Digital Low-pass Filter Research Articles

GAM-Based Mooring Alignment for SINS Based on An Improved CEEMD Denoising Method.

To solve the self-alignment problem of the Strapdown Inertial Navigation System (SINS), a novel adaptive filter based on Complementary Ensemble Empirical Mode Decomposition (CEEMD) is proposed. The Gravitational Apparent Motion (GAM) is used in the coarse alignment, and the problem of obtaining the attitude matrix between the body frame and the navigation frame is attributed to obtaining the matrix between the initial body frame and the current navigation frame using two gravitational apparent motion vectors at different moments. However, the accuracy and time of this alignment method always suffer from the measurement noise of sensors. Thus, a novel adaptive filter based on CEEMD using an -norm to calculate the similarity measure between the Probability Density Function (PDF) of each Intrinsic Mode Function (IMF) and the original signal is proposed to denoise the measurements of the accelerometer. Furthermore, the advantage of this filter is verified by comparing with other conventional denoising methods, such as PDF-based EMD (EMD-PDF) and the Finite Impulse Response (FIR) digital low-pass filter method. The results of the simulation and experiments indicate that the proposed method performs better than the conventional methods in both alignment time and alignment accuracy.

High Spectral Efficiency 400 Gb/s Transmission by Different Modulation Formats and Advanced DSP

We experimentally demonstrate probabilistically shaped 64-ary quadrature-amplitude-modulation (64QAM) 50-GHz-grid wavelength-division-multiplexing (WDM) transmission with a bit rate of 400-Gbit/s per channel over 3,600-km Raman-amplified ultra-large effective area fiber (ULAF). Our results show that the probabilistically shaped 64QAM outperforms the hybrid-32/64QAM by 50% reach improvement. Thanks to pre-equalization and look-up-table pre-distortion, a 5.5-dB optical signal-to-noise ratio (OSNR) gain can be obtained. Furthermore, utilizing ULAF with Raman amplifier causes an apparent improvement on the transmission performance compared with using the SSMF with EDFA. We also compare the optical coupler with the wavelength selective switch utilized in the WDM system to explore a suitable way for WDM transmission. Advanced DSP including Butterworth low-pass digital filter is also used at the receiver end.

A novel AC filter system for the line commutated converter high voltage DC transmission system

This paper proposes a novel AC filter system for a line commutated converter high voltage DC (LCC-HVDC) transmission system. Through the coordination of the hybrid active power filters (APF) and the existing reactive compensation devices, the proposed filter system can not only enhance the suppression performance for LCC-HVDC harmonics, but also optimize the AC yard layout with reduced reactive power subbanks, reducing the cost of HVDC projects. The novel filter system adopts a serial passive resonance topology obtained by careful comparison of different APFs. A proper control scheme is then designed integrating the control strategy of the APF and impedance characteristics of the HVDC system, which is able to realize harmonic suppression and dynamic reactive power support simultaneously. In addition, a novel self-adaption digital low-pass filter algorithm is presented, which is used in the APF harmonic detecting step, enhancing both high precision and fast dynamic response. On the basis of a real HVDC project, the advantages of proposed filter system in harmonic suppression, reactive power regulation, and sub-banks reduction are simulated and demonstrated.

Gravimeter with two-dimensional digital filtering and error compensation of measuring information on mechanical quantities

The methods of two-dimensional digital filtering of the output signal of a gravimeter as part of an aviation gravimetric system are considered. The result of filtering is to increase the accuracy of measuring the acceleration of gravity as a result of eliminating the effect of vertical acceleration, translational and angular vibration accelerations of the aircraft. The problem of filtering and compensating for errors in measuring information on mechanical quantities was solved by algorithmic processing of the gravimeter output signal. Two-dimensional digital filtering of measurement information is performed on the basis of the formation of a two-dimensional array of digital readings of gravimetric measurement information about anomalies of gravitational acceleration, taking into account the coordinates of the Earth's surface where these readings were taken. This array corresponds to a number of adjacent flight lines of an aviation gravimetric system. After that, the generated array is filtered using a two-dimensional digital low-pass filter. The filtering process additionally takes into account the two-dimensional correlations that are present in the useful signal of the gravitational acceleration anomalies. Such filtering can be performed during the post-flight processing of the results of gravimetric measurements. The use of two-dimensional digital filtering of measurement information about mechanical quantities allows to increase the accuracy of determining the gravitational acceleration anomalies up to 2 times (compared to one-dimensional filtering) and 3 ... 5 times (compared to the output signal of the integrating gravimeter).

