Energy model of change in technical condition of aircraft power plants and space propulsion systems

Augustyn, Sławomir

doi:10.1515/afit-2017-0009

Cited by 3 publications

(1 citation statement)

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“…Gas turbine in-service monitoring proved to be useful in potential failure diagnosis and prevention as well as in its emission monitoring [36]. Appropriate gas turbine utilization, for example in de-rated temperature mode, may have significant contribution to decrease in harmful exhaust emissions [20] as well as to extend reliable operation of the system [1]. In this article accumulated gas turbine operating service data has been studied to predict key parameters.…”

Section: Introductionmentioning

confidence: 99%

Industrial gas turbine operating parameters monitoring and data-driven prediction

Pawełczyk¹,

Fulara²,

Sepe³

et al. 2020

Eksploatacja i Niezawodność – Maintenance and Reliability

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The article reviews traditional and modern methods for prediction of gas turbine operating characteristics and its potential failures. Moreover, a comparison of Machine Learning based prediction models, including Artificial Neural Networks (ANN), is presented. The research focuses on High Pressure Compressor (HPC) recoup pressure level of 4th generation LM2500 gas generator (LM2500+G4) coupled with a 2-stage High Speed Power Turbine Module. The researched parameter is adjustable and may be used to balance net axial loads exerted on thrust bearing to ensure stable gas turbine operation, but its direct measurement is technically difficult implicating the need to indirect measurement via set of other gas turbine sensors. Input data for the research have been obtained from BHGE manufactured and monitored gas turbines and consists of real-time data extracted from industrial installations. Machine learning models trained using the data show less than 1% Mean Absolute Percentage Error (MAPE) as obtained with the use of Random Forest and Gradient Boosting Regression models. Multilayer Perceptron Artificial Neural Networks (MLP ANN) models are reviewed, and their performance checks inferior to Random Forest algorithm-based model. The importance of hyperparameter tuning and feature engineering is discussed.

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Section: Introductionmentioning

confidence: 99%

Industrial gas turbine operating parameters monitoring and data-driven prediction

Pawełczyk¹,

Fulara²,

Sepe³

et al. 2020

Eksploatacja i Niezawodność – Maintenance and Reliability

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Crew – Spacecraft – Environment Anthropotechnical System in View of Engineering Systems

Augustyn¹

2018

Research Works of Air Force Institute of Technology

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The publication describes an example of the anthropotechnical system (crew-spacecraft-environment) in view of engineering systems, which enables to shape their dependability by simultaneously ensuring the safety of space flight operations and more economical operations. Further research on developing the anthropotechnical system should involve the implementation of the elements of artificial intelligence based on expert systems or artificial neural networks.

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A New Strategy for Developing of Space Logistics

Augustyn

2020

Journal of KONBiN

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This paper shows a new strategy for developing of space logistics which is supported by safety engineering for the operational techniques and technologies in space. A new strategy is a very important for developing of space technology because account improvement range and its independence from most terrestrial network failures. The developing space logistics is observable during make of satellites which are ensuring wide-ranging continuous information flow among people, businesses and governments for assuring of safety and security when terrestrial network connections are disrupted. The main goal in this publication is presenting example of analysis and assessment in an industrial enterprise of space logistics.

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Energy model of change in technical condition of aircraft power plants and space propulsion systems

Cited by 3 publications

References 0 publications

Industrial gas turbine operating parameters monitoring and data-driven prediction

Industrial gas turbine operating parameters monitoring and data-driven prediction

Crew – Spacecraft – Environment Anthropotechnical System in View of Engineering Systems

A New Strategy for Developing of Space Logistics

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