Debris flow velocity estimation: a comparison between gradient-based method and cross-correlation method

2002 ◽  
Author(s):  
Mohammad S. Uddin ◽  
Hiroyuki Inaba ◽  
Yasuo Yoshida ◽  
Yasumasa Itakura
Keyword(s):  
Debris Flow ◽  
Flow Velocity ◽  
Cross Correlation ◽  
Correlation Method ◽  
Velocity Estimation ◽  
Gradient Based

scholarly journals Debris-flow velocity and volume estimations based on seismic data

2021 ◽  
Author(s):  
Andreas Schimmel ◽  
Velio Coviello ◽  
Francesco Comiti
Keyword(s):  
Debris Flow ◽  
Flow Velocity ◽  
Seismic Data ◽  
Debris Flows ◽  
Cross Correlation ◽  
Sampling Rate ◽  
Early Warning Systems ◽  
Velocity Estimation ◽  
Mitigation Measures ◽  
Strong Control

Abstract. The estimation of debris-flow velocity and volume is a fundamental task for the development of early warning systems, the design of control structures and other mitigation measures. Previous analysis of the seismic energy produced by debris flows showed that the peak amplitudes are representative of the kinetic energy of each surge and debris-flow discharge can be therefore estimated based on seismic signals. Also, the debris-flow velocity can be calculated using seismic data recorded at two spatial separated stations located along the channel by the use of cross-correlation. This work provide a first approach for estimating the total volume of debris flows based on the seismic signal detected with simple, low-cost geophones installed along the debris-flow channel. The developed methods was applied to seismic data collected on three different test sites in the Alps: Gadria (IT), Lattenbach (AT), and Cancia (IT). An adaptable cross-correlation time window was used, which can offer a better estimation of the velocity compared to a constant window length. The analyses of the seismic data of 14 debris flows that occurred from 2014 to 2018 shows the strong control of the sampling rate and the sensor-distance on the velocity estimation. A simple approach based on a linear relation between square of the seismic amplitude and the event magnitude is proposed for a first order estimation of the debris-flow magnitude.

Measurement of Flow Velocity in Diesel Flames by a Cross-Correlation Method

1982 ◽  
Author(s):  
T. Kamimoto ◽  
Y. Miyairi ◽  
K. Nagakura ◽  
S. Matsuoka
Keyword(s):  
Flow Velocity ◽  
Cross Correlation ◽  
Correlation Method

scholarly journals Датчик скорости потока жидкости на основе волоконных брэгговских решеток с индукционным нагревом

2021 ◽  
Vol 47 (17) ◽  
pp. 22
Author(s):  
А.В. Умнова ◽  
А.С. Алейник ◽  
В.Е. Стригалев ◽  
В.А. Новикова ◽  
А.Н. Аширов
Keyword(s):  
Flow Velocity ◽  
Induction Heating ◽  
Cross Correlation ◽  
Fiber Bragg Gratings ◽  
Correlation Method ◽  
Temperature Sensors ◽  
Heat Pulse ◽  
Experimental Results ◽  
Time Response ◽  
Velocity Range

The paper presents simulating and experimental results of flowmeter operation with induction heating, where fiber Bragg gratings were used as sensitive elements of temperature sensors. The operating principle of flowmeter based on cross-correlation method. During the experiment, it was detected time response of heat pulse from 0.2 s to 0.5 s that corresponds to a flow velocity range 0.1-0.5 m/s.

Performances of a High-Speed Impedance Camera for Flow Informatics

Volume 1 ◽  
2004 ◽  
Author(s):  
Y. Ma ◽  
M. Wang
Keyword(s):  
Image Reconstruction ◽  
Flow Velocity ◽  
Cross Sections ◽  
Digital Signal Processor ◽  
High Speed ◽  
Cross Correlation ◽  
Correlation Method ◽  
Digital Signal ◽  
Two Phase ◽  
Impedance Contrast

An impedance camera has been developed and optimized for visualization and measurement of two-phase flows. This camera, in its basic construction, can synchronously map two cross sections of a pipeline flow in time sequence, where the components of the flow have impedance contrast. Flow velocity distribution can be implemented from the two series of images using the cross-correlation method. The data capture, image reconstruction, concentration and velocity implementation, all are processed on-line using multi-digital signal processor built in the camera. This paper presents a part of test results regarding to the system major performances of the measurement repeatability, consistency of 16 parallel measurement channels, speeds of data acquisition, rate of image reconstruction and cross-correlation implementation, estimation of the discrimination error in flow velocity and flow rate measurements, etc.

