Signal Processing Method for Coriolis Mass Flowmeter Based on Lattice Notch Filter and DTFT

A novel signal processing method for Coriolis mass flowmeter is proposed based on time-varying signal model. First, an adaptive lattice notch filter is applied to filter the output signal, whose frequency, amplitude and phase are time-varying based on the random walk model, of Coriolis mass flowmeter to get its frequency and enhanced signal. Then, by short window intercepting, the DTFT algorithm with negative frequency contribution is introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference, the time interval between two signals is calculated. Simulation results show that the proposed method is efficient. Furthermore, the computation of algorithms is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.     

Frequency tracking method and simulation for coriolismass flowmter based on a new adaptive notch filter

In order to improve the long-playing frequency tracking ability in the signal processing for coriolis mass flowmeter (CMF) , a new IIR adaptive notch filter (ANF) is developed via steiglitz-mcBride method (SMM) and applied to filter the sensor output signal whose frequency, amplitude and phase are time-varying following the random walk model. The proposed method can detect the signal frequency fleetly and track the frequency variations continuously. The tracking performances of the proposed method and the adaptive lattice notch filter (LANF) method are investigated with computer simulations. Simulations demonstrate the superiority of the proposed method and show it has advantages of fast convergence rate, insensitivity to initial phase variations, and higher long-playing tracking stability and accuracy than LANF method.     

EEG Signal Denoising Based on Wavelet Transform

The article focuses on the method of noise cancellation for EEG signal. The method of notch filter is discussed. According to the frequency of noise and the principle of notch filter, the design result of the notch filter and the denoised signal are presented. Then, the analysis of EEG signal are proposed based on wavelet transform (WT) and noise cancellation using WT. Wavelet transform is a multi-resolution time-frequency analysis method. It can decompose mixed signal into signals at different frequency bands. The EEG signal is analyzed and denoised using WT, then the results are presented respectively. Comparing the experiment results shows that WT can detect and process noise in the EEG signal effectively.     

The application research on improvement of constant sinusoidal signal sampling precision based on adaptive filter

A novel scheme is present to improve the conversion accuracy of ADC. The proposed approach uses adaptive sinusoidal filter. For the measurement of the signal with given frequency, the automatic adjustment of filter coefficients is based on least mean-square error rule, which is a mathematical tool can be employed to make filter output signal achieve the best approximation to the needed one. Then based on the result, it is able to get the amplitude and phase of the measured signal accurately. MATLAB software is used to verify the effectiveness of the algorithm. It proves that adaptive filter has improved the accuracy and signal-to-noise ratio of ADC, which is equal to increase the conversion digits.     

Flowmeter Based Virtual Instrument

The flowmeter based virtual instrument is a new test instrument, which has more advantages than the traditional flowmeter. This flowmeter is based on Qin's model. Apply to the flowrate measurement realm the virtual instrument technique. The design method has been introduced from hardware, software and panel, modelize the different flowrate measure way, with the virtual instrument's figural calculation and show to replace the traditional flowrate measurement, realize multi-threading long-distance flowrate measure easily.     

The Application of Narrowband Interference Suppression in Direct Sequence Spread Spectrum

In order to improve the system effect, it is necessary take the technique of digital signal process to suppress interference, because of the finite gain and the narrow-band interference in system of direct sequence spread spectrum. The authors design a new filter structure improving on tunable digital heterodyne adaptive notch filters. This filter can adaptively track the interference frequency and control the bandwidth and depth of notch, which has the excellent agility and utility. The experiment proves this method overcomes limitation of other interference suppressions, hardly weaken the system performances, enhances the stability of the filter system, and can quickly track the interference frequency.     

汽车转弯自动照明控制系统数据采集滤波方法

为了减少汽车转弯自动照明控制系统数据滤波处理中的延时,在滑动中值滤波方法基础上,提出了一种带补偿的限幅滑动中值滤波算法,通过补偿的方式跟随信号的变化趋势。该算法通过2个步骤完成滤波,先对数据进行带补偿方式的限幅处理,再进行滑动中值滤波处理。该算法综合了滑动中值滤波法的实时性以及限幅滤波法对偶然性干扰滤除的有效性,实现更准确的滤波。仿真与实测结果表明,与滑动中值滤波方法相比较,改进后的算法滤波能够实时地滤除数据中的干扰,处理时间可减少62%,滤波效果较好,且速度信号的数据滞后时间较短,实时性较高,满足系统设计要求。     

Filtering Construct of Adaptive Filter Grou Pwith Multi-scale Decomposition

The principle and method of the adaptive filter and the filtering with wavelet transform were analyzed, and the model and method of adaptive filtering with wavelet transforms for the transient signal was established. The separated noise of signal by the multi-scale decomposition of wavelet transforms, was the input signal of adaptive filter, and accordingly the optimal filtering method of signal-noise decomposition was realized. By the adaptive filter grou Pbased on the wavelet transform, the optimal filtering to the multi-noise of signal is achieved at the same time, and the method presented in this paper has the excellent filtering capability. Examples of application demonstrate that this method presented is excellent to realize the optimal estimate to the valuable signal and noise of the transient signal in the same frequency segment.     

