Fault detection of damper in railway vehicle suspension based on the cross-correlation analysis of bogie accelerations

2019 ◽  
Vol 20 (1) ◽  
pp. 102 ◽  
Author(s):  
Mădălina Dumitriu
Keyword(s):  
Fault Detection ◽  
Numerical Simulations ◽  
Cross Correlation ◽  
Fault Detection And Isolation ◽  
Condition Based Maintenance ◽  
Normal Operation ◽  
Railway Vehicle ◽  
Operation Condition ◽  
Cross Correlation Analysis ◽  
The Cross

Nowadays, the condition-based maintenance is associated more and more with railway transport to improve the safety, availability, reliability and capacity of this transport system, and to reduce life cycle costs for the railway vehicles. The condition-based maintenance requires that vehicle components are replaced based on their real condition, which implies the fault detection and isolation during the train's operation. The paper proposes a method to detect the failure of the damper in the primary suspension of the rail vehicle, based on the analysis of cross-correlation of the vertical accelerations measured on the bogie frame against the two axles. The numerical simulations and experimental results show a very good correlation between the bogie accelerations when the dampers are in a normal operation condition. This thing is shown based on the values of the cross-correlation coefficient (CCC) of the bogie accelerations. The failure in a damper can be detected by the decrease of the CCC of the bogie accelerations, a confirmed fact in the results derived from numerical simulations. The proposed method has more advantages, namely, it is a signal-based method and hence does not require a complex mathematical modelling of the vehicle-track system and knowledge of its parameters or of the external conditions; the method makes relative comparisons between measurements and hence reduces the effect of the factors that influence outputs; the method can be also extended for the secondary suspension; the method can be easily implemented on any type of bogie.

Analyzing the Impact of COVID-19 on the Cross-Correlations between Financial Search Engine Data and Movie Box Office

2020 ◽  
pp. 2150021
Author(s):  
Renyu Wang ◽  
Yujie Xie ◽  
Hong Chen ◽  
Guozhu Jia
Keyword(s):  
Financial Market ◽  
Cross Correlation ◽  
Multifractal Spectrum ◽  
Movie Industry ◽  
Box Office ◽  
Cross Correlation Analysis ◽  
Cross Correlations ◽  
The Cross ◽  
Google Search ◽  
The Impact

This paper explores the COVID-19 influences on the cross-correlation between the movie market and the financial market. The nonlinear cross-correlations between movie box office data and Google search volumes of financial terms such as Dow Jones Industrial Average (DJIA), NASDAQ and PMI are investigated based on multifractal detrended cross-correlation analysis (MF-DCCA). The empirical results show there are nonlinear cross-correlations between movie market and financial market. Metrics such as Hurst exponents, singular exponents and multifractal spectrum demonstrate that the cross-correlation between movie market and financial market is persistent, and the cross-correlation in long term is more stable than that in short term. In the COVID-19 period, the multifractal features of cross-correlation become stronger implying that COVID-19 enhanced the complexity between the movie industry and the financial market. Furthermore, through the rolling window analysis, the Hurst exponent dynamic trends indicate that COVID-19 has a clear influence on the cross-correlation between movie market and financial market.

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.

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.

scholarly journals Analysis of the transmembrane potential of embryos exposed to action of nickel, cobalt, tin and zinc

2018 ◽  
Vol 9 (2) ◽  
pp. 216-222
Author(s):  
G. V. Galyk ◽  
Z. Y. Fedorovych ◽  
E. I. Lychkovsky ◽  
D. I. Sanagursky
Keyword(s):  
Correlation Functions ◽  
Cross Correlation ◽  
Transmembrane Potential ◽  
Development Stage ◽  
Time Shift ◽  
Transmembrane Potentials ◽  
Nickel Cobalt ◽  
Cross Correlation Analysis ◽  
The Cross ◽  
Degree Of Similarity

Germ cells of aquatic organisms are complex systems whose growth and development depends on many factors, one of which is the composition of the aquatic environment. We used parameters in our analysis from aggregate data available from published literature. They are data of the transmembrane potential of the germinal cells of Misgurnus fossilis (Linnaeus, 1758) at the development stage from 180th to 360th minutes. Embryos were incubated in an environment with nickel, cobalt, tin, and zinc ions and without them. Plotted lines of the transmembrane potential were digitized and calibrated at intervals of 10 minutes. Rows of numerical values of the transmembrane potentials were obtained. These rows were used for calculation of autocorrelation and cross-cross-correlation functions. It was established that the transmembrane potential describes nonperiodic and quasi-periodic oscillations. The higher statistically significant values of the autocorrelation coefficients were observed in the first lags. Autocorrelation analysis indicates that the periods of oscillations of the transmembrane potential increase with the action of nickel, cobalt, tin and zinc on the germ. The phenomena and processes that occur in the germ cell are well reflected at the initial stages of the auto-correction and are lost when the magnitude of the lag increases. The degree of similarity of transmembrane potentials with the help of cross-correlation analysis is quantitatively characterized. The distribution of fluctuations of cross-correlation functions with complex dynamics, which arise with time shifts both in the forward and reverse directions, were established. It is established that for large values of time shifts, the cross-correlation coefficient is a low-informative indicator, since information about the influence of the factor on the living system is lost. A graph for a given time shift was constructed. The connection between the nodes is the magnitude of the cross-correlation coefficients between the vapor of the transmembrane potentials, which indicate the degree of similarity of the bioelectric processes. Graphs will be used for qualitative and quantitative study of system dynamics. The obtained results confirm the existence of a close relationship between environmental nickel, cobalt, tin, and zinc and the oscillation of transmembrane potential during early embryogenesis.

