Guidelines for Integrating Typical Engine Health Management Functions Within Aircraft Systems

2016 ◽  
Author(s):  
Keyword(s):  
Health Management ◽  
Aircraft Systems ◽  
Management Functions

scholarly journals Implementation of Unconstrained Chair-Type Smart Health Management Monitoring System

2018 ◽  
Vol 7 (3.34) ◽  
pp. 296
Author(s):  
Ji Yun Seo ◽  
Yun Hong Noh ◽  
Do Un Jeong
Keyword(s):  
Monitoring System ◽  
Health Management ◽  
Daily Life ◽  
Estimation Method ◽  
Discrimination Performance ◽  
Long Time ◽  
Control Section ◽  
Smart Health ◽  
Management Functions ◽  
System Disorder

Modern people spend many hours of daily life, such as study and work, to the sitting position with chairs and sofas.  If you sit for a long time with a wrong posture, musculoskeletal system disorder can occur and distraction due to low concentrations. In this research, we implemented the chair-type smart health management monitoring system which provides the user with the traditional functions of the chair more effectively and also enables various health management functions. For this reason Three load cells (SB S - beam load cell, 100 kgf) were arranged in an equilateral triangle shape between the top plate and the lower plate of the chair to construct a control section. In addition, we designed a measuring section composed of a filter and an amplifier so that we can simultaneously measure weight signal and BCG. We implemented an information-based posture discrimination algorithm of weight information and a distraction estimation method and implemented a PC and Android-based smartphone monitoring system. We conducted two experiments to evaluate the performance of the implemented system. First of all, in order to evaluate the performance of the posture discrimination algorithm, nine postures were obtained for 10 test subjects in an arbitrary order. As a result of comparing arbitrary posture and posture discrimination results, it showed discrimination performance of 97.9%. Finally, experiment was conducted to confirm the usefulness of the discrimination of distraction in daily life. The experimenter checked the change of the indicator according to the posture change during audiovisual data appreciation. Distraction continued changing posture as a result of confirming the image of the section where the numerical value is high, and confirmed that it is not concentrating on the image. The implement system can help not only health care function in daily life, but also to induce proper posture and improve sitting habit. In future studies, we intend to conduct a research to objectively demonstrate the usefulness of the Distraction estimated index. 

scholarly journals A simplified monitoring model for PMSM servoactuator prognostics

2019 ◽  
Vol 304 ◽  
pp. 04013 ◽  
Author(s):  
Pier Carlo Berri ◽  
Matteo D.L. Dalla Vedova ◽  
Paolo Maggiore ◽  
Francesco Viglione
Keyword(s):  
Failure Modes ◽  
Position Control ◽  
Health Management ◽  
Risk Mitigation ◽  
Fuel Efficiency ◽  
Computational Cost ◽  
Weight Ratio ◽  
Safety Critical ◽  
Aircraft Systems ◽  
Fidelity Model

Electromechanical actuators (EMAs) based on Permanent Magnet Synchronous Motors (PMSMs) are currently employed on various aircraft systems, and are becoming more and more widespread in safety critical applications. Compared to other electrical machines, PMSM offer a high power to weight ratio and low cogging: this makes them suited for position control and actuation tasks. EMAs offer several advantages over hydraulic servoactuators, in terms of modularity, mechanical simplicity, overall weight and fuel efficiency. At the same time, their basic reliability is inherently lower compared to hydraulic actuators. Then, the use of EMAs for safety critical aircraft systems requires the adoption of risk mitigation techniques to counter this issue. In this framework, diagnostic and prognostic strategies can be used for the system health management, to monitor its behaviour in search of the early signs of the most common or dangerous failure modes. We propose a low fidelity model of a PMSM based EMA, intended for model-based diagnostic and prognostic monitoring. The model features low computational cost, allowing the execution in nearly real-time, combined with suitable accuracy in the simulation of faulty system operations. This simplified emulator is validated by comparing its behaviour to a higher fidelity model, employed as a simulated test bench.

