Single Image Super-Resolution with Arbitrary Magnification Based on High-Frequency Attention Network

Among various developments in the field of computer vision, single image super-resolution of images is one of the most essential tasks. However, compared to the integer magnification model for super-resolution, research on arbitrary magnification has been overlooked. In addition, the importance of single image super-resolution at arbitrary magnification is emphasized for tasks such as object recognition and satellite image magnification. In this study, we propose a model that performs arbitrary magnification while retaining the advantages of integer magnification. The proposed model extends the integer magnification image to the target magnification in the discrete cosine transform (DCT) spectral domain. The broadening of the DCT spectral domain results in a lack of high-frequency components. To solve this problem, we propose a high-frequency attention network for arbitrary magnification so that high-frequency information can be restored. In addition, only high-frequency components are extracted from the image with a mask generated by a hyperparameter in the DCT domain. Therefore, the high-frequency components that have a substantial impact on image quality are recovered by this procedure. The proposed framework achieves the performance of an integer magnification and correctly retrieves the high-frequency components lost between the arbitrary magnifications. We experimentally validated our model’s superiority over state-of-the-art models.

Residue Regulating Homotopy Method for Strongly Nonlinear Oscillator

It is highly desired yet challenging to obtain analytical approximate solutions to strongly nonlinear oscillators accurately and efficiently. Here we propose a new approach, which combines the homtopy concept with a “residue-regulating” technique to construct a continuous homotopy from an initial guess solution to a high-accuracy analytical approximation of the nonlinear problems, namely the residue regulating homotopy method (RRHM). In our method, the analytical expression of each order homotopy-series solution is associated with a set of base functions which are pre-selected or generated during the previous order of approximations, while the corresponding coefficients are solved from deformation equations specified by the nonlinear equation itself and auxiliary residue functions. The convergence region, rate and final accuracy of the homotopy are controlled by a residue-regulating vector and an expansion threshold. General procedures of implementing RRHM are demonstrated using the Duffing and Van der Pol-Duffing oscillators, where approximate solutions containing abundant frequency components are successfully obtained, yielding significantly better convergence rate and performance stability compared to the other conventional homotopy-based methods.

3D Inductive Frequency Selective Structures Using Additive Manufacturing and Low-Cost Metallization

The use of additive manufacturing and different metallization techniques for prototyping radio frequency components such as antennas and waveguides are rising owing to their high precision and low costs. Over time, additive manufacturing has improved so that its utilization is accepted in satellite payloads and military applications. However, there is no record of the frequency response in the millimeter-wave band for inductive 3D frequency selective structures implemented by different metallization techniques. For this reason, three different prototypes of dielectric 3D frequency selective structures working in the millimeter-wave band are designed, simulated, and manufactured using VAT photopolymerization. These prototypes are subsequently metallized using metallic paint atomization and electroplating. The manufactured prototypes have been carefully selected, considering their design complexity, starting with the simplest, the square aperture, the medium complexity, the woodpile structure, and the most complex, the torus structure. Then, each structure is measured before and after the metallization process using a measurement bench. The metallization used for the measurement is nickel spray flowed by the copper electroplating. For the electroplating, a detailed table showing the total area to be metallized and the current applied is also provided. Finally, the effectiveness of both metallization techniques is compared with the simulations performed using CST Microwave Studio. Results indicate that a shifted and reduced band-pass is obtained in some structures. On the other hand, for very complex structures, as in the torus case, band-pass with lower loss is obtained using copper electroplating, thus allowing the manufacturing of inductive 3D frequency selective structures in the millimeter-wave band at a low cost.

