按照指定巡检航线飞行，对港口机械进行航拍。
在一个实施例中，该巡检方法还包括：
手动控制步骤，通过手持遥控器操作，无人机退出自动运行，由手持遥控器控制飞行，对港口机械进行航拍。
本发明的港口机械的巡检装置及巡检方法能根据港口机械的基础数据自动规划无人机的航线，无人机根据规划的航线自动飞行并航拍以完成巡检工作，采集港口机械的图像数据和视频数据。图像数据和视频数据被传输至数据管理评估装置，对图像进行病害识别和病害分析，并基于病害识别和病害分析生成评估结果。在必要时，可以手动修改无人机的航线或者将无人机切换至手动操作模式。该巡检装置和巡检方法自动化程度高，检测效率高，应用范围广，且安全系数高。
附图说明
本发明上述的以及其他的特征、性质和优势将通过下面结合附图和实施例的描述而变的更加明显，在附图中相同的附图标记始终表示相同的特征，其中：
图1揭示了根据本发明的一实施例的港口机械的巡检装置的结构示意图。
图2揭示了根据本发明的一实施例的港口机械的巡检装置的结构框图。
图3揭示了根据本发明的一实施例的港口机械的巡检装置中地面监控处理装置的结构框图。
图4a和图4b揭示了根据本发明的一实施例的港口机械的巡检方法的示例流程。
具体实施方式
首先参考图1所示，图1揭示了根据本发明的一实施例的港口机械的巡检装置的结构示意图。该港口机械的巡检装置包括：无人机组101、地面定位器组102、地面监控处理装置103和数据管理评估装置104。
无人机组101包括一个或多个无人机，无人机对港口机械进行巡检，获取港口机械的图像。地面定位器组102包括一个或多个地面定位器，地面定位器对无人机的三维位置进行定位。地面监控处理装置103与无人机通信，地面监控处理装置控制无人机飞行，接收无人机获取的图像，并监测无人机的状态。数据管理评估装置104与地面监控处理装置通信，数据管理评估装置保存有港口机械的基础数据，数据管理评估装置从地面监控处理装置接收无人机获取的图像，根据图像进行病害识别和病害分析，并基于病害识别和病害分析生成评估结果。
参考图2所示，图2揭示了根据本发明的一实施例的港口机械的巡检装置的结构框图，揭示了该港口机械的巡检装置更加详细的结构。无人机组101包括一个或多个无人机，在图2中无人机组101中的各个无人机被标记为101.1～101.n。此处使用的无人机是具有自动循迹飞行和航拍功能的无人机，在一个实施例中，该无人机包括：机身、飞行模块、飞行控制模块、数据传输模块、图像传输模块、障碍规避模块、定位模块、航拍摄像机和循迹摄像机。具有自动循迹飞行和航拍功能的无人机是从市场上采购获得，其基本结 构和功能此处不详细描述。地面定位器组102包括一个或多个地面定位器，在图2中地面定位器102中的各个地面定位器被标记为102.1～102.m。地面定位器对无人机的三维位置进行定位。在一个实施例中，地面定位器根据无线脉冲信号或者卫星信号对无人机的三维位置进行定位。当然，本领域的技术人员需要理解，地面定位器对无人机的三维位置的定位方法并不限于上述的无线脉冲信号或者卫星信号。
地面监控处理装置103包括：主控机131和手持遥控器132。主控机131规划无人机的巡检航线，控制无人机沿规划的巡检航线飞行和航拍以获取港口机械的图像，监测无人机的状态。手持遥控器132接收操作指令，根据操作指令控制无人机飞行和航拍以获取港口机械的图像。手持遥控器132处于未操作状态时，无人机由主控机131控制自动运行。手持遥控器132处于操作状态时，无人机退出自动运行，由手持遥控器132控制。图3揭示了根据本发明的一实施例的港口机械的巡检装置中地面监控处理装置的结构框图。参考图3所示，主控机131包括：界面交互模块301、前端数据管理模块302、航线规划模块303、航拍控制模块304、监视模块305和通信模块306。界面交互模块301产生交互界面，交互界面接收指令并显示信息。前端数据管理模块302从数据管理评估装置104或界面交互模块301获取港口机械的基础数据。在一个实施例中，港口机械的基础数据包括港口机械的尺寸数据和位置数据。航线规划模块303根据前端数据管理模块302获取的港口机械的基础数据规划自动巡检航线，即根据港口机械的尺寸和位置规划自动巡检航线。或者，航线规划模块303根据交互界面获取的指令规划指定巡检航线。