CN111999298A - Unmanned aerial vehicle bridge system of patrolling and examining fast based on 5G technique - Google Patents

Unmanned aerial vehicle bridge system of patrolling and examining fast based on 5G technique Download PDF

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CN111999298A
CN111999298A CN202010615965.7A CN202010615965A CN111999298A CN 111999298 A CN111999298 A CN 111999298A CN 202010615965 A CN202010615965 A CN 202010615965A CN 111999298 A CN111999298 A CN 111999298A
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aerial vehicle
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孙克肇
苏毅
许睿
张新宇
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Nanjing Forestry University
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Nanjing Forestry University
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Abstract

The invention discloses a bridge system for rapidly inspecting an unmanned aerial vehicle based on a 5G technology, relates to the technical field of bridge detection, and combines the 5G network technology and the unmanned aerial vehicle to rapidly and autonomously inspect a bridge, so that the problems of data transmission, time delay and the like existing in the process of inspecting the bridge by the existing unmanned aerial vehicle are solved, and an automatic system for inspecting the bridge by the unmanned aerial vehicle is realized. It includes unmanned aerial vehicle platform, multi-functional ground station two parts. The unmanned aerial vehicle platform includes unmanned aerial vehicle main part and unmanned aerial vehicle and goes up the module crowd of carrying on. The carrying module group comprises an image acquisition module, a storage module, a flight state processing module and a 5G network communication module. The multifunctional ground station comprises a 3D coordinate modeling subsystem, an unmanned aerial vehicle air route subsystem, a flight control subsystem, a bridge defect detection subsystem, a bridge defect report subsystem and a VR subsystem. The bridge inspection system and the bridge inspection method realize full automation of the bridge inspection process, save human resources and time cost, greatly improve bridge inspection efficiency and improve inspection quality.

Description

Unmanned aerial vehicle bridge system of patrolling and examining fast based on 5G technique
Technical Field
The invention relates to an unmanned aerial vehicle rapid bridge inspection system based on a 5G technology, and relates to the technical field of bridge detection.
Background
In recent years, with the rapid development of civil engineering field in China, a large amount of infrastructure is built and put into use, and the rapid development of the infrastructure maintenance field is promoted. In the aspect of bridges, according to data of China department of transportation, the total number of bridges in active service exceeds millions, the bridges are divided according to service life, the proportion of the bridges in critical service reaches 10%, 40% of the bridges enter an aging stage, and a large amount of time and energy are needed to be invested for later detection, maintenance and reinforcement of the bridges.
The conventional bridge detection has two modes of manual detection and detection vehicle detection, wherein the manual detection comprises visual observation and telescope detection, the visual observation mode is difficult to ensure the safety of detection personnel, the efficiency is low, and the manpower input is large; the telescope detection mode has the problems of detection blind area, large difficulty coefficient, low efficiency and low precision. For detection of a detection vehicle, the investment is large, a detection blind area exists, the efficiency is low, and the applicability is limited.
Compared with the traditional conventional bridge detection method, the conventional mode for detecting the bridge by the unmanned aerial vehicle is to manually control the unmanned aerial vehicle, plan the route of the unmanned aerial vehicle, shoot the details of the frequent detection points of the bridge, transmit the shot picture data to the monitoring screen of the ground station in real time, and judge whether the bridge has defects by detection personnel.
The mode greatly improves the safety and the detection efficiency, saves the manpower, greatly saves the expenditure, and still has the following problems: firstly, the existing unmanned aerial vehicle bridge detection is only limited to local details of a bridge, and the whole structure of the bridge is not judged, so that the bridge is judged wrongly; secondly, the existing mode of detecting the bridge by the unmanned aerial vehicle is too dependent on the capability of a controller of the unmanned aerial vehicle, so that a crash event is easy to happen, and the cost is increased; thirdly, bridge detailed data that unmanned aerial vehicle shot can receive the influence of surrounding environment, has data transmission disappearance problem and time delay problem.
