Non-stationary Disturbances Research Articles

Extraction of patterns from images using a model of combined frequency localization spaces

An algorithm for image decomposition and separation of superposed stationary contributions is proposed. It is based on the concept of sparse-to-sparse domain representation achieved through a relationship between block-based and full-size discrete cosine transform. The L-statistics is adapted to discard nonstationary components from the frequency domain vectors, leaving just a few coefficients associated with stationary pattern. These fewer stationary components are then used under the compressive sensing framework to reconstruct the stationary pattern. The original image is observed as a nonstationary component, acting as a non-desired part at this stage of the procedure, while the stationary pattern is observed as a “desired part” that should be extracted through the reconstruction process. The problem of interest is formulated as underdetermined system of equations resulting from a relationship between the two considered transformation spaces. Once the stationary pattern is reconstructed, it can be removed entirely from the image. Furthermore, it will be shown that the efficiency of pattern extraction cannot be affected, even when image contains additional nonstationary disturbance (here, the noisy image is observed as nonstationary undesired part). The proposed approach is motivated by challenges in removing Moiré-like patterns from images, enabling some interesting applications, including extraction of hidden sinusoidal signatures.

Optimal disturbances in round submerged jets

In this paper, optimal growth analysis of spatial disturbances in round submerged jets is performed. Optimal energy growth is studied for various Reynolds numbers Re and frequencies ω. Different velocity profiles proposed by Michalke [“Survey on jet instability theory,” Prog. Aerosp. Sci. 21, 159–199 (1984)] are investigated by varying the shear layer momentum thickness δ, while the jet radius R is considered fixed (as characteristic length). In the case of stationary disturbances, there are no amplified eigenmodes, so eventually the energy of such disturbances decays downstream. Such disturbances are characterized by optimal energy growth as a function of streamwise coordinate z. At certain location downstream zmax this value reaches its maximum Gmax and then decays, although not monotonically, unlike the result of the temporary setting [Jimenez-Gonzalez et al., “Modal and non-modal evolution of perturbations for parallel round jets,” Phys. Fluids 27, 044105 (2015); Jimenez-Gonzalez and Brancher, “Transient energy growth of optimal streaks in parallel round jets,” Phys. Fluids 29, 114101 (2017)]. The well-known scaling Gmax∝Re2 and zmax∝Re is confirmed for stationary disturbances. Conversely, for nonstationary disturbances there is a range of frequencies in which an amplified mode is present. In this case, optimal perturbations far downstream consist only of the amplified mode. The main effect of non-modality here is “the energy pumping” of the amplified mode, so the disturbances are characterized by the “energy ratio” G/Em, i.e., the ratio of the energy of an arbitrary perturbation to the energy of the amplified mode. The influence of the shear layer momentum thickness on optimal disturbances is studied; increasing the shear layer momentum thickness of the base flow “smears” the area occupied by the optimal disturbance, although it does not dramatically affect energy gain values, slightly decreasing maximum energy as shear layer momentum thickness increases. Spatial oscillations in the energy of stationary optimal disturbances in jet flows are discovered. The spectrum structure examination shows that the frequency of these oscillations corresponds to the frequencies of the two least damped discrete eigenmodes.

A source of controlled nonstationary harmonic flow disturbances

A source of controlled nonstationary harmonic flow disturbances

Simultaneous state‐estimator tuning and parameter estimation for systems with nonstationary disturbances, multi‐rate data, and measurement delays

AbstractModel‐based monitoring and control of chemical and biochemical processes rely on state estimators such as extended Kalman filters (EKFs) to ensure accurate online model predictions. Accurate predictions depend on appropriate model parameters and suitable state‐estimator tuning factors. Extensions to our previously developed simultaneous parameter estimation and tuning (SPET) method are proposed so that SPET can be used for systems with nonstationary disturbances, time‐varying parameters, multi‐rate data, and measurement delays. A continuous stirred tank reactor (CSTR) case study with simulated data is used to illustrate and test the proposed method. Superior online model predictions and state‐estimator performance are achieved using SPET compared to a traditional approach for parameter estimation and EKF tuning, with improvements in the average sum‐of‐squared prediction errors ranging from 3% to 52% for the scenarios tested. The SPET approach will also be useful for more‐advanced state estimators that require the same tuning information as EKFs.

