Principal Investigator Oral Buyukozturk
Co-investigators Hao Sun , Kunal Kupwade Patil , Robert W Haupt , Robert Shin , Huseyin Sadi Kuleli , Thomas Herring , M Toksöz , Ju Li , John Fisher , Fredo Durand , William Freeman , Christoph Reinhart , John Ochsendorf , Markus Buehler , Sidney Yip
The structural health monitoring (SHM) process consists of various inter-related tasks such as sensor network management, energy optimization, information extraction, uncertainty quantification (UQ), and decision making. Accomplishment of each one of these tasks requires certain information and the objective of signal processing is to efficiently extract such information mainly from the raw signals provided by the sensor network. One of our proposed methods in this regards is the sparse generalized pencil-of-functions (SGPOF) that characterized a signal in terms of damped harmonic modes. In this method, we made use of sparsity-based regularization in order to exclude the spurious modes from the expansion of signals and hence, avoid energy leakage. Figure 6 shows a simple comparison between SGPOF and other common signal processing method.