Disclosure of Invention
According to the defects of the prior art, the invention provides the unmanned aerial vehicle rapid inspection bridge system based on the 5G technology, so that the automatic unmanned aerial vehicle inspection bridge system is realized, the blind areas possibly occurring in the detection process are reduced, the integral judgment on the bridge structure is realized, and the problems of data transmission and time delay are solved.
The invention relates to an unmanned aerial vehicle rapid inspection bridge system based on a 5G technology. The unmanned aerial vehicle platform comprises an unmanned aerial vehicle main body and a carrying module group; the multifunctional ground station comprises a 3D coordinate modeling subsystem, an unmanned aerial vehicle air route subsystem, a flight control subsystem, a bridge defect detection subsystem, a bridge defect report subsystem and a VR subsystem. Unmanned aerial vehicle platform quantity chooses for use according to bridge structures actual conditions, here plans to adopt four, is unmanned aerial vehicle A, unmanned aerial vehicle B, unmanned aerial vehicle C, unmanned aerial vehicle D respectively, and these four unmanned aerial vehicles carry on same module crowd. The unmanned aerial vehicle A, B is used for collecting the left side, the right side and the peripheral topographic data of the detected bridge respectively; unmanned aerial vehicle B, C is used for the structure detection on bridge left side, right side respectively.
The carrying module group consists of an image acquisition module, a storage module, a flight state processing module and a 5G network communication module; the image acquisition module consists of a long-focus lens, a short-focus lens and an infrared lens which are mutually independent, the three cameras can be respectively controlled by a multifunctional ground station, bridge structure data are acquired by adopting an oblique photography mode and are respectively transmitted to the storage module; the storage module is in wired connection with the image acquisition module, the flight state processing module and the 5G network communication module of the carrying module group, and stores bridge data and unmanned aerial vehicle flight state data obtained by oblique photography; the flight state processing module comprises a sensor module and a GPS positioning navigation module, wherein the sensor module acquires distance data to ensure that the unmanned aerial vehicle keeps a safe distance of at least 0.5m with the bridge, and the GPS positioning navigation module determines information such as the course and the position of the unmanned aerial vehicle and transmits the flight state data of the unmanned aerial vehicle to the storage module; the 5G network communication module comprises a preposed pilot frequency and a novel frame structure, and is connected with the storage module, transmits data stored by the storage module and receives signals sent by the multifunctional ground station.
The image acquisition module consists of a long-focus lens, a short-focus lens and an infrared lens, and works respectively. When the unmanned aerial vehicle A, B gathers bridge and surrounding terrain data, only use the telephoto lens at the same time, adopt the mode of oblique photography. Oblique photography synchronously acquires image data through one vertical angle, four oblique angles and five different visual angles, the data comprises an image model and GPS data of each point, and the accuracy of the bridge and the surrounding terrain model is guaranteed. When the unmanned aerial vehicle C, D detects a bridge structure, a telephoto lens is adopted when a large crack needs to be acquired in the length direction or the outer contour line of the bridge needs to be detected; when the width of the crack needs to be measured, a short-focus lens is adopted; when the ambient light is darker, an infrared lens is adopted to collect data of the crack at the point. The three cameras are controlled by a flight control subsystem of the multifunctional ground station, independently transmit data to the ground, are not interfered with each other, and widen the application range of image acquisition.
