Multiple Fault Isolation in Redundant Systems

Fault diagnosis in large-scale systems that are products of modem technology present formidable challenges to manufacturers and users. This is due to large number of failure sources in such systems and the need to quickly isolate and rectify failures with minimal down time. In addition, for fault-tolerant systems and systems with infrequent opportunity for maintenance (e.g., Hubble telescope, space station), the assumption of at most a single fault in the system is unrealistic. In this project, we have developed novel block and sequential diagnostic strategies to isolate multiple faults in the shortest possible time without making the unrealistic single fault assumption

Multiple Fault Isolation in Redundant Systems

Fault diagnosis in large-scale systems that are products of modern technology present formidable challenges to manufacturers and users. This is due to large number of failure sources in such systems and the need to quickly isolate and rectify failures with minimal down time. In addition, for fault-tolerant systems and systems with infrequent opportunity for maintenance (e.g., Hubble telescope, space station), the assumption of at most a single fault in the system is unrealistic. In this project, we have developed novel block and sequential diagnostic strategies to isolate multiple faults in the shortest possible time without making the unrealistic single fault assumption

Model-Based Organization Analysis and Design for an ESG Organization

11th Command and Control Research and Technology Symposium (CCRTS), June 20-22, 2006, San Diego, C

Congruence of Human Organizations and Missions: Theory versus Data

1999 Command and Control Research and Technology Symposium (CCRTS), June 29 - July 1, 1999, U.S. Naval War College, Rhode IslandIn this paper, we present a methodology for quantifying the degree of fit between a mission and an organization based on the closeness between the task structure (i.e., resource requirements and task interdependence) and the DM-asset allocation across the organization (i.e., amount and distribution of resource capabilities among DMs, and organizational processes). This closeness is based on three main characteristics of organizational performance: workload balance, communication requirements, and DM-DM dependence. These characteristics are affected, in turn, by the interactions and interdependencies of the organizational processes and the demands of the mission scenario. Invariably, coordination is essential to achieve good performance because the information required for decisionmaking is often distributed. However, excessive DM-DM communication and coordination are harmful to performance, since they increase the processing workload/overhead that delays task execution. Performance improvements can be obtained by changing the structure and processes of an organization to decrease the requisite coordination, while balancing the levels of workload across the organization and reducing inter DM dependence.This work was supported by the Office of Naval Research under contract # N00014-00-1-0101

A Review of Diagnostic Techniques for ISHM Applications

System diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern