The defense and industrial communities are faced with major challenges to monitor, process, and optimize the operation of complex systems/processes. Of particular interest to the Navy are critical shipboard auxiliary systems that support chilled water and electrical processes. The complexity of modern shipboard systems and the requirements for their reliable and safe operation suggest that optimum means must be deployed to make effective use of multiple sensors providing an enormous amount of raw data. Impact Technologies, in collaboration with the Georgia Institute of Technology and its industrial partners, is proposing to develop, test and evaluate an intelligent/hierarchical sensor data fusion architecture to improve the information derived from raw data at various levels of abstraction: the data, feature, sensor and knowledge levels. The data/sensor fusion approach is based on a hybrid analytical/intelligent methodology that exploits the concept of focus of attention 0x9D via active perception in order to optimize auxiliary system component classification accuracy while reducing substantially the computational burden. The proposed fusion scheme incorporates several levels of abstraction: fusion at the data level, the feature level, the sensor level and the knowledge level. The enabling technologies build upon the fundamental premise that fusion is an optimization problem and rigorous computational models, coupled with intelligent search algorithms (Genetic Programming, Particle Swarm Optimization, etc.) are employed to fuse sensor data, resolve conflicts and arrive at a verifiable solution to data fusion. Our targeted testbed is a typical shipboard auxiliary system supported by the water chiller/electrical processes. Our target application domain for the data/sensor fusion algorithms to be developed in this program is equipment damage assessment and process control.
Benefit: Navys maintenance personnel will initially benefit from the successful results of the proposed effort. The sensor data fusion architecture promises to enhance their capabilities to realize and implement the emerging Condition Based Maintenance and Prognostics and Health Management technologies so that they can improve the reliability, safety and maintainability of critical assets. Breakthrough technologies intended to optimize the data requirements for fault detection and identification can benefit multiple branches of the military services: aircraft operations and maintenance, weapons, ground vehicles, unmanned systems, among many others. When integrated into a monitoring environment and in conjunction with novel and verifiable fault diagnosis and failure prognosis algorithms, such software advances can reduce the risk of false ID, enhance the data reliability and utility while achieving maximum computational efficiency. The potential application domain beyond the military arena encompasses a diverse list such as industrial processes, transportation systems, aerospace, energy systems, bioengineering, business and finance, etc.
Keywords: Optimization, Optimization, Active Perception, Intelligent Algorithms, sensor fusion
