CN109060281B - Integrated bridge detection system based on unmanned aerial vehicle - Google Patents
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Abstract
本发明涉及一种基于无人机的一体化桥梁检测系统，属于无人机桥梁检测技术领域，包括桥梁建模无人机A、桥梁表面数据采集无人机B、地面综合信息处理控制系统，地面综合信息处理控制系统包括3D坐标建模系统、无人机巡航路径规划系统、桥面缺陷检测及标注系统、桥梁质量检测报告生成系统：无人机A用于被检测桥梁及周边地形环境摄影；3D坐标建模系统用于建立桥体及周边地形环境的3D坐标模型；无人机巡航路径规划系统用于规划无人机B的巡航路径；桥面缺陷检测及标注系统的用于检测桥面对应位置的缺陷，计算缺陷程度指标并标记在模型中。本发明实现桥梁检测过程的全自动化，大幅提高检测效率，提高检测质量。
The invention relates to an unmanned aerial vehicle-based integrated bridge detection system, belonging to the technical field of unmanned aerial vehicle bridge detection, comprising a bridge modeling unmanned aerial vehicle A, a bridge surface data acquisition unmanned aerial vehicle B, and a ground comprehensive information processing control system. The ground comprehensive information processing and control system includes a 3D coordinate modeling system, a UAV cruise path planning system, a bridge deck defect detection and labeling system, and a bridge quality inspection report generation system: UAV A is used for photography of the detected bridge and surrounding terrain environment. ; The 3D coordinate modeling system is used to establish the 3D coordinate model of the bridge body and the surrounding terrain environment; the UAV cruise path planning system is used to plan the cruise path of UAV B; the bridge deck defect detection and labeling system is used to detect the bridge The defect at the corresponding position of the surface, calculate the defect degree index and mark it in the model. The invention realizes the full automation of the bridge detection process, greatly improves the detection efficiency and improves the detection quality.
Description
Technical Field
The invention relates to an integrated bridge detection system based on an unmanned aerial vehicle, and belongs to the technical field of bridge detection of unmanned aerial vehicles.
Background
In recent years, with the rapid development of infrastructure construction in China, a plurality of infrastructure constructions are put into use, and thus, a huge market space in the aspect of infrastructure maintenance is brought. Aiming at the aspect of bridges, according to statistics, the total number of bridges in service in China exceeds millions, and 40% of bridges have service life of more than 25 years, belong to the aging stage, and need to invest larger post-detection and maintenance energy.
The traditional bridge detection is realized in a manual detection mode or a detection vehicle detection mode. The manual detection has the problems of high difficulty coefficient, large capital investment, detection blind areas, difficulty in ensuring the safety of detection personnel, low efficiency, large manpower investment and the like; the detection of the detection vehicle has the problems of high difficulty coefficient, large capital investment, detection blind area, limited applicability, low efficiency and the like. Neither method can meet the increasing requirements for bridge detection and maintenance.
The current popular remote unmanned aerial vehicle bridge outward appearance detection mode is that the shooting on bridge surface is detected through manual control unmanned aerial vehicle, generally by two professional technical personnel control fuselage motion respectively, detect the two parts of making a video recording and fly and data acquisition, the data acquisition shows in real time on ground station monitor screen, whether the inspection personnel exist the disease according to the control judgement.
The method can effectively reduce the defects of manual detection and detection vehicle detection, but still has the following problems: firstly, the requirement of bridge detection of the unmanned aerial vehicle on the flying hand level of the unmanned aerial vehicle is high, and the problems of increased detection cost and reduced detection effect are caused by the fact that crash events are easy to occur in some complex terrain environments; secondly, the quality of the existing unmanned aerial vehicle bridge detection image is uneven, and the integral performance and structure parameter indexes of the bridge are lacked, so that the damage degree of the bridge is judged mistakenly; thirdly, detection blind areas are easy to appear in bridge detection in complex environments, and detection holes are caused.
Disclosure of Invention
According to the defects of the prior art, the invention provides the integrated bridge detection system based on the unmanned aerial vehicle, so that the full automation of the bridge detection process is realized, the detection blind area is eliminated, the detection cost is effectively reduced, and the detection quality is improved.