在一些情况下，需要修改自动巡检航线，此时可以通过界面交互模块301产生的交互界面输入指令，手动对巡检航线进行修改，生成指定巡检航线。在生成指定巡检航线后，无人机根据新修改的指定巡检航线飞行并航拍。航拍控制模块304根据航线规划模块规划的自动巡检航线或者指定巡检航线控制无人机飞行和航拍，以获取港口机械的图像。监视模块305监测无人机的三维位置和状态。通信模块306与数据管理评估装置104、手持遥控器132进行通信。在一个实施例中，前端数据管理模块302还对港口机械的基础数据、航线数据、无人机状态数据、港口机械的图像数据进行处理。该处理包括：保存、删除、修改、加密、解密、分类、筛选、统计、导入、导出等。继续参考图3所示，手持遥控器132包括：手持操作器307、数据传输模块308 和图像传输模块309。手持操作器307由操作人员手持，接收操作指令，根据操作指令控制无人机飞行。在一个实施例中，手持操作器307包括摇杆、按键和滚轮。数据传输模块308与无人机和主控机进行数据通信，监测无人机的状态。数据传输模块308主要用于港口机械的基础数据、航线数据、无人机状态数据的传输。图像传输模块309与无人机和主控机进行图像通信，获取无人机航拍获得的港口机械的图像和视频。图像传输模块309主要用于港口机械的图像数据或者视频数据的传输。
回到图2，数据管理评估装置104包括：后端数据管理模块141、图像病害识别模块142、图像病害分析模块143和评估模块144。后端数据管理模块141对港口机械的基础数据、航线数据、无人机状态数据、港口机械的图像数据进行处理。在一个实施例中，港口机械的基础数据包括港口机械的尺寸数据和位置数据。航线数据包括规划航线数据和实际航线数据。无人机状态数据包括：时间、检测点编号、水平横坐标(或者经度坐标)、水平纵坐标(或者纬度坐标)、高度坐标、俯仰角、倾斜角、偏航角、拍摄云台的俯仰角、倾斜角、偏航角。对港口机械的基础数据、航线数据、无人机状态数据、港口机械的图像数据的处理包括：保存、删除、修改、加密、解密、分类、筛选、统计、导入、导出等。图像病害识别模块142识别港口机械的图像中的病害区域，对病害区域进行标记和分类。在一个实施例中，病害区域的分类包括：锈蚀、裂纹、螺栓缺损、脱漆和其他病害。图像病害分析模块143对图像病害识别模块所标记和分类的病害区域进行量化计算，并将量化计算的结果与病害区域相关联。在一个实施例中，对病害区域的量化计算包括：锈蚀区域面积、脱漆区域面积、裂纹长度和宽度、螺栓缺损数量和位置。评估模块144基于所述量化计算的结果以及量化计算的结果与病害区域的关联生成评估结果。
本发明还提出一种港口机械的巡检方法，使用前述的港口机械的巡检装置，该巡检方法包括：
航线规划步骤，根据港口机械的基础数据规划自动巡检航线。
无人机航拍步骤，控制无人机按照自动巡检航线飞行，无人机对港口机械进行航拍，监测无人机的状态并接收无人机获取的图像。
数据处理步骤，对无人机获取的图像进行病害识别和病害分析，并基于病害识别和病害分析生成评估结果。
在一个实施例中，在需要对自动巡检航线进行调整时，该港口机械的巡检方法还包括：航线调整步骤，根据交互界面获取的指令规划指定巡检航线，无人机按照指定巡检航线飞行，对港口机械进行航拍。
在一个实施例中，在需要对无人机进行手动操作时，该港口机械的巡检方法还包括：手动控制步骤，通过手持遥控器操作，无人机退出自动运行，由手持遥控器控制飞行，对港口机械进行航拍。
图4a和图4b揭示了根据本发明的一实施例的港口机械的巡检方法的示例流程。该示例流程包括如下的步骤：
步骤S1：启动地面监控处理装置103，检查确认主控机131和手持遥控器132均处于正常状态。
步骤S2：通过主控机131的界面交互模块301输入待检港机尺寸数据，或者通过主控机131的通信模块306从后端数据管理模块141下载待检港机尺寸数据。
步骤S3：将无人机101和地面定位器102分别摆放在初始位置，无人机101的初始位置是预先定义的一个参考待检港机位置的相对位置，地面定位器102按无人机定位精度要求布置于地面上适当的位置。
步骤S4：启动无人机101和地面定位器102，检查确认无人机和地面定位器均处于正常状态。
步骤S5：在主控机131中记录无人机101的初始位置坐标，包括其水平横坐标(或经度坐标)、水平纵坐标(或纬度坐标)、高度坐标。
