Research on High-Velocity Impact Damage Monitoring Method of CFRP Based on Guided Wave

Carbon fiber-reinforced polymer(CFRP)is widely used in aerospace applications.This kind of material may face the threat of high-velocity impact in the process of dedicated service,and the relevant research mainly considers the impact resistance of the material,and lacks the high-velocity impact damage monitoring research of CFRP.To solve this problem,a real high-velocity impact damage experiment and structural health monitoring(SHM)method of CFRP plate based on piezoelectric guided wave is proposed.The results show that CFRP has obvious perforation damage and fiber breakage when high-velocity impact occurs.It is also proved that guided wave SHM technology can be effectively used in the monitoring of such damage,and the damage can be reflected by quantifying the signal changes and damage index(DI).It provides a reference for further research on guided wave structure monitoring of high/hyper-velocity impact damage of CFRP.

Monitoring of Wind Turbine Blades Based on Dual-Tree Complex Wavelet Transform

Structural health monitoring(SHM)in-service is very important for wind turbine system.Because the central wavelength of a fiber Bragg grating(FBG)sensor changes linearly with strain or temperature,FBG-based sensors are easily applied to structural tests.Therefore,the monitoring of wind turbine blades by FBG sensors is proposed.The method is experimentally proved to be feasible.Five FBG sensors were set along the blade length in order to measure distributed strain.However,environmental or measurement noise may cover the structural signals.Dual-tree complex wavelet transform(DT-CWT)is suggested to wipe off the noise.The experimental studies indicate that the tested strain fluctuate distinctly as one of the blades is broken.The rotation period is about 1 s at the given working condition.However,the period is about 0.3 s if all the wind blades are in good conditions.Therefore,strain monitoring by FBG sensors could predict damage of a wind turbine blade system.Moreover,the studies indicate that monitoring of one blade is adequate to diagnose the status of a wind generator.

New Developments in Structural Health Monitoring Based on Diagnostic Lamb Wave

Structure health monitoring based on diagnostic Lamb waves has been found to be one of the most promising techniques recently. This paper has a brief review of the new developments on this method including the basic novel of the method, fundamentals and mathematics of Lamb wave propagation, narrowband and wideband Lamb wave excitation methods, optimization of excitation factors and diagnostic Lamb wave interpretation methods.

Wind-induced instabilities and monitoring of wind turbine

This paper presents real-time monitoring data and analysis results of the non-stationary vibrations of an operational wind turbine. The advanced time-frequency spectrum analysis reveals varied non-stationary vibrations with timevarying frequencies, which are correlated with certain system natural modes characterized by finite element analysis. Under the effects of strong wind load, the wind turbine system exhibits certain resonances due to blade passing excitations. The system also exhibits certain instabilities due to the coupling of the tower bending modes and blade flapwise mode with blade passing excitations under the variation of wind speed. An analytical model is used to elaborate the non-stationary and instability phenomena observed in experimental results. The properties of the nonlinear instabilities are evaluated by using Lyapunov exponent estimation.

Comparisons of Wave Force Model Effects on the Structural Responses and Fatigue Loads of a Semi-Submersible Floating Wind Turbine

The selection of wave force models will significantly impact the structural responses of floating wind turbines.In this study,comparisons of wave force model effects on the structural responses and fatigue loads of a semi-submersible floating wind turbine(SFWT)were conducted.Simulations were performed by employing the Morison equation(ME)with linear or second-order wave kinematics and potential flow theory(PFT)with first-or second-order wave forces.A comparison of regular waves,irregular waves,and coupled wind/waves analyses with the experimental data showed that many of the simulation results and experimental data are relatively consistent.However,notable discrepancies are found in the response amplitude operators for platform heave,tower base bending moment,and tension in mooring lines.PFT models give more satisfactory results of heave but more significant discrepan-cies in tower base bending moment than the ME models.In irregular wave analyses,low-frequency resonances were captured by PFT models with second-order difference-frequency terms,and high-frequency resonances were captured by the ME models or PFT models with second-order sum-frequency terms.These force models capture the response frequencies but do not reasonably predict the response amplitudes.The coupled wind/waves analyses showed more satisfactory results than the wave-only analyses.However,an important detail to note is that this satisfactory result is based on the overprediction of wind-induced responses.

Extreme Responses of An Integrated System with A Semi-Submersible Wind Turbine and Four Torus-Shaped Wave Energy Converters in Different Survival Modes

Offshore wind power is a kind of important clean renewable energy and has attracted increasing attention due to the rapid consumption of non-renewable energy.To reduce the high cost of energy,a possible try is to utilize the combination of wind and wave energy considering their natural correlation.A combined concept consisting of a semi-submersible wind turbine and four torus-shaped wave energy converters was proposed and numerically studied under normal operating conditions.However,the dynamic behavior of the integrated system under extreme sea conditions has not been studied yet.In the present work,extreme responses of the integrated system under two different survival modes are evaluated.Fully coupled time-domain simulations with consideration of interactions between the semi-submersible wind turbine and the torus-shaped wave energy converters are performed to investigate dynamic responses of the integrated system,including mooring tensions,tower bending moments,end stop forces,and contact forces at the Column-Torus interface.It is found that the addition of four tori will reduce the mean motions of the yaw,pitch and surge.When the tori are locked at the still water line,the whole integrated system is more suitable for the survival modes.