The integrated bridge detection system based on the unmanned aerial vehicle comprises a bridge modeling unmanned aerial vehicle A, a bridge surface data acquisition unmanned aerial vehicle B and a ground comprehensive information processing control system, wherein the ground comprehensive information processing control system comprises a 3D coordinate modeling system, an unmanned aerial vehicle cruise path planning system, a bridge deck defect detection and marking system and a bridge quality detection report generation system: the unmanned aerial vehicle A is used for photographing the detected bridge and the surrounding terrain environment; the 3D coordinate modeling system is used for establishing a 3D coordinate model of the bridge body and the surrounding terrain environment; the unmanned aerial vehicle cruise path planning system is used for planning a cruise path of an unmanned aerial vehicle B; the bridge deck defect detection and marking system is used for detecting defects at corresponding positions of the bridge deck, calculating defect degree indexes and marking the defect degree indexes in the model; the bridge quality detection report generation system is used for generating a bridge quality detection report.
Unmanned aerial vehicle A adopts oblique photography collection to be detected the pontic and peripheral topography environment data, and data include oblique photography image model and each point GPS position coordinate, and oblique photography acquires the image through following a perpendicular, four slopes, five different visual angles synchronization acquisition images, acquires abundant bridge top surface and the high resolution texture data who looks sideways at, has guaranteed bridge model's precision.
Unmanned aerial vehicle B carry on flight control system, flight control system includes gesture perception control system, GPS navigation: the attitude sensing control system comprises an accelerometer, a gyroscope and a position sensor, wherein the accelerometer and the gyroscope form an inertial navigation system and are used for measuring the flight attitude; the position sensor is used for measuring the height and the course information of the airplane; the GPS navigation system is used to determine the aircraft flight direction and speed and lens orientation.
Unmanned aerial vehicle B still carry on communication control system and cloud platform control system, communication control system contains instruction communication system, image processing transmission system: the instruction communication system comprises a wireless data transmission radio station and a GPRS wireless module and is used for keeping contact with the ground comprehensive information processing control system; the image processing and transmitting system comprises a video processing module and a digital image transmitting module; the pan-tilt control system is used for controlling the angle of the camera. Because of the high real-time performance, 900MHz radio data transmission stations are adopted. The radio station receiver is connected with the flight controller through a serial port, sends the received instruction to the flight control system, and returns the attitude information and the geographic position information of the airplane analyzed by the flight control system to the ground comprehensive information processing control system. When the data transmission radio station receives interference, data transmission can be carried out through the GPRS wireless module, and the connection between the unmanned aerial vehicle and the ground integrated information processing control system is guaranteed. The video processing module uses a special digital signal processing chip to carry out electronic stability augmentation processing on the acquired video, and the digital image after stability augmentation is transmitted to the ground comprehensive information processing control system through the digital image transmission module. The tripod head control module is responsible for controlling the angle of the camera, and when the aircraft is in an inclined state, the tripod head can keep the camera horizontal stable, eliminate jitter and adjust the angle in real time according to a control instruction of a ground station. The attitude information of the pan-tilt is determined by the angle data of the mutually vertical y axis, p axis and r axis, the rotation of the pan-tilt is controlled by three motors respectively, and the actual orientation of the camera lens is determined by the calculation of the attitude coordinate information of the pan-tilt and the coordinate information of the bridge.
The unmanned aerial vehicle B is provided with an ultrasonic module and a three-way visual positioning module, and the three-way visual positioning module is arranged at the front part of the unmanned aerial vehicle in a first direction and is used for positioning and feeding back the relative position of the unmanned aerial vehicle from the bridge upright; the second direction is arranged at the upper part of the unmanned aerial vehicle and is used for positioning and feeding back the relative position of the unmanned aerial vehicle from the bridge bottom or the bridge abutment in the cruising detection process of the unmanned aerial vehicle; the third direction is installed in the unmanned aerial vehicle lower part for fix a position and feed back the relative position that unmanned aerial vehicle apart from ground or horizontal plane at unmanned aerial vehicle detection process that cruises. Except for a conventional ultrasonic module, obstacle recognition is carried out in the front direction, the rear direction, the left direction, the right direction, the upper direction and the lower direction of the unmanned aerial vehicle, and a recognition mechanism is divided into two parts, namely ultrasonic and machine vision. That is, besides the conventional ultrasonic module, cameras are specially arranged in all directions for acquiring visual images, and then the visual images are directly transmitted to an onboard processor for calculation processing. When carrying out bridge bottom bridge and detecting, the illumination condition is generally not too good, and ultrasonic wave and machine vision combined action can carry out good discernment to multiple material basically under any illuminance to provide better guidance to unmanned aerial vehicle flight under the bridge bottom, the effective range and the precision of discernment can show the promotion. Meanwhile, the functions of the ultrasonic module and the visual positioning module can be used for accurately positioning to determine gps data information besides obstacle avoidance.
