Further results on Kendall's autoregressive series

1975 ◽  
Vol 12 (01) ◽  
pp. 180-182
Author(s):  
Jay C. Hardin ◽  
Thomas J. Brown
Keyword(s):  
Fourier Transform ◽  
Difference Equation ◽  
Fast Fourier Transform ◽  
Cross Correlation ◽  
Input And Output ◽  
The Cross ◽  
The Difference ◽  
Autoregressive Series

Theoretical expressions for the cross correlation and cross spectra of the input and output variables in the difference equation Xt =aXt −1 + bXt− 2 + Yt are derived. These expressions are compared with estimates of these expectations obtained by employing a Fast Fourier Transform technique on digitally generated series.

Further results on Kendall's autoregressive series

1975 ◽  
Vol 12 (1) ◽  
pp. 180-182
Author(s):  
Jay C. Hardin ◽  
Thomas J. Brown
Keyword(s):  
Fourier Transform ◽  
Difference Equation ◽  
Fast Fourier Transform ◽  
Cross Correlation ◽  
Input And Output ◽  
The Cross ◽  
The Difference ◽  
Autoregressive Series

Theoretical expressions for the cross correlation and cross spectra of the input and output variables in the difference equation Xt=aXt−1 + bXt−2+ Yt are derived. These expressions are compared with estimates of these expectations obtained by employing a Fast Fourier Transform technique on digitally generated series.

scholarly journals Imbalance Detection of Rotor Rotational Speed Using Doppler Radar

2021 ◽  
Vol 21 (2) ◽  
pp. 111-118
Author(s):  
Young-Jae Choi ◽  
In-Sik Choi
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Wind Turbine ◽  
Rotational Speed ◽  
Doppler Radar ◽  
Numerical Data ◽  
Accumulated Damage ◽  
The Difference

In operating a wind turbine, both predictive and condition-based maintenances are required to minimize the downtime caused by maintenance. The imbalance of rotor rotational speed is an important factor for diagnosing wind turbine failures. The rotational speed imbalance can be caused by accumulated damage or the accumulation of ice, dust, and moisture. In this paper, we proposed a method for detecting the rotational speed imbalance of a wind turbine using a Doppler radar. We calculated the difference in the rotational speed for different times using spectrograms obtained by observing the wind turbine with a Doppler radar and determined the rotational speed imbalance using the fast Fourier transform. The performance of the proposed algorithm was verified using both synthetic and numerical data.

Application of fast Fourier transform cross-correlation and mass spectrometry data for accurate alignment of chromatograms

2013 ◽  
Vol 1286 ◽  
pp. 175-182 ◽  
Author(s):  
Yi-Bao Zheng ◽  
Zhi-Min Zhang ◽  
Yi-Zeng Liang ◽  
De-Jian Zhan ◽  
Jian-Hua Huang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Cross Correlation ◽  
Mass Spectrometry Data

scholarly journals Magnetic storm free ULF analysis in relation with earthquakes in Taiwan

2012 ◽  
Vol 12 (5) ◽  
pp. 1747-1754 ◽  
Author(s):  
S. Wen ◽  
C.-H. Chen ◽  
H.-Y. Yen ◽  
T.-K. Yeh ◽  
J.-Y. Liu ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Cross Correlation ◽  
Low Frequency ◽  
Magnetic Anomalies ◽  
Magnetic Storms ◽  
Frequency Range ◽  
Geomagnetic Data ◽  
Before And After ◽  
The Cross ◽  
The Fourier Transform

