Underwater acoustic signal processing is one of the research hotspots in underwater acoustics.Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing.Owing to the complexity ...Underwater acoustic signal processing is one of the research hotspots in underwater acoustics.Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing.Owing to the complexity of marine environment and the particularity of underwater acoustic channel,noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing.In order to solve the dilemma,we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),minimum mean square variance criterion(MMSVC) and least mean square adaptive filter(LMSAF).This noise reduction technique,named CEEMDAN-MMSVC-LMSAF,has three main advantages:(i) as an improved algorithm of empirical mode decomposition(EMD) and ensemble EMD(EEMD),CEEMDAN can better suppress mode mixing,and can avoid selecting the number of decomposition in variational mode decomposition(VMD);(ii) MMSVC can identify noisy intrinsic mode function(IMF),and can avoid selecting thresholds of different permutation entropies;(iii) for noise reduction of noisy IMFs,LMSAF overcomes the selection of deco mposition number and basis function for wavelet noise reduction.Firstly,CEEMDAN decomposes the original signal into IMFs,which can be divided into noisy IMFs and real IMFs.Then,MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs.Finally,both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained.Compared with other noise reduction techniques,the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals,which has the better noise reduction effect and has practical application value.CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection,feature extraction,classification and recognition of underwater acoustic signals.展开更多
针对复杂电子系统产生的传导EMI噪声,该文分别利用电偶极子模型、电路分析方法和散射参数方法提出了3种传导EMI噪声理论模型及其等效电路,包括因串扰引起的传导噪声模型,因接地不良引起的传导噪声模型,以及因PCB线缆阻抗失配引起的传导...针对复杂电子系统产生的传导EMI噪声,该文分别利用电偶极子模型、电路分析方法和散射参数方法提出了3种传导EMI噪声理论模型及其等效电路,包括因串扰引起的传导噪声模型,因接地不良引起的传导噪声模型,以及因PCB线缆阻抗失配引起的传导噪声模型。同时,还设计了一种串扰扼流圈以有效抑制因串扰引起的传导EMI噪声。实验结果表明,采用文中方法,某型商用车载导航和刷卡器能够通过GB 9254标准测试,噪声抑制效果分别可达44.8和29.28 dB V,从而验证了方法的有效性。展开更多
The experiment presented in this paper is to investigate and analyze the noise reduction at low frequency using stiff light composite panels. Since these composite panels are made of lightweight and stiff materials, t...The experiment presented in this paper is to investigate and analyze the noise reduction at low frequency using stiff light composite panels. Since these composite panels are made of lightweight and stiff materials, this actuation strategy will enable the creation of composite panels for duct noise control without using traditional heavy structural mass. The results suggest that the mass-spring resonance absorption in the case of a comparatively stiff thick panel with a thin flexible plate is more efficient with minimum weight, when subjected to low-frequency (<500 Hz). The efficiency of the panel absorber depends on the mass of the thin flexible plate and the stiffness of the panel.展开更多
Statistical energy analysis (SEA) is an effective method for predicting high frequency vibro-acoustic performance of automobiles. A full vehicle SEA model is presented for interior noise reduction. It is composed of a...Statistical energy analysis (SEA) is an effective method for predicting high frequency vibro-acoustic performance of automobiles. A full vehicle SEA model is presented for interior noise reduction. It is composed of a number of subsystems based on a 3D model with all parameters for each subsystem. The excitation inputs are measured through road tests in different conditions,including inputs from the engine vibration and the sound pressure of the engine bay. The accuracy in high frequency of SEA model is validated,by comparing the analysis results with the testing pressure level data at driver's right ear. Noise contribution and sensitivity of key subsystems are analyzed. Finally,the effectiveness of noise reduction is verified. Based on the SEA model,an approach combining test and simulation is proposed for the noise vibration and harshness (NVH) design in vehicle development. It contains building the SEA model,testing for subsystem parameter identification,validating the simulation model,identifying subsystem power inputs,analyzing the design sensitivity. An example is given to demonstrate the interior noise reduction in high frequency.展开更多
