Design and development of prognostic and health management system for fly-by-wire primary flight control

Electro-Hydraulic Servo Actuators (EHSA) is the principal technology used for primary flight control in new aircrafts and legacy platforms. The development of Prognostic and Health Management technologies and their application to EHSA systems is of great interest in both the aerospace industry and the air fleet operators. This Ph.D. thesis is the results of research activity focused on the development of a PHM system for servovalve of fly-by-wire primary flight EHSA. One of the key features of the research is the implementation of a PHM system without the addition of new sensors, taking advantage of sensing and information already available. This choice allows extending the PHM capability to the EHSAs of legacy platforms and not only to new aircrafts. The enabling technologies borrow from the area of Bayesian estimation theory and specifically particle filtering and the information acquired from EHSA during pre-flight check is processed by appropriate algorithms in order to obtain relevant features, detect the degradation and estimate the Remaining Useful Life (RUL). The results are evaluated through appropriate metrics in order to assess the performance and effectiveness of the implemented PHM system. The major objective of this contribution is to develop an innovative fault diagnosis and failure prognosis framework for critical aircraft components that integrates effectively mathematically rigorous and validated signal processing, feature extraction, diagnostic and prognostic algorithms with novel uncertainty representation and management tools in a platform that is computationally efficient and ready to be transitioned on-board an aircraft

Health Management System for the Hydraulic Servoactuators of Fly-by-Wire Primary Flight Control Systems

Aircraft maintenance is one of the most important cost items faced by the operators of air fleets and is a major contributor to the aircraft life cycle cost. An aircraft fly-by-wire flight control system has a total of primary flight control actuators ranging from 10 to 20 depending on the aircraft type, with a failure rate of 1/1000 flight-hours; therefore, a health monitoring system for primary flight control actuators, able to recognize an actuator degradation in its early stage could greatly contribute to optimize the maintenance operations, reduce the airplane downtime and prevent missions interruptions. This note presents the initial part of an ongoing research project aimed at developing a prognostic and health management system for fly-by-wire primary flight control actuators. A key feature of the project is to develop a PHM system for these actuators suitable for the flight control actuators of legacy airplanes, which are poised to operate for still a long time, and not only for those of new aircraft. The primary flight control actuators of fly-by-wire flight control systems of existing aircraft are electrohydraulic servoactuators with a typical configuration and complement of transducers, and there is no practical possibility of introducing additional sensors. For this reason, the research activity was directed towards the study of algorithms able to identify faults only by using the already available information of the servoactuators state variables. The implemented algorithms are a combination of mathematical and neural network based ones, and the identification of degradations was performed by the analysis of the response of the servoactuators to a sequence of selected stimuli provided in preflight or postflight. The servovalve current and the feedback position are processed by dedicated algorithms in order to obtain significant indicators of the servocatuator health condition. The values of the indicators obtained during the sequence of stimuli are analyzed in combination with those obtained in the past. This is performed by the neural network part of the algorithm which allows a reliable identification of presence and of type of a degradation. The results obtained from the initial part of the research activity are interesting and encouraging. Individual degradations of the servoactuator parameters have so far been addressed and the algorithms for identifying them have been developed. All that makes up the foundations of the future research activity which will be focused on analyzing the effects of simultaneous multiple degradations and to the estimation of the remaining useful lif

A new Machine Learning-based method for identification of time-correlated events at tagged photon facilities

We present a new Machine Learning-based multivariate analysis method for the selection of time-correlated hits in the tagging system and devices used to detect particles in the final state at the bremsstrahlung-based tagged photon facilities. This method can be applied instead of the widely used sampling and subtraction of the time-uncorrelated background, in particular at experiments aiming for high precision, where the subtraction of the time-uncorrelated background leads to increased uncertainties. Moreover, the identification of events with Machine Learning algorithms allows to preserve the information about correlations of kinematic variables in the final state, which can be advantageous for further phenomenological analyses of the experimental results.Comment: 11 pages, 6 figure

Health Management System for the Hydraulic Servoactuators of Fly-by-Wire Primary Flight Control Systems

