The article presents a multiaxial fatigue criterion in the frequency domain. The criterion uses the power spectral density of the hydrostatic stress, the stress consistent with the von Mises criterion and determines the equivalent power spectral density as the sum of these quantities for further use in fatigue analyses. The methodology for deriving the criterion weights in two cases of determining

Interfacial debonding defects in rectangular steel–concrete composite structures (RSCCS) can significantly diminish the confinement effect of the steel on the concrete core and reduce load transfer efficiency, potentially impacting the overall performance of the structure. Detection of these defects in RSCCS is therefore considered critical. This study investigates the complexities of stress wave propagation

This paper explores the application of tri-stable energy harvesting technology in tire rotation and proposes an innovative approach of optimizing the output of energy harvester by adjusting the centrifugal distance of the magnet at the free end of a cantilever beam. By leveraging the tunable linear stiffness in the electromechanical coupling equations of the rotating tri-stable state, this study derives

This research introduces an innovative method for real-time monitoring thin film growth and surface roughness using a single mode optical fiber without any additional treatment. The cleaved end of the fiber was installed within the deposition chamber, allowing the thin film to be deposited directly onto the fiber tip. During the deposition process, a Fabry-Pérot interferometer was formed with its cavity

The existing reconstruction methods for dam monitoring data have the problems of being unable to reconstruct in the non-complete dataset and the reconstruction accuracy is not high enough. Therefore, this paper proposes the dam monitoring data reconstruction method (DSVD) to realize the accurate reconstruction of dam monitoring data in non-complete datasets. The method first adopts the sorting method

The aerostatic bearing-rotor system plays a critical role in ensuring the stable operation of high-speed, high-precision rotating machinery. Despite its importance, the system is often affected by nonlinear sub-synchronous vibration instabilities, which limit its performance and development. To address this issue, this study proposes a novel tangentially supplied (TS) bearing. Modified gas lubrication

Ultrasonic sensing, for instance for damage or fouling detection, is commonly carried out using rigid transducer collars, carefully placed for monitoring a well-defined local area of a structure. A distributed sensing network consisting of individually placed transducers offers significant opportunities for monitoring larger areas or more complex geometries. For analyzing the signals of such a distributed

Gear wear is an inevitable consequence of friction and load during operation. However, the nonlinear and non-stationary nature of the vibration signals under variable speed conditions and their complex interaction with gear wear make it extremely challenging to extract wear-related features from them. Since the gear wear area visually indicates the severity of wear under varying speed conditions, we

Enhancing anomaly detection performance is essential for effective gas turbine condition monitoring and health maintenance. However, in industrial applications, gas turbine operating conditions frequently change, and fault data are scarce or even unavailable. Therefore, identifying anomalies in unknown conditions with training based only on normal data is challenging. Inspired by human communication

Quasi-zero-stiffness (QZS) mechanism is widely exploited in tailoring vibration isolators for balancing the load capacity and low/ultra-low frequency isolation performance. For these isolators, broadening QZS region, improving manufacturability, and enhancing tunability are relentless design pursuits. We here propose a cutting-edge tensegrity-based quasi-zero-stiffness (TQZS) isolator for torsional

Digital hydraulic systems are composed of parallel fast switching valves (FSVs) and have unique fault tolerance characteristics, while fault identification and localization are the premise of fault tolerance. However, due to the similar fault features, it is difficult to accurately diagnose the faulty valve in an equal-coded digital hydraulic system (EDHS) without its additional sensors. Aiming at

Clamp-on ultrasonic flowmeters suffer from crosstalk—i.e., measurement errors due to the interference of signals generated in solid regions and solid–fluid interfaces with the required signal from the fluid. Although several approaches have been proposed to alleviate crosstalk, they only work in specific ranges of flow rates and pipe diameters, and some also introduce additional issues. We propose

Chatter detection is crucial for both micro- and macro-milling, as chatter can cause detrimental damage on machining process and machined surface. Compared to macro-milling, micro-milling is more susceptible to external non-Gaussian noise interference, making it extremely difficult to extract chatter features and identify chatter modes at the micrometer scale due to the lower chatter component which

It has been observed experimentally that flow-induced ambient noise propagated in an icy thin-plate structure decays quickly. The attenuation rate is sensitive to the ice thickness and is thus potentially an important feature for passive ice detection. The main goal of the present paper is to develop a theoretical model to explain this damping behavior qualitatively and quantitatively. The wave propagation

Aerostatic spindle utilizes gas as the lubricating and supporting medium, enabling it to exhibit outstanding characteristics such as high precision, low temperature rise, and environmental friendliness during operation, thereby fulfilling the requirements of high-speed machining applications. However, during the operation of the aerostatic spindle, the increase in spindle speed induces velocity effects

