In this paper a closed-form approximated expression is proposed for the Intersymbol Interference (ISI) as a function of time valid during the entire stages of the non-blind adaptive deconvolution process and is suitab...In this paper a closed-form approximated expression is proposed for the Intersymbol Interference (ISI) as a function of time valid during the entire stages of the non-blind adaptive deconvolution process and is suitable for the noisy, real and two independent quadrature carrier input case. The obtained expression is applicable for type of channels where the resulting ISI as a function of time can be described with an exponential model having a single time constant. Based on this new expression for the ISI as a function of time, the convergence time (or number of iteration number required for convergence) of the non-blind adaptive equalizer can be calculated. Up to now, the equalizer’s performance (convergence time and ISI as a function of time) could be obtained only via simulation when the channel coefficients were known. The new proposed expression for the ISI as a function of time is based on the knowledge of the initial ISI and channel power (which is measurable) and eliminates the need to carry out any more the above mentioned simulation. Simulation results indicate a high correlation between the simulated and calculated ISI (based on our proposed expression for the ISI as a function of time) during the whole deconvolution process for the high as well as for the low signal to noise ratio (SNR) condition.展开更多
Recently, two expressions (for the noiseless and noisy case) were proposed for the residual inter-symbol interference (ISI) obtained by blind adaptive equalizers, where the error of the equalized output signal may be ...Recently, two expressions (for the noiseless and noisy case) were proposed for the residual inter-symbol interference (ISI) obtained by blind adaptive equalizers, where the error of the equalized output signal may be expressed as a polynomial function of order 3. However, those expressions are not applicable for biased input signals. In this paper, a closed-form approximated expression is proposed for the residual ISI applicable for the noisy and biased input case. This new proposed expression is valid for blind adaptive equalizers, where the error of the equalized output signal may be expressed as a polynomial function of order 3. The new proposed expression depends on the equalizer’s tap length, input signal statistics, channel power, SNR, step-size parameter and on the input signal’s bias. Simulation results indicate a high correlation between the simulated results and those obtained from our new proposed expression.展开更多
The semi-blind deconvolution algorithm improves the separation accuracy by introducing reference information.However,the separation performance depends largely on the construction of reference signals.To improve the r...The semi-blind deconvolution algorithm improves the separation accuracy by introducing reference information.However,the separation performance depends largely on the construction of reference signals.To improve the robustness of the semi-blind deconvolution algorithm to the reference signals and the convergence speed,the reference-based cubic blind deconvolution algorithm is proposed in this paper.The proposed algorithm can be combined with the contribution evaluation to provide trustworthy guidance for suppressing satellite micro-vibration.The normalized reference-based cubic contrast function is proposed and the validity of the new contrast function is theoretically proved.By deriving the optimal step size of gradient iteration under the new contrast function,we propose an efficient adaptive step optimization method.Furthermore,the contribution evaluation method based on vector projection is presented to implement the source contribution evaluation.Numerical simulation analysis is carried out to validate the availability and superiority of this method.Further tests given by the simulated satellite experiment and satellite ground experiment also confirm the effectiveness.The signals of control moment gyroscope and flywheel were extracted,respectively,and the contribution evaluation of vibration sources to the sensitive load area was realized.This research proposes a more accurate and robust algorithm for the source separation and provides an effective tool for the quantitative identification of the mechanical vibration sources.展开更多
