A Multiswitch Open-Circuit Fault Diagnosis of Microgrid Inverter Based on Slidable Triangularization Processing

Abstract

In this article, a robust inverter fault diagnosis algorithm is proposed under microgrid environment considering unbalanced state and overcurrent component interference. First, the detected signals are transformed into different data triangles by the proposed slidable triangularization processing which can conveniently and effectively extract the multiscale trend features and data jitter components. Further, the signed features are obtained by the proposed jitter signing processing method, which can reduce the influence of amplitude, and facilitate the logical operation and mixed operation. Then, a quantitative trend fault degree is calculated by the signed information to reflect the fault degree and location information, which has the characteristics of quantitative change. It can reduce the fluctuation and quantity of fault data features. Finally, echo state network is used to implement the intelligent classification. Because the design of hidden layer and the network training speed is simple and fast, which makes the design, implementation, and debugging of fault diagnosis more convenient. Compared with the existing fault diagnosis algorithms, it is robust to unbalanced state and overcurrent component interference of microgrid. These features make it more suitable for inverter fault diagnosis of microgrid environment. The effectiveness of fault diagnosis algorithm is verified by the experiments and comparisons.