Data-driven fault detection (FD) or diagnosis methods are key technologies to ensure safe operation of rotating machinery. These methods rely on a requisite volume of fault data. However, acquiring fault data from rotating machinery is typically problematic and can be entirely unattainable. The critical challenge is to accurately detect and localize the fault states of rotating machinery under the

Blade is the core working components of an aero-engine, and its blade tip clearance (BTC) exerts a direct influence on the efficiency and safety of the engine. Aiming to extract the BTC region from the echo signal, a novel microwave-based dynamic measurement system through nonlinear I/Q imbalance correction is proposed. Firstly, to achieve accurately correction of the sensor under non-linear amplitude

Due to extensive detection range and high sensitivity to defects, ultrasonic Lamb waves are extensively studied in the fields of Nondestructive Testing and Structural Health Monitoring. In scenarios where the material parameters or geometric parameters of the waveguide are unknown, the dispersion relation of the guided wave cannot be calculated by the forward model. Consequently, it becomes imperative

Displacement plays a pivotal role in bridge assessment, but accurate displacement monitoring remains a challenging task. Unmanned Aerial Vehicles (UAVs) provide a cost-effective, time-efficient, and high maneuverability alternative to infrastructure monitoring, as they overcome the spatial limitations of the fixed camera and acquire the high-resolution image sequence. However, the measurement accuracy

Hazardous failures of engineering structures can be prevented by implementing passive vibration absorbers. Although tuned mass dampers (TMD) are used most frequently in practice, nonlinear energy sinks (NES) offer a broader frequency performance due to their targeted energy transfer (TET) mechanisms. However, this behavior occurs only in a limited amplitude range. In this work, the vibration suppression

Time-frequency (TF) rearrangement methods represented by synchrosqueezing transform (SST) and synchroextracting transform (SET) have recently been considered efficient tools for obtaining time-varying features of nonstationary signals. However, so far improving concentration and accuracy is still an open problem, especially for the signal with strongly time-varying instantaneous frequency (IF), due

Looseness detection of complex multi-bolted flange joints has long been an important problem to be focused on, especially for the scene of unknown multi-bolt loosening at the same time. In this study, a stable, efficient and robust guided wave recognition method for multi-bolt loosening is proposed for the first time by taking long-term monitoring data. This method studies the nonlinear characteristics

This article proposes a practical and effective damage identification approach for plate-like structures. This approach measures the back scattering caused by damage, and decomposes it into individual contributions from each defect, using the responses of the healthy structure as a dictionary. A data-driven model is used, which circumvents the challenge of numerically simulating the effect of damage

As urbanization progresses, metropolitan transit vehicles are encountering a growing frequency of curved pathways, which presents challenges pertaining to both the safety of the vehicles and the comfort of the passengers. There is no doubt that reliable acquisition of wheel-rail force is critical, since it has great significance for the safety and stability of vehicle operation. However, conventional

Cylindrical roller bearings are inevitably impacted by external moments or mounting error, which leads to uneven load distribution on the rollers and triggers deformation. Current methods are insufficient to simulate the deformation while ensuring solution accuracy. To address this, a new slicing approach is innovatively proposed in the paper, where springs are added between the neighboring slices

Accurately diagnosing bearing faults is crucial for maintaining the efficient operation of rotating machinery. However, traditional diagnosis methods face challenges due to the diversification of application environments, including cross-condition adaptability, small-sample learning difficulties, and cross-dataset generalization. These challenges have hindered the effectiveness and limited the application

A novel approach to metamaterial design is introduced through the development of a stable 3D woodpile structure composed of slender cylindrical beams. These beam elements possess diverse bending vibration modes, intricately coupled with propagating waves, leading to complex wave dynamics within the structure. For the efficient analysis of various architectures, an extended discrete element model (DEM)

A new concept of vibration synergized energy harvesting is proposed for ultra-low frequency scenarios. A dual-oscillator synergized piezoelectric energy harvester (DOS-PEH), inspired by hummingbirds, is designed to demonstrate the new concept, both theoretically and experimentally. Mimicking the synergy mechanism of hummingbird muscles and wings, the DOS-PEH adopts a supporting oscillator (SO) and

In consideration of significant uncertainties arising from the degradation of in-service train-slab track-bridge coupled systems and the limitation in accurately reproducing track irregularities using prescribed track spectra, this study presents a novel framework to establish a digital twin for dynamics of an in-service train-slab track-bridge coupled system to best simulate and predict its dynamic

Reliable tool wear prediction is of great importance for the improvement of machining quality and efficiency. With the advent of the big data era, data-driven tool wear prediction methods have proven to be highly effective. However, these methods have also revealed issues such as shallow feature extraction and limited generalization of models across different machining processes. The objective of this