The flight state processing module comprises a sensor module and a GPS positioning navigation module, wherein the sensor module consists of three high-precision laser ranging sensors and optical sensors, the three high-precision laser ranging sensors are respectively arranged at the front part, the upper part and the lower part of the unmanned aerial vehicle, the front sensor is used for positioning and feeding back the relative position of the unmanned aerial vehicle from a bridge upright post in the unmanned aerial vehicle inspection process, the upper sensor is used for positioning and feeding back the relative position of the unmanned aerial vehicle from a bridge bottom or a bridge abutment in the unmanned aerial vehicle inspection process, and the lower sensor is used for positioning and feeding back the relative position of the unmanned aerial vehicle from the ground or the water surface in the unmanned aerial vehicle inspection process, so that the safety distance of at least 0.5 meter is ensured, and the unmanned; the optical sensor is used for acquiring light conditions of the surrounding environment, can be matched with a flight control subsystem of the multifunctional ground station to realize conversion of the camera, and adopts an infrared camera to shoot when the light intensity of the surrounding environment is smaller than a fixed value; the GPS positioning navigation module determines information such as the course and the position of the unmanned aerial vehicle, positions the unmanned aerial vehicle in the established three-dimensional model, and is convenient to inspect.
The 5G network communication module and the storage module are used for transporting and storing the data acquired by the image acquisition module and the flight state data of the unmanned aerial vehicle, and meanwhile, stable and time-delay-free data connection between the multifunctional ground station and the unmanned aerial vehicle is guaranteed. The 5G network communication module is connected with the multifunctional ground station by adopting a 5G signal. The data storage module provides a plurality of interfaces and can be connected with storage equipment such as a storage card.
The 3D coordinate modeling subsystem of the multifunctional ground station receives Bridge and peripheral topographic data of a storage module, comprises spatial data of Bridge piers, Bridge abutments and Bridge span structures, and combines Open Bridge Modeller software to carry out three-dimensional modeling on the Bridge.
The unmanned aerial vehicle route subsystem of the multifunctional ground station automatically marks detection points needing to be detected of buildings in the routing inspection route according to the three-dimensional model of the bridge through compiled related programs, comprises bridge span expansion joints, bridge head and embankment connecting parts, an upper structure, a conical slope, a slope protection, abutments, foundations and supports, plans the routing inspection route of the unmanned aerial vehicle, and transmits the routing inspection route to the flight control subsystem.
The flight control subsystem of the multifunctional ground station receives unmanned aerial vehicle routing inspection route data of the unmanned aerial vehicle air route subsystem and unmanned aerial vehicle flight state data transmitted by the 5G network communication module, controls lenses used by unmanned aerial vehicle flight and image acquisition, and sends a control instruction to the unmanned aerial vehicle.
The bridge defect detection subsystem of the multifunctional ground station comprises an image processing module, a defect identification module and a defect marking module, wherein the image processing module carries out filtering and noise reduction processing on a received image and sends the processed image to the defect identification module; the defect identification module identifies the defects in the image by using an identification algorithm and calculates the defect degree, and sends the obtained data to the defect marking module; the defect marking module marks the identified defects, the questionable defects and the defect degrees in the three-dimensional model; and finally, transmitting the data to a bridge defect reporting subsystem, wherein the specific steps comprise:
1) loading an image file;
2) image preprocessing, namely converting an RGB image into a gray image and filtering the image;
3) edge detection, namely performing relatively accurate edge detection on the image and segmenting a crack from the background image;
4) the cracks are connected, so that the continuity of the cracks is maintained, and the actual conditions of the cracks are completely expressed;
5) identifying a linear target of the crack, matching a three-dimensional coordinate model, and marking the crack by using a visual frame;
6) failure of the system to identify defects, additional labeling is performed as well;
7) the system calculates the defect degree for identifying the defects and deduces the cause of the defects;
8) and transmitting the analysis data to a bridge defect reporting subsystem.
The bridge defect detection subsystem detection structure of the multifunctional ground station comprises: guardrail (railing), expansion joint, bridge deck pavement, bridgehead and embankment connecting portion, drainage facility, superstructure, taper slope, bank protection, mound, platform basis, support.
The bridge defect report subsystem of the multifunctional ground station integrates based on the transmitted data, and automatically generates a bridge inspection report, wherein the bridge inspection report comprises the following components: the method comprises the following steps of bridge original structure data, bridge defect pictures, defect degree index marking, defect cause inference and bridge question defects.
