Blackman Window Research Articles

Application of the reciprocity principle to evaluation of mode-converted scattered shear horizontal (SH) wavefields in tapered thinning plates

The interaction of guided waves with wall thinning can be complex, depending on the thinning geometry and the frequency. At a high frequency–thickness, when a shear-horizontal (SH) guided wave mode impinges upon a tapered wall thinning region, there is mode conversion to other propagating SH modes, either in reflection or transmission, which heavily depends on the shape of the taper. In this paper, we have combined the reciprocity theorem of elastodynamics and the theory of multiple reflections, in order to analytically calculate the scattered SH wavefield in plates, due to the interaction with an arbitrary tapered thinning. The taper is discretized into several sections and the formulation is addressed in matrix notation, in order to tackle several modes which arise due to mode interconversion distributed within the taper. The method was validated with experimental and numerical data at linear tapered thinning, in the high-frequency–thickness regime. It was also applied to provide understanding of the reflection behaviour within smoother taper profiles, namely, raised-cosine and Blackman window tapers, and to visualize the propagating field of each mode. It is shown that for a linear taper profile, the reflection within the taper is virtually constant, which produces an interference pattern in the overall reflection from the whole taper. Such a mechanism is broken with smoother tapers, since they impose lower reflection close to the taper ends. The method proves itself useful for analytically investigating the scattering from arbitrary wall thinning when mode-conversion arises.

Automatic Sub-Pixel Co-Registration of Remote Sensing Images Using Phase Correlation and Harris Detector

In this paper, we propose a new approach for sub-pixel co-registration based on Fourier phase correlation combined with the Harris detector. Due to the limitation of the standard phase correlation method to achieve only pixel-level accuracy, another approach is required to reach sub-pixel matching precision. We first applied the Harris corner detector to extract corners from both references and sensed images. Then, we identified their corresponding points using phase correlation between the image pairs. To achieve sub-pixel registration accuracy, two optimization algorithms were used. The effectiveness of the proposed method was tested with very high-resolution (VHR) remote sensing images, including Pleiades satellite images and aerial imagery. Compared with the speeded-up robust features (SURF)-based method, phase correlation with the Blackman window function produced 91% more matches with high reliability. Moreover, the results of the optimization analysis have revealed that Nelder–Mead algorithm performs better than the two-point step size gradient algorithm regarding localization accuracy and computation time. The proposed approach achieves better accuracy than 0.5 pixels and outperforms the speeded-up robust features (SURF)-based method. It can achieve sub-pixel accuracy in the presence of noise and produces large numbers of correct matching points.

M-ary phase-shift keying using finite impulse response filter based on window function method

Digital filters are vastly utilized in the area of communication. A perfect digital filter efficiency is significant and hence to design a digital finite impulse response filter (FIR) favorable all the wanted situations is necessary. In this paper, a new proposed FIR digital filter designed, the fineness of the submitted filter is tested in terms of BER and then matched with another window, namely Hamming, Hanning, and Blackman. The design procedure done in the MATLAB software. It is concluded that the Blackman window is the best window to design the FIR digital filter, because it is bit error rate is better than another window.

Fast Convergence Method for Scaling Window Sidelobe Magnitude

Windows such as Dolph-Chebyshev window and Kaiser window are adjustable, whereas windows such as Hamming window and Blackman window are traditionally not adjustable. In [1], a technique for trading off main lobe width against sidelobe magnitude for any arbitrary window, including the traditionally non-adjustable windows, was presented. However, the method in [1] requires a large number of iterations if the specification is very tight. Developed based on a new perspective on the window adjustment principle, a new method to achieve the same adjustment capability as in [1], but at a very much fewer iterations is presented in this letter. Our new method is particular useful if the specification is very tight.

An accuracy improving method for composite grating phase measuring profilometry

An accuracy improving method for composite grating phase measuring profilometry (CGPMP) based on mixed filtering window is proposed. When CGPMP is used to carry out three-dimensional (3D) measurement, the phase-shifting deformed patterns can be demodulated effectively from the captured composite deformed pattern by proper filters. So the selection of the filtering window is very important. By analyzing the characteristics of noises and their different effects on the spectrum components along different orientations, searching for the best filtering window of the spatial spectrum along the two mutually orthogonal directions, a mixed filtering window to improve measuring accuracy is established. Digital simulating results show that the designedly mixed filtering window has better noise suppression than rectangular, triangular, Blackman and Hanning filtering windows. The experimental results show that the measuring error using the mixed filtering window equalizing noise and spectrum leakage is the smallest, and the root mean square error (RMSE) is reduced by 9.64%, and the measuring accuracy is improved effectively.

