Deferred time-frequency cross-correlation for EM source determination with one-port measurements

In this paper Wavelet Transform (WT) and Hilbert-Huang Transform (HHT) are used as bearing diagnostics tools in drives executing arbitrary motion profiles. This field is increasingly drawing the attention of the industries because the modern electric motors work as electric cams inducing the shaft to move with a cyclic variable-velocity profile. The literature papers take into account only a constant velocity profile and they are not suitable for such applications. In fact literature methods analyse the signal only in the frequency domain, while in variable-velocity condition the bearing diagnostics should be performed in time domain. Both WT and HHT are time-frequency techniques which describe an input signal as a sum of specific functions. These functions are compared with a signal which simulates the expected vibrations of a bearing with a given fault, e.g. on the outer race. The comparison is done through a cross-correlation between the expected signal and the time-frequency techniques output. WT and HHT are used separately in an industrial case, which consists in bearing fault prediction in an automated packaging machine. In the end of the paper the WT and HHT results are discussed to analyse the different responses.

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Cross-correlation time-frequency analysis for multiple EMG signals in Parkinson’s disease: a wavelet approach

Medical Engineering & Physics ◽

10.1016/s1350-4533(03)00034-1 ◽

2003 ◽

Vol 25 (5) ◽

pp. 361-369 ◽

Cited By ~ 39

Author(s):

Gennaro De Michele ◽

Stefano Sello ◽

Maria Chiara Carboncini ◽

Bruno Rossi ◽

Soo-Kyung Strambi

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Frequency Analysis ◽

Correlation Time ◽

Cross Correlation ◽

Time Frequency Analysis ◽

Time Frequency

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Investigation of the Rotating Stall in a Centrifugal Compressor

Volume 1: Fora, Parts A and B ◽

10.1115/fedsm2002-31113 ◽

2002 ◽

Cited By ~ 1

Author(s):

Longin Horodko ◽

Wladyslaw Kryllowicz

Keyword(s):

Cross Correlation ◽

Static Pressure ◽

Reverse Flow ◽

Time Lag ◽

Rotating Stall ◽

Driving System ◽

Time Frequency ◽

Frequency Representation ◽

Signal Time ◽

Oscillatory Pressure

Instability of the compressor operation is manifested in two forms: by mild or deep surge. Both of them should be avoided as they lead to reduced performance or serious damage to the machine and its driving system. One of the pre-surge symptoms is rotating stall that appears mainly in the impeller and transfers to other parts of the compressor. This phenomenon can be described as a rotating pressure wave arising and decaying intermittently. Such an irregularly changing object needs an analyzing tool that allows for a spectrum fluctuation study. The authors used the signal time-frequency representation with progressive wavelets to analyze the static pressure signals acquired during a few deep surge cycles. The rotating stall was identified with the cross-correlation of the continuous wavelet transform. The same method allowed for calculation of the time lag between oscillatory pressure signals coming from the diffuser and the inlet of the compressor, which estimates the reverse flow velocity.

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Wavelet cross-correlation and phase analysis of a free cantilever subjected to band excitation

Beilstein Journal of Nanotechnology ◽

10.3762/bjnano.3.33 ◽

2012 ◽

Vol 3 ◽

pp. 294-300 ◽

Cited By ~ 11

Author(s):

Francesco Banfi ◽

Gabriele Ferrini

Keyword(s):

Cross Correlation ◽

Relative Phase ◽

Correlation Technique ◽

Time Frequency ◽

Driver Response ◽

Impulsive Excitation ◽

The Common ◽

Frequency Map ◽

Cross Correlation Technique ◽

Driving Signal

This work introduces the concept of time–frequency map of the phase difference between the cantilever response signal and the driving signal, calculated with a wavelet cross-correlation technique. The wavelet cross-correlation quantifies the common power and the relative phase between the response of the cantilever and the exciting driver, yielding “instantaneous” information on the driver-response phase delay as a function of frequency. These concepts are introduced through the calculation of the response of a free cantilever subjected to continuous and impulsive excitation over a frequency band.

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CEREBRAL OXYGENATION AND PERIPHERAL OXIMETRY IN EXTREMELY PRETERM INFANTS WITH PULMONARY AND/OR CEREBRAL INTRAVENTRICULAR HEMORRHAGE IN THE FIRST 72 HOURS OF LIFE

Paediatrics & Child Health ◽

10.1093/pch/pxy054.056 ◽

2018 ◽

Vol 23 (suppl_1) ◽

pp. e22-e23

Author(s):

Thierry Beausoleil ◽

Marie Janaillac ◽

Keith Barrington ◽

Marie-Josée Raboisson ◽

Oliver Karam ◽

...

