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An RCM Implementation for Wind Turbine Maintenance using MFEA Method and NHPP Model |
Published in: | Innovation in Education and Inclusion : Proceedings of the 16th LACCEI International Multi-Conference for Engineering, Education and Technology | |
Date of Conference: | July 18-20, 2018 |
Location of Conference: | Lima, Perú |
Authors: |
Reynaldo Condori Yucra (Universidad Nacional de Juliaca, PE)
Norman Jesús Beltrán Castañón (Universidad Nacional del Altiplano Puno, PE)
Jose Ramos Cutipa (Universidad Nacional del Altiplano Puno, PE)
Saul Huaquipaco Encinas (Universidad Nacional de Juliaca, PE)
Rodrigo Aquino Larico (Universidad Nacional de Juliaca, PE)
Henry Pizarro Viveros (Universidad Nacional de Juliaca, PE)
Henry Shuta Lloclla (Universidad Nacional del Altiplano, PE) |
Full Paper: | #500 |
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Abstract:The implementation of wind power plants for the generation of energy is becoming increasingly popular, however the generation equipment may have failures due to factors of the equipment or operation, in this sense it is important to have a predictive maintenance strategy that allows to anticipate the possible faults that could arise. In this paper we propose the implementation of a Reliability-Centered Maintenance (RCM) scheme, applied to a wind turbine plant using Failure Mode Effect Analysis (FMEA) and Non-Homogeneous Poisson Process (NHPP), which require minimal use of advanced monitoring technologies and simple data acquisition systems. For this, the critical components of the wind system that may present failure are used as indicators to predict the general maintenance time of the system. First, these components to be used as indicators for predictive maintenance are chosen using the FMEA method, where the most critical components are chosen. Second, the fault information of the chosen components are analyzed using the NHPP model; Finally, the analysis of the results is carried out, especially calculating the average time of failure and thus deciding the time of general maintenance of the wind system. The present work demonstrates the validity of these known techniques applied to a wind generation plant, thus supporting the development of the implementation of more wind generator centers.
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