Phase-based Method Research Articles

Experimental Investigation of Nonlinear Forces on a Monopile Offshore Wind Turbine Foundation Under Directionally Spread Waves

Abstract Accurate prediction of nonlinear wave loading is crucial for designing marine and offshore structures, yet it remains a challenging task. Prior research has primarily focused on uni-directional extreme sea states, revealing that linear loading cannot accurately represent the total wave forces acting on offshore wind turbine foundations, with significant contributions from high-order harmonics. This study broadens the scope to include multi-directional and bi-directional wave interactions with monopile offshore wind turbine foundations. We use a phase-based harmonic separation method to isolate harmonic components in the presence of complex wave scenarios. This approach allows for the clear delineation of individual harmonics from the total wave force by controlling the phase of incident focused waves. Remarkably, this method shown effective even with multi-directional and bi-directional spreading. The clean separation of individual harmonics enables the estimation of contributions from each harmonic. Our findings are in line with previous research, showing that nonlinear loading can constitute up to 40% of the total under certain wave conditions. We have also observed that wider wave spreading reduces nonlinear high-order harmonics, and uni-directional waves induce the most severe nonlinear forces. These insights emphasise the importance of accounting for high-order nonlinear wave loading in offshore structure design.

Phase-based video vibration measurement and fault feature extraction method for compound faults of rolling bearings

Vibration characterization of rotating machinery is crucial for determining rotational and failure frequencies. Traditional contact measurement methods have limitations, while high-speed cameras offer a non-contact alternative for measuring target vibrations, spatial phase-based techniques have recently been widely used in detecting subtle vibrations and show good robustness to imaging noise. In this paper, a vision-based vibration extraction method for rotating machinery is proposed, aiming at extracting minor vibrations of bearings from them and further analyzing their fault frequencies. To address the challenge of separating a single fault frequency from the extracted compound faulty vibration signals, kurtosis is employed to analyze the inverse convolution period of multiple periodic components, and the MOMEDA filter length is optimized using the golden section algorithm. MOMEDA is then used to enhance each periodic pulse separately, and fault frequency is obtained through envelope spectrum demodulation. In the experimental part, a phase-based method is used to extract minor vibration displacements from rotor vibration video, which is subsequently compared with eddy current sensors in both time and frequency domains to verify the accuracy of the proposed method in extracting vibration displacements based on vision. Finally, vibration signals are extracted from the bearing compound fault video, and the single fault frequency characteristics of the bearing are successfully separated using the adaptive MOMEDA method, which provides an efficient and reliable method in the field of rotating machinery fault diagnosis.

Phaseless inverse scattering with a parametrized spatial spectral volume integral equation for finite scatterers in the soft x-ray regime

Soft x-ray wafer-metrology experiments are characterized by low signal-to-noise ratios and lack phase information, which both cause difficulties with the accurate three-dimensional profiling of small geometrical features of structures on a wafer. To this end, we extend an existing phase-based inverse-scattering method to demonstrate a sub-nanometer and noise-robust reconstruction of the targets by synthetic soft x-ray scatterometry experiments. The targets are modeled as three-dimensional finite dielectric scatterers embedded in a planarly layered medium, where a scatterer’s geometry and spatial permittivity distribution are described by a uniform polygonal cross section along its height. Each cross section is continuously parametrized by its vertices and homogeneous permittivity. The combination of this parametrization of the scatterers and the employed Gabor frames ensures that the underlying linear system of the spatial spectral Maxwell solver is continuously differentiable with respect to the parameters for phaseless inverse-scattering problems. In synthetic demonstrations, we demonstrate the accurate and noise-robust reconstruction of the parameters without any regularization term. Most of the vertex parameters are retrieved with an error of less than λ/13 with λ=13.5nm, when the ideal sensor model with shot noise detects at least five photons per sensor pixel. This corresponds to a signal-to-noise ratio of 3.5 dB. These vertex parameters are retrieved with an accuracy of λ/90 when the signal-to-noise ratio is increased to 10 dB, or approximately 100 photons per pixel. The material parameters are retrieved with errors ranging from 0.05% to 5% for signal-to-noise ratios between 10 dB and 3.5 dB.

