scholarly journals Optimization of receiving window width of the correlation receiver for radiofrequency identification marker localization

2019 ◽  
Vol 15 (9) ◽  
pp. 155014771987809
Author(s):  
Peter Vestenický ◽  
Martin Vestenický
Keyword(s):  
Numerical Solution ◽  
Time Window ◽  
Theoretical Calculations ◽  
Signal To Noise Ratio ◽  
Analytical Description ◽  
Analytical Form ◽  
Electric Circuits ◽  
Window Width ◽  
Radiofrequency Identification ◽  
Correlation Receiver

The radiofrequency identification (RFID) technology is widely used in modern industry to identify and localize the final manufactured products and their parts. This article analyses and optimizes the localization process of special RFID transponders – markers used to mark the position and type of the underground facility networks (pipes, cables, etc.). The analysis of electric circuits representing the system consisting of the marker and the localization device is performed by numerical solution of the corresponding equations. The results of the numerical solution are then used for calculation of the analytical description of the waveform received as response from the excited marker. The constants obtained from the analytical form of the solution are then used as input parameters for optimization of time window width in the correlation receiver of the marker responses. The optimization is focused on the maximization of the signal-to-noise ratio in the receiving time window. The theoretical calculations are completed by the processing of real signals recorded by an oscilloscope from the localization device where the correlation receiver is planned to apply.

Adaptive Multiple Second-order Synchrosqueezing Wavelet Transform and Its Application in Wind Turbine Gearbox Fault Diagnosis

2021 ◽  
Author(s):  
Zhaohong Yu ◽  
Cancan Yi ◽  
Xiangjun Chen ◽  
Tao Huang
Keyword(s):  
Wavelet Transform ◽  
Wind Turbine ◽  
Time Window ◽  
Vibration Signal ◽  
Second Order ◽  
Center Frequency ◽  
Wind Turbine Gearbox ◽  
Adaptive Wavelet ◽  
Time Frequency ◽  
Window Width

Abstract Wind turbines usually operate in harsh environments and in working conditions of variable speed, which easily causes their key components such as gearboxes to fail. The gearbox vibration signal of a wind turbine has nonstationary characteristics, and the existing Time-Frequency (TF) Analysis (TFA) methods have some problems such as insufficient concentration of TF energy. In order to obtain a more apparent and more congregated Time-Frequency Representation (TFR), this paper proposes a new TFA method, namely Adaptive Multiple Second-order Synchrosqueezing Wavelet Transform (AMWSST2). Firstly, a short-time window is innovatively introduced on the foundation of classical Continuous Wavelet Transform (CWT), and the window width is adaptively optimized by using the center frequency and scale factor. After that, a smoothing process is carried out between different segments to eliminate the discontinuity and thus Adaptive Wavelet Transform (AWT) is generated. Then, on the basis of the theoretical framework of Synchrosqueezing Transform (SST) and accurate Instantaneous Frequency (IF) estimation by the utilization of second-order local demodulation operator, Adaptive Second-order Synchrosqueezing Wavelet Transform (AWSST2) is formed. Considering that the quality of actual time-frequency analysis is greatly disturbed by noise components, through performing multiple Synchrosqueezing operations, the congregation of TFR energy is further improved, and finally, the AMWSST2 algorithm studied in this paper is proposed. Since Synchrosqueezing operations are performed only in the frequency direction, this method AMWSST2 allows the signal to be perfectly reconstructed. For the verification of its effectiveness, this paper applies it to the processing of the vibration signal of the gearbox of a 750 kW wind turbine.

scholarly journals Arrival-Time Detection in Wind-Speed Measurement: Wavelet Transform and Bayesian Information Criteria

Sensors ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 269 ◽  
Author(s):  
Wei Zhang ◽  
Zhipeng Li ◽  
Xuyang Gao ◽  
Yanjun Li ◽  
Yibing Shi
Keyword(s):  
Wavelet Transform ◽  
Wind Speed ◽  
Arrival Time ◽  
Time Window ◽  
Signal To Noise Ratio ◽  
Information Criteria ◽  
Echo Signal ◽  
Time Frequency ◽  
Ultrasonic Echo ◽  
Ultrasonic Anemometer

The time-difference method is a common one for measuring wind speed ultrasonically, and its core is the precise arrival-time determination of the ultrasonic echo signal. However, because of background noise and different types of ultrasonic sensors, it is difficult to measure the arrival time of the echo signal accurately in practice. In this paper, a method based on the wavelet transform (WT) and Bayesian information criteria (BIC) is proposed for determining the arrival time of the echo signal. First, the time-frequency distribution of the echo signal is obtained by using the determined WT and rough arrival time. After setting up a time window around the rough arrival time point, the BIC function is calculated in the time window, and the arrival time is determined by using the BIC function. The proposed method is tested in a wind tunnel with an ultrasonic anemometer. The experimental results show that, even in the low-signal-to-noise-ratio area, the deviation between mostly measured values and preset standard values is mostly within 5 μs, and the standard deviation of measured wind speed is within 0.2 m/s.