The bridge deck defect detecting and labeling system detection categories comprise: detecting bridge deck cracks, bridge bottom cracks, rough surfaces and exposed ribs; detecting the breakage and corrosion of the protection facilities, and detecting dislocation, cracks, pitted surfaces and exposed ribs of the abutment; the bridge pier cracks, pitted surfaces, exposed ribs and verticality are detected, and the types of bridge defects can be comprehensively analyzed.
The bridge quality detection report content comprises: the method comprises the steps of bridge original structure data, detection standards, detection contents, detection results, defect pictures, defect degree index marking, defect cause analysis and detection conclusions.
The detection process comprises the following steps: the method comprises the following steps: the unmanned aerial vehicle A collects the data of the detected bridge body and the surrounding terrain environment and transmits the data back to the ground comprehensive information processing control system; step two: a 3D coordinate modeling system of the ground comprehensive information processing control system generates a 3D coordinate model of the bridge body and the surrounding terrain environment according to the returned data; step three: an unmanned aerial vehicle cruise path planning system of the ground comprehensive information processing control system establishes an autonomous cruise path of an unmanned aerial vehicle B according to the 3D coordinate models of the bridge body and the surrounding terrain environment, and sends an instruction to the unmanned aerial vehicle B; step four: the unmanned aerial vehicle B executes the autonomous cruise path to acquire images of the bridge body and transmits acquired information back to the ground comprehensive information processing control system; step five: the bridge deck defect detection and marking system of the ground comprehensive information processing control system matches the 3D coordinate model according to the bridge deck image returned by the unmanned aerial vehicle B, identifies the defect part of the bridge deck by using an identification algorithm, calculates the defect degree of the defect part, and marks the defect part and the defect degree index in the 3D coordinate model; step six: and a bridge quality detection report generation system of the ground comprehensive information processing control system automatically generates a bridge quality detection report.
Unmanned aerial vehicle A accomplishes the first collection to being detected the pontic and peripheral topography environmental data, establishes 3D coordinate model, and unmanned aerial vehicle B automatic acquisition data thereafter, ground integrated information processing control system automated inspection defect and mark, then automatic generation bridge quality detection report, wholly realize the automated process, improved the detection efficiency of bridge by a wide margin, reduce the cost of labor, detect the defect degree of bridge through the index simultaneously, reduced the erroneous judgement rate of defect, improve detection quality.
In the fifth step, the bridge deck defect identification and marking comprises the following steps: 1) loading an image file;
2) histogram equalization, namely adjusting the gray value through an accumulation function to enhance the contrast; 3) median filtering and denoising, namely replacing the value loaded into the image by the median of each point value in one field of the point to eliminate an isolated noise point; 4) binarization processing, namely setting the gray value of a pixel point on an image to be 0 or 255; 5) filtering the binary image, and inhibiting the noise of the target image under the condition of keeping the detail characteristics of the image; 6) identifying cracks, namely hiding other irrelevant factors loaded into the picture through the processing of a computer and visually displaying the positions of the cracks; 7) and (4) marking the crack by using a visual frame.
And step six, the bridge quality detection report generation system compares the original bridge structure parameters in the system with the standard bridge defect degree indexes according to the defect part and the defect degree indexes to calculate a harm degree index, and then automatically generates a bridge quality detection report.
Compared with the prior art, the invention has the beneficial effects that:
1. the bridge quality detection system and method provided by the invention have the advantages that the automatic acquisition of bridge data, the automatic detection and marking of bridge defects and the automatic generation of bridge quality detection reports are realized, the full automation of the bridge detection process is realized, the detection efficiency is greatly improved, and the problems of time and labor waste and low efficiency of the traditional bridge detection are solved.
2. And the oblique photography technology is adopted, rich high-resolution texture data of the top surface and the side view of the bridge are obtained, and the precision of the bridge model is ensured.
3. Unmanned aerial vehicle B carries out the detection route that cruises automatically, avoids the potential safety hazard that traditional detection mode detection personnel exist, eliminates simultaneously and detects the blind area.
4. Keep away the barrier through ultrasonic wave module and three-dimensional visual positioning module are automatic, can carry out good discernment to multiple material basically under any illuminance, and the effective range and the precision of discernment are showing and are promoting, effectively avoid detecting the probability of falling into the air of unmanned aerial vehicle bridge inspection process, have reduced the cost that the bridge detected simultaneously, have good economic benefits.
Drawings
FIG. 1 is a block diagram of a bridge inspection system according to the present invention.
FIG. 2 is a flow chart of a bridge inspection method of the present invention.
Fig. 3 is a front two-dimensional coordinate model diagram of a 3D coordinate model according to an embodiment of the invention.
