The objective of the present work is to evaluate the performance of a data-driven approach to simulate a multiphysics vibroacoustic field. Of particular interest is the complex propagation of anechoic waves in a finite 1D-structure submerged in water. Experimental data from an underwater beam actuated by two macro-fiber composites (MFCs) serves as the experimental framework for the data-driven model

Multistability is the phenomenon of multiple coexistent stable states, which are highly sensitive to perturbations, initial conditions, system parameters, etc. Multistability has been widely found in various scientific areas including biology, physics, chemistry, climatology, sociology, and ecology. In a number of systems where multistability naturally exists, it is found to be undesirable because

This note focuses on stability issues of linear time-invariant second-order systems with delayed control input. We provide a computational method to determine the set of purely imaginary characteristic roots which reveals the critical values of frequency and time-delay where the stability switching of the controlled system may takes place. This method requires computing only the solutions of an eigenvalue

The dynamic responses of assembled structures are greatly affected by the mechanical joints, which are often the cause of nonlinear behavior. To better understand and, in the future, tailor the nonlinearities, accurate methods are needed to characterize the dynamic properties of jointed structures. In this paper, the nonlinear characteristics of a jointed beam is studied with the help of multiple identification

Jointed structures are ubiquitous constituents of engineering systems; however, their dynamic properties (e.g., natural frequencies and damping ratios) are challenging to identify correctly due to the complex, nonlinear nature of interfaces. This research seeks to extend the efficacy of traditional experimental methods for linear system identification (such as impact testing, shaker ringdown testing

In order to characterize cutting mechanics during high-speed milling and micromilling applications, high-end piezoelectric dynamometers with a wide frequency bandwidth are necessary. Nevertheless, when installed into the machine tool their signal bandwidth is limited by the dynamic behaviour of the machining system. Thus, special filters have to be adopted for dynamics compensation. State of the art

In the present work, we deal with a dynamical analysis and passive control of chaos with magnetic rheological (MR) rotational damper in a pendulum driven by a DC motor via slider mechanism. A mathematical model for electromechanical system composed of a pendulum driven horizontally by through a DC motor and a slider-crank mechanism is presented and the parameters are estimated based on experimental

FWRVs (Four-way reversing valves) are widely used to switch operating conditions in air conditioner systems. Most previous research focused on the efficiency of the FWRVs in heat pump systems. However, the vibrations during the valve reversing processes are not yet well investigated. The friction-induced vibration (FIV) is generated when the slider slides on the valve seat under the high pressure in

This paper develops a methodology to compute variance-based sensitivity indices for dynamic systems with time series inputs and outputs, while accounting for both aleatory and epistemic uncertainty sources, and both random process and random variable inputs. We present semi-analytical methods for computing sensitivity indices for linear systems with Gaussian random process inputs, and for the general

For human-robot collaboration (HRC), one of the most practical methods to ensure human safety with a vision-based system is establishing a minimum safe distance. This study proposes a novel integrated mixed reality (MR) system for safety-aware HRC using deep learning and digital twin generation. The proposed approach can accurately measure the minimum safe distance in real-time and provide MR-based

Digital Twin (DT) technology, as one of the top ten strategic technology trends for 2020, has received widespread attentions and gradually being used in manufacturing system. However, for the implementation strategy of these applications, most of the current researches are focused on the digital aspect (data processing, algorithm application research, etc.), few researches have been done on the physical

The manipulation of deformable linear objects is a hot spot and difficult problem in robotics research. Cables, as one kind of deformable linear objects, are characterized by elongation and uncertain shape. Although previous research has paid attention to deformable linear object’s manipulation, it still remains a challenge to detect and grasp cables in unstructured environments. In this paper, a new

In this study, self-powered fault diagnosis of rolling bearing (SP-FDRB) is conducted based on the triboelectric effect. Flexible interdigital electrodes are glued to the outer ring of a rolling bearing to form a rolling-type free standing mode triboelectric nanogenerator (RF-TENG). The RF-TENG has adequate service life because it is designed to avoid direct contact between the flexible electrode and

The automotive industry is facing a rapid technological evolution and the request of a very high level of customization of the products. This requires production systems able to manage a high variety of products with low volumes. To this aim, this paper focuses on multi-product assembly lines consisting of a set of stations with a robot operating the transportation and handling of the parts. Due to

Robot manipulators with 6 degree-of-freedom (DOF) have advantages of good flexibility and large working space. However, the relatively low stiffness deteriorates the machining accuracy and stability in robotic milling tasks, which restricts the widely application of robotic milling in industry. To increase the machining accuracy, taking advantage of a redundant degree of freedom of the robot, this

One of the main issues about safety in human-robot interaction is the distance calculation between robot and human. The acquisition of real-time distance information between robot and human allows the robot to modify its motion to ensure safety. This paper presents a real-time distance calculation framework that enables safe human-robot interaction. The human is tracked by an RGB-D sensor, and the

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On the heels of the successful launch of the inaugural edition of Focused Section on TMECH/AIM Emerging Topics, which was published in the August issue of TMECH in 2020, the second edition has experienced a difficult start due to worldwide pandemic outbreak. However, for this edition, a total of 86 submissions were received by January 8, 2021, on a broad range of mechatronics topics as mentioned before

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Brain-inspired neural network architecture overcomes unsolved classical control theory problem for telerobotics.