A variable step-size parameter is usually used to accelerate the convergence speed of a blind adaptive equalizer with N1 + N2 -1 coefficients where N1 and N2 are odd values. In this paper we show that improved equaliz...A variable step-size parameter is usually used to accelerate the convergence speed of a blind adaptive equalizer with N1 + N2 -1 coefficients where N1 and N2 are odd values. In this paper we show that improved equalization performance is achieved when using two blind adaptive equalizers connected in series where the first and second blind adaptive equalizer have N1 and N2 coefficients respectively compared with the case where a single blind adaptive equalizer is applied with N1 + N2 -1 coefficients. It should be pointed out that the same algorithm (cost function) is used for updating the filter taps for the different equalizers and that a fixed step-size parameter is used. Simulation results show that for the low signal to noise ratio (SNR) environment and for the case where the convergence speed is slow due to the channel characteristics, the new method has a faster convergence speed with a factor of approximately two while leaving the system with approximately the same or lower residual intersymbol interference (ISI).展开更多
In the communication field, during transmission, a source signal undergoes a convolutive distortion between its symbols and the channel impulse response. This distortion is referred to as Intersymbol Interference (ISI...In the communication field, during transmission, a source signal undergoes a convolutive distortion between its symbols and the channel impulse response. This distortion is referred to as Intersymbol Interference (ISI) and can be reduced significantly by applying a blind adaptive deconvolution process (blind adaptive equalizer) on the distorted received symbols. But, since the entire blind deconvolution process is carried out with no training symbols and the channel’s coefficients are obviously unknown to the receiver, no actual indication can be given (via the mean square error (MSE) or ISI expression) during the deconvolution process whether the blind adaptive equalizer succeeded to remove the heavy ISI from the transmitted symbols or not. Up to now, the output of a convolution and deconvolution process was mainly investigated from the ISI point of view. In this paper, the output of a convolution and deconvolution process is inspected from the leading digit point of view. Simulation results indicate that for the 4PAM (Pulse Amplitude Modulation) and 16QAM (Quadrature Amplitude Modulation) input case, the number “1” is the leading digit at the output of a convolution and deconvolution process respectively as long as heavy ISI exists. However, this leading digit does not follow exactly Benford’s Law but follows approximately the leading digit (digit 1) of a Gaussian process for independent identically distributed input symbols and a channel with many coefficients.展开更多
针对设备背景噪声影响机械故障检测的问题,提出一种融合自适应噪声完全集成局部均值分解(Complete Ensemble Local Mean Decomposition with Adaptive Noise,CELMDAN)与改进的多点最优最小熵去卷积调整(Improved Multipoint Optimal Min...针对设备背景噪声影响机械故障检测的问题,提出一种融合自适应噪声完全集成局部均值分解(Complete Ensemble Local Mean Decomposition with Adaptive Noise,CELMDAN)与改进的多点最优最小熵去卷积调整(Improved Multipoint Optimal Minimum Entropy Deconvolution Adjusted,IMOMEDA)的微弱机械特征增强方法。该方法首先利用CELMDAN方法把复杂振动信号分解为多个单模态的乘积函数(Product Functions,PFs),解决了集成局部均值分解(Ensemble Local Mean Decomposition,ELMD)对信号施加噪声幅值和试错次数难以确定的问题。其次,提出一种具有鲁棒性较强、物理意义明确以及尺度不变性的周期调制强度(Periodic Modulation Intensity,PMI),以筛选出有效的PFs。接着,针对所选PFs中的噪声,提出IMOMEDA方法进行消除,该方法通过迭代估计最优模型参数,自适应地提取振动信号中的周期性故障瞬态特征,能够在频域中定位瞬态的谱峭度,从而抽取被背景噪声淹没的微弱故障特征。最后,以煤矿提升机为研究对象,设计了多种振动信号特征增强方法对比实验、机械运行状态诊断性能实验以及信号特征增强算法性能对比实验,多角度验证了本文方法的有效性。展开更多
A convolution model of flaw scattering echoes and an adaptive filtering deconvolution method are presented. The effect of the method is analyzed by simulating a given system. By deconvolution, the influence of the tra...A convolution model of flaw scattering echoes and an adaptive filtering deconvolution method are presented. The effect of the method is analyzed by simulating a given system. By deconvolution, the influence of the transducer on echoes is reduced greatly and the flaw features stand out more clearly in the deconvolved echoes than in flaw echoes themselves. flaw echo signals of 18 flaw samples are processed by adaptive filtering deconvolution. As a result, flaws are classified successfully展开更多
