Oscar Serradilla
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View article: Best Practice Data Sharing Guidelines for Wind Turbine Fault Detection Model Evaluation
Best Practice Data Sharing Guidelines for Wind Turbine Fault Detection Model Evaluation Open
In this paper, a set of best practice data sharing guidelines for wind turbine fault detection model evaluation is developed, which can help practitioners overcome the main challenges of digitalisation. Digitalisation is one of the key dri…
View article: Best Practice Data Sharing Guidelines for Wind Turbine Fault Detection Model Evaluation
Best Practice Data Sharing Guidelines for Wind Turbine Fault Detection Model Evaluation Open
The digital era offers many opportunities to the wind energy industry and research community. Digitalisation is one of the key drivers for reducing costs and risks over the whole wind energy project life cycle. One of the largest challenge…
View article: Methodology for data-driven predictive maintenance models design, development and implementation on manufacturing guided by domain knowledge
Methodology for data-driven predictive maintenance models design, development and implementation on manufacturing guided by domain knowledge Open
The 4th industrial revolution has connected machines and industrial plants, facilitating process monitoring and the implementation of predictive maintenance (PdM) systems that can save up to 60% of maintenance costs. Nowadays, most PdM res…
View article: Adaptable and Explainable Predictive Maintenance: Semi-Supervised Deep Learning for Anomaly Detection and Diagnosis in Press Machine Data
Adaptable and Explainable Predictive Maintenance: Semi-Supervised Deep Learning for Anomaly Detection and Diagnosis in Press Machine Data Open
Predictive maintenance (PdM) has the potential to reduce industrial costs by anticipating failures and extending the work life of components. Nowadays, factories are monitoring their assets and most collected data belong to correct working…
View article: Deep learning models for predictive maintenance: a survey, comparison, challenges and prospect
Deep learning models for predictive maintenance: a survey, comparison, challenges and prospect Open
Given the growing amount of industrial data spaces worldwide, deep learning solutions have become popular for predictive maintenance, which monitor assets to optimise maintenance tasks. Choosing the most suitable architecture for each use-…
View article: Interpreting Remaining Useful Life estimations combining Explainable Artificial Intelligence and domain knowledge in industrial machinery
Interpreting Remaining Useful Life estimations combining Explainable Artificial Intelligence and domain knowledge in industrial machinery Open
This paper presents the implementation and explanations of a remaining life estimator model based on machine learning, applied to industrial data. Concretely, the model has been applied to a bushings testbed, where fatigue life tests are p…