桥梁健康监测海量数据预处理及存储策略研究

Massive Data Preprocessing and Storage Strategy for Bridge Health Monitoring

针对桥梁健康监测的海量数据在预处理及存储方面的问题,结合当前大数据的分布式处理思想、数据流的滑动窗口处理技术以及小波包降噪方面的优势,提出了一种桥梁健康监测海量数据预处理及存储模型,该模型不仅可以有效保存桥梁监测的原始数据,而且把数据的预处理融入其存储过程,并可根据传感器是否工作而进行报警。结果证明了该模型应用在桥梁健康监测海量数据预处理及存储上的可行性。

In order to solve the problems of the massive data preprocessing and storage about the bridge, we propose a data preprocessing and storage model for bridge which combines the advantages of the concept of distributed processing of large data, the data stream sliding window technology and wavelet packet processing for noise reduction. The model not only saves the raw data of bridge monitoring and integrate the data preprocessing into their storage, but also alarms when the sensor is stop working. The results show that it is feasible to apply the model in massive data preprocessing and storage in bridge health monitoring.