IoT enabled Intelligent Fault Diagnosis System for Two-level Voltage Source Converter

Abstract

Power electronic converters are essential in the conditioning of electrical energy in a wide range of applications. To enhance the reliability of these power converters, different condition monitoring approaches are adapted that can analyze the health condition of power converters in real-time. The Intelligent Health Surveillance and IoT fault diagnosis system has recently gained attention due to its readiness and operational flexibility. This article proposes an intelligent fault diagnostic algorithm for an IoT-integrated three-phase two-level voltage converter. The proposed fault diagnosis scheme detects single and double open circuit switch faults using simple Park’s vector-based technique. The normalized mean value and the absolute average value of phase currents are used as fault indicators in the proposed scheme. Obtained real-time fault data is further processed in cloud platforms for long-term storage and analysis. An application is developed for the acquisition and visualization of fault data, as well as to receive an alert message in their registered e-mail account.