Influence of aerodynamic valve structural parameters on detonation initiation and back pressure characteristics of air-breathing pulse detonation engine

In order to enhance the stability of detonation initiation in air-breathing pulse detonation engines (APDE), while simultaneously mitigating the non-stationary back pressure disturbance due to the huge pressure gain in the APDE, a central blunt body aerodynamic valve (aero-valve) was developed and tested with a single-tube pulse detonation combustor (PDC). The detonation initiation and back pressure characteristics of PDC were then discussed. In order to reveal the influence of the aero-valve's structural parameters on the cold-state filling, detonation initiation, and back pressure characteristics of PDC, numerical simulations were carried out based on the experimental setup. The numerical results indicated that the cold-state flow characteristics within the aero-valve was predominantly influenced by the inner diameter of the aero-valve shell (Das), while the cold-state flow inside the combustor was primarily dominated by the axial distance from the thrust wall to the aero-valve shell (Lx) and the inner diameter of the aero-valve outlet (dout). And dout has a larger impact on the cold-state flow inside the combustor. During the hot state, reducing Lx or dout is beneficial for both the generation of detonation and the suppression of back pressure, with the most significant gain effect coming from decreasing dout. The optimal combination scheme for the aero-valve is identified as Das/R = 4.5, Lx/R = 0.25 and dout/R = 0.7, where R is the detonation combustor radius. The PDC equipped with this optimized aero-valve not only has better detonation initiation characteristics, but also a smaller pressure oscillation ratio.

Adaptive semiactive control of structure with magnetorheological dampers using wavelet packet transform

Conventional active controllers generally adopt initial dynamic properties of intact structures to calculate optimal control force for magnetorheological damper, which eventually leads to ideal damping force of the device. Also, they cannot assure trade-off between damping force and response reduction under non-stationary excitations. To this end, an adaptive semiactive control algorithm for magnetorheological damper is proposed. Using wavelet packet transform, an improved control law determines optimal control forces in terms of resonant and non-resonant frequency bands in time interval. Both frequency bands are established based on natural frequency(ies) of structures, making damping force rely on actual structural properties and achieving trade-off under non-stationary disturbances. A refined clipped-optimal control algorithm is then deployed to convert optimal control force to the device’s voltage. A numerical study of a six-degree-of-freedom structure under four near- and far-fault ground accelerations reveals that the scheme outperforms existing controllers while attaining cost-effectiveness of damping force versus response alleviations.

NON-STATIONARY WAVES IN A FUNCTIONALLY GRADED VISCOELASTIC PLANE-PARALLEL LAYER2

The propagation of nonstationary disturbances in a plane-parallel layer of infinite extent, which arise as a result of normal dynamic loading of one of its surfaces when the other surface is stationary, is investigated. The material of the layer is assumed to be functionally graded and, at the same time, viscoelastic. The hereditary properties of such a material are taken into account using linear integral Boltzmann–Volterra relations with regular kernels in the form of partial sums of the Prony's series. The peculiarity of this work is that here the parameters of the relaxation kernels are considered continuous functions of the transverse coordinate in the same way as other physical and mechanical characteristics. A method was used for the study, which consists in replacing a functionally graded material with an approximating layered homogeneous structure with continuity conditions at the contact of homogeneous layers. The solution of the nonstationary dynamic linear viscoelasticity problem for a package of plane homogeneous viscoelastic layers is presented in a special form, which greatly simplifies its numerical implementation, especially with a large number of layers with different hereditary properties. This made it possible to successfully apply this method and carry out a series of calculations using an efficient algorithm. Transient wave processes are investigated in the case when the parameters of a functionally graded material are non-monotonic functions of the transverse coordinate, symmetrical with respect to the middle surface of the layer. A comparison of transient wave processes for different types of these functions is carried out. The convergence of the calculation results with an increase in the number of approximating homogeneous layers with a continuous dependence of the external load on time is confirmed. The significant influence of both heterogeneity and viscosity of the material on nonstationary wave processes has been established.