Aiming at the defect parts which can not be identified by some systems, the VR subsystem of the multifunctional ground station can be observed and detected in real time by professional detection personnel wearing VR glasses, and the VR subsystem is divided into a first visual angle and a third visual angle.
The process of the invention comprises the following steps:
the method comprises the following steps: the unmanned aerial vehicle collects the bridge and the environmental data around the bridge, and transmits the data to the multifunctional ground station;
step two: the 3D coordinate modeling subsystem of the multifunctional ground station establishes a 3D coordinate model of the bridge and the periphery of the bridge based on the returned data;
step three; an unmanned aerial vehicle air route subsystem of the multifunctional ground station establishes an autonomous cruising path of the unmanned aerial vehicle according to the relevant three-dimensional model and sends a signal to the unmanned aerial vehicle;
step four: the unmanned aerial vehicle acquires data of the bridge according to the autonomous cruising path and transmits the acquired data to the multifunctional ground station;
step five: the bridge defect detection subsystem of the multifunctional ground station identifies the defect part of the bridge and estimates the defect degree according to the bridge image returned by the unmanned aerial vehicle by combining with the three-dimensional model, marks the defect part in the model, and also marks the defect which cannot be identified by the system;
step six: the bridge inspection report generation subsystem of the multifunctional ground station automatically generates a bridge inspection quality report;
step seven: for bridge defects which are difficult to identify by some systems, relevant personnel carry out on-site judgment through a VR subsystem.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention breaks the problem that the existing unmanned aerial vehicle bridge detection is only limited to bridge details, adopts an oblique photography mode to acquire data of the bridge and surrounding terrain, establishes a three-dimensional model, realizes the judgment of the whole structure of the bridge, and marks the defect type, the defect degree and the defect cause on the model, so that the detection is visual and clear;
2. the invention realizes the automatic acquisition of bridge data, the automatic detection and labeling of bridge defects, the automatic generation of bridge quality detection reports, the full automation of the bridge detection process, the elimination of detection blind areas, the effective reduction of detection cost and the improvement of detection quality;
3. keep away the barrier through the ultrasonic wave module is automatic, show effective range and the precision that promotes discernment, effectively reduce unmanned aerial vehicle and patrol and examine the probability that the process takes place accidental collision and crash, reduce the cost that the bridge detected, have good economic benefits.
Drawings
In order to more clearly illustrate the technical solutions in the embodiment technologies of the present invention, the drawings used in the description of the embodiment technologies will be briefly introduced below.
FIG. 1 is a hierarchy of components of the present invention;
FIG. 2 is a diagram of the interrelationship of the various parts of the present invention;
fig. 3 is a flow chart of the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. A
The method comprises the following steps: after the air route is automatically planned, the unmanned aerial vehicle A, B is released to carry out shooting autonomously, environmental data of the bridge and the periphery of the bridge are collected in an oblique shooting mode, five lenses including a long-focus lens, a short-focus lens and an infrared lens are integrated by a camera used for oblique shooting of the unmanned aerial vehicle, the five lenses are collected at the position 20-50 m higher than the bridge, the shooting area is twice as large as the area of the bridge, the modeling precision is changed along with the height, and the overall modeling precision is smaller than 0.5 m. Unmanned aerial vehicle passes through a perpendicular, four slopes, and five different visual angles gather image data in step, and data include the GPS data of image model and each point, guarantee bridge and peripheral topography model's accuracy nature. And the data is stored in the airborne storage module and is transmitted to the multifunctional ground station through the 5G network communication module.
Step two: and the 3D coordinate modeling subsystem of the multifunctional ground station generates a three-dimensional model of the bridge body and the surrounding terrain environment based on the returned data, and the three-dimensional model can switch the model angle at any visual angle.
Step three: the unmanned aerial vehicle airline subsystem of the multifunctional ground station establishes an autonomous cruise path of the unmanned aerial vehicle C, D according to the relevant three-dimensional model, and sends a signal to the unmanned aerial vehicle C, D.
