Digital Filtering Techniques Research Articles

An Innovative Approach to Mass Measurement of Liquids and Gases in Closed Containers By The Use of Piezo Ceramic Sensor

This article focuses on developing an innovative system for the precise and accurate measurement of the masses of liquids and pressurized gases in sealed containers. The system is based on piezoelectric sensors that detect pressure changes and process these signals to determine the mass of the liquid. The pressure changes detected by the piezoelectric sensors are converted into electrical signals, amplified by an amplifier circuit, and transmitted to a processor. The processor analyses these electrical signals utilizing developed algorithms to determine the mass of the liquid. The sensors used operate in a wide frequency band, adapting to different types of liquids and container shapes. Experimental results show that the developed system offers a great advantage, especially in industrial applications as it measures the liquid mass with high accuracy and does not require direct contact with the liquid. With the developed system, electronic amplifier circuits and digital filtering techniques were used together to minimize signal noise. This way, current voltage gains were increased and measurement accuracy was improved. This project offers an economical, non-contact, and reliable solution for determining the mass of the measured substance and brings an important innovation, especially in areas such as the chemical, food, and pharmaceutical sectors.

Comparison of milk-clotting activity measurement using the Berridge's operator-based approach and a proposed digital method

The milk clotting activity (MCA) analysis of coagulants used in the production of cheese is an important parameter used in the modern dairy industry. The MCA is calculated using the estimated milk-clotting time (MCT). The standard method used for estimation of MCT is presented in the ISO 23058/IDF 199 Standard using the Berridge's operator-based approach. In this paper a new method is presented to estimate the MCT using digital image acquisition and signal processing. The estimate is obtained by processing a sequence of images of the wall of a round bottom flask containing milk and the coagulant. Digital signal processing and filter techniques were used to remove interferences and artifacts and improve the clotting time estimation. A set of 28 samples of milk plus coagulant were processed. The method's accuracy is about 1/30 s and the average relative error, when compared to an experienced human operator, was με = 2.82%, according to the experimental results, with an associated standard deviation of σε = 3.07% and a median of mε = 1.92%. The method may be used to replace the human operator during the MCT estimation procedure.

Analysis of Electromyography (EMG) Signal Processing with Filtering Techniques

The paper presents the Analysis of Electromyography (EMG) Signal Processing with Filtering Techniques. The problem in this study is how to consider the filtering techniques for fundamental EMG signal processing with high-level accuracy. The research method for designing the simulation codes for observing the EMG signal modeling and digital filtering techniques with mathematical approaches from the signals and systems concepts. The results confirm that the outcomes of this study met the performance target for noise removal techniques of EMG signals in real-world applications.

Analysis of improved digital filter inflow generation methods for compressible turbulent boundary layers

We propose several enhancements to improve the accuracy and performance of the digital filter turbulent inflow generation technique and assess their efficacy in the context of wall-resolved large-eddy simulations of a compressible turbulent boundary layer. Improvements of accuracy include a more realistic correlation function for the transversal directions, target length scales that vary with wall-distance, and a counter-intuitive approach that involves the suppression of streamwise velocity fluctuations at the inflow. For improving the computational performance, we propose to generate the inflow data in parallel in single precision and at a prescribed time interval based on the turbulence time scale, and not at every time-step of the simulation. Based on the results of 7 wall-resolved large-eddy simulations, we find that the new correlation functions and the considered performance improvements are beneficial and therefore desired. Suppressing streamwise velocity fluctuations at the inflow leads to the fastest relaxation of the pressure fluctuations; however, this approach increases the adaptation length defined in terms of compliance with the von Kármán integral equation. The adaptation length can be shortened by artificially increasing the wall-normal Reynolds stresses, thereby preserving the desired turbulence kinetic energy level. A detailed inspection of the Reynolds stress transport budgets reveals that the observed spurious spatial transients are largely driven by pressure-related terms. For instance, increased values of u′p′¯ are found throughout the computational domain when a physical Reynolds stress distribution is prescribed at the inflow. Therefore, efforts to enhance digital filter techniques should aim at modeling pressure fluctuations as well as their correlation with the velocity components.

