CN-122022274-A - Highway engineering inspection platform based on unmanned aerial vehicle

CN122022274ACN 122022274 ACN122022274 ACN 122022274ACN-122022274-A

Abstract

The invention relates to the technical field of highway engineering, in particular to a highway engineering inspection platform based on an unmanned aerial vehicle, which comprises a highway model module, a work task management module, an inspection module, a model updating module and an operation management module, wherein the highway model module is used for constructing a model before highway construction through the unmanned aerial vehicle and constructing a virtual model according to construction requirements, the work task management module is used for planning a construction task and recording a planning operation task, the inspection module is used for setting an inspection task and an inspection route so as to obtain a real-time inspection image through the unmanned aerial vehicle, the model updating module is used for updating the model before highway construction in the highway construction process so as to generate the highway model according to construction progress, the management center comprises a construction management module and the operation management module is used for identifying hidden danger situations of the highway according to the inspection image. The invention can ensure the progress and safety of highway construction and ensure the safe and stable operation of the highway.

Inventors

SUN HUI
LI SHIJIAN
RONG YAN
YANG YIQIONG
SU QIANG
MA WENHUI
LU YUGE
Lan Songyao
HUANG SHENG
NONG YUHONG
ZHANG XINYUE
Peng Yidiao
WU MENGLAN
LI YONGYOU
XIE WEIWEI
HAN YU
Lan Qiuzu
LIN FENG
WEI YONGCAI
CHEN XIAOQIANG

Assignees

广西路桥工程集团有限公司

Dates

Publication Date: 20260512
Application Date: 20260106

Claims (10)

