Structural freeplay due to loosened mechanical linkages is a discrete nonlinear event which occurs pseudo-routinely in modern aircraft, causing severe airframe vibration. This impacts fatigue life, and has serious implications for fleet management and Structural Health Monitoring (SHM). While the concepts which drive SHM for aircraft are traditionally based on reactive procedures, we are currently

Variance-based sensitivity indices play an important role in scientific computation and data mining, thus the significance of developing numerical methods for efficient and reliable estimation of these sensitivity indices based on (expensive) computer simulators and/or data cannot be emphasized too much. In this article, the estimation of these sensitivity indices is treated as a statistical inference

This study identified fatigue cracks in a steel joint under vibration by nonlinear guided waves based on second harmonic generation. Piezoelectric transducers were utilised to excite S1 Lamb wave mode in experiment and the nonlinear ultrasonic testing was performed at different crack lengths. The contact acoustic nonlinearity (CAN) was measured in experiments and quantified by a nonlinear index to

Nowadays, with the growing scale of high-speed railways and the increasing number of high-speed trains, the research on train equipment fault diagnosis and health management becomes more and more significant. Bearings are parts which are prone to be the failure equipment on high-speed trains. The temperature of a faulty bearing will increase suddenly during the working process, which may lead to potential

The monitoring of rotating machinery is an essential task in today’s production processes. Currently, several machine learning and deep learning-based modules have achieved excellent results in fault detection and diagnosis. Nevertheless, to further increase user adoption and diffusion of such technologies, users and human experts must be provided with explanations and insights by the modules. Another

Non-ideal factors can cause steady-state speed ripples for Permanent Magnet Synchronous Motor (PMSM). In this paper current measurement error is mainly analyzed since it can cause multiple (not only 1st- or 2nd-order as analyzed in the existing literature) harmonics when considering its influence on electrical angle. In order to suppress the ripples, a robust plug-in repetitive controller with phase

Acoustic emission (AE) event location plays an important role in structural safety assessments. However, accurately locating an AE event is usually difficult, especially for a small structure. Interestingly, a pencil-lead break (PLB) experiment shows that the P-wave arrival time of a sensor is always significantly different (~260 µs) from that of the other sensors. This time difference is much greater

A nonlinear Euler–Bernoulli model of slender piezoelectric beams is employed to investigate parametric resonance motions driven by a pulsating voltage with a DC component. The beam model is based on 3D electric charge conservation and 1D reduction of the momentum balance laws assuming as space coordinate the arclength along the beam base line as space coordinate. The 3D constitutive relationships for

This paper proposes a generalized subset simulation (GSS) method for estimating small failure probability. The basic idea is to modify the failure threshold and amplify the variability of input variables simultaneously in a sequential way. With a proper choice of the intermediate failure thresholds and amplification factors, the problem of estimation of a small failure probability is decomposed into

In order to improve the energy efficiency and suppress the environmental pollutants of marine diesel engines, analysis and control of combustion phases including late combustion phase and premixed combustion phase are considered as an attractive potential strategy. Consequently, it is necessary to accurately identify the combustion parameters that are representative to these combustion phases, such

Rolling bearing fault diagnosis is of great significance to the stable operation of rotating machinery systems. However, the fault data collected in practical engineering is seriously imbalanced, which degrades the diagnosis performance. In this paper, a novel data synthesis method called deep feature enhanced generative adversarial network is proposed to improve the performance of imbalanced fault

We study the geometrically nonlinear vibrations of rectangular micro/nanoplates with an account of small-scale effects in a framework of the nonlocal elasticity theory. Hamilton’s principle yields the governing system of nonlinear partial differential equations (PDEs) based on the Kirchhoff-Love hypotheses and geometric nonlinearity introduced through the von Kármán theory. Next, we employed a strategy

As a multi-frequency identification method, the MUSIC method has received more and more attention in the field of blade tip-timing (BTT) signal reconstruction. So far, an improved MUSIC method and a subspace dimension-reduced MUSIC (SDR-MUSIC) method were proposed to analyze BTT signals. However, they must rely on the expanded snapshot matrix to overcome the spectrum aliasing. The computational complexity

Most of stochastic optimal control methods were developed on the basis of Itô stochastic differential equation, which assumes that the external excitation is white Gaussian noise or filtered white Gaussian noise. However, this assumption is far from the real excitations, which hinders the applications of stochastic optimal control theory. In this paper, the reliability-based stochastic optimal control