FIG. 4 is a side view two-dimensional coordinate model diagram of a 3D coordinate model according to an embodiment of the invention.
FIG. 5 is a schematic diagram of crack defect detection and labeling according to an embodiment of the invention.
Detailed Description
Embodiments of the present invention are further described below with reference to the accompanying drawings.
As shown in fig. 1, the system of the integrated bridge detection method based on the unmanned aerial vehicle comprises a bridge modeling unmanned aerial vehicle a, a bridge surface data acquisition unmanned aerial vehicle B, and a ground comprehensive information processing control system, wherein the ground comprehensive information processing control system comprises a 3D coordinate modeling system, an unmanned aerial vehicle cruise path planning system, a bridge deck defect detection and labeling system, and a bridge quality detection report generation system, and the unmanned aerial vehicle B carries a flight control system, a communication control system, and a pan-tilt control system.
The unmanned aerial vehicle A is used for oblique photography of the detected bridge and the surrounding terrain environment, and can transmit data back to the ground comprehensive information processing control system by using the image transmission module or store the data in the storage device of the unmanned aerial vehicle A, and after the shooting task is executed, the data are transmitted to the ground comprehensive information processing control system.
The unmanned aerial vehicle B autonomously finishes the data acquisition of the bridge according to the route planning of the ground comprehensive information processing control system, and transmits the acquired data back to the ground comprehensive information processing control system through the image transmission module.
The 3D coordinate modeling system has the functions of carrying out three-dimensional modeling on the bridge and surrounding terrain image data obtained by the unmanned aerial vehicle A oblique photography and establishing an actual size coordinate system.
The unmanned aerial vehicle cruising path planning system has the function of automatically planning the cruising path of the unmanned aerial vehicle B according to the three-dimensional coordinate model of the bridge and the surrounding terrain environment and sending data to the unmanned aerial vehicle B.
The bridge deck defect detection and marking system has the functions that after the data image returned by the unmanned aerial vehicle B is fused with the three-dimensional image, the defect of the corresponding position of the bridge deck is detected, and the defect degree index is calculated and marked in the model;
the bridge quality detection report generation system has the function of automatically generating a bridge quality detection report according to the defect degree index.
The flight control system comprises an attitude sensing control system and a GPS navigation system: the attitude sensing control system comprises an accelerometer, a gyroscope and a position sensor, wherein the accelerometer and the gyroscope form an inertial navigation system and are used for measuring the flight attitude; the position sensor is used for measuring the height and the course information of the airplane; the GPS navigation system is used for determining the flight direction and speed of the airplane and the orientation of a lens according to the current GPS coordinate information of the airplane and the received coordinate information of the target point.
The communication control system comprises an instruction communication system and an image processing and transmitting system: the instruction communication system comprises a wireless data transmission radio station and a GPRS wireless module and is used for keeping contact with the ground comprehensive information processing control system; the image processing and transmitting system comprises a video processing module and a digital image transmitting module.
The tripod head control system is used for controlling the angle of the camera, the posture information of the tripod head is determined by the angle data of a y axis, a p axis and an r axis which are mutually vertical, the rotation of the tripod head is controlled by three motors respectively, and the actual orientation of the lens of the camera is determined by the posture coordinate information of the tripod head and the coordinate information of the bridge through calculation.
As shown in fig. 2, the present invention has the steps as follows:
the method comprises the following steps: unmanned aerial vehicle A automatically carries out autonomic shooting after the route is automatically planned, carries out oblique photography to being detected bridge and peripheral topography environment, and five camera lenses of aircraft camera integration are gathered 20 ~ 100 meters eminence in bridge height about h, and the area of shooing is 2 ~ 4 times bridge area, and the different high modeling precision is different, and the modeling precision is less than 0.5 meter. Oblique photography acquires abundant bridge top surface and high-resolution texture data of side view through synchronous acquisition of images from a perpendicular angle, four inclinations and five different visual angles, the precision of a bridge model is guaranteed, an unmanned aerial vehicle A can store the acquired image data in a memory carried by the unmanned aerial vehicle A, and the data comprise oblique photography image models and GPS position coordinates of each point.
Step two: and the 3D coordinate modeling system of the ground comprehensive information processing control system generates a 3D coordinate model M of the bridge body and the surrounding terrain environment according to the returned data.
As shown in fig. 3 and 4, the 3D coordinate model M is represented by a front-view two-dimensional coordinate model diagram of the 3D coordinate model and a side-view two-dimensional coordinate model diagram of the 3D coordinate model, respectively.