scholarly journals A New Spiral Potato Cleaner to Enhance the Removal of Impurities and Soil Clods in Potato Harvesting

2020 ◽  
Vol 12 (23) ◽  
pp. 9788
Author(s):  
Volodymyr Bulgakov ◽  
Simone Pascuzzi ◽  
Semjons Ivanovs ◽  
Zinoviy Ruzhylo ◽  
Ivan Fedosiy ◽  
...  
Keyword(s):  
Numerical Solution ◽  
Experimental Studies ◽  
Analytical Description ◽  
Potato Production ◽  
Angular Speed ◽  
Plant Residues ◽  
Agricultural Field ◽  
Production Chain ◽  
Removal Of Impurities ◽  
The Mathematical Model

Sustainability in the agricultural field suggests the conservation and maintenance of a natural environment of soil. Nevertheless, in the potato production chain, the mechanized harvest is carried out with the concurring removal of impurities and fertile soil. The authors have developed a new spiral potato cleaner which is able to capture and efficiently remove soil lumps of various sizes and shapes, as well as various plant residues. Theoretical and experimental studies have been performed on this soil clod cleaner to determine the structural and kinematic parameters that provide efficient capturing, motion and sifting down of the soil, through the gaps between the helices of its cleaning spirals. An analytical description of the motion of the clod of soil has been made and a system of differential equations has been compiled, whose numerical solution made it possible to determine the indicated reasonable operative parameters of the developed spiral potato cleaner. The results of the experimental research confirmed those ones obtained through the numerical solution of the mathematical model, i.e., rational angular speed ω of the rotation of the spirals from 20.0 to 30.0 rad s−1 and the radius R of spirals between 0.12 and 0.15 m.

Assisted traveltime picking of crosshole GPR data

Geophysics ◽  
2009 ◽  
Vol 74 (4) ◽  
pp. J35-J48 ◽  
Author(s):  
Bernard Giroux ◽  
Abderrezak Bouchedda ◽  
Michel Chouteau
Keyword(s):  
Time Window ◽  
Signal To Noise Ratio ◽  
Real Data ◽  
Information Criterion ◽  
High Signal ◽  
Data Sets ◽  
Signal To Noise ◽  
Arrival Times ◽  
Common Time ◽  
Waveform Similarity

We introduce two new traveltime picking schemes developed specifically for crosshole ground-penetrating radar (GPR) applications. The main objective is to automate, at least partially, the traveltime picking procedure and to provide first-arrival times that are closer in quality to those of manual picking approaches. The first scheme is an adaptation of a method based on cross-correlation of radar traces collated in gathers according to their associated transmitter-receiver angle. A detector is added to isolate the first cycle of the radar wave and to suppress secon-dary arrivals that might be mistaken for first arrivals. To improve the accuracy of the arrival times obtained from the crosscorrelation lags, a time-rescaling scheme is implemented to resize the radar wavelets to a common time-window length. The second method is based on the Akaike information criterion(AIC) and continuous wavelet transform (CWT). It is not tied to the restrictive criterion of waveform similarity that underlies crosscorrelation approaches, which is not guaranteed for traces sorted in common ray-angle gathers. It has the advantage of being automated fully. Performances of the new algorithms are tested with synthetic and real data. In all tests, the approach that adds first-cycle isolation to the original crosscorrelation scheme improves the results. In contrast, the time-rescaling approach brings limited benefits, except when strong dispersion is present in the data. In addition, the performance of crosscorrelation picking schemes degrades for data sets with disparate waveforms despite the high signal-to-noise ratio of the data. In general, the AIC-CWT approach is more versatile and performs well on all data sets. Only with data showing low signal-to-noise ratios is the AIC-CWT superseded by the modified crosscorrelation picker.

scholarly journals High-contrast photoacoustic imaging through scattering media using correlation detection of adaptive time window

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Liqi Yu ◽  
Jialin Sun ◽  
Xinjing Lv ◽  
Qi Feng ◽  
Huimei He ◽  
...  
Keyword(s):  
Light Scattering ◽  
Time Window ◽  
Photoacoustic Imaging ◽  
Signal To Noise Ratio ◽  
Photoacoustic Signal ◽  
High Contrast ◽  
Scattering Media ◽  
Window Method ◽  
Adaptive Time ◽  
Imaging Depth

AbstractPhotoacoustic imaging has the advantages of high contrast and deep imaging depth. However, with the increasing of imaging depth, the signal-to-noise ratio (SNR) of the detected signal decreases, due to the light scattering that seriously affects the recovery image quality. In this paper, we experimentally demonstrated that higher contrast photoacoustic imaging was achieved using photoacoustic wavefront shaping technology in the presence of light scattering and low SNR signals. The imaging contrast is improved from 1.51 to 5.30. More importantly, we propose a dynamic time window method for the photoacoustic signal extraction algorithm, named correlation detection of adaptive time window, which further improves the contrast of photoacoustic imaging to 9.57. Our method effectively improves the contrast of photoacoustic imaging through scattering media.