Influence of low-frequency variability on high and low groundwater levels: example of aquifers in Paris Basin

Groundwater levels (GWL) very often fluctuate over a wide range of timescales (infra-annual, annual, multi-annual, decadal). In many instances, aquifers act as low-pass filters, dampening the high-frequency variability and amplifying low-frequency variations (from multi-annual to decadal timescales) which basically originate from large-scale climate variability. In the aim of better understanding and ultimately anticipating groundwater droughts and floods, it appears crucial to evaluate whether (and how much) the very high or very low GWLs are sensitive to such low-frequency variability (LFV), which was the main objective of the study presented here. As an example, we focused on exceedance and non-exceedance of the 80 % and 20 % GWL percentiles respectively, in the Paris Basin aquifers over the 1976–2019 period. GWL time series were extracted from a database consisting of relatively undisturbed GWL time series regarding anthropogenic influence (water abstraction by either continuous or periodic pumping) over Metropolitan France. Based on this dataset, our approach consisted of exploring the effect of GWL low-frequency components on threshold exceedance and non-exceedance by successively filtering out low-frequency components of GWL signals using maximum overlap discrete wavelet transform (MODWT). Multi-annual (~7-yr) and decadal (~17-yr) variabilities were found to be the predominant LFVs in GWL signals, in accordance with previous studies in the northern France area. Filtering out these components (either independently or jointly) to (i) examine the proportion of high level (HL) and low level (LL) occurrences generated by these variabilities, (ii) estimate the contribution of each of these variabilities in explaining the occurrence of major historical events associated to well-recognized societal impacts. A typology of GWL variations in Paris Basin aquifers was first determined by quantifying the variance distribution across timescales. Four GWL variation types could be found according to the predominance of annual, multi-annual or/and decadal variabilities in these signals: decadal dominant (type iD), multi-annual and decadal dominant (type iMD), annual dominant (type cA), annual and multi-annual dominant (type cAM). We observed a clear dependence of high and low GWL to LFV for aquifers exhibiting these four GWL variation types. In addition, the respective contribution of multi-annual and decadal variabilities in the threshold exceedance varied according to the event. In numerous aquifers, it also appeared that the sensitivity to LFV was higher for LL than HL. A similar analysis was conducted on the only available long-term GWL time series which covered a hundred years. This allowed us to highlight a potential influence of multidecadal variability on HL and LL too. This study underlined the key role of LFV in the occurrence of HL and LL. Since LFV originates from large-scale stochastic climate variability as demonstrated in many previous studies in the Paris Basin or nearby regions, our results point out that i) poor representation of LFV in General Circulation Models (GCM) outputs used afterwards for developing hydrological projections can result in strong uncertainty in the assessment of future groundwater extremes (GWE), ii) potential changes in the amplitude of LFV, be they natural or induced by global climate change, may lead to substantial changes in the occurrence and severity of GWE for the next decades. Finally, this study also stresses the fact that due to the stochastic nature of LFV, no deterministic prediction of future GWE for the mid- or long term horizons can be achieved even though LFV may look periodic.

Investigation on vibro-impacts of driveline system based on a nonlinear clearance element with time-varying stiffness and oil-squeeze damping

The transient vibro-impacts induced by clearance between the connected rotors in driveline system easily causes serious transient noise and vibration, especially between the gear teeth with backlash. To analyze the transient vibro-impacts of the driveline system excited by a step-down engine torque, a new piecewise nonlinear clearance element with time-varying stiffness and oil squeeze damping is proposed, and an 8 degree-of-freedom lumped parameters model with the new piecewise nonlinear clearance elements is established. The transient vibro-impact phenomena of the vehicle driveline during fast disengagement of the clutch are numerically simulated. Colormaps of angular acceleration and vibro-impact force shows the difference of frequency components from transient impact to stable tooth-meshing. The phase plane reveals the phenomenon of multiple impacts and rebounds in each transient impact, and shows the relationship between the relative contact displacement and velocity. The frequency responses of the angular velocity, angular acceleration and vibro-impact forces with time-varying stiffness and linear stiffness are compared respectively. Compared with the widely used clearance element with piecewise linear stiffness, the new nonlinear clearance element with the piecewise nonlinear time-varying stiffness can better reveal the transient vibro-impact responses between the driving and driven gears. Lastly, the transient vibro-impact results of driveline system are verified by the vehicle experiments.