To enhance the speech quality that is degraded by environmental noise,an algorithm was proposed to reduce the noise and reinforce the speech.The minima controlled recursive averaging(MCRA) algorithm was used to estima...To enhance the speech quality that is degraded by environmental noise,an algorithm was proposed to reduce the noise and reinforce the speech.The minima controlled recursive averaging(MCRA) algorithm was used to estimate the noise spectrum and the partial masking effect which is one of the psychoacoustic properties was introduced to reinforce speech.The performance evaluation was performed by comparing the PESQ(perceptual evaluation of speech quality) and segSNR(segmental signal to noise ratio) by the proposed algorithm with the conventional algorithm.As a result,average PESQ by the proposed algorithm was higher than the average PESQ by the conventional noise reduction algorithm and segSNR was higher as much as 3.2 dB in average than that of the noise reduction algorithm.展开更多
The satellite transponder is a widely used module in satellite missions, and the most concerned issue is to reduce the noise of the transferred signal. Otherwise, the telemetry signal will be polluted by the noise con...The satellite transponder is a widely used module in satellite missions, and the most concerned issue is to reduce the noise of the transferred signal. Otherwise, the telemetry signal will be polluted by the noise contained in the transferred signal, and the additional power will be consumed. Therefore, a method based on wavelet packet de-noising （WPD） is introduced. Compared with other techniques, there are two features making WPD more suit- able to be applied to satellite transponders： one is the capability to deal with time-varying signals without any priori information of the input signals; the other is the capability to reduce the noise in band, even if the noise overlaps with signals in the frequency domain, which provides a great de-noising performance especially for wideband signals. Besides, an oscillation detector and an av- eraging filter are added to decrease the partial oscillation caused by the thresholding process of WPD. Simulation results show that the proposed algorithm can reduce more noises and make less distortions of the signals than other techniques. In addition, up to 12 dB additional power consumption can be reduced at -10 dB signal-to-noise ratio （SNR）.展开更多
针对齿轮故障诊断中采集到的振动信号常伴有噪声干扰且故障特征难以提取的问题,以傅里叶-贝塞尔级数展开(Fourier-Bessel series expansion,FBSE)为基础,提出了一种将FBSE和基于能量的尺度空间经验小波变换(energy scale space empirica...针对齿轮故障诊断中采集到的振动信号常伴有噪声干扰且故障特征难以提取的问题,以傅里叶-贝塞尔级数展开(Fourier-Bessel series expansion,FBSE)为基础,提出了一种将FBSE和基于能量的尺度空间经验小波变换(energy scale space empirical wavelet transform,ESEWT)相结合的齿轮振动信号降噪方法,即FBSE-ESEWT。首先,将采集到的齿轮振动信号利用FBSE技术获得其频谱,以替代传统的傅里叶谱,接着凭借能量尺度空间划分法对获取的FBSE频谱进行自适应分割和筛选,以精确定位有效频带的边界点。随后通过构建小波滤波器组得到信号分量并进行重构,以减小噪声和冗余信息干扰;然后,为捕捉到更全面的特征信息将处理后的信号进行广义S变换得到时频图,输入2D卷积神经网络进行故障诊断验证算法可行性。通过对Simulink仿真信号和实际采集信号进行实验,结果表明,相对于原始经验小波变换(EWT)、经验模态分解(EMD)等方法,FBSE-ESEWT具有更好的降噪效果,信噪比提高了13.96 dB,诊断准确率高达98.03%。展开更多
基金The authors gratefully acknowledge the support of the National Natural Science Foundation of China(No.11574250).
文摘Underwater acoustic signal processing is one of the research hotspots in underwater acoustics.Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing.Owing to the complexity of marine environment and the particularity of underwater acoustic channel,noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing.In order to solve the dilemma,we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),minimum mean square variance criterion(MMSVC) and least mean square adaptive filter(LMSAF).This noise reduction technique,named CEEMDAN-MMSVC-LMSAF,has three main advantages:(i) as an improved algorithm of empirical mode decomposition(EMD) and ensemble EMD(EEMD),CEEMDAN can better suppress mode mixing,and can avoid selecting the number of decomposition in variational mode decomposition(VMD);(ii) MMSVC can identify noisy intrinsic mode function(IMF),and can avoid selecting thresholds of different permutation entropies;(iii) for noise reduction of noisy IMFs,LMSAF overcomes the selection of deco mposition number and basis function for wavelet noise reduction.Firstly,CEEMDAN decomposes the original signal into IMFs,which can be divided into noisy IMFs and real IMFs.Then,MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs.Finally,both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained.Compared with other noise reduction techniques,the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals,which has the better noise reduction effect and has practical application value.CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection,feature extraction,classification and recognition of underwater acoustic signals.