1. The highway engineering inspection platform based on the unmanned aerial vehicle is characterized by comprising a highway model module (1), a work task management module (2), an inspection module (3), a model updating module (4) and a management center (5), The highway model module (1) is used for constructing a three-dimensional highway model, the highway model module (1) acquires highway point cloud data through an unmanned plane, the highway model module (1) processes the highway point cloud data to construct a model before highway construction before construction, and the highway model module (1) constructs a virtual model according to construction requirements; The work task management module (2) is used for storing a planned construction task and a planned operation task; The inspection module (3) is used for setting an inspection task and an inspection route, and the inspection module (3) controls the unmanned aerial vehicle to carry out highway shooting according to the inspection task and the inspection route so as to obtain real-time inspection images; The model updating module (4) is used for acquiring data of the inspection module (3) so as to update the model before highway construction in the highway construction process, so that a highway model is generated according to the construction progress; The management center (5) is used for acquiring data of the highway model module (1), the work task management module (2) and the inspection module (3), the management center (5) comprises a construction management module (51) and an operation management module (52), the construction management module (51) is used for obtaining the progress condition of highway construction by matching and comparing the inspection image with the planned construction task, and the operation management module (52) is used for identifying hidden danger conditions of the highway according to the inspection image.
2. The unmanned aerial vehicle-based highway engineering inspection platform of claim 1, wherein unmanned aerial vehicle measurement is performed on a highway to obtain highway point cloud data, the highway model module (1) processes the point cloud data through Civil 3D to generate a highway pre-construction model with position coordinates, and the model updating module (4) updates the highway pre-construction model to a highway model with position coordinates according to the data of the inspection module (3).
3. The highway engineering inspection platform based on the unmanned aerial vehicle according to claim 2, wherein the inspection module (3) comprises an inspection task setting sub-module (31) and an inspection route setting sub-module (32), The inspection task setting sub-module (31) is used for acquiring data of the planned construction task so as to obtain a required inspection position, the inspection task setting sub-module (31) marks the required inspection position in the highway model, and the inspection task setting sub-module (31) obtains inspection coordinates according to the marks of the highway model; The routing inspection route setting sub-module (32) is used for acquiring data of the highway model module (1) and the routing inspection task setting sub-module (31), and the routing inspection route setting sub-module (32) determines an optimal cruising route according to the routing inspection coordinates and the highway model.
4. The unmanned aerial vehicle-based highway engineering inspection platform of claim 3, wherein the inspection route setting sub-module (32) generates a plurality of cruising routes according to the inspection coordinates and the topography condition, and the inspection route setting sub-module (32) calculates and obtains an optimal solution according to the topography threat cost: Formula (1) Wherein, the To pass from the start point through the node The total cost to reach the endpoint, Is from the start point to the node Is set, the actual path cost of (a); is from the start point to the node Is the smallest possible cost of (a); Is a node The terrain threat costs of (a); and generating paths with different terrain adaptations by adjusting different terrain weight coefficients for the terrain weight coefficients.
5. The unmanned aerial vehicle-based highway engineering inspection platform of claim 4, wherein the terrain threat cost comprises a gradient threat cost and an obstacle threat cost, and the gradient threat cost calculation method comprises the following steps: Formula (2) Wherein, the Threat cost for grade; Is the current grade; the maximum allowable gradient of the unmanned aerial vehicle is set; Formula (3) Wherein, the To the first path Distance of individual obstacles; As the threat coefficient of the obstacle, determining according to the volume shape of the obstacle; is the total number of obstacles.
6. The highway engineering inspection platform based on unmanned aerial vehicle according to claim 3, wherein the inspection module (3) further comprises an aerial photographing obstacle avoidance sub-module (33), the aerial photographing obstacle avoidance sub-module (33) is used for identifying obstacles in the aerial photographing process of the unmanned aerial vehicle, the photographing angle and the position of the unmanned aerial vehicle are adjusted, and the obstacle avoidance step of the aerial photographing obstacle avoidance sub-module (33) comprises the following steps: A1. the obstacle is shot in real time through the unmanned aerial vehicle so as to dynamically update the obstacle, and the coordinates and the shape of the obstacle are calibrated: A2. generating a foreign no-fly area according to the coordinates and the shape of the obstacle, and calculating the height of the obstacle; A3. and performing voxel sampling according to the height of the anisotropic non-flying area and the height of the obstacle to generate an initial viewpoint, generating a safety viewpoint according to a scene depth model, and performing quality optimization and viewpoint compensation on the safety viewpoint to enable an unmanned aerial vehicle to fly and shoot in the safety viewpoint.
7. The unmanned aerial vehicle-based highway engineering inspection platform of claim 1, wherein the construction management module (51) comprises a construction progress management sub-module (511) and a safety management sub-module (512), The construction progress management sub-module (511) is used for analyzing the inspection image, and the construction progress management sub-module (511) is used for carrying out matching comparison on the inspection image and the corresponding part of the virtual model so as to calculate and obtain data of the actual completion percentage of the task; the construction progress management sub-module (511) performs semantic analysis on the planned construction task to judge data of a task plan completion percentage at the current time, compares the data of the task actual completion percentage with the task plan completion percentage to obtain a delay value, and when the delay value is larger than a delay threshold value, the construction progress management sub-module (511) sends an abnormal reminding signal and marks the abnormal reminding signal in the virtual model and the highway model; the safety management sub-module (512) is used for marking a constructor who does not wear a safety helmet through the acquisition of the inspection image and through a visual algorithm so as to obtain a marked image, the safety management sub-module (512) is used for obtaining a corresponding construction task and responsible personnel in the planning construction task in a matching mode according to the coordinate position corresponding to the inspection image, and the safety management sub-module (512) is used for sending the marked image to the corresponding responsible personnel terminal.
8. The unmanned aerial vehicle-based highway engineering inspection platform of claim 7, wherein the construction progress management sub-module (511) is further configured to adjust the construction progress, and the construction progress management sub-module (511) adjusts the construction progress according to the environmental impact and the delay threshold: Formula (4) Wherein, the The construction progress after being adjusted; The construction progress before adjustment is carried out; is the first Weights of individual environmental factors; is the first Influence coefficients of the individual environmental factors; % is a delay threshold and is adjusted for different circumstances.
9. The unmanned aerial vehicle-based highway engineering inspection platform of claim 1, wherein the operation management module (52) comprises a hidden danger identification sub-module (521) and a hidden danger monitoring sub-module (522), The hidden danger identification sub-module (521) is used for acquiring the inspection image, and acquiring a key image in the inspection image according to the position coordinates of the inspection image, and the periodic inspection module (521) processes the key image through a deep learning algorithm to acquire a real-time suspected hidden danger image and corresponding position data thereof; The hidden danger identification sub-module (521) collects suspected hidden danger data at the position corresponding to the suspected hidden danger image through a plurality of sensors carried by the unmanned aerial vehicle, the hidden danger identification sub-module (521) identifies and obtains a final hidden danger image through multi-sensor fusion mode of the suspected hidden danger data, and marks hidden danger of the final hidden danger image. The operation management module (52) further comprises a hidden danger monitoring sub-module (522), wherein the hidden danger monitoring sub-module (522) is used for acquiring data of the hidden danger identification sub-module (521), the hidden danger monitoring sub-module (522) acquires hidden danger influence values through calculation of the hidden danger positions, hidden danger types and hidden danger data of the final hidden danger image, and when the increase rate of the hidden danger influence values is larger than an increase threshold value, the hidden danger monitoring sub-module (522) sends out alarm signals.
10. The unmanned aerial vehicle-based highway engineering inspection platform of claim 9, wherein the operation management module (52) further comprises a hidden danger coordination sub-module (523), the hidden danger coordination sub-module (523) is used for data storage of a historical processing scheme of highway hidden danger, the hidden danger coordination sub-module (523) matches the hidden danger position, the hidden danger type and the hidden danger data in the historical processing scheme through a semantic matching algorithm so as to obtain a similar hidden danger processing scheme, and the hidden danger coordination sub-module (523) uses the similar hidden danger processing scheme as a coordination scheme.

Description

Highway engineering inspection platform based on unmanned aerial vehicle Technical Field The invention relates to the technical field of highway engineering, in particular to a highway engineering inspection platform based on an unmanned aerial vehicle. Background The highway engineering full life cycle inspection refers to a management process for ensuring the safe and efficient operation of a highway through systematic inspection activities from the planning, design, construction and operation of the highway project to the maintenance of the highway project. The existing highway engineering full life cycle inspection work mainly relies on manual inspection, traditional video monitoring and single unmanned aerial vehicle aerial photography, and has the core problems of low efficiency, incomplete coverage, poor precision, response lag and the like. The method has the advantages of low metering efficiency of the meter before construction, high metering difficulty of the earth and stone in the construction process, manual measurement of the land and stone, large drop and other terrains, errors exceeding 15%, dependence on manual pile number extraction, time consumption and easy leakage, lag in the construction process, 20 km less than the manual inspection day, long hidden danger discovery period, 30 minutes exceeding of emergency response, high maintenance risk in the operation period, dependence on equipment such as hanging baskets for bridge detection, traffic sealing influence, insufficient coverage of high piers and mountainous areas, and easy leakage detection of diseases. Disclosure of Invention In order to solve the problems, the invention provides an unmanned aerial vehicle-based highway engineering inspection platform which can ensure the progress and safety of highway construction and ensure the safe and stable operation of a highway. In order to achieve the above purpose, the technical scheme adopted by the invention is as follows: A highway engineering inspection platform based on unmanned aerial vehicle, which comprises a highway model module, a work task management module, an inspection module, a model updating module and a management center, The highway model module is used for constructing a three-dimensional highway model, acquires highway point cloud data through an unmanned plane, processes the highway point cloud data to construct a model before highway construction before construction, and constructs a virtual model according to construction requirements; The work task management module is used for storing a planned construction task and a planned operation task; the inspection module is used for setting an inspection task and an inspection route, and controlling the unmanned aerial vehicle to carry out highway shooting according to the inspection task and the inspection route so as to obtain real-time inspection images; The model updating module is used for acquiring data of the inspection module so as to update the model before highway construction in the highway construction process, so that a highway model is generated according to the construction progress; The management center is used for obtaining data of the highway model module, the work task management module and the inspection module, the management center comprises a construction management module and an operation management module, the construction management module is used for obtaining the progress condition of highway construction by matching and comparing the inspection image with the planned construction task, and the operation management module is used for identifying hidden danger conditions of the highway according to the inspection image. Further, unmanned aerial vehicle measurement measures the highway to obtain highway point cloud data, and the highway model module processes the point cloud data through Civil 3D to generate a highway pre-construction model with position coordinates, and the model update module updates the highway pre-construction model to a highway model with position coordinates according to the data of the inspection module. Further, the inspection module comprises an inspection task setting sub-module and an inspection route setting sub-module, The inspection task setting sub-module is used for acquiring data of the planned construction task so as to obtain a required inspection position, the inspection task setting sub-module marks the required inspection position in the highway model, and the inspection task setting sub-module obtains inspection coordinates according to the marks of the highway model; The routing inspection route setting submodule is used for obtaining data of the highway model module and the routing inspection task setting submodule, and the routing inspection route setting submodule determines an optimal cruising route according to routing inspection coordinates and the highway model. Further, the routing inspection route setting submodule generates a plurality of cruising