AN ANALOG SEISMlC CORRELATOR

Geophysics ◽  
1961 ◽  
Vol 26 (3) ◽  
pp. 298-308 ◽  
Author(s):  
F. N. Tullos ◽  
L. C. Cummings
Keyword(s):  
Seismic Data ◽  
Cross Correlation ◽  
Correlation Coefficients ◽  
Analog Computer ◽  
Signal Power ◽  
Arrival Times ◽  
Data Points ◽  
The Cross ◽  
Correlation Process ◽  
Total Average

An analog computer has been built to compute the cross‐correlation coefficients of multi‐trace seismograms. The evaluation program has shown that the computer has greater accuracy than is normally required to compute the cross‐correlation functions of short samples of data. Points on the correlation curves are computed and plotted at the rate of approximately 50 points per minute. Scanning is in difference of arrival times (Δt) across the record, with increments of [Formula: see text] to 16 millisecond. The correlation process is completely automatic with the exception of normalization, which is approximated by holding the total average signal power constant with a ganged attenuator. Analysis of synthetic and actual seismic data indicates that the correlation will be an interpretational aid in areas where the data are poor.

scholarly journals DrumCorr program for selecting volcanic earthquake multiplets based on cross-correlation analysis

2021 ◽  
Vol 2094 (3) ◽  
pp. 032048
Author(s):  
I A Zavedevkin ◽  
A A Shakirova ◽  
P P Firstov
Keyword(s):  
Seismic Data ◽  
Cross Correlation ◽  
Correlation Coefficients ◽  
Volcanic Earthquake ◽  
Primary Analysis ◽  
Volcanic Earthquakes ◽  
Cross Correlation Analysis ◽  
Wave Forms ◽  
The Cross ◽  
Correlation Detector

Abstract The DrumCorr program based on cross-correlation detection has been developed to identify multiplets of the volcanic earthquakes. The program is implemented in Python 3 and reads ASCII and MiniSEED seismic data formats. The article presents the algorithm of the program, describing the cross-correlation detector and an example of subsequent processing of seismic data. The program was applied to volcanic earthquakes of the «drumbeats» seismic regime and allowed to identify earthquake multiplets characterized by various wave forms. The article presents the algorithm of the program, describing the cross-correlation detector, the features of the weak volcanic earthquakes selection by the STA/LTA method. And the primary analysis of the values of the correlation coefficients with the calculation of their standard errors depending on different signal-to-noise ratios.

scholarly journals Insights to enhance the examination of tool marks in human cartilage

2021 ◽  
Author(s):  
Matthias Weber ◽  
Anja Niehoff ◽  
Markus A. Rothschild
Keyword(s):  
Light Microscope ◽  
Cross Correlation ◽  
Costal Cartilage ◽  
Correlation Coefficients ◽  
Human Cartilage ◽  
Cut Marks ◽  
Tool Marks ◽  
The Cross ◽  
Cleaning Methods ◽  
The Individual

AbstractThis work deals with the examination of tool marks in human cartilage. We compared the effectiveness of several cleaning methods on cut marks in porcine cartilage. The method cleaning by multiple casts achieved the significantly highest scores (P = 0.02). Furthermore, we examined the grain-like elevations (dots) located on casts of cut cartilage. The results of this study suggest that the casting material forms these dots when penetrating cartilage cavities, which are areas where the strong collagen fibres leave space for the chondrocytes. We performed fixation experiments to avoid this, without success. In addition, 31 casting materials were compared regarding contrast under light-microscope and 3D tool marks scanner. Under the light-microscope, brown materials achieved significantly higher values than grey (P = 0.02) or black (P = 0.00) whereas under the 3D scanner, black materials reached higher contrast values than grey (P = 0.04) or brown (P = 0.047). To compare the accuracy and reproducibility of 6 test materials for cartilage, we used 10 knives to create cut marks that were subsequently scanned. During the alignment of the individual signals of each mark, the cross-correlation coefficients (Xmax) and lags (LXmax) were calculated. The signals of the marks in agarose were aligned with significantly fewer lags and achieved significantly higher cross-correlation coefficients compared to all tested materials (both P = 0.00). Moreover, we determined the cross-correlation coefficients (XC) for known-matches (KM) per material. Agarose achieved significantly higher values than AccuTrans®, Clear Ballistics™, and gelatine (all P = 0.00). The results of this work provide valuable insights for the forensic investigation of marks in human costal cartilage.

