Optimizing the data acquisition rate for a remotely controllable structural monitoringsystem with parallel operation and self-adaptive sampling

Abstract

We present a novel technique that optimizes the real-time remote monitoring and control ofdispersed civil infrastructures. The monitoring system is based on fiber Bragg gating(FBG) sensors, and transfers data via Ethernet. This technique combines parallel operationand self-adaptive sampling to increase the data acquisition rate in remote controllablestructural monitoring systems. The compact parallel operation mode is highly efficient atachieving the highest possible data acquisition rate for the FBG sensor based local dataacquisition system. Self-adaptive sampling is introduced to continuously coordinate localacquisition and remote control for data acquisition rate optimization. Key issues whichimpact the operation of the whole system, such as the real-time data acquisitionrate, data processing capability, and buffer usage, are investigated. The resultsshow that, by introducing parallel operation and self-adaptive sampling, the dataacquisition rate can be increased by several times without affecting the systemoperating performance on both local data acquisition and remote process control.