Step three: the unmanned aerial vehicle cruise path planning system of the ground integrated information processing control system establishes an autonomous cruise path of the unmanned aerial vehicle B according to the 3D coordinate models of the bridge body and the surrounding terrain environment, and sends an instruction to the unmanned aerial vehicle B.
Step four: and the unmanned aerial vehicle B executes the autonomous cruise path to acquire images of the bridge body and transmits acquired information back to the ground comprehensive information processing control system by using the airborne image transmission module.
Step five: the bridge deck defect detection and marking system of the ground comprehensive information processing control system matches a 3D coordinate model through software according to a bridge deck image returned by the unmanned aerial vehicle B, identifies a defect part of the bridge deck by using an identification algorithm, calculates the defect degree of the defect part, and marks the defect part and a defect degree index P in the 3D coordinate modeliThe method comprises the following steps: loading an image file; histogram equalization, namely adjusting the gray value through an accumulation function to enhance the contrast; 3) median filtering and denoising, namely replacing the value loaded into the image by the median of each point value in one field of the point to eliminate an isolated noise point; 4) binarization processing, namely setting the gray value of a pixel point on an image to be 0 or 255; 5) filtering of binary images, preservingSuppressing the noise of the target image under the condition of the image detail characteristics; 6) identifying cracks, namely hiding other irrelevant factors loaded into the picture through the processing of a computer and visually displaying the positions of the cracks; 7) and (4) marking the crack by using a visual frame.
The bridge defect detection categories include: detecting bridge deck cracks, bridge bottom cracks, rough surfaces and exposed ribs; detecting the breakage and corrosion of the protection facilities, and detecting dislocation, cracks, pitted surfaces and exposed ribs of the abutment; the bridge pier cracks, pitted surfaces, exposed ribs and verticality are detected, and the types of bridge defects can be comprehensively analyzed.
As shown in fig. 5, the crack defect degree index P of the middle detection section is obtained from the binarized image obtained by processing the crack defect with software and the image detected and labeled by the crack region range1＝33mm。
Step six: the bridge quality detection report generation system of the ground integrated information processing control system is based on the defect part and the defect degree index PiComparing the original structural parameters of the bridge in the system with the standard bridge defect degree index PdiAnd calculating to obtain a hazard degree index epsiloniAnd then automatically generating a bridge quality detection report. The bridge quality detection report content comprises the following contents: the method comprises the steps of bridge original structure data, detection standards, detection contents, detection results, defect pictures, defect degree index marking, defect cause analysis and detection conclusions.
The unmanned aerial vehicle B is provided with an ultrasonic module and a three-way visual positioning module, and the three-way visual positioning module is arranged at the front part of the unmanned aerial vehicle in a first direction and is used for positioning and feeding back the relative position of the unmanned aerial vehicle from the bridge upright; the second direction is arranged at the upper part of the unmanned aerial vehicle and is used for positioning and feeding back the relative position of the unmanned aerial vehicle from the bridge bottom or the bridge abutment in the cruising detection process of the unmanned aerial vehicle; the third direction is installed in the unmanned aerial vehicle lower part for fix a position and feed back the relative position that unmanned aerial vehicle apart from ground or horizontal plane at unmanned aerial vehicle detection process that cruises.
The bridge quality detection system and the bridge quality detection method realize automatic acquisition of bridge data, automatic detection and marking of bridge defects and automatic generation of bridge quality detection reports, realize full automation of bridge detection processes, greatly improve detection efficiency, and solve the problems of time and labor waste and low efficiency of traditional bridge detection; the oblique photography technology is adopted to obtain abundant high-resolution texture data of the top surface and the side view of the bridge, so that the precision of the bridge model is ensured; the unmanned aerial vehicle B automatically executes a cruise detection path, potential safety hazards of detection personnel in a traditional detection mode are avoided, and meanwhile, a detection blind area is eliminated; keep away the barrier through ultrasonic wave module and three-dimensional visual positioning module are automatic, can carry out good discernment to multiple material basically under any illuminance, and the effective range and the precision of discernment are showing and are promoting, effectively avoid detecting the probability of falling into the air of unmanned aerial vehicle bridge inspection process, have reduced the cost that the bridge detected simultaneously, have good economic benefits.
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| CN109885097B (en) * | 2019-04-11 | 2022-02-11 | 株洲时代电子技术有限公司 | Method for planning inspection route of outer edge surface of bridge |
| CN109960280A (en) * | 2019-04-11 | 2019-07-02 | 株洲时代电子技术有限公司 | A kind of bridge pier shaft inspection flight course planning method |
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