| 宋华建,穆瑞林,周子奇.一种基于特征点提取的扬声器异常声检测方法*[J].,2022,41(2):243-249 |
| 一种基于特征点提取的扬声器异常声检测方法* |
| Method for detecting Rub & Buzz of loudspeaker based on feature points |
| 投稿时间：2021-03-12 修订日期：2022-02-27 |
| 中文摘要: |
| 针对短时傅里叶变换在扬声器异常声检测中有效信息提取的随机性问题，提出了特征点法在扬声器异常声检测中的应用。此方法基于扬声器经扫频信号激励所得响应信号的短时傅里叶变换时频图，用改进的尺度不变特征转换(SIFT)算法对合格扬声器与异常声扬声器做特征提取，并将多组特征点经分割剔除后叠加组成特征矩阵模板。以合格扬声器样本提取特征曲线阈值构建检测模型判断扬声器是否存在异常声故障，以不同故障类型扬声器的专有特征点进行故障分类。实验结果表明，此方法可有效提取扬声器异常声特征，故障样本检出率可达97.63%，故障分类精度可达95%。 |
| 英文摘要: |
| Aiming at the randomness of effective information extraction by Short-Time Fourier Transform(STFT) in loudspeakers Rub & Buzz detection. The application of feature points method in loudspeaker Rub & Buzz detection was proposed. This method was based on the time-frequency spectrum which was changed from the sound signal by STFT. And the sound signal was emitted by the loudspeaker which was excited by a sweep signal. Improved Scale-Invariant?Feature?Transform(SIFT) algorithm was used to extract feature points from the time-frequency spectrum of the qualified loudspeakers and Rub & Buzz of loudspeakers. The feature matrix can be obtained with removing the invalid points. The detection model can be constructed with the qualified loudspeakers to test whether the loudspeakers were Rub & Buzz of loudspeaker. And the characteristic points of loudspeakers with different fault types were used for fault classification. The experimental results show that the proposed method can effectively extract the feature of loudspeaker Rub & Buzz. The detection rate of fault samples can reach 97.63 percent. The accuracy of fault classification can reach 95 percent. |
| DOI：10.11684/j.issn.1000-310X.2022.02.009 |
| 中文关键词: 特征点 异常声 时频图 尺度不变特征转换 |
| 英文关键词: feature points Rub & Buzz time-frequency spectrum SIFT |
| 基金项目:天津市建委科技项目（2017-10） |
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