Integrating tactile and kinesthetic feedback in a bionic arm results in performance closer to able-bodied individuals.

Motor systems neuroscience seeks to understand how the brain controls movement. To minimize confounding variables, large-animal studies typically constrain body movement from areas not under observation, ensuring consistent, repeatable behaviors. Such studies have fueled decades of research, but they may be artificially limiting the richness of neural data observed, preventing generalization to more

The presence of computation and transmission-variable time delays within a robotic control loop is a major cause of instability, hindering safe human-robot interaction (HRI) under these circumstances. Classical control theory has been adapted to counteract the presence of such variable delays; however, the solutions provided to date cannot cope with HRI robotics inherent features. The highly nonlinear

In most everyday life situations, the brain needs to engage not only in making decisions but also in anticipating and predicting the behavior of others. In such contexts, gaze can be highly informative about others’ intentions, goals, and upcoming decisions. Here, we investigated whether a humanoid robot’s gaze (mutual or averted) influences the way people strategically reason in a social decision-making

Bionic prostheses have restorative potential. However, the complex interplay between intuitive motor control, proprioception, and touch that represents the hallmark of human upper limb function has not been revealed. Here, we show that the neurorobotic fusion of touch, grip kinesthesia, and intuitive motor control promotes levels of behavioral performance that are stratified toward able-bodied function

The application of anthropomorphic design features is widely assumed to facilitate human-robot interaction (HRI). However, a considerable number of study results point in the opposite direction. There is currently no comprehensive common ground on the circumstances under which anthropomorphism promotes interaction with robots. Our meta-analysis aims to close this gap. A total of 4856 abstracts were

Input estimation is an involved task with wide applications in nonlinear dynamic systems. Model-based input estimation methods are not feasible solutions for problems in which the underlying behavior is not sufficiently known. Data-driven methods have recently shown promise in capturing hidden and subtle nonlinearities in problems from various domains. In this study, we introduce a machine learning

General path models and stochastic process models are two widely applied categories of probabilistic degradation models. The former explains the randomness of degradation data as normal distributed errors with zero mean. The latter describes degradation with stochastic processes such as Wiener process, Gamma process and Inverse Gaussian process. For general path models, a limitation is the assumption

Most of the current approaches and studies in stochastic FE model updating are based on experimental modal data considering updating of uncertain parameters related to stiffness and mass matrices. In many instances, it is desired that the stochastic FE model is able to predict the variability of dynamic response. This calls for identifying the variability of damping matrix also along with variabilities

The diagnosis and monitoring of surface wear are very critical for the prevention of shutdown and even catastrophic destruction of a geared transmission system. However, the detection for the evolutionary status of surface wear in a planetary gear train is quite challengeable due to the complicated and weak characteristics buried in the vibration signals. To assess the wear status of gears in a planetary

The contributions of air-borne tyre noise to the overall interior noise sources of a vehicle were investigated using an acoustic beamforming technique based on the conditioned spectral analysis (CSA). This was realised using a set of accelerometers located at the various sources to measure the reference signals of these sources and, these reference signals were then applied successively in the CSA

The non-contact sensing techniques using image/video processing have flourished in recent years benefited from the rapid development of digital cameras. However, high-fidelity motion extraction from acquired image frames is still challenging. A novel motion estimation method based on phase-domain image processing, named Hilbert phase-based motion estimation, is proposed in this study to identify motions

The galloping energy harvesting technique has been extensively applied to harvest fluid energy and utilize the aeroelastic instability of mechanical systems in a flow field for low-powered electronic devices. However, the flow field is random in the real world. In previous studies, fluid motion was regarded as a deterministic process (i.e., with a constant wind speed). However, to determine the actual

This paper proposes a novel liner stick–slip actuator with compact structure which can achieve forward and backward motion. A novel rhombus-type displacement amplification mechanism (RTDAM) with symmetric structure is used to generate lateral motion to improve the actuator performance. Theoretical analysis and finite element analysis (FEA) are carried out to calculate the coupling ratio and natural