Automatic analog meter reading for plant inspection using a deep neural network

Abstract

The high demand for automatic plant inspections by robots has been because a plant has many dangerous locations to cover during daily inspections. In this study, we propose automatically reading an analog meter using a Deep Neural Network (DNN), because reading an analog meter is included in the daily inspections. In particular, we artificially generate training data including shooting noise and apply these data for training the DNN. The learned DNN is robust against readable angles, meter contamination, and meter light reflection, and achieves a reading absolute error within 0.05. Additionally, we verify the effectiveness of the proposed method using cross-validation and accuracy comparison with conventional methods.