scholarly journals Advancements of the examination of tool marks in human cartilage

2021 ◽  
Author(s):  
Matthias Weber ◽  
Anja Niehoff ◽  
Markus A. Rothschild
Keyword(s):  
Light Microscope ◽  
Cross Correlation ◽  
Costal Cartilage ◽  
Correlation Coefficients ◽  
Human Cartilage ◽  
Cut Marks ◽  
Tool Marks ◽  
The Cross ◽  
Cleaning Methods ◽  
The Individual

Abstract This work deals with the examination of tool marks in human cartilage. We compared the effectiveness of several cleaning methods on cut marks in porcine cartilage. The method cleaning by multiple casts achieved the significantly highest scores (P = 0.02). Furthermore, we examined the grain-like elevations (dots) located on casts of cut cartilage. The results of this study suggest that the casting material forms these dots when penetrating cartilage cavities, which are areas where the strong collagen fibers leave space for the chondrocytes. We performed fixation experiments to avoid this, without success. In addition, 31 casting materials were compared regarding contrast under light-microscope and 3D tool marks scanner. Under the light-microscope, brown materials achieved significantly higher values than grey (P = 0.02) or black (P = 0.00) whereas under the 3D scanner, black materials reached higher contrast values than grey (P = 0.04) or brown (P = 0.047). To compare the accuracy and reproducibility of 6 test materials for cartilage, we used 10 knives to create cut marks that were subsequently scanned. During the alignment of the individual signals of each mark, the cross-correlation coefficients (Xmax) and lags (LXmax) were calculated. The signals of the marks in agarose were aligned with significantly fewer lags and achieved significantly higher cross-correlation coefficients compared to all tested materials (both P = 0.00). Moreover, we determined the cross-correlation coefficients (XC) for known-matches (KM) per material. Agarose achieved significantly higher values than AccuTrans®, Clear Ballistics™, and gelatine (all P = 0.00). The results of this work provide valuable insights for the forensic investigation of marks in human costal cartilage.

Research on Feature Recognition of Nuclear Power Equipment Based on the Optimal Wavelet Basis

2013 ◽  
Author(s):  
Bin Li ◽  
Hong Xia
Keyword(s):  
Nuclear Power ◽  
Cross Correlation ◽  
Feature Recognition ◽  
Correlation Coefficients ◽  
Frequency Component ◽  
Discrete Wavelet ◽  
Wavelet Basis ◽  
Cracked Rotor ◽  
Coolant Pump ◽  
The Cross

Touching upon that the crack fault of the rotor may occur after the reactor coolant pump (RCP) has operated a long time, the fault feature can be identified effectively by the method of the wavelet analysis. In this research, based on the simulation signal of crack fault and the method of discrete wavelet transform (DWT), the cross-correlation coefficients between the fault signal and the different wavelet basis which are selected from the wavelet basis library can be computed. After confirming the maximum of the cross-correlation coefficients, the optimal wavelet basis applied to the fault signal of the cracked rotor will be found. And the main frequency component of the fault feature is recognized by use of the wavelet packet transform (WPT) based on the optimal wavelet basis. The results of simulation illustrate that the wavelet basis selected by the maximum cross-correlation coefficients can become the optimal wavelet basis, and the fault feature of the cracked rotor can be recognized effectively.

