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Developing health indicators for composite structures based on a two-stage semi-supervised machine learning model using ...

Project: ENHAnCE

Updated at: 30-08-2024

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A general approach to assessing SHM reliability considering sensor failures based on information theory

Project: ENHAnCE

Updated at: 14-07-2024

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Training of physics-informed Bayesian neural networks with ABC-SS for prognostic of Li-ion batteries

Project: ENHAnCE

Updated at: 14-07-2024

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A Novel machine learning model to design historical-independent health indicators for composite structures.

Project: ENHAnCE

Updated at: 14-07-2024

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Intelligent and adaptive asset management model for railway sections using the ipn method.

Project: ENHAnCE

Updated at: 14-07-2024

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Self-adaptative optimized maintenance of offshore wind turbines by intelligent Petri nets

Project: ENHAnCE

Updated at: 28-04-2024

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Guided waves-based damage identification in plates through an inverse Bayesian process

Project: ENHAnCE

Updated at: 28-04-2024

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An assessment of different reinforcement learning methods for creating a decision support system based on the Petri net ...

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Asset management modelling approach integrating structural health monitoring data for composite components of wind turbi...

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Numerical simulation-aided particle filter-based damage prognosis using Lamb waves

Project: ENHAnCE

Updated at: 28-04-2024

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Physics-guided Bayesian neural networks by ABC-SS: Application to reinforced concrete

Project: ENHAnCE

Updated at: 28-04-2024

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Risk-based maintenance strategy selection for wind turbine composite blades

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Particle filter-based hybrid damage prognosis considering measurement bias

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Evaluation Guidelines for ERS recruitment

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

End of Year 2 Summary Report & Perspective

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Lecture synthesis of TWs 1 to 6

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Progress Report

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

A wind turbine blade leading edge rain erosion computational framework

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Intelligent Health Indicators Based on Semi-supervised Learning Utilizing Acoustic Emission Data

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Minutes of Mid-term SB meeting and report about financial, legal and risk managements

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Planned recruitments completed

Project: ENHAnCE

Updated at: 28-04-2024

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PCDP plans

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Structural digital twin framework: Formulation and technology integration

Project: ENHAnCE

Updated at: 28-04-2024

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Particle filter-based delamination shape prediction in composites subjected to fatigue loading

Project: ENHAnCE

Updated at: 28-04-2024

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Probabilistic safety assessment in composite materials using bnn by ABC-SS

Project: ENHAnCE

Updated at: 28-04-2024

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Periodic Reporting for period 1 - ENHAnCE (European training Network in intelligent prognostics and Health mAnagement in...

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Training overview and monitoring methodology

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Consortium Agreement

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Intelligent health indicator construction for prognostics of composite structures utilizing a semi-supervised deep neura...

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Uncertainty quantification in Neural Networks by Approximate Bayesian Computation: Application to fatigue in composite m...

Project: ENHAnCE

Updated at: 28-04-2024

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Project acronym ENHAnCE

Resources

Selected filters:

Developing health indicators for composite structures based on a two-stage semi-supervised machine learning model using ...

A general approach to assessing SHM reliability considering sensor failures based on information theory

Training of physics-informed Bayesian neural networks with ABC-SS for prognostic of Li-ion batteries

A Novel machine learning model to design historical-independent health indicators for composite structures.

Intelligent and adaptive asset management model for railway sections using the ipn method.

Self-adaptative optimized maintenance of offshore wind turbines by intelligent Petri nets

Guided waves-based damage identification in plates through an inverse Bayesian process

An assessment of different reinforcement learning methods for creating a decision support system based on the Petri net ...

Asset management modelling approach integrating structural health monitoring data for composite components of wind turbi...

Numerical simulation-aided particle filter-based damage prognosis using Lamb waves

Physics-guided Bayesian neural networks by ABC-SS: Application to reinforced concrete

Risk-based maintenance strategy selection for wind turbine composite blades

Particle filter-based hybrid damage prognosis considering measurement bias

Evaluation Guidelines for ERS recruitment

End of Year 2 Summary Report & Perspective

Lecture synthesis of TWs 1 to 6

Progress Report

A wind turbine blade leading edge rain erosion computational framework

Intelligent Health Indicators Based on Semi-supervised Learning Utilizing Acoustic Emission Data

Minutes of Mid-term SB meeting and report about financial, legal and risk managements

Planned recruitments completed

PCDP plans

Structural digital twin framework: Formulation and technology integration

Particle filter-based delamination shape prediction in composites subjected to fatigue loading

Probabilistic safety assessment in composite materials using bnn by ABC-SS

Periodic Reporting for period 1 - ENHAnCE (European training Network in intelligent prognostics and Health mAnagement in...

Training overview and monitoring methodology

Consortium Agreement

Intelligent health indicator construction for prognostics of composite structures utilizing a semi-supervised deep neura...

Uncertainty quantification in Neural Networks by Approximate Bayesian Computation: Application to fatigue in composite m...