Superresolution Reconstruction of Electrical Equipment Incipient Fault

Manran Wang,Li Guo,Bingqi Lv,Jinhao Chen,Yang Yang

doi:10.1155/2018/1630402

Abstract

With the rapid development of industry and technology, the electrical power system becomes more complex and the electrical equipment becomes more diverse. Defective equipment is often the cause of industrial accidents and electrical injuries, which can result in serious injuries, such as electrocution, burns, and electrical shocks. In some cases, electrical equipment fault may result in death. However, in some special situation, some fault is very small even invisible, such as equipment aging, holes, and cracks, so the detection of these incipient faults is difficult or even impossible. These potential incipient faults become the biggest hidden danger in the electrical equipment and electricity power system. For these reasons, this paper proposes a superresolution reconstruction method for electrical equipment incipient fault to ensure complete detection in electrical equipment, which aims to guarantee the security of electrical power system operation and industry production. Experimental results show that this method can get a state-of-the-art reconstruction effect of incipient fault, so as to provide reliable fault detection of electrical power system.

Highlights

In the electrical power system, there is no doubt that the safety of electrical equipment is the basis for ensuring the stability and reliability [1]
Huang D et al presented an improved hidden Markov model (HMM) algorithm for fault diagnosis of urban rail transit motors equipment; they used a back-propagation neural network for multiple fault of complex equipment bearings [5, 6]. These methods can only be targeted at minor devices, failing to accurately determine potential incipient fault, which is a limitation in fault detection application
In view of the above situation, this paper proposes a preprocessing method based on superresolution (SR) reconstruction, which can helpfully detect the incipient fault by improving the resolution of the electrical equipment image

Summary

Introduction

In the electrical power system, there is no doubt that the safety of electrical equipment is the basis for ensuring the stability and reliability [1]. Huang D et al presented an improved hidden Markov model (HMM) algorithm for fault diagnosis of urban rail transit motors equipment; they used a back-propagation neural network for multiple fault of complex equipment bearings [5, 6] These methods can only be targeted at minor devices, failing to accurately determine potential incipient fault, which is a limitation in fault detection application. In view of the above situation, this paper proposes a preprocessing method based on superresolution (SR) reconstruction, which can helpfully detect the incipient fault by improving the resolution of the electrical equipment image.

SR Reconstruction Method of Electrical Equipment Incipient Fault

Experiment

Conclusion