Insulation Resistance Measurement of Airport Navigational Lighting System Based on Deep Learning and Transfer Learning

Abstract

The insulation resistance value is one of the important indexes for the safe operation of airport navigational lighting system. In this paper, a method based on deep learning and transfer learning is proposed to measure the insulation resistance value. To reduce the influence of high voltage environment and signal injection on the measurement accuracy, a multilayer LSTM model is established, in which the network convergence rate is accelerated by introducing a normalized layer in front of the first LSTM layer. Based on the constructed deep network, transfer learning is employed by sharing the weight parameters of the pretraining model to solve the problem of small data sample. The experimental results demonstrate that the proposed method can effectively improve the measurement accuracy of the insulation resistance value.