PDF《抗环境音干扰的设备声音故障监测方法①》

? ? 抗环境音干扰的设备声音故障监测方法① 李兰村1,2 ,??廉东本2 ,??毛立爽2

1 (中国科学院大学,?北京?100049)

2 (中国科学院?沈阳计算技术研究所,?沈阳?110168) 通讯作者:?李兰村,?E-mail:?530468294@qq.

com 摘要:?变压器等大型设备在运行过程中发声具有辨识性和平稳性的特点,?但容易受各种环境音的干扰,?针对该问 题,?本文利用声音信号处理、特征提取、模式匹配等技术,?提出了一种抗多种环境音干扰的设备声音故障监测方 案.?首先对在各种环境声音中变压器的正常和故障声音进行采集和预处理,?然后对其提取出 MFCC 特征并降维,?对 变压器正常工作声音特征通过 OPTICS 算法进行训练,?得到一个具有多个分类的标准集,?最后将标准集与包含故障 声音的测试样本进行匹配,?若出现不匹配情况但经人工检验为误报,?则将其归为新的分类.?实验结果表明:?该方法不 仅能很好的识别样本,?也能在新的正常声音出现时通过标准集增强模块来优化标准集,?从而提高识别准确率并降低 误警率. 关键词:?特征提取;

?聚类算法;

?数据降维;

?声音识别;

?故障监测 引用格式:??李兰村,廉东本,毛立爽.抗环境音干扰的设备声音故障监测方法.计算机系统应用,2019,28(6):89C94.?http://www.c-s-a.org.cn/1003- 3254/6930.html Device Sound Fault Monitoring Method of Anti-Environmental Sound Interference LI?Lan-Cun1,2 ,?LIAN?Dong-Ben2 ,?MAO?Li-Shuang2

1 (University?of?Chinese?Academy?of?Sciences,?Beijing?100049,?China)

2 (Shenyang?Institute?of?Computing?Technology,?Chinese?Academy?of?Sciences,?Shenyang?110168,?China) Abstract:?Large?equipment?such?as?transformers?has?the?characteristics?of?identification?and?stability?during?operation,?but it?is?easily?interfered?by?various?environmental?sounds.?To?solve?this?problem,?by?using?sound?signal?processing,?feature extraction,?pattern?matching,?and?other?techniques,?this?study?proposes?a?device?sound?fault?monitoring?scheme?that?is resistant?to?multiple?environmental?sound?disturbances.?First?of?all,?the?normal?and?faulty?sounds?of?transformers?in various?ambient?sounds?are?collected?and?preprocessed.?Then,?MFCC?features?are?extracted?and?dimensionality?is?reduced. Next,?the?normal?working?sound?characteristics?of?the?transformer?are?trained?through?the?OPTICS?algorithm?to?obtain?a standard?set?with?multiple?clusters.?Last,?the?standard?set?is?matched?with?the?test?sample?containing?the?faulty?sound.?If there?is?a?mismatch,?but?the?manual?test?is?a?false?positive,?it?will?be?classified?as?a?new?cluster.?The?experimental?results show?that?the?proposed?method?can?not?only?identify?the?sample?well,?but?also?optimize?the?standard?set?through?the standard?set?enhancement?module?when?the?new?normal?sound?appears,?thus?improving?the?recognition?accuracy?and reducing?the?false?alarm?rate. Key words:?feature?extraction;

?clustering?algorithm;

?data?reduction;

?voice?recognition;

?fault?monitoring ? ? ? 计算机系统应用?ISSN?1003-3254,?CODEN?CSAOBN E-mail:?csa@iscas.ac.cn Computer?Systems?&

?Applications,2019,28(6):89?94?[doi:?10.15888/j.cnki.csa.006930] http://www.c-s-a.org.cn ?中国科学院软件研究所版权所有. Tel:?+86-10-62661041 ①??收稿时间:?2018-12-10;

?修改时间:?2018-12-29;

?采用时间:?2019-01-08;

?csa 在线出版时间:?2019-05-25 System?Construction?系统建设?89 1???引言 变压器等大型设备在运行时的声音具有一定的辨 识性,?目前普遍通过拥有多年设备检修经验的技术人 员对变压器运行声音进行监听,?并判断设备是否正常 运行.?但该方式有两个不足之处,?一是需要技术人员时 刻在设备前监测设备运行声音,?若在恶劣环境条件下 安全难以保障;