The Effects of Variable Time Window Width and Signal Position Within FFT Bin on WISPR Performance.

1996 ◽  
Author(s):  
Jacob George ◽  
Ronald A. Wagstaff
Keyword(s):  
Time Window ◽  
Variable Time ◽  
Window Width

scholarly journals A single‐shot autocorrelator for the ultraviolet with a variable time window

1990 ◽  
Vol 61 (3) ◽  
pp. 998-1003 ◽  
Author(s):  
S. Szatmári ◽  
F. P. Schäfer ◽  
J. Jethwa
Keyword(s):  
Time Window ◽  
Single Shot ◽  
Variable Time

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.

Fixed versus variable time window warehousing strategies in real time

2020 ◽  
Vol 9 (4) ◽  
pp. 315-324
Author(s):  
Sergio Gil-Borrás ◽  
Eduardo G. Pardo ◽  
Antonio Alonso-Ayuso ◽  
Abraham Duarte
Keyword(s):  
Real Time ◽  
Time Window ◽  
Variable Time

scholarly journals Self-Correction Ship Tracking and Counting with Variable Time Window Based on YOLOv3

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Chun Liu ◽  
Jian Li
Keyword(s):  
Time Window ◽  
Time Windows ◽  
Target Object ◽  
Variable Time ◽  
Ship Detection ◽  
Detection Model ◽  
Maritime Surveillance ◽  
Model Training ◽  
Direction Judgment ◽  
Deep Learning Model

Automatic ship detection, recognition, and counting are crucial for intelligent maritime surveillance, timely ocean rescue, and computer-aided decision-making. YOLOv3 pretraining model is used for model training with sample images for ship detection. The ship detection model is built by adjusting and optimizing parameters. Combining the target HSV color histogram features and LBP local features’ target, object recognition and selection are realized by using the deep learning model due to its efficiency in extracting object characteristics. Since tracking targets are subject to drift and jitter, a self-correction network that composites both direction judgment based on regression and target counting method with variable time windows is designed, which better realizes automatic detection, tracking, and self-correction of moving object numbers in water. The method in this paper shows stability and robustness, applicable to the automatic analysis of waterway videos and statistics extraction.

Research and application of waveform clustering with variable time window in dolomite distribution prediction

2021 ◽  
Author(s):  
Yunfeng Huang ◽  
Zhanlong Yang ◽  
Wang YanFang ◽  
Xu YunZe ◽  
Lei Lv
Keyword(s):  
Time Window ◽  
Variable Time

MARTINI: Towards a mobile and variable time window identification for spatio-temporal data

2019 ◽  
Author(s):  
Lucas Zanco Ladeira ◽  
Allan Mariano de Souza ◽  
Geraldo Pereira Rocha Filho ◽  
Thiago Henrique Silva ◽  
Matheus Ferraroni Sanches ◽  
...  
Keyword(s):  
Time Window ◽  
Temporal Data ◽  
Variable Time ◽  
Spatio Temporal

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.

Sign in / Sign up

Export Citation Format

Share Document