Application of digital phase-locked loop and filtering technique in PWM rectifier

VHS-ADC high speed digital signal processing platform based on MATLAB and FPGA could be used to build three-phase voltage source rectifier with space voltage vector PWM(SVPWM).The initial phase of coordinate transformation from three phase static coordinate to two phase static coordinate which is called Park transformation and from two phase rotating reference frame to two phase static coordinate is uncertain. There existed noise in acquiring grid voltage and current. Digital phase-locked loop is added to follow the frequency and phase of grid voltage, FIR filter is added to process signal and reduce the interference. External voltage control loop, internal current control loop and the model of coordinate transformation are designed on the VHS-ADC platform. The small power experiment is conducted to verify the stability and feasibility of the control system. The experimental results show that the digital phase-locked loop and FIR digital filter can be applied to three-phase voltage source rectifier.     

Real time monitoring for multivariate statistical process with on line multiscale filtering

By analyzing shortages of current MSPCA model, an on line multi variable statistical process monitoring method is proposed, which uses some concepts from online multi scale filtering and can be applied to sensor fault diagnosis. In the method, wavelet decomposition is employed to the signals using edge correction filter in a fixed length data window, and then wavelet denoising is conducted with wavelet threshold filtering. Next, an on line multi scale model is constructed for data combining wavelet transformation and adaptive PCA in the previous data window. This model avoids time waste in direct signal denoising and reduces time cost in multi scale data with conventional PCA, which eventually increases accuracy in fault diagnosis. Experiments on eight vibration signals of 6135D diesel engine under severe leak condition prove the practicability and feasibility of the proposed method.     

Direction of Arrival Estimation for CDMA Communication Signal

MUSIC algorithm is often applied in direction of arrival estimation of communication signal or radar signal. But the traditional MUSIC algorithm is not applicable in the presence of the correlational signals. Combining with time average processing, an algotithm of two-dimensional space-time average is suggested on the base of space average technic especially for the DOA estimation of CDMA communication signal. A detaild analysis and a conclusion about this improved algorithm is presented. Ensuring the accurary of the estimation an efficient decrease in quantity of operation is achieved with the algorithm, so it is more suitable for real-time processing. The efficiency of the improved algorithm is attested by the emulating results.     

Independent component analysis and its application in estimating VEP

Original signals can be effectively estimated from their linear mixed signals by independent component analysis (ICA), even though their frequency components are overlapped, which provides a way to estimate the faint electrophysiological signals. And many researchers who study biomedical signal processing have paid great attention to the technique. We discuss the ICA model and the implement of a fixed-point fast ICA algorithm based on negentropy criterion. With the algorithm, we availably pick up the simulated visual evoked potential (VEP) from the mixing signals.     

A blind adaptive reduced-rank receiver for ultra-wideband communication systems

A low-complexity blind adaptive receiver for ultra-wideband (UWB) systems in the presence of both multiple access interference (MAI) and inter symbol interference (ISI) is proposed, which is composed of two stages. In the first stage, a reduced-rank algorithm based on the multi-stage Wiener filter (MSWF) is considered to suppress the MAI and extract multi-path components. Channel estimation using the projection approximation subspace tracking with deflation (PASTd) algorithm and multi-path combining are then performed to further enhance the signal to interference plus noise ratio (SINR) of the desired user in the second stage. The simulation results show that the proposed receiver exhibits reasonably good bit error ratio (BER) performance compared with those of matched filter, conventional Rake receiver, decorrelating Rake receiver and adaptive receiver based on constant modulus algorithm (CMA). Moreover, it has faster convergence speed and less complexity.     

State of charge estimation of lithium iron phosphate batteriesbased on adaptive Kalman filters

The Kalman filter algorithm can be used to estimate the state of charge (SOC) of power batteries, however, it easily causes divergence due to uncertain of system noise and its estimation performance is affected by model. An adaptive Kalman filter algorithm is adopted to dynamically estimate SOC of lithium iron phosphate batteries for application in electric vehicles. At first, an equivalent circuit model, appropriate for SOC estimation is built after studying battery models. Then some charging and discharging experiments are carried out for parameter identification and the results are verified. At last, the adaptive Kalman filter algorithm is used on this model for on-line SOC estimation under unknown interfering noise. Simulation results show that adaptive Kalman filter method can correct SOC estimation error caused by tiny model error online, and the estimate accuracy is higher than Kalman filter method. Adaptive Kalman filter algorithm can also correct the initial error. Full-cycle test in electric vehicles proves that the algorithm is appropriate for SOC estimation of lithium iron phosphate battery.     

