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 A Novel Gesture Recognition System Based on CSI Extracted from a Smartphone with Nexmon Firmware

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 222
Author(s):  
Tao Li ◽  
Chenqi Shi ◽  
Peihao Li ◽  
Pengpeng Chen
Keyword(s):  
Frequency Domain ◽  
Gesture Recognition ◽  
Channel State Information ◽  
Cross Correlation ◽  
Recognition Accuracy ◽  
Correlation Method ◽  
Bottom Layer ◽  
Recognition System ◽  
Channel State ◽  
State Information

In this paper, we propose a novel gesture recognition system based on a smartphone. Due to the limitation of Channel State Information (CSI) extraction equipment, existing WiFi-based gesture recognition is limited to the microcomputer terminal equipped with Intel 5300 or Atheros 9580 network cards. Therefore, accurate gesture recognition can only be performed in an area relatively fixed to the transceiver link. The new gesture recognition system proposed by us breaks this limitation. First, we use nexmon firmware to obtain 256 CSI subcarriers from the bottom layer of the smartphone in IEEE 802.11ac mode on 80 MHz bandwidth to realize the gesture recognition system’s mobility. Second, we adopt the cross-correlation method to integrate the extracted CSI features in the time and frequency domain to reduce the influence of changes in the smartphone location. Third, we use a new improved DTW algorithm to classify and recognize gestures. We implemented vast experiments to verify the system’s recognition accuracy at different distances in different directions and environments. The results show that the system can effectively improve the recognition accuracy.

scholarly journals RECOGNIZING DIFFERENT TYPES OF STOCHASTIC PROCESSES

2006 ◽  
Vol 06 (01) ◽  
pp. L1-L6
Author(s):  
JONG U. KIM ◽  
LASZLO B. KISH
Keyword(s):  
Image Processing ◽  
Stochastic Processes ◽  
Cross Correlation ◽  
Correlation Method ◽  
Correlation Coefficients ◽  
Power Density Spectrum ◽  
Density Spectrum ◽  
Random Telegraph Signals ◽  
Different Types ◽  
Coefficient Method

We propose a new cross-correlation method that can recognize independent realizations of the same type of stochastic processes and can be used as a new kind of pattern recognition tool in biometrics, sensing, forensic, security and image processing applications. The method, which we call bispectrum correlation coefficient method, makes use of the cross-correlation of the bispectra. Three kinds of cross-correlation coefficients are introduced. To demonstrate the new method, six different random telegraph signals are tested, where four of them have the same power density spectrum. It is shown that the three coefficients can map the different stochastic processes to specific sub-volumes in a cube.

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