Nick Eleftheroglou

Delft University of Technology | TU · Aerospace Structures and Materials (ASM)

The performance of prognostic models used for prognostic health management (PHM) applications heavily depend on the quality of features extracted from raw sensor data. Traditionally, feature extraction criteria such as monotonicity, prognosability, and trendability are selected intuitively. However, this intuitive selection may not be optimal. Thi...

This study focuses on a critical aspect of implementing prognostics and health management (PHM) for assets: the creation of a descriptive dataset. In real-world applications, dealing with sparse and unlabelled big data is common, particularly in industries like production lines where complex subprocesses are monitored by multiple sensors. Moreover,...

Prognostic methodologies have found increasing use the last decade and provide a platform for remaining useful life (RUL) predictions of engineering systems utilizing condition monitoring data. Of particular interest is the reliable RUL prediction of engineering assets that either underperform or outperform due to unexpected phenomena that might oc...

Prognosis of the Remaining Useful Life (RUL) of a structure from Structural Health Monitoring data is the ultimate level in the SHM hierarchy. Reliable prognostics are key to a Condition Based Maintenance paradigm for aerospace systems and structures. In the present work, we propose a methodology for RUL prognosis of generic aeronautical elements i...

We investigate the performance of three different data-driven prognostic methodologies towards the Remaining Useful Life estimation of commercial aircraft brakes being continuously monitored for wear. The first approach utilizes a probabilistic multi-state deterioration mathematical model i.e. a Hidden Semi Markov model whilst the second utilizes a...

This paper presents the results for an experimental campaign of in-situ impact during tension-tension fatigue loading for open-hole carbon fibre reinforced polymer specimens. High-speed low energy impact was introduced to the specimen with the use of a canon, which was attached to testing bench enabling the impact without the need to remove the spe...

Prognostics is an emerging field of research that enables the real-time health assessment of an engineering system and the prediction of its future state based on up-to-date information. This field integrates various scientific disciplines including physics/mechanics, computational statistics and probabilistic modeling, machine learning and sensing...

Data driven probabilistic methodologies have found increasing use the last decade and provide a platform for the remaining useful life (RUL) prediction of composite structures utilizing health-monitoring data. Of particular interest is the RUL prediction of composite structures that either underperform or outperform due to unexpected phenomena that...

This paper examines diagnostics and prognostics of Lithium-Polymer (Li-Po) batteries for unmanned aerial vehicles (UAVs). Several discharge voltage histories obtained during actual indoor flights constitute the training data for a data-driven approach, utilizing the Non-Homogenous Hidden Semi Markov model (NHHSMM). NHHSMM is a suitable candidate as...

In this paper, the discharge voltage is utilized as a critical indicator towards the probabilistic estimation of the Remaining Useful Life until the End-of-Discharge of the Lithium-Polymer batteries of unmanned aerial vehicles. Several discharge voltage histories obtained during actual flights constitute the in-house developed training dataset. Thr...

In the present paper, temperature measurements are utilized to develop health indicators based on principal component analysis towards the probabilistic estimation of the Remaining Useful Life (RUL) of reciprocating compressors in service. Temperature degradation histories obtained from thirteen actual valve failure cases constitute the training da...

The procedure of fatigue damage accumulation in composite structures is still unknown and depends on several parameters such as type and frequency of loading, stacking sequence and material properties. Additionally, the nonhomogeneous and anisotropic nature of composites result to a stochastic activation of the different failure mechanisms and make...

The procedure of fatigue damage accumulation in composite structures is still unknown and depends on several parameters such as type and frequency of loading, stacking sequence and material properties. Additionally, the nonhomogeneous and anisotropic nature of composites result to a stochastic activation of the different failure mechanisms and make...

A new structural health monitoring (SHM) data fusion methodology is proposed in order to produce features with strong prognostic capability. The Non-Homogenous Hidden Semi Markov model (NHHSMM) is utilized to estimate the remaining useful life (RUL) of composite structures using conventional as well as fused SHM data. The proposed data fusion metho...

A novel framework to fuse structural health monitoring (SHM) data from different in-situ monitoring techniques is proposed aiming to develop a hyper-feature towards more effective prognostics. A state-of-the-art Non-Homogenous Hidden Semi Markov Model (NHHSMM) is utilized to model the damage accumulation of composite structures, subjected to fatigu...

The procedure of fatigue damage accumulation in composite structures, is a complex phenomenon due to the multiphase nature of composites, the variation of inherent manufacturing defects, the randomness of loads, the stochastic activation of different damage mechanisms and an incomplete knowledge about the physics behind the evolution and interactio...

An innovative prognostic data-driven framework is proposed to deal with the real-time estimation of the remaining useful life of composite materials under fatigue loading based on acoustic emission data and a sophisticated multi-state degradation Non Homogeneous Hidden Semi Markov Model (NHHSMM). The acoustic emission data pre-processing to extract...

The present study utilizes a state-of-the-art stochastic modeling with structural health monitoring (SHM) data derived from strain measurements, in order to assess the remaining useful life (RUL) online in composite materials under fatigue loading. Non-Homogenous Hidden Semi Markov model (NHHSMM) is a suitable candidate with a rich mathematical str...

The present study utilizes a state-of-the-art stochastic modeling with structural health monitoring (SHM) data derived from strain measurements, in order to assess the remaining useful life (RUL) online in composite materials under fatigue loading. Non-Homogenous Hidden Semi Markov model (NHHSMM) is a suitable candidate with a rich mathematical str...

A diagnostic/prognostic framework for damage state assessment and estimation of the remaining useful life of composite materials under fatigue loading is proposed based on acoustic emission data and a sophisticated Non Homogenous Hidden Semi Markov Model. Bayesian neural networks are also utilized as an alternative machine learning technique for th...

This study focused on the in-situ fatigue damage assessment of open-hole carbon/epoxy coupons using Acoustic Emission (AE) and Digital Image Correlation (DIC) techniques. Constant amplitude fatigue tests were performed and the main objective was to investigate the damage process, the degradation process of the fatigue modules and to identify featur...

The procedure of damage accumulation in composites, especially during fatigue loading, is a complex phenomenon of stochastic nature which depends on a number of parameters such as type and frequency of loading, stacking sequence, material properties, and so on. Toward condition-based health monitoring and decision making, the need for not only diag...

The procedure of damage accumulation in composite materials, especially during fatigue loading, is a complex phenomenon which depends on a number of parameters such as ply orientation, material properties, geometrical non-linearities etc. Towards condition based health monitoring and decision making, the need not only for diagnostic but also for pr...

The procedure of damage accumulation in composite materials, especially during fatigue loading, is a complex phenomenon which depends on a number of parameters such as ply orientation, material properties, geometrical non-linearities etc. Towards condition based health monitoring and decision making, the need not only for diagnostic but also for pr...

The procedure of damage accumulation in composite materials, especially during fatigue loading, is a complex phenomenon which depends on a number of parameters such as service loading conditions, ply orientation, material properties, geometrical non-linearities etc. Due to the stochastic nature of damage evolution, its mathematical modelling, param...