Partially coherent migration

Geophysics ◽  
1993 ◽  
Vol 58 (9) ◽  
pp. 1301-1313 ◽  
Author(s):  
Delman Lee ◽  
Geoffrey M. Jackson ◽  
Iain M. Mason
Keyword(s):  
Signal To Noise Ratio ◽  
Velocity Model ◽  
Lateral Resolution ◽  
Signal To Noise ◽  
Timing Errors ◽  
Macro Model ◽  
Partially Coherent ◽  
Window Width ◽  
Stochastic Framework ◽  
Noise Ratio

Partially coherent migration reduces the spurious details introduced by velocity macro‐model imperfections. In a partially coherent migration, instead of summing coherently over the full aperture to achieve maximum lateral resolution, (1) a coherent stack is performed over a limited window width, and then (2) the collection of coherent stacks for different windows along the full aperture are summed incoherently to produce an amplitude value for each output point. Amplitude accuracy of a migration is improved with some sacrifice in spatial (lateral) resolution. A parameter in partially coherent migration is the running coherent window width, which accounts for the spatial correlation of errors in the velocity model. The coherent window width controls the trade‐off between signal‐to‐noise ratio and lateral resolution. Assuming that timing errors introduced by imperfections of a velocity macro‐model are from a zero‐mean stationary Gaussian process, partially coherent migration is shown to raise the signal‐to‐noise ratio of the migrated image as compared to a conventional migration. The two competing aspects of signal‐to‐noise ratio and lateral resolution of the partially coherent migration in the presence of timing errors are analyzed in a stochastic framework. The intuitively attractive idea of limiting the coherent window width to the correlation length of the timing errors is confirmed numerically.

scholarly journals A compact lightweight multipurpose ground-penetrating radar for glaciological applications

2011 ◽  
Vol 57 (206) ◽  
pp. 1113-1118 ◽  
Author(s):  
E.V. Vasilenko ◽  
F. Machío ◽  
J.J. Lapazaran ◽  
F.J. Navarro ◽  
K. Frolovskiy
Keyword(s):  
Dynamic Range ◽  
Time Window ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Peak Voltage ◽  
Recording Time ◽  
Single Person ◽  
Radio Echo Sounding ◽  
Power Peak ◽  
Ground Penetrating

AbstractWe describe a compact lightweight impulse radar for radio-echo sounding of subsurface structures designed specifically for glaciological applications. The radar operates at frequencies between 10 and 75 MHz. Its main advantages are that it has a high signal-to-noise ratio and a corresponding wide dynamic range of 132 dB due mainly to its ability to perform real-time stacking (up to 4096 traces) as well as to the high transmitted power (peak voltage 2800 V). The maximum recording time window, 40 μs at 100 MHz sampling frequency, results in possible radar returns from as deep as 3300 m. It is a versatile radar, suitable for different geophysical measurements (common-offset profiling, common midpoint, transillumination, etc.) and for different profiling set-ups, such as a snowmobile and sledge convoy or carried in a backpack and operated by a single person. Its low power consumption (6.6 W for the transmitter and 7.5 W for the receiver) allows the system to operate under battery power for >7 hours with a total weight of <9 kg for all equipment, antennas and batteries.

Principal component transforms of triaxial recordings by singular value decomposition

Geophysics ◽  
1991 ◽  
Vol 56 (4) ◽  
pp. 528-533 ◽  
Author(s):  
G. M. Jackson ◽  
I. M. Mason ◽  
S. A. Greenhalgh
Keyword(s):  
Singular Value Decomposition ◽  
Time Window ◽  
Signal To Noise Ratio ◽  
Random Noise ◽  
Principal Component ◽  
Singular Value ◽  
Data Matrix ◽  
Single Station ◽  
Window Selection ◽  
Value Decomposition

Polarization analysis can be achieved efficiently by treating a time window of a single‐station triaxial recording as a matrix and doing a singular value decomposition (SVD) of this seismic data matrix. SVD of the triaxial data matrix produces an eigenanalysis of the data covariance (cross‐energy) matrix and a rotation of the data onto the directions given by the eigenanalysis (Karhunen‐Loève transform), all in one step. SVD provides a complete principal components analysis of the data in the analysis time window. Selection of this time window is crucial to the success of the analysis and is governed by three considerations: the window should contain only one arrival; the window should be such that the signal‐to‐noise ratio is maximized; and the window should be long enough to be able to discriminate random noise from signal. The SVD analysis provides estimates of signal, signal polarization directions, and noise. An F‐test is proposed which gives the confidence level for the hypothesis of rectilinear polarization. This paper illustrates the analysis and interpretation of synthetic rectilinearly and elliptically polarized arrivals at a single triaxial station by SVD.

Sign in / Sign up

Export Citation Format

Share Document