Cell degradation detection based on an inter-cell approach

Fault management is a crucial part of cellular network management systems. The status of the base stations is usually monitored by well-defined key performance indicators (KPIs). The approaches for cell degradation detection are based on either intra-cell or inter-cell analysis of the KPIs. In intra-cell analysis, KPI profiles are built based on their local history data whereas in inter-cell analysis, KPIs of one cell are compared with the corresponding KPIs of the other cells. In this work, we argue in favor of the inter-cell approach and apply a degradation detection method that is able to detect a sleeping cell that could be difficult to observe using traditional intra-cell methods. We demonstrate its use for detecting emulated degradations among performance data recorded from a live LTE network. The method can be integrated in current systems because it can operate using existing KPIs without any major modification to the network infrastructure

A report on SHARP (Spacecraft Health Automated Reasoning Prototype) and the Voyager Neptune encounter

The development and application of the Spacecraft Health Automated Reasoning Prototype (SHARP) for the operations of the telecommunications systems and link analysis functions in Voyager mission operations are presented. An overview is provided of the design and functional description of the SHARP system as it was applied to Voyager. Some of the current problems and motivations for automation in real-time mission operations are discussed, as are the specific solutions that SHARP provides. The application of SHARP to Voyager telecommunications had the goal of being a proof-of-capability demonstration of artificial intelligence as applied to the problem of real-time monitoring functions in planetary mission operations. AS part of achieving this central goal, the SHARP application effort was also required to address the issue of the design of an appropriate software system architecture for a ground-based, highly automated spacecraft monitoring system for mission operations, including methods for: (1) embedding a knowledge-based expert system for fault detection, isolation, and recovery within this architecture; (2) acquiring, managing, and fusing the multiple sources of information used by operations personnel; and (3) providing information-rich displays to human operators who need to exercise the capabilities of the automated system. In this regard, SHARP has provided an excellent example of how advanced artificial intelligence techniques can be smoothly integrated with a variety of conventionally programmed software modules, as well as guidance and solutions for many questions about automation in mission operations

An integrated approach to system design, reliability, and diagnosis

The requirement for ultradependability of computer systems in future avionics and space applications necessitates a top-down, integrated systems engineering approach for design, implementation, testing, and operation. The functional analyses of hardware and software systems must be combined by models that are flexible enough to represent their interactions and behavior. The information contained in these models must be accessible throughout all phases of the system life cycle in order to maintain consistency and accuracy in design and operational decisions. One approach being taken by researchers at Ames Research Center is the creation of an object-oriented environment that integrates information about system components required in the reliability evaluation with behavioral information useful for diagnostic algorithms. Procedures have been developed at Ames that perform reliability evaluations during design and failure diagnoses during system operation. These procedures utilize information from a central source, structured as object-oriented fault trees. Fault trees were selected because they are a flexible model widely used in aerospace applications and because they give a concise, structured representation of system behavior. The utility of this integrated environment for aerospace applications in light of our experiences during its development and use is described. The techniques for reliability evaluation and failure diagnosis are discussed, and current extensions of the environment and areas requiring further development are summarized

Making intelligent systems team players: Case studies and design issues. Volume 1: Human-computer interaction design

Initial results are reported from a multi-year, interdisciplinary effort to provide guidance and assistance for designers of intelligent systems and their user interfaces. The objective is to achieve more effective human-computer interaction (HCI) for systems with real time fault management capabilities. Intelligent fault management systems within the NASA were evaluated for insight into the design of systems with complex HCI. Preliminary results include: (1) a description of real time fault management in aerospace domains; (2) recommendations and examples for improving intelligent systems design and user interface design; (3) identification of issues requiring further research; and (4) recommendations for a development methodology integrating HCI design into intelligent system design

Space station advanced automation

In the development of a safe, productive and maintainable space station, Automation and Robotics (A and R) has been identified as an enabling technology which will allow efficient operation at a reasonable cost. The Space Station Freedom's (SSF) systems are very complex, and interdependent. The usage of Advanced Automation (AA) will help restructure, and integrate system status so that station and ground personnel can operate more efficiently. To use AA technology for the augmentation of system management functions requires a development model which consists of well defined phases of: evaluation, development, integration, and maintenance. The evaluation phase will consider system management functions against traditional solutions, implementation techniques and requirements; the end result of this phase should be a well developed concept along with a feasibility analysis. In the development phase the AA system will be developed in accordance with a traditional Life Cycle Model (LCM) modified for Knowledge Based System (KBS) applications. A way by which both knowledge bases and reasoning techniques can be reused to control costs is explained. During the integration phase the KBS software must be integrated with conventional software, and verified and validated. The Verification and Validation (V and V) techniques applicable to these KBS are based on the ideas of consistency, minimal competency, and graph theory. The maintenance phase will be aided by having well designed and documented KBS software

Making intelligent systems team players: Overview for designers

This report is a guide and companion to the NASA Technical Memorandum 104738, 'Making Intelligent Systems Team Players,' Volumes 1 and 2. The first two volumes of this Technical Memorandum provide comprehensive guidance to designers of intelligent systems for real-time fault management of space systems, with the objective of achieving more effective human interaction. This report provides an analysis of the material discussed in the Technical Memorandum. It clarifies what it means for an intelligent system to be a team player, and how such systems are designed. It identifies significant intelligent system design problems and their impacts on reliability and usability. Where common design practice is not effective in solving these problems, we make recommendations for these situations. In this report, we summarize the main points in the Technical Memorandum and identify where to look for further information

Artificial intelligence for multi-mission planetary operations

A brief introduction is given to an automated system called the Spacecraft Health Automated Reasoning Prototype (SHARP). SHARP is designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real-time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. Telecommunications link analysis of the Voyager II spacecraft is the initial focus for evaluation of the prototype in a real-time operations setting during the Voyager spacecraft encounter with Neptune in August, 1989. The preliminary results of the SHARP project and plans for future application of the technology are discussed

Automated post-fault diagnosis of power system disturbances

In order to automate the analysis of SCADA and digital fault recorder (DFR) data for a transmission network operator in the UK, the authors have developed an industrial strength multi-agent system entitled protection engineering diagnostic agents (PEDA). The PEDA system integrates a number of legacy intelligent systems for analyzing power system data as autonomous intelligent agents. The integration achieved through multi-agent systems technology enhances the diagnostic support offered to engineers by focusing the analysis on the most pertinent DFR data based on the results of the analysis of SCADA. Since November 2004 the PEDA system has been operating online at a UK utility. In this paper the authors focus on the underlying intelligent system techniques, i.e. rule-based expert systems, model-based reasoning and state-of-the-art multi-agent system technology, that PEDA employs and the lessons learnt through its deployment and online use