步骤S6：根据已导入主控机131的港机尺寸数据，由航线规划模块303执行航线规划程序自动生成与待检港机相匹配的自动巡检航线。在需要的时候，检测人员按实际需求，可以通过界面交互模块301手动修改自动巡检航线，修改为指定巡检航线并将指定巡检航线保存为最新规划航线。
步骤S7：按最新规划航线自动控制航拍无人机101执行航拍任务。
步骤S8：地面监控处理系统103接收到无人机101执行任务状态，判断是否完成航拍任务。若判断未完成航拍任务，进入步骤S9；若判断完成航拍任务，进入步骤S15。
步骤S9：主控机131实时检测手持遥控器132的操控指令，判断是否接收到指令。若判断是，进入步骤S10，若判断否，返回步骤S7。
步骤S10：地面监控处理系统103向无人机101发送指令，控制无人机 101暂停航拍并悬停。
步骤S11：主控机131通过交互界面显示出三种选择项：修改航线、手动控制和误操作，等待检测人员做出选择；若选择修改航线，进入步骤S12；若选择手动控制，进入步骤S14)；若选择误操作，返回步骤S7。
步骤S12：检测人员根据实际需要，在主控机131中手动修改航线参数，指定巡检航线并将指定巡检航线保存为最新规划航线。
步骤S13：主控机131通过交互界面询问检测人员是否继续自动控制；若检测人员选择否，进入步骤S14，若检测人员选择是，返回步骤S7。
步骤S14：检测人员手动操作手持遥控器132，控制无人机101根据手动控制指令执行航拍任务。
步骤S15：在自动控制模式下，地面监控处理系统103自动控制无人机101结束飞行任务并返回地面，在手动控制模式下，检测人员操作手持遥控器132手动控制无人机101结束飞行任务并返回地面。
步骤S16：检测人员将无人机101采集的图片和视频数据导入主控机131。
步骤S17：检测人员按实际需要，人工检查和筛选已导入主控机131中的图片。
步骤S18：检测人员将主控机131中的航线数据、全部或筛选图片和视频数据传送至数据管理评估装置104中的后端数据管理模块141。
步骤S19：数据管理评估装置104中的图像病害识别模块142自动识别图片中的结构表面病害，将表面病害分类为锈蚀、裂纹、螺栓缺损、脱漆和其他类型，对识别出病害的图片标注其病害区域和类型，将标注处理后图片保存到后端数据管理模块141中。
步骤S20图像病害分析模块143将已识别分类为锈蚀、裂纹、螺栓缺损和脱漆病害的图片进行自动定量计算，计算出锈蚀或脱漆区域面积、裂纹长度宽度、螺栓缺损数量位置，再将计算结果与病害图片关联。
步骤S21：评估模块144将结构病害图片及分析结果作为评估结果自动写入预存的评估报告模板文档中，形成基本评估报告。
步骤S22：专业评估人员在评估模块144中，检查基本评估报告，在基本评估报告中写入维修保养等建议，保存为完整评估报告。
本发明的港口机械的巡检装置及巡检方法能根据港口机械的基础数据自 动规划无人机的航线，无人机根据规划的航线自动飞行并航拍以完成巡检工作，采集港口机械的图像数据和视频数据。图像数据和视频数据被传输至数据管理评估装置，对图像进行病害识别和病害分析，并基于病害识别和病害分析生成评估结果。在必要时，可以手动修改无人机的航线或者将无人机切换至手动操作模式。该巡检装置和巡检方法自动化程度高，检测效率高，应用范围广，且安全系数高。
上述实施例是提供给熟悉本领域内的人员来实现或使用本发明的，熟悉本领域的人员可在不脱离本发明的发明思想的情况下，对上述实施例做出种种修改或变化，因而本发明的保护范围并不被上述实施例所限，而应该是符合权利要求书提到的创新性特征的最大范围。

Claims (11)

  1. 一种港口机械的巡检装置，其特征在于，包括：
    无人机组，无人机组包括一个或多个无人机，无人机对港口机械进行巡检，获取港口机械的图像；
    地面定位器组，地面定位器组包括一个或多个地面定位器，地面定位器对无人机的三维位置进行定位；
    地面监控处理装置，地面监控处理装置与无人机通信，地面监控处理装置控制无人机飞行，接收无人机获取的图像，并监测无人机的状态；
    数据管理评估装置，数据管理评估装置与地面监控处理装置通信，数据管理评估装置保存有港口机械的基础数据，数据管理评估装置从地面监控处理装置接收无人机获取的图像，根据图像进行病害识别和病害分析，并基于病害识别和病害分析生成评估结果。
