Preventive maintenance of spring applying vibration diagnostic tool- a Malaysian experience
Broad ranges of spring switchgears have been extensively used in most of Malaysian substations. Condition monitoring of hydraulic and spring switchgears have been a critical problem since the conventional methods applied failed to alert prior occurrence of faults. Recent routine reports of TNB Malaysia highlight an occurrence of 20% failures over a period of 5 year. This has lead to greater loss and high expenditure in replacing these switchgears. One of the major contributing factors in failure of hydraulic switchgears is occurrence of mechanical faults, which the conventional method of monitoring failed to detect and locate. However the recent vibration testing prevents and minimizes the breakdowns due to mechanical faults. This current vibration analysis is a noninvasive diagnostic tool applied in comprehensive monitoring of HV switchgears. This method of investigation is well ventured in many countries in Europe and USA but not yet in Malaysia. TNB Malaysia is taking the stepping stone is venturing this technology in line with our objective of seeking predictive maintenance, cost effective and reliable diagnostic tool. This paper will explore in depth the possible mechanical faults that contribute to spring switchgears failures applying vibration analysis. This paper will further interpret the results of vibration testing on 118 spring switchgears 132 kV. This, preliminary study involves interpreting the vibration signal during the event of close and open only to better understand the movement of the mechanical component during operation time enabling us to distinguish which component contributes to the fault of the switchgear.
The Real-Time Monitoring Tool States Based on Cross-Correlation Detection
Monitoring of tool condition is one of the most important techniques to be developed in the automatic cutting processes as it can help to prevent damages of machine tools and work pieces. In this paper, cross-correlation detection is used as a tool, to characterize the real time power signal during cutting. Firstly, we use the Mallat algorithms to get the standard wavelet transform result from the power signal. During the detection period, we get the real time wavelet transform result on certain level through the real time wavelet algorithms. The real time wavelet result was examined by the correlation to its normal result. According to the magnitude of the correlation factors, we can make sure whether the tools work normally. The experiment results show that the method is capable of detecting the cutting condition effectively.
Simulation and control of hybrid renewable energy system connected to the grid
This paper presents a control and simulation of hybrid renewable energy system connected to the grid. The studied system includes a photovoltaic panel, synchronous permanent magnet generator based wind turbine, and a battery for storage energy. The PV array and wind systems are connected to the common DC bus by a boost converter. The battery is connected by a bi-directional DC/DC converter, and then integrated into the AC utility grid via a common DC/AC inverter. In order to extract the maximum energy, a simulation study has been carried out according to the meteorological conditions (wind speed and variable solar irradiance) while maintaining power quality at a satisfactory level. In order to capture the maximum power, a MPPT algorithm is applied for both wind turbine and photovoltaic panel. The modeling and simulation of the whole system has been performed under Matlab/Simulink environment. The obtained results show that the current and the voltage of grid side are sinusoidal and alternative forms, and the power injected to the grid is around the power produced by the hybrid system.