Data-driven neural network methodology to remaining life predictions for aircraft actuator components

Byington, Carl S.; Watson, Matthew J.; Edwards, D.

doi:10.1109/aero.2004.1368175

Cited by 88 publications

(61 citation statements)

References 2 publications

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“…It is possible to control the rotating movement of the machine; in addition, some work has been done on linear movement. For example, Electro Mechanical Actuators (EMA) are widely used in aeronautic systems; the use of Health Monitoring is also widespread [8,9,10]. Similar actuators are used in machine tools.…”

Section: Condition Monitoring Of Machine Toolsmentioning

confidence: 99%

Risk management based on the assessment of safety barriers

Sobral¹,

Soares²

2014

Proceedings of Maintenance Performance Measurement and Management (MPMM) Conference 2014

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Section: Condition Monitoring Of Machine Toolsmentioning

confidence: 99%

Risk management based on the assessment of safety barriers

Sobral¹,

Soares²

2014

Proceedings of Maintenance Performance Measurement and Management (MPMM) Conference 2014

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“…It is also possible to control the rotating movement of the machine; in addition, some work has been done on linear movement. For example, Electro Mechanical Actuators (EMA) are widely used in aeronautic systems; the use of Health Monitoring is widespread [8,9,10] as well. Similar actuators are used in machine tools.…”

Section: Condition Monitoring Of Machine Toolsmentioning

confidence: 99%

Aggregation of Electric Current Consumption Features to Extract Maintenance KPIs

Simon

Johansson

Galar

2017

Management Systems in Production Engineering

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Abstract:All electric powered machines offer the possibility of extracting information and calculating Key Performance Indicators (KPIs) from the electric current signal. Depending on the time window, sampling frequency and type of analysis, different indicators from the micro to macro level can be calculated for such aspects as maintenance, production, energy consumption etc. On the micro-level, the indicators are generally used for condition monitoring and diagnostics and are normally based on a short time window and a high sampling frequency. The macro indicators are normally based on a longer time window with a slower sampling frequency and are used as indicators for overall performance, cost or consumption. The indicators can be calculated directly from the current signal but can also be based on a combination of information from the current signal and operational data like rpm, position etc. One or several of those indicators can be used for prediction and prognostics of a machine's future behavior. This paper uses this technique to calculate indicators for maintenance and energy optimization in electric powered machines and fleets of machines, especially machine tools.

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“…In fact, the data driven methods such as neural networks [109], decision tree classifiers [110] and Bayesian techniques [111] do not capture the difference between failure modes and mechanisms, although they can obtain the complex relationship and degradation trend in the data without the need for the particular product characteristics such as degradation mechanism or material properties. The PoF models are more rigorous in terms of employing the specific knowledge of products, such as failure mechanism, material properties, loading profile and geometry.…”

Section: Structural Reliability and Health Assessmentmentioning

confidence: 99%

An Entropy-Based Damage Characterization

Amiri

Modarres

2014

Entropy

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This paper presents a scientific basis for the description of the causes of damage within an irreversible thermodynamic framework and the effects of damage as observable variables that signify degradation of structural integrity. The approach relies on the fundamentals of irreversible thermodynamics and specifically the notion of entropy generation as a measure of degradation and damage. We first review the state-of-the-art advances in entropic treatment of damage followed by a discussion on generalization of the entropic concept to damage characterization that may offers a better definition of damage metric commonly used for structural integrity assessment. In general, this approach provides the opportunity to described reliability and risk of structures in terms of fundamental science concepts. Over the years, many studies have focused on materials damage assessment by determining physics-based cause and affect relationships, the goal of this paper is to put this work in perspective and encourage future work of materials damage based on the entropy concept.

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Data-driven neural network methodology to remaining life predictions for aircraft actuator components

Cited by 88 publications

References 2 publications

Risk management based on the assessment of safety barriers

Risk management based on the assessment of safety barriers

Aggregation of Electric Current Consumption Features to Extract Maintenance KPIs

An Entropy-Based Damage Characterization

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