[HTML][HTML] Relation between prognostics predictor evaluation metrics and local interpretability SHAP values
Maintenance decisions in domains such as aeronautics are becoming increasingly
dependent on being able to predict the failure of components and systems. When data …
dependent on being able to predict the failure of components and systems. When data …
An ensemble framework based on convolutional bi-directional LSTM with multiple time windows for remaining useful life estimation
Effectively estimating remaining useful life (RUL) is crucially important for evaluating
machine health. In the industry, there exists a high degree of inconsistency among the …
machine health. In the industry, there exists a high degree of inconsistency among the …
Applications of metaheuristics in reservoir computing techniques: a review
Reservoir computing approaches have been around for almost two decades. They were
developed to solve the difficult gradient-descent training of recurrent neural networks …
developed to solve the difficult gradient-descent training of recurrent neural networks …
A method for fault detection in multi-component systems based on sparse autoencoder-based deep neural networks
In multi-component systems, degradation, maintenance, renewal and operational mode
change continuously the operating conditions. The identification of the onset of abnormal …
change continuously the operating conditions. The identification of the onset of abnormal …
Transfer learning for remaining useful life prediction based on consensus self-organizing models
The traditional paradigm for developing machine prognostics usually relies on
generalization from data acquired in experiments under controlled conditions prior to …
generalization from data acquired in experiments under controlled conditions prior to …
Comparison of computational prognostic methods for complex systems under dynamic regimes: a review of perspectives
O Bektas, J Marshall, JA Jones - Archives of Computational Methods in …, 2020 - Springer
Complex systems are expected to play a key role in the progress of Prognostics Health
Management but the breadth of technologies that will highlight gaps in the dynamic regimes …
Management but the breadth of technologies that will highlight gaps in the dynamic regimes …
Ensemble of optimized echo state networks for remaining useful life prediction
Abstract The use of Echo State Networks (ESNs) for the prediction of the Remaining Useful
Life (RUL) of industrial components, ie the time left before the equipment will stop fulfilling its …
Life (RUL) of industrial components, ie the time left before the equipment will stop fulfilling its …
An echo state network for fuel cell lifetime prediction under a dynamic micro-cogeneration load profile
Abstract Improving Proton Exchange Membrane Fuel Cell durability is a key that paves the
way to its large scale industrial deployment. During the last five years, the prognostics …
way to its large scale industrial deployment. During the last five years, the prognostics …
An improved grasshopper optimization algorithm based echo state network for predicting faults in airplane engines
In today's age of industrialization, sensor devices installed on equipment generate a vast
amount of data. One of the engineers' main jobs is utilizing these data to provide better …
amount of data. One of the engineers' main jobs is utilizing these data to provide better …
Deep reinforcement learning based on proximal policy optimization for the maintenance of a wind farm with multiple crews
The life cycle of wind turbines depends on the operation and maintenance policies adopted.
With the critical components of wind turbines being equipped with condition monitoring and …
With the critical components of wind turbines being equipped with condition monitoring and …