Simulation and experimental verification on dynamic calibration of fuel gear flowmeters

Wang, Bin; Du, Yihao; Xu, Nanyue

doi:10.1016/j.measurement.2019.02.044

Cited by 18 publications

(5 citation statements)

References 13 publications

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“…Find potential failures affecting fuel metering and supply, develop more reliable metering methods [27][28][29] Icing issue Reproduce the accident and analyse the cause to improve the existing system [30,31] Fuel filter Explore and resolve potential failures and challenges presented by new technologies/fuels [32][33][34][35][36][37] Other vulnerable components…”

Section: Referencesmentioning

confidence: 99%

“…Furthermore, accurate fuel flow measurement is always a problem since the flowmeter needs to be placed directly in the flow field. Therefore, they are easily affected by factors such as contamination in the fuel, fluid property, turbulence, and fluctuation in the flow, including flow rate and pressure changes [35]. Apart from some advanced flowmeters, such as ultrasonic and electromagnetic flowmeters, researchers also worked on alternative ways of measuring flow.…”

Section: Referencesmentioning

confidence: 99%

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Intelligent Fault Diagnosis of an Aircraft Fuel System Using Machine Learning—A Literature Review

King

Jennions

2023

Machines

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The fuel system, which aims to provide sufficient fuel to the engine to maintain thrust and power, is one of the most critical systems in the aircraft. However, possible degradation modes, such as leakage and blockage, can lead to component failure, affect performance, and even cause serious accidents. As an advanced maintenance strategy, Condition Based Maintenance (CBM) can provide effective coverage, by combining state-of-the-art sensors with data acquisition and analysis techniques to guide maintenance before the asset’s degradation becomes serious. Artificial Intelligence (AI), particularly machine learning (ML), has proved effective in supporting CBM, for analyzing data and generating predictions regarding the asset’s health condition, thus influencing maintenance plans. However, from an engineering perspective, the output of ML algorithms, usually in the form of data-driven neural networks, has come into question in practice, as it can be non-intuitive and lacks the ability to provide unambiguous engineering signals to maintainers, making it difficult to trust. Engineers are interested in a deterministic decision-making process and how it is being revealed; algorithms should be able to certify and convince engineers to approve recommended actions. Explainable AI (XAI) has emerged as a potential solution, providing some of the logic on how the output is derived from the input given, which may help users understand the diagnostic result of the algorithm. In order to inspire and advise data scientists and engineers who are about to develop and use AI approaches in fuel systems, this paper explores the literature of experiment, simulation, and AI-based diagnostics for the fuel system to make an informed statement as to the progress that has been made in intelligent fault diagnostics for fuel systems, emphasizing the necessity of giving unambiguous engineering signals to maintainers, as well as highlighting potential areas for future research.

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Section: Referencesmentioning

confidence: 99%

Section: Referencesmentioning

confidence: 99%

Intelligent Fault Diagnosis of an Aircraft Fuel System Using Machine Learning—A Literature Review

King

Jennions

2023

Machines

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“…Исследования Zhen, Wang и др. [8,9] показали, что результаты, полученные при моделировании расходомеров методами компьютерной гидродинамики (CFD), близки к натурным, что дает возможность существенно быстрого и менее трудоемкого прогнозирования влияния рабочих параметров потока и геометрии элементов расходомера.…”

Section: Introductionunclassified

Improving the quality of turbine flowmeters on the basis of the use of a rotor with internal screw relief

Bashmur¹,

Bukhtoyarov²,

Sergienko³

et al. 2022

SOCAR Proceedings

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This research aims to improve the quality of measurement of fluid flow rates by turbine flowmeters. The quality criteria for a turbine flowmeter include the accuracy of measurement and the cost of its implementation. To compare the criteria, the article presents a hydrodynamic simulation of the movement of the flow of the working medium through the rotors of the flowmeters of the developed and standard types. The developed type of rotor is a hollow shaft with an internal screw relief. A propeller type of rotor was used as standard. Based on the results of the literature analysis, the purpose of the study was reduced to determining the characteristics of hydraulic resistance that affect the linearity of the flow-pressure characteristics of the flowmeter rotor. The tasks of hydrodynamic computer simulation included its implementation for various indicators of the viscosity of the working fluid - from low-viscosity to high-viscosity. It showed that the use of a rotor with an internal screw relief in a flowmeter reduces the hydraulic resistance of the flow by more than 2 times for any viscosity of the working medium compared to a propeller-type rotor, which significantly reduces the energy costs for moving the flow. At the same time, the linearity of characteristics for both types of flowmeter rotors remains approximately the same in the studied range of characteristics, which indicates a similar accuracy of parameter measurements. Keywords: turbine flowmeter; viscosity; hydraulic resistance; oil transportation; computational fluid dynamics; CFD.

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“…The dynamic response of pressure transmission tubes is essentially a flow phenomenon governed by Navier-Stokes (N-S) equations, and various theoretical models are simplifications of N-S equations on different assumptions. CFD technology for solving N-S equations has progressed remarkably nowadays and has been used in flow rate measurement, such as pressure probes [29], pneumatic components [49], Venturi nozzles [50,51], stacks [52] and fuel gear flowmeters [53]. The tap-flow interaction in unsteady pressure measurement can also be simulated by CFD tools and the response of the measurement system can be predicted easily.…”

Section: Introductionmentioning

confidence: 99%

Flow structure of pressure transmission tube and its influence on unsteady pressure measuring results in compressible flow

Tong

Zhang

Yue

et al. 2021

Aerospace Science and Technology

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Simulation and experimental verification on dynamic calibration of fuel gear flowmeters

Cited by 18 publications

References 13 publications

Intelligent Fault Diagnosis of an Aircraft Fuel System Using Machine Learning—A Literature Review

Intelligent Fault Diagnosis of an Aircraft Fuel System Using Machine Learning—A Literature Review

Improving the quality of turbine flowmeters on the basis of the use of a rotor with internal screw relief

Flow structure of pressure transmission tube and its influence on unsteady pressure measuring results in compressible flow

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