Flight deck engine advisor

The focus of this project is on alerting pilots to impending events in such a way as to provide the additional time required for the crew to make critical decisions concerning non-normal operations. The project addresses pilots' need for support in diagnosis and trend monitoring of faults as they affect decisions that must be made within the context of the current flight. Monitoring and diagnostic modules developed under the NASA Faultfinder program were restructured and enhanced using input data from an engine model and real engine fault data. Fault scenarios were prepared to support knowledge base development activities on the MONITAUR and DRAPhyS modules of Faultfinder. An analysis of the information requirements for fault management was included in each scenario. A conceptual framework was developed for systematic evaluation of the impact of context variables on pilot action alternatives as a function of event/fault combinations

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

AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments

This report considers the application of Articial Intelligence (AI) techniques to the problem of misuse detection and misuse localisation within telecommunications environments. A broad survey of techniques is provided, that covers inter alia rule based systems, model-based systems, case based reasoning, pattern matching, clustering and feature extraction, articial neural networks, genetic algorithms, arti cial immune systems, agent based systems, data mining and a variety of hybrid approaches. The report then considers the central issue of event correlation, that is at the heart of many misuse detection and localisation systems. The notion of being able to infer misuse by the correlation of individual temporally distributed events within a multiple data stream environment is explored, and a range of techniques, covering model based approaches, `programmed' AI and machine learning paradigms. It is found that, in general, correlation is best achieved via rule based approaches, but that these suffer from a number of drawbacks, such as the difculty of developing and maintaining an appropriate knowledge base, and the lack of ability to generalise from known misuses to new unseen misuses. Two distinct approaches are evident. One attempts to encode knowledge of known misuses, typically within rules, and use this to screen events. This approach cannot generally detect misuses for which it has not been programmed, i.e. it is prone to issuing false negatives. The other attempts to `learn' the features of event patterns that constitute normal behaviour, and, by observing patterns that do not match expected behaviour, detect when a misuse has occurred. This approach is prone to issuing false positives, i.e. inferring misuse from innocent patterns of behaviour that the system was not trained to recognise. Contemporary approaches are seen to favour hybridisation, often combining detection or localisation mechanisms for both abnormal and normal behaviour, the former to capture known cases of misuse, the latter to capture unknown cases. In some systems, these mechanisms even work together to update each other to increase detection rates and lower false positive rates. It is concluded that hybridisation offers the most promising future direction, but that a rule or state based component is likely to remain, being the most natural approach to the correlation of complex events. The challenge, then, is to mitigate the weaknesses of canonical programmed systems such that learning, generalisation and adaptation are more readily facilitated

Using formal methods to support testing

Formal methods and testing are two important approaches that assist in the development of high quality software. While traditionally these approaches have been seen as rivals, in recent years a new consensus has developed in which they are seen as complementary. This article reviews the state of the art regarding ways in which the presence of a formal specification can be used to assist testing

A design for an intelligent monitor and controller for space station electrical power using parallel distributed problem solving

The emphasis is on defining a set of communicating processes for intelligent spacecraft secondary power distribution and control. The computer hardware and software implementation platform for this work is that of the ADEPTS project at the Johnson Space Center (JSC). The electrical power system design which was used as the basis for this research is that of Space Station Freedom, although the functionality of the processes defined here generalize to any permanent manned space power control application. First, the Space Station Electrical Power Subsystem (EPS) hardware to be monitored is described, followed by a set of scenarios describing typical monitor and control activity. Then, the parallel distributed problem solving approach to knowledge engineering is introduced. There follows a two-step presentation of the intelligent software design for secondary power control. The first step decomposes the problem of monitoring and control into three primary functions. Each of the primary functions is described in detail. Suggestions for refinements and embelishments in design specifications are given

Time domain analysis of switching transient fields in high voltage substations

Switching operations of circuit breakers and disconnect switches generate transient currents propagating along the substation busbars. At the moment of switching, the busbars temporarily acts as antennae radiating transient electromagnetic fields within the substations. The radiated fields may interfere and disrupt normal operations of electronic equipment used within the substation for measurement, control and communication purposes. Hence there is the need to fully characterise the substation electromagnetic environment as early as the design stage of substation planning and operation to ensure safe operations of the electronic equipment. This paper deals with the computation of transient electromagnetic fields due to switching within a high voltage air-insulated substation (AIS) using the finite difference time domain (FDTD) metho

Diagnosis of Fault Modes Masked by Control Loops with an Application to Autonomous Hovercraft Systems

This paper introduces a methodology for the design, testing and assessment of incipient failure detection techniques for failing components/systems of an autonomous vehicle masked or hidden by feedback control loops. It is recognized that the optimum operation of critical assets (aircraft, autonomous systems, etc.) may be compromised by feedback control loops by masking severe fault modes while compensating for typical disturbances. Detrimental consequences of such occurrences include the inability to detect expeditiously and accurately incipient failures, loss of control and inefficient operation of assets in the form of fuel overconsumption and adverse environmental impact. We pursue a systems engineering process to design, construct and test an autonomous hovercraft instrumented appropriately for improved autonomy. Hidden fault modes are detected with performance guarantees by invoking a Bayesian estimation approach called particle filtering. Simulation and experimental studies are employed to demonstrate the efficacy of the proposed methods