Search results for " Applications"
showing 10 items of 4541 documents
A linearization technique and error estimates for distributed parameter identification in quasilinear problems
1996
The identification problem of a nonlinear functional coefficient in elliptic and parabolic quasilinear equations is considered. A distributed observation of the solution of the corresponding equation is assumed to be known a priori. An identification method is introduced, which needs only a linear equation to be solved in each iteration step of the optimization. Estimates of the rate of convergence for the proposed approach are proved, when the equation is discretized with the finite element method with respect to space variables. Some numerical results are given.
On Boundary Conditions for Wedge Operators on Radial Sets
2008
We present a theorem about calculation of fixed point index for k-$\psi$-contractive operators with 0 < k <1 defined on a radial set of a wedge of an infinite dimensional Banach space. Then results on the existence of eigenvectors and nonzero fixed points are obtained.
Hilbert-Huang versus Morlet wavelet transformation on mismatch negativity of children in uninterrupted sound paradigm
2008
Background Compared to the waveform or spectrum analysis of event-related potentials (ERPs), time-frequency representation (TFR) has the advantage of revealing the ERPs time and frequency domain information simultaneously. As the human brain could be modeled as a complicated nonlinear system, it is interesting from the view of psychological knowledge to study the performance of the nonlinear and linear time-frequency representation methods for ERP research. In this study Hilbert-Huang transformation (HHT) and Morlet wavelet transformation (MWT) were performed on mismatch negativity (MMN) of children. Participants were 102 children aged 8–16 years. MMN was elicited in a passive oddball parad…
On utilizing an enhanced object partitioning scheme to optimize self-organizing lists-on-lists
2020
With the advent of “Big Data” as a field, in and of itself, there are at least three fundamentally new questions that have emerged, namely the Artificially Intelligence (AI)-based algorithms required, the hardware to process the data, and the methods to store and access the data efficiently. This paper (The work of the second author was partially supported by NSERC, the Natural Sciences and Engineering Council of Canada. We are very grateful for the feedback from the anonymous Referees of the original submission. Their input significantly improved the quality of this final version.) presents some novel schemes for the last of the three areas. There have been thousands of papers written rega…
Optimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations
2022
AbstractWe introduce novel concepts to solve multiobjective optimization problems involving (computationally) expensive function evaluations and propose a new interactive method called O-NAUTILUS. It combines ideas of trade-off free search and navigation (where a decision maker sees changes in objective function values in real time) and extends the NAUTILUS Navigator method to surrogate-assisted optimization. Importantly, it utilizes uncertainty quantification from surrogate models like Kriging or properties like Lipschitz continuity to approximate a so-called optimistic Pareto optimal set. This enables the decision maker to search in unexplored parts of the Pareto optimal set and requires …
Robust Active Learning Multiple Fault Diagnosis of PMSM Drives with Sensorless Control under Dynamic Operations and Imbalanced Datasets
2022
Authors accepted manuscript © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This paper proposes an active learning scheme to detect multiple faults in permanent magnet synchronous motors in dynamic operations without using historical labelled faulty training data. The proposed method combines the self-supervised anomaly detector based on a local outlier factor…
A new control parameter to predict micro-warping-induced job failure in LPBF of TI6AL4V titanium alloy
2023
Abstract Laser powder bed fusion (LPBF) includes a few printing techniques widely used, in recent years, concerning the additive manufacturing of Ti6Al4V alloys. These produced parts, typically utilized in sectors such as aerospace and biomedical, are characterized by very high added value. It is therefore fundamental to identify the influence of process parameters typical of LPBF technology on the occurrence of warping leading to process failure. This study deals with the characterization of single-track and “micro-scale” level warping phenomena which may lead to protrusion of material over the powder bed and process failure before normal termination. This phenomenon was investigated as a …
A novel approach to enhance mechanical properties during recycling of aluminum alloy scrap through friction stir consolidation
2021
Solid state recycling (SSR) is a new approach for making metals recycling more efficient with respect to remelting-based approaches. Friction stir consolidation (FSC) is a new solid-state process that is employed to recycle metallic scraps. Until now, a single-step FSC process was applied to recycled metal chips. During the single-step approach, critical processes parameters, especially processing time and rotational speed, are considered vital to control the quality and mechanical properties of the billet. However, the effectiveness of process parameters is highly restricted by challenging masses of recycling chips and machine competency. The present study first highlights the issues of th…
RMS Based Health Indicators for Remaining Useful Lifetime Estimation of Bearings
2022
Estimating the remaining useful life (RUL) of bearings from healthy to faulty is important for predictive maintenance. The bearing fault severity can be estimated based on the energy or root mean square (RMS) of vibration signals, and a stopping criterion can be set based on a threshold given by an ISO standard. However, the vibration RMS is often not monotonically increasing with damage, which renders a challenge for predicting the RUL. This study proposes a novel method for splitting the vibration signal into multiple frequency bands before RMS calculations to generate multiple health indicators. Monotonic health indicators are identified using the Spearman coefficient, and the RUL is aft…
Experimental System Identification and Black Box Modeling of Hydraulic Directional Control Valve
2015
Directional control valves play a large role in most hydraulic systems. When modeling the hydraulic systems, it is important that both the steady state and dynamic characteristics of the valves are modeled correctly to reproduce the dynamic characteristics of the entire system. In this paper, a proportional valve (Brevini HPV 41) is investigated to identify its dynamic and steady state characteristics. The steady state characteristics are identified by experimental flow curves. The dynamics are determined through frequency response analysis and identified using several transfer functions. The paper also presents a simulation model of the valve describing both steady state and dynamic charac…