Font Size: a A A

The Research Of Health Monitoring Systems At Highway Tunnel Based On FNN

Posted on:2011-04-08Degree:MasterType:Thesis
Country:ChinaCandidate:W D YuFull Text:PDF
GTID:2132360305462653Subject:Road and Railway Engineering
Abstract/Summary:PDF Full Text Request
With the large-scale construction of highway tunnel in China, the problem of highway tunnel disease is quite serious. Second lining of tunnel cracks is one of the most frequent diseases in the highway tunnel construction, which adversely impacts the project quality as well as traffic safety. By borrowing data from the highway tunnel safety monitoring project in Zhejiang province, the thesis adopts long-term on-site monitoring data, conducts the second lining of tunnel cracks finite element modeling, resolves to assessment modeling based on fuzzy neural networks, and then evaluates the safety of the second lining of tunnel cracks occurred on the stage of tunnel operation. The results are as follows:1. The research studies tunnel cracks by borrowing data from Zhu-Yong highway tunnel safety monitoring project and basing on the theories of tunnel lining cracks and existing projects. This includes the patterns,types and distributions of lining cracks, and takes into consideration managing and analyzing monitoring data in circumstances of varied geologies and supporting patterns, etc..2. A finite element model of spring-contact tunnel in complex lining is established by using data from monitored tunnels and is used to analyze varied lining cracking reasons and discover the rules of stress-intensity factor changes internally and externally, and put forward the evaluation standards for the safety of cracks.3. Having borrowed the studies of safety assessment in the fields of bridging, motor vehicles and aviation as well as comparing the current assessment methods, this research selects fuzzy neural networks as the method to evaluate the safety of tunnel lining cracks.4. According to the standards of assessing the safety of lining cracks, the research sets up an assessment model on the basis of fuzzy neural networks, and then imports the data collected on site as sample to make a fuzzy assessment from which the assessment result is drawn about the safety of tunnel lining cracks.5. By summarizing and studying the current technology of health monitoring and assessing home and abroad, the research analyzes data by employing the health monitoring software of the actual project as well as managing varied real-time monitoring data collected, and makes a final assessment which is used as reference for conducting tunnel security monitor as well as preventing lining cracks.
Keywords/Search Tags:Fuzzy Neural Networks (FNN), Healthy Monitoring Systems, Lining Cracks, Temperature Stress, Stress Intensity Factors, Safety Assessment, FEM, Data Base
PDF Full Text Request
Related items