针对旋转矢量(rotary vector, RV)减速器多源耦合严重,行星齿轮局部故障所引起的冲击易被其他干扰分量所淹没,故障特征提取困难的问题,结合编码器信号的优势提出了一种基于自适应最大二阶循环平稳盲解卷积(adaptive maximum second orde...针对旋转矢量(rotary vector, RV)减速器多源耦合严重,行星齿轮局部故障所引起的冲击易被其他干扰分量所淹没,故障特征提取困难的问题,结合编码器信号的优势提出了一种基于自适应最大二阶循环平稳盲解卷积(adaptive maximum second order cyclostationarity blind deconvolution, ACYCBD)的RV减速器行星齿轮局部故障检测方法。首先,拾取伺服电机内置光编码器信号,并利用向前差分计算获得瞬时角速度(instantaneous angular speed, IAS)信号;然后,依据特征评价指标(characteristic evaluation indicator, CEI)最大化原则自适应确定ACYCBD优化滤波器长度,并对IAS信号进行增强;最后,通过识别时域中与故障冲击周期相匹配的理论齿数实现RV减速器故障检测。通过试验数据分析,并将所提方法与现有的稀疏低秩分解算法和增强CYCBD算法对比,验证了所提方法的有效性。展开更多
文摘In this paper a closed-form approximated expression is proposed for the Intersymbol Interference (ISI) as a function of time valid during the entire stages of the non-blind adaptive deconvolution process and is suitable for the noisy, real and two independent quadrature carrier input case. The obtained expression is applicable for type of channels where the resulting ISI as a function of time can be described with an exponential model having a single time constant. Based on this new expression for the ISI as a function of time, the convergence time (or number of iteration number required for convergence) of the non-blind adaptive equalizer can be calculated. Up to now, the equalizer’s performance (convergence time and ISI as a function of time) could be obtained only via simulation when the channel coefficients were known. The new proposed expression for the ISI as a function of time is based on the knowledge of the initial ISI and channel power (which is measurable) and eliminates the need to carry out any more the above mentioned simulation. Simulation results indicate a high correlation between the simulated and calculated ISI (based on our proposed expression for the ISI as a function of time) during the whole deconvolution process for the high as well as for the low signal to noise ratio (SNR) condition.
文摘Recently, two expressions (for the noiseless and noisy case) were proposed for the residual inter-symbol interference (ISI) obtained by blind adaptive equalizers, where the error of the equalized output signal may be expressed as a polynomial function of order 3. However, those expressions are not applicable for biased input signals. In this paper, a closed-form approximated expression is proposed for the residual ISI applicable for the noisy and biased input case. This new proposed expression is valid for blind adaptive equalizers, where the error of the equalized output signal may be expressed as a polynomial function of order 3. The new proposed expression depends on the equalizer’s tap length, input signal statistics, channel power, SNR, step-size parameter and on the input signal’s bias. Simulation results indicate a high correlation between the simulated results and those obtained from our new proposed expression.
基金Supported by National Natural Science Foundation of China(Grant No.51775410)Science Challenge Project of China(Grant No.TZ2018007).
文摘The semi-blind deconvolution algorithm improves the separation accuracy by introducing reference information.However,the separation performance depends largely on the construction of reference signals.To improve the robustness of the semi-blind deconvolution algorithm to the reference signals and the convergence speed,the reference-based cubic blind deconvolution algorithm is proposed in this paper.The proposed algorithm can be combined with the contribution evaluation to provide trustworthy guidance for suppressing satellite micro-vibration.The normalized reference-based cubic contrast function is proposed and the validity of the new contrast function is theoretically proved.By deriving the optimal step size of gradient iteration under the new contrast function,we propose an efficient adaptive step optimization method.Furthermore,the contribution evaluation method based on vector projection is presented to implement the source contribution evaluation.Numerical simulation analysis is carried out to validate the availability and superiority of this method.Further tests given by the simulated satellite experiment and satellite ground experiment also confirm the effectiveness.The signals of control moment gyroscope and flywheel were extracted,respectively,and the contribution evaluation of vibration sources to the sensitive load area was realized.This research proposes a more accurate and robust algorithm for the source separation and provides an effective tool for the quantitative identification of the mechanical vibration sources.