An empirical method for joint inversion of wave and wind parameters based on SAR and wave spectrometer data

Synthetic aperture radar(SAR)and wave spectrometers,crucial in microwave remote sensing,play an essential role in monitoring sea surface wind and wave conditions.However,they face inherent limitations in observing sea surface phenomena.SAR systems,for instance,are hindered by an azimuth cut-off phenomenon in sea surface wind field observation.Wave spectrometers,while unaffected by the azimuth cutoff phenomenon,struggle with low azimuth resolution,impacting the capture of detailed wave and wind field data.This study utilizes SAR and surface wave investigation and monitoring(SWIM)data to initially extract key feature parameters,which are then prioritized using the extreme gradient boosting(XGBoost)algorithm.The research further addresses feature collinearity through a combined analysis of feature importance and correlation,leading to the development of an inversion model for wave and wind parameters based on XGBoost.A comparative analysis of this model with ERA5 reanalysis and buoy data for of significant wave height,mean wave period,wind direction,and wind speed reveals root mean square errors of 0.212 m,0.525 s,27.446°,and 1.092 m/s,compared to 0.314 m,0.888 s,27.698°,and 1.315 m/s from buoy data,respectively.These results demonstrate the model’s effective retrieval of wave and wind parameters.Finally,the model,incorporating altimeter and scatterometer data,is evaluated against SAR/SWIM single and dual payload inversion methods across different wind speeds.This comparison highlights the model’s superior inversion accuracy over other methods.

Vibration Deformation Monitoring of Offshore Wind Turbines Based on GBIR

In view of the disadvantages of vibration safety monitoring technology for offshore wind turbines,a new method is proposed to obtain deformation information of towering and dynamic targets in real-time by the ground-based interferometric ra-dar(GBIR).First,the working principle and unique advantages of the GBIR system are introduced.Second,the offshore wind turbines in Rongcheng,Shandong Province are selected as the monitoring objects for vibration safety monitoring,and the GPRI-II portable radar interferometer is used for the health diagnosis of these wind turbines.Finally,the interpretation method and key processing flow of data acquisition are described in detail.This experiment shows that the GBIR system can accurately identify the millimeter-scale vibration deformation of offshore wind turbines and can quickly obtain overall time series deformation images of the target bodies,which demonstrate the high-precision deformation monitoring ability of the GBIR technology.The accuracy meets the requirements of wind turbine vibration monitoring,and the method is an effective spatial deformation monitoring means for high-rise and dynamic targets.This study is beneficial for the further enrichment and improvement of the technical system of wind turbine vibration safety monitoring in China.It also provides data and technical support for offshore power engineering management and control,health diagnosis,and disaster prevention and mitigation.

Improving autoencoder-based unsupervised damage detection in uncontrolled structural health monitoring under noisy conditions

Structural health monitoring is widely utilized in outdoor environments,especially under harsh conditions,which can introduce noise into the monitoring system.Therefore,designing an effective denoising strategy to enhance the performance of guided wave damage detection in noisy environments is crucial.This paper introduces a local temporal principal component analysis(PCA)reconstruction approach for denoising guided waves prior to implementing unsupervised damage detection,achieved through novel autoencoder-based reconstruction.Experimental results demonstrate that the proposed denoising method significantly enhances damage detection performance when guided waves are contaminated by noise,with SNR values ranging from 10 to-5 dB.Following the implementation of the proposed denoising approach,the AUC score can elevate from 0.65 to 0.96 when dealing with guided waves corrputed by noise at a level of-5 dB.Additionally,the paper provides guidance on selecting the appropriate number of components used in the denoising PCA reconstruction,aiding in the optimization of the damage detection in noisy conditions.

A time reversal damage imaging method for structure health monitoring using Lamb waves

This paper investigates the Lamb wave imaging method combining time reversal for health monitoring of a metallic plate structure. The temporal focusing effect of the time reversal Lamb waves is investigated theoretically. It demonstrates that the focusing effect is related to the frequency dependency of the time reversal operation. Numerical simulations are conducted to study the time reversal behaviour of Lamb wave modes under broadband and narrowband excitations. The results show that the reconstructed time reversed wave exhibits close similarity to the reversed narrowband tone burst signal validating the theoretical model. To enhance the similarity, the cycle number of the excited signal should be increased. Experiments combining finite element model are then conducted to study the imaging method in the presence of damage like hole in the plate structure. In this work, the time reversal technique is used for the recompression of Lamb wave signals. Damage imaging results with time reversal using broadband and narrowband excitations are compared to those without time reversal. It suggests that the narrowband excitation combined time reversal can locate and determine the size of structural damage more precisely, but the cycle number of the excited signal should be chosen reasonably.

