Prognostic Reasoner based adaptive power management system for a more electric aircraft

This research work presents a novel approach that addresses the concept of an adaptive power management system design and development framed in the Prognostics and Health Monitoring(PHM) perspective of an Electrical power Generation and distribution system(EPGS).PHM algorithms were developed to detect the health status of EPGS components which can accurately predict the failures and also able to calculate the Remaining Useful Life(RUL), and in many cases reconfigure for the identified system and subsystem faults. By introducing these approach on Electrical power Management system controller, we are gaining a few minutes lead time to failures with an accurate prediction horizon on critical systems and subsystems components that may introduce catastrophic secondary damages including loss of aircraft. The warning time on critical components and related system reconfiguration must permits safe return to landing as the minimum criteria and would enhance safety. A distributed architecture has been developed for the dynamic power management for electrical distribution system by which all the electrically supplied loads can be effectively controlled.A hybrid mathematical model based on the Direct-Quadrature (d-q) axis transformation of the generator have been formulated for studying various structural and parametric faults. The different failure modes were generated by injecting faults into the electrical power system using a fault injection mechanism. The data captured during these studies have been recorded to form a “Failure Database” for electrical system. A hardware in loop experimental study were carried out to validate the power management algorithm with FPGA-DSP controller. In order to meet the reliability requirements a Tri-redundant electrical power management system based on DSP and FPGA has been develope

Contextual normalization applied to aircraft gas turbine engine diagnosis

Diagnosing faults in aircraft gas turbine engines is a complex problem. It involves several tasks, including rapid and accurate interpretation of patterns in engine sensor data. We have investigated contextual normalization for the development of a software tool to help engine repair technicians with interpretation of sensor data. Contextual normalization is a new strategy for employing machine learning. It handles variation in data that is due to contextual factors, rather than the health of the engine. It does this by normalizing the data in a context-sensitive manner. This learning strategy was developed and tested using 242 observations of an aircraft gas turbine engine in a test cell, where each observation consists of roughly 12,000 numbers, gathered over a 12 second interval. There were eight classes of observations: seven deliberately implanted classes of faults and a healthy class. We compared two approaches to implementing our learning strategy: linear regression and instance-based learning. We have three main results. (1) For the given problem, instance-based learning works better than linear regression. (2) For this problem, contextual normalization works better than other common forms of normalization. (3) The algorithms described here can be the basis for a useful software tool for assisting technicians with the interpretation of sensor data

Energy efficient transport technology: Program summary and bibliography

The Energy Efficient Transport (EET) Program began in 1976 as an element of the NASA Aircraft Energy Efficiency (ACEE) Program. The EET Program and the results of various applications of advanced aerodynamics and active controls technology (ACT) as applicable to future subsonic transport aircraft are discussed. Advanced aerodynamics research areas included high aspect ratio supercritical wings, winglets, advanced high lift devices, natural laminar flow airfoils, hybrid laminar flow control, nacelle aerodynamic and inertial loads, propulsion/airframe integration (e.g., long duct nacelles) and wing and empennage surface coatings. In depth analytical/trade studies, numerous wind tunnel tests, and several flight tests were conducted. Improved computational methodology was also developed. The active control functions considered were maneuver load control, gust load alleviation, flutter mode control, angle of attack limiting, and pitch augmented stability. Current and advanced active control laws were synthesized and alternative control system architectures were developed and analyzed. Integrated application and fly by wire implementation of the active control functions were design requirements in one major subprogram. Additional EET research included interdisciplinary technology applications, integrated energy management, handling qualities investigations, reliability calculations, and economic evaluations related to fuel savings and cost of ownership of the selected improvements

Diagnostics of an Aircraft Engine Pumping Unit Using a Hybrid Approach based-on Surrogate Modeling

This document introduces a hybrid approach for fault detection and identification of an aircraft engine pumping unit. It is based on the complementarity between a model-based approach accounting for uncertainties aimed at quantifying the degradation modes signatures and a data-driven approach aimed at recalibrating the healthy syndrome from measures. Because of the computational time costs of uncertainties propagation into the physics based model, a surrogate modeling technic called Kriging associated to Latin hypercube sampling is utilized. The hybrid approach is tested on a pumping unit of an aircraft engine and shows good results for computing the degradation modes signatures and performing their detection and identification

Report on research and technology-FY 1981

More than 65 technical reports, papers, and articles published by personnel and contractors at the Dryden Flight Research Center are listed. Activities performed for the Offices of Aeronautics and Space Technology, Space and Terrestrial Applications, Space Transportation Systems, and Space Tracking and Data Systems are summarized. Preliminary stability and control derivatives were determined for the shuttle orbiter at hypersonic speeds from the data obtained at reentry. The shuttle tile tests, spin research vehicle nose shapes flight investigations, envelope expansion flights for the Ames tilt rotor research aircraft, and the AD-1 oblique wing programs were completed as well as the KC-135 winglet program

TERA- A Tool for Aero-engine Modelling and Management

One of the distinguishing features of the civil aero-engine market is its high competitiveness. The costs and risks associated with new projects are such that the difference between two apparently equally attractive options could result in success from one and a threat to the survival of the company from the other. To conceive and assess engines with minimum global warming impact and lowest cost of ownership in a variety of emission legislation scenarios, emissions taxation policies, fiscal and Air Traffic Management environments, a Techno-economic and Environmental Risk Assessment (TERA) model is needed. TERA incorporates multi-disciplinary modules for modelling gas turbine and aircraft performance, estimation of engine weight, noise and emissions as well as environment impact and operating economics. The TERA software is integrated with a commercial optimiser and provides a means for cycle studies. It is to be expected that new legislative and fiscal constraints on air travel will demand an extension to the customary range of asset management parameters. In such a business environment there is potential for TERA to develop into a useful tool for aircraft and engine asset management. This paper presents a description of this tool as well as gives some results from scenario studies

Hybrid automated reliability predictor integrated work station (HiREL)

The Hybrid Automated Reliability Predictor (HARP) integrated reliability (HiREL) workstation tool system marks another step toward the goal of producing a totally integrated computer aided design (CAD) workstation design capability. Since a reliability engineer must generally graphically represent a reliability model before he can solve it, the use of a graphical input description language increases productivity and decreases the incidence of error. The captured image displayed on a cathode ray tube (CRT) screen serves as a documented copy of the model and provides the data for automatic input to the HARP reliability model solver. The introduction of dependency gates to a fault tree notation allows the modeling of very large fault tolerant system models using a concise and visually recognizable and familiar graphical language. In addition to aiding in the validation of the reliability model, the concise graphical representation presents company management, regulatory agencies, and company customers a means of expressing a complex model that is readily understandable. The graphical postprocessor computer program HARPO (HARP Output) makes it possible for reliability engineers to quickly analyze huge amounts of reliability/availability data to observe trends due to exploratory design changes