As the actuator of the turbine speed control system, the performance and response characteristics of the speed control valve actuator directly affect the operational economy, maneuverability, and reliability of the turbine unit. When faults occur in scenarios where data scarcity is coupled with high noise levels, existing deep neural network models are limited by their inability to extract key discriminative

The broadband vibration reduction performance of nonlinear energy sink (NES) has attracted wide attention. However, the impact of the NES’s additional mass other than the oscillator and how it is connected to the primary structure has been ignored. More recently, it has been discovered that vibration attenuation through the cellular application of NES can achieve greater efficiency. However, the connection

As a main task of inverse problem, model updating has received more and more attention in the area of inspection, sensing, and monitoring technologies during the recent decades, where the estimation of posterior probability density function (PDF) of unknown model parameters is still challenging for expensive-to-evaluate models of interest. In this paper, a novel variational Bayesian inference method

To address the recurring vibration in the integrated unit-plant structure system during the transitional phases of pumped storage power station (PSPS), the magnetorheological damper (MRD) is introduced in this paper to investigate transient vibration control within the coupled unit-plant structure (CUPS). Firstly, taking an actual PSPS as a case study, a unit regulation system model is developed based

Bolt joints are commonly used in aviation structures. Bolt looseness may pose serious safety risks and its online monitoring is of great importance to structure and air safety. Active guided wave detection methods can accurately identify the tightness status of bolts. However, the excitation of active guided waves requires big and heavy equipment, such as waveform generators and power amplifiers, which

Regenerative chatter is an unstable and detrimental vibration phenomenon stemming from the regenerative excitation of time-delay dynamic systems. Currently, research on regenerative chatter predominantly focuses on machining process, wherein chatter occurs when the process frequency aligns closely with the natural frequency of the tool-holder system. However, in plastic forming process conducted by

Monitoring and nowcasting of mooring line are of paramount significance for maintaining the stability of floating structure. Recently, data-driven approaches for mooring monitoring have been proposed to identify potential mooring damage, aiming to achieve digital real-time integrity management. This paper proposes a framework for detection and nowcasting of health status of mooring line. The framework

Rotating and Length-Varying Flexible Manipulators (RLVFMs) benefit from the ability to transform their length to adapt to complex and demanding workspaces but suffer from increased complexity in nonlinear dynamical characteristics and thus difficulties in modeling. To provide an in-depth understanding of the RLVFMs, this paper proposes a novel dynamical modeling approach for the RLVFMs, called the

Due to their unpredictable nature, many impact events (e.g., overheight vehicles striking on bridges) go unnoticed or get reported many hours later. However, they can induce structural failures or hidden damage that accelerates the structure’s long-term degradation. Therefore, prompt impact detection and localization strategies are essential for early warning of impact events and rapid maintenance

Flexible rotor systems with spline joints often encounter critical resonances and sudden self-excited vibrations. This paper introduces an innovative state-switching scheme utilizing auxiliary support with a pre-loaded snubber ring to suppress these undesirable vibrations. A prototype of an auxiliary support was designed, and a coupled rotor dynamics model incorporating a nonlinear auxiliary support

To improve the mode decomposition capacity of the empirical Fourier transform for time-varying structures, an empirical multi-synchroextracting decomposition method has been proposed and applied to mode analysis of time-varying structures. The multi-synchroextracting transform is introduced to obtain the time–frequency coefficients and the time–frequency spectra of response signals. Then, the time–frequency

Autoencoder reconstruction-based unsupervised damage detection is widely utilized in structural health monitoring. However, such methods typically necessitate a comprehensive collection of historical guided waves as training data. Acquiring such data presents challenges, as it requires prolonged monitoring to cover various environmental and operational conditions (EOCs), making these methods less practical

Harvesting mechanical energy from traffic environments is an effective way to power low-power wireless sensors. In this paper, a compact mechanical energy harvester (MEH) is designed for common traffic scenarios, converting reciprocating vertical vibrations into unidirectional rotational motion of a generator through the use of two one-way clutches integrated within bevel gears. A nonlinear coupling

The dynamic parameters of high-speed train axle box bearing have time-varying characteristics, it is necessary to investigate the influence of time-varying characteristics on the dynamic response of the bearing. In this paper, based on the time-varying characteristics of the internal and external dynamic parameters of the bearing, a two-degree-of-freedom dynamic model of axle box bearing is established

Ultrasonic assisted high-speed machining (UAHSM) can be served as a thermomechanical surface sever plastic deformation (SSPD), because of the high-frequency impact load exerting to the sample together with thermomechanical loads due to shearing and plowing. Despite existing of few works which studied the impact of ultrasonic vibration on fatigue life assessment of difficult-to-cut material by experimental

