Rotor imbalance detection and quantification in wind turbines via vibration analysis

Rotor imbalance is a common fault in wind turbines, which may enhance radial loads that induce faults on the main bearing and gearbox. It usually results from the asymmetry of the air dynamics caused by blade crack, icing, etc. A simple and effective method on rotor imbalance detection and quantification is presented using the vibration signal collected from the accelerometer monitoring the wind turbine drive train. A vibration model describing the rotor imbalance under blade crack is proposed. The complex morlet wavelet transform is applied to the detection of the rotational frequency of rotor hub which represents the rotor hub. A health indicator that can quantify the degree of the rotor imbalance is designed. The proposed methods have successfully detected and quantified the rotor imbalance caused by blade crack in an on-site wind turbine.

Comparison between polar motion excitation functions estimated from recent geophysical models and observations

<p>Continental hydrological loading by land water, snow, and ice is a process that influences the Earth’s inertia tensor and is very important for full understanding of the excitation of polar motion. In this study, the hydrological contribution to decadal, inter-annual and multi-annual suppress polar motion derived from different GRACE (Gravity Recovery and Climate Experiment) solutions as well as from SLR (Satellite Laser Ranging) and some climate models from CMIP6 project data is discussed here.</p><p>The main aim of this study is to show the influence of different representations of hydrological angular momentum (HAM) coming from different GRACE (mas concentration solutions - mascons, Terrestrial Water Storage changes, and Stokes Coefficients), SLR, and climate models solutions on agreement between Geodetic Angular Momentum (GAM) and geophysical excitations of polar motion been a sum of Atmospheric, Oceanic and Hydrological Angular Momentum (AAM+OAM+HAM) in different spectral bands.</p><p>To do that, the geodetic and geophysical excitation functions are transformed into time-scale domain using the discrete wavelet transform based on the Complex Morlet wavelet functions. Next, the time series (GAM vs. geophysical ones) are compared in terms of semblance filtering, on the basis of their phase, as a function of frequency, and amplitude information of their cross-wavelet power.</p><p>Here, we would like to present the consistency between full polar motion excitations and geophysical fluids,  that are the sum of AAM  (pressure + wind), OAM  (bottom pressure +  currents), and HAM contributions. This analysis could let us indicate, which hydrological representation of different HAM solutions cause the biggest errors in the geodetic budget.</p>

Estimation of seasonal changes in the frequency characteristics of wind speed and direction in coastal Dagestan, Russia

Aim. To analyse seasonal changes in the frequency characteristics of wind speed and direction in coastal Dagestan, namely the urban districts of the cities of Makhachkala and Derbent, from the point of view of wind power potential.Material and Methods. The research was based on time series of wind speed and direction for the period 2011-2018, obtained as a result of observations at the Makhachkala and Derbent weather stations. As a mathematical research tool, a continuous wavelet transform with a complex Morlet wavelet function was used.Results. According to the results of analysis, it was found that the main frequency of fluctuations in the time series is one day and one-day periodicity in the time series has pronounced seasonal changes. Also, differences in seasonal changes of one-day periodicity for wind speed and direction between the regions of Makhachkala and Derbent were established and described.Conclusion. The parameters considered in assessing seasonal changes in the dynamics of wind speed and direction can be used as additional parameters for the classification and clustering of regions to identify the best areas of wind power potential.

Evaluating internal condition of hardwood logs based on AR-minimum entropy deconvolution combined with wavelet based spectral kurtosis approach

The aim of this research was to explore the potential of acoustic impact test to evaluate the condition of hardwood logs in regard to internal decay, void, crack and defect ratio using an acoustic signal separation and enhancement algorithm. Longitudinal acoustic signals were obtained from 15 logs of four hardwood species through acoustic impact testing. The defect components were separated from the acoustic response signals and enhanced based on the autoregressive minimum entropy deconvolution (AR-MED) method, and from which the kurtosis was derived and used as the global feature parameter for evaluating the internal condition of logs. Compared with the acoustic velocity obtained directly from the original signal, the kurtosis was deemed to be a more powerful predictor of log defect ratio with higher coefficient of determination (R2 = 0.89) and was not affected by log species. To identify the type of defects, a complex Morlet wavelet-based spectral kurtosis (SK) method was proposed. The research results indicated that the SK can not only determine the type and primary and secondary major defects, but also be able to identify those that were not detectable by global acoustic parameters.

Demodulation Method of F-P Sensor Based on Wavelet Transform and Polarization Low Coherence Interferometry

Polarized low-coherence interferometry (PLCI) is widely used for the demodulation of Fabry–Perot (F-P) sensors. To avoid the influence of noise and dispersion on interference fringes, this paper proposes a data processing method in which the wavelet tools are applied to extract useful information from the extremum locations and envelope center of the fringes. Firstly, the wavelet threshold denoising (WTD) algorithm is used to remove electrical noise, and the complex Morlet wavelet is used to extract the fringe envelope. Based on this, the envelope center is used to predict the extremum locations of the specified order in its adjacent interval, the predicted locations are used as references to track the exact extremum locations, and the middle location of the peak and valley values is obtained to demodulate the F-P cavity accurately. The validity of this demodulation theory is verified by an air F-P cavity whose cavity length varies from 17 to 20 μm. With a sampling interval of 30 nm, the experimental results indicate that the repeatability accuracy is higher than 6.04 nm, and the resolution is better than 4.0 nm.

Influence of lack of night sleep on the cognitive set by indicators of EEG rhythms coupling

The aim of the study is investigation of nighttime sleep effect on the performance of a cognitive setting in terms of the coupling of EEG rhythms. The coupling of 5 rhythm: beta-1, beta-2, gamma, alpha and theta rhythms of EEG during the formation and testing of cognitive set was studied for 120 students (17 with short-term night sleep and 15 with a full night sleep). Multi-channel EEG was recorded. EEG evaluation was carried out by continuous wavelet transform based on the “mother” complex Morlet wavelet in the range of 1–35 Hz. Maps of the distribution of the values of the modulus of the wavelet transformation coefficient, which reflect amplitude changes of the potentials were analyzed. The Pearson correlation coefficient was a measure evaluating the coupling of EEG rhythms. The subjects with a short night’s sleep showed almost all of the relations of EEG rhythms (8 couples) during the formation stage of presentation. Students with a full night’s sleep showed statistically significant coupling of the following pairs of rhythms: alpha–beta-1, alpha–gamma and beta-2–gamma. Students with short-term night sleep demonstrated the 3 significant couples: alpha–beta-1, beta-1–gamma and beta-2–gamma during the testing stage. Well-slept students showed an increase in the number of connections (6 couples) in relation to the stage of formation of the set due to the addition of connections with the theta rhythm. The obtained data could indicate that the thalamo-cortical and cortico-hippocampal structural-functional associations work differently in the groups of subjects.