This paper presents a multi-domain dynamic simulation model for continuous-contact helical gear pumps, which is an unconventional hydraulic pump design that is capable of canceling its kinematic flowrate variation. In this model, the fluid dynamics (in its lumped-element representation) are fully coupled in a closed feedback loop with other physical domains, including critical tribological interfaces

The coupled simulation of numerical and real subsystems is sometimes called ‘hybrid substructuring’, ‘hardware in the loop (HIL)’, ‘cyberphysical simulation’, or ‘hybrid simulation’, and is an active field of research. In this publication, an iterative algorithm for a coupled simulation of a numerical subsystem and a real (experimental) one is presented. The term ‘iterative’ means that the subsystems

Sparse polynomial chaos expansion (PCE) can be used to emulate the stochastic model output where the original model is computationally expensive. It is a powerful tool in efficient uncertainty quantification and sensitivity analysis. Structural systems are usually associated with high dimensional and probabilistic input. The number of candidate basis functions increases significantly with input dimension

Smoothed Particle Hydrodynamics (SPH) is a fully Lagrangian method that does not require the use of any mesh. Due to its advantages, SPH method is usually adopted to simulate flows with free surfaces. Based on traditional SPH, non-inertial SPH as a new method is proposed recently to deal with cases when the liquid is subjected to inertial force for the motion of reference frame. This study finds that

Structural Health Monitoring is gaining popularity in recent times because of advancements in technology and the increasing need for repair and rehabilitation. The shift from conventional wired technologies to advanced wireless technologies is also gradually increasing in the past decade. These sensor networks are economical when used for monitoring huge structures with high design life and safety

In recent years, research on the effect of uncertainty on the results of structural system identification in order to effectively enhance structural safety has been rarely conducted. This paper studies identification and uncertainty quantification of structural flexibility from ambient vibration measurements to develop an efficient reliability analysis. The structural deflection with a confidence interval

A growing body of evidence has suggested that fractional-order models are able to describe dynamic processes with higher accuracy, such that thermal conduction processes are found to be depicted with time-delay with single-fractional-pole (TDSFP) models. Actuator rate limit phenomenon is extremely common in manufacturing due to either physical limitation or production safety guarantee. The popular

In this paper, a novel piecewise affine (PWA) modeling framework and a hybrid optimal control scheme based on the developed PWA model for the intelligent vehicle longitudinal dynamics are proposed. The proposed methodology approximates the nonlinear characteristics of the system major components, i.e. the engine, the automatic transmission and the tire, using the PWA representation method firstly.

We propose an asymmetric viscoelastic metamaterial constructed from a unit with two distinct resonators selected to isolate elastic waves in a large coupled locally resonant bandgap (LRBG) and simultaneously realize designed unidirectional zero reflection (UZR). A generalized Maxwell model, as opposed to a Kelvin–Voigt model or standard linear solid model, is adopted to more accurately describe actual

For a structural dynamics engineer assessing a system’s vibration characteristics, the frequency response function (FRF) is indispensable, irrespective of whether the setup being tested is experimental, numerical or analytical. This paper outlines the different FRF estimation techniques that have been developed over the years. Algorithms that compute an ordinary least squares (OLS) estimate of the

In this work parametric reduced order models (pROMs) for cracked shells are developed and applied to crack detection problems. Mesh morphing is employed to allow for parameterization of the models with respect to the crack location and size, while a clustering approach is adopted to partition the parameter space in sub-domains, for which efficient local reduced order models (ROMs) are constructed.

Damage localization in plate-type structures via full-field vibration measurements has attracted much more attention. Traditionally, the damage-induced local shape singularities at a certain mode are harnessed for damage localization, but this is not reliable and robust for multi-damage localization. Therefore, a general strategy is that the damage features in different modes should be accurately extracted

Conventional stochastic response analysis methods of vehicle-bridge (VB) systems involve a brute-force calculation based on a large number of simulations, which imposes huge computational burdens because the dynamic analysis of a time-dependent VB system requires repeated assembles of system matrices. This paper proposes a novel stochastic analysis method of transient responses for time-dependent VB

Engineers often use similitude analyses to design small scale models for experimental tests or to design size ranges of mechanical structures such as drive technology systems. This paper is concerned with similitude analysis methods for vibration analyses of rectangular plates. If their geometry is scaled by different factors (distorted similitude), the scaling laws approximate the actual vibration

