Combustion Sound Classification Employing Gaussian Mixture Models

被引：0

作者：

Lupu, E. ^{[1
]}

Ghiurcau, M. V. ^{[1
]}

Hodor, V. ^{[1
]}

Emerich, S. ^{[1
]}

机构：

[1] Tech Univ Cluj Napoca, Cluj Napoca, Romania

来源：

PROCEEDINGS OF 2010 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION, QUALITY AND TESTING, ROBOTICS (AQTR 2010), VOLS. 1-3 | 2010年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a method suitable for the detection of various states of combustion in progress by means of sound analogy analysis. Visual inspection, electro-chemical transducers or analyzing the sound produced during the burning process consist of means by which the quality of the burning process can be assessed. The results may be used when taking decisions with the goal of optimally controlling the combustion process. Classification was performed by using the GMM (Gaussian Mixture Models), the parameters extracted from the recorded sound being the phase parameters and the MFCC (Mel-frequency cepstral coefficients) coefficients. The results prove to be promising and encourage future research in the acoustic relevance in burning quality detection.

引用

页数：4

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