Bridge health monitoring using deflection measurements under random traffic

This paper demonstrates the potential to use measured deflection responses of a bridge to random traffic as a means of monitoring its structural health. Three displacement transducers are simulated on the bridge at different locations, providing absolute deflection data. The stiffness profile through the length of the bridge is calculated using these data. Vehicle axle loads are calculated as well as the relative bridge stiffness profile using a combined iteration approach. Axle spacings for each vehicle are currently measured in Bridge Weigh-in-Motion systems and are presumed to be known here. After estimating axle weights for each passing vehicle, the profile of bridge stiffness is calculated from batches of 1,000 vehicles with a focus on detecting any local damage. A moving average filter and a filtering method based on the Blackman window are used to reduce dynamic effects and the influence of noise. This stiffness profile approach is shown to be suitable for both damage location and quantification.

Bridge flexural rigidity calculation using measured drive-by deflections

This paper uses simulated deflections on a bridge taken from a model of an instrumented moving vehicle in an attempt to back calculate the distribution of flexural rigidity along the bridge length and hence to evaluate bridge condition. Eight sensors are simulated at different locations on the vehicle. It is assumed that measured deflections are absolute, i.e. they have been corrected for vehicle motion and that the characteristics of the vehicle are known. The unit load theorem is used to relate the measured deflections to the reciprocals of flexural rigidity at every location on the bridge. A Blackman window filter is used to regularise the problem and to improve the conditioning of an ill-conditioned system of equations. In addition, a moving average filter is used to reduce the influence of noise and dynamics, which are sources of inaccuracy in this study. This method is shown to give good results in indicating the presence and intensity of bridge damage and contains some weak information on location.

STUDY OF TIME FREQUENCY TRANSFORMS APPLIED TO POWER QUALITY SIGNALS

This work presents a scientific study on Short-Time Frequency Transforms (STFT) with different windows, also called Windowed Fourier Transforms, applied to power quality signals. Additionally, it deals with S transforms, with its frequency-dependent window. The disturbances related to energy quality have non-stationary nature, in which the spectral content varies over time. So, the Fourier Transform is not appropriate for such analysis, because it doesn’t show time locations, only information about existing frequencies in the signal. Therefore, the spectral analysis by windowed transforms helps to identify and detect a series of defects associated to these power signals. The motivation behind this document is to verify which window will provide a more precise identification of the characteristics of the disturbances in time-frequency domain. For this work, synthetic signals were generated for some of these disturbances, and their spectra were compared considering Gaussian, Hann and Blackman windows, as well as the S transform. Based on the obtained results, it was verified that each transform presents different behaviours acording to the input signal, except for the ones with Hann and Blackman windows, that showed similar spectra. For all of them, there is always a tradeoff between time and frequency resolutions. Therefore, the choice of the window must be done according to the desired outputs. The Dev-C ++ ® IDE was used for C ++ programming, and the Gnuplot ® program for graphics generation.

Best Lag Window for Spectrum Estimation of Law Order MA Process

In this article, we investigate spectrum estimation of law order moving average (MA) process. The main tool is the lag window which is one of the important components of the consistent form to estimate spectral density function (SDF). We show, based on a computer simulation, that the Blackman window is the best lag window to estimate the SDF of MA1 and MA2 at the most values of parameters βi and series sizes n, except for a special case when β=−1 and n≥40 in MA1. In addition, the Hanning–Poisson window appears as the best to estimate the SDF of MA2 when β1=β2=−0.5 and n≥40.

A Design of a low-pass FIR filter using Hamming Window Functions in Matlab

The reduction and filtering of the input components of an original signal in one or more frequency bands using a finite impulse response, better known as FIR, is designed using a function of the Hamming window. Although there are various window functions such as the Blackman window function, the Hanning window function and the rectangular window functions that can be used as digital filters, the Hamming window function was used in this study for the reason of its minimum damping/decibel of the stopband with a reduced transition bandwidth. Among the other three widow functions that can be used, the Blackman window function is closest to the Hamming window function in terms of minimum bandstop attenuation/decibel, since both have a dB value greater than -50. However, in terms of transition bandwidth (Δω), the Hamming window has a narrower bandwidth than the Blackman window, making it more appropriate to use in this FIR filter design. This type of filter is important for analyzing the different types of signals that are essential in a world where digital filters play a major role in DSP applications. This research paper offers a Matlab-based low-pass FIR digital filter that uses Hamming window functions. Keywords: FIR filters, Hamming window, Blackman window Hanning window, Matlab. DOI: 10.7176/CEIS/11-2-04 Publication date: February 29 th 2020

Fault Monitoring System for the Multistage Gear Box Based on MSTFT and GFLA Algorithm

