Arias Velásquez Ricardo Manuel, Mejía Lara Jennifer Vanessa
Universidad Privada Peruano Alemana, Peru.
Universidad Nacional de San Agustín de Arequipa, Peru.
Heliyon. 2022 Aug 12;8(8):e10094. doi: 10.1016/j.heliyon.2022.e10094. eCollection 2022 Aug.
In the last years, the knowledge management methodology increased the perspective and deeply analysis in the energy evaluation, with great emphasis in the training of the maintenance teams and early detection of failure modes; these inefficiencies detection is associated to patterns recognition with expert systems. Several energy brands, utilities, universities, and design companies investigated about this problem with limits in the integration between maintenance team knowledge and the degradation of the energy equipment. Therefore, our findings are a new approach of the root cause analysis (RCA) improved with the knowledge management perspective, associated to the failure mode analysis for 164 inverters in photo-voltaic solar plant by using twenty-one failures modes; by incorporate the graph theory called Erdös-Rényi graphs with a quantitative methodology and qualitative evaluation with the knowledge management method in the root cause analysis; the dataset evaluated has 120,561 signals associated to 3,014,025 patterns, during the period from 2018 to 2021 in a PV solar plant. In this new root cause analysis method, the knowledge management is analyzed as a complement for the solution for sudden failure modes and early degradation.
在过去几年中，知识管理方法拓宽了能源评估的视野并进行了深入分析，重点是对维护团队的培训以及故障模式的早期检测；这些低效率检测与专家系统的模式识别相关。一些能源品牌、公用事业公司、大学和设计公司对维护团队知识与能源设备退化之间整合存在局限的这一问题进行了研究。因此，我们的研究结果是一种从知识管理角度改进的根本原因分析（RCA）新方法，通过使用21种故障模式与光伏电站中164个逆变器的故障模式分析相关联；在根本原因分析中，通过将称为厄多斯 - 雷尼图的图论与定量方法以及知识管理方法的定性评估相结合；在2018年至2021年期间，对一个光伏电站评估的数据集有与3,014,025个模式相关的120,561个信号。在这种新的根本原因分析方法中，知识管理被视为解决突发故障模式和早期退化问题的补充。
