Clustering of decomposed strain signal energy for durability classification

2021 ◽  
Author(s):  
Y. S. Kong ◽  
Shahrum Abdullah ◽  
S. S. K. Singh
Keyword(s):  
Signal Energy ◽  
Strain Signal

scholarly journals The duration-energy-size enigma for acoustic emission

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Blai Casals ◽  
Karin A. Dahmen ◽  
Boyuan Gou ◽  
Spencer Rooke ◽  
Ekhard K. H. Salje
Keyword(s):  
Acoustic Emission ◽  
Mean Field Theory ◽  
Mean Field ◽  
Maximum Amplitude ◽  
Time Profile ◽  
Power Law Distribution ◽  
Model Predictions ◽  
Ae Signal ◽  
Strain Signal ◽  
Better Than

AbstractAcoustic emission (AE) measurements of avalanches in different systems, such as domain movements in ferroics or the collapse of voids in porous materials, cannot be compared with model predictions without a detailed analysis of the AE process. In particular, most AE experiments scale the avalanche energy E, maximum amplitude Amax and duration D as E ~ Amaxx and Amax ~ Dχ with x = 2 and a poorly defined power law distribution for the duration. In contrast, simple mean field theory (MFT) predicts that x = 3 and χ = 2. The disagreement is due to details of the AE measurements: the initial acoustic strain signal of an avalanche is modified by the propagation of the acoustic wave, which is then measured by the detector. We demonstrate, by simple model simulations, that typical avalanches follow the observed AE results with x = 2 and ‘half-moon’ shapes for the cross-correlation. Furthermore, the size S of an avalanche does not always scale as the square of the maximum AE avalanche amplitude Amax as predicted by MFT but scales linearly S ~ Amax. We propose that the AE rise time reflects the atomistic avalanche time profile better than the duration of the AE signal.

Trial Study on Methods of Damage Extent Identification Based on Wavelet Transform of Strain Signal

2010 ◽  
Vol 163-167 ◽  
pp. 2543-2548
Author(s):  
Jin Fan ◽  
Hong Po Liu
Keyword(s):  
Wavelet Transform ◽  
Wavelet Coefficient ◽  
Maximum Modulus ◽  
Steel Beam ◽  
Simply Supported ◽  
Relative Damage ◽  
Damage Extent ◽  
Strain Signal

Wavelet transform of strain signal can be used in the damage relative damage extent identification. The proposed method is validated by trial on a simply supported steel beam. And meanwhile the relative damage extent can be identified by drawing the curve of the maximum modulus of the wavelet coefficient and damage extent.

scholarly journals Accounting for the surface temperature persistence by using signal energy

2021 ◽  
Vol 144 (1-2) ◽  
pp. 363-377
Author(s):  
Jiangnan Li ◽  
Zhian Sun ◽  
Feng Zhang
Keyword(s):  
Surface Temperature ◽  
Critical Exponent ◽  
Random Noise ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Signal Energy ◽  
The North ◽  
Power Rule ◽  
Short Period ◽  
Temporal Intervals

AbstractThe autocorrelation function (ACF) and its finite Fourier transform, referred to as signal energy, have been investigated using the ECMWF daily surface temperature data. ACF itself provides a measure of the influence of leading fluctuation between two different time points. Considering the decay of ACF, it is found that the scaling power-rule of ACF is only valid in a very short period, as the decay of ACF exists before it reaches a random noise state. Therefore, the method of the critical exponent of ACF is limited in the short length of the temporal interval. On the other hand, the distributions of the signal energy always show nice patterns, indicating the degree of persistence change. It is found, for a short period, that the distributions of the signal energy and the critical exponent are very similar, with a correlation coefficient over 0.97. For a longer period, though the critical exponent of ACF becomes invalid, the signal energy can always provide an effective method to investigate climate persistence in different lengths of time. In a 5-day period of boreal winter, the southern part of North America has a larger value of signal energy compared to the northern part; thus, the surface temperature is more stable in the north part. The result becomes opposite in the boreal summer. The method of signal energy can also be applied to a particular interval of time. In different temporal intervals, the signal energy presents very different results, especially over the El Nino regions

Assessment of Damage Progression in Automotive Electronics Assemblies Subjected to Temperature and Vibration

2018 ◽  
Author(s):  
Pradeep Lall ◽  
Tony Thomas
Keyword(s):  
Instantaneous Frequency ◽  
Low Frequency ◽  
Principal Component ◽  
Large Data ◽  
Data Sets ◽  
Automotive Electronics ◽  
Damage Progression ◽  
Mode Decomposition ◽  
Electronic Assemblies ◽  
Strain Signal

