Adquisición de Señales Acústicas y de Vibración para el Diagnóstico de Fallos en un Compresor Reciprocante de Doble Etapa

This study focused on the acquisition of acoustic and vibration signals for fault diagnosis in a two-stage reciprocating compressor. A comprehensive literature review was conducted on condition monitoring and the most relevant compressor faults. A data acquisition system was set up, and experimental plans were designed to simulate valve and bearing faults. Signals were acquired using accelerometers and capacitive microphones. The results showed that acoustic signals are sensitive to changes in amplitude due to faults, similar to vibration signals. It is concluded that both techniques provide a more complete assessment of the compressor's condition. The study highlights the importance of using artificial intelligence techniques for acoustic signal analysis due to their signal processing capabilities, laying the groundwork for the development of more robust diagnostic systems for reciprocating compressors.