Generalised performance of neural network controllers for feedforward active noise control of nonlinear systems

Advances in digital technologies have allowed for the development of complex active noise and vibration control solutions that have been utilised in a wide range of applications. Such control systems are commonly designed using linear filters, which cannot fully capture the dynamics of nonlinear systems. To overcome such issues, it has been shown that replacing linear controllers with Neural Networks (NNs) can improve control performance in the presence of nonlinearities. Many real systems are subject to non-stationary disturbances where the magnitude of the system excitation time dependent. However, within the literature, the performance of single NN controllers across different excitation levels has not been thoroughly explored. In this paper, a method of training Multilayer Perceptrons (MLPs) for single-input-single-output (SISO) feedforward acoustic noise control is presented. In a simple time-discrete simulation, the performance of the trained NNs is investigated for different excitation levels. The effects of the properties of the training data and NN controller on generalised performance are explored. It is demonstrated that the generalised control performance of the MLP controllers falls as the range of magnitudes included in the training data is increased, and that this performance can be recovered by increasing the number of hidden nodes within the controller.

Convergence Analysis of the Phase-Scheduled-Command FXLMS Algorithm with Phase Error

In this paper, a phase-scheduled-command filtered-x least mean square (FXLMS) algorithm with a phase error between the disturbance and command signal is analyzed in detail. The influence of the phase error on the control effort, convergence time constant and performance of convergence is explained for both stationary and nonstationary disturbance signal cases. An estimation ratio, in both stationary and nonstationary disturbance cases, of the pseudo-error MSE convergence performance is also developed and discussed. Simulation results were collected to verify the analysis. The results show that, for both stationary and nonstationary disturbance, the phase error may heavily increase the distance of the optimum vector from the initial value, leading to a large control effort, a large convergence time constant and poor convergence performance. The estimation ratio also has a satisfactory performance for estimating the influence of the phase error.

Deconvolutional Suppression of Resolution Degradation in Coherent Optical Spectrum Analyzer

Optical spectral analysis is essential to demonstrate the light-matter interactions from the frequency domain. Although the existing coherent spectrum analyzers (COSA) have already achieved resolutions of ∼50 fm, the mirror effect limits the further improvement in spectral resolution and thus the detection of low-concentration, small-scale analytes. Focusing on this problem, we first formulate the resolution degradation of COSA caused by the mirror effect, indicating the tuning nonlinearity of the local oscillator could introduce a non-stationary disturbance to the spectral data sampled at equal time intervals. Subsequent theoretical and experimental works have proved that the combination of dynamic wavelength calibration and spectral deconvolution can suppress the non-stationary disturbance. And the spectral resolution could reach 8 fm without extra compressions. This deconvolution-based scheme also avoids the long fibers used in scattering compressed schemes, improving the system's environmental stability.

Design of Sliding Mode Controller based on Radial Basis Function Neural Network for Spacecraft Autonomous Proximity

Since the dynamic model of spacecraft has the characteristics of non-linear, kinematic couplings, uncertainties and nonstationary disturbance, it has become a challenging problem to accurately control the relative position and attitude of the spacecraft. A radial basis function neural network (RBFNN)-based sliding mode controller (SMC) is proposed for trajectory tracking of spacecraft autonomous proximity in this paper. Firstly, a six degree-of-freedom (DOF) relative motion dynamics model is developed for close proximity operations. The modified Rodrigues parameters are applied to solve the problem of singularity. Then, a SMC that does not require accurate model information is designed. RBFNN is used to adaptively eliminated the model uncertainty impacts on the system. Finally, the stability of the relative motion dynamics is proved via Lyapunov stability theory. Simulation results illustrate that the method can attenuate the attitude and position errors, reduce the chattering of the input and decrease the overshoot of the control torque effectively.