文摘A variable step-size parameter is usually used to accelerate the convergence speed of a blind adaptive equalizer with N1 + N2 -1 coefficients where N1 and N2 are odd values. In this paper we show that improved equalization performance is achieved when using two blind adaptive equalizers connected in series where the first and second blind adaptive equalizer have N1 and N2 coefficients respectively compared with the case where a single blind adaptive equalizer is applied with N1 + N2 -1 coefficients. It should be pointed out that the same algorithm (cost function) is used for updating the filter taps for the different equalizers and that a fixed step-size parameter is used. Simulation results show that for the low signal to noise ratio (SNR) environment and for the case where the convergence speed is slow due to the channel characteristics, the new method has a faster convergence speed with a factor of approximately two while leaving the system with approximately the same or lower residual intersymbol interference (ISI).
文摘In the communication field, during transmission, a source signal undergoes a convolutive distortion between its symbols and the channel impulse response. This distortion is referred to as Intersymbol Interference (ISI) and can be reduced significantly by applying a blind adaptive deconvolution process (blind adaptive equalizer) on the distorted received symbols. But, since the entire blind deconvolution process is carried out with no training symbols and the channel’s coefficients are obviously unknown to the receiver, no actual indication can be given (via the mean square error (MSE) or ISI expression) during the deconvolution process whether the blind adaptive equalizer succeeded to remove the heavy ISI from the transmitted symbols or not. Up to now, the output of a convolution and deconvolution process was mainly investigated from the ISI point of view. In this paper, the output of a convolution and deconvolution process is inspected from the leading digit point of view. Simulation results indicate that for the 4PAM (Pulse Amplitude Modulation) and 16QAM (Quadrature Amplitude Modulation) input case, the number “1” is the leading digit at the output of a convolution and deconvolution process respectively as long as heavy ISI exists. However, this leading digit does not follow exactly Benford’s Law but follows approximately the leading digit (digit 1) of a Gaussian process for independent identically distributed input symbols and a channel with many coefficients.
文摘针对设备背景噪声影响机械故障检测的问题,提出一种融合自适应噪声完全集成局部均值分解(Complete Ensemble Local Mean Decomposition with Adaptive Noise,CELMDAN)与改进的多点最优最小熵去卷积调整(Improved Multipoint Optimal Minimum Entropy Deconvolution Adjusted,IMOMEDA)的微弱机械特征增强方法。该方法首先利用CELMDAN方法把复杂振动信号分解为多个单模态的乘积函数(Product Functions,PFs),解决了集成局部均值分解(Ensemble Local Mean Decomposition,ELMD)对信号施加噪声幅值和试错次数难以确定的问题。其次,提出一种具有鲁棒性较强、物理意义明确以及尺度不变性的周期调制强度(Periodic Modulation Intensity,PMI),以筛选出有效的PFs。接着,针对所选PFs中的噪声,提出IMOMEDA方法进行消除,该方法通过迭代估计最优模型参数,自适应地提取振动信号中的周期性故障瞬态特征,能够在频域中定位瞬态的谱峭度,从而抽取被背景噪声淹没的微弱故障特征。最后,以煤矿提升机为研究对象,设计了多种振动信号特征增强方法对比实验、机械运行状态诊断性能实验以及信号特征增强算法性能对比实验,多角度验证了本文方法的有效性。
文摘A convolution model of flaw scattering echoes and an adaptive filtering deconvolution method are presented. The effect of the method is analyzed by simulating a given system. By deconvolution, the influence of the transducer on echoes is reduced greatly and the flaw features stand out more clearly in the deconvolved echoes than in flaw echoes themselves. flaw echo signals of 18 flaw samples are processed by adaptive filtering deconvolution. As a result, flaws are classified successfully