ON THE APPLICATION OF THE CROSS-CORRELATIONS IN THE CHINESE FUND MARKET: DESCRIPTIVE PROPERTIES AND SCALING BEHAVIORS

2011 ◽  
Vol 14 (01) ◽  
pp. 97-109
Author(s):  
WEIBING DENG ◽  
WEI LI ◽  
XU CAI ◽  
QIUPING A. WANG
Keyword(s):  
Correlation Matrix ◽  
Cross Correlation ◽  
Matrix Theory ◽  
Factorial Moment ◽  
Correlation Coefficients ◽  
Mean Value ◽  
Distribution Of Eigenvalues ◽  
Cross Correlations ◽  
The Cross ◽  
Simple Definition

On the basis of the relative daily logarithmic returns of 88 different funds in the Chinese fund market (CFM) from June 2005 to October 2009, we construct the cross-correlation matrix of the CFM. It is shown that the logarithmic returns follow an exponential distribution, which is commonly shared by some emerging markets. We hereby analyze the statistical properties of the cross-correlation coefficients in different time periods, such as the distribution, the mean value, the standard deviation, the skewness and the kurtosis. By using the method of the scaled factorial moment, we observe the intermittence phenomenon in the distribution of the cross-correlation coefficients. Also by employing the random matrix theory (RMT), we find a few isolated large eigenvalues of the cross-correlation matrix, and the distribution of eigenvalues exhibits the power-law tails. Furthermore, we study the features of the correlation strength with a simple definition.

Changes in Kinematic Coupling Among the Rearfoot, Midfoot, and Forefoot Segments During Running and Walking

2018 ◽  
Vol 108 (1) ◽  
pp. 45-51 ◽  
Author(s):  
Tomoya Takabayashi ◽  
Mutsuaki Edama ◽  
Erika Yokoyama ◽  
Chiaki Kanaya ◽  
Takuma Inai ◽  
...  
Keyword(s):  
Cross Correlation ◽  
Three Dimensional ◽  
Correlation Coefficients ◽  
Frontal Plane ◽  
Vector Coding ◽  
Kinematic Coupling ◽  
Foot Model ◽  
The Cross ◽  
Coupling Angle ◽  
Rearfoot Eversion

Background: Understanding the concept of kinematic coupling is essential when selecting the appropriate therapeutic strategy and grasping mechanisms for the occurrence of injuries. A previous study reported that kinematic coupling between the rearfoot and shank during running and walking were different. However, because foot mobility involves not only the rearfoot but also the midfoot or forefoot, kinematic coupling is likely to occur among the rearfoot, midfoot, and forefoot segments. We investigated changes in kinematic coupling among the rearfoot, midfoot, and forefoot segments during running and walking. Methods: Ten healthy young men were instructed to run (2.5 ms–1) and walk (1.3 ms–1) on a treadmill at speeds set by the examiner. The three-dimensional joint angles of the rearfoot, midfoot, and forefoot were calculated based on the Leardini foot model Kinematic coupling was evaluated with the absolute value of the cross-correlation coefficients and coupling angles obtained by using a vector coding technique. Results: The cross-correlation coefficient between rearfoot eversion/inversion and midfoot dorsiflexion/plantarflexion was significantly higher during running (r = 0.79) than during walking (r = 0.58), suggesting that running requires stronger kinematic coupling between rearfoot eversion/inversion and midfoot plantarflexion/dorsiflexion than walking. Furthermore, the coupling angle between midfoot eversion/inversion and forefoot eversion/inversion was significantly less during running (30.0°) than during walking (40.7°) (P < .05). Hence, the magnitude of midfoot frontal plane excursion during running was greater than that during walking. Conclusions: Excessive rearfoot eversion during running is likely to lead to excessive midfoot dorsiflexion, and such abnormal kinematic coupling between the rearfoot and midfoot may be associated with mechanisms for the occurrence of injuries.

scholarly journals A semi-automatic approach to identify first arrival time: the Cross-Correlation Technique

2015 ◽  
Vol 18 (2) ◽  
pp. 107-113 ◽  
Author(s):  
Mustafa Senkaya ◽  
Hakan Karslı
Keyword(s):  
Cross Correlation ◽  
Seismic Refraction ◽  
Correlation Technique ◽  
Arrival Times ◽  
Refraction Tomography ◽  
First Arrival ◽  
The Cross ◽  
Seismic Refraction Data ◽  
Cross Correlation Technique ◽  
Refraction Data