This work presents a new technique for nonlinear system identification that utilizes near-resonant steady-state harmonically excited vibration measurements to estimate the Nonlinear Normal Mode backbones. The algorithm is based on the previously proposed Single Nonlinear Resonant Mode formula and uses it in a new and more effective way to estimate one point on the nonlinear mode from only one steady-state

In this paper, we propose a numerical method to calculate the dynamic mesh forces of planetary gear transmissions (PGTs). In this model, the effects of addendum modification are included in the time-varying mesh stiffness (TVMS) and then the influence of TVMS and relative mesh phase on the dynamic mesh forces are considered in the proposed model. To verify the proposed model, an experimental method

The widespread use of plastic pipes in different fluid conveyance systems has greatly driven the recent development and application of transient-based methods (TBMs) for leak detection in viscoelastic/polymeric pipelines. Current TBMs for viscoelastic pipe leak detection are usually achieved by a two-step procedure, namely viscoelastic parameters identification and leak detection, which requires the

The paper investigates the static and dynamic lubrication parameters of the floating ring bearing (FRB). Modified lubrication models considering the effects of various coupling factors are proposed. Multiscale methods are exploited to enhance the accuracy and efficiency of the calculation. The simulation procedures are developed to analyze the lubrication performances. Theoretical results agree well

This paper investigates the control issue of the trajectory tracking of vertical take-off and landing (VTOL) unmanned aerial vehicles (UAVs) in the presence of partial propeller fault and external disturbance. In particular, a robust passive fault-tolerant control strategy is proposed by introducing a first-order filter based dynamics estimator. First, a bounded force command is exploited by employing

The amplitude and phase estimation of a sinusoid (APES) method, receiving superior results to conventional Fourier transform (FT) featured as narrower spectral peaks and lower side-lobe levels, has been widely applied in the fields of medical imaging, remote sensing, synthetic aperture radar, etc. Both FT and APES suppose the signal collected is stationary. When handing with non-stationary signals

Stereo digital image correlation (stereo-DIC) technique shows a powerful capacity on full-field three-dimensional (3D) deformation measurement of rotary machine structures. However, it remains a challenge for underwater applications due to difficulties in imaging, stereo calibration, light refraction, and so on. In this paper, its potential in characterizing 3D dynamic deformation of the underwater

The wheel tread wear of heavy haul freight car in operation leads to shortened wheel turning period, reduced operation life, and poor train operation performance. In addition, wheel rail wear is a complex non-linear problem that integrates multiple disciplines. Thus, using a single physical or mathematical model to accurately describe and predict it is difficult. How to establish a model that could

In the last years, scientific and industrial communities have put a lot of efforts into the development of a new framework for the assessment of structural integrity, generally known as Structural Health Monitoring (SHM), which should allow real-time, automatic evaluations of the state of the structures based on a network of permanently installed sensors. In the context of mechanical, aerospace and

Structural health monitoring (SHM) has played a crucial role in continuously assuring adequate integrity across equipment, especially early loosening estimation of bolt joints. Recently, the vibro-acoustic modulation (VAM) technique for bolt early loosening monitoring has received much attention due to its high sensitivity to contact-type defects. However, the current early loosening monitoring mostly

The computational efficiency of a sampling based nonlinear Kalman filtering process is mainly conditional on the number of sigma/sample points required by the filter at each time step to effectively quantify statistical properties of related states and parameters. Efficaciously minimizing the needed number of points would therefore have important implications, especially for large n-dimensional nonlinear

This paper presents a wavelet-based method for determining response evolutionary power spectrum density (EPSD) of linear/non-linear systems endowed with fractional derivative elements. Specifically, first, the generalized harmonic wavelets (GHWs) based Galerkin approximation of the stochastic processes are utilized to transform the fractional-order stochastic linear/non-linear differential equations

Testing nonlinear structures to characterise their internal nonlinear forces is challenging. Often nonlinear structures are excited by harmonic forces and yield a multi-harmonic response. In many systems, particularly ones with strong nonlinearities, the effect of higher harmonics in the force and responses cannot be ignored. Even if the intended excitation is a single frequency sinusoidal force, the

An improved method, termed as the AL-DLGPR-PDEM, is presented to address high-dimensional reliability problems. The novelty of this work lies in developing a complete framework for combining the deep learning (DL) architectures, serving as the utility of dimension reduction, and the Gaussian process regression (GPR), resulting in the so-called DLGPR model. First, the parameters of both the DL and the

