scholarly journals Design of a PHM system for electro-mechanical flight controls: a roadmap from preliminary analyses to iron-bird validation

2019 ◽  
Vol 304 ◽  
pp. 04018 ◽  
Author(s):  
Andrea De Martin ◽  
Giovanni Jacazio ◽  
Massimo Sorli
Keyword(s):  
Fault Diagnosis ◽  
Control Systems ◽  
Flight Control ◽  
Management System ◽  
Health Management ◽  
Prognostics And Health Management ◽  
Case Scenario ◽  
Flight Controls ◽  
Definition Of ◽  
New Algorithms

Literature on PHM is focused on research dedicated to the definition of new algorithms to achieve better failures prognosis or earlier and more accurate fault diagnosis, but lacks of examples on the design of novel PHM frameworks and the practical issues related with their implementation. This paper describes a roadmap for the design of a novel Prognostics and Health Management system while making reference to a real-case scenario applied to electro-mechanical actuators for flight control systems.

scholarly journals A Case Study on the Detection and Prognosis of Internal Leakages in Electro-Hydraulic Flight Control Actuators

Actuators ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 215
Author(s):  
Antonio Carlo Bertolino ◽  
Andrea De Martin ◽  
Giovanni Jacazio ◽  
Massimo Sorli
Keyword(s):  
Flight Control ◽  
Particle Filtering ◽  
Health Management ◽  
State Of The Art ◽  
Commercial Aircraft ◽  
Flight Data ◽  
Prognostic System ◽  
Hydraulic Servo ◽  
Definition Of

Electro-hydraulic servo-actuators (EHSAs) are currently considered the state-of-the art solution for the control of the primary flight control systems of civil and military aircraft. Combining the expected service life of a commercial aircraft with the fact that electro-hydraulic technology is employed in the vast majority of currently in-service aircraft and is planned to be used on future platforms as well, the development of an effective Prognostic and Health Management (PHM) system could provide significant advantages to fleet operators and aircraft maintenance, such as the reduction of unplanned flight disruptions and increased availability of the aircraft. The occurrence of excessive internal leakage within the EHSAs is one of the most common causes of return from the field of flight control actuators, making this failure mode a priority in the definition of any dedicated PHM routine. This paper presents a case study on the design of a prognostic system for this degradation mode, in the context of a wider effort toward the definition of a prognostic framework suitable to work on in-flight data. The study is performed by means of a high-fidelity simulation model supported by experimental activities. Results of both the simulation and the experimental work are used to select a suitable feature, then implemented within the prognostic framework based on particle filtering. The algorithm is at first theoretically discussed, and then tested against several degradation patterns. Performances are evaluated through state-of-the-art metrics, showing promising results and providing the basis towards future applications on real in-flight data.

A Simulation Survey on the Effects of Progressing Faults Within the SCAS of a Flight Control Actuator for Helicopters

2021 ◽  
Author(s):  
Andrea De Martin ◽  
Giovanni Jacazio ◽  
Massimo Sorli ◽  
Giuseppe Vitrani
Keyword(s):  
Flight Control ◽  
Health Management ◽  
Risk Mitigation ◽  
Selection Process ◽  
Stability Control ◽  
Features Selection ◽  
Vertical Walls ◽  
Low Altitude ◽  
Definition Of ◽  
Rotary Wing

Abstract Stability Control Augmentation Systems (SCAS) are widely adopted to enhance the flight stability of rotary-wing aircraft operating in difficult aerodynamic conditions, such as low altitude missions, stationary flight nearby vertical walls or in presence of heavy gusts. Such systems are based upon small electro-hydraulic servosystems controlled in position through a dedicated servovalve. The SCAS operates with limited authority over the main control linkage translating the pilot input in the movement of the main flight control actuator. Being critical for the operability of the helicopter, the definition of a Prognostics and Health Management (PHM) framework for the SCAS systems would provide significant advantages, such as better risk mitigation, improved availability, and a reduction in the occurrences of unpredicted failures which still represent one of the most known downsides of helicopters. This paper provides the results of a preliminary analysis on the effects of the inception and progression of several degradation types within a simulated SCAS system. Signals usually available within such devices are hence combined with measurements provided by additional sensors to check the feasibility of a PHM system with and without dedicated sensors. The resulting features selection process shows that although the dedicated measurements are required to design a complete PHM system, it appears nonetheless possible to obtain valuable information on the health status of the SCAS system without resorting to additional sensors.

ANALYSIS OF SPACECRAFT TELEMETRY INFORMATION USING THE KNOWLEDGE BASE, REPLENISHED DURING THEIR OPERATION

2021 ◽  
pp. 12-17
Author(s):  
S. V. Soloviev
Keyword(s):  
Time Series ◽  
Flight Control ◽  
Control Process ◽  
State Control ◽  
Mathematical Apparatus ◽  
Analysis Algorithm ◽  
Intelligent Analysis ◽  
Flight Controls ◽  
Basic Concepts ◽  
Definition Of

The method for intellectualizing the analysis of telemetric information from spacecraft arriving at ground-based flight controls is discusses. The features of state control during the spacecraft operation are formulated. The basic concepts, terms and basic properties of time series are presented, the definition of the physical meaning of the characteristic quantities for the spacecraft flight control process is given. The use of the mathematical apparatus for the analysis of time radars is substantiated in solving problems of telemetry support in the process of controlling the flight of spacecraft. A mathematical apparatus for analyzing time series is proposed to identify the actual trend. An approach to solving the problem of predicting the state of a spacecraft based on a comparative version is presented. Requirements for the intelligent analysis algorithm are presented and an integrated algorithm is proposed, a method based on time series.

scholarly journals A health management system for large vertical mill

2020 ◽  
Vol 16 (3) ◽  
pp. 155014772091211
Author(s):  
Sugai Han ◽  
Ansheng Li ◽  
Hongchao Wang ◽  
Xiaoyun Gong ◽  
Liangwen Wang ◽  
...  
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Optimization Algorithm ◽  
Management System ◽  
Health Management ◽  
Back Propagation ◽  
Trend Prediction ◽  
Backtracking Search ◽  
Search Optimization ◽  
Backtracking Search Optimization Algorithm

The large vertical mill has complicated structure and tens of thousands of parts, which is a critical grinding equipment for slag and cinder. As large vertical mill always works in severe conditions, the on-line monitoring, timely fault diagnosis, and trend prediction are very important guarantees for the safe service and saving maintaining costs. To address this issue, the health management system for large vertical mill is developed. More specifically, in order to manage reservoirs of state-related running data, the intrinsic physic data, and diagnosis knowledge base, an entity-relationship-model-based database is first constructed. Based on the fault diagnosis reasoning of experts, the fault tree is developed and the fault diagnosis rules are derived. Especially, a hybrid condition prognosis method based on backtracking search optimization algorithm and neural network is developed, and in comparison with traditional back propagation neural network and ant colony neural network, the developed backtracking search optimization algorithm and neural network gets superior hybrid prediction performance in prediction accuracy and training efficiency. Finally, the health management system, including the functions of condition monitoring, fault diagnosis, and trend prediction for large vertical mill is implemented using Microsoft Visual Studio C # and Microsoft SQL Server.

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