  2. 如权利要求1所述的港口机械的巡检装置，其特征在于，所述地面监控处理装置包括：
    主控机，主控机规划无人机的巡检航线，控制无人机沿巡检航线飞行和航拍以获取港口机械的图像，监测无人机的状态；
    手持遥控器，手持遥控器接收操作指令，根据操作指令控制无人机飞行和航拍以获取港口机械的图像；
    其中，手持遥控器处于未操作状态，无人机由主控机控制自动运行，手持遥控器处于操作状态，无人机退出自动运行，由手持遥控器控制。
  3. 如权利要求2所述的港口机械的巡检装置，其特征在于，所述主控机包括：
    界面交互模块，产生交互界面，交互界面接收指令并显示信息；
    前端数据管理模块，前端数据管理模块从数据管理评估装置或界面交互模块获取港口机械的基础数据；
    航线规划模块，航线规划模块根据前端数据管理模块获取的港口机械的基础数据规划自动巡检航线，或者根据交互界面获取的指令规划指定巡检航线；
    航拍控制模块，根据航线规划模块规划的自动巡检航线或者指定巡检航线控制无人机飞行和航拍，以获取港口机械的图像；
    监视模块，监测无人机的三维位置和状态；
    通信模块，与数据管理评估装置、手持遥控器进行通信。
  4. 如权利要求2所述的港口机械的巡检装置，其特征在于，所述手持遥控器包括：
    手持操作器，由操作人员手持，接收操作指令，根据操作指令控制无人机飞行；
    数据传输模块，与无人机和主控机进行数据通信，监测无人机的状态；
    图像传输模块，与无人机和主控机进行图像通信，获取无人机航拍获得的港口机械的图像和视频。
  5. 如权利要求1所述的港口机械的巡检装置，其特征在于，所述数据管理评估装置包括：
    后端数据管理模块，对港口机械的基础数据、航线数据、无人机状态数据、港口机械的图像数据进行处理；
    图像病害识别模块，识别港口机械的图像中的病害区域，对病害区域进行标记和分类；
    图像病害分析模块，对图像病害识别模块所标记和分类的病害区域进行量化计算，并将量化计算的结果与病害区域相关联；
    评估模块，基于所述量化计算的结果以及量化计算的结果与病害区域的关联生成评估结果。
  6. 如权利要求5所述的港口机械的巡检装置，其特征在于，
    病害区域的分类包括：锈蚀、裂纹、螺栓缺损、脱漆和其他病害；
    对病害区域的量化计算包括：锈蚀区域面积、脱漆区域面积、裂纹长度和宽度、螺栓缺损数量和位置。
  7. 如权利要求5所述的港口机械的巡检装置，其特征在于，
    所述港口机械的基础数据包括港口机械的尺寸数据和位置数据；
    所述航线数据包括规划航线数据和实际航线数据，其中规划航线数据包括自动巡检航线数据和指定巡检航线数据；
    无人机状态数据包括：时间、检测点编号、水平横坐标、水平纵坐标、高度坐标、俯仰角、倾斜角、偏航角、拍摄云台的俯仰角、倾斜角、偏航角；
    对港口机械的基础数据、航线数据、无人机状态数据、港口机械的图像数据的处理包括：保存、删除、修改、加密、解密、分类、筛选、统计、导入、导出。
  8. 如权利要求1所述的港口机械的巡检装置，其特征在于，所述无人机包括：机身、飞行模块、飞行控制模块、数据传输模块、图像传输模块、障碍规避模块、定位模块、航拍摄像机和循迹摄像机。
  9. 一种港口机械的巡检方法，使用如权利要求1-8中任一项所述的港口机械的巡检装置，其特征在于，该巡检方法包括：
    航线规划步骤，根据港口机械的基础数据规划自动巡检航线；
    无人机航拍步骤，控制无人机按照自动巡检航线飞行，无人机对港口机械进行航拍，监测无人机的状态并接收无人机获取的图像；
    数据处理步骤，对无人机获取的图像进行病害识别和病害分析，并基于病害识别和病害分析生成评估结果。
  10. 如权利要求9所述的港口机械的巡检方法，其特征在于，还包括：
    航线调整步骤，根据交互界面获取的指令规划指定巡检航线，无人机按照指定巡检航线飞行，对港口机械进行航拍。
  11. 如权利要求9所述的港口机械的巡检方法，其特征在于，还包括：
    手动控制步骤，通过手持遥控器操作，无人机退出自动运行，由手持遥控器控制飞行，对港口机械进行航拍。
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