Step four: the unmanned aerial vehicle C, D carries out image acquisition to the pontic according to autonomic cruise route, and data storage is to airborne storage module, transmits to multi-functional ground satellite station through 5G network communication module. When the unmanned aerial vehicle C, D detects a bridge structure, a telephoto lens is adopted when a large crack needs to be acquired in the length direction or the outer contour line of the bridge needs to be detected; when the width of the crack needs to be measured, a short-focus lens is adopted; when the ambient light is darker, an infrared lens is adopted to collect data of the crack at the point. When the inspection time is long, the multifunctional ground station autonomously releases the unmanned aerial vehicle A, B which has completed the three-dimensional model data acquisition task, and completes the inspection task together with the unmanned aerial vehicle C, D.
Step five: the bridge defect detection subsystem of the multifunctional ground station analyzes the structural defects of the bridge according to the bridge image returned by the unmanned aerial vehicle, and comprises the following specific steps:
1) loading an image file;
2) image preprocessing, namely converting an RGB image into a gray image and filtering the image;
3) edge detection, namely performing relatively accurate edge detection on the image and segmenting a crack from the background image;
4) the cracks are connected, so that the continuity of the cracks is maintained, and the actual conditions of the cracks are completely expressed;
5) identifying a linear target of the crack, matching a three-dimensional coordinate model, and marking the crack by using a visual frame;
6) failure of the system to identify defects, additional labeling is performed as well;
7) the system calculates the defect degree for identifying the defects and deduces the cause of the defects;
8) and transmitting the analysis data to a bridge defect reporting subsystem.
Bridge defect detection subsystem detects structure includes: guardrail (railing), expansion joint, bridge deck pavement, bridgehead and embankment connecting portion, drainage facility, superstructure, taper slope, bank protection, mound, platform basis, support.
Step six: the bridge defect report subsystem of multi-functional ground station integrates based on the data that transmit, and the automatic generation bridge is patrolled and examined the report, and the bridge is patrolled and examined the report and is included: the method comprises the following steps of bridge original structure data, bridge defect pictures, defect degree index marking, defect cause inference and bridge question defects.
Step seven: the VR subsystem of multi-functional ground station to some defect parts that the system can't be discerned, can wear VR glasses by professional detection personnel and observe in real time and detect, and it is divided into two kinds of first visual angle and third visual angle.
The invention breaks the problem that the existing unmanned aerial vehicle bridge detection is only limited to bridge details, adopts an oblique photography mode to acquire data of the bridge and surrounding terrain, establishes a three-dimensional model, realizes the judgment of the whole structure of the bridge, and marks the defect type, the defect degree and the defect cause on the model, so that the detection is visual and clear; the automatic acquisition of bridge data, the automatic detection and labeling of bridge defects, the automatic generation of bridge quality detection reports, the full automation of the bridge detection process, the elimination of detection blind areas, the effective reduction of detection cost and the improvement of detection quality are realized; keep away the barrier through the ultrasonic wave module is automatic, show effective range and the precision that promotes discernment, effectively reduce unmanned aerial vehicle and patrol and examine the probability that the process takes place accidental collision and crash, reduce the cost that the bridge detected, have good economic benefits.

Claims (8)

1. An unmanned aerial vehicle rapid inspection bridge system based on a 5G technology is characterized by comprising an unmanned aerial vehicle platform (1) and a multifunctional ground station (2), wherein the unmanned aerial vehicle platform (1) comprises an unmanned aerial vehicle main body (3) and a carrying module group (4); the multifunctional ground station (2) comprises a 3D coordinate modeling subsystem (5), an unmanned aerial vehicle air route subsystem (6), a flight control subsystem (7), a bridge defect detection subsystem (8), a bridge defect report subsystem (9) and a VR subsystem (10).