The quest for low-frequency and broadband underwater sound absorption materials with lightweight and pressure-resistant properties is constantly pursued in engineering applications. However, existing underwater absorbers are restricted by conventional design concepts and struggle to strike a balance among these requirements. Notably, the acoustic performance of these absorbers tends to deteriorate

Bayesian inference has been demonstrated as a rigorous tool for updating models and predicting responses in structural dynamics. Most often, the likelihood function within the Bayesian framework is formulated based on a point-to-point probabilistic description of the discrepancy between the measurements and model predictions. This description results in an underestimation of uncertainties due to the

Thin-sheet components are widely used in many industrial applications. Structural integrity of these components largely depends on the strength of the joints. Ensuring the durability of these joints is essential, and therefore, routine inspection is critical to maintain the safety and performance of these components. However, most traditional Non-Destructive Evaluation (NDE) techniques fall short for

Reliability analysis of dynamic structural systems and its implications for structural design have garnered increasing attention. Sample-based methods prove insensitive to the dimension of the probability integral. Nontheless, a substantial number of realizations is necessary for estimating small failure probabilities, resulting in time-consuming computations. Recently, the Directional Importance Sampling

In the last decade, the class of polynomial chaos (PC) methods for non-Gaussian random field modeling has received considerable attention. However, these methods have been limited to low random dimension problems due to the curse of dimensionality in the Rosenblatt transformation. In this paper, we develop an optimal transport method for the PC representation of non-Gaussian fields. Our method firstly

The nonlinear time-varying vibrations of the axially moving nested composite cantilever wing are investigated by using the theoretical and experimental methods when the axially moving wing deploys and retracts. Subjected to the in-plane force and first- order aerodynamic press, the axially moving nested composite cantilever wing is simplified to an axially moving cantilever composite stepped plate

The monitored seismic response data provides useful insight into the dynamic characteristics of cable-stayed bridges during an earthquake shaking. However, the unavailable earthquake input data, as is the case for most cable-stayed bridges, would prevent the system identification using the during-shaking structural response. This study proposes to employ the post-shaking structural response only for

Laser ultrasound array scanning imaging has extremely high flexibility in space arrangement and scanning parameter adjustment. However, a major challenge is how to achieve high-speed inspection and high-resolution real-time defect imaging using a limited number of scanning configurations. In this study, the detection sensitivity of laser ultrasonic synthetic aperture focusing technique (SAFT) is analyzed

To address the challenges in off-grid frequency estimation, such as computational complexity and sparse frequency recovery, in this paper, we propose a novel data-driven approach for off-grid frequency estimation. Specifically, in terms of computational complexity, the off-grid frequency estimation problem is first formulated by transforming the iterative process of the model-based alternating direction

This article introduces an innovative servo gap control mechanism for the micro-electrical discharge machining (µ-EDM) process. Magnetic levitation serves as the foundation for innovative gap control. Here, the magnetic force (Fem) is made balanced to gravitational force (Fg) and spring restoring force (Fs) to achieve a state of equilibrium. The equilibrium state of these forces provides the essential

This study introduces an innovative approach that employs Physics-Informed Neural Networks (PINNs) to address inverse problems in structural analysis. Specifically, this technique is applied to the 4th order partial differential equation (PDE) of the Euler–Bernoulli formulation to estimate beam displacement and identify structural parameters, including damping and elastic modulus. The methodology incorporates

In order to solve the problem that the stochastic resonance (SR) signal processing method enhances the characteristic signal while enhancing the interference signal, which leads to a lack of desired results, this paper proposed a hybrid resonant sparse (RS) decomposition and tri-stable SR (RSSR) signal method. Firstly, the feasibility and superiority of the RSSR method have been demonstrated by analyzing

Based on the noise-enhanced signal characteristics of stochastic resonance (SR), this paper proposes a nonlinear multi-order coupled SR model, aiming to make full use of nonlinear zero-order vibrational coupling and first-order damping coupling to enhance the detected signal-to-noise ratio (SNR) and increase the detection distance of the underwater passive sonar. First, the influence of nonlinear vibration

Cracks in disc components can significantly reduce their service life. Most existing studies on cracked discs assume predefined crack paths (such as tangential or radial cracks) and rarely analyze the stress of the cracked disc during vibration. Additionally, dynamic models of the disc typically involve a significant number of degrees of freedom, resulting in substantial computational time when calculating

The purpose of degradation modeling in mechanical equipment is to describe the transition from a healthy state to degradation, enabling monitoring and prediction. Commonly used degradation models can effectively capture the overall trend of progression and regression, yet struggle with fluctuations around critical degradation stages, which leads to the failure of early warning thresholds. To address