An Integrated Approach Improved Fast S-transform and SVD Noise Reduction for Classification of Power Quality Disruptions in Noisy Environments

Degraded power quality (PQ) significantly jeopardizes the safety, economics, and efficiency of electricity users. Effective power quality disturbance (PQD) classification is critical for power quality control. To address the issue of noise obscuring the time-frequency domain characteristics of PQD extraction, this research introduces a novel method based on singular value decomposition (SVD) and an improved fast S-transform (IFST). To begin, the disturbance signal is noise reduced using SVD to produce a denoised signal. This denoised signal is then processed using differential sum to generate the exact feature F1, which is used to distinguish stationary from nonstationary disturbances. Additionally, the denoised signal is subjected to IFST to extract features F2–F5. Finally, the five most effective features are fed into a simple ruled decision tree (DT) to automate the classification of disturbances, which includes seven single PQDs and six complex PQDs. The utility of the proposed technique was proven in this research by utilizing both simulated disturbances under varied noise conditions and real data. In comparison to established techniques, the unique method outperforms them in terms of anti-noise performance, allowing for more precise classification of varied types of disturbances, and the extracted specific features can intuitively reflect the dynamic changes in disturbances.

Parameter and uncertainty estimation in stochastic differential equation models with multi-rate data and nonstationary disturbances

Updated methods are proposed for estimating model parameters and error-covariance matrices in stochastic differential equation (SDE) models. New expressions, based on the LAMLE (Laplace Approximation Maximum Likelihood Estimation) and LAB (Laplace Approximation Bayesian) SDE estimation methods are derived so that LAMLE and LAB can be used for systems with multi-rate data and nonstationary disturbances. The updated LAMLE method is tested using simulated data from a two-state continuous stirred tank reactor (CSTR) model. Comparisons are made with the results obtained using the continuous-time stochastic method (CTSM), confirming that the updated LAMLE algorithm provides reliable estimates for unknown model parameters, measurement noise variances, and process-error variances. In all situations tested, the updated LAMLE algorithm converged to reliable parameter and uncertainty estimates, while avoiding convergence difficulties encountered by CTSM in some situations. The updated LAMLE and LAB algorithms will be useful for parameter estimation in online models used in advanced process monitoring and control applications where multi-rate data and nonstationary disturbances are often encountered. Estimates of measurement noise variances and process-error variances will be helpful for state-estimator tuning.

Dual Identification of Multi-Complex and Non-Stationary Power Quality Disturbances Using Variational Mode Decomposition in Hybrid Modern Power Systems

Dual Identification of Multi-Complex and Non-Stationary Power Quality Disturbances Using Variational Mode Decomposition in Hybrid Modern Power Systems

Robust selection of clean swept-sine measurements in non-stationary noise.

The exponential sine sweep is a commonly used excitation signal in acoustic measurements, which, however, is susceptible to non-stationary noise. This paper shows how to detect contaminated sweep signals and select clean ones based on a procedure called the rule of two, which analyzes repeated sweep measurements. A high correlation between a pair of signals indicates that they are devoid of non-stationary noise. The detection threshold for the correlation is determined based on the energy of background noise and time variance. Not being disturbed by non-stationary events, a median-based method is suggested for reliable background noise energy estimation. The proposed method is shown to detect reliably 95% of impulsive noises and 75% of dropouts in the synthesized sweeps. Tested on a large set of measurements and compared with a previous method, the proposed method is shown to be more robust in detecting various non-stationary disturbances, improving the detection rate by 30 percentage points. The rule-of-two procedure increases the robustness of practical acoustic and audio measurements.

Online Performance Monitoring of Processes Subject to Non-stationary Stochastic Disturbance

Since non-stationary disturbances are common in practical situation due to the varying stochastic disturbance or some deterministic disturbance injected, the traditional algorithm based on FCOR is not valid anymore. This paper develop a new approach, which combines EMD method with FCOR algorithm, to handle this problem such that the minimum variance (MV) performance of the closed-loop system can be monitored online. In the presence of varying stochastic disturbance and step/sine disturbance, the numerical example demonstrates the effectiveness of the proposed algorithm.