Due to the tower cranes usually working in an outdoor environment, it is generally unavoidable for the obstacle to exist in the transportation path. Thus, it is critical for the tower crane systems to guarantee their safety and efficiency simultaneously. In this paper, for the 4DOF tower cranes, a novel adaptive tracking control approach is proposed by considering obstacle-avoidance trajectory planning

This paper presents the continuous monitoring of an eight-story cross-laminated timber (CLT) building. The monitoring process includes daily acceleration measurements at the rooftop, along with external temperature, humidity, and wind velocity data. Additionally, moisture content (MC) of timber at various locations in the internal and perimeter walls is measured. The extraction of modal parameters

This study established a corrected system for a dielectric barrier discharge plasma actuator (DBD-PA) model and applied the corrected plasma model in research on the control of vehicle buffeting noise. Firstly, experiments on static ion wind characteristics under different excitation voltages were conducted, and the spatial distribution of the body force vector field during actuator operation was estimated

This paper explores the semi-active omnidirectional liquid column vibration absorber, a unique tuned liquid column damper consisting of multiple circularly distributed columns for the control of vibrations in all lateral directions. Each column features actuator-controlled cells that can trap liquid and adjust column cross-sections, facilitating a rapid shift in natural frequency during operation.

This paper introduces a mathematical method for the flexible dual-rotor-disc-bearing coupled system in aeroengines. Through meticulous simulation and experimental observation, the impact of the unbalanced disc on the response characteristic and interference relation of rotor systems is investigated. Beyond the general focus on the dynamic behavior, the discussion delves into uncovering the generation

Spall type classification, a task in which the type of the spall is estimated, is an important stage for bearing diagnosis and prognosis. Many machine learning algorithms have been suggested for spall type classification. However, they are not relevant for diagnosing critical rotating machinery, where very few, if any, faulty examples (labeled and unlabeled) are available due to safety considerations

The gearbox plays a crucial role in the transmission system of mechanical equipment, yet its failure is frequent due to complex operational environments. Existing data-driven methods utilizing deep learning (DL) have yielded satisfactory results in intelligent fault diagnosis (IFD). However, most IFD methods rely on supervised learning, which requires a large number of labeled samples to train the

Stress–strain (SS) curves are essential for understanding material properties, such as yield and ultimate tensile strength. However, traditional destructive tensile testing has constraints in terms of material reusability and the detection of local behavioral changes. This study proposes two novel techniques: (1) nondestructive SS curve estimation using ultrasound and (2) 3D visualization of SS curves

This paper presents a comprehensive characterization of a woven glass fiber composite sample with two notches in the gauge area subjected to cyclic tension using an Arcan fixture. An advanced optical setup was developed, comprising two visible light cameras and an infrared camera. Additionally, an X-ray scanner was employed to examine ex-situ the bulk for microstructural changes during the experiment

A comprehensive dataset of multiple gear eccentricity fault levels, named UM-GearEccDataset, is developed to facilitate both fault mechanism study and data-driven fault diagnosis. Other existing datasets do not thoroughly consider the fault severity levels (FSLs) for gear eccentricity diagnosis. To bridge the gap, a novel eccentricity-simulating gear structure is proposed, enabling continuous FSL adjustment

Thermal errors affect the machining quality to a great extent. The basis for error compensation and thermal structure optimization is thermal error modeling. However, existing analytical models encounter challenges in dealing with complex structures, determining boundary conditions and solving the temperature and deformation fields. In this paper, a thermal error analytical model of full-closed-loop

For machine tools composed of functional components bonded by joints with structural nonlinearities, the load- and temperature-dependent nonlinear restoring force,stiffness, and frictional heat generationfrom the jointdetermine its complex dynamic fully coupled thermal-structural-vibration characteristics. In response, in this work, considering the vibration feedback dominated by the structural vibration

Local wavenumber imaging has been proven effective for damage detection in thin-walled structures. Such structures are, however, often inherently anisotropic, posing serious challenges to the known algorithms of local wavenumber mapping. The use of local wavenumber mapping algorithm designed for isotropic, rather than anisotropic, structures results in processing artifacts that may prohibit correct

In this work, the dynamic behaviors of L-shaped piezoelectric vibration energy harvester that result from the combination internal resonance are numerically, analytically and experimentally presented. The electromechanically coupled governing equations of the energy harvester were employed in accordence with our previous study. The multi-branch approximate responses of the system are derived by using

This paper proposes a novel in-vacuo adaptive beam element for vibration control, which, in this study, is employed as an adaptive tuneable vibration absorber. The element is formed by a composite beam with a core of structured fabrics wrapped in a deflated plastic bag skin. The fabrics consist of 3D-printed chain mails of hollowed truss-like particles. A base post is connected at the middle section

