Intelligent Sensor Fusion for Shipboard Auxiliary Systems Navy SBIR FY2011.2 Sol No.: Navy SBIR FY2011.2 Topic No.: N112-159 Topic Title: Intelligent Sensor Fusion for Shipboard Auxiliary Systems Proposal No.: N112-159-0651 Firm: Techno-Sciences, Inc. 11750 Beltsville Drive 3rd Floor Beltsville, Maryland 20705-4044 Contact: Murat Yasar Phone: (240) 790-0673 Web Site: www.technosci.com Abstract: Data analysis and sensor fusion is undeniably the most pertinent part of science and practical applications related to information management for damage detection and condition monitoring. Unfortunately, for a general solution to be tractable for coupled, distributed systems, such as shipboard auxiliary systems, sensor fusion requires innovative techniques and algorithms. The ultimate goal for the proposed sensor fusion is to address the problem of damage detection in the auxiliary systems, to improve situational awareness, and to formulate appropriate control actions. Our technique combines a statistical signal processing approach based on Hidden Markov Modeling with nonlinear estimation theory developed for complex distributed systems. Fusion of data from multiple sources will lead to managing the information regarding sensor features simultaneously. We aim to achieve a reliable and computationally inexpensive sensor fusion technology targeted for shipboard auxiliary systems. Benefits: Sensor fusion algorithms can be used to enable information management for distributed systems, while the extension of the algorithms are significant since the outcome of such analysis methods can be applicable to many areas from target detection and tracking to condition based maintenance, and threat identification. These techniques can be used for control and efficiency increase, and making intelligent trade-offs between performance and remaining life. Techno-Sciences, Inc. has a variety of commercial products ranging from aircraft electrical health management to engine accessory monitoring to structural health monitoring that can incorporate the developed algorithms. These techniques will also have impact on maintenance management systems that is used to schedule preventive maintenance for elevators and power systems. Return