Deep transfer learning has been shown to be effective when performing intelligent fault diagnosis (IFD) because of its strong feature representation performance when characterizing vibration signals under variable working conditions. However, when target domain data is not available, the ability to train a model effectively could be very challenging since the feature distribution of the target domain

Incorporating the porous characteristics inspired by bio-materials into the phononic crystal (PnC) structure may lead to a more extensive range of properties or new functional spaces. On the contrary, the mechanical deficiencies in PnCs, apart from the band gap (BG) characteristics, pose challenges for engineering applications. Therefore, a floating projection topology optimization (FPTO) framework

Aerostatic thrust bearings are extensively utilized in ultra-precision machining. Enhancing bearing load capacity, stiffness, and reducing vibration is a continuing demand. This paper introduces a novel active recess compensation aerostatic thrust bearing (ARCATB) with hermetic squeeze film damper (HSFD), aiming to achieving active compensation of bearing load capacity and stiffness while maintaining

The study of rolling mill vibration theory has always been a scientific frontier in the field of rolling forming, which is very important to the quality of sheet metal and the stable operation of equipment. A magnetorheological fluid damper absorber is designed to control the nonlinear vertical vibration of rolling mill. Considering the fractional order and delay factors in the control effect of magnetorheological

Remaining useful life (RUL) prediction has great significance in reducing operating costs and enhancing the maintainability and safety of rolling bearings. Recently, significant progress has been achieved in this field by leveraging deep learning approaches. However, advanced deep learning methods suffer from a black-box nature that makes them lack interpretability. Moreover, the prediction results

Vibration-based piezoelectric energy harvesting technology, characterized by its straightforward structure, has potential applications in powering microelectronic devices. To address the demand for low-frequency energy harvesting performance, a double pendulum piezoelectric energy harvester with stoppers-assisted bending vibration was designed inspired by the bird wing. Its originality is to employ

Deep learning has been widely used for intelligent fault diagnosis of rotating machinery. However, owing to the limitations of training sample data and the complex industrial environments with variable operating conditions and noise interference, the existing deep learning-based fault diagnosis methods have difficulty achieving satisfactory performance. To address these issues, this paper proposes

To achieve high-quality in-situ machining of large thin-walled workpieces, the dual-robot mirror milling technology has attracted much attention due to its ability to synchronously provide mirror support on the opposite side of the milling area of the tool. However, mirror support has a complex and unclear dynamics mechanism for improving the dynamic characteristics of workpieces, and strongly affects

Truss structures provide support and connection as essential components of spacecrafts. However, they are constantly disturbed and vibrated, which affects the pointing accuracy and operating stability. An active vibration isolation method for truss structures with embedded piezoelectric actuators (EPAs) is proposed in this study to address the challenges of excessive weight, large size, and limited

The smooth interaction between the pantograph and the catenary is crucial for the operational safety of railway vehicles. Coupled dynamic models of the pantograph–catenary system (PCS) constructed based on physical principles are important tools for analyzing their interactions; however, these models rely on accurate system parameters (such as stiffness, damping, and mass). Under actual operating conditions

Designing health indicators (HIs) for aerospace composite structures that demonstrate their health comprehensively, including all types of damage that can be adaptively updated, is challenging, especially under complex conditions like impact and compression-fatigue loadings. This paper introduces a new AI-based approach to designing reliable HIs (fulfilling requirements—monotonicity, prognosability

The acoustic vibration characteristics play a crucial role in determining the performance of aero double-helical planetary gear transmission systems. Considering the coupling effect among temperature, fluid, and structure in double-helical planetary gear transmission systems, an improved mesh stiffness model is constructed in this paper, which also considers the fractal tooth, tooth friction, thermal

The ballast bed constitutes the cornerstone of the ballasted track. A fouled ballast bed poses a significant threat to its performance, potentially resulting in severe consequences. In recent years, studies have shown that infrared thermography (IRT) technology has emerged as a promising method for detecting the fouled ballast bed. The surface temperatures of clean and fouled ballast beds differ because

Offshore wind turbine structures experience combined wind and wave loading during their lifetime, and the cyclic characteristics of these loads significantly impact the fatigue life of the support structure. Continuous monitoring of stress-related quantities, such as strain time histories at hotspot locations of the structure, can help to estimate the fatigue life. However, sparse measurements from

Internal resonance isa unique phenomenon in nonlinear structures. It can lead to pronounced energy transfer between vibrating modes, causing unexpected stress concentrations in local areas and posing a risk to structural integrity. This paper presents a general model updating procedure for nonlinear structures with such internal resonances using experimentally measured data. The test involves using