Demonstration of a Low-Cost and Portable Optical Cavity-Based Sensor through Refractive Index Measurements.

An optical cavity-based sensor using a differential detection method has been proposed for point-of-care diagnostics. We developed a low-cost and portable optical cavity-based sensor system using a 3D printer and off-the-shelf optical components. In this paper, we demonstrate the sensing capability of the portable system through refractive index measurements. Fabricated optical cavity samples were tested using the portable system and compared to simulation results. A referencing technique and digital low pass filtering were applied to reduce the noise of the portable system. The measurement results match the simulation results well and show the improved linearity and sensitivity by employing the differential detection method. The limit of detection achieved was 1.73 × 10−5 Refractive Index Unit (RIU), which is comparable to other methods for refractive index sensing.

A Biomedical Sensor System With Stochastic A/D Conversion and Error Correction by Machine Learning

This paper presents a high-precision biomedical sensor system with a novel analog-frontend (AFE) IC and error correction by machine learning. The AFE IC embeds an analog-to-digital converter (ADC) architecture called successive stochastic approximation ADC. The proposed ADC integrates a stochastic flash ADC (SF-ADC) into a successive approximation register ADC (SAR-ADC) to enhance its resolution. The SF-ADC is also used as a digitally controlled variable threshold comparator to provide error correction of the SAR-ADC. The proposed system also calibrates the ADC error using the machine learning algorithm on an external PC without additional power dissipation at a sensor node. Due to the flexibility of the system, the design complexity of an AFE IC can be relaxed by using these techniques. The target resolution is 18 bits, and the target bandwidth (without digital low-pass filter) is about 5 kHz to deal with several types of biopotential signals. The design is fabricated in a 130-nm CMOS process and operates at 1.2-V supply. The fabricated ADC achieves the SNDR of 88 dB at a sampling frequency of 250 kHz by using the proposed calibration techniques. Due to the high-resolution ADC, the input-referred noise is 2.52 μV <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rms</sub> with a gain of 28.5 dB.

Study of structural complexity of optimal order digital filters for de-noising ECG signal

Selection and implementation of optimal order digital filter for denoising ECG signal on FPGA, based on Signal to Noise Ratio (SNR), error and accuracy using wavelet toolbox is a tedious task. To overcome this problem, an attempt has been made in MATLAB to obtain a noise-free ECG signal based on SNR and mean square error to select optimal order digital filter. An ECG sample from MIT-BIH arrhythmia database is artificially corrupted by adding noise and is filtered through different low-pass IIR and FIR digital filters. The hardware complexity of optimal order digital filters structure is checked in terms of multipliers, adders and delays in MATLAB and their performance is compared based on the number of basic elements and visual inspections. It is found that the elliptic IIR filter and Kaiser window FIR filter require low-filter order for a given specification and hence, requires less number of basic elements.

Adaptive Discrete-Time Estimated Inverse Control for Piezoelectric Positioning Stage

This article aims at designing an adaptive estimated inverse control scheme to realize precise tracking control for a class of discrete-time nonlinear system with hysteresis nonlinearities. To this end, firstly, the dynamic surface control technology with digital first-order low-pass filter is designed and the original control system does not need to be transformed into an unknown special form. Then, the procedures of the controller design are greatly simplified. Secondly, the hysteresis nonlinearity is mitigated by constructing an discrete-time estimated inverse hysteresis compensator. Finally, the validity of the proposed adaptive control scheme is verified by the computer control experiments on a hardware-in-the-loop simulation platform. It is proved that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SUUB).

