Research of signal recognition of distributed optical fiber vibration sensors
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摘要: 为了能够更好地识别入侵振动信号,通过研究分布式光纤振动传感器及振动信号的识别技术,根据振动信号的特点,借鉴语音信号的处理方法,对比原有基于快速傅里叶变换频谱分析算法,引入了基于Mel频率倒谱系数的识别算法。新算法从频域的角度对振动信号进行分析,提取不同环境状态下的Mel频率倒谱系数,并将其作为新的特征参量。通过实验对比分析两种算法,两者的误报率分别为27.5%和7.5%。结果表明,基于Mel频率倒谱系数的算法相比基于快速傅里叶变换的频谱分析算法,在误报率上可以降低20%甚至更多,在不漏报的前提下,显然误报率更低的基于Mel频率倒谱系数的算法更加适用于安防体系。
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关键词:
- 传感器技术 /
- 分布式光纤振动传感器 /
- 振动信号 /
- 快速傅里叶变换 /
- Mel频率倒谱系数
Abstract: In order to identify the invasion of vibration signal, a recognition algorithm based on Mel frequency cepstral coefficients (MFCC) was introduced according to the feature of vibration signal, taking processing method of voice signal as a reference and comparing with original spectrum analysis algorithm based on fast Fourier transform (FFT) after the investigation of distributed optical fiber vibration sensor and vibration signal recognition technology.。In the new algorithm, the vibration signal was analyzed in frequency domain. MFCC under different conditions was extracted and was taken as a new characteristic parameter. After comparing the experimental results, false alarm rates of both the algorithms are 27.5% and 7.5% respectively. The results show that false alarm rate of the algorithm based on MFCC can be reduced by 20% or more compared with the algorithm based on FFT. Obviously, under the premise of not omitting, MFCC algorithm with lower false alarm rate is more suitable for security systems. -
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