Application of Deep Learning In The Diagnosis of Faulty Electrical Equipment

Electricity is closely related to human life, to say the least, in modern society, countries and cities without electricity can be paralyzed. National defense, transportation, daily life and so on are inseparable from electricity. Electrical energy is the most basic energy in modern society, and people are almost always in the moment. Electric cookers for cooking need electricity, refrigerators, TVS, air conditioners, computers and fans need electricity, as well as electric lights that give us light in the dark night. Therefore, a power failure in daily life is just like the sky falling down, which is extremely painful. Adults can’t see the news; the elderly can’t use high-tech to cook the rice; even children can’t play the computer. Electricity is an indispensable electrical appliance in people’s daily life and work. Once faulty electrical equipment is not diagnosed and resolved effectively, it will seriously affect people’s normal life and work. So it is very important to do a good job in the diagnosis of faulty electrical equipment. The image retrieval method based on deep learning is an effective fault diagnosis technology. Based on this, the relevant electrical fault diagnosis department should deeply explore the effective application methods of deep learning in the diagnosis of faulty electrical equipment, so as to give full play to the value of image retrieval and improve the diagnosis of faulty electrical equipment.