Программно-аппаратная реализация цифрового фильтра нижних частот на основе микроконтроллера dsPIC

Программно-аппаратная реализация цифрового фильтра нижних частот на основе микроконтроллера dsPIC

VISUAL ANALYSIS OF RECURRENCE OF TIME SERIES OF THE COORDINATES ENU IN THE GPS STATIONS

Abstract The time series content information about the dynamic behavior of the system under study. This behavior could be complex, irregular and no lineal. For this reason, it is necessary to study new models that can solve this dynamic more satisfactorily. In this work a visual analysis of recurrence from time series of the coordinate’s variation ENU (East, North, Up) will be made. This analysis was obtained from nine continuous monitoring stations GPS (Global Navigation Satellite System); the intention is to study their behavior, they belong to the Equatorian GPS Network that materializes the reference system SIRGAS - ECUADOR. The presence of noise in the observations was reduced using digital low pass filters with Finite Impulse Response (FIR). For these series, the time delay was determined using the average mutual information, and for the minimum embedding dimension the False Nearest Neighbours (FNN) method was used; the purpose is to obtain the recurrent maps of each coordinates. The results of visual analysis show a strong tendency, especially in the East and North coordinates, while the Up coordinates indicate discontinued, symmetric and periodic behavior.

Are complex black-box models for Permanent Downhole Gauge pressure estimation necessary?

The Permanent Downhole Gauge (PDG) is a pressure and temperature sensor located subsea near the perforation point in the offshore oil production system. This sensor is very useful in operation problems detection (fouling, valves, plugging, etc.), multiphasic flow analysis, production tests adjustment, control strategy and model identification. Given its location under hazardous conditions, it may come to failure or imprecisions in measurement. The high costs related to the maintenance make it infeasible to perform. To overcome this issue, a methodology based on digital signal processing (DSP) is proposed in order to design a low pass digital filter aiming the PDG pressure reconstruction. The proposed methodology requires no plant model, low computational cost and only the Christmas-Tree pressure measurement. The proposed methodology is compared with two commonly employed black-box methodologies: Neural Network and Transfer Function Estimation. The results show the success of the designed filter and the advantages over the black-box approaches. The estimation of the PDG pressure from three operating wells using real process data was performed.

Development of a high-speed full digital processing phase detector for interferometry.

This study describes the development of a fully digital-type phase detector for plasma interferometry. This detector functions even in situations in which the phase changes rapidly or the input signal is too small to derive the correct phase shift from the intermediate frequency (IF) signal. The detector directly converts the IF signal waveform of the interferometer to the phase shift signal by means of data processing in a logic circuit. Thus, the phase is derived from the whole waveform of the IF signal. The IF signal of the interferometer is converted to in-phase and quadrature-phase signals by Hilbert transformation, processed by a digital low-pass filter, and converted to polar coordinates by a coordinate rotation digital computer algorithm to obtain the phase shift. A simulation of the high-speed full digital processing phase detector shows that a fringe jump does not occur unless the phase change rate exceeds 0.8 × 106 rad/s. This value is sufficiently large compared to the phase change velocity in rapid density increase resulting from a pellet injection. The phase conversion is simulated using a real IF signal from an interferometer measured with a Heliotron J device. The results show that the phase signal is correctly calculated by the full digital processing method from the IF signal, the phase derivation of which is typically difficult to obtain when using a conventional analog phase detector.

Robust Position Sensorless Technique for a PMBLDC Motor

The main objective of this paper is to present a new mechanical sensorless control technique of a permanent magnet brushless dc (PMBLDC) motor, which relies on the speed independent H functions. Two major challenges in the sensorless operation of PMBLDC motor drive are the starting the motor and driving it from a low speed to the rated speed. A speed independent H function is used to decide the commutation instant. Due to speed independence, the commutation instant is predicted even at low speed. The H function depends only on line voltages, which makes the overall system simple and cost effective. The proposed technique does not require any analog filter circuit or any phase compensation circuit. To eliminate the commutation ripple from the line voltages, digital low-pass filters and digital phase compensators are used. This makes the system compact, simple, and cost effective. This cost-effective solution proves perfect for low-cost appliances such as fan, air-conditioner, refrigerator, vacuum cleaner, and other home appliances. The proposed algorithm is implemented on a low-cost DSP (TMS320F28377S) to justify the effectiveness of the proposed sensorless technique for wide speed variation.