Improved noise performance from the next-generation buried-channel p-MOSFET SiSeROs

The Single electron Sensitive Read Out (SiSeRO) is a novel on-chip charge detector output stage for charge-coupled device (CCD) image sensors. Developed at MIT Lincoln Laboratory, this technology uses a p-MOSFET transistor with a depleted internal gate beneath the transistor channel. The transistor source-drain current is modulated by the transfer of charge into the internal gate. At Stanford, we have developed a readout module based on the drain current of the on-chip transistor to characterize the device. In our earlier work, we characterized a number of first prototype SiSeROs with the MOSFET transistor channels at the surface layer. An equivalent noise charge (ENC) of around 15 electrons root mean square (RMS) was obtained. In this work, we examine the first buried-channel SiSeRO. We have achieved substantially improved noise performance of around 4.5 electrons root mean square (RMS) and a full width half maximum (FWHM) energy resolution of 132 eV at 5.9 keV, for a readout speed of 625 kpixel/s. We also discuss how digital filtering techniques can be used to further improve the SiSeRO noise performance. Additional measurements and device simulations will be essential to further mature the SiSeRO technology. This new device class presents an exciting new technology for the next-generation astronomical X-ray telescopes requiring fast, low-noise, radiation-hard megapixel imagers with moderate spectroscopic resolution.

All‐Optical Parametric‐Assisted Oversampling and Decimation for Signal Denoising Amplification

AbstractDecimation is a common process in digital signal processing that involves reducing the sampling rate of an oversampled signal by linearly combining consecutive samples. Among other applications, this process represents a simple means to mitigate noise content in the digital signal. In this work, a novel optical signal processing concept inspired by these operations is proposed, which is called Parametric‐assisted Oversampling and Decimation (POD). By using a simple all‐fiber setup, the POD processor first realizes an ultra‐fast parametric oversampling of the incoming temporal signal (at >100 Gigasamples per second), a process that is followed by a decimation that reduces the sampling rate by any user‐defined factor in a lossless manner. In this way, the POD delivers an amplified sampled copy of the optical signal, where the peak‐to‐peak gain results from the combination of parametric amplification and a “passive” amplification equal to the decimation factor. In this report, joint parametric and passive amplification by a factor ≈50 on GHz‐bandwidth signals is demonstrated. Furthermore, it is shown that the decimation process can effectively mitigate effects of narrowband noise, outperforming traditional optical and digital filtering techniques. By experimentally achieving ultra‐high decimation factors (>750), narrowband (MHz‐bandwidth) optical waveformsthat are lost in a much stronger noise background are recovered.

Modifying the water table fluctuation method for calculating recharge in sloping aquifers

Study regionRobit Bata and Dengeshita watersheds, Upper Blue Nile basin, Ethiopia Study focusSustainable development of groundwater in the Ethiopian Highlands requires recharge measurements. The Water Table Fluctuation (WTF) method has been used to measure recharge. Lateral flow in sloping hillside aquifers violates the assumptions on which the original WTF method is based. We modified the original WTF method to include lateral flow controlled by gravity. New hydrological insightsPreviously it was shown that the sum of recharge over the travel time in a sloping aquifer is equal to the base flow. Since recharge cannot be measured directly, the recharge calculated with the modified WTF method was tested using baseflow measurement in two contrasting highland watersheds, Robit Bata and Dengeshita, where groundwater depth and streamflow data were monitored from 2015 to 2018. Baseflow was determined with the one-parameter digital filter technique. Predicted and observed monthly baseflow agreed well with R2 > 0.9 and RMSE < 20 mm during calibration and validation. Recharge in Robit Bata, in which the aquifer underlays 55% of the watershed, was 293 mm a−1 of 1378 mm a−1 precipitation. In Dengeshita, where the entire watershed has an aquifer, the average annual recharge was 525 mm a−1 of 1550 mm a−1. Our findings indicate that the modified WTF method is simple and practical for determining aquifer recharge for highlands and other sloping aquifers.

