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The existence of harmonic waves may cause some errors during measurement of dielectric loss, thus hindering accurate evaluation of insulation. By taking the influence caused by harmonic waves into consideration, this article introduces an approach which may achieve higher accuracy in the calculation of dielectric loss. Calculation results show that harmonic components and orders of harmonic waves may have big impact on dielectric loss. This article also develops a dielectric loss on-line monitoring system based on bus, which can fulfill tasks including signal conditioning, data acquisition and conversion, upper computer communication and data transmission. This system uses A/D conversion controlled by industrial computer to implement remote communication and synchronous sampling of harmonic waves and is able to able to improve accuracy of dielectric loss under the influence of high order harmonics, therefore, make accurate on-line evaluation of equipment’s insulative conditions.

In recent years, infrared detection technology is widely used in the field of state detection of power equipment. It can timely and effectively find equipment defects and avoid the further development of equipment defects. However, the conventional manual inspection has some problems, such as heavy workload, long time-consuming and low efficiency. Based on the research of infrared image intelligent detection technology of substation equipment based on deep learning algorithm and digital image lossless compression technology, a set of infrared video intelligent diagnosis device of substation equipment based on edge calculation is developed and applied in practice. The device realizes local real-time rapid processing and timely diagnosis of equipment defects, and the accuracy of defect identification is about 94.44%, which greatly improves the safe and stable operation level and power supply reliability of substation equipment.