首页> 外文期刊>Archives of Metallurgy and Materials >DIAGNOSTICS OF DC MACHINE BASED ON ANALYSIS OF ACOUSTIC SIGNALS WITH APPLICATION OF MFCC AND CLASSIFIER BASED ON WORDS
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DIAGNOSTICS OF DC MACHINE BASED ON ANALYSIS OF ACOUSTIC SIGNALS WITH APPLICATION OF MFCC AND CLASSIFIER BASED ON WORDS

机译:基于MFCC的声信号分析的直流电机诊断和基于词的分类器。

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Technical diagnostics is concerned with the assessment of technical conditions of the machine through the study of properties of machine processes. Diagnostics is particularly important for factories and ironworks. In paper is presented method of diagnostics of imminent failure conditions of DC machine. This method is based on a study of acoustic signals generated by DC machine. System of sound recognition uses algorithms for data processing, such as Mel Frequency Cepstral Coefficient and classifier based on words. Software to recognize the sounds of DC machine was implemented on PC computer. Studies were carried out for sounds of faultless machine and machine with shorted coils. The results confirm that the system can be useful for diagnostics of dc and ac machines used in metallurgy.
机译:技术诊断涉及通过研究机器过程的特性来评估机器的技术条件。诊断对于工厂和炼铁厂尤其重要。本文提出了一种直流电机即将发生故障的诊断方法。该方法基于对直流电机产生的声信号的研究。声音识别系统使用算法​​进行数据处理,例如梅尔频率倒谱系数和基于单词的分类器。在PC机上实现了识别DC机器声音的软件。对无故障机器和线圈短路机器的声音进行了研究。结果证实该系统可用于诊断冶金中使用的直流和交流电机。

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