Results 21 to 30 of about 222 (98)

Axioms for the category of Hilbert spaces and linear contractions

open access: yesBulletin of the London Mathematical Society, Volume 56, Issue 4, Page 1532-1549, April 2024.
Abstract The category of Hilbert spaces and linear contractions is characterised by elementary categorical properties that do not refer to probabilities, complex numbers, norm, continuity, convexity or dimension.
Chris Heunen   +2 more
wiley   +1 more source

Rolling bearing weak fault detection using transient structure‐optimal VMD and adaptive group sparse coding

open access: yesIET Science, Measurement &Technology, Volume 18, Issue 2, Page 86-102, March 2024.
The contributions of this paper are mainly reflected in: (1) A method for determining the modes number of VMD using SVS technology is proposed, which can effectively avoid the shortcomings of the optimization algorithm. (2) The TSM index is established to describe the transient structure of bearing fault signals, and the balance factor selection based ...
Xing Yuan, Hui Liu, Huijie Zhang
wiley   +1 more source

A p$p$‐adic approach to the existence of level‐raising congruences

open access: yesProceedings of the London Mathematical Society, Volume 128, Issue 2, February 2024.
Abstract We construct level‐raising congruences between p$p$‐ordinary automorphic representations, and apply this to the problem of symmetric power functoriality for Hilbert modular forms. In particular, we prove the existence of the nth$n\text{th}$ symmetric power lift of a Hilbert modular eigenform of regular weight for each odd integer n=1,3,⋯,25$n =
Jack A. Thorne
wiley   +1 more source

Hierarchical Deep Learning for Bearing Fault Detection in BLDC Motors Using Time‐Frequency Analysis

open access: yesJournal of Electrical and Computer Engineering, Volume 2024, Issue 1, 2024.
This paper presents new hierarchical image‐based time‐frequency convolutional neural network (HTFICNN) for sorted bearing fault detection in brushless DC (BLDC) motors. The HTFICNN combines three different time‐frequency visualisation methods: scalogram, spectrogram, and Hilbert spectrum for the transformation of current and vibration signals into time‐
Ahmed K. Ali   +2 more
wiley   +1 more source

Effectiveness of Drive‐By Monitoring in Short‐Span Bridges: A Real‐Scale Experimental Evaluation

open access: yesStructural Control and Health Monitoring, Volume 2024, Issue 1, 2024.
This paper experimentally assesses the efficacy of the indirect Structural Health Monitoring (iSHM) framework on a full‐scale short‐span bridge of nine meters long, using an instrumented vehicle with non‐negligible mass with respect to the mass of the bridge.
Kyriaki Gkoktsi   +3 more
wiley   +1 more source

Research on the Application of Variational Mode Decomposition Optimized by Snake Optimization Algorithm in Rolling Bearing Fault Diagnosis

open access: yesShock and Vibration, Volume 2024, Issue 1, 2024.
The rolling bearing is one of the commonly used mechanical components in rotating machinery, and its health directly affects the normal operation of equipment. However, the fault signal of rolling bearing is susceptible to noise interference, which makes it difficult to extract the fault characteristics of the rolling bearing and thus affects the ...
Houxin Ji   +3 more
wiley   +1 more source

Deep Domain Adaptation Approach Using an Improved Parallel Residual Network for Cross‐Domain Bearing Fault Diagnosis

open access: yesShock and Vibration, Volume 2024, Issue 1, 2024.
Recently, bearing fault diagnosis based on transfer learning (TL) has been a hot topic, which has attracted widespread interest due to its ability to adapt bearing fault datasets with different feature distributions. However, existing research suffer from low diagnosis efficiency and poor generalization capabilities.
Jiezhou Huang, Luca Pugi
wiley   +1 more source

A New Framework Based on Supervised Joint Distribution Adaptation for Bearing Fault Diagnosis across Diverse Working Conditions

open access: yesShock and Vibration, Volume 2024, Issue 1, 2024.
To address the degradation of diagnostic performance due to data distribution differences and the scarcity of labeled fault data, this study has focused on transfer learning‐based cross‐domain fault diagnosis, which attracts considerable attention. However, deep transfer learning‐based methods often present a challenge due to their time‐consuming and ...
Chengyao Liu, Fei Dong, Zhipeng Zhao
wiley   +1 more source

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