基于行人动力学模型的人桥竖向动力相互作用

基于行人动力学模型，研究了人桥竖向动力相互作用。行人动力学模型采用以行人步频和体重表示的刚度质量阻尼（SMD）模型，人行桥假定为Euler-Bernoulli梁模型，建立人桥竖向动力相互作用控制方程。采用状态空间法进行非比例阻尼系统瞬时模态的求解，得到系统的时变频率和阻尼比；利用变步长四阶五级Runge-Kutta-Felhberg算法求解时变控制方程，对比分析考虑人桥竖向动力相互作用和只在人行荷载作用下人行桥的动力响应。结果表明：考虑人桥动力相互作用，人行桥自振频率略有降低，阻尼有显著增大；当行人以人行桥的频率行走时，考虑人桥竖向动力相互作用结构的动力响应比不考虑人桥相互作用显著降低。     

PD Online Measurement of Transformers with Wide Frequency Band System and the Noise Eliminating Method by Cascaded IIR Lattice Notch Digital Filter

The frequency band of conventional partial discharge (PD) measurement systems is selected just within several ten kilohertz. With the development of computer and digital signal processing techniques, wide frequency band (WFB) measurement systems have been used to detect PD in electrical equipment for its higher sensitivity. Nevertheless, the WFB measurement systems are easy suffered from the interference of strong field electromagnetism noises. A set of PD online monitoring system with frequency band from 50 kHz to 1 megahertz used for transformer is developed, in which pre-processing device and cascaded 2nd order IIR lattice notch digital filter are mainly used to suppress periodic narrow-band interference. With analysis of field monitored signal at a 220 kV substation, it is shown that the monitoring system not only can detect and extract the discharge pulse signal effectively, but also has the powerful capability of suppressing interference.     

Weighted fusion algorithm for frequency estimation of the short signal with the same frequency and length

For high precise frequency estimation of the short sinusoid signal at low signal-to-noise ratio (SNR), a weighted fusion algorithm for frequency estimation of the short signal with the same frequency and length (SFL-Signal) is proposed. The spectrum model of SFL-Signal and the phase compensation matrix with phase coherent and noise cancellation are constructed. Secondly, the SFL-signal spectrum is weight-fused with the phase compensation matrix to obtain the result almost the same as that of the spectrum of the phase-coherent sinusoid signal. Consequently, high frequency estimation precision is obtained with spectral peak searching of the weight-fusion spectrum. Algorithm analysis and simulation results show that, compared with the existing methods,the proposed algorithm works better in term of precision, calculation complexity, noise immunity, and fits for any type of SFL-Signal.     

A RELIABILITY PROCESSING ALGORITHM SUITABLE FOR STOCHASTIC AND SUDDENLY VARYING DATA

In regard to stochastic and suddenly varying data,a new kind of data processor algorithm based on adaptive prediction is presented.The algorithm describes the changing pattern of measured variables by means of time series models with slowly time-varying parameters,forms the criterion by use of the adaptive and its 95% belief limit,and processes the measured data so as to reject or restrain outliers mixed in them.The simulation example indicates that the algorithm surmounts difficulties which most current algorithms encounter when processing stochastic and suddenly varying data and that it is of obvious effects.     

Study on the Difference Phase Degree Division Displacement Transducer

Pointing out the shortages of the traditional bar thread displacement transducer, brings forward new thought of designing difference phase degree division displacement transducer, which transforms the problem of measuring displacement directly in angle into the problem of measuring the difference between the phases of two signals which have the same frequency and then gets the displacement in angle indirectly. The theories on designing the phase difference calculation displacement transducer and correlation displacement transducer is suggested. Because the difference phase degree division displacement transducer, supported by the computer technology and the signal processing technology, adapts to the development of instrument's fictionzing and intelligentizings, it is an advanced technology.     

FPGA Implementation of Pipelined FFT

A pipelined FFT processor designed for fast and real-time requirements with FPGA is introduced. This FFT processor can be used to real-time frequency analysis and its working frequency can reach to 75 MHz. The leakage error is reduced through multiply the sampled signal by a weighting window. In order to improve FFT's working frequency and economize FPGA resources, an algorithm of 1024-point complex to compute 2048-point real data is adopted. In addition, an approximate algorithm to compute module value of complex number is introduced.