A new partial discharge online detecting equipment based on TEV method is introduced in this paper. Its application to 3~35kV metal-enclosed switchgear partial discharge detection is clarified by an instance. Advice for improvement is also presented.

An on-line monitoring system of vacuum pressure for 35KV vacuum tube is designed in this paper. The operation principle, hardware structure and software plan are explained in details. The system can valuate the internal pressure of the vacuum tube by monitoring the static charge of the shields using electrical field sensors with rotating electrode. At the same time, the data-collecting machine and the controller are developed for long-range and on-line monitoring. The result shows that such system runs steadily and reliably. It can estimate the vacuum degree accurately laying 35cm from the vacuum tube. Besides, it is steady and anti-jamming with less-cost.

In order to assess switchgear insulation status, a novel association rule mining (ARM) algorithm is presented. It is used to recognize the severity of switchgear cabinet partial discharge. The algorithm uses fuzzy C-means clustering (FCM) to divide partial discharge feature interval, candidate sets meeting minimum support and minimum confidence are sought based on an improved Apriori algorithm. Multiple recursions and scans are performed on candidate sets to generate association rules library for classification. Fuzzy reasoning based on association rules are performed over multiple needle corona partial discharge signals sampled in 10KV switchgear cabinets. The results show that partial discharge classification rate using association rules is high and classification conclusions are accurate. It has provided theoretical basis and practical value for insulation status assessment of switchgear cabinets.

In order to study propagation process of partial discharge ultrasonic signal in power transformer, the finite element method is used for simulation modeling and calculation. Ultrasonic waves can be activated by partial discharges (PD) in power transformers. The ultrasonic method is used for evaluating the insulation condition of power transformers by analyzing the partial discharge signals information which is detected by AE sensors. Compared with other diagnostic methods the AE method causes relatively low disturbance, and measuring apparatus is simple and easy to use. This technique is noninvasive and immune to electromagnetic noise. Simulate partial discharge sources of different positions respectively. Achieved results indicate that the space and time distributions of the acoustic pressure depend on the induction position. Furthermore, a greater pressure gradient is observed in domains with higher speed of sound while the signal amplitude decays when it moves away from the PD source.

Various harmonics exist in the electrical power system, and the harmonics include both integer harmonics and non-integer harmonics. It is hard to analyze all the harmonics accurately. In order to improve the precision of harmonic analysis and the minimum resolution, this paper presents a new algorithm named binary scale time windows FFT based on traditional algorithm.This algorithm considers the calculative time and precision well. The results of the test indicate that this algorithm can both guarantee the accuracy and raise the resolving power in the harmonic analysis without increasing the hardware level and the time of calculation obviously. It can restrain the increasingly serious harmonic pollution in power system effectively.