Abstract
In recent times, multilevel inverters are used as a high priority in many sizeable industrial drive applications. However, the reliability and performance of multilevel inverters are affected by the failure of power electronic switches. In this paper, the failure of power electronic switches of multilevel inverters is identified with the help of a high-performance diagnostic system during the open switch and low condition. Experimental and simulation analysis was carried out on five levels cascaded h-bridge multilevel inverter, and its output voltage waveforms were synthesized at different switch fault cases and different modulation index parameter values. Salient frequency-domain features of the output voltage signal were extracted using a Fast Fourier Transform decomposition technique. The real-time work of the proposed fault diagnostic system was implemented through the LabVIEW software. The Offline Artificial neural network was trained using the MATLAB software, and the overall system parameters were transferred to the LabVIEW real-time system. With the proposed method, it is possible to identify the individual faulty switch of multilevel inverters successfully.
Highlights
In recent years, multilevel inverters are drawing intense interest in the research of solid industrial electric drives organizes in the direction of attaining the high power demands necessary with them.The foremost merits of Multilevel Inverters (MLIs) are minimization of harmonic deformation of the output voltage waveform by way of raising incapacity of levels as well as litheness for the usage of battery sets or fuel for in-between periods [1,2,3]. MLIs are effectively used in engineering applications employing a confirmed technology, the collapse of power electronic switches and its fault investigation is until now a recent research issue for researchers
National Instruments (NI) USB-6251 (1.25 MSa/Sec) are worn as data fetching arrangement that are interfaced with the computer to record as well as facilitate the new process for obtaining signals
The significant attributes of load voltage output waveform are examined with simulation as well as experimental analysis on dissimilar open-switch and short-switch faulty conditions
Summary
Multilevel inverters are drawing intense interest in the research of solid industrial electric drives organizes in the direction of attaining the high power demands necessary with them. Semiconductor switches, an open-switch as well as theSeveral short-switch fault, directs in collapse the gate of driving Researchers used the to current harmonics andvoltage generates in the gate driving circuits It reduces inverter output current and fortroubles constructing that fault identification arrangement [11,12]. While the range of that neural network is extremely complex because of 40 input neurons, a different method that contains a mixture of FFT principal constituent analysis, genetic algorithm inside of a new paper, Surin Khomfoi et al projected a different method that contains a mixture of as well as neural network technology for identifying the fault category as well as fault location in an FFT principal constituent analysis, genetic algorithm as well as neural network technology for inverter [14]. Recognition of faulty switches of MLIs is still an emerging research area, and numerous areresearchers steadily working on theworking way to identify the faults precisely. The help of ANN [15,16,17]
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