Critical current density of high-temperature superconducting ceramics BSCCO Bi-2223

In the paper the results of the study on the synthesis of high-temperature superconducting ceramics of nomi- nal composition Bi1.6Pb0.4Sr2Ca2Cu3Oy by various methods were presented based on amorphous phases using glass-ceramic technology and solid-phase method. For comparison, amorphous phases were obtained in two ways. In the first case, a heating furnace of a special design was developed to obtain an amorphous phase, which provides melting without using a crucible. The heating of the initial samples for melting is carried out due to the combined effect of the convection heat flux and the radiation of heating elements, which consists of the IR region of the spectrum at a melting temperature in the spectral range of 1300–1350 nm. In the se- cond case, melting is carried out under the influence of broadband optical radiation, including UV, visible and IR spectral regions. The production of glassy precursors is carried out by draining the melt onto a quenching device in the form of a propeller made of stainless steel. Studies of the formation rate of the superconducting high-temperature phase Bi-2223 were carried out in the same temperature conditions at 848–850 °C with in- termediate grinding every 24 hours and the study of the phase composition by X-ray diffraction method. Studies showed that the glass phase-based method ensures the completeness of the formation of the high- temperature phase Bi-2223 and the rate of its formation is significantly higher than by the solid-phase method (2.5–3 times). Studies of the critical density of the transport current have shown that the current value is 7.05×103 mA/cm2, (measured by the criterion of 1 µV/cm), which is significantly higher compared to other methods.

The wavenumber linearisation without calibration device for spectral-domain optical coherence tomography.

The wavenumber nonlinearity leads to blurred reconstructed images in spectral-domain optical coherence tomography (SDOCT). In this work, a wavenumber-linearisation method without calibration devices is presented, based on the fact that the difference between the phases of adjacent peak and valley points is equal to . The theoretical model is derived, and the efficacy of the method was proven by acquiring SDOCT data from TiO2 phantom and zebrafish. The results exhibit the superior performance of our method. Compared with the linear phase-based method, the resolution could be improved at least a factor of 2. Compared with the polynomial fitting method, the resolution could also be improved by nearly half.

Abstract 3430: Mosaic loss of the Y chromosome is associated with prostate cancer risk

Abstract Mosaic loss of the Y chromosome (mLOY), a type of clonal hematopoiesis, is the most frequent chromosomal alteration observed in leukocytes of aging men. mLOY is a putative biomarker of genomic instability with evidence of associations with risk of some solid tumors, but more studies are needed to refine associations and identify potential mechanisms for cancer risk. Prostate cancer (PCa), the most common non-cutaneous cancer in males, is also associated with aging. To further investigate potential relationships between mLOY and PCa, we examined DNA derived from leukocytes of male participants in two large biobanks: the UK Biobank (UKBB; N = 210,103) and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO, N = 26,795). Of the 236,898 male participants without previous cancer diagnosis, 14,253 (6.0%) were diagnosed with incident PCa after DNA collection. High-density genotyping array data collected during the studies were used to create virtual karyotypes for detecting mLOY in whole blood samples utilizing a phase-based detection method in MoChA software. Analyses were restricted to men without cancer at genotyping and multivariable regression models were adjusted for age, smoking status, and genetic similarity. Men with detectable mLOY were older (mean = 62 vs 56 years) and more likely to be smokers (14.8% vs 9.7%) than men without mLOY. A total of 3,848 (27.0%) men with PCa and 42,835 (19.2%) men free of PCa had detectable mLOY. mLOY clonal fraction ranged from 0.01% to 72.1% of total leukocytes. 18.7% of PCa cases and 13.6% of men free of PCa had high clonal fraction mLOY, defined as greater than 10% of leukocytes with mLOY. Fixed effect meta-analysis of multivariable models from UKBB and PLCO produced evidence for a positive association between mLOY in leukocytes and incident PCa; (Odds Ratio (OR) = 1.062, 95% Confidence Interval (CI) [1.020, 1.107], P-Value (p) = 0.004). The effect estimate was the same in men with low clonal fraction of mLOY (OR = 1.062, 95% CI [1.012, 1.113], p = 0.014) and men with high clonal fraction of mLOY (OR = 1.065, 95% CI [0.998, 1.137], p = 0.057). Age at PCa diagnosis was not associated with mLOY or the clonal fraction of mLOY. A sub-analysis of separate participants from PLCO with mLOY detected in buccal cells (n = 18,011) also showed a small positive effect between mLOY and PCa risk, but the relationship did not reach statistical significance (OR = 1.036, 95% CI [0.877, 1.224], p = 0.673)). Our investigation of the relationship between mLOY and PCa in two large prospective studies provides additional evidence for an association between mLOY detected in the blood and increased PCa risk, meriting additional studies of potential biologic mechanisms underlying the relationship. Citation Format: Rebecca L. Kelly, Weiyin Zhou, Kara M. Barnao, Corey D. Young, Aubrey K. Hubbard, Sairah M. Khan, Wen-Yi Huang, Stephen J. Chanock, Mitchell J. Machiela. Mosaic loss of the Y chromosome is associated with prostate cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3430.