Non-contact breath cycle analysis for different breathing patterns using RGB-D videos

Traditionally, yogic breathing exercises have been considered an effective adjunct in managing stress, chronic pain and depression. Real-time bio-feedback based gaming applications can provide an opportunity to broaden the reach of yogic breathing exercises. To extract the bio-feedback parameters on human breathing behavior, robust real-time quantification of inhalation, exhalation, and retention durations for each breath cycle is very crucial. This paper implements the extraction of every respiration cycle of a person along with the duration of inhalation and exhalation using RGB-D videos under minimal movement. The proposed method uses the abdominal-thoracic region as the region of interest (ROI) and relates the small displacement of the chest region with breath and obtains a time-series signal that represents the user's breathing pattern. Appropriate digital filtering techniques are employed in eliminating the noise components and a novel algorithm is proposed to extract individual breath cycle parameters. From the extracted parameters, a gamified bio-feedback application to regulate respiration in real-time is demonstrated. The proposed methodology is evaluated for different breathing patterns against a collected representative dataset, which includes ten participants of different age groups and gender. Results indicate that the breathing rate can be detected with a mean RMSE error of 0.435 s and 0.467 s for the inhalation and exhalation times between the proposed method and the ground truth measurement.

Contribution of nonpoint source pollution from baseflow of a typical agriculture-intensive basin in northern China

Baseflow is an essential component of total surface runoff that is widely considered one of the most influential factors regarding water quality via nonpoint source (NPS) pollution. Previously, many researchers and policy makers have directed their efforts toward surface runoff pollution, largely ignoring nutrient delivery via baseflow. Taking a typical agriculture-intensive basin of northern China as an example, this study explored the spatiotemporal characteristics of baseflow and pollution load in relation to NPS pollution. Baseflow was quantified using digital filtering techniques, and the results together with observed pollution data were used to validate a physically based hydrological model, i.e., the Soil and Water Assessment Tool. Then, the spatial and temporal distribution characteristics of NPS and baseflow pollution were investigated using the modeling results. Results indicated that baseflow contribution to total runoff accounted for more than 70% during the studied years (2016–2018), and 84.15% of the basin area showed non-point source pollution dominated by baseflow pollution; both baseflow and its pollution load were greater in the nonflood seasons (spring, autumn, and winter) than in the flood season (summer); the spatial distribution of baseflow total nitrogen and total phosphorus pollution intensity showed higher values in the east and lower values in the west; the scaling effects of baseflow and its pollution load was found with increasing basin area. The results of our study highlighted the necessity for management of pollution load via baseflow in the river basin and provided reference information for improvement of NPS pollution management in other similar basins.

Frequency splitting approach using wavelet for energy management strategies in fuel cell ultra-capacitor hybrid system

Using frequency splitting, two energy management strategies (EMS) based on Haar wavelet decomposition and Fourier analysis for fuel cell hybrid vehicle (FCHV) are proposed to manage efficiently the power flow between components. The paper aims to discuss the performances of the proposed EMS in terms of dynamic behavior, robustness operation, real time application and fuel economy. For apply this methodology, two EMS approaches are elaborated and successfully tested for parallel Fuel Cell/UC: conventional approach using Fourier Transform analysis (FT) and Wavelet analysis approach allowing natural frequency splitting. Finally, and to evaluate the performance and relevance of the developed approach, a comparison analysis were conducted. The simulation results exhibit the effectiveness of both strategies. Indeed, Wavelet analysis leads to better results in terms of energy flow and dynamic behavior, excellent robustness and stability of system, as well as energy economy improvement. A very relevant strategy is proposed based on Wavelet analysis using digital filtering techniques, which enables a natural frequency splitting to ensure the best global performances. In addition, the approach remains simple and suitable for real time operation.

