Analog instrument pointer monitoring and parameter estimation via line scan vision

Abstract

Analog instruments are widely used in energy engineering. However, an analog instrument is only human-readable because it does not have a built-in digital communication interface. In power system, it is necessary not only to record the final output value but also to monitor the associated dynamic power process. The present paper develops an analog instrument pointer monitoring and parameter estimation system via line scan vision. A line scan camera is used to collect the dynamic process data of the analog instrument. The captured images can be regarded as a discrete temporal sequence. The light-spot centroid method is implemented to extract the initial pointer position. Data normalization is used to process the initial data. By analysing the system step response function, we construct a cost function, and Least-squares identification algorithm is used to estimate the damp and natural frequency. The proposed method monitors the dynamic process of the analog instrument with various inputs, such as sine signals and random signals, thereby enabling condition monitoring. Experimental prediction results show that the proposed estimation method is effective and robust.