Gearbox functions as a significant transmission module in the mechanical devices in spite of its failure prone nature and hence there exists a need for the diagnosing the gearbox faults with an optimized solution and new methods should be engaged for improving the effectiveness, accuracy, reliability and few other such parameters. These attempts could meet the growing requirements for the condition monitoring in the detection of gear faults. The feature selection process is a notable process in the machine learning to achieve good performance in the diagnostic process. This framework builds up an innovative structure for fault diagnosis in the gearbox system. Six vibrating signals which are healthy gear signal, fault gear signal, healthy gear signal affected by noise, faulty gear signal affected by noise, distributed fault signal, and local fault signal have been generated with the prescribed dataset and the feature extraction was done by employing the Modified Short-Time Fourier Transform on the basis of Blackman window. This step was followed by selection of the features by using the combination of Genetic algorithm and Frog Leaping algorithm that is termed as GFLA.This novelty approach enhances the initialization process thereby enabling for the calculation of accurate best score calculation. The classification method is performed Support points on the basis of neural network. Finally the performance analysis with respect to the existing methodologies proved the efficiency in detecting the fault of the proposed framework.

Adaptive transmit array sidelobe control using FDA-MIMO for tracking in joint radar-communications

In this paper, we present an adaptive closed–loop range-angle dependent sidelobe control using frequency diverse array (FDA) multiple-input multiple-output (MIMO) design for joint radar-communications. The system carries out tracking of the target and the communication receiver, while transmitting information bits towards the intended communication receiver using a flexible sidelobe control, i.e., controlling the power emitted at a certain angle-range position. The range-angle dependent sidelobe control utilizing an overlapped-FDA generated uncoupled beampattern with the proposed Blackman window based non-uniform frequency offsets enables the communication links to use the same radar spectrum. Moreover, we adaptively design two transmit weight vectors and finally compute a beamspace matrix that facilitates to generate the range-angle dependent beam patterns with a same radar main lobe, but distinct sidelobe levels (in accordance with the binary bit to be transmitted) for the moving target and communication receiver, respectively. Furthermore, we propose a cognitive algorithm to discriminate the target and communication receiver positions. Finally, the information bits can be efficiently detected by the intended communication receiver, merely, due to the power difference in sidelobe levels of the directed range-angle dependent radiated patterns without affecting the radar performance. The improved performance of the proposed design is verified in terms of bit error rate and inherent security for the communication functionality, while target detection, target tracking and parameter estimation are considered for the radar application.

Airborne gravity survey, towards a precise Indonesian geoid model (case study: Sumatera Island)

Airborne gravity method for high-resolution geoid model in Indonesia held in Sumatera Island using Lacoste & Romberg Air-Sea Gravity Meter S-130 and Trimble R9S GNSS installed in the cessna grand caravan type C208B. Flight altitude ranging from 3000 to 4000 meters and the aircraft speed is 277 km/h. Processing GNSS are using differential processing which is tied to SRGI2013 with a standard deviation tolerance <7 cm in high position and 90% data fix. The gravity raw data (LCR file) is filtered using the lowpass filtering filter mode with the weight function blackman window, the filter window used is 150-seconds. From crossover analysis, some cross over misfit relatively large difference with more than ±20 mGal difference, the average and standard deviation of crossover misfit were -0.0023 mGal and 9.0214 mGal respectively. The result of spectral analysis, airborne gravity signal has minimum 10 km of wavelength while the EGM2008 degree 2190 has minimum 18 km of wavelength.

A 13-Channel 1.53-mW 11.28-mm2 Electrical Impedance Tomography SoC Based on Frequency Division Multiplexing for Lung Physiological Imaging.

An electrical impedance tomography (EIT) system based on frequency division multiplexing (FDM) is proposed for real-time lung physiological imaging. The FDM technique allows the integration of 13 dedicated voltage sensing channels by combining data on-chip and sharing of ADC to alleviate area penalty caused by multi-channel. The EIT system-on-chip (SoC) is of the following features. 1) Early I/Q demodulation to relax the bandwidth requirement of analog front end and minimize the impact of motion artifacts and dc electrode offset. 2) Eliminates the need of adaptive gain control with constant inverted "U-shape" gain configuration to compensate amplitude variations across all channels. 3) FDM to combine 13 pairs of I/Q signals into two data streams for quantization using only two ΔΣ modulators. 4) Batch data recovery by Blackman window corrected fast Fourier transform without any digital filtering involved. 5) Lowest power consumption and smallest area occupation per channel reported to date. The EIT SoC occupies an area of 11.28mm2 in 130-nm CMOS technology with a total power consumption of 1.53mW under 1-V power supply. As a result, it generates lung EIT images at up to five frames per second.

Research on Dielectric Loss Angle of Capacitive Equipment Based on Blackman Window Improved FFT

According to the fact that the dielectric loss angle of capacitive equipment is mainly determined by the phase difference between its terminal voltage and leakage current, cutting short the voltage and current signals by Blackman window, and correcting the spectrum of voltage and current signals by three-spectral line interpolation method and 7-order polynomial fitting technique, a simple and practical frequency correction formula and a formula for calculating dielectric loss angle based on improved FFT are given. The results of simulation and measurement show that the spectrum correction method presented in this paper is effective under harmonic interference and frequency fluctuation of power grid, and the measurement results of dielectric loss angle delta are accurate and stable.