An Optimal Digital Filtering Technique for Incremental Delta-Sigma ADCs Using Passive Integrators

This paper presents an optimal digital filtering technique to enhance the resolution of incremental delta-sigma modulators (incremental DSMs, IDSMs) using a low-power passive integrator. We first describe a link between a passive integrator and its impact on the output of the IDSM. We then show that the optimal digital filter design can be cast as a convex optimization problem, which can be efficiently solved. As a test vehicle of the proposed technique, we use a behavioral 2nd-order IDSM model that captures critical non-idealities of the integrator, such as gain compression and output saturation. The effectiveness of the presented technique is verified using extensive simulations. The result shows that the presented filtering technique improves signal-to-noise and distortion ratio (SNDR) by 15 dB–20 dB, achieving SNDR over 90 dB when the oversampling ratio (OSR) = 256, and this corresponds to best-in-class performance when compared to previously published DSM designs using passive integrators.

Application of Derivative Transform Spectroscopy in Gas Detection

Digital filtering technique is of great significance in real-time signal processing and analysis, but the stability, efficiency and flexibility of filter algorithm are important indicators to reflect its application value. In this paper, an adaptive derivative transformation based on Savitzky-Golay filter algorithm was proposed for laser absorption spectroscopy analysis. To demonstrate this analysis algorithm, first-order and second-order derivative spectroscopy are evaluated for the analysis of infrared methane absorption spectra, and compared with the original direct absorption spectral signals. The results indicated that the proposed signal processing algorithm has good performance on noise suppression and spectral resolution improvement, and the 2nd derivative spectroscopy shows better de-noising efficiency.

Application of the PODFS method to inlet turbulence generated using the digital filter technique

In the past the digital filter technique has been used to successfully generate inflow turbulence for a number of academic and industrially relevant reacting and non-reacting flows. Weaknesses of the method include the requirement that the filter be computed over a structured mesh and can require extremely long computation times in cases where the turbulent length scales or filter widths are large as compared to the mesh spacing. Once computed, the inflow data may be saved and reused, however tens-of-thousands of time steps worth of data must be saved, copied and re-loaded into memory for each new computation and temporal interpolation must be used if the time step is adjusted. The newly developed PODFS (proper orthogonal decomposition Fourier series) method uses proper orthogonal decomposition (POD) to compress this large data set into a handful of modes that are optimally chosen to represent the high energy turbulent structures while a Fourier series representation of the temporal components of the POD modes means that the data becomes continuous, periodic and flexible in terms of time step. The PODFS is first applied to a set of inflow data generated using the digital filter method and used to simulate a turbulent planar jet with the results compared against a DNS simulation. A practical application of the method is then demonstrated where it is used to generate inlet turbulence from a time averaged URANS profile for a swirl stabilised combustor case. In this case, two PODFS models are linearly combined, one that represents acoustic forcing from downstream and one that represents turbulent fluctuations. This highlights a feature of the method which is its ability to represent different flow phenomena using the linear addition of two or more PODFS models. A subsequent LES calculation shows that the method results in the correct penetration of the airflow jets whilst neglecting the inlet turbulence results in the incorrect jet penetration depth.

Improvement of measuring range in fiber interferometric liquid level sensor by employing digital filter for mode selectivity

AbstractA liquid level sensor system based on dual tapers all‐fiber Mach‐Zehnder interferometer incorporating digital filtering is proposed for extended measurement range. Digital filtering technique is employed to selectively isolate beating of a particular dominant cladding mode, resulting a more consistent response in terms of spectra quality and wavelength shift. Sensing characteristics of cladding modes also are studied theoretically and experimentally. From experiment, continuous measurement of water level is demonstrated over 1016‐mm range with sensitivity of −0.0021 nm/mm and R2 of 0.9972. To our knowledge, this is the highest measurement range and linearity for liquid level sensor based on interferometric sensing system has been reported. The proposed technique can be very useful to enhance sensing performance for various fiber interferometric sensor applications.