Experimental study on the variation of optical remote sensing imaging characteristics of internal solitary waves with wind speed

Optical remote sensing has been widely used to study internal solitary waves(ISWs).Wind speed has an important effect on ISW imaging of optical remote sensing.The light and dark bands of ISWs cannot be observed by optical remote sensing when the wind is too strong.The relationship between the characteristics of ISWs bands in optical remote sensing images and the wind speed is still unclear.The influence of wind speeds on the characteristics of the ISWs bands is investigated based on the physical simulation experiments with the wind speeds of 1.6,3.1,3.5,3.8,and 3.9 m/s.The experimental results show that when the wind speed is 3.9 m/s,the ISWs bands cannot be observed in optical remote sensing images with the stratification of h_(1)∶h_(2)=7∶58,ρ_(1)∶ρ_(2)=1∶1.04.When the wind speeds are 3.1,3.5,and 3.8 m/s,which is lower than 3.9 m/s,the ISWs bands can be obtained in the simulated optical remote sensing image.The location of the band’s dark and light extremum and the band’s peak-to-peak spacing are almost not affected by wind speed.More-significant wind speeds can cause a greater gray difference of the light-dark bands.This provided a scientific basis for further understanding of ISW optical remote sensing imaging.

Piezoelectric Actuator/Sensor Wave Propagation Based Nondestructive Active Monitoring Method of Concrete Structures

In order to monitor the basic mechanical properties and interior damage of concrete structures,the piezoelectric actuator/sensor based wave propagation method was investigated experimentally in the laboratory using a specifically designed test setup.The energy attenuation of stress waves was measured by the relative index between the output voltage of sensors and the excitation voltage at the actuator.Based on the experimental results of concrete cube and cylinder specimens,the effect of excitation frequencies,excitation amplitude,wave propagation paths and the curing age on the output signals of sensors are evaluated.The results show that the relative voltage attenuation coefficient RVAC is an effective indicator for measuring the attenuation of stress waves through the interior of concrete.

Comparative Study on Tree Classifiers for Application to Condition Monitoring ofWind Turbine Blade through Histogram Features Using Vibration Signals: A Data-Mining Approach

Wind energy is considered as a alternative renewable energy source due to its low operating cost when compared with other sources.The wind turbine is an essential system used to change kinetic energy into electrical energy.Wind turbine blades,in particular,require a competitive condition inspection approach as it is a significant component of the wind turbine system that costs around 20-25 percent of the total turbine cost.The main objective of this study is to differentiate between various blade faults which affect the wind turbine blade under operating conditions using a machine learning approach through histogram features.In this study,blade bend,hub-blade loose connection,blade erosion,pitch angle twist,and blade cracks were simulated on the blade.This problem is formulated as a machine learning problem which consists of three phases,namely feature extraction,feature selection and feature classification.Histogram features are extracted from vibration signals and feature selection was carried out using the J48 decision tree algorithm.Feature classification was performed using 15 tree classifiers.The results of the machine learning classifiers were compared with respect to their accuracy percentage and a better model is suggested for real-time monitoring of a wind turbine blade.

Vibration Signals and Condition Monitoring for Wind Turbines

Rolling element bearings are critical parts of modern wind turbines as they carry the loads of the turning structure and the wind force. The stochastic nature of the wind loads makes it difficult to estimate the useful operational life of the bearings. Condition monitoring of these bearings in a real time environment could be very helpful in estimating their performance and in scheduling maintenance actions when a condition-based maintenance strategy is followed. This procedure can be successfully implemented by using vibration analysis in the time domain or in the frequency domain, giving useful results about the current condition of bearings and the location of potential faults. Permanently located transducers on proper positions on the bearings’ housings can be used in order to collect, process and evaluate real time measurements and provide information about the bearing’s performance. In this work, a test rig is utilized in order to evaluate the performance of rolling bearings. The results of the experimentation are satisfactory and the progress of fatigue failures can be predicted through vibration analysis techniques showing that implementation in real scale may be useful.

Monitoring and Detection of Wind Turbine Vibration with KNN-Algorithm

Maintenance for wind turbines has been transformed using supervised machine learning techniques. This method of automatic and autonomous learning can identify, monitor, and detect electrical and mechanical components of wind turbines and predict, detect, and anticipate their degeneration. Using a machine learning classifier and frequency analysis, we simulate two failure states caused by bearing vibrations. Implementing KNN facilitates efficient monitoring, monitoring, and fault-finding for wind turbines. It is possible to reduce downtime, anticipate breakdowns, and import offshore aspects through these technologies.

