arXiv research

The paper analyzes the stability of an observer error in a vibrating string system.

This research optimizes plate structures to reduce vibrations in vehicles and aircraft.

A novel ensemble classifier improves vibration-based quality monitoring accuracy.

The wave equation $u_{tt} = c^2 u_{xx}$ is generally regarded as a linear approximation to the equation describing the amplitude of a transversely vibrating elastic string in the plane. But, as is shown in \cite{BC96}, the assumption of transverse vibration in fact implies that the wave equation describes the vibration…

Transformer model predicts train axle vibrations for safer maintenance.

This paper reviews traditional and modern methods for detecting structural damage using vibrations.

Paper predicts bearing degradation stages for pharmaceutical industry maintenance.

Sample size determination for a data set is an important statistical process for analyzing the data to an optimum level of accuracy and using minimum computational work. The applications of this process are credible in every domain which deals with large data sets and high computational work. This study uses Bayesian a…

This work models variability in composite blades' vibrations.

Safe RL-based vibration control using LQR guidance.

Study monitors wind turbine drivetrain bearings using dictionary learning from vibration data.

The paper proposes an ensemble of convolution-based methods for fault detection in gearboxes.

The paper identifies clusters in the World Trade Network using communicability distances.

Study uses Android smartphones to measure road roughness, finds ML better than RMS.

Study examines how body segments respond to random vibrations.

Develops a new geometric framework for field theories with dissipation.

Improves Marsden-Weinstein reduction theory for k-polysymplectic manifolds.

This is a survey of several approaches to the framework for working with infinitesimals and infinite numbers, originally developed by Abraham Robinson in the 1960s, and their constructive engagement with the Cantor-Dedekind postulate and the Intended Interpretation hypothesis. We highlight some applications including (…

We try to present an estimate relating the first Dirichlet and Neumann eigenvalues of a compact bordered Riemannian surface.

New metric tensor field on symmetric matrices simplifies eigenvector computation.

Affirm Lord Rayleigh's conjecture on curved spaces for clamped plates.

GMMSEQ clusters AE data streams, identifying cluster onsets and growth.

This paper studies an intelligent ultimate technique for health-monitoring and prognostic of common rotary machine components, particularly bearings. During a run-to-failure experiment, rich unsupervised features from vibration sensory data are extracted by a trained sparse auto-encoder. Then, the correlation of the ex…

In this paper, we propose a classification based glottal closure instants (GCI) detection from pathological acoustic speech signal, which finds many applications in vocal disorder analysis. Till date, GCI for pathological disorder is extracted from laryngeal (glottal source) signal recorded from Electroglottograph, a d…

Innovative ball bearing converts rotary to reciprocating motion.

MACE architecture outperforms alternatives in various molecular and materials science tasks.

New method predicts VIV in 3D currents for marine risers.

Random forest identifies key features for diagnosing machine faults.

In industrial applications, nearly half the failures of motors are caused by the degradation of rolling element bearings (REBs). Therefore, accurately estimating the remaining useful life (RUL) for REBs are of crucial importance to ensure the reliability and safety of mechanical systems. To tackle this challenge, model…

In this paper, we take the first steps towards a novel unified framework for the analysis of perturbations in both the Time and Frequency domains. The identification of type and source of such perturbations is fundamental for monitoring reactor cores and guarantee safety while running at nominal conditions. A 3D Convol…

We study the distributions of event-time returns and clock-time returns at different microscopic timescales using ultra-high-frequency data extracted from the limit-order books of 23 stocks traded in the Chinese stock market in 2003. We find that the returns at the one-trade timescale obey the inverse cubic law. For la…

Vortex induced vibrations of bluff bodies occur when the vortex shedding frequency is close to the natural frequency of the structure. Of interest is the prediction of the lift and drag forces on the structure given some limited and scattered information on the velocity field. This is an inverse problem that is not str…

For a bounded domain $Ω\subset {\Bbb R}^n$ with smooth boundary, we explicitly calculate the first two coefficients of the asymptotic expansion of the trace of the strongly continuous semigroup associated with the Navier-Lamé operator on $Ω$ as $t\to 0^+$. These coefficients (i.e., spectral invariants) provide precise …

We uniquely and explicitly reconstruct the instantaneous intrinsic metric of the Kerr-Newman Event Horizon from the spectrum of its Laplacian. In the process we find that the angular momentum parameter, radius, area; and in the uncharged case, mass, can be written in terms of these eigenvalues. In the uncharged case th…

Paper proposes a federated learning framework for UAV swarms, optimizing convergence rate and energy consumption.

Sophie Germain's mean curvature deserves recognition as a surface shape measure.

A GAN method for stochastic boundary conditions in fast dynamics.

New method detects bearing faults using multivariate statistical process control.

The high structural deficient rate poses serious risks to the operation of many bridges and buildings. To prevent critical damage and structural collapse, a quick structural health diagnosis tool is needed during normal operation or immediately after extreme events. In structural health monitoring (SHM), many existing …

Paper designs energy-based controllers and observers for complex systems.

Deep learning's convolutional networks improve system identification.

We study a quantum system in a Riemannian manifold M on which a Lie group G acts isometrically. The path integral on M is decomposed into a family of path integrals on a quotient space Q=M/G and the reduced path integrals are completely classified by irreducible unitary representations of G. It is not necessary to assu…

Framework detects anomalies in fleet-based machine monitoring.

This paper details the techniques and algorithms implemented in Kahler, a Python library that implements discrete exterior calculus on arbitrary Hermitian manifolds. Borrowing techniques and ideas first implemented in PyDEC, Kahler provides a uniquely general framework for computation using discrete exterior calculus. …

Stokes-Dirac structures are infinite-dimensional Dirac structures defined in terms of differential forms on a smooth manifold with boundary. These Dirac structures lay down a geometric framework for the formulation of Hamiltonian systems with a nonzero boundary energy flow. Simplicial triangulation of the underlaying m…

Footfall based biometric system is perhaps the only person identification technique which does not hinder the natural movement of an individual. This is a clear edge over all other biometric systems which require a formidable amount of human intervention and encroach upon an individual's privacy to some extent or the o…

Material recognition enables robots to incorporate knowledge of material properties into their interactions with everyday objects. For example, material recognition opens up opportunities for clearer communication with a robot, such as "bring me the metal coffee mug", and recognizing plastic versus metal is crucial whe…

New method uses topological features for chatter detection in turning processes.