Detection of Pneumatic Conveying by Acoustic Emissions

• Main Authors: Liansuo An, Weilong Liu, Yongce Ji, Guoqing Shen, Shiping Zhang
• Format: Article
• Language: English
• Published: MDPI AG 2019-02-01
• Series: Applied Sciences
• Subjects: ensemble empirical mode decomposition algorithm; particle mass flow rate; particle size; pneumatic conveying
• Online Access: https://www.mdpi.com/2076-3417/9/3/501

The acoustic emission (AE) method is used in certain industries for the measurement of pneumatic conveying. Instead of the non-intrusive sensors, the comparison of two different intrusive probes in pneumatic conveying is presented in this work, and the AE signals generated by the flow for different particle flow rates and particle sizes were studied. Comparing the distribution of root mean square (RMS) values indicates that the AE signal acquired by a wire mesh probe was more reliable than that from a T-type probe. Limited intrinsic mode functions (IMFs) were extracted from the raw signals by the ensemble empirical mode decomposition (EEMD) algorithm. The characteristics of these signals were analyzed in both the time and frequency domains, and the energies of different IMFs were used to predict the particle mass flow rates, demonstrating a relative error under 10% achieved by the proposed monitoring system. Additionally, the mean squared error contribution fraction, instead of the energy fraction, can predict the particle size.