Safari Ashkan, Sabahi Mehran, Oshnoei Arman
Ashkan Safari and Mehran Sabahi with the Faculty of Electrical and Computer Engineering, Tabriz, Iran.
Arman Oshnoei with Department of Energy, Aalborg University, Aalborg, Denmark.
Heliyon. 2024 Jul 26;10(15):e35243. doi: 10.1016/j.heliyon.2024.e35243. eCollection 2024 Aug 15.
Intelligent fault detection considered as a paramount importance in Power Electronics Systems (PELS) to ensure operational reliability along with rising complexities and critical application demands. However, most of the developed methods in real-world scenarios can have better detection, and accurate diagnosis. In this regard, ResFaultyMan, a novel unsupervised isolation forest-based model, is presented in this paper, for real-world fault/anomaly detection in PELS. Capitalizing on the dynamics of faults, ResFaultyMan utilizes a tree-based structure for effective anomaly isolation, demonstrating adaptability to diverse fault scenarios. The test bench, comprising a load, Triac switch, resistor, voltage source, and Pyboard microcontroller, provides a dynamic setting for performance evaluation. The integration of a Pyboard microcontroller and a Python-to-Python interface facilitates fast data transfer and sampling, enhancing the efficiency of ResFaultyMan in real-time fault detection scenarios. Comparative analysis with OneClassSVM and LocalOutlierFactor, utilizing Key Performance Indicators (KPIs) of Accuracy, Precision, and Recall, as well as F1 Score, manifest ResFaultyMan's fault detection capabilities for fault detection in PELSs, and its performance in the related applications.
智能故障检测在电力电子系统（PELS）中被视为至关重要，以确保随着复杂性的增加和关键应用需求的提升，系统能够可靠运行。然而，在实际场景中，大多数已开发的方法在检测和准确诊断方面可能表现得更好。在这方面，本文提出了一种名为ResFaultyMan的新型基于无监督隔离森林的模型，用于电力电子系统中的实际故障/异常检测。ResFaultyMan利用故障的动态特性，采用基于树的结构进行有效的异常隔离，展现出对各种故障场景的适应性。由负载、双向可控硅开关、电阻、电压源和Pyboard微控制器组成的测试平台，为性能评估提供了动态设置。Pyboard微控制器与Python到Python接口的集成促进了快速数据传输和采样，提高了ResFaultyMan在实时故障检测场景中的效率。通过使用准确率、精确率、召回率以及F1分数等关键性能指标（KPI）与OneClassSVM和LocalOutlierFactor进行对比分析，证明了ResFaultyMan在电力电子系统故障检测中的故障检测能力及其在相关应用中的性能。
