Pipeline system identification through cross-correlation analysis

2002 ◽  
Vol 216 (3) ◽  
pp. 133-142 ◽  
Author(s):  
S B M Beck ◽  
N J Williamson ◽  
N D Sims ◽  
R Stanway
Keyword(s):  
Correlation Analysis ◽  
Cross Correlation ◽  
Correlation Technique ◽  
Pipeline System ◽  
Pipe Network ◽  
Cross Correlation Analysis ◽  
Valve Position ◽  
Single Sensor ◽  
The Cross ◽  
Cross Correlation Technique

The pipeline systems used to carry liquids and gases for the ventilation of buildings, water distributions networks, and the oil and chemical industries are usually monitored by a multiplicity of pressure, flow, and valve position sensors. By comparing the input signal to a valve with the pressure reading from the network using cross-correlation analysis, the technique described in this paper enables a single sensor to be used for monitoring. Specifically, the offset and gradient change of the cross-correlation function show the time delay between the input wave and the acquired output signal. These reflections arise from junctions, valves, and terminations, which can be located effectively using the cross-correlation technique. Investigations using a T-shaped pipe network have been conducted with a valve inserted in the pipeline to introduce artificial water hammer-type perturbations into the system. Both computational and experimental data are presented and the results are compared with the actual pipe network geometry. It is shown that it is possible to identify the location of various features of the network from the reflections and thus to perform either system characterisation or condition monitoring.

Multiscale Multifractal Detrended Cross-Correlation Analysis of High-Frequency Financial Time Series

2019 ◽  
Vol 18 (03) ◽  
pp. 1950014 ◽  
Author(s):  
Jingjing Huang ◽  
Danlei Gu
Keyword(s):  
Time Series ◽  
Correlation Analysis ◽  
High Frequency ◽  
Cross Correlation ◽  
Financial Time Series ◽  
Chinese Market ◽  
Change Of Scale ◽  
Cross Correlation Analysis ◽  
Cross Correlations ◽  
The Cross

In order to obtain richer information on the cross-correlation properties between two time series, we introduce a method called multiscale multifractal detrended cross-correlation analysis (MM-DCCA). This method is based on the Hurst surface and can be used to study the non-linear relationship between two time series. By sweeping through all the scale ranges of the multifractal structure of the complex system, it can present more information than the multifractal detrended cross-correlation analysis (MF-DCCA). In this paper, we use the MM-DCCA method to study the cross-correlations between two sets of artificial data and two sets of 5[Formula: see text]min high-frequency stock data from home and abroad. They are SZSE and SSEC in the Chinese market, and DJI and NASDAQ in the US market. We use Hurst surface and Hurst exponential distribution histogram to analyze the research objects and find that SSEC, SZSE and DJI, NASDAQ all show multifractal properties and long-range cross-correlations. We find that the fluctuation of the Hurst surface is related to the positive and negative of [Formula: see text], the change of scale range, the difference of national system, and the length of time series. The results show that the MM-DCCA method can give more abundant information and more detailed dynamic processes.

MULTISCALE DETRENDED CROSS-CORRELATION ANALYSIS OF STOCK MARKETS

Fractals ◽  
2014 ◽  
Vol 22 (04) ◽  
pp. 1450007 ◽  
Author(s):  
YI YIN ◽  
PENGJIAN SHANG
Keyword(s):  
Correlation Analysis ◽  
Stock Markets ◽  
Cross Correlation ◽  
Statistical Characteristics ◽  
Detailed Knowledge ◽  
Stock Indices ◽  
Regional Markets ◽  
Cross Correlation Analysis ◽  
Cross Correlations ◽  
The Cross

In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997–2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and issue.

scholarly journals Investigations on the Coregistration of Sentinel-1 TOPS with the Conventional Cross-Correlation Technique

2018 ◽  
Vol 10 (9) ◽  
pp. 1405 ◽  
Author(s):  
Yuxiao Qin ◽  
Daniele Perissin ◽  
Jing Bai
Keyword(s):  
Cross Correlation ◽  
Phase Error ◽  
Impulse Response Function ◽  
Correlation Method ◽  
Correlation Technique ◽  
Geometrical Approach ◽  
Rigid Transformation ◽  
Interferometric Phase ◽  
The Cross ◽  
Cross Correlation Technique

In Sentinel-1 TOPS mode, the antenna sweeps in the azimuth direction for the purpose of illuminating the targets with the entire azimuth antenna pattern (AAP). This azimuth sweeping introduces an extra high-frequency Doppler term into the impulse response function (IRF), which poses a more strict coregistration accuracy for the interferometric purpose. A 1/1000 pixel coregistration accuracy is required for the interferometric phase error to be negligible, and the enhanced spectral diversity (ESD) method is applied for achieving such accuracy. However, since ESD derives miscoregistration from cross-interferometric phase, and phase is always wrapped to [ − π , π ) , an initial coregistration method with enough accuracy is required to resolve the phase ambiguity in ESD. The mainstream for initial coregistration that meets this requirement is the geometrical approach, which accuracy mainly depends on the accuracy of orbits. In this article, the authors propose to investigate the feasibility of using the conventional coregistration approach, namely the cross-correlation-and-rigid-transformation, as the initial coregistration method. The aim is to quantify the coregistration accuracy for cross-correlation-and-rigid-transformation using the Cramér-Rao lower bound (CRLB) and determine whether this method could eventually help to resolve the phase ambiguities of ESD. In addition, we studied the feasibility and robustness of the cross-correlation plus ESD under different conditions. For validation, we checked whether the cross-correlation plus ESD approach could reach the same coregistration accuracy as geometrical plus ESD approach. In general, for large areas with enough coherence and little topography variance, the cross-correlation method could be used as an alternative to the geometrical approach. The interferogram from the two different approaches (with ESD applied afterward) shows a negligible difference under such circumstances.

scholarly journals The cross-correlation analysis in Z source GX 349+2

2015 ◽  
Vol 455 (3) ◽  
pp. 2959-2968 ◽  
Author(s):  
G. Q. Ding ◽  
W. Y. Zhang ◽  
Y. N. Wang ◽  
Z. B. Li ◽  
J. L. Qu ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Cross Correlation ◽  
Cross Correlation Analysis ◽  
The Cross

scholarly journals Speckle Cross-Correlation Method in Measuring Fine Surface Displacements

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
M. Bahrawi ◽  
N. Farid ◽  
M. Abdel-Hady
Keyword(s):  
Cross Correlation ◽  
Correlation Method ◽  
Industrial Applications ◽  
Correlation Technique ◽  
Surface Displacements ◽  
Speckle Patterns ◽  
The Cross ◽  
And Performance ◽  
The Stability ◽  
Cross Correlation Technique

Industrial applications need regular testing for the lifetime, movement, strength, and performance of manufacturing machines during production process. Since speckle photography is a simple economic technique, it is used in investigating object response under mechanical and thermal effects depending on the movement of the speckle patterns with respect to the deformation strength and direction. In the present work, the cross-correlation technique is used to analyze the speckle patterns by iterative method to define both values and directions of rigid body translation and expansion. In order to check the accuracy of the cross-correlation technique, the results are compared with the displacement values given by analyzing the Young's interference fringes resulted from the Fourier transformation of the speckle patterns. This noncontact technique is found to be accurate and informative depending on the stability and sensitivity of the optical system. This method of measurement is an effective tool in studying the hard cases of objects and machines under various effects.

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