The radar echo signal of non-stationary and singular points usually contains false echoes,which affects the recognition and measurement of liquid level echo signal.In order to eliminate false echo interference and imp...The radar echo signal of non-stationary and singular points usually contains false echoes,which affects the recognition and measurement of liquid level echo signal.In order to eliminate false echo interference and improve the recognition and measurement accuracy of the liquid level gauge,a method of echo recognition and correction based on adaptive least mean square(LMS)is proposed.The short-time amplitude function and short-time zero crossing rate function are combined to recognize the echo signal.The weight vector iteration and updating weight coefficients are obtained by LMS method.The echo signal is recognized and the false echo interference is suppressed.The experimental results show that the level echo signal can be accurately recognized by this method,and level measurement accuracy can reach0.47%F.S.Compared with other denoising methods,adaptive LMS can keep the signal singularity characteristics while suppressing the noise.Moreover,it has better robustness.展开更多
In the measurement of liquid level in industrial site environment,noise interference can affect the measurement accuracy.In order to improve the measurement accuracy of liquid level in the viscous state,a nuclear radi...In the measurement of liquid level in industrial site environment,noise interference can affect the measurement accuracy.In order to improve the measurement accuracy of liquid level in the viscous state,a nuclear radiation level measurement system based on the least mean square(LMS)filtering correction method is designed.The system uses STM32F103 as the control core and adopts HART bus HT1200M chip for remote signal transmission and reception.The adaptive LMS algorithm can be used for more accurate filtering,calculating iterative weight vector,updating weighted coefficient,effectively removing system measurement noise and improving the measurement accuracy.The results show that the nuclear radiation level gauge based on normalized LMS can correct the measurement system accuracy in adaptive rules,improve the measurement accuracy to meet the requirements of industrial field environment for liquid level measurement and enhance the industrial automation control degree.展开更多
Adaptive digital self-interference cancellation(ADSIC)is a significant method to suppress self-interference and improve the performance of the linear frequency modulated continuous wave(LFMCW)radar.Due to efficient im...Adaptive digital self-interference cancellation(ADSIC)is a significant method to suppress self-interference and improve the performance of the linear frequency modulated continuous wave(LFMCW)radar.Due to efficient implementation structure,the conventional method based on least mean square(LMS)is widely used,but its performance is not sufficient for LFMCW radar.To achieve a better self-interference cancellation(SIC)result and more optimal radar performance,we present an ADSIC method based on fractional order LMS(FOLMS),which utilizes the multi-path cancellation structure and adaptively updates the weight coefficients of the cancellation system.First,we derive the iterative expression of the weight coefficients by using the fractional order derivative and short-term memory principle.Then,to solve the problem that it is difficult to select the parameters of the proposed method due to the non-stationary characteristics of radar transmitted signals,we construct the performance evaluation model of LFMCW radar,and analyze the relationship between the mean square deviation and the parameters of FOLMS.Finally,the theoretical analysis and simulation results show that the proposed method has a better SIC performance than the conventional methods.展开更多
Perovskite solar cells(PSCs)have undergone a dramatic increase in laboratory-scale effi ciency to more than 25%,which is comparable to Si-based single-junction solar cell effi ciency.However,the effi ciency of PSCs dr...Perovskite solar cells(PSCs)have undergone a dramatic increase in laboratory-scale effi ciency to more than 25%,which is comparable to Si-based single-junction solar cell effi ciency.However,the effi ciency of PSCs drops from laboratory-scale to large-scale perovskite solar modules(PSMs)because of the poor quality of perovskite fi lms,and the increased resistance of large-area PSMs obstructs practical PSC applications.An in-depth understanding of the fabricating processes is vital for precisely controlling the quality of large-area perovskite fi lms,and a suitable structural design for PSMs plays an impor-tant role in minimizing energy loss.In this review,we discuss several solution-based deposition techniques for large-area perovskite fi lms and the eff ects of operating conditions on the fi lms.Furthermore,diff erent structural designs for PSMs are presented,including the processing technologies and device architectures.展开更多
Filter bank multicarrier quadrature amplitude modulation(FBMC-QAM)will encounter inter-ference and noise during the process of channel transmission.In order to suppress the interference in the communication system,cha...Filter bank multicarrier quadrature amplitude modulation(FBMC-QAM)will encounter inter-ference and noise during the process of channel transmission.In order to suppress the interference in the communication system,channel equalization is carried out at the receiver.Given that the con-ventional least mean square(LMS)equilibrium algorithm usually suffer from drawbacks such as the inability to converge quickly in large step sizes and poor stability in small step sizes when searching for optimal weights,in this paper,a design scheme for adaptive equalization with dynamic step size LMS optimization is proposed,which can further improve the convergence and error stability of the algorithm by calling the Sigmoid function and introducing three new parameters to control the range of step size values,adjust the steepness of step size,and reduce steady-state errors in small step sta-ges.Theoretical analysis and simulation results demonstrate that compared with the conventional LMS algorithm and the neural network-based residual deep neural network(Res-DNN)algorithm,the adopted dynamic step size LMS optimization scheme can not only obtain faster convergence speed,but also get smaller error values in the signal recovery process,thereby achieving better bit error rate(BER)performance.展开更多
基金National Natural Science Foundation of China(No.61261029)
文摘The radar echo signal of non-stationary and singular points usually contains false echoes,which affects the recognition and measurement of liquid level echo signal.In order to eliminate false echo interference and improve the recognition and measurement accuracy of the liquid level gauge,a method of echo recognition and correction based on adaptive least mean square(LMS)is proposed.The short-time amplitude function and short-time zero crossing rate function are combined to recognize the echo signal.The weight vector iteration and updating weight coefficients are obtained by LMS method.The echo signal is recognized and the false echo interference is suppressed.The experimental results show that the level echo signal can be accurately recognized by this method,and level measurement accuracy can reach0.47%F.S.Compared with other denoising methods,adaptive LMS can keep the signal singularity characteristics while suppressing the noise.Moreover,it has better robustness.
