Presentation Information
[P02]AE energy analysis method for predictive maintenance of mechanical seals
○MOTOFUMI SHIMIZU1, JIANG YONG1, YOSHIKAZU SUWA1 (1. Sumitomo Heavy Industries Process Equipment Co.,Ltd.)
Keywords:
Acoustic Emission,Condition Monitoring,Mechanical Seal
This study proposes a condition monitoring method using Acoustic Emission (AE) sensors to enhance predictive maintenance in industrial plants. AE waveforms are processed using Short-Time Fourier Transform (STFT) to generate time-series energy data for each frequency band, enabling simultaneous evaluation of friction/contact-related features and vibration-related characteristics. Application to a mechanical seal in an agitator system demonstrated that the proposed method can detect early signs of anomalies earlier than conventional RMS-based indicators. Changes in frequency components allowed identification of damage progression. The method is effective for early fault detection and improved understanding of equipment conditions.