微型电脑应用2026，Vol.42Issue(7)：21-24,29,5.
基于数据驱动和概率神经网络的光伏阵列智能故障诊断与监控
Intelligent Fault Diagnosis and Monitoring of Photovoltaic Arrays Based on Data-driven and Probabilistic Neural Networks
摘要
Abstract
To improve the diagnostic accuracy of current photovoltaic array fault diagnosis methods,this paper proposes an in-telligent fault diagnosis and monitoring method for photovoltaic arrays based on data-driven and probabilistic neural networks.A photovoltaic array model is constructed.The normal and faulty operation data of the photovoltaic array model are integrated into 9 types of fault samples as input data.A fault diagnosis algorithm model is designed by the particle swarm optimizer and probabilistic neural networks based on the ideals of parallel and transfer learning.The experimental results confirm that the fault diagnosis accuracy rate of the proposed algorithm reaches 97.81％,with an improvement range of 1.51％to 11.20％compared to various deep learning algorithms.It still maintains a robustness of over 95％under different degrees of noise inter-ference.关键词
光伏阵列/故障诊断/数据驱动/概率神经网络/粒子群优化器/迁移学习Key words
photovoltaic arrays/fault diagnosis/data-driven/probabilistic neural networks/particle swarm optimizer/transfer learning分类
信息技术与安全科学引用本文复制引用
程航,张晖,代家昆,陈友,岑心..基于数据驱动和概率神经网络的光伏阵列智能故障诊断与监控[J].微型电脑应用,2026,42(7):21-24,29,5.基金项目
国能长源汉川发电有限公司工程项目(HCXNY-GC-2024-001) （HCXNY-GC-2024-001）