A new method called the subsignals technique for estimating parameters of signals or STEPS is proposed for accurate parameter estimation of sinusoidal signals with noise and harmonics. This method is based on the fact that the parameters of a sinusoidal signal and its subsignals are either the same or related. By taking two different subsignals and using discrete Fourier transform, we were able to

The traditional integer order model cannot well describe the complex mechanical behavior of viscoelastic materials, so the fractional derivative is proposed to model the constitutive relationship of viscoelastic materials. The value of the fractional order of the fractional viscoelastic model is vital to the application. This paper proposes a guided wave technology for determining the fractional order

A high potential barrier is not conducive to triggering the snap-through motion of a bistable oscillator. The magnetically coupled bistable energy harvester with multiple degrees of freedom, which possesses a considerable bandwidth due to its high-order resonances, also faces the same issue. To address this challenge, a novel magnetically coupled bistable energy harvester with a barrier-decreasing

In recent years, energy harvesting technology has provided a promising solution for powering low-power sensors. Rotational motions are ubiquitous in nature and human activities, making the design and study of rotational energy harvesters highly significant for the development of the Internet of Things. Previous studies have shown that nonlinear bistability and multiple degrees of freedom (MDOF) can

Accurately obtaining the dynamic load of a structure is crucial for structural design, optimization, and maintenance. However, dynamic methods based on classical mechanics systems often introduce artificial dissipation and other flaws. This paper presents a novel time-domain centralized load identification method to address structural dynamic load problems, leveraging Birkhoffian system dynamics and

This paper develops a geometrically nonlinear mathematical model of a flexible cantilevered beam hosting a guided axially elastic tendon. The model is intended as an enabling tool to explore the guided tendon-based dynamic enhancement methods in application to highly flexible and lightweight structures. To both validate the model and to generate further insights, an experiment-guided study is performed

This study introduces movable-track nonlinear energy sinks (MT-NESs) featuring customizable restoring forces. MT-NESs employ a novel track-spring configuration where the track parts themselves act as the movable mass, significantly reducing device dimensions and weight. The paper commences with the development of MT-NESs. A small-scale MT-NES is then experimentally realized on a two-story structure

In a laser-tracing measurement system, the tracking control performance largely determines the measurement accuracy. However, the continuous forward and reverse movements of the system required for the tracking process, frictional torque, and external disturbances affect the tracking performance. In addition, when a two-dimensional position-sensitive detector extracts the target information, the required

The application of computer vision for estimating structural motion has garnered significant interest in the field of structural modal identification due to its non-contact, full-field, and cost-effective characteristics. Nevertheless, the sensitivity of CMOS visual sensors is markedly inferior to non-contact coherent optical sensors. This level of sensitivity is insufficient for detecting structural

Various local deformations inevitably occur during the construction and operation stages of long-distance oil and gas pipelines, which affect their safe operation. IMU internal detection technology is the main method for detecting local deformations in pipelines. This paper establishes an important database containing 33,177 sample pipe sections based on the IMU internal detection data of six rounds

Complex boundary conditions pose a significant challenge to the construction of digital twin models for structures. To tackle it, virtual damper/force has been proposed to capture structural complexities within a two-step model updating framework, which successfully achieved time domain alignment between the structural responses of the numerical model and physical structure. This paper focuses on investigating

Energy harvesting technology based on smart piezoelectric materials still faces the challenge of expanding bandwidth and increasing frequency bands of harvesters. In response to this challenge, a magnetically excited piezoelectric harvester with nonlinear energy sink is proposed. This work establishes a nonlinear magnetic force model for the magnetic rotor and auxiliary magnets. The electromechanical

Modal identification is the initial step to know the fundamental dynamic characteristics of a target structure, which mainly includes the natural frequency, damping ratio, and mode shape. These modal parameters can be used to assess the discrepancy between the design values and the actual values. Based on these, model updating and damage detection can be carried out in conjunction with the finite element

The intrinsic damping of the superconducting electrodynamic suspension (EDS) system is very small, and even negative damping in some speed ranges. It is necessary to develop electromagnetic damper to improve the suspension stability and running stability of the maglev train. In this paper, the magnetic-electric-mechanical interaction (MEMI) model of superconducting EDS considering superconducting magnets

Consider making Bayesian inference of vector-valued model parameters x,y based on observed data D. When the ‘posterior’ (i.e., given data) probability density function (PDF) of x,y has a centralised shape, it can be approximated in the spirit of Laplace integral asymptotics by a Gaussian PDF centred at the ‘most probable value’ (MPV) that minimises the objective function Lx,y=-lnpD|x,yp(x,y), where