2. The unmanned aerial vehicle rapid inspection bridge system based on the 5G technology according to claim 1, wherein the carrying module group (4) is composed of an image acquisition module (11), a storage module (12), a flight state processing module (13) and a 5G network communication module (14); the image acquisition module (11) consists of a long-focus lens, a short-focus lens and an infrared lens which are mutually independent, the three cameras can be respectively controlled by a multifunctional ground station, bridge structure data are acquired by adopting an oblique photography mode and are respectively transmitted to the storage module (12); the storage module (12) is in wired connection with the image acquisition module (11) carrying the module group, the flight state processing module (13) and the 5G network communication module (14) and stores bridge data and unmanned aerial vehicle flight state data obtained by oblique photography; the flight state processing module (13) comprises a sensor module and a GPS positioning navigation module, wherein the sensor module acquires distance data to ensure that the unmanned aerial vehicle keeps a safe distance of at least 0.5m with a bridge, and the GPS positioning navigation module determines information such as the course and the position of the unmanned aerial vehicle and transmits the flight state data of the unmanned aerial vehicle to the storage module (12); the 5G network communication module (14) comprises a preposed pilot frequency and a novel frame structure, is connected with the storage module (12), and is used for transmitting data stored in the storage module (12) and receiving signals sent by the multifunctional ground station (2).
3. The unmanned aerial vehicle rapid inspection Bridge system based on the 5G technology according to claim 1, wherein the 3D coordinate modeling subsystem (5) of the multifunctional ground station (2) receives Bridge data of the storage module (12), including spatial data of Bridge piers, Bridge abutments and Bridge span structures, and performs Bridge 3D modeling by combining with Open Bridge Modeler software.
4. The unmanned aerial vehicle rapid inspection bridge system based on the 5G technology according to claim 1, wherein the unmanned aerial vehicle route subsystem (6) of the multifunctional ground station (2) automatically marks detection points, required to be detected, of buildings in the inspection route according to the 3D bridge model through compiled relevant programs, the detection points comprise bridge span expansion joints, bridge head and embankment connecting parts, upper structures, conical slopes, slope protection, abutments, foundations and supports, the unmanned aerial vehicle inspection route is planned and transmitted to the flight control subsystem (7).
5. The unmanned aerial vehicle rapid inspection bridge system based on the 5G technology according to claim 1, wherein the flight control subsystem (7) of the multifunctional ground station (2) receives unmanned aerial vehicle inspection route data of the unmanned aerial vehicle route subsystem (6) and unmanned aerial vehicle flight state data transmitted by the 5G network communication module (14), controls the unmanned aerial vehicle to fly, and sends a flight instruction to the unmanned aerial vehicle.
6. The unmanned aerial vehicle rapid inspection bridge system based on the 5G technology according to claim 1, wherein the bridge defect detection subsystem (8) of the multifunctional ground station (2) comprises an image processing module (15), a defect identification module (16) and a defect marking module (17), the image processing module (15) performs filtering and noise reduction on the received image, and sends the processed image to the defect identification module (16); the defect identification module (16) identifies the defects in the image by using an identification algorithm and calculates the defect degree, and sends the obtained data to the defect marking module (17); the defect marking module (17) marks the identified defects, the questionable defects and the defect degrees in the three-dimensional model; and finally transmitting the data to a bridge defect reporting subsystem (9).
7. The unmanned aerial vehicle rapid inspection bridge system based on 5G technology according to claim 1, wherein the bridge defect reporting subsystem (9) of the multifunctional ground station (2) integrates based on the transmitted data to generate a bridge inspection report, and the bridge inspection report comprises: the method comprises the following steps of bridge original structure data, bridge defect pictures, defect degree index marking, defect cause inference and bridge question defects.
8. The unmanned aerial vehicle rapid inspection bridge system based on 5G technology according to claim 1, wherein the VR subsystem (10) of the multifunctional ground station (2) aims at defective parts which can not be identified by some systems, and professional inspectors can wear VR glasses for real-time observation and detection, and the system is divided into a first visual angle and a third visual angle.
