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   Articles with "intelligent fault" as a keyword



An Intelligent Fault Diagnosis Method for Lithium Battery Systems Based on Grid Search Support Vector Machine

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recommendations! Published in 2021 at "Energy"

DOI: 10.1016/j.energy.2020.118866

Abstract: Abstract For the safe operation of the electric vehicle, it is critical to quickly detect the safety state and accurately identify the fault degree in battery packs. This article proposes a novel intelligent fault diagnosis… read more here.

Keywords: intelligent fault; diagnosis method; method; support vector ... See more keywords
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Intelligent fault diagnosis of machines with small & imbalanced data: A state-of-the-art review and possible extensions.

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recommendations! Published in 2021 at "ISA transactions"

DOI: 10.1016/j.isatra.2021.02.042

Abstract: The research on intelligent fault diagnosis has yielded remarkable achievements based on artificial intelligence-related technologies. In engineering scenarios, machines usually work in a normal condition, which means limited fault data can be collected. Intelligent fault… read more here.

Keywords: fault; imbalanced data; research; diagnosis ... See more keywords

Intelligent fault detection of high voltage line based on the Faster R-CNN

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recommendations! Published in 2019 at "Measurement"

DOI: 10.1016/j.measurement.2019.01.072

Abstract: Abstract To realize intelligent fault detection of high voltage line, a deep convolution neural network method based on Faster R-CNN method is proposed to locate the broken insulators and bird nests. With the region proposal… read more here.

Keywords: intelligent fault; faster cnn; line; fault detection ... See more keywords

MiDAN: A framework for cross-domain intelligent fault diagnosis with imbalanced datasets

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recommendations! Published in 2021 at "Measurement"

DOI: 10.1016/j.measurement.2021.109834

Abstract: Abstract The success of deep learning techniques for intelligent fault diagnosis relies on two explicit assumptions: (1) the training and testing data are drawn from the same distribution; (2) the data are class-wise balanced. However,… read more here.

Keywords: diagnosis; intelligent fault; domain; fault diagnosis ... See more keywords

A neural network constructed by deep learning technique and its application to intelligent fault diagnosis of machines

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recommendations! Published in 2018 at "Neurocomputing"

DOI: 10.1016/j.neucom.2017.07.032

Abstract: In traditional intelligent fault diagnosis methods of machines, plenty of actual effort is taken for the manual design of fault features, which makes these methods less automatic. Among deep learning techniques, autoencoders may be a… read more here.

Keywords: fault; layer; deep learning; intelligent fault ... See more keywords

Batch-normalized deep neural networks for achieving fast intelligent fault diagnosis of machines

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recommendations! Published in 2019 at "Neurocomputing"

DOI: 10.1016/j.neucom.2018.10.049

Abstract: Abstract Numerous researches have been conducted on developing effective intelligent fault diagnosis systems. As a commonly used deep learning technique, stacked autoencoders (SAEs) have shown the ability of automatic feature extraction and classification. However, the… read more here.

Keywords: fault; deep neural; neural networks; intelligent fault ... See more keywords

A novel model with the ability of few-shot learning and quick updating for intelligent fault diagnosis

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recommendations! Published in 2020 at "Mechanical Systems and Signal Processing"

DOI: 10.1016/j.ymssp.2019.106608

Abstract: Abstract Both of traditional intelligent fault diagnosis (TIFD) based on artificial features and modern intelligent fault diagnosis (MIFD) based on deep learning have made healthy progress in recent times. But, the bulk of methods neglects… read more here.

Keywords: diagnosis; model; intelligent fault; fault diagnosis ... See more keywords

An intelligent fault detection (IFD) system for lithium-ion battery using machine learning approach

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-17145-4

Abstract: In recent years, electric vehicles (EVs) have become increasingly popular, driven by advancements in battery technology, growing environmental awareness, and the demand for sustainable transportation. Compared to internal combustion engines, EVs not only produce fewer… read more here.

Keywords: fault detection; battery; approach; intelligent fault ... See more keywords

An intelligent fault diagnosis method for rolling bearings based on feature transfer with improved DenseNet and joint distribution adaptation

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recommendations! Published in 2021 at "Measurement Science and Technology"

DOI: 10.1088/1361-6501/ac3b0b

Abstract: Mechanical intelligent fault diagnosis is an important method to accurately identify the health status of mechanical equipment. Traditional fault diagnosis methods perform poorly in the diagnosis of rolling bearings under complex conditions. In this paper,… read more here.

Keywords: intelligent fault; method; diagnosis; distribution ... See more keywords

Research and Application of Regularized Sparse Filtering Model for Intelligent Fault Diagnosis Under Large Speed Fluctuation

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recommendations! Published in 2020 at "IEEE Access"

DOI: 10.1109/access.2020.2975531

Abstract: The speed of mechanical rotating parts often fluctuates during the working process. Vibration signals collected under constant speed have a strong correlation with the corresponding fault types. However, the mapping relationship becomes complex under large… read more here.

Keywords: speed; speed fluctuation; large speed; intelligent fault ... See more keywords

Towards a Standard Benchmarking Framework for Domain Adaptation in Intelligent Fault Diagnosis

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3537817

Abstract: Domain shift is a major problem facing contemporary data-based intelligent fault diagnosis (IFD) solutions. While domain adaptation (DA) methods have been proposed to address this issue, standardizing DA benchmarks has not received much attention. Existing… read more here.

Keywords: framework; intelligent fault; fault diagnosis; domain adaptation ... See more keywords