Dynamic Cross-Correlations between Investors’ Attention and CSI300 Index Futures

2019 ◽  
Vol 18 (04) ◽  
pp. 1950022
Author(s):  
Xiong Xiong ◽  
Kewei Xu ◽  
Dehua Shen
Keyword(s):  
Cross Correlation ◽  
Futures Market ◽  
Relative Activity ◽  
Short Term ◽  
Index Futures ◽  
Search Volume ◽  
Cross Correlation Analysis ◽  
Cross Correlations ◽  
The Cross

Using search volume on Baidu Index as the proxy for investors’ attention, we investigate the dynamic nonlinear relationship between investors’ attention and CSI300 index futures market. Multifractal detrend cross-correlation analysis (MF-DCCA) is employed to explore the multifractal features of the cross-correlations between investors’ attention and the return and relative activity of index futures market. We find that the power-law cross-correlations between investors’ attention and CSI300 index futures market are stronger in the short term than in the long term, and the cross-correlations are significantly multifractal. Precisely, the cross-correlation between abnormal search volume (ASV) and the relative activity is persistent, and the cross-correlation between ASV and return of IF is persistent in the short term but weakly anti-persistent in the long term. Besides, we also find that, with the restriction on index futures market, the cross-correlations between investors’ attention and CSI300 index futures market become less stable.

scholarly journals Multiwavelength cross-correlation analysis of the simulated cosmic web

2020 ◽  
Vol 494 (4) ◽  
pp. 5603-5618 ◽  
Author(s):  
C Gheller ◽  
F Vazza
Keyword(s):  
Faraday Rotation ◽  
Cross Correlation ◽  
Future Generation ◽  
Matter Distribution ◽  
X Ray ◽  
Galaxy Distribution ◽  
Cross Correlation Analysis ◽  
The Galaxy ◽  
The Cross ◽  
Diffuse Matter

ABSTRACT We used magnetohydrodynamical cosmological simulations to investigate the cross-correlation between different observables (i.e. X-ray emission, Sunyaev–Zeldovich (SZ) signal at 21 cm, H i temperature decrement, diffuse synchrotron emission, and Faraday Rotation) as a probe of the diffuse matter distribution in the cosmic web. We adopt a uniform and simplistic approach to produce synthetic observations at various wavelengths, and we compare the detection chances of different combinations of observables correlated with each other and with the underlying galaxy distribution in the volume. With presently available surveys of galaxies and existing instruments, the best chances to detect the diffuse gas in the cosmic web outside of haloes is by cross-correlating the distribution of galaxies with SZ observations. We also find that the cross-correlation between the galaxy network and the radio emission or the Faraday Rotation can already be used to limit the amplitude of extragalactic magnetic fields, well outside of the cluster volume usually explored by existing radio observations, and to probe the origin of cosmic magnetism with the future generation of radio surveys.

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 A qualitative study of the seismo-ionospheric precursors prior to the 6 April 2009 earthquake in L'Aquila, Italy

2010 ◽  
Vol 10 (1) ◽  
pp. 133-137 ◽  
Author(s):  
G. S. Tsolis ◽  
T. D. Xenos
Keyword(s):  
Correlation Coefficient ◽  
Cross Correlation ◽  
Seismic Event ◽  
Correlation Method ◽  
L’Aquila Earthquake ◽  
Earthquake Preparation ◽  
Mode Decomposition ◽  
Cross Correlation Analysis ◽  
Correlation Analysis Method ◽  
The Cross

Abstract. In this paper we use the Cross Correlation analysis method in conjunction with the Empirical Mode Decomposition to analyze foF2 signals collected from Rome, Athens and San Vito ionospheric stations, in order to verify the existence of seismo-ionospheric precursors prior to M=6.3 L'Aquila earthquake in Italy. The adaptive nature of EMD allows for removing the geophysical noise from the foF2 signals, and then to calculate the correlation coefficient between them. According to the cross correlation coefficient theory, we expect the stations which located inside the earthquake preparation area, as evaluated using Dobrovolsky equation, to capture the ionospheric disturbances generated by the seismic event. On the other hand the stations outside of this area are expected to remain unaffected. The results of our study are in accordance with the theoretical model, evidencing ionospheric modification prior to L'Aquila earthquake in a certain area around the epicenter. However, it was found that the selection of stations at the limits of the theoretically estimated earthquake preparation area is not the best choice when the cross correlation method is applied, since the modification of the ionosphere over these stations may not be enough for the ionospheric precursors to appear. Our experimental results also show that when a seismic event constitutes the main shock after a series of pre-seismic activity, precursors may appear as early as 22 days prior to the event.

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