文摘针对复杂电子系统产生的传导EMI噪声,该文分别利用电偶极子模型、电路分析方法和散射参数方法提出了3种传导EMI噪声理论模型及其等效电路,包括因串扰引起的传导噪声模型,因接地不良引起的传导噪声模型,以及因PCB线缆阻抗失配引起的传导噪声模型。同时,还设计了一种串扰扼流圈以有效抑制因串扰引起的传导EMI噪声。实验结果表明,采用文中方法,某型商用车载导航和刷卡器能够通过GB 9254标准测试,噪声抑制效果分别可达44.8和29.28 dB V,从而验证了方法的有效性。
文摘The experiment presented in this paper is to investigate and analyze the noise reduction at low frequency using stiff light composite panels. Since these composite panels are made of lightweight and stiff materials, this actuation strategy will enable the creation of composite panels for duct noise control without using traditional heavy structural mass. The results suggest that the mass-spring resonance absorption in the case of a comparatively stiff thick panel with a thin flexible plate is more efficient with minimum weight, when subjected to low-frequency (<500 Hz). The efficiency of the panel absorber depends on the mass of the thin flexible plate and the stiffness of the panel.
基金Sponsored by the Key Project of the Development of Science and Technology of Jilin Province (20040332-1)the National"863"Project(2006AA110102-3)
文摘Statistical energy analysis (SEA) is an effective method for predicting high frequency vibro-acoustic performance of automobiles. A full vehicle SEA model is presented for interior noise reduction. It is composed of a number of subsystems based on a 3D model with all parameters for each subsystem. The excitation inputs are measured through road tests in different conditions,including inputs from the engine vibration and the sound pressure of the engine bay. The accuracy in high frequency of SEA model is validated,by comparing the analysis results with the testing pressure level data at driver's right ear. Noise contribution and sensitivity of key subsystems are analyzed. Finally,the effectiveness of noise reduction is verified. Based on the SEA model,an approach combining test and simulation is proposed for the noise vibration and harshness (NVH) design in vehicle development. It contains building the SEA model,testing for subsystem parameter identification,validating the simulation model,identifying subsystem power inputs,analyzing the design sensitivity. An example is given to demonstrate the interior noise reduction in high frequency.
文摘To enhance the speech quality that is degraded by environmental noise,an algorithm was proposed to reduce the noise and reinforce the speech.The minima controlled recursive averaging(MCRA) algorithm was used to estimate the noise spectrum and the partial masking effect which is one of the psychoacoustic properties was introduced to reinforce speech.The performance evaluation was performed by comparing the PESQ(perceptual evaluation of speech quality) and segSNR(segmental signal to noise ratio) by the proposed algorithm with the conventional algorithm.As a result,average PESQ by the proposed algorithm was higher than the average PESQ by the conventional noise reduction algorithm and segSNR was higher as much as 3.2 dB in average than that of the noise reduction algorithm.
基金supported by the National Natural Science Foundation of China(61401389)
文摘The satellite transponder is a widely used module in satellite missions, and the most concerned issue is to reduce the noise of the transferred signal. Otherwise, the telemetry signal will be polluted by the noise contained in the transferred signal, and the additional power will be consumed. Therefore, a method based on wavelet packet de-noising （WPD） is introduced. Compared with other techniques, there are two features making WPD more suit- able to be applied to satellite transponders： one is the capability to deal with time-varying signals without any priori information of the input signals; the other is the capability to reduce the noise in band, even if the noise overlaps with signals in the frequency domain, which provides a great de-noising performance especially for wideband signals. Besides, an oscillation detector and an av- eraging filter are added to decrease the partial oscillation caused by the thresholding process of WPD. Simulation results show that the proposed algorithm can reduce more noises and make less distortions of the signals than other techniques. In addition, up to 12 dB additional power consumption can be reduced at -10 dB signal-to-noise ratio （SNR）.
文摘针对齿轮故障诊断中采集到的振动信号常伴有噪声干扰且故障特征难以提取的问题,以傅里叶-贝塞尔级数展开(Fourier-Bessel series expansion,FBSE)为基础,提出了一种将FBSE和基于能量的尺度空间经验小波变换(energy scale space empirical wavelet transform,ESEWT)相结合的齿轮振动信号降噪方法,即FBSE-ESEWT。首先,将采集到的齿轮振动信号利用FBSE技术获得其频谱,以替代传统的傅里叶谱,接着凭借能量尺度空间划分法对获取的FBSE频谱进行自适应分割和筛选,以精确定位有效频带的边界点。随后通过构建小波滤波器组得到信号分量并进行重构,以减小噪声和冗余信息干扰;然后,为捕捉到更全面的特征信息将处理后的信号进行广义S变换得到时频图,输入2D卷积神经网络进行故障诊断验证算法可行性。通过对Simulink仿真信号和实际采集信号进行实验,结果表明,相对于原始经验小波变换(EWT)、经验模态分解(EMD)等方法,FBSE-ESEWT具有更好的降噪效果,信噪比提高了13.96 dB,诊断准确率高达98.03%。
