应我院智能检测与仪器研究所徐光华、张小栋两位教授的邀请，美国奥克拉荷马州立大学电气与计算机工程学院成琪副教授、博士来校进行学术讲座交流，特请感兴趣的师生届时光临。

讲座题目：系统健康管理中的分布式时空信号处理方法

讲座地点：曲江校区西五楼（国家重点实验室）A228会议室

讲座时间：2013年7月26日（周五）上午9：00-11：00

Abstract: System anomalies/damages due to improper maintenance and fatigue are significant causes and contributing factors in many accidents across the world. Health management is considered to be critical for accurately locating the onset of small anomalies to detect potential failures earlier, formulating an effective mitigation strategy, thus maintaining the integrity of systems. The concept of health management has been around for many years. Most research in health management focuses on the development of advanced sensing technologies. More recently, large numbers ofin-situsensors can be deployed on or inside the system for non-destructive health management purposes. This imposes new challenges. This talk focuses on the emerging and more acute issue on how to efficiently process the large amount of collected sensing data for improved detection/estimation accuracy and timeliness of decision making. Specifically, we consider two problems that arise in anomaly/fault detection using wireless sensor networks (WSNs). One is for dynamic systems, in which there exists complicated correlation between distributed sensors. We investigate the effect of correlation on the accuracy of decision making and develop two approximation models when there is no way to represent or obtain exact correlation. The second problem is on spatial event region detection, in which sensor nodes may observe heterogeneous regions, and the underlying phenomena at sensor nodes can be correlated. By utilizing the spatial correlation information of the field, distributed algorithms are proposed for event region detection.

Biography:Dr. Qi Cheng received the B.E. degree in electrical engineering from Shanghai Jiao Tong University, Shanghai, China in July 1999. From 1999 to 2000, she worked as a System Engineer in Guoxin Lucent Technologies Network Technologies Co. Ltd., Shanghai, China. She received the M.S. and Ph.D. degrees in Electrical Engineering from Syracuse University, Syracuse, NY, in 2003 and 2006, respectively. Dr. Cheng joined Oklahoma State University, Stillwater, OK USA in 2006 and currently is an associate professor with the School of Electrical and Computer Engineering. Dr. Cheng has done extensive research in the areas of distributed detection and estimation, distributed change/fault/anomaly detection, statistical learning theory, communications and information theory and their applications to distributed sensor networks. Dr. Cheng has authored and coauthored more than 50 papers in prestigious journals and proceedings. Dr. Cheng is a Senior Member of IEEE and has served as Associate Editor for the IEEE Communications Letters. The work presented is supported by NSF under Grant 0932297.