Non-contact monitoring of 3-dimensional vibrations of bodies using a neural network

Abstract

Gas piping systems in power plants and factories are always influenced by the mechanical vibrations of rotational machines such as pumps, blowers, and compressors. Unusual vibrations in a gas piping system influence possible leakages of liquids or gases, which can lead to large explosive accidents. Real-time measurements of unusual vibrations in piping systems in situ prohibit them from being possible leakages owing to the repeated fatigue of vibrations. In this paper, a non-contact 3-dimensional measurement system that can detect the vibrations of a solid body and monitor its vibrational modes is introduced. To detect the displacements of a body, a stereoscopic camera system is used, through which the major vibration types of solid bodies (such as X-axis-major, Y-axis-major, and Z-axis-major vibrations) can be monitored. In order to judge the vibration types, an artificial neural network is used. The measurement system consists of a host computer, stereoscopic camera system (two-camera system, high-speed high-resolution camera), and a measurement target. Through practical application on a flat plate, the measured data from the non-contact measurement system showed good agreement with those from the original vibration mode produced by an accelerator.