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首页> 外文会议>2013 IEEE 1st International Conference on Condition Assessment Techniques in Electrical Systems >Wavelet transform based error detection in signal acquired from artillery unit
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Wavelet transform based error detection in signal acquired from artillery unit

机译：炮兵信号中基于小波变换的误差检测

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摘要

In real time environment, noise often embeds with the signal during data acquisition process. Error detection will be difficult task when signals are corrupted with noise. Therefore, noise removal is the first step towards the detection of error in signal acquired from artillery unit. In this work, wavelet based signal enhancement technique is proposed to remove the noise from acquired signal. Doubechies wavelet with order 1 is used to decompose the signal up to four levels. Empirically chosen thresholds are applied in each detail coefficient and the denoised signal is reconstructed using the approximation coefficient and threshold detail coefficients. To detect the error, Doubechies wavelet with order 6 is applied to decompose the enhanced signal up to four-level. Each detail coefficient represents the distortion if original signal is erroneous. The proposed method is tested by means of signal to noise ratio, average power and spectrogram analysis. Experimental results show that the performance of the proposed method is consistently well at different SNR both off line testing and online testing, and also able to detect the error properly.
机译：在实时环境中，数据采集过程中经常会在信号中嵌入噪声。当信号被噪声破坏时，错误检测将是一项艰巨的任务。因此，消除噪声是检测从火炮单元获取的信号中的错误的第一步。在这项工作中，提出了基于小波的信号增强技术，以去除采集信号中的噪声。使用阶数为1的Doubechies小波将信号分解为四个电平。根据经验选择的阈值将应用到每个细节系数中，并且使用近似系数和阈值细节系数来重建去噪信号。为了检测误差，应用具有6阶的Doubechies小波将增强的信号分解为四级。如果原始信号错误，则每个细节系数代表失真。通过信噪比，平均功率和频谱图分析测试了该方法。实验结果表明，所提出的方法在离线测试和在线测试中，在不同的信噪比下都具有良好的性能，并且能够正确检测出误差。

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