Time-Frequency Analysis of Accelerometery Data for Detection and Identification of Faults on a Pneumatic Production Machine*

As pneumatic cylinders are nowadays an integral part of manufacturing machines in a variety of industries, there is a growing demand for development of cost-effective and reliable techniques for detection and identification of faults on these machines. In this paper, we propose a novel algorithm for condition indicator extraction from the time-frequency domain. The algorithm uses signal-based condition indicators extracted from a frequency spectrum obtained by a modified version of the Short-Time Fourier Transform (STFT). The aim of this article is to demonstrate that the processing of readings from an accelerometer by the proposed method provides higher accuracy in detecting and identifying faults. We achieve all this by processing only a fraction of the measured signal. As result of that, the computational requirements are decreasing, leading to lower hardware cost which is advantageous as the proposed method is developed for industrial deployment.