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Foster-Miller is experienced with research & development of diagnostics and prognostics systems that collect data from various types of sensors and use special analytical techniques to analyze the data in real-time to diagnose performance problems, discern impending faults, and schedule maintenance procedures. The research & development of diagnostics and prognostics systems by our engineers can be grouped into two categories: Nonlinear Dynamics/Chaos, which is a strategy based on discerning system dynamics and fault indicators from empirical data, and Model-Based, which uses a simplified model of how the system behaves to determine whether or not faults have occurred and decide what to do about them. Foster-Miller's unique "dynamical instruments" approach can be applied as a diagnostic method. Through this approach, collections of measured data (signature quantities) are identified that highly correlate to specific performance problems. Since these signature quantities are discovered through the inspection of empirical data, a complicated, first-principles model of the monitored system is not necessary. We have applied this approach to a wide range of systems, from multiphase flow measurement to the diagnosis of faults in flight actuators of jet fighter aircraft. Foster-Miller is experienced in making health-monitoring systems that simultaneously measure numerous aspects of machine performance and process the information in an intelligent way to reveal any machine health problems. These are typically highly distributed systems with hundreds of sensors that communicate back to a centralized processor via a communications network such as the Ethernet. In the most “intelligent” implementations, the central processor uses a simplified “world model” to reason about the implications of faults and to determine fault mitigation strategies. We have demonstrated complete monitoring and diagnostic systems for military, commercial, and utility customers.
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