scholarly journals Performance Evaluation of Traditional Signal Processing Methods in Localizing Tursiops truncatus Whistles in a Reverberant Aquatic Environment

2019 ◽  
Author(s):  
SF Woodward ◽  
MO Magnasco
Keyword(s):  
Signal Processing ◽  
Aquatic Environment ◽  
Tursiops Truncatus ◽  
Cross Correlation ◽  
Correlation Method ◽  
Extraction Methods ◽  
Phase Transform ◽  
Atlantic Bottlenose Dolphin ◽  
Signature Whistles ◽  
Signal Processing Methods

AbstractRelative to individually distinctive signature whistles, little is known about the “non-signature” calls – particularly the non-signature whistles – of the common Atlantic bottlenose dolphin, Tursiops truncatus. While such calls are suspected to serve social function, tracking their exchange among conspecifics and correlating their usage with non-acoustic behavior has proven challenging, given both their relative scarcity in the dolphin repertoire and their characteristic shared use among dolphins, which precludes the unique identification of callers on the basis of whistle properties alone. Towards the goal of robustly identifying the callers of non-signature whistles (equivalently, attributing non-signature whistles to callers), we present a new, long-term audiovisual monitoring system designed for and tested at the Dolphin Discovery exhibit of the National Aquarium in Baltimore, Maryland. In this paper, we confirm the system’s ability to spatially localize impulse-like sounds using traditional signal processing approaches that have already been used to localize dolphin echolocation clicks. We go on to provide the first rigorous experimental evaluation of the component time-difference-of-arrival-(TDOA) extraction methods on whistle-like tonal sounds in a (reverberant) aquatic environment, showing that they are generally not suited to sound localization. Nevertheless, we find that TDOA extraction under these circumstances is performed significantly better using a Generalized Cross-Correlation with Phase Transform (GCC-PHAT) method than a standard circular cross-correlation method, a potentially important result.

scholarly journals Phase and Frequency Matching-based Signal Processing Method for Coriolis Mass Flowmeters

2016 ◽  
Vol 16 (2) ◽  
pp. 62-67 ◽  
Author(s):  
Yaqing Tu ◽  
Yanlin Shen ◽  
Haitao Zhang ◽  
Ming Li
Keyword(s):  
Signal Processing ◽  
Phase Difference ◽  
Cross Correlation ◽  
Measurement Accuracy ◽  
Frequency Estimation ◽  
Correlation Method ◽  
Processing Method ◽  
Transform Method ◽  
Frequency Matching ◽  
Signal Processing Method

AbstractSignal processing precision of Coriolis mass flowmeters affects the measurement accuracy directly. To improve the measurement accuracy of Coriolis mass flowmeters, a phase and frequency matching-based signal processing method for Coriolis mass flowmeters is proposed. Estimated phase difference is obtained by means of frequency estimation, 90° phase shift, generating reference signals and cross-correlation. Simulated results demonstrate that the proposed method has better phase difference estimation and anti-interference performance than the Hilbert transform method, cross-correlation method, data extension-based correlation method, and quadrature delay estimator. Measurement results of Coriolis mass flowmeters verify the effectiveness and superiority of the proposed method in practice.

scholarly journals Application of Vibration Signal Processing Methods to Detect and Diagnose Wheel Flats in Railway Vehicles

2021 ◽  
Vol 11 (5) ◽  
pp. 2151
Author(s):  
JaeSeok Shim ◽  
GeoYoung Kim ◽  
ByungJin Cho ◽  
JeongSeo Koo
Keyword(s):  
Signal Processing ◽  
Cross Correlation ◽  
Vibration Signal ◽  
Analysis Method ◽  
Order Analysis ◽  
Cepstrum Analysis ◽  
Cross Correlation Analysis ◽  
Train Speed ◽  
Wheel Flat ◽  
Signal Processing Methods

This paper studied two useful vibration signal processing methods for detection and diagnosis of wheel flats. First, the cepstrum analysis method combined with order analysis was applied to the vibration signal to detect periodic responses in the spectrum for a rotating body such as a wheel. In the case of railway vehicles, changes in speed occur while driving. Thus, it is difficult to effectively evaluate the flat signal of the wheel because the time cycle of the flat signal changes frequently. Thus, the order analysis was combined with the existing cepstrum analysis method to consider the changes in train speed. The order analysis changes the domain of the vibration signal from time domain to rotating angular domain to consider the train speed change in the cepstrum analysis. Second, the cross correlation analysis method combined with the order analysis was applied to evaluate the flat signal from the vibration signal well containing the severe field noise produced by the vibrations of the rail irregularities and bogie components. Unlike the cepstrum analysis method, it can find out the wheel flat size because the flat signal linearly increases to the wheel flat. Thus, it is more effective when checking the size of the wheel flat. Finally, the data tested in the Korea Railroad Research Institute were used to confirm that the cepstrum analysis and cross correlation analysis methods are appropriate for not only simulation but also test data.

scholarly journals Study on time delay estimation in boiler acoustic temperature measurement based on third correlation PHAT-β

2021 ◽  
Vol 257 ◽  
pp. 01025
Author(s):  
Mianmian Wang ◽  
Wenhong Liu ◽  
Keni Xu
Keyword(s):  
Time Delay ◽  
Power Plant ◽  
Cross Correlation ◽  
Correlation Method ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Value Of Time ◽  
Phase Transform ◽  
Power Plant Boiler ◽  
Plant Boiler

In order to accurately measure the temperature of power plant boiler, a new algorithm of time delay was proposed based on third correlation and phase transform weighting on the basis of the research of traditional cross-correlation method and generalized cross-correlation. Small peaks can be weakened with the help of phase transform weighting and the addition of exponential coefficient β. The simulation result shows that the PHAT-β algorithm based on third correlation can accurately measure the value of time delay estimation compared with first correlation, second correlation and traditional third correlation, so as to improve the accurancy of temperature of power plant boiler.

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.

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