Aircraft maintenance is one of the most important cost items faced by the operators of air fleets and is a major contributor to the aircraft life cycle cost. An aircraft fly-by-wire flight control system has a total of primary flight control actuators ranging from 10 to 20 depending on the aircraft type, with a failure rate of 1/1000 flight-hours; therefore, a health monitoring system for primary flight control actuators, able to recognize an actuator degradation in its early stage could greatly contribute to optimize the maintenance operations, reduce the airplane downtime and prevent missions interruptions. This note presents the initial part of an ongoing research project aimed at developing a prognostic and health management system for fly-by-wire primary flight control actuators. A key feature of the project is to develop a PHM system for these actuators suitable for the flight control actuators of legacy airplanes, which are poised to operate for still a long time, and not only for those of new aircraft. The primary flight control actuators of fly-by-wire flight control systems of existing aircraft are electrohydraulic servoactuators with a typical configuration and complement of transducers, and there is no practical possibility of introducing additional sensors. For this reason, the research activity was directed towards the study of algorithms able to identify faults only by using the already available information of the servoactuators state variables. The implemented algorithms are a combination of mathematical and neural network based ones, and the identification of degradations was performed by the analysis of the response of the servoactuators to a sequence of selected stimuli provided in preflight or postflight. The servovalve current and the feedback position are processed by dedicated algorithms in order to obtain significant indicators of the servocatuator health condition. The values of the indicators obtained during the sequence of stimuli are analyzed in combination with those obtained in the past. This is performed by the neural network part of the algorithm which allows a reliable identification of presence and of type of a degradation. The results obtained from the initial part of the research activity are interesting and encouraging. Individual degradations of the servoactuator parameters have so far been addressed and the algorithms for identifying them have been developed. All that makes up the foundations of the future research activity which will be focused on analyzing the effects of simultaneous multiple degradations and to the estimation of the remaining useful life

A Robust Adaptive Hydraulic Power Generation System for Jet Engines

The paper presents an innovative hydraulic power generation system able to enhance performance, reliability and survivability of hydraulic systems used in military jet engines, as well as to allow a valuable power saving. This is obtained by a hydraulic power generation system architecture that uses variable pressure, smart control, emergency power source and suitable health management procedures. A key issue is to obtain all these functions while reducing to a minimum the number of additional components with respect to the conventional hydraulic power generation systems. The paper firstly presents the state-of-art of these systems and their critical issues, outlines the alternative solutions, and then describes architecture, characteristics and performance of the hydraulic power generation system that was eventually defined as a result of a research activity aimed at moving beyond the present state-of-art in this fiel

A Robust Adaptive Hydraulic Power Generation System for Jet Engines

The paper presents an innovative hydraulic power generation system able to enhance performance, reliability and survivability of hydraulic systems used in military jet engines, as well as to allow a valuable power saving. This is obtained by a hydraulic power generation system architecture that uses variable pressure, smart control, emergency power source and suitable health management procedures. A key issue is to obtain all these functions while reducing to a minimum the number of additional components with respect to the conventional hydraulic power generation systems. The paper firstly presents the state-of-art of these systems and their critical issues, outlines the alternative solutions, and then describes architecture, characteristics and performance of the hydraulic power generation system that was eventually defined as a result of a research activity aimed at moving beyond the present state-of-art in this fiel

A scalable data taking system at a test beam for LHC

We propose the installation of a data taking system at a test beam for the simultaneous test of LHC detectors, trigger and readout electronics, together with the development of the supporting architecture in a multiprocessor environment. A strong emphasis is put on a highly modular design, such that new hardware and software developments can be conveniently introduced for training and evaluation. One of the main thrusts of the project will be the modelling and system integration of different readout architectures, which are meant to provide a valuable training ground for new techniques. To address these aspects in a realistic manner, we propose to collaborate with two detector R+D projects

First Concurrent Extraction of the Leading-Order Scalar and Spin Proton Polarizabilities

We performed the first simultaneous extraction of the six leading-order proton polarizabilities. We reached this milestone thanks to both new high-quality experimental data and an innovative bootstrap-based fitting method. These new results provide a self-consistent and fundamental benchmark for all future theoretical and experimental polarizability estimates

Development of a PbWO4 Detector for Single-Shot Positron Annihilation Lifetime Spectroscopy at the GBAR Experiment

We have developed a PbWO4 (PWO) detector with a large dynamic range to measure the intensity of a positron beam and the absolute density of the ortho-positronium (o-Ps) cloud it creates. A simulation study shows that a setup based on such detectors may be used to determine the angular distribution of the emission and reflection of o-Ps to reduce part of the uncertainties of the measurement. These will allow to improve the precision in the measurement of the cross-section for the (anti)hydrogen formation by (anti)proton-positronium charge exchange and to optimize the yield of antihydrogen ion which is an essential parameter in the GBAR experiment