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Lightweight fault diagnosis method in embedded system based on knowledge distillation
Deep learning (DL) has garnered attention in mechanical device health management for its ability to accurately identify faults and predict component...
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An effective torque-based method for automatic turn fault detection and turn fault severity classification in permanent magnet synchronous motor
This article presents a novel approach based on the electromechanical torque signal for the inter-turn short-circuit fault (ISCF) detection and the...
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Context Adaptive Fault Tolerant Multi-sensor fusion: Towards a Fail-Safe Multi Operational Objective Vehicle Localization
In many transport applications, one of the safety critical function is the localization. This is all the more true for land transport applications...
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Rolling bearing fault diagnosis method based on MTF and PC-MDCNN
A rolling bearing fault diagnosis method based on Markov transition field (MTF) and the pyramid cascade multidimensional convolutional neural network...
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Denoising Fault-Aware Wavelet Network: A Signal Processing Informed Neural Network for Fault Diagnosis
Deep learning (DL) is progressively popular as a viable alternative to traditional signal processing (SP) based methods for fault diagnosis. However,...
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Gray relation weighted wavelet neural network integrated model and its application in rotating machinery fault diagnosis
Considering the variability and complexity of rotating machinery fault diagnosis, the fault diagnosis information carried out by a single model is...
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Recent Advancements in Fault Diagnosis of Spherical Roller Bearing: A Short Review
PurposeEarly detection of bearing faults is an essential task of machine health monitoring. The bearings are one of the vital components of rotary...
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Fault Detection in Photovoltaic Systems Using Optimized Neural Network
AbstractFault detection in photovoltaic (PV) arrays is one of the prime challenges for the operation of solar power plants. This paper proposes an...
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Performance Efficient and Fault Tolerant Approximate Adder
Fault tolerant adders are an important design paradigm to improve the robustness of the adder while at the same time improving the yield. The major...
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Decentralized Fault Estimation and Distributed Fault-tolerant Tracking Control Co-design for Sensor Faulty Multi-agent Systems with Bidirectional Couplings
This study proposes a co-design framework of decentralized fault estimation and distributed fault-tolerