A BIM technology-based underwater structure damage identification and management method

• Autorzy: Li Xiaofei , Su Rongrong , Cheng Peng , Sun Heming , Meng Qinghang , Song Taiyi , Wei Mengpu , Zhang Chen

Identyfikatory

DOI

10.24425/bpasts.2023.144602

• Języki publikacji: EN

Abstrakty

EN

With the continuous development of bridge technology, the condition assessment of large bridges has gradually attracted attention. Structural Health Monitoring (SHM) technology provides valuable information about a structure's existing health, keeping it safe and uninterrupted use under various operating conditions by mitigating risks and hazards on time. At the same time, the problem of bridge underwater structure disease is becoming more obvious, affecting the safe operation of the bridge structure. It is necessary to test the bridge’s underwater structure. This paper develops a bridge underwater structure health monitoring system by combining building information modeling (BIM) and an underwater structure damage algorithm. This paper is verified by multiple image recognition networks, and compared with the advantages of different networks, the YOLOV4 network is used as the main body to improve, and a lightweight convolutional neural network (Lite-yolov4) is built. At the same time, the accuracy of disease identification and the performance of each network are tested in various experimental environments, and the reliability of the underwater structure detection link is verified.

Słowa kluczowe

EN

building information modelling; underwater structural disease; damage identification; deep learning

PL

modelowanie informacji o budynku; identyfikacja uszkodzeń; uczenie głębokie; uszkodzenie podwodnej konstrukcji

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2023
• Tom: Vol. 71, nr 2
• Strony: art. no. e144602
• Opis fizyczny: Bibliogr. 28 poz., rys., tab.

Twórcy

autor

Li Xiaofei

• College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China

autor

Su Rongrong

• College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China

autor

Cheng Peng

• College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China

autor

Sun Heming

• ZJYY (Dalian) Bridge Underwater Inspection Co., Ltd. Dalian 116023, China

• https://orcid.org/0000-0003-1508-5767

autor

Meng Qinghang

• College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China

autor

Song Taiyi

• College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China
• ZJYY (Dalian) Bridge Underwater Inspection Co., Ltd. Dalian 116023, China

autor

Wei Mengpu

• College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China

autor

Zhang Chen

• College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China
• ZJYY (Dalian) Bridge Underwater Inspection Co., Ltd. Dalian 116023, China

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).