ICEMS: Intelligent Condition-Based Engine/Equipment Management System (www.icems.com)

2001 ◽  
Author(s):  
Link Jaw ◽  
Yu-tsung (Jim) Wang ◽  
Richard Friend
Keyword(s):  
Air Force ◽  
Management System ◽  
Health Management ◽  
Equipment Management ◽  
Turbine Engine ◽  
Software Modules ◽  
Air Force Base ◽  
Using Data ◽  
Diagnostics System ◽  
Management Functions

Health management of a machine, such as a gas turbine engine, offers the potential benefits of efficient operations planning and the reduced cost of ownership. It requires a tight integration of major health management functions, such as trending, failure identification, forecasting, life prediction, operations and maintenance planning. This paper introduces a suite of plug-in tools that enhance the condition monitoring and health management capabilities of operational (or legacy) systems. One of these systems is the U. S. Air Force Comprehensive Engine Trending and Diagnostics System (CETADS), which has been used as the baseline for the development of the tools. These tools are collectively called the Intelligent Condition-based Engine/Equipment Management System (ICEMS). These tools are configured as software modules, which can be incorporated into an operational health management system individually or as a group. ICEMS modules implement the advanced algorithms containing artificial intelligence, statistical, model-based analysis techniques, and RCM practices. Although these modules have been developed and tested using data from the Pratt & Whitney F100-PW-220 engine in service at Luke Air Force Base, the modules are also generalized to cover many generic machines (or equipment).

scholarly journals A Survey of Health Management User Objectives in Aerospace Systems Related to Diagnostic and Prognostic Metrics

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Kevin R. Wheeler ◽  
Tolga Kurtoglu ◽  
Scott D. Poll
Keyword(s):  
Health Management ◽  
Lessons Learned ◽  
Management Systems ◽  
Detailed Survey ◽  
Engineering Development ◽  
Diagnosis And Prognosis ◽  
Aerospace Applications ◽  
Aerospace Systems ◽  
Technical Challenges ◽  
Management Functions

One of the most prominent technical challenges to effective deployment of health management systems is the vast difference in user objectives with respect to engineering development. In this paper, a detailed survey on the objectives of different users of health management systems is presented. These user objectives are then mapped to the metrics typically encountered in the development and testing of two main systems health management functions: diagnosis and prognosis. Using this mapping, the gaps between user goals and the metrics associated with diagnostics and prognostics are identified and presented with a collection of lessons learned from previous studies that include both industrial and military aerospace applications.

scholarly journals Prediction of the Remaining Useful Life of Aircraft Systems via Web Interface

2020 ◽  
Vol 16 (04) ◽  
pp. 23
Author(s):  
Daniel Azevedo ◽  
Bernardete Ribeiro ◽  
Alberto Cardoso
Keyword(s):  
Machine Learning ◽  
Health Management ◽  
Remaining Useful Life ◽  
Machine Learning Techniques ◽  
Web Interface ◽  
Web Based ◽  
Aircraft Systems ◽  
Public Data ◽  
Useful Life ◽  
User Friendly

In this work a web-based tool is presented for the simulation of a Prognostics and Health Management (PHM) system used for exploring and testing different machine learning experimental scenarios with the goal of predicting the Remaining Useful Life (RUL) of aircraft systems. With this tool, the user can select a set of options like the datasets to use, its size, the machine learning method to apply for the RUL prediction and the metrics used for comparing the results. The proposed datasets correspond to public data extracted from a model which aims to simulate a Turbofan Engine dataset of an aircraft. Also, three different State of the Art machine learning techniques are made available to be applied and tested: a Similarity-based, a Neural Network-based and an Extrapolation-based approach. The results obtained by the different approaches can be graphically compared in the web interface. As the methods are executed remotely, the user incurs no computational costs, which constitutes an advantage of using this tool. This web tool aims to be a user-friendly interface used for simulating online experiments regarding the RUL prediction.

Sign in / Sign up

Export Citation Format

Share Document