DISPONIBILIDADE HÍDRICA E BALANÇO HÍDRICO DA BACIA DO RIO CACHOEIRA NA REGIÃO DE ITABUNA/BA

Foi estimado o balanço hídrico na Bacia do Rio Cachoeira, na região de Itabuna (Sul da Bahia), para o período de 1973 a 2005, utilizando-se a série histórica de vazão do Rio Cachoeira e a precipitação acumulada nesse período, com base em dados obtidos de cinco estações pluviométricas. Para o cálculo dos escoamentos de base e superficial foi aplicada a técnica de filtros digitais, que permite separar, de maneira automatizada e sistemática, a contribuição das componentes fluxo de base e escoamento superficial. A evapotranspiração acumulada anual média da bacia hidrográfica corresponde a cerca de 85% da precipitação, enquanto 15% desta corresponde ao escoamento total. O escoamento superficial representa a maior parcela da água escoada, com média anual de 84,53% e máximo de 92,2% no período chuvoso, indicando baixa capacidade de infiltração de água no subsolo. A recarga média anual estimada para o aquífero (27.35 mm/a) corresponde a 15% da vazão média do rio Cachoeira e a 2,34% da precipitação média anual.

Effect of percolation on hydrodynamic lubrication of rough bilayer porous bearing with circular contact

PurposeThe purpose of this paper was to study the hydrodynamic lubrication of rough bilayer porous bearing to reveal the effect of percolation.Design/methodology/approachThe seepage lubrication model of the circular bilayer porous bearing was established in polar coordinates. The digital filtering technique and Darcy’s law were used to simulate the rough surface and the percolation characteristic of the oil bearing, respectively. The influence of the structural parameters on the lubrication performance was analyzed.FindingsCompared with the ordinary monolayer oil bearing with high porosity, the bilayer bearing can reduce the whole porosity, prevent oil infiltrating into the porous medium and have better lubrication performance. The lubrication performance of bilayer oil bearing is better than that of the single-layer oil bearing which has a higher porosity. With increasing root-mean-square roughness or decreasing surface porosity, the lubrication performance of the bilayer bearing improves. The lower the porosity of the surface layer, the better the lubrication performance.Originality/valueThis research provides a theoretical basis for clarifying the lubrication mechanism and influence the mechanism of the bilayer oil bearing.

Study of a quantitative screening method of magnetotelluric sounding curves

An accurate tensor estimation function is a guarantee for acquiring a reliable underground electrical structure model. The past studies regarding transmission functions aim at obtaining smooth and continuous sounding curves through the time domain by data screening means such as least square, robust and remote reference processing methods as well as digital filtering techniques such as wavelet denoising, empirical mode decomposition and Hilbert–Huang transform denoising. As SNRs in different field measurement sites are different, if different data processing algorithms like single-site processing, remote reference processing, magnetic field correlation-based remote reference processing and magnetic channel sharing are used for data processing at the same measuring site, 3N-2 groups of sounding curves with different qualities will be obtained. Manual screening method has been mainly used in the past for screening of the abovementioned 3N-2 groups of sounding curves. If the quantity of sounding site is large, this manual screening method is of low efficiency without quantitative screening indexes. In this paper, discrete Frechet distance is mainly utilized to carry out quantitative screening of 3N-2 groups of sounding curves processed through the abovementioned four processing methods in order to obtain smooth, continuous and reliable sounding curves, thus avoiding subjectivity and low efficiency problems in the past manual screening. A quantitative sorting of all kinds of data processing results can be conducted, and the optimal sounding curve is finally picked out for data inversion. The above sounding curve selection result has improved processing accuracy of magnetotelluric data.

