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

Due to the structural resemblance of redundant dual-arm robots to human arms, they are widely employed to replace humans in open operational environments. Addressing safety concerns related to the autonomous operations of redundant dual-arm robots in open environments, this paper proposes a real-time collision avoidance method. Firstly, an avoidance direction adjustment algorithm is designed based

Tool wear monitoring (TWM) is essential for enhancing the machining accuracy of intelligent manufacturing systems and ensuring the consistency and reliability of products. The complex and dynamic processing environment demands higher real-time monitoring and generalization ability of TWM. Traditional data-driven models lack guided training in physical processes and are limited by the amount of samples

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

Adrian Tchaikovsky's new novel Service Model humorously imagines a robot Jeeves coping with the end of civilization.

Holistic consideration of the human and the robot is necessary to overcome hurdles in human-robot interaction.

To achieve human-level dexterity, robots must infer spatial awareness from multimodal sensing to reason over contact interactions. During in-hand manipulation of novel objects, such spatial awareness involves estimating the object’s pose and shape. The status quo for in-hand perception primarily uses vision and is restricted to tracking a priori known objects. Moreover, visual occlusion of objects

We present the self-organizing nervous system (SoNS), a robot swarm architecture based on self-organized hierarchy. The SoNS approach enables robots to autonomously establish, maintain, and reconfigure dynamic multilevel system architectures. For example, a robot swarm consisting of n independent robots could transform into a single n –robot SoNS and then into several independent smaller SoNSs, where

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)

Abrasive slurry and water jets can be used together with erosion-resistant masks to rapidly machine micro-pockets. However, the use of masks can result in an undesirable erosion and mask under-etching which can locally increase the depth twofold or more in the vicinity of the mask edges. Although the detailed mechanisms leading to the undesirable erosion are not well understood, they appear to be related

Mixed reality remote collaboration assembly is a type of computer-supported collaborative assembly work that uses mixed reality technology to enable spatial information and collaboration status sharing among geographically distributed collaborators, including remote experts and local users. However, due to the abundance of mixed virtual and real-world information in the MR space and the limitations

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