Detalhes
Nome
Felipe YamadaCargo
InvestigadorDesde
21 março 2022
Nacionalidade
BrasilCentro
Centro de Engenharia e Gestão IndustrialContactos
+351222094000
felipe.yamada@inesctec.pt
2023
Autores
Bacalhau, ET; Barbosa, F; Casacio, L; Yamada, F; Guimarães, L;
Publicação
Proceeding of the 33rd European Safety and Reliability Conference
Abstract
2023
Autores
Yamada, L; Rampazzo, P; Yamada, F; Guimaraes, L; Leitao, A; Barbosa, F;
Publicação
OPERATIONAL RESEARCH, IO 2022-OR
Abstract
Data clustering combined with multiobjective optimization has become attractive when the structure and the number of clusters in a dataset are unknown. Data clustering is the main task of exploratory data mining and a standard statistical data analysis technique used in many fields, including machine learning, pattern recognition, image analysis, information retrieval, and bioinformatics. This project analyzes data to extract possible failure patterns in Solar Photovoltaic (PV) Panels. When managing PV Panels, preventive maintenance procedures focus on identifying and monitoring potential equipment problems. Failure patterns such as soiling, shadowing, and equipment damage can disturb the PV system from operating efficiently. We propose a multiobjective evolutionary algorithm that uses different distance functions to explore the conflicts between different perspectives of the problem. By the end, we obtain a non-dominated set, where each solution carries out information about a possible clustering structure. After that, we pursue a-posteriori analysis to exploit the knowledge of non-dominated solutions and enhance the fault detection process of PV panels.
The access to the final selection minute is only available to applicants.
Please check the confirmation e-mail of your application to obtain the access code.