Agglomeration Feature Extraction from Voiceprint of Fluidized Bed by PCA and MFCC

Abstract:

Agglomeration reduces the productivity and the quality of polyethylene fluidized bed. The mathematical model cant characterize the nonlinearity of two-phase flow in the fluidized bed exactly, which make state monitoring and failure diagnosis to inner state of fluidized bed lacking assessment criterion. Acoustic emission sensor could monitor the signals from polyethylene granules impacting on the wall of fluidized beds. Use wavelet packet analysis to process the acoustic emission signals and extract voiceprint feature by MFCC. The feature vector is combined with the MFCC of all sensors. Reduce the dimensionality of vector by PCA and test the feature vector by BP neural network.

• Periodical: Advanced Materials Research (Volumes 850-851)
• Pages: 851-855
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.850-851.851
• Online since: December 2013
• Authors: Lei Chen*, Wei Guo Lin, Zhong Zhao, Hao Tong Hou
• Keywords: Fluidized Bed, MFCC, PCA, Voiceprint Feature, Wavelet Packet Analysis

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