Analysis of Electrical and Non-electrical Causes of Variable Frequency Drive Failures

VFDs （variable frequency drives） are an integral part of many industrial plants and stations. Reliable operation and maintenance of these drives is vital to ensure sustained plant operation and availability. Understanding of the principles of operation of VFD systems as well as knowledge about their required operating environment is necessary for all operating personnel. Many times the operating personnel do not get involved with different technical issues until a complete failure has occurred. Hence, the awareness of the most dominant failure causes has a significant impact on assisting operators to avoid catastrophic failures and tremendous economic losses due to VFD shutdown. Proper plant design, accurate monitoring and data logging, following manufacturer preventive maintenance schedule, and choosing qualified team of operators can be the key to an efficient operation and a long lifetime for any VFD system. In this paper, we have analyzed the electrical and non-electrical causes of VFD failures based on a case study of a typical medium voltage VFD pumping station. Finally, recommendations are given from field analysis and observations.

Multilevel Feature Moving Average Ratio Method for Fault Diagnosis of the Microgrid Inverter Switch

Multilevel feature moving average ratio method is proposed to realize an open-switch fault diagnosis for any switch of the microgrid inverter. The main steps of the proposed method include multilevel signal decomposition, coefficient reconstruction, absolute average ratio process and artificial neural network U+0028 ANN U+0029 classification. Specifically, multilevel signal decomposition is realized by using the means of multi resolution analysis to obtain the different frequency band coefficients of the three-phase current signal. The related coefficient reconstruction is executed to achieve signals decomposition in different levels. Furthermore, according to the obtained data, the absolute average ratio process is used to extract absolute moving average ratio of signal decomposition in different levels for the three-phase current. Finally, to intelligently classify the inverter switch fault and realize the adaptive ability, the ANN technology is applied. Compared to conventional fault diagnosis methods, the proposed method can accurately detect and locate the open-switch fault for any location of the microgrid inverter. Additionally, it need not set related threshold of algorithm and does not require normalization process, which is relatively easy to implement. The effectiveness of the proposed fault diagnosis method is demonstrated through detailed simulation results. © 2017 Chinese Association of Automation.