CN202010615965.7A 2020-06-30 2020-06-30 Unmanned aerial vehicle bridge system of patrolling and examining fast based on 5G technique Pending CN111999298A (en)

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Cited By (9)

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Publication number Priority date Publication date Assignee Title
CN112802021A (en) * 2021-04-09 2021-05-14 泰瑞数创科技(北京)有限公司 Urban bridge road diagnosis method and system based on digital twin technology
CN112858476A (en) * 2021-01-13 2021-05-28 深圳市正杰智能工程有限公司 Building structure monitoring method, system, terminal and storage medium based on 5G
CN113408396A (en) * 2021-06-15 2021-09-17 广西交科集团有限公司 Bridge intelligent sensing system based on cloud computing
CN113762183A (en) * 2021-09-13 2021-12-07 墙管家建筑科技(上海)有限公司 Intelligent checking and analyzing system for existing building safety and operation method
CN114020043A (en) * 2021-12-16 2022-02-08 河南祥辰工程管理有限公司 Unmanned aerial vehicle building project supervision system and method, electronic equipment and storage medium
CN114550107A (en) * 2022-04-26 2022-05-27 深圳联和智慧科技有限公司 Bridge linkage intelligent inspection method and system based on unmanned aerial vehicle cluster and cloud platform
CN114840014A (en) * 2022-03-16 2022-08-02 深圳大学 Unmanned aerial vehicle collaborative path planning method and system for holographic bridge inspection
CN117406781A (en) * 2023-11-27 2024-01-16 温州信达交通工程试验检测有限公司 Bridge intelligent inspection system based on unmanned aerial vehicle
CN117523389A (en) * 2023-11-07 2024-02-06 温州信达交通工程试验检测有限公司 Unmanned aerial vehicle cruises disease discernment and 3D location management system

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112858476A (en) * 2021-01-13 2021-05-28 深圳市正杰智能工程有限公司 Building structure monitoring method, system, terminal and storage medium based on 5G
CN112802021A (en) * 2021-04-09 2021-05-14 泰瑞数创科技(北京)有限公司 Urban bridge road diagnosis method and system based on digital twin technology
CN112802021B (en) * 2021-04-09 2021-07-30 泰瑞数创科技(北京)有限公司 Urban bridge road diagnosis method and system based on digital twin technology
CN113408396A (en) * 2021-06-15 2021-09-17 广西交科集团有限公司 Bridge intelligent sensing system based on cloud computing
CN113408396B (en) * 2021-06-15 2022-03-18 广西交科集团有限公司 Bridge intelligent sensing system based on cloud computing
CN113762183A (en) * 2021-09-13 2021-12-07 墙管家建筑科技(上海)有限公司 Intelligent checking and analyzing system for existing building safety and operation method
CN114020043A (en) * 2021-12-16 2022-02-08 河南祥辰工程管理有限公司 Unmanned aerial vehicle building project supervision system and method, electronic equipment and storage medium
CN114840014A (en) * 2022-03-16 2022-08-02 深圳大学 Unmanned aerial vehicle collaborative path planning method and system for holographic bridge inspection
CN114550107A (en) * 2022-04-26 2022-05-27 深圳联和智慧科技有限公司 Bridge linkage intelligent inspection method and system based on unmanned aerial vehicle cluster and cloud platform
CN114550107B (en) * 2022-04-26 2022-07-26 深圳联和智慧科技有限公司 Bridge linkage intelligent inspection method and system based on unmanned aerial vehicle cluster and cloud platform
CN117523389A (en) * 2023-11-07 2024-02-06 温州信达交通工程试验检测有限公司 Unmanned aerial vehicle cruises disease discernment and 3D location management system
CN117406781A (en) * 2023-11-27 2024-01-16 温州信达交通工程试验检测有限公司 Bridge intelligent inspection system based on unmanned aerial vehicle

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