Research To Health Diagnosis And Early Warning Of Highway Tunnel Based On Things

Due to the influence of factors on highway tunnel such as formation pressure, the roles of corrosive medium, human factors and auto cycle load, tunnel structure will then be damaged and instability will occur. Thus tunnel health will be deteriorated and the tunnel will even collapse. With the increasing mileage of highway tunnel in our country, how to effectively prevent the deteriorating effect on traffic safety of the tunnel health becomes necessary. By the analysis of the diagnosis of tunnel health, this article builds an early warning system of tunnel health diagnosis, thus forming a set of highway tunnel health diagnosis of early warning system which integrates the technology of Internet of things and the comprehensive diagnosis, in order to achieve the health degradation trend during the period of highway tunnel operation real-time diagnosis and early warning. The main research results are as follows:(1)Research has conducted on the highway tunnel health diagnosis and early warning platform overall function structure framework, including platform structure, composition and communication, etc.(2)Based on the application technology of Internet of things, the intellectualized and facilitate control on highway tunnel health diagnostic information and facilitation has been realized. Also the high efficiency, stable and intelligent remote communication solution has been developed with the combination of the reality of highway tunnel monitoring information remote communication.(3)With reference to relevant national laws and regulations, detailed diagnostic analysis has been made to the health status of the tunnel we study, early warning index system of tunnel health diagnosis has been build and methods of the establishment, the measurement and the combination weighting on expressway tunnel health diagnosis have been discussed. On the basis of decision criteria established diagnosis of early warning indicators, we establish a set of early warning indicators evaluation of the highway tunnel health diagnosis, and divide the tunnel health grade quantitative standard as well as the diagnosis of early warning level.(4)Through the practical research of highway tunnel, on the one hand, we establish the tunnel health diagnosis and early-warning index weight; On the other hand, we put forward the tunnel health diagnosis early warning method of fuzzy neural network by the integrated use of interdisciplinary technology such as neural networks and fuzzy logic and the basis on the diagnosis of early warning concept.(5)Based on the above theory and technology research, with Wuchiba highway tunnel as an example, we develop Wuchiba highway tunnel health diagnosis of early warning platform.