Modal Identification Research Of Wireless Smart Sensor Based On HHT

The technique for structural health monitoring is in widespread use in the field ofcivil engineering, which judges the situation of the structural health through dealingwith the dynamic signal. With the development of the micro-electronics and theprogress of interdiscipline, the structural health monitoring based on wireless smartsensors network is growing gradually and secures success in the competition withtraditional field-bus technique in the way of detection and its performance. And it hasbeen applied in the practical engineering.The article combines the measured dynamic test of the Binzhou Yellow RiverBridge Model with model analysis algorithm and downloads the fundamental algorithmof modal identification to the wireless smart sensor node to achieve the aim of on-boardcomputing of the dynamic signal detected in the experiment. So the node can send outthe intrinsic mode functions directly to base station and conduct local signal proceeding.The model analysis algorithm used in this article is a parametric recognitionmethod based on Hilbert-Huang Transformation, which is a time-frequency method fornon-linear and non-stationary signal. The mainly part of the algorithm is directlyproceeding Empirical Mode Decomposition to any complex signal. Then the signal isdecomposed into limited intrinsic mode functions. The characteristic of the EmpiricalMode Decomposition is partial time-frequency and self-adapting. The article verifiesthe effect of modal parameter identification based on Hilbert-Huang Transform throughhandling dynamic signal by programming Hilbert-Huang Transformation on MATLABplatform.The IRIS sensors used in the article is a intelligent wireless sensor invented byAmerican Crossbow which has the ability of on-board computing, on which we create asimple wireless smart sense network for structural health monitoring. Through TinyOSoperating system, we can carry out second development by embedding interrelated filterand Empirical Mode Decomposition programs on the sensor node. Then we get thesmart sensor node which can directly output intrinsic mode functions of dynamicaccelerator signal via implementing the on-board computing of modal identification.The result of comparing the output of on-board computing with the other computingplatform showed that the output of on-board computing is correct. Finally, we achievethe aim of the true time on-line signal processing for structural modal parameteridentification by experimental research.