The high-rise frame structure has become more and more widespread, like its damage from the complication of the environment. The traditional method of damage detection, which is only suitable for the stationary signal...The high-rise frame structure has become more and more widespread, like its damage from the complication of the environment. The traditional method of damage detection, which is only suitable for the stationary signal, does not apply to a high-rise frame structure because its damage signal is non-stationary. Thus, this paper presents an application of the short-time Fourier transform(STFT) to damage detection of high-rise frame structures. Compared with the fast Fourier transform, STFT is found to be able to express the frequency spectrum property of the time interval using the signal within this interval. Application of STFT to analyzing a Matlab model and the shaking table test with a twelve-story frame-structure model reveals that there is a positive correlation between the slope of the frequency versus time and the damage level. If the slope is equal to or greater than zero, the structure is not damaged. If the slope is smaller than zero, the structure is damaged, and the less the slope is, the more serious the damage is. The damage results from calculation based on the Matlab model are consistent with those from the shaking table test, demonstrating that STFT can be a reliable tool for the damage detection of high-rise frame structures.展开更多
针对射频指纹识别中单一特征无法全面表示信号的完整性,且类间特征差异较小从而限制识别准确率等问题,提出了一种基于时频和双谱特征融合的DA-ResNeXt50(ResNeXt50 with dense connection and ACBlock)射频指纹识别方法。首先,对采集到...针对射频指纹识别中单一特征无法全面表示信号的完整性,且类间特征差异较小从而限制识别准确率等问题,提出了一种基于时频和双谱特征融合的DA-ResNeXt50(ResNeXt50 with dense connection and ACBlock)射频指纹识别方法。首先,对采集到的不同设备的信号分别进行短时傅里叶变换(short-time Fourier transform,STFT)和双谱变换,将得到的图像二值化处理并拼接,综合利用两种变换分别在时频域和高阶统计特性上的优势,更全面地提取和表征不同设备的射频指纹特征;然后,提出了DA-ResNeXt50网络模型,借鉴密集连接思想,使四层残差单元每一层都与前面所有层直接相连,促进了特征的复用和传递,能更好地捕捉类间细微差异;最后,使用非对称卷积模块(asymmetric convolution block,ACBlock)替换模型最后一层残差单元的3×3卷积,可以有效地增加网络的感受野,增强卷积核的骨架部分,从而提高射频指纹识别性能。实验结果表明,相较于使用单一特征提取方法,提出的特征融合方法的性能有较大的提升,改进后的模型与多种经典模型相比,具有较高的识别精度。展开更多
文摘The high-rise frame structure has become more and more widespread, like its damage from the complication of the environment. The traditional method of damage detection, which is only suitable for the stationary signal, does not apply to a high-rise frame structure because its damage signal is non-stationary. Thus, this paper presents an application of the short-time Fourier transform(STFT) to damage detection of high-rise frame structures. Compared with the fast Fourier transform, STFT is found to be able to express the frequency spectrum property of the time interval using the signal within this interval. Application of STFT to analyzing a Matlab model and the shaking table test with a twelve-story frame-structure model reveals that there is a positive correlation between the slope of the frequency versus time and the damage level. If the slope is equal to or greater than zero, the structure is not damaged. If the slope is smaller than zero, the structure is damaged, and the less the slope is, the more serious the damage is. The damage results from calculation based on the Matlab model are consistent with those from the shaking table test, demonstrating that STFT can be a reliable tool for the damage detection of high-rise frame structures.
文摘针对射频指纹识别中单一特征无法全面表示信号的完整性,且类间特征差异较小从而限制识别准确率等问题,提出了一种基于时频和双谱特征融合的DA-ResNeXt50(ResNeXt50 with dense connection and ACBlock)射频指纹识别方法。首先,对采集到的不同设备的信号分别进行短时傅里叶变换(short-time Fourier transform,STFT)和双谱变换,将得到的图像二值化处理并拼接,综合利用两种变换分别在时频域和高阶统计特性上的优势,更全面地提取和表征不同设备的射频指纹特征;然后,提出了DA-ResNeXt50网络模型,借鉴密集连接思想,使四层残差单元每一层都与前面所有层直接相连,促进了特征的复用和传递,能更好地捕捉类间细微差异;最后,使用非对称卷积模块(asymmetric convolution block,ACBlock)替换模型最后一层残差单元的3×3卷积,可以有效地增加网络的感受野,增强卷积核的骨架部分,从而提高射频指纹识别性能。实验结果表明,相较于使用单一特征提取方法,提出的特征融合方法的性能有较大的提升,改进后的模型与多种经典模型相比,具有较高的识别精度。