基金National Natural Science Foundation of China(Nos.61761027,61261029)
文摘In the measurement of liquid level in industrial site environment,noise interference can affect the measurement accuracy.In order to improve the measurement accuracy of liquid level in the viscous state,a nuclear radiation level measurement system based on the least mean square(LMS)filtering correction method is designed.The system uses STM32F103 as the control core and adopts HART bus HT1200M chip for remote signal transmission and reception.The adaptive LMS algorithm can be used for more accurate filtering,calculating iterative weight vector,updating weighted coefficient,effectively removing system measurement noise and improving the measurement accuracy.The results show that the nuclear radiation level gauge based on normalized LMS can correct the measurement system accuracy in adaptive rules,improve the measurement accuracy to meet the requirements of industrial field environment for liquid level measurement and enhance the industrial automation control degree.
文摘Adaptive digital self-interference cancellation(ADSIC)is a significant method to suppress self-interference and improve the performance of the linear frequency modulated continuous wave(LFMCW)radar.Due to efficient implementation structure,the conventional method based on least mean square(LMS)is widely used,but its performance is not sufficient for LFMCW radar.To achieve a better self-interference cancellation(SIC)result and more optimal radar performance,we present an ADSIC method based on fractional order LMS(FOLMS),which utilizes the multi-path cancellation structure and adaptively updates the weight coefficients of the cancellation system.First,we derive the iterative expression of the weight coefficients by using the fractional order derivative and short-term memory principle.Then,to solve the problem that it is difficult to select the parameters of the proposed method due to the non-stationary characteristics of radar transmitted signals,we construct the performance evaluation model of LFMCW radar,and analyze the relationship between the mean square deviation and the parameters of FOLMS.Finally,the theoretical analysis and simulation results show that the proposed method has a better SIC performance than the conventional methods.
基金supported by the National Key Research and Development Program of China(No.2017YFE0127100)the National Natural Science Foundation of China(No.22025505)the Program of Shanghai Academic/Technology Research Leader(No.20XD1422200).
文摘Perovskite solar cells(PSCs)have undergone a dramatic increase in laboratory-scale effi ciency to more than 25%,which is comparable to Si-based single-junction solar cell effi ciency.However,the effi ciency of PSCs drops from laboratory-scale to large-scale perovskite solar modules(PSMs)because of the poor quality of perovskite fi lms,and the increased resistance of large-area PSMs obstructs practical PSC applications.An in-depth understanding of the fabricating processes is vital for precisely controlling the quality of large-area perovskite fi lms,and a suitable structural design for PSMs plays an impor-tant role in minimizing energy loss.In this review,we discuss several solution-based deposition techniques for large-area perovskite fi lms and the eff ects of operating conditions on the fi lms.Furthermore,diff erent structural designs for PSMs are presented,including the processing technologies and device architectures.
基金the National Natural Science Foundation of China(No.61601296,61701295)the Science and Technology Innovation Action Plan Project of Shanghai Science and Technology Commission(No.20511103500)the Talent Program of Shanghai University of Engineering Science(No.2018RC43).
文摘Filter bank multicarrier quadrature amplitude modulation(FBMC-QAM)will encounter inter-ference and noise during the process of channel transmission.In order to suppress the interference in the communication system,channel equalization is carried out at the receiver.Given that the con-ventional least mean square(LMS)equilibrium algorithm usually suffer from drawbacks such as the inability to converge quickly in large step sizes and poor stability in small step sizes when searching for optimal weights,in this paper,a design scheme for adaptive equalization with dynamic step size LMS optimization is proposed,which can further improve the convergence and error stability of the algorithm by calling the Sigmoid function and introducing three new parameters to control the range of step size values,adjust the steepness of step size,and reduce steady-state errors in small step sta-ges.Theoretical analysis and simulation results demonstrate that compared with the conventional LMS algorithm and the neural network-based residual deep neural network(Res-DNN)algorithm,the adopted dynamic step size LMS optimization scheme can not only obtain faster convergence speed,but also get smaller error values in the signal recovery process,thereby achieving better bit error rate(BER)performance.