Adaptive Scheme for Detecting Induction Motor Incipient Broken Bar Faults at Various Load and Inertia Conditions

This paper introduces a novel online adaptive protection scheme to detect and diagnose broken bar faults (BBFs) in induction motors during steady-state conditions based on an analytical approach. The proposed scheme can detect precisely adjacent and non-adjacent BBFs in their incipient phases under different inertia, variable loading conditions, and noisy environments. The main idea of the proposed scheme is monitoring the variation in the phase angle of the main sideband frequency components by applying Fast Fourier Transform to only one phase of the stator current. The scheme does not need any predetermined settings but only one of the stator current signals during the commissioning phase. The threshold value is calculated adaptively to discriminate between healthy and faulty cases. Besides, an index is proposed to designate the fault severity. The performance of this scheme is verified using two simulated motors with different designs by applying the finite element method in addition to a real experimental dataset. The results show that the proposed scheme can effectively detect half, one, two, or three broken bars in adjacent/non-adjacent versions and also estimate their severity under different operating conditions and in a noisy environment, with accuracy reaching 100% independently from motor parameters.

The value of very low frequencies and far offsets for seismic data in the Permian Basin: Case study on a new dense survey from the Central Basin Platform

The depth of penetration and multidimensional characteristics of seismic waves make them an essential tool for subsurface exploration. However, their band-limited nature can make it difficult to integrate them with other types of ground measurements. Consequently, far offsets and very low-frequency components are key factors in maximizing the information jointly inverted from all recorded data. This explains why extending seismic bandwidth and available offsets has become a major industry focus. Although this requirement generally increases the complexity of acquisition and has an impact on its cost, improvements have been clearly and widely demonstrated on marine data. Onshore seismic data have generally followed the same trend but face different challenges, making it more difficult to maximize the benefits, especially for full-waveform inversion (FWI). This paper describes a new dense survey acquired in 2020 in the Permian Basin and aims to objectively assess the quality and benefits brought by a richer low end of the spectrum and far offsets. For this purpose, we considered several aspects, from acquisition design and field data to FWI imaging and quantitative interpretation.

Fault Frequency Identification of Rolling Bearing Using Reinforced Ensemble Local Mean Decomposition

The vibration signal of rolling bearing exhibits the characteristics of energy attenuation and complex time-varying modulation caused by the transmission with multiple interfaces and complex paths. In view of this, strong ambient noise easily masks faulty signs of rolling bearings, resulting in inaccurate identification or even totally missing the real fault frequencies. To overcome this problem, we propose a reinforced ensemble local mean decomposition method to capture and screen the essential faulty frequencies of rolling bearing, further boosting fault diagnosis accuracy. Firstly, the vibration signal is decomposed into a series of preliminary features through ensemble local mean decomposition, and then the frequency components above the average level are energy-enhanced. In this way, principal frequency components related to rolling bearing failure can be identified with the fast spectral kurtosis algorithm. Finally, the efficacy of the proposed approach is verified through both a benchmark case and a practical platform. The results show that the selected fault characteristic components are accurate, and the identification and diagnosis of rolling bearing status are improved. Especially for the signals with strong noise, the proposed method still could accurately diagnose fault frequency.

Experimental Study on Source Failure Mechanism and Acoustic Emission Characteristics of Red Sandstone Under Uniaxial Compression

In order to study the rock fracture mechanism and precursor characteristics, uniaxial compression experiments of red sandstone were carried out. Using acoustic emission technology and digital speckle correlation method as experimental observation means, the evolution characteristics of deformation field and acoustic emission index during rock deformation were studied. The results show that : (1) The deformation concentration of rock deformation localization zone is the main cause of nonlinear evolution of rock stress-strain curve. (2) The volume parameters of different types of cracks in rock acoustic emission change with the relative displacement rate and dislocation rate of deformation localization zone. (3) In terms of failure types, there are more high-frequency components of tensile fracture main frequency, more low-frequency components of shear fracture main frequency, and wider distribution of mixed fracture main frequency. In the time sequence, the spectrum distribution of acoustic emission signals is wide and the amplitude is small at the sudden change time. At the sudden change time, the spectrum distribution of acoustic emission signals becomes narrow, the amplitude increases, and the spectrum distribution of peak points is greatly narrowed. Therefore, it is considered that the spectrum distribution is greatly narrowed can be used as an early warning precursor.