Title

An Architecture For Monitoring And Anomaly Detection For Space Systems

Abstract

Complex aerospace engineering systems require innovative methods for performance monitoring and anomaly detection. The interface of a real-time data stream to a system for analysis, pattern recognition, and anomaly detection can require distributed system architectures and sophisticated custom programming. This paper presents a case study of a simplified interface between Programmable Logic Controller (PLC) real-time data output, signal processing, cloud computing, and tablet systems. The discussed approach consists of three parts: First, the connectivity of real-time data from PLCs to the signal processing algorithms, using standard communication technologies. Second, the interface of legacy routines, such as NASA's Inductive Monitoring System (IMS), with a hybrid signal processing system. Third, the connectivity and interaction of the signal processing system with a wireless and distributed tablet, (iPhone/iPad) in a hybrid system configuration using cloud computing. This proposed configuration allows for back-and-forth interactivity between tablet logic, standard signal processing systems, PLC logic, and remote aerospace system hardware. The application of tablet computing in the cloud can provide flexibility of operations in spacecraft systems. Astronauts can use tablets as a mobile device for monitoring and visualization of space hardware. The tablet can work as a display interface, while all computing and processing is done in the cloud. The preliminary study will involve a case of the propulsion system of a spacecraft. Copyright © 2013 SAE International.

Publication Date

1-1-2013

Publication Title

SAE International Journal of Aerospace

Volume

6

Issue

1

Number of Pages

81-86

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.4271/2013-01-2090

Socpus ID

84904809785 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84904809785

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