Combined with virtual sensing techniques, active noise control can generate quiet zones in places without error microphones. Many existing virtual sensing techniques require pretraining of the system with physical microphones placed temporarily at the control location as well as retraining if the primary sound field or the secondary paths change. This process responds slowly and is infeasible in many

Mechanical vibrations in low-frequency resonance and harmonic modes severely affect the closed-loop performance of inertially stabilized platforms (ISPs). This article proposes a new vibration control scheme capable of suppressing low-frequency vibration with large amplitude and harmonic disturbances in application to an ISP. Concretely, we first design an optimized repetitive control (ORC) framework

High-speed imaging is essential for high-frequency vibration measurement techniques that utilize images, such as digital image correlation (DIC). However, it poses challenges, including reduced displacement resolution due to decreased image resolution, increased measurement and calculation costs, and greater data volume. A previous method used compressed sensing to reconstruct time information from

Over the past decade, the growing importance of machine learning-based structural health monitoring (SHM) for early-stage damage detection has become evident. Time series forecasting, using deep learning, has emerged as a key focus, significantly contributing to improving damage detection, localization, and quantification processes. Researchers in SHM have conducted numerous studies utilizing neural

Structural health monitoring (SHM) is essential for managing infrastructure by continuously monitoring performance. To address the complexity of SHM for large systems, this study introduces a dynamic graph neural network (DynGNN) approach for near-real-time damage identification. The approach represents the infrastructure as a graph and uses a dynamic adjacency matrix based on proper orthogonal decomposition

This paper proposes a hierarchical Bayesian model updating approach to quantify variability of aerodynamic stiffness and damping of an offshore wind turbine (OWT) under different environmental and operational conditions (EOCs) using in-situ vibration data and SCADA (supervisory control and data acquisition) over two months of continuous monitoring. The considered OWT is a Haliade 150, 6 MW GE turbine

This paper presents a novel baseline-free online method for fatigue crack detection and growth modelling of aluminium plates based on the relative second harmonic parameter β′ˆ, which is defined as the ratio of the amplitude of the fundamental frequency A1 over the square of the second harmonic frequency A2, obtained from the response under cyclic fatigue loading. Results reveal that β′ˆ is an effective

This research contributes to the field of reliability engineering and system safety by introducing aninnovative diagnostic method to enhance the reliability and safety of complex technological systems. Steam turbines are specifically referred to. This study focuses on the integration of advanced signal processing techniques and engineering dynamics in addressing critical issues in the monitoring and

Tracking vibration displacement across multiple points on large-scale bridges in the field poses significant challenges due to perspective distortion by camera tilting, interference from adverse environmental factors and low-resolution images by long distance measurement. To address these issues, this study proposed a novel vision-based displacement measurement framework that combined the Fast Spatio-Temporal

The identification of bushings dynamics is crucial for the development of innovative model-based digital tools, such as for example predictive maintenance or virtual sensing. Quite a few nonlinear modelling techniques have been proposed over the years, which can be suitably used to develop advanced models that capture the linear and nonlinear dynamics of a vast range of mechanical components and materials

This paper proposes a framework for mixed uncertainty quantification in the remaining service life assessment of existing deteriorated reinforced concrete (RC) bridges under temperature climate changes. The probability bound analysis (PBA) is deployed for quantifying mixed uncertainty. The epistemic uncertainty in climate change is modelled using a distribution-free p-box in the PBA framework. An extension

Thermal barrier coatings (TBCs) are crucial for protecting high-temperature components in gas turbines and aeroengines. However, conventional non-destructive testing (NDT) methods, such as infrared thermography, face challenges in precisely detecting and quantifying debonding defects due to limitations in imaging contrast and sensitivity to surface states. In this work, a novel scheme for imaging debonding

When the rubber O-ring follows the primary seal in the axial direction as a secondary seal, there is hysteresis behavior between the restoring force and displacement. However, the dynamic parameters of O-rings are mostly expressed as constants in dynamic analysis at present, which cannot accurately describe the dynamic behavior of sealing systems. In response to the problem of poor track performance

Remaining useful life (RUL) prediction is crucial to supporting intelligent maintenance and health management of safety–critical products. Although advanced data-driven approaches such as deep neural networks are effective in processing high-dimensional non-linear health features, their application to field RUL prediction confronts with two challenges: (a) adaptivity of the lifetime parameter learning

Nonlinear hysteretic isolators are widely applied in the field of vibration isolation due to their excellent energy dissipation capacity. However, the dynamic response prediction of nonlinear hysteretic isolators highly depends on accurate modeling methods for nonlinear hysteresis under varying conditions. This paper proposes a dynamic response prediction model based on quasi-static characteristics