A New Algorithm Based Charge Controller for Global MPPT of Si Solar Cell

This work illustrates the development of a new hybrid MPPT algorithm and the construction of an efficient charge controller based on this algorithm. The existing perturb &amp; observe (P&amp;O) methodology and incremental conductance (IC) method are unable to trace the global maximum power point (GMPP) once there's a frequent modification in solar irradiance. These algorithms stick to local maxima in such scenario so the controller efficiency drops. Here a new hybrid MPPT algorithm was designed to track the GMPP efficiently, which involves the concept of Savitzky Golay digital filter technique. This filter is employed to swish a collection of digital information points that additional will increase the S/N of the signal while not greatly distorting it. The substitute sub-sets of niggardly observations fact are passable about a low-degree polynomial by the come nigh of neat least squares by means of convolution. This algorithm first smoothens the output of photovoltaic using the described technique and removes the local maxima and then further applies the P&amp;O method to find out the GMPP. The circuit was simulated using Proteus and later on, an experimental setup was built using Arduino UNO (ATMEGA328P) to run the algorithm in real-time environment. The controller successfully tracked the GMPP voltages for variable irradiance both in simulation and real-time environment.

Dynamic reconstruction of chaotic system based on exponential weighted online sequential extreme learning machine with kernel

For the dynamic reconstruction of the chaotic dynamical system, a method of identifying an exponential weighted online sequential extreme learning machine with kernel(EW-KOSELM) is proposed. The kernel recursive least square (KRLS) algorithm is directly extended to an online sequential ELM framework, and weakens the effect of old data by introducing a forgetting factor. Meanwhile, the proposed algorithm can deal with the ever-increasing computational difficulties inherent in online kernel learning algorithms based on the ‘fixed-budget’ memory technique. The employed EW-KOSELM identification method is firstly applied to the numerical example of Duffing-Ueda oscillator for chaotic dynamical system based on simulated data, the qualitative and quantitative analysis for various validation tests of the dynamical properties of the original system as well as the identification model are carried out. A set of qualitative validation criteria is implemented by comparing chaotic attractors i.e. embedding trajectories, computing the corresponding Poincare mapping, plotting the bifurcation diagram, and plotting the steady-state trajectory i.e. the limit cycle between the original system and the identification model. Simultaneously, the quantitative validation criterion which includes computing the largest positive Lyapunov exponent and the correlation dimension of the chaotic attractors is also calculated to measure the closeness i.e. the approximation error between the original system and the identification model. The employed method is further applied to a practical implementation example of Chua's circuit based on the experimental data which are generated by sampling and recording the measured voltage across a capacitor, the inductor current from the double-scroll attractor, the measured voltage across a capacitor from the Chua's spiral attractor and an experimental time series from a chaotic circuit. The digital filtering technique is then used as a preprocessing approach, on the basis of wavelet denoising the measured data with lower signal-noise ratio (SNR) which can produce the double-scroll attractor or the spiral attractor, the reconstruction attractor of the identification model is compared with the reconstruction attractor from the experimental data for original system. The above experimental results confirm that the EW-FB-KOSELM identification method has a better performance of dynamic reconstruction, which can produce an accurate nonlinear model of process exhibiting chaotic dynamics. The identification model is dynamically equivalent or system approximation to the original system.

Heart Condition Telediagnosis via Bio-Signals Surveillance Workbench Based on Simple Mail Transfer Protocol Technique

This article leads to the implementation and development of a Laboratory Virtual Instrument Engineering Workbench-based vital signs surveillance system for cardiovascular patients based on the Simple Mail Transfer Protocol technology. There are three main parts comprising the designed device, the first portion is a lap (circuit) built utilizing a hardware amplifier (AD620) called an electrocardiogram amplifier lap. Then comes the signal-conditioning lap with a practical amplifier (LM741). The second portion, is the signal conversion part from an analog signal to the digital signal using a data acquisition card. Moreover, cardiac data is processed and digital filtering techniques are performed to eliminate artifacts (noise) from the electrocardiogram signal acquired through the Laboratory Virtual Instrument Engineering Workbench system. Additionally, after preprocessing the cardiac signal the developed algorithm is utilized to calculate the heart-rate and analyze the heart condition (analyze the arrhythmia condition). In order to make the current labor more effective and attractive, Simple Mail Transfer Protocol technology has been added for remote diagnosis and monitoring purpose the state of the electrocardiogram signals easily over the internet, where the Simple Mail Transfer Protocol technology benefits is low-cost and effective in telediagnosis, which was previously a major problem overcome by this technique.