A survey of design methods for failure detection in dynamic systems

A number of methods for the detection of abrupt changes (such as failures) in stochastic dynamical systems were surveyed. The class of linear systems were emphasized, but the basic concepts, if not the detailed analyses, carry over to other classes of systems. The methods surveyed range from the design of specific failure-sensitive filters, to the use of statistical tests on filter innovations, to the development of jump process formulations. Tradeoffs in complexity versus performance are discussed

Technical approaches for measurement of human errors

Human error is a significant contributing factor in a very high proportion of civil transport, general aviation, and rotorcraft accidents. The technical details of a variety of proven approaches for the measurement of human errors in the context of the national airspace system are presented. Unobtrusive measurements suitable for cockpit operations and procedures in part of full mission simulation are emphasized. Procedure, system performance, and human operator centered measurements are discussed as they apply to the manual control, communication, supervisory, and monitoring tasks which are relevant to aviation operations

F-8C adaptive flight control extensions

An adaptive concept which combines gain-scheduled control laws with explicit maximum likelihood estimation (MLE) identification to provide the scheduling values is described. The MLE algorithm was improved by incorporating attitude data, estimating gust statistics for setting filter gains, and improving parameter tracking during changing flight conditions. A lateral MLE algorithm was designed to improve true air speed and angle of attack estimates during lateral maneuvers. Relationships between the pitch axis sensors inherent in the MLE design were examined and used for sensor failure detection. Design details and simulation performance are presented for each of the three areas investigated

Fault detection, identification and accommodation techniques for unmanned airborne vehicles

Unmanned Airborne Vehicles (UAV) are assuming prominent roles in both the commercial and military aerospace industries. The promise of reduced costs and reduced risk to human life is one of their major attractions, however these low-cost systems are yet to gain acceptance as a safe alternate to manned solutions. The absence of a thinking, observing, reacting and decision making pilot reduces the UAVs capability of managing adverse situations such as faults and failures. This paper presents a review of techniques that can be used to track the system health onboard a UAV. The review is based on a year long literature review aimed at identifying approaches suitable for combating the low reliability and high attrition rates of today’s UAV. This research primarily focuses on real-time, onboard implementations for generating accurate estimations of aircraft health for fault accommodation and mission management (change of mission objectives due to deterioration in aircraft health). The major task of such systems is the process of detection, identification and accommodation of faults and failures (FDIA). A number of approaches exist, of which model-based techniques show particular promise. Model-based approaches use analytical redundancy to generate residuals for the aircraft parameters that can be used to indicate the occurrence of a fault or failure. Actions such as switching between redundant components or modifying control laws can then be taken to accommodate the fault. The paper further describes recent work in evaluating neural-network approaches to sensor failure detection and identification (SFDI). The results of simulations with a variety of sensor failures, based on a Matlab non-linear aircraft model are presented and discussed. Suggestions for improvements are made based on the limitations of this neural network approach with the aim of including a broader range of failures, while still maintaining an accurate model in the presence of these failures

Probabilistic Monte-Carlo method for modelling and prediction of electronics component life

Power electronics are widely used in electric vehicles, railway locomotive and new generation aircrafts. Reliability of these components directly affect the reliability and performance of these vehicular platforms. In recent years, several research work about reliability, failure mode and aging analysis have been extensively carried out. There is a need for an efficient algorithm able to predict the life of power electronics component. In this paper, a probabilistic Monte-Carlo framework is developed and applied to predict remaining useful life of a component. Probability distributions are used to model the component’s degradation process. The modelling parameters are learned using Maximum Likelihood Estimation. The prognostic is carried out by the mean of simulation in this paper. Monte-Carlo simulation is used to propagate multiple possible degradation paths based on the current health state of the component. The remaining useful life and confident bounds are calculated by estimating mean, median and percentile descriptive statistics of the simulated degradation paths. Results from different probabilistic models are compared and their prognostic performances are evaluated

The historical development and basis of human factors guidelines for automated systems in aeronautical operations

In order to derive general design guidelines for automated systems a study was conducted on the utilization and acceptance of existing automated systems as currently employed in several commercial fields. Four principal study area were investigated by means of structured interviews, and in some cases questionnaires. The study areas were aviation, a both scheduled airline and general commercial aviation; process control and factory applications; office automation; and automation in the power industry. The results of over eighty structured interviews were analyzed and responses categoried as various human factors issues for use by both designers and users of automated equipment. These guidelines address such items as general physical features of automated equipment; personnel orientation, acceptance, and training; and both personnel and system reliability

Aeronautical engineering: A continuing bibliography with indexes, supplement 100

This bibliography lists 295 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System in August 1978

NASA/RAE collaboration on nonlinear control using the F-8C digital fly-by-wire aircraft

Design procedures are reviewed for variable integral control to optimize response (VICTOR) algorithms and results of preliminary flight tests are presented. The F-8C aircraft is operated in the remotely augmented vehicle (RAV) mode, with the control laws implemented as FORTRAN programs on a ground-based computer. Pilot commands and sensor information are telemetered to the ground, where the data are processed to form surface commands which are then telemetered back to the aircraft. The RAV mode represents a singlestring (simplex) system and is therefore vulnerable to a hardover since comparison monitoring is not possible. Hence, extensive error checking is conducted on both the ground and airborne computers to prevent the development of potentially hazardous situations. Experience with the RAV monitoring and validation procedures is described

Information Management to Mitigate Loss of Control Airline Accidents

Loss of control inflight continues to be the leading contributor to airline accidents worldwide and unreliable airspeed has been a contributing factor in many of these accidents. Airlines and the FAA developed training programs for pilot recognition of these airspeed events and many checklists have been designed to help pilots troubleshoot. In addition, new aircraft designs incorporate features to detect and respond in such situations. NASA has been using unreliable airspeed events while conducting research recommended by the Commercial Aviation Safety Team. Even after significant industry focus on unreliable airspeed, research and other evidence shows that highly skilled and trained pilots can still be confused by the condition and there is a lack of understanding of what the associated checklist(s) attempts to uncover. Common mode failures of analog sensors designed for measuring airspeed continue to confound both humans and automation when determining which indicators are correct. This paper describes failures that have occurred in the past and where/how pilots may still struggle in determining reliable airspeed when confronted with conflicting information. Two latest generation aircraft architectures will be discussed and contrasted. This information will be used to describe why more sensors used in classic control theory will not solve the problem. Technology concepts are suggested for utilizing existing synoptic pages and a new synoptic page called System Interactive Synoptic (SIS). SIS details the flow of flight critical data through the avionics system and how it is used by the automation. This new synoptic page as well as existing synoptics can be designed to be used in concert with a simplified electronic checklist (sECL) to significantly reduce the time to configure the flight deck avionics in the event of a system or sensor failure