Abstract. Despite early optimism, pre-earthquake anomalous phenomena can be determined by using enhanced amplitude at the ultra-low-frequency range from geomagnetic data via the Fourier transform. In reality, accuracy of the enhanced amplitude in relation to earthquakes (deduced from time-varied geomagnetic data) would be damaged by magnetic storms and/or other unwanted influences resulting from solar activity and/or variations in the ionosphere, respectively. We substitute values of the cross correlation between amplitudes, summarized from the earthquake-related (0.1–0.01 Hz) and the comparable (0.01–0.001 Hz) frequency bands, for isolated amplitude enhancements as indexes of determination associated with seismo-magnetic anomalies to mitigate disturbance caused by magnetic storms. A station located about 300 km away from the others is also taken into account to further examine whether changes of the cross correlation values are caused by seismo-magnetic anomalies limited within local regions or not. Analytical results show that the values suddenly decrease near epicenters a few days before and after 67% (= 6/9) of earthquakes (M > = 5) in Taiwan between September 2010 and March 2011. Seismo-magnetic signals determined by using the values of cross correlation methods partially improve results yielded from the Fourier transform alone and provide advantageous information of earthquake locations.

scholarly journals CCID: Cross-Correlation Identity Distinction Method for Detecting Shrew DDoS

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Cheng Huang ◽  
Ping Yi ◽  
Futai Zou ◽  
Yao Yao ◽  
Wei Wang ◽  
...  
Keyword(s):  
Cross Correlation ◽  
Transmission Control Protocol ◽  
Denial Of Service ◽  
Gaussian White Noise ◽  
Normal Flow ◽  
Flow Properties ◽  
Data Packets ◽  
Lower Maximum ◽  
The Cross ◽  
The Difference

This study presents a new method for detecting Shrew DDoS (Distributed Denial of Service) attacks and analyzes the characteristics of the Shrew DDoS attack. Shrew DDoS is periodic to be suitable for the server’s TCP (Transmission Control Protocol) timer. It has lower maximum to bypass peak detection. This periodicity makes it distinguishable from normal data packets. By proposing the CCID (Cross-Correlation Identity Distinction) method to distinguish the flow properties, it quantifies the difference between a normal flow and an attack flow. Simultaneously, we calculated the cross-correlation between the attack flow and the normal flow in three different situations. The server can use its own TCP flow timer to construct a periodic attack flow. The cross-correlation between Gaussian white noise and simulated attack flow is less than 0.3. The cross-correlation between single-door function and simulated attack flow is 0.28. The cross-correlation between actual attack flow and simulated attack flow is more than 0.8. This shows that we can quantitatively distinguish the attack effects of different signals. By testing 4 million data, we can prove that it has a certain effect in practice.

The Implementation of Fast Fourier Transform and Coherence Function to Detect the Millimetric Hole on Strip Iron Plate

2020 ◽  
Vol 840 ◽  
pp. 430-437
Author(s):  
Ardi Wiranata ◽  
Ekrar Winata
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Trigger Point ◽  
Coherence Function ◽  
Digital Signal ◽  
Vibration Signal ◽  
Computational Time ◽  
Iron Plate ◽  
The Difference ◽  
Magnitude Squared Coherence

In this study, Fast Fourier Transform (FFT) was used in order to detect bore hole in a structure. FFT is a common method in digital signal processing (DSP) to characterize the frequency emitted by some structure. This method is widely used because of its simplicity. Computational time needed for FFT is relatively lower than another method. The use of FFT to analyze defect in structure is not commonly used since FFT has some weakness for example spatial frequency cannot be extracted to point out the defect location. In this paper, defect was designated as a hole in a strip iron plate with 20 mm in diameter. The strip iron plate was 1 meter long, 38 mm wide and 3 mm thick. This strip iron plate was clamped at one of its ends while the other side is left free. In order to produce vibration signal, impact hammer Bruel Kjaer Type 8202 was used with plastic tip to limit the vibration frequency in to the range of 0 - 1000 Hz. The trigger point was 30 mm from its free end. Three accelerometers were placed series in one line with the trigger point with 300 mm distance of each accelerometer. The position of the hole was varied in three different position. The first position was between trigger point and first accelerometer, between first and second accelerometer and between the second and third accelerometer. The raw signal obtained from the accelerometer was processed by using FFT to understand the mode shape changes in the strip iron plate due to the bore hole. Furthermore, the FFT result was analyzed as function of receiver position to determine the position of hole. The result shows that the frequency characters were different in each case and further analysis by using magnitude-squared coherence function need to be used in order to quantitatively find the difference between FFT result.

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