A FUNDAMENTAL SOLUTION FOR AN ANISOTROPIC PLATE ON AN INERTIAL FOUNDATION

The work is devoted to the construction of a new fundamental solution for a thin elastic anisotropic unbounded Kirchhoff plate on an inertial Winkler foundation. The fundamental solution is a function of the normal movement of two spatial coordinates and time in response to the impact of a single concentrated load, mathematically modeled by the Dirac delta function. The anisotropy model considered in this article has one plane of symmetry that geometrically coincides with the median plane of the plate and is characterized for the Kirchhoff plate model by six independent components of the tensor of elastic constants of the material. The problem statement includes the equations of motion of an anisotropic plate in displacements and initial conditions. The solution of the corresponding initial problem for the fundamental solution is constructed using integral Laplace transformations in time and two-dimensional integral Fourier transform in spatial coordinates. The inverse integral Laplace transform is found analytically with a preliminary analysis of the invertible function. The original fundamental Fourier solution is constructed using the numerical method of integrating rapidly oscillating functions. The parameters of numerical integration are calculated with a given accuracy when analyzing the quality of the desired functions by a continuous norm. For the constructed new fundamental solution, a numerical analysis of the nature of the propagation of nonstationary disturbances is carried out, and the influence of the parameters of the inertial Winkler foundation on the behavior of the normal deflection of an anisotropic plate in time at the point of action of the delta function is investigated. The asymmetric nature of unsteady plate oscillations consistent with the model of the elastic medium under consideration is demonstrated. The constructed fundamental solution makes it possible to investigate the nonstationary normal deflection of an anisotropic plate on an inertial basis under the action of arbitrary loads using an integral operator of the convolution type in spatial coordinates and time. In addition, the fundamental solution has versatility with respect to the properties of the plate materials and the parameters of the foundation, namely: isotropic, transversally isotropic and orthotropic materials can act as the plate material. In this case, the foundation may be inertialess or absent altogether.

A Novel MRE Adaptive Seismic Isolator Using Curvelet Transform Identification

Magnetorheological elastomeric (MRE) material is a novel type of material that can adaptively change the rheological property rapidly, continuously, and reversibly when subjected to real-time external magnetic field. These new type of MRE materials can be developed by employing various schemes, for instance by mixing carbon nanotubes or acetone contents during the curing process which produces functionalized multiwall carbon nanotubes (MWCNTs). In order to study the mechanical and magnetic effects of this material, for potential application in seismic isolation, in this paper, different mathematical models of magnetorheological elastomers are analyzed and modified based on the reported studies on traditional magnetorheological elastomer. In this regard, a new feature identification method, via utilizing curvelet analysis, is proposed to make a multi-scale constituent analysis and subsequently a comparison between magnetorheological elastomer nanocomposite and traditional magnetorheological elastomers in a microscopic level. Furthermore, by using this “smart” material as the laminated core structure of an adaptive base isolation system, magnetic circuit analysis is numerically conducted for both complete and incomplete designs. Magnetic distribution of different laminated magnetorheological layers is discussed when the isolator is under compressive preloading and lateral shear loading. For a proof of concept study, a scaled building structure is established with the proposed isolation device. The dynamic performance of this isolated structure is analyzed by using a newly developed reaching law sliding mode control and Radial Basis Function (RBF) adaptive sliding mode control schemes. Transmissibility of the structural system is evaluated to assess its adaptability, controllability and nonlinearity. As the findings in this study show, it is promising that the structure can achieve its optimal and adaptive performance by designing an isolator with this adaptive material whose magnetic and mechanical properties are functionally enhanced as compared with traditional isolation devices. The adaptive control algorithm presented in this research can transiently suppress and protect the structure against non-stationary disturbances in the real time.

Propagation of non-stationary kinematic disturbances from a spherical cavity in the pseudo-elastic cosserat medium

Propagation of non-stationary kinematic disturbances from a spherical cavity in the pseudo-elastic cosserat medium

The Moon is the Source of Unstable Nonstationary Disturbances in the Earth’s Atmosphere

The Moon is the Source of Unstable Nonstationary Disturbances in the Earth’s Atmosphere