ABSTRACT
The basic connotation of bridge health monitoring is to send warning signals to the bridge maintenance and management decision-making body when the bridge is in the special climate and traffic conditions or serious abnormal operating conditions, through the monitoring and evaluation of the bridge state. With the development of the economy and people’s increasingly attention to disaster prevention and mitigation, the structural health monitoring system research has become a hot research direction in many fields such as aerospace, defense, composite materials, civil engineering, etc. Many countries have established the health monitoring system in the new or built important engineering structures.
These structure monitoring systems generally contain dozens to hundreds sensors, producing hundreds to thousands MB monitoring data daily. According to these vast amounts of raw data, many professionals are only to process and analyze a part of it according to their own research expertise, such as wind, seismic, durability and fatigue, etc., and the methods of overall carding, analysis and mining are lacked. Data analysis is like a person’s thinking, which is the key part of the monitoring system. So, there is no any value that if the health monitoring system without thinking ability. Therefore, it is necessary to establish a quick and effective method to analyze and compress these massive amounts of raw data. After compression and analysis, these data can preliminarily reflect the effective information of environment, vehicle load and the key structural response, for the correct evaluation of large structural health condition, and deeply understanding to mechanical properties of structure, to ensure the structure safety operation.
In this paper, the huge amounts of raw data from Zhoushan sea-crossing bridge structure monitoring system has been taken as the research object. In view of the actual demand of daily maintenance and management work, the large bridge structure monitoring data analysis system was developed which can seamless dock with the original monitoring system. The functions of this system include: first, make the result data can effectively reflect the current mechanical properties of structures, after the different types of raw data have been processed and analyzed; second, the amount of data can be reduced substantially after processing compared with the number of raw data, usually no more than 5%. third, the subsequent data display and structure evaluation can just calls the result data and no longer need to call the raw data, that the work efficiency of data display and evaluation will be greatly increased.
