Sensors: Statistical Algorithm Development for Distributed Sensor Networks with Application to Structural Health Monitoring and State Assessment

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ABSTRACT0428585PI: John SweetmanTexas Engineering Experiment StationNew statistical and random vibration techniques are developed and applied to interpret measured data from distributed sensor networks. The new methods build statistical distributions of selected random variables developed from the data and dynamic numerical models of the structure. The overall goal is to develop methodologies to identify relatively minor structural damage or changes in structural state prior to initiation of a major structural failure. Application within the project is marine risers on offshore oil-production structures and to structural health monitoring of onshore structures; each of these applications makes use of extensive measured data. The offshore application addresses vortex induced vibrations of marine risers, a complex problem due to irregular variations in system mass caused by fluid-structure interaction. These vibrations are a dominant design consideration for marine risers in high current, deep-water areas. The onshore application offers an improved methodology for monitoring the structural condition of various civil structures. The work is being done jointly between two campuses of Texas A&M University (College Station and Galveston). The project and its results will enhance the graduate and undergraduate engineering curricula at both campuses. The project also directly increases interaction between the two campuses, which will lead to greater future collaboration. This project is supported under the Sensors Initiative NSF 04-522.