Short-term traffic flow prediction at isolated intersections based on parallel multi-task learning

This paper proposes a novel phase-based short-term traffic flow prediction method based on parallel multi-task learning for isolated intersections. Different from traditional short-term traffic flow prediction methods, we take the traffic flow of each phase as the minimum prediction unit, instead of directly utilising the traffic flow of a single lane with large random fluctuations. Meanwhile, we design a novel encoding and decoding structure whereby external influencing factors have been incorporated both into encoding and decoding operations. Furthermore, a fusion strategy is proposed to predict the traffic flow of each phase by integrating the traffic flows of lanes whose right of way are provided by the phase. In the fusion strategy, we develop a parallel multi-task prediction framework whereby a new loss function is defined to improve the prediction accuracy. Finally, the proposed method is tested with the traffic flow data collected from an intersection of South Changsheng Road located in the city of Jiaxing. The findings illustrate that the proposed method can achieve better prediction results at different sampling time scales, compared to the existing short-term traffic flow prediction methods.

Fast and accurate visual vibration measurement via derivative-enhanced phase-based optical flow

Visual vibration measurement using a digital camera is an emerging non-contact modality capable of enabling flexibility, high spatial resolution, and full field. However, the massive amounts of video data with vibration information (thousands of time-lapse images per measurement) to be handled lead to an actual bottleneck. This prevents the system from extracting the vibration information with high speed and fidelity. Here, a straightforward phase-based optical flow approach is proposed by introducing a derivative operation to perform vibration measurements in a more accurate and efficient manner, in contrast to the state-of-the-art phase-based visual method. This approach generates analytical signals by considering each raw gray image as the real part and its first-order derivative as the imaginary part. As a result, the physical vibration can be extracted from the phase variations of the analytical signals from one to the next. Numerical simulations and experiments are conducted to validate the effectiveness and accuracy of this simple but powerful approach. The results indicate that the proposed approach provides a significantly higher speed than current methods and a correlation coefficient of 99.2 % with the identification results.

Impedance-Based Stability Analysis: Nodal Admittance or Bus Admittance?

Impedance-based stability analysis is widely adopted for small-signal stability demonstration of power electronics dominated power systems. Stability assessment can be performed using either nodal admittance or bus admittance (i.e. equivalent admittance of a network viewed from a specific bus). This paper demonstrates that stability analysis using the bus admittance may not always produce correct results, even though it is easier to implement. Unstable multi-bus systems can be wrongly identified as stable by the single-bus analysis, in the cases where other buses play a dominant role in causing instabilities. A detailed comparison between nodal and bus admittance stability analysis is presented, leading to recommendations for their practical use. A phase-based method is proposed to facilitate the acquisition of eigenloci encirclement around the critical point, which can be used in the stability analysis based on either nodal or bus admittance. Following the conclusion of our work, we recommend multi-bus analysis in white-box model applications for instability mode analysis and stability-oriented design. Single-bus analysis is preferable in black-box model applications due to its simplicity. It is also suggested to select a bus for analysis from those connected to a high share of inverter-based resources, to ensure the correctness of results.

