KR-20260065021-A - Smart System for Structural Safety Diagnosis Using Unmanned Vehicles

Abstract

The present invention provides a function to inspect a structure along an automated route using an unmanned vehicle and accurately measure the location and size of damaged areas. By detecting temperature changes, cracks, and damage conditions in real time through sensors mounted on the unmanned vehicle and transmitting this data to a server for analysis, efficiency and accuracy can be enhanced. In addition, by intuitively providing the location and size of defects through 3D modeling, a user-friendly interface (UI) can be provided that visualizes data, allowing users to easily identify the condition of the structure and take action.

Inventors

• 이준성
• 서정헌
• 옥동윤
• 고성윤
• 김찬혁
• 이기봉
• 문희영
• 서두원
• 박윤민
• 김윤수
• 황설희
• 이성진
• 최으뜸

Assignees

• 주식회사 가설안전구조연구
• 경상국립대학교산학협력단

Dates

Publication Date

20260508

Application Date

20241031

Claims (8)

1. In a smart system for structural safety diagnosis using unmanned vehicles, The above-mentioned unmanned mobile vehicle that checks the condition of a structure to collect and generate data, and measures and determines risk factors in real time through the said data; A server that receives data collected in real time from the above-mentioned unmanned mobile object and the above-mentioned risk factors, and analyzes and diagnoses dangerous situations and abnormal situations through the received data and risk factors; A smart system for structural safety diagnosis including
2. In claim 1, The above system is, A user interface that provides fused data of the above server to the user; Includes more, The above user interface is, The method is characterized by providing a way to visually display the fusion data on the server and to intuitively determine the location and status of the defects, wherein It is characterized by visually displaying the location of detected cracks to allow the user to determine the location, size, and status information of the detected defects and take action, and The above user interface is, A smart system for structural safety diagnosis further comprising the characteristic that, in the case where the above-mentioned unmanned mobile vehicle is configured, an administrator or user directly manages and operates the unmanned mobile vehicle through a user interface without going through a server.
3. In claim 2, The above-mentioned unmanned mobile body is, A thermal imaging sensor module that detects temperature changes in a structure and identifies defects and damaged areas; A LiDAR sensor module that generates detailed 3D geometry of a structure and precisely measures the location and size of cracks; A transmission module that measures the condition of a structure in real time through data collected by the thermal imaging sensor module and the lidar sensor module, determines risk factors, and transmits the data in real time to the server and the user interface; A receiving module that receives flight (movement) path data transmitted from the above server and modifies the flight (movement) path in real time based thereon; An automatic flight (movement) path adjustment module that automatically adjusts the flight (movement) path according to the complex shape of the structure, thereby enabling precise inspection even in difficult terrain; and A battery management module that monitors battery consumption in real time during flight (movement), dynamically manages energy according to the flight (movement) path and workload, and transmits a warning message to the unmanned vehicle and the user interface and performs an emergency landing when the battery of the unmanned vehicle falls below a set threshold; A smart system for structural safety diagnosis characterized by further including
4. In claim 3, The above server is, A data preprocessing module that processes the collected data transmitted from the above unmanned mobile vehicle and performs preprocessing work to improve the accuracy of the collected data; Includes, The above data preprocessing module is, A smart system for structural safety diagnosis characterized by converting the above-mentioned collected data into analysis data using a labeling system established through noise removal, filtering, and normalization processes, and thereby precisely processing defect data to enable real-time analysis.
5. In claim 4, The above server is, A crack detection module that automatically detects cracks and defects in a structure through an AI-based deep learning model based on the preprocessed analysis data; Includes, The above crack detection module is, A smart system for structural safety diagnosis characterized by using a CNN-based YOLO model and generating defect data by integrating GNSS and LiDAR information to track location.
6. In claim 5, The above server is, A data fusion module that stores setting values for the above risk factors and above abnormal situations, integrates and analyzes the defect data of the crack detection module based on the collected data of the thermal imaging sensor module and the lidar sensor module of the unmanned vehicle and the above risk factors, and combines defect location and status information to diagnose risk situations and abnormal situations and generates fusion data; Includes, The above fusion data is, A smart system for structural safety diagnosis characterized by combining the above-mentioned collected data and risk data, transmitting the data analyzed in real-time from the server to the above-mentioned user interface, and providing the status of the structure in real-time.
7. In claim 6, The above server is, A path transmission module that calculates and modifies the flight (movement) path of the above unmanned mobile vehicle in real time and transmits the modified flight (movement) path information to the above unmanned mobile vehicle through the transmission module; An unmanned vehicle control module that controls the unmanned vehicle to fly (move) through flight (movement) path information received by the receiving module; A defect prediction module that analyzes the risk data and structural condition data measured by the unmanned mobile vehicle through an AI-based deep learning model and immediately transmits them to the server, and analyzes the data collected by the unmanned mobile vehicle to predict the possibility of defect occurrence in the structure; and A notification module that warns of future risk situations based on the predicted data of the above-mentioned defect prediction module; A smart system for structural safety diagnosis characterized by including
8. In claim 6, The above user interface is, A 3D modeling module that converts defect data collected by the above-mentioned unmanned vehicle into a 3D model and provides visual monitoring through various devices and platforms; Includes, A smart system for structural safety diagnosis characterized by including a function that transmits data measuring the condition of a structure in real time and risk factors from the thermal imaging sensor module and the lidar sensor module of the unmanned vehicle to the user, and provides the current location and condition of the unmanned vehicle and real-time streamed building exterior video, thereby enabling the user to monitor the condition of the unmanned vehicle and the location of defects in real time.