SEISMIC WAVE VELOCITY MONITORING OF CO_2 MIGRATION IN POROUS SANDSTONES SATURATED WITH WATER

Laboratory experiments were conducted to measure the compressional wave velocities under hydrostatic pressure in Shirahama Tako sandstones with a porosity of 12% and 24%,respectively.In dry samples,the pressure dependence of velocity is ascribed to the difference in pore structures.Velocities were also measured to map the movement of the injected CO2 within water-saturated samples during CO2 injection.In the water-saturated samples,velocity changes caused by the CO2 injection are typically on the order of 10%.A series of seismic tomography experiments are conducted on porous sandstone samples to demonstrate the use of cross-well seismic profiling for monitoring the migration of CO2 in geological sequestration projects.

Early monitoring of gas infl ux of drilling fl uid in risers during deepwater drilling using Lamb waves

Early warning of gas in deepwater drilling risers is critical to the timely detection of seepage and consequently blowout reduction. We numerically simulate the acoustic fi eld in water-based drilling fl uids from a sound source outside the riser by using a 3D cylindrical coordinates finite-difference method. By changing the gas content of the drilling fluid, the relation between the amplitude and attenuation of the A0- and the S0-mode Lamb waves in the riser, the fl uid properties in the pipe, and the position of the top and bottom interfaces of the slug fl ow were assessed. The simulation results suggests that the amplitude and attenuation of the Lamb waves refl ect the gas content in the riser and are sensitive to low gas content. Moreover, the Lamb waves amplitude and attenuation reflect the position of the top and bottom interface of the slug fl ow.

Real-Time Electrostatic Monitoring of Wear Debris for Wind Turbine Gearbox

Engineering practice has shown that early faults of gearboxes are a leading maintenance cost driver that can easily lower the profit from a wind turbine operation.A novel oil-lubricated electrostatic monitoring of wear debris for a wind turbine gearbox is presented.The continuous wavelet transform(CWT)is used to eliminate the noises of the original electrostatic signal.The kurtosis and root mean square(RMS)values of the time domain signal are extracted as the characteristic parameters to reflect the deterioration of the gearbox.The overall tendency of electrostatic signals in accelerated life test is analyzed.In the eighth cycle,the abnormal wear in the wind turbine gearbox is detected by electrostatic monitoring.A comparison with the popular MetalScan monitoring is given to illustrate the effectiveness of the electrostatic monitoring method.The results demonstrate that the electrostatic monitoring method can detect the fault accurately.

Elimination of the impact of vessels on ocean wave height inversion with X-band wave monitoring radar

Directional wave spectra and integrated wave parameters can be derived from X-band radar sea surface images.A vessel on the sea surface has a significant influence on wave parameter inversions that can be seen as intensive backscatter speckles in X-band wave monitoring radar sea surface images.A novel algorithm to eliminate the interference of vessels in ocean wave height inversions from X-band wave monitoring radar is proposed.This algorithm is based on the characteristics of the interference.The principal components(PCs) of a sea surface image sequence are extracted using empirical orthogonal function(EOF)analysis.The standard deviation of the PCs is then used to identify vessel interference within the image sequence.To mitigate the interference,a suppression method based on a frequency domain geometric model is applied.The algorithm framework has been applied to OSMAR-X,a wave monitoring system developed by Wuhan University,based on nautical X-band radar.Several sea surface images captured on vessels by OSMAR-X are processed using the method proposed in this paper.Inversion schemes are validated by comparisons with data from in situ wave buoys.The root-mean-square error between the significant wave heights(SWH) retrieved from original interference radar images and those measured by the buoy is reduced by 0.25 m.The determinations of surface gravity wave parameters,in particular SWH,confirm the applicability of the proposed method.

A speckle noise suppression method based on surface waves investigation and monitoring data

The internal energy distribution of waves can be described using ocean-wave spectra.In many ways,obtaining wave spectra on a global scale is critical.Surface waves investigation and monitoring onboard the Chinese-French oceanography satellite is the first space-borne instrument for detecting wave spectra specially,which was launched on October 29,2018.It can avoid the shortage of synthetic aperture radar detection results while still having some problems,especially with the effects of speckle noise.In this study,a method to suppress the speckle noise is proposed.First,the empirical formula for background speckle noise is established.Second,many spatio-temporal representative fluctuation spectra are classified and averaged.Third,rational transfer function filtering is used to obtain speckle noise close to the along-track direction.Finally,a signal-to-noise ratio threshold is used to suppress the abnormal speckle noise.This method solves the problems existing in previous denoising methods,such as excessive denoising in the along-track direction and the inability of some abnormal noises to be denoised in the two-dimensional directional wave spectra.