Electronics in automotive underhood environments is used for a number of safety critical functions. Reliable continued operation of electronic safety systems without catastrophic failure is important for safe operation of the vehicle. There is need for prognostication methods, which can be integrated, with on-board sensors for assessment of accrued damage and impending failure. In this paper, leadfree electronic assemblies consisting of daisy-chained parts have been subjected to high temperature vibration at 5g and 155°C. Spectrogram has been used to identify the emergence of new low frequency components with damage progression in electronic assemblies. Principal component analysis has been used to reduce the dimensionality of large data-sets and identify patterns without the loss of features that signify damage progression and impending failure. Variance of the principal components of the instantaneous frequency has been shown to exhibit an increasing trend during the initial damage progression, attaining a maximum value and decreasing prior to failure. The unique behavior of the instantaneous frequency over the period of vibration can be used as a health-monitoring feature for identifying the impending failures in automotive electronics. Further, damage progression has been studied using Empirical Mode Decomposition (EMD) technique in order to decompose the signals into Independent Mode Functions (IMF). The IMF’s were investigated based on their kurtosis values and a reconstructed strain signal was formulated with all IMF’s greater than a kurtosis value of three. PCA analysis on the reconstructed strain signal gave better patterns that can be used for prognostication of the life of the components.

scholarly journals Meteorological noise in wire strainmeter data from Parkfield, California

1979 ◽  
Vol 69 (6) ◽  
pp. 1983-1988
Author(s):  
N. R. Goulty ◽  
P. M. Davis ◽  
R. Gilman ◽  
N. Motta
Keyword(s):  
Earthquake Prediction ◽  
Residual Strain ◽  
San Andreas Fault ◽  
Peak Amplitude ◽  
Wiener Filtering ◽  
Base Line ◽  
Signal Power ◽  
San Andreas ◽  
Filtering Technique ◽  
Strain Signal

abstract Four invar-wire strainmeters have been operated in shallow trench sites for 19 months beside the San Andreas Fault at Parkfield, California. Temperature and rainfall records were correlated with 1 yr of strainmeter data, and 90 per cent of the strain signal power at periods between 2 and 120 days was predicted entirely from these records, using a multi-channel, Wiener filtering technique. The residual strain series fluctuates with a peak-to-peak amplitude of nearly 10−6 strain. Anomalous strain signals taking place over several days would have to be larger than this to be identifiable. Previous work shows that signals of amplitude 10−7 strain are identifiable if they take place within hours. Deep creep events giving rise to such signals, which may occur as precursors to earthquakes, would need to be very large. Other workers have shown that shallow, short-base line tiltmeters in California are also very sensitive to meteorological noise. Strainmeter and tiltmeter installations can be made less sensitive to meteorological noise, either by manufacturing instruments with long (∼1 km) base lines, or by using tunnel or borehole sites (≳100 m deep). Proven instruments of these types are costly, unless an underground site was already available. However, if networks of shallow, shortbase line strainmeters or tiltmeters are to be used for earthquake prediction, it is obviously desirable to invest in at least a few installations which are less sensitive to noise of meteorological origin.

scholarly journals The power features of Masseter muscle activity in tension-type and migraine without aura headache during open-close clench cycles

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3556 ◽  
Author(s):  
Behrouz Alizadeh Savareh ◽  
Ali Ghanjal ◽  
Azadeh Bashiri ◽  
Monireh Motaqhey ◽  
Boshra Hatef
Keyword(s):  
Muscle Activity ◽  
Masseter Muscle ◽  
Migraine Without Aura ◽  
Mouth Opening ◽  
Tension Type Headache ◽  
Emg Activity ◽  
Statistical Parameters ◽  
Signal Energy ◽  
Type Headache ◽  
Mean Variance

Introduction Different types of headaches and TMJ click influence the masseter muscle activity. The aim of this study was to assess the trend of energy level of the electromyography (EMG) activity of the masseter muscle during open-close clench cycles in migraine without aura (MOA) and tension-type headache (TTH) with or without TMJ click. Methods Twenty-five women with MOA and twenty four women with TTH participated in the study. They matched with 25 healthy subjects, in terms of class of occlusion and prevalence of temporomandibular joint (TMJ) with click. The EMG of both masseter muscles were recorded during open-close clench cycles at a rate of 80 cycles per minute for 15 seconds. The mouth opening was restricted to two centimeters by mandibular motion frame. Signal processing steps have been done on the EMG as: noise removing, smoothing, feature extraction, and statistical analyzing. The six statistical parameters of energy computed were mean, Variance, Skewness, Kurtosis, and first and second half energy over all signal energy. Results A three-way ANOVA indicated that during all the cycles, the mean of energy was more and there was a delay in showing the peak of energy in the masseter of the left side with clicked TMJ in MOA group compared to the two other groups, while this pattern occurred inversely in the side with no-clicked TMJ (P < 0.009). The variation of energy was significantly less in MOA group compared to the two other groups in the no-clicked TMJ (P < 0.003). However, the proportion of the first or second part of signal energy to all energy showed that TTH group had less energy in the first part and more energy in the second part in comparison to the two other groups (P < 0.05). Conclusion The study showed different changes in the energy distribution of masseter muscle activity during cycles in MOA and TTH. MOA, in contrast to TTH, had lateralization effect on EMG and interacted with TMJ click.

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