Written for researchers, scientists, and reliability engineers, these Research Papers describe the software engineering and sophisticated math and algorithms that go into building a world-class Service Intelligence solution.
Ideal for those needing a deep understanding of the challenges and issues confronting reliability and serviceability engineers working with a range of complex systems and technologies.
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A Model-based Health Monitoring and Diagnostic System for the UH-60 Helicopter Model-based reasoning techniques hold much promise in providing comprehensive monitoring and diagnostics capabilities for complex systems.
An Integrated Diagnostics Virtual Test Bench for Life Cycle Support The Virtual Test Bench architecture used by TEAMS addresses design for testability, safety, and risk reduction.
Fault Detection and Isolation in the Non-Toxic Orbital Maneuvering System This paper considers the problem of test design for real-time fault detection and diagnosis in the space shuttle’s non-toxic orbital maneuvering system and reaction control system (NT-OMS/RCS).
Model-based Prognostic Techniques Conventional maintenance strategies, such as corrective and preventive maintenance, are not adequate to fulfill the needs of expensive and high availability industrial systems. A new strategy is needed.
Multi-Signal Flow Graphs: A Novel Approach for System Testability Analysis and Fault Diagnosis This paper presents a comprehensive methodology for a formal cause-effect dependency model using multi-signal directed graphs that correspond to hierarchical system schematics.
Multisignal Modeling for Diagnosis, FMECA, and Reliability Multisignal modeling methodology is a simple and efficient knowledge representation scheme that captures the basic attributes of a system (structure, specifications, etc.) that are obtainable from design data and product specifications.
Remote Diagnosis of the International Space Station utilizing Telemetry Data Modern complex systems need to be monitored around the clock. Based on telemetry data from such systems, the Remote Diagnosis Server provides online monitoring of sensor-rich, network capable legacy systems such as jet engines, building heating-ventilation-air-conditioning systems, and automobiles.
Remote Diagnosis Server Many legacy systems were originally not designed for real-time onboard diagnosis. Such systems can be equipped to transmit sensor data to a remote-processing center for continuous health monitoring.
Remote Diagnosis Server Architecture The Remote Diagnosis Server is built on a three-tier architecture with a “Broker” application in the middle layer and multiple TEAMS-RT and TEAMATE-based reasoners at the backend.