Keyword(s):

Oxygen Saturation ◽

Preterm Infants ◽

Premature Infants ◽

Cross Correlation ◽

Cerebral Oxygenation ◽

Invasive Monitoring ◽

Time Frequency ◽

Non Invasive ◽

Extremely Preterm ◽

Extremely Preterm Infants

Abstract BACKGROUND Extremely premature infants born <28 weeks of gestation are at higher risk of pulmonary (PH) and cerebral intraventricular (IVH) hemorrhage due to immature cardiovascular and transitioning physiology. Non-invasive monitoring has the potential to detect early abnormal circulation. OBJECTIVES To explore time-frequency relationships between cerebral oxygenation and peripheral oximetry. DESIGN/METHODS Near infrared spectroscopy cerebral regional haemoglobin oxygen saturation (CrSO2), preductal peripheral perfusion index (PI), heart rate (HR), capillary oxygen saturation (SpO2), and blood pressure (BP) were monitored in the first 72h of life. Patients were grouped in infants with PH and/or IVH (n=8) and controls (n=10). Signals were decomposed in wavelets allowing the analysis of localized variations of power. This approach allowed to quantify the common power and determine the duration of significant cross-correlation, phase and coherence between each pair of signals. Groups were compared with Wilcoxon tests. RESULTS Figure 1 shows an example of CrSO2 and PI, and their cross-correlation, phase (semblance) and coherence in a control (left column) and a PH-IVH patient (right column). Durations of significant cross-correlation between CrSO2 and HR (p<0.01), and CrSO2 and SpO2 (p=0.02) were significantly lower in PH-IVH infants compared to controls. The duration of significant anti-phase between CrSO2 and SpO2 (p=0.01) and the duration of significant coherence between PI and BP (p=0.03) were also significantly lower in PH-IVH infants compared to controls. These differences may indicate a disruption in auto-regulation, which is currently incompletely understood in this population. CONCLUSION This study is the first to apply time-frequency analysis to simultaneous NIRS and preductal peripheral oximetry in extremely preterm infants early in life. Significantly lower durations of cross-correlation (CrSO2 with HR and SpO2), anti-phase (CrSO2, SpO2) and coherence (PI, BP) in PH-IVH patients may reflect early abnormal circulation. Our results show the potential of non-invasive monitoring to identify premature infants at-risk of early PH-IVH.

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Relationship Between Knee Extensors Power Output and Vastus Lateralis EMG Activation in Elderly Women: Influence of Mother Wavelet Selection

The Open Sports Sciences Journal ◽

10.2174/1875399x01710010263 ◽

2017 ◽

Vol 10 (1) ◽

pp. 263-271

Author(s):

João Pedro Pinho ◽

Bruno Mezêncio ◽

Desidério Cano Porras ◽

Julio Cerca Serrão ◽

Alberto Carlos Amadio

Keyword(s):

Cross Correlation ◽

Elderly Women ◽

Vastus Lateralis ◽

Biceps Femoris ◽

Knee Extension ◽

Knee Extensors ◽

Mother Wavelet ◽

Time Frequency ◽

Wavelet Selection ◽

Mother Wavelets

Purpose:The main objective of this study was to compare frequency parameters produced by six mother wavelets pinpointing the most feasible to investigate electromyographic (EMG) parameters while producing knee extension power in elderly women. The influence of different load conditions in mother wavelet selection and power output were also analyzed.Methods:Thirteen sedentary elderly women (69.3 ± 4.1 years) took part in the study. Participants executed 6 repetitions of 3 load condition (30%, 50% and 70% of the maximal) with the concentric phase of the knee extension movement as quickly as possible. Kinematic data obtained by video analysis, an anthropometric model and Newtonian mechanics were used to calculate knee extensors’ power. A continuous wavelet analysis was used as a time-frequency transformation strategy of vastus lateralis and biceps femoris EMG data and six different mother wavelets were selected: Morlet; 4th, 8th and 44th order Daubechie, 4th order Coiflet and 5th order Symlet.Results:44th order Daubechie showed the highest maximal cross correlation value and no differences were seen between different mother wavelets and cross correlation at zero lag and in the lag variable. Although increased knee extensors peak power at higher loads were seen, no differences in vastus lateralis or biceps femoris root mean square values were obtained.Conclusion:44th order Daubechie mother wavelet was pinpointed as the most suitable to obtain EMG time-frequency parameters. We have also seen that different load conditions do not seem to have an influence on mother wavelet selection.

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CoViD-19, learning from the past: A wavelet and cross-correlation analysis of the epidemic dynamics looking to emergency calls and Twitter trends in Italian Lombardy region

PLoS ONE ◽

10.1371/journal.pone.0247854 ◽

2021 ◽

Vol 16 (2) ◽

pp. e0247854

Author(s):

Bruno Alessandro Rivieccio ◽

Alessandra Micheletti ◽

Manuel Maffeo ◽

Matteo Zignani ◽

Alessandro Comunian ◽

...