Description

Smart System for Structural Safety Diagnosis Using Unmanned Vehicles The present invention relates to a smart system for structural safety diagnosis using an unmanned vehicle that utilizes unmanned vehicles and various sensor technologies. The system is capable of detecting abnormal signs in a structure in real time, collecting and analyzing data to rapidly evaluate the safety status of a structure, and identifying and responding to problems in advance. In modern society, the importance of the safety industry is increasing day by day, and in particular, the safety management of various structures such as construction sites, bridges, tunnels, and public infrastructure is directly linked to social stability and the protection of people's lives. Accordingly, the development of safety management systems utilizing advanced technology is essential. Traditionally, humans have directly accessed structures to diagnose their safety status and carry out maintenance work; however, this method consumes a significant amount of time and money and has limitations in locations that are difficult for humans to access or in complex environments. For example, defects occurring in structures such as the undersides of bridges or slopes are difficult for humans to inspect directly and are easily missed, which can lead to fatal accidents. Most current safety inspection methods are manual. The primary approach involves humans reviewing captured photos or videos to identify the location and size of damaged areas and recording this information on paper or drawings. However, because this manual method relies on the subjective judgment of each worker, it suffers from inconsistent results and limits the accuracy of the diagnosis. Visually inspecting and arbitrarily marking the location of cracks or defects can lead to errors and makes accurate defect analysis difficult. The severity of these issues is amplified, particularly in large-scale structures, highlighting the need for rapid and accurate safety inspections. In addition, structural inspection work in public places such as roads inevitably entails occupying the road, which disrupts traffic flow and increases the risk of traffic accidents. The longer the time spent blocking or occupying a structure during the inspection process, the greater the risk of accidents, which acts as a threat to public safety. [Prior Art Literature] [Patent Literature] Republic of Korea Registered Patent No. 2080490 FIG. 1 is a diagram showing the schematic flow of a system according to the present invention. FIG. 2 is a schematic diagram showing the configuration of an unmanned mobile body according to the present invention in a block format. FIG. 3 is a schematic diagram showing the configuration of a server according to the present invention in a block format. FIG. 4 is an example image measured by a thermal imaging sensor module and a lidar sensor module of an unmanned mobile vehicle according to the present invention. Figure 5 is an image showing the data processing process of a server according to the present invention. Figure 6 is an example image of a result according to the data preprocessing method according to the present invention. FIG. 7 is a schematic diagram of a crack detection technology according to the present invention. FIG. 8 is a schematic diagram illustrating the process in which a user interface according to the present invention receives data from a thermal imaging sensor module and a lidar sensor module, and transmits commands to an unmanned vehicle through an unmanned vehicle control module. FIG. 9 is a flowchart of the user interface of a structure diagnosis system using an unmanned mobile body according to the present invention. The present invention will be described below with reference to the attached drawings. However, the present invention can be implemented in various different forms and is therefore not limited to the embodiments described herein. In order to clearly explain the present invention in the drawings, parts unrelated to the explanation have been omitted, and similar parts throughout the specification have been given similar reference numerals. Throughout the specification, when it is stated that a part is "connected (connected, in contact, combined)" with another part, this includes not only cases where they are "directly connected," but also cases where they are "indirectly connected" with other members in between. Furthermore, when it is stated that a part "includes" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but rather allows for additional components to be provided. The terms used in this specification are used merely to describe specific embodiments and are not intended to limit the invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this specification, terms such as “comprising” or “having” are intended to indicate the existen