Fault detection method and system for tunnel dome lights based on improved localization loss function

US11908120B2 · kind B2 · utility

Assignee

• EAST CHINA JIAOTONG UNIVERSITY · CN

Inventors

• Gang Yang · Nanhu, CN
• Cailing Tang · Nanchang, CN
• Lizhen Dai · Nanchang, CN
• Zhipeng Yang · Longbeilingcun, CN
• Yuyu Weng · Nanchang, CN
• Hui Yang · Taichung, TW
• Rongxiu Lu · Nanchang, CN
• Fangping Xu · Nanchang, CN
• Shuo Xu · Nanchang, CN

Key dates

• Filing date: Aug 25, 2022
• Grant date: Feb 20, 2024
• Expiry date: Oct 12, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T2207/20084
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A fault detection method and system for tunnel dome lights based on an improved localization loss function. The method includes: constructing a dataset of tunnel dome light detection images; acquiring a you only look once (YOLO) v5s neural network based on the improved localization loss function; training the YOLO v5s neural network according to the dataset to obtain a trained YOLO v5s neural network; acquiring a to-be-detected tunnel dome light image; detecting, with the trained YOLO v5s neural network, the to-be-detected tunnel dome light image to obtain position coordinates of luminous dome lights; and determining, according to the position coordinates of the luminous dome lights, whether a fault occurs in the tunnel dome lights. The present disclosure can accurately localize the tunnel dome lights and label the positions, and can detect whether the tunnel dome lights work normally according to a relative positional relationship between the labeled dome lights.