Optimal design of minimum multiplier lattice wave digital lowpass filter using metaheuristic techniques

This study aims towards the efficient design of arbitrary-band and halfband lowpass (LP) filter based on lattice wave digital filter (LWDF) structure with the usage of minimal number of multipliers in its structural realisation. The designing of the LP filter is formulated as an optimisation problem where coefficients of LWDF transfer function are iteratively optimised by the evolutionary algorithms. The potential of four optimisation algorithms, real-coded genetic algorithm, particle swarm optimisation, differential evolution algorithm, and cuckoo search algorithm, are explored for determining the optimal LWDF coefficients by minimising the error objective function. The structural realisation of LP using LWDF structure enhances the design accuracy as the usage of multiplier prominently reduces. The simulation and statistical results of the proposed lattice wave digital lowpass filter (LWDLF) and bireciprocal lattice wave digital lowpass filter (BLWDLF) design show significant improvement in the mean square error, passband ripples, transition bandwidth, stopband attenuation, rate of convergence, and execution time. To manifest the efficient design of the proposed LWDLF and BLWDLF, the results are compared with the designed arbitrary-band, halfband canonic-LP filters and previous published works.

Band-pass filtering algorithms for adaptive control of compressor pre-stall modes in aircraft gas-turbine engine

The methods for increasing gas-turbine aircraft engines' (GTE) adaptive properties to interference based on empowerment of automatic control systems (ACS) are analyzed. The flow pulsation in suction and a discharge line of the compressor, which may cause the stall, are considered as the interference. The algorithmic solution to the problem of GTE pre-stall modes’ control adapted to stability boundary is proposed. The aim of the study is to develop the band-pass filtering algorithms to provide the detection functions of the compressor pre-stall modes for ACS GTE. The characteristic feature of pre-stall effect is the increase of pressure pulsation amplitude over the impeller at the multiples of the rotor’ frequencies. The used method is based on a band-pass filter combining low-pass and high-pass digital filters. The impulse response of the high-pass filter is determined through a known low-pass filter impulse response by spectral inversion. The resulting transfer function of the second order band-pass filter (BPF) corresponds to a stable system. The two circuit implementations of BPF are synthesized. Designed band-pass filtering algorithms were tested in MATLAB environment. Comparative analysis of amplitude-frequency response of proposed implementation allows choosing the BPF scheme providing the best quality of filtration. The BPF reaction to the periodic sinusoidal signal, simulating the experimentally obtained pressure pulsation function in the pre-stall mode, was considered. The results of model experiment demonstrated the effectiveness of applying band-pass filtering algorithms as part of ACS to identify the pre-stall mode of the compressor for detection of pressure fluctuations’ peaks, characterizing the compressor’s approach to the stability boundary.

Driving style indicator using UDRIVE NDS data

ABSTRACTObjective: In order to analyze specific events while driving (such as a safety critical event [SCE] or secondary task), we were interested in studying whether driving behavior was unusual around the event. An indicator characterizing driving style (driving style indicator [DSI]) was estimated for each driver by using naturalistic data. The analysis of the gap in driving style could be calculated for a specific trip or even a time window and could help characterize events: a more risky situation when DSI was above average, increase in safety margins when under average.Methods: Lateral acceleration and longitudinal acceleration were used for DSI calculation. The first step consisted in filtering the signal acquired by the inertial measurement unit (60 Hz). The noise was filtered out with an eighth order, phase-compensated digital low-pass Butterworth filter with a cut-out frequency of 5 Hz and offsets were compensated for. The second step consisted in calculating the jerk of the acceleration in lateral and longitudinal directions for each trip. The third step summarized the distribution of these jerks for all trips of each driver. Finally, the DSI was defined as the standard deviation of this distribution. A driver was represented by lateral DSI and longitudinal DSI.Results: The indicator was used on French pilot data (10 drivers) and on UK data (30 drivers) from the UDRIVE project. To assess this indicator, tests on track were conducted by professional drivers simulating two opposite driving style. The first results were promising and discriminated a smooth from a rough driving style. Indeed, in the pilot data, the classification was in accordance with our expectations and confirmed by videos. The same kind of distribution was observed in the UK data and needs to be confirmed when the UDRIVE database is complete.Conclusion: DSI is a new parameter that will be used to define clusters of drivers and study variation of driving parameters in each class during selected events (SCE, secondary task, etc.) in the UDRIVE project.

