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7-tik 1-7 emaitza erakusten
Interpreting Remaining Useful Life estimations combining Explainable Artificial Intelligence and domain knowledge in industrial machinery
(IEEE, 2020)
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 ...
Automatic Web Navigation Problem Detection Based on Client-Side Interaction Data
(Korea Information Processing Society-Computer Software Research Group, 2021)
The current importance of digital competence makes it essential to enable people with disabilities to use digital devices and applications and to automatically adapt site interactions to their needs. Although most of the ...
Data-Driven Fault Diagnosis for Electric Drives: A Review
(MDPI, 2021)
The need to manufacture more competitive equipment, together with the emergence of the digital technologies from the so-called Industry 4.0, have changed many paradigms of the industrial sector. Presently, the trend has ...
Using Machine Learning to Build Test Oracles: an Industrial Case Study on Elevators Dispatching Algorithms
(IEEE, 2021)
The software of elevators requires maintenance over several years to deal with new functionality, correction of bugs or legislation changes. To automatically validate this software, test oracles are necessary. A typical ...
Sensor signal selection for tool wear curve estimation and subsequent tool breakage prediction in a drilling operation
(Taylor & Francis, 2021)
Tool condition monitoring have an important role in machining processes to reduce defective component and ensure quality requirements. Stopping the process before the tool breaks or an excessive tool wear is reached can ...
Data-driven energy resource planning for Smart Cities
(IEEE, 2020)
Cities are growing and, therefore, the primary needs, such as the energy resources. Hence, managing them in the proper way becomes essential for a sustainable growth. This paper proposes a data-driven tool based on IoT ...
Application of Computer Vision and Deep Learning in the railway domain for autonomous train stop operation
(IEEE, 2020)
The purpose of this paper is to present the results of the analysis of the application of Deep Learning in the railway domain with a particular focus on a train stop operation. The paper proposes an approach consisting of ...