TAPSTROKE: A novel intelligent authentication system using tap frequencies

Emerging security requirements lead to new validation protocols to be implemented to recent authentication systems by employing biometric traits instead of regular passwords. If an additional security is required in authentication phase, keystroke recognition and classification systems and related interfaces are very promising for collecting and classifying biometric traits. These systems generally operate in time-domain; however, the conventional time-domain solutions could be inadequate if a touchscreen is so small to enter any kind of alphanumeric passwords or a password consists of one single character like a tap to the screen. Therefore, we propose a novel frequency-based authentication system, TAPSTROKE, as a prospective protocol for small touchscreens and an alternative authentication methodology for existing devices. We firstly analyzed the binary train signals formed by tap passwords consisting of taps instead of alphanumeric digits by the regular (STFT) and modified short time Fourier transformations (mSTFT). The unique biometric feature extracted from a tap signal is the frequency-time localization achieved by the spectrograms which are generated by these transformations. The touch signals, generated from the same tap-password, create significantly different spectrograms for predetermined window sizes. Finally, we conducted several experiments to distinguish future attempts by one-class support vector machines (SVM) with a simple linear kernel for Hamming and Blackman window functions. The experiments are greatly encouraging that we achieved 1.40%–2.12% and 2.01%–3.21% equal error rates (EER) with mSTFT; while with regular STFT the classifiers produced quite higher EER, 7.49%–11.95% and 6.93%–10.12%, with Hamming and Blackman window functions, separately. The whole methodology, as an expert system for protecting the users from fraud attacks sheds light on new era of authentication systems for future smart gears and watches.

Analytic method for fast design of aperiodic fiber Bragg grating devices

An analytic method for fast design of aperiodic fiber Bragg grating (AFBG) devices by use of Fourier mode coupling (FMC) theory is presented. AFBG devices, which are often used in practice, include the superstructure, phase-shifted FBG, and the apodized FBGs with Gauss, cosine, raised-cosine, Hamming, or Blackman windows, and include the in-fiber Fabry–Perot cavities formed by two AFBGs. The analytic solutions to the reflectivities of these AFBG devices are obtained on the basis of FMC theory, from which closed-form expressions for the relation between the AFBG structure parameters and their reflection properties are derived. According to these expressions, an analytic algorithm is established to quickly design AFBG devices with the desired reflection properties, which has linear complexity. The design of each AFBG device was achieved in ∼50 ms on a general PC, and the reflection properties of the designed AFBG device were confirmed by using the transfer matrix method. This indicates that the analytic design methods proposed are highly efficient and sufficiently accurate.

Does Fourier analysis yield reliable amplitudes of quantum oscillations?

Quantum oscillation amplitudes of multiband metals, such as high-Tc superconductors in the normal state, heavy fermions or organic conductors, are generally determined through Fourier analysis of the data even though the oscillatory part of the signal is field dependent. It is demonstrated that the amplitude of a given Fourier component can strongly depend on both the nature of the windowing (either flat, Hahn or Blackman window) and, since oscillations are obtained within a finite field range, the window width. Consequences on the determination of the Fourier amplitudes, hence of the effective masses, are examined in order to determine the conditions for reliable data analysis.

Implementation of the Finite Impulse Response (FIR) Filter on the DSK TMS320C6713 Transceiver Using Windowing Techniques

In this study, implementing the FIR filter with the Blackman window and Rectangular window methods with the types of low pass, highpass, and bandpass filters using 2 DSK TMS320C6713 boards as sender (Tx) and receiver (Rx) using the code composer studio (CCS) V software program. .3.1, which will then be displayed on Matlab to observe the output results. From the test results, data will be obtained which are then analyzed to determine the filter performance of the design results and the real implementation results using the DSK TMS320C6713. The results showed that the design of the low pass, high pass and bandpass filters was in accordance with the desired specifications, although in the highpass filter design, the filter results were still incomplete.

A Direct Approach to Separate Forward-Scattered Waves from the Direct Blast in Doppler Domain for Forward-Scattering Detection

Forward-scattered waves are often interfered with and overwhelmed by direct blasts when a submerged target crosses the source–receiver line. The approach named low Doppler analysis and recording gram (LODARGRAM) is developed to separate forward-scattered waves from direct blasts in the Doppler domain. This separation, which is based on the kinetic characteristic of the target and the procedure, is conducted using a sliding Blackman window combined with fast Fourier transform. The concept along with its application is validated using the data collected in a tank experiment. The moving target is recognized and identified by a tilt striation on LODARGRAM. Limitations of the LODARGRAM approach are also discussed.