Keyword(s):

Time Series ◽

Correlation Analysis ◽

Health System ◽

Cross Correlation ◽

Future Perspective ◽

Lombardy Region ◽

Time Frequency ◽

Emergency Calls ◽

First Case ◽

Cross Correlation Analysis

The first case of Coronavirus Disease 2019 in Italy was detected on February the 20th in Lombardy region. Since that date, Lombardy has been the most affected Italian region by the epidemic, and its healthcare system underwent a severe overload during the outbreak. From a public health point of view, therefore, it is fundamental to provide healthcare services with tools that can reveal possible new health system stress periods with a certain time anticipation, which is the main aim of the present study. Moreover, the sequence of law decrees to face the epidemic and the large amount of news generated in the population feelings of anxiety and suspicion. Considering this whole complex context, it is easily understandable how people “overcrowded” social media with messages dealing with the pandemic, and emergency numbers were overwhelmed by the calls. Thus, in order to find potential predictors of possible new health system overloads, we analysed data both from Twitter and emergency services comparing them to the daily infected time series at a regional level. Particularly, we performed a wavelet analysis in the time-frequency plane, to finely discriminate over time the anticipation capability of the considered potential predictors. In addition, a cross-correlation analysis has been performed to find a synthetic indicator of the time delay between the predictor and the infected time series. Our results show that Twitter data are more related to social and political dynamics, while the emergency calls trends can be further evaluated as a powerful tool to potentially forecast new stress periods. Since we analysed aggregated regional data, and taking into account also the huge geographical heterogeneity of the epidemic spread, a future perspective would be to conduct the same analysis on a more local basis.

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Passive Detection of Low-Altitude Signal Sources Using an Improved Cross-Correlation Algorithm

Applied Sciences ◽

10.3390/app8122348 ◽

2018 ◽

Vol 8 (12) ◽

pp. 2348

Author(s):

Conghui Cao ◽

Hua Yang ◽

Hao Zhang ◽

Yan Wang ◽

Thomas Aaron Gulliver

Keyword(s):

Cross Correlation ◽

Signal To Noise Ratio ◽

Correlation Method ◽

Signal Source ◽

Long Distance ◽

Time Frequency ◽

Passive Detection ◽

Correlation Threshold ◽

Low Altitude ◽

Signal Sources

The passive detection of low-altitude signal sources is studied using an improved cross-correlation method in the time–frequency domain. A matching template is designed for signal cross-correlation, and a cross-correlation threshold is used to determine whether a signal source is present or not. An improved cross-correlation method is also proposed to estimate the direction of arrival and communication frequency of a signal source. Furthermore, the distance and signal-to-noise ratio are estimated using an energy detector. Outdoor data from a bridge in the Jimo District, Qingdao, and indoor data from a research laboratory are used for performance evaluation. The results obtained show that the proposed method can provide better passive detection of low-altitude signal sources compared to several well-known algorithms in the literature. In addition, this method is more suitable for long-distance detection.

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Wavelet transform-based cross-correlation in the time-delay estimation applications

Journal of Physics Conference Series ◽

10.1088/1742-6596/2142/1/012019 ◽

2021 ◽

Vol 2142 (1) ◽

pp. 012019

Author(s):

S B Sharkova ◽

V A Faerman

Keyword(s):

Wavelet Transform ◽

Time Delay ◽

Cross Correlation ◽

Fourier Transforms ◽

Time Delay Estimation ◽

Delay Estimation ◽

Practical Case ◽

Discrete Fourier Transforms ◽

Time Frequency ◽

Dyadic Wavelet

Abstract The article discusses the application of wavelet analysis for the time-frequency time-delay estimation. The proposed algorithm is wavelet transform-based cross-correlation time delay estimation that applies discrete time wavelet transform to filter the input signal prior to computation of cross-correlation function. The distinguishing feature of the algorithm that it uses the variation of continuous wavelet transform to process the discrete signals instead of dyadic wavelet transform that is normally applied to the case. Another feature that the implication of convolution theorem is used to compute coefficients of the wavelet transform. This makes possible to omit redundant discrete Fourier transforms and significantly reduce the computational complexity. The principal applicability of the proposed method is shown in the course of a computational experiments with artificial and real-world signal. So the method demonstrated expected selectivity for the signals localized in the different frequency bands. The application of the method to practical case of pipeline leak detection was also successful. However, the study concluded that this method provides no specific advantages in comparison with the conventional one. In the future, alternative applications in biological signal processing will be considered.

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