The Measurement of Flow Rate in Mud Transporting Base on Cross-Correlation Method

2014 ◽  
Vol 687-691 ◽  
pp. 984-989
Author(s):  
Pan Jiang ◽  
Shi Dong Fan ◽  
Quan Wen
Keyword(s):  
Flow Velocity ◽  
Flow Rate ◽  
Cross Correlation ◽  
Correlation Method ◽  
Capacitive Sensor ◽  
High Accuracy ◽  
Electrical Capacitance Tomography ◽  
Electrical Capacitance ◽  
Actual Measurement ◽  
Capacitance Tomography

The paper using electrical capacitance tomography to test the flow velocity and flow rate of the mud transporting in the dredging.The testing process based on two 12 electrodes capacitive sensor sets (ie,the upstream and downstream sensors).The computer can gather the capacitance signals from the upstream and downstream sensor,then by the method of cross-correlation method it can calculate the flow velocity and flow rate of the mud in the slurry pipelines.In oader to verify the measurement error,the system measure the flow velocity and flow rate of the mud in the same situation at the different time (including five different time).Comparing the results of related calculations and the actual measurement it can prove that the cross-relation method is feasible and reliable,the tesing result have high accuracy.

Application of cross correlation to HREM images of surfaces

1987 ◽  
Vol 45 ◽  
pp. 754-755
Author(s):  
D. E. Luzzi ◽  
L. D. Marks ◽  
M. I. Buckett
Keyword(s):  
Cross Correlation ◽  
A Priori ◽  
Matrix Material ◽  
Correlation Method ◽  
Accurate Knowledge ◽  
Complex Image ◽  
Fourier Filtering ◽  
The Matrix ◽  
Low Pass ◽  
Data Reduction Technique

As the HREM becomes increasingly used for the study of dynamic localized phenomena, the development of techniques to recover the desired information from a real image is important. Often, the important features are not strongly scattering in comparison to the matrix material in addition to being masked by statistical and amorphous noise. The desired information will usually involve the accurate knowledge of the position and intensity of the contrast. In order to decipher the desired information from a complex image, cross-correlation (xcf) techniques can be utilized. Unlike other image processing methods which rely on data massaging (e.g. high/low pass filtering or Fourier filtering), the cross-correlation method is a rigorous data reduction technique with no a priori assumptions.We have examined basic cross-correlation procedures using images of discrete gaussian peaks and have developed an iterative procedure to greatly enhance the capabilities of these techniques when the contrast from the peaks overlap.

Cross-Correlation Method for the Formation of Laser Energy Fields with Complex Distributions

2013 ◽  
Vol 58 (2) ◽  
pp. 122-125 ◽  
Author(s):  
O.V. Gnatovskyy ◽  
◽  
A.M. Negriyko ◽  
V.O. Gnatovskyy ◽  
A.V. Sidorenko ◽  
...  
Keyword(s):  
Cross Correlation ◽  
Laser Energy ◽  
Correlation Method

scholarly journals Flow velocity quantification by exploiting the principles of the Doppler effect and magnetic particle imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dennis Pantke ◽  
Florian Mueller ◽  
Sebastian Reinartz ◽  
Fabian Kiessling ◽  
Volkmar Schulz
Keyword(s):  
Flow Velocity ◽  
Magnetic Particle ◽  
Imaging Techniques ◽  
Radiation Risk ◽  
Medical Application ◽  
Velocity Estimation ◽  
Magnetic Particle Imaging ◽  
Measurable Velocity ◽  
Depth Dependency ◽  
Particle Imaging

AbstractChanges in blood flow velocity play a crucial role during pathogenesis and progression of cardiovascular diseases. Imaging techniques capable of assessing flow velocities are clinically applied but are often not accurate, quantitative, and reliable enough to assess fine changes indicating the early onset of diseases and their conversion into a symptomatic stage. Magnetic particle imaging (MPI) promises to overcome these limitations. Existing MPI-based techniques perform velocity estimation on the reconstructed images, which restricts the measurable velocity range. Therefore, we developed a novel velocity quantification method by adapting the Doppler principle to MPI. Our method exploits the velocity-dependent frequency shift caused by a tracer motion-induced modulation of the emitted signal. The fundamental theory of our method is deduced and validated by simulations and measurements of moving phantoms. Overall, our method enables robust velocity quantification within milliseconds, with high accuracy, no radiation risk, no depth-dependency, and extended range compared to existing MPI-based velocity quantification techniques, highlighting the potential of our method as future medical application.

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