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E. Parimalasundar,N. Suthanthira Vanitha 대한전기학회 2015 Journal of Electrical Engineering & Technology Vol.10 No.6
In recent times, multilevel inverters are given high priority in many large industrial drive applications. However, the reliability of multilevel inverters are mainly affected by the failure of power electronic switches. In this paper, open-switch and short-switch failure of multilevel inverters and its identification using a high performance diagnostic system is discussed. Experimental and simulation studies were carried out on five level cascaded H-Bridge multilevel inverter and its output voltage waveforms were analyzed at different switch fault cases and at different modulation index values. Salient frequency domain features of the output voltage signal were extracted using the discrete wavelet transform multi resolution signal decomposition technique. Real time application of the proposed fault diagnostic system was implemented through the LabVIEW software. Artificial neural network was trained offline using the Matlab software and the resultant network parameters were transferred to LabVIEW real time system. In the proposed system, it is possible to precisely identify the individual faulty switch (may be due to open-switch (or) short-switch failure) of multilevel inverters.
Parimalasundar, E.,Vanitha, N. Suthanthira The Korean Institute of Electrical Engineers 2015 Journal of Electrical Engineering & Technology Vol.10 No.6
In recent times, multilevel inverters are given high priority in many large industrial drive applications. However, the reliability of multilevel inverters are mainly affected by the failure of power electronic switches. In this paper, open-switch and short-switch failure of multilevel inverters and its identification using a high performance diagnostic system is discussed. Experimental and simulation studies were carried out on five level cascaded H-Bridge multilevel inverter and its output voltage waveforms were analyzed at different switch fault cases and at different modulation index values. Salient frequency domain features of the output voltage signal were extracted using the discrete wavelet transform multi resolution signal decomposition technique. Real time application of the proposed fault diagnostic system was implemented through the LabVIEW software. Artificial neural network was trained offline using the Matlab software and the resultant network parameters were transferred to LabVIEW real time system. In the proposed system, it is possible to precisely identify the individual faulty switch (may be due to open-switch (or) short-switch failure) of multilevel inverters.
Embedded System based Monitoring and Controlling of Parameters in Die Casting Industry
S.Thulasiram,Dr. N.Suthanthira Vanitha,M.Rajendiran,N.Kavitha 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.5
Die casting is the process for manufacturing the metal parts with desired shape for various industrial applications. Casting Process depends on many parameters variation such as die temperature, moisture level and viscosity of liquid level. At present days all the process parameters in die casting industry are measured manually. Manual measurement leads to error in measurement also time consuming. To overcome this issue non-contact type temperature measurement device is used for die temperature measurement but moisture and viscosity of the die is measured manually. Because die temperature is very sensitive one in die casting process. The proposed system is partially automated with PIC microcontroller and monitoring of the process is done through LabVIEW software.
An Intelligent Approach in Monitoring and Controlling of Bunker Coal Level in Thermal Power Plant
M.Surekha,R.Preethi,S.Kalpanadevi,N. Suthanthira Vanitha 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.4
Currently coal fired power plant requires bunker or stock piles in order to place the coal for storage purpose and to use it effectively when demand arises. Real time sensors are used to sense level of the coal and to pass data to computational systems for processing hence further actions such as refilling and distributing of coal can be automated. Further the control action in level sensing can be enhanced by using fuzzy logic controller which is an intelligent system. Thus the proposed system of coal unit provides the optimum control with increased efficiency. The simulation results are achieved by using LabVIEW.