When the primary reference signal obtained by the existing Active noise control (ANC) system is not accurate, the control effect of interior noise will be reduced or even fail. Considering the fault-tolerate and robustness of the system, the study proposes an adaptive nonlinear ANC system for interior noise, which contains noise signal decomposition, multi-network reconstruction model and Variable

An elliptical ring is used to implement a novel type of high-static-low-dynamic vibration isolation. Under the compression deformation, the elliptical ring produces a nonlinear restoring force due to the coupling of the tension and the curvature caused by the stretching. For the elliptical ring under a uniaxial pressure, its force-displacement relation is derived from the Euler–Bernoulli beam theory

This paper presents the design, fabrication, and testing of a novel bistable piezoelectric energy harvester dedicated to vibration energy harvesting in the direction of gravity. Its unique feature is that the bistability is realized by combining the elastic potential energy of a bridge-type compliant mechanism and the gravitational potential energy of a proof mass together, which simplifies the preloading

By facilitating the generation of samples from arbitrary probability distributions, Markov Chain Monte Carlo (MCMC) is, arguably, the tool for the evaluation of Bayesian inference problems that yield non-standard posterior distributions. In recent years, however, it has become apparent that Sequential Monte Carlo (SMC) samplers have the potential to outperform MCMC in several ways. SMC samplers are

This paper performs the detailed simulation analyses of airfoil-based piezoaeroelastic energy harvester with two degrees of freedom self-induced plunge-pitch motions, for exploring the flow field characteristic and enhancing the harvesting performance. The designing of the harvester for achieving flutter is first accomplished, finite element model is then built and simulation analyses are performed

Considering the vibration of a Tuned Mass Damper (TMD), a dynamic model composed of the cable and TMD is investigated. Different from the other studies, this paper is mainly devoted to nonlinear behaviours of the model by considering the participation of the damper in energy transfer and coupling interaction between the cable and damper. According to the extended Hamilton’s principle, the classical

The entropy-based method has been demonstrated to be an effective approach to extract the fault features by estimating the complexity of signals, but how to remove the strong background noises in analyzing early weak impulsive signal remains unexplored. To solve this problem, this paper proposes symbolic fuzzy entropy (SFE) based on symbolic dynamic filtering and fuzzy entropy to eliminate the noises

A general tactic for machine performance degradation assessment (PDA) is to develop a health indicator (HI) to identify different degradation stages. A suitable HI is not only capable of distinguishing different machine degradation stages but also has an inherent characteristic of monotonicity because of irreversible machine degradation. Since informative frequency bands, such as resonance frequency

The prediction of tunnel geological conditions plays an important role in underground engineering, such as the tunnel construction and tunnel dynamic design. However, due to the invisibility of underground geological conditions, there remain many challenges in the design of geological prediction models. In this paper, we propose a generative adversarial network for geological prediction (GAN-GP) to

Model updating techniques have achieved extensive applications in numerical models with uncertainties inherently in practical systems, whereas the stochastic theory is ineffective under insufficient knowledge. Additionally, model updating in the face of correlated uncertainties and complex numerical models remains challenging. In the present study, a novel interval model updating framework was proposed

Uncertainty quantification metrics have a critical position in inverse problems for dynamic systems as they quantify the discrepancy between numerically predicted samples and collected observations. Such metric plays its role by rewarding the samples for which the norm of this discrepancy is small and penalizing the samples otherwise. In this paper, we propose a novel entropy-based metric by utilizing

It has always been an issue of significance to diagnose compound faults of machines. Existing intelligent diagnosis methods have to be trained by sufficient data of each compound fault. However, both labeled and unlabeled data of mechanical compound faults are usually difficult to collect or even completely inaccessible for training in real scenarios. Therefore, compound faults are usually unseen fault

This paper proposes a new algorithm for the online monitoring of slow varying modal parameters in vibrating structures subjected to unknown excitations. In this method, an Auto-Regressive (AR) model will be applied in a Short-Time Sliding Window (STSW) on measured signals. The model parameters will be determined and updated through the order and time obtained from the previous computational window

We propose a novel algorithm for dynamic response suppression via semi-active control devices, which we refer to as broad learning, robust, semi-active control (BLRSAC). To configure the semi-active controller, a nonparametric reliability-based output feedback control strategy is introduced. In particular, an adaptive broad learning network is developed to formulate the control strategy using the clipped-optimal