Research On High-Speed Railway Tunnel Monitoring System Based On Computer Vision

In recent years,the safety of high-speed railway tunnels has gradually attracted great attention.As tunnel diseases pose a serious threat to the operational safety of high-speed railways,it is essential to detect the occurrence of the disease in time and take effective treatment measures to reduce the loss of life and property.At present,the detection of tunnel diseases mainly relies on periodic manual inspections.The method of real-time monitoring and automatic identification of tunnel diseases has not been applied in tunnel projects along the high-speed rail.At present,the impact of some unpredictable geological disasters on the tunnel cannot be realized in real time.In response to the above problems,this paper analyzes the visual characteristics of the diseases of high-speed railway tunnels,and designs an online monitoring system for visually observable diseases.Using mature monitoring technology,through the intelligent analysis of audio and video data,the tunnel diseases that endanger driving safety can be sensed in real time.The core content and research results of this paper are as follows:(1)Analysis of high-speed railway tunnels disease.In this paper,The high-speed railway tunnel diseases are classified into different risk levels,and the types of disease characteristics that can be automatically identified by computer vision methods are analyzed.(2)New Research on intelligent identification algorithms and schemes for visually observable tunnel diseases.According to the types of visually observable tunnel diseases,combined with algorithms such as sound source location,image background modeling,image segmentation,target detection,etc.,the tunnel visual crack detection and railway lining fall down event monitoring are realized.(3)Design a visually observable real-time monitoring system for tunnel diseases.Design video surveillance and microphone array equipment configuration deployment plan.The use of intelligent analysis algorithms for real-time processing of audio and video data to assist railway workers to identify tunnel diseases that are critical to driving safety in advance,and gain more time for railway emergency treatment,thereby reducing the risk of serious railway safety accidents.