<p class="MsoNormal" style="line-height: 200%;">The high-quality interpretation of seismic refraction data depends on the accurate and reliable identification of the first arrival times. First arrivals can be identified on a graphic or image by conventional picking, but this process depends on external factors, such as the scale and quality of the imaging data, amplitude ratio, sensitivity of the picking cursor and user experience. Under these considerations, identifying first arrivals in noisy data becomes more complex and unstable. In this study, the Cross-Correlation Technique (CCT), which is widely used in the process of analyzing reflection data, has been used to pick the first arrival times in noisy or noiseless seismic refraction data by a semi-automatic process. The CCT has reduced the dependence on user and decreased incorrect picking caused by environmental noise, displaying characteristics and scaling factors. The CCT has been tested with synthetic models with different noise contents and various field data. The Chi-square error criterion was used to assess the performance of the pickings. In addition, effects of small-time differences between the conventional picking process and the CCT have been demonstrated on a refraction tomography velocity section. Therefore, we believe that our proposed method is a useful contribution to the existing methods of first arrival picking.</p><p class="MsoNormal" style="line-height: 200%;"> </p><p class="MsoNormal" style="line-height: 200%;"><strong>Resumen</strong></p><p class="MsoNormal" style="line-height: 200%;">La buena interpretación de datos estadísticos de refracción sísmica depende de la identificación acertada y confiable de los tiempos de llegada. Los primeros tiempos de llegada se pueden identificar en un gráfico o imagen por picado convencional, pero este proceso depende de factores externos como la escala y la calidad de información de la imagen, el índice de amplitud, la sensibilidad del cursor de recolección y la experiencia del usuario. Bajo estas consideraciones, la identificación de los tiempos de llegada bajo información ruidosa se vuelve más compleja e inestable. En este estudio, la técnica de Correlación Cruzada (CCT, en inglés), que es ampliamente trabajada en el proceso de análisis de datos de reflexión, se utilizó para seleccionar los primeros tiempos de llegada en información sísmica ruidosa o no ruidosa con un proceso semiautomático. La CCT redujo la dependencia en el usuario y bajó el nivel de selección incorrecta causada por el ruido ambiental al desplegar características y factores de escala. La CCT se ha probado en modelos sintéticos con diferentes contenidos de ruidos y diversa información de campo. El error de la norma Chi-cuadrado se utilizó para evaluar el desempeño de las selecciones. En adición, los efectos de las pequeñas diferencias de tiempo entre el proceso convencional de selección y la CCT se han demostrado en una tomografía reflexiva de velocidad. Además, se estima que el método propuesto es una contribución útil a los métodos existentes de la recolección de los primeros tiempos de llegada.</p>

scholarly journals FAULT LOCATION ON A DISTRIBUTION FEEDER USING FAULT GENERATED HIGH FREQUENCY CURRENT SIGNATURES

2017 ◽  
Vol 25 (2) ◽  
pp. 191-203
Author(s):  
Hashim Hizam ◽  
P.A. Crossley
Keyword(s):  
High Frequency ◽  
Fault Location ◽  
Cross Correlation ◽  
Travelling Waves ◽  
High Frequency Current ◽  
Single Location ◽  
Distribution Feeder ◽  
The Cross ◽  
Correlation Process ◽  
Frequency Current

This paper describes how the fault generated travelling waves detected in the current signals at a single location on a distribution feeder can be used for fault location. The method identifies the fault section and the probable location of the fault by comparing the relative distance of each “peak” in the high frequency current signals to the known reflection points in the distribution feeder. The probable fault location is then used within a transient power system simulator that models the actual network. The resulting simulated current waveforms are then cross-correlated against the original signal. If the estimated fault location is correct, the high frequency signatures in the simulated waveform will be similar to those of the measured waveforms and the cross-correlation value will be a high positive value. If the signatures differ, the cross correlation value  will be negative or small. The simulation and correlation process is repeated with the next “most likely” fault location until a high degree of correlation is obtained. Simulation studies using PSCAD/EMTDC and analysis using cross-correlation suggest that this method can accurately locate a fault on a distribution feeder using measurements at a single location.      

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