Phase-Based Optical Flow Method with Optimized Parameter Settings for Enhancing Displacement Measurement Adaptability

Phase-Based Optical Flow Method with Optimized Parameter Settings for Enhancing Displacement Measurement Adaptability

3D vibration modes estimation of complex-shaped structure by Phase-based motion magnification and DIC method

Knowing the 3D mode shapes of a structure is important in solving unwanted vibration and noise problems in mechanical systems. Accordingly, various analysis methods for estimating the vibration modes of complex-shaped structures have been proposed. However, it is difficult to attach accelerometers to a complex-shaped structure, and to cover a large area, many accelerometers must be attached. So experimental verification of the mode shapes of an actual structure is insufficient. Therefore, the purpose of this study is to experimentally estimate the 3D vibration modes of a complex structure using two cameras by Phase-based image magnification and DIC method. In addition, by using non-contact sensor such as a camera, it is possible to estimate the modes without affecting the mass or stiffness of the structure.

Motion estimation from noisy data with unknown distributions using multi-frame phase-preserving denoising

Phase-based motion estimation method is promising due to its high resolution and wide measurement range. Generally, noise exists in digital images and ruins the constant phase assumption of the same target among different frames. However, traditional image-denoising techniques do not consider the phase and result in inaccurate motion estimation. A novel phase-preserving denoising method considering multiple frames is proposed. In this approach, multi-scale and multi-orientation quadrature filters transform noisy images into complex pyramids to preserve the phase of the content. An instability indicator is designed to evaluate the relative noise intensity at each level of the complex pyramid among multiple frames. The threshold is then estimated to retain the phase of interest and reconstruct a denoised image with unknown noise distributions. Numerical and experimental examples demonstrate that the proposed method effectively preserves the phase of interest and decreases the error of the estimated motion, outperforming other typical denoising methods under various types of noise.

Cross-correlation-guided operational modal identification of bridge considering asynchronous signals

The accurate identification of modal parameters is crucial for bridge health monitoring. In practical scenarios, there is often an asynchronization in the multi-channel vibration signals obtained from wireless sensors or offline measurements without temporal data. This asynchronization can lead to significant bias in the mode shapes when using the classical operational modal identification method. To address this issue, a new cross-correlation (CC) coefficient-based time lag detection is proposed. This technique aims to determine whether the multi-channel signals are synchronous and to prepare the reliably synchronous signals for modal identification. Because this detection technique specifically focuses on detecting the time lag between single degree-of-freedom (DOF) asynchronous signals, a multivariate variational mode decomposition (VMD) technique is developed to handle the multiple DOF signals of a bridge. To ensure that the decomposed components are not distorted or mixed, the penalty parameter in the multivariate VMD is optimized by minimizing the proposed similarity index. The proposed time lag detection process is validated using numerical and actual bridge examples. The results demonstrate that the new CC coefficient-based method is more effective than the classical CC coefficient or phase-based method, regardless of the employed mode or the amount of time lag present.

High-precision composite 3D shape measurement of aeroengine blade based on parallel single-pixel imaging and high-dynamic range N-step fringe projection profilometry

Aeroengine blade is a core component of aircrafts. Accurate measurement of its profile has a great significance for flight safety. However, obtaining a high-quality 3D model of blade is difficult because traditional methods are limited in simultaneously meeting the requirements of large-scale measurement of smooth areas and high-precision measurement of fine structures. We develop a high-precision composite 3D shape measurement method of aeroengine blade. The proposed system consists of two sensors: a global sensor for large-range measurement and a local sensor for high-precision measurement. The global sensor based on parallel single-pixel imaging is used for smooth areas such as blade body and back, which undertakes most of the measurement tasks. The local sensor based on high-dynamic range N-step fringe projection profilometry has a high resolution to measure fine structures such as blade edge and top. We also use the local sensor to complete the missing point cloud of strong reflective areas. A phase-based data alignment method is developed to obtain coordinate transformation between the global and local sensors. Experiment results demonstrate that the proposed method can achieve accurate measurement and finally reconstruct the high-quality 3D model of aeroengine blade.

