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The oil level of the power transformer is an important predictor to analyze the working state. The conventional oil level detection method cannot detect the level when the power transformer is working, which is not convenient for the actual application. In this paper, an oil level detection method based on double pressure sensors is proposed to online measure the oil level for power transformer, the basic principle of the proposed oil level detection method is explained and studied, and a prototype is developed to verify the proposed method. The tested results show that the developed prototype can reach high precision for oil level detection of a transformer.

Tooth wear is one of the most common faults in gear transmission systems. However, due to its limited influences on gear dynamics, the condition monitoring of gear wear experiences more challenges. To investigate the relationship between tooth wear and gear dynamics, this study develops an eight-degree of freedom dynamic model which takes into account the gear mesh impact induced by tooth wear. In this model, the gear mesh impact force induced by tooth wear was calculated as an extra input excitation for the gear dynamic model. Besides, a comparative study was carried out to explore the real reason that causes the poor dynamic behaviour due to the wear from two points of view: 1) the reduction in gear mesh stiffness; 2) the increase in gear mesh impact force. The simulation results show that the wear causes a slight reduction in gear mesh stiffness, thus leading to the decrease in the amplitude of gear mesh frequency. This is not consistent with the phenomena observed in the lab experiment which shows the increase in the gear vibrations. The second simulation of impact force demonstrates that the wear causes an increase in the impact force which further leads to the increase in the amplitude of gear mesh frequency. This study investigates the cause for the deterioration in gear dynamics induced by gear wear, which can benefit the early condition monitoring and fault diagnosis of the gear tooth wear.

The transformer is the core equipment in the substation. The lifecycle and health of transformer will directly affect the reliability of substation, but the lifecycle of transformer depends on the oil-paper insulation status. Water, oxygen and temperature are the three factors that affect the performance of oil-paper insulation. The most important factor is the water. This paper designed an intelligent and safe dehydrating device based on the molecular sieve adsorption principle which can realize the on-line drying of transformer.