An improved ring removal procedure for in-line x-ray phase contrast tomography

The suppression of ring artifacts in x-ray computed tomography (CT) is a required step in practical applications; it can be addressed by introducing refined digital low pass filters within the reconstruction process. However, these filters may introduce additional ringing artifacts when simultaneously imaging pure phase objects and elements having a non-negligible absorption coefficient. Ringing originates at sharp interfaces, due to the truncation of spatial high frequencies, and severely affects qualitative and quantitative analysis of the reconstructed slices. In this work, we discuss the causes of ringing artifacts, and present a general compensation procedure to account for it. The proposed procedure has been tested with CT datasets of the mouse central nervous system acquired at different synchrotron radiation facilities. The results demonstrate that the proposed method compensates for ringing artifacts induced by low pass ring removal filters. The effectiveness of the ring suppression filters is not altered; the proposed method can thus be considered as a framework to improve the ring removal step, regardless of the specific filter adopted or the imaged sample.

Trajectory tracking control for rotary steerable systems using interval type-2 fuzzy logic and reinforcement learning

Rotary steerable system (RSS) is a directional drilling technique which has been applied in oil and gas exploration under complex environment for the requirements of fossil energy and geological prospecting. The nonlinearities and uncertainties which are caused by dynamical device, mechanical structure, extreme downhole environment and requirements of complex trajectory design in the actual drilling work increase the difficulties of accurate trajectory tracking. This paper proposes a model-based dual-loop feedback cooperative control method based on interval type-2 fuzzy logic control (IT2FLC) and actor-critic reinforcement learning (RL) algorithms with one-order digital low-pass filters (LPF) for three-dimensional trajectory tracking of RSS. In the proposed RSS trajectory tracking control architecture, an IT2FLC is utilized to deal with system nonlinearities and uncertainties, and an online iterative actor-critic RL controller structured by radial basis function neural networks (RBFNN) and adaptive dynamic programming (ADP) is exploited to eliminate the stick–slip oscillations relying on its approximate properties both in action function (actor) and value function (critic). The two control effects are fused to constitute cooperative controller to realize accurate trajectory tracking of RSS. The effectiveness of our controller is validated by simulations on designed function tests for angle building hole rate and complete downhole trajectory tracking, and by comparisons with other control methods.

Structure evolution-based design for low-pass IIR digital filters with the sharp transition band and the linear phase passband

Digital filters are generally designed by identifying the transfer functions. Most researches are focused on the goal of approaching the desired frequency response and take less additional consideration of structure characteristics. As a matter of fact, structure characteristics can greatly affect the performance of the digital filter. If only the frequency response is considered, the identified transfer function may not be the optimum. In this situation, structure synthesis is also limited by the form of the identified transfer function. This paper proposes a structure evolution-based optimization algorithm which allows the integrated consideration of structure issues and frequency response specifications in design stage. The method generates digital filter structures by a structurally automatic generation algorithm which can randomly generate and effectively represent digital structures. The structures, seen as chromosomes, are evolved over genetic algorithm for the search of the optimal solution in structure space. They are evaluated according to the mean square error between the designed and the desired frequency responses. Simulation results validate that the algorithm designs diversified structures of digital filters, and they meet target frequency specifications and structure constraints tightly. It is a promising way for optimized and automated design of digital filters.

Simulating the injection of magnetized plasma without electromagnetic precursor wave

Injecting magnetized plasma with changes in magnetization or injection rate necessitate a time variable magnetic field at the boundary of the simulation box. Naive implementation will lead to electromagnetic precursor waves that can affect the simulation results. The problem is well-known and is described e.g. in Lemebege and Dawson 1987. Since then few papers have attempted to deal with this problem and no standard solution exists. In this research note we suggest that the ad-hoc pulse shape that was used in the paper by Lemebege and Dawson 1987 can be replaces by a standard digital low pass filter. The cut off frequency of this filter should coincide with the gyro frequency in the magnetized plasma, to make use of (Doppler-broadend) resonant absorption caused by gyrating electrons. We illustrate this idea with a code example and demonstrate the efficency of this method throug sample simulations with our electromagnetic particle-in-cell code.