Spatial and temporal distributions of atmospheric refractive-index structure parameter measured by moiré deflectometry

Random fluctuation of refractive index distorts the wavefront of light propagation in the atmosphere, which destroys the coherence of the light waves, as well as has an impact on optical detection and communication, etc. In this paper, a phase-based measurement method for synchronously temporal and spatial distributions of atmospheric refractive-index structure parameter is applied. First of all, the depended relation between phase and refractive-index structure parameter is established, based on which an experiment is adopted. In experiment, 3600 frames of moiré fringes were obtained within an hour. And then, the phase and deflection angles distributions of moiré fringes are obtained by Fourier analysis and multi-grid method. Finally, the temporal and spatial distributions of refractive-index structure parameter are yielded according to the deduced theoretical relationship. The results show that both the temporal and spatial distributions refractive-index structure parameter could be measured by moiré deflectometry, and they are in good agreement with the existing methods. In a word, the related results could provide some references for studying the refractive-index structure parameter and the influence of atmosphere on optical detection and communication.

Phase-Based Quantification of Sports Performance Metrics Using a Smart IoT Sensor

Sports performance is often judged based on the results of a series of motions rather than observing and analyzing the detailed sequential motions that lead to the results. Hence, subjective feedback from the coaches is often ineffective in improving player performance. In this work, we custom-built a smart Internet-of-Things wristband motion sensor to implement data-based sports performance evaluation. A phase-based feature selection method is also proposed to assess the athletes sequential detailed motion for selected sport activities. To demonstrate the merits of this technology, we quantified the quality of the sequential motions of a specific type of volleyball-serve by analyzing 183 samples of motion data obtained from a total of 18 players. The general skill levels (i.e., elite, sub-elite, and amateur) of the players were identified by machine learning algorithms, with accuracies of up to 95%. Moreover, we adopted biomechanical principles to extract 11 motion-related performance metrics from various phases of the players serve motion. We identified the distributions of these metrics across different skill levels and found 8 key metrics that were highly correlated to the skill level of a players. We suggest that these metric distributions can be used as a reference for providing feedback to the coaches and players, to improve a players skill in the future. This phased-based analysis method can potentially be applied across many sports to increase the effectiveness of athletes training.

Clutter and Interference Cancellation in River Surface Velocity Measurement with a Coherent S-Band Radar

Using a Doppler radar to measure river surface velocity is a safe and effective technique. However, the measurement would be severely affected by undesired targets that enter the illuminated area of radar. The issue is worsened when measuring the surface velocities of wide rivers because undesired targets such as boats and ships are more likely to be present. The buoy boats fixed on the river surface and cargo ships sailing on the river would generate ground clutter and moving target interference, respectively. The clutter and interference can mask the signal produced by the Bragg scattering and seriously bias the extraction result of river surface velocity. This paper proposes two effective methods to remove ground clutter and moving target interference, respectively. One is an improved phase-based method that eliminates ground clutter after obtaining its boundaries through the phase in the frequency domain, and another is an improved constant false alarm rate (CFAR) detector that combines smallest-of selection logic and a multi-step deletion scheme to detect and remove interference in the time-Doppler spectrum. The experimental data measuring the surface velocity of the Yangtze River with a coherent S-band radar in July 2022 are used to verify the proposed methods. The results show that the proposed methods can effectively remove ground clutter and moving target interference, respectively. After clutter and interference cancellation, a more reasonable result of river surface velocity distribution can be extracted. Therefore, the methods proposed in this paper can be used to remove clutter and interference when extracting the surface velocity of rivers with numerous undesired targets.

Extreme Wave Loading on a Vertical Circular Cylinder

Extreme wave loading on a marine structure, consisting of a quasi-static and a dynamically slamming component, often drives the design of such a structure. Their accurate predictions remain challenging tasks. This paper examines the slamming contribution to the force–time histories from a series of experiments in which the crest of a wave is forced to hit a truncated cylinder suspended from above. A range of inundation levels, representing the breaker heights, are considered. The work also provides insights into nonlinear load characteristics on a vertical truncated cylinder. A simple analytical model based on the Newtonian momentum analysis is extended to describe the scaling of the horizontal peak force with the inundation level, i.e., the relationship between the wave slamming loads and the breaker height. More specially, it is found that the peak horizontal impact force is proportional to the inundation level and the square of the linear wave amplitude. In addition, the horizontal and the vertical impact forces on a truncated cylinder are found to increase with the increasing inundation level, while the effect from the wave steepness is relatively small. Furthermore, the higher-order wave components driving nonlinear (quasi-static) loading on a structure are separated by applying a phase-based separation method assuming a Stokes-like approximation. The separation method is found to work well even for long shallow-water waves that have strong nonlinearities. The results suggested that the relative contribution from the fundamental linear wave and higher-order wave components decreases and increases with the increasing nonlinearity of long waves, respectively, characterized by the Ursell number. Finally, this increase in the higher-order wave components is found to be saturated at large Ursell numbers.

Extracting high-precision full-field displacement from videos via pixel matching and optical flow

Accurate sensing of full-field displacements plays a significant role in dynamic testing for structural health monitoring (SHM). Recently, video camera has become a more promising tool in displacement sensing due to advantages such as low price, agility, simultaneous measurement, and high spatial sensing resolution. Traditional target tracking approaches (e.g., digital image correlation, template matching, etc.) typically require clear targets on the structure surface and thus only provide sparse displacement. Phase-based motion extraction enables full-field displacement measurement at subpixel precision without the need of markers as tracking targets, which has achieved great success in structural modal identification among many other SHM applications. However, the phase-based approach in a Eulerian framework fails to deal with large motions. To tackle these challenges, an enhanced phase-based method, that synergistically combines the developed local amplitude supplemented pixel matching algorithm and optical flow processing, is proposed for full-field displacement sensing with subpixel precision meanwhile capable of dealing with large motions. In particular, the pixel matching estimates the integer-pixel motion vectors of pixels which have sufficient texture contrast determined by local amplitude. The optical flow, represented by the first order Taylor series, is then employed to approximate the rest subpixel motion associated with the integer-pixel motion vectors. The proposed technique is validated by processing a field-test videos with LVDT reference and then applied to other several lab/field recorded videos of different vibrational objects for displacement extraction and modal identification.

A Phase-based EEG Epoch Selection Method for Decoding Bi-directional Hand Movement Imagination in Stroke Patients.

Electroencephalogram (EEG) based non-invasive Brain Computer Interface (BCI) system is gaining significant attention as a promising solution for stroke rehabilitation. Accurate selection of informative EEG time segment, that accommodates the specific neural activity patterns associated with the underlying mental task can help to improve the efficacy of the BCI system. In this work, we propose a phase-based EEG epoch selection algorithm to extract the discriminative EEG time segment corresponding to bi-directional hand motor imagery. The imagined center-out hand movement in two directions is decoded using the selected epoch of the EEG, recorded from 16 stroke patients with hemiparesis and specifically hand weakness. Phase Lock Value (PLV) EEG features extracted from the selected EEG epoch is used as discriminative feature for binary classification of imagined hand movement direction using Linear Discriminant Analysis. The use of selected EEG epoch yielded an improvement of 11.5% and 11.7% in the average direction classification accuracy of calibration and feedback session data respectively, compared to the baseline method employing the whole EEG signal. In addition to improvement in decoding accuracy, the epoch selection also yielded an average Information Transfer Rate (ITR) of 39.8±24.6 bits per minute, which is 86% improvement compared to the baseline method.Clinical Relevance- The proposed Motor Imagery (MI)-BCI system may be of clinical relevance as an active rehabilitation tool for stroke-affected patients, to enhance neural plasticity and recovery of centre-out activities of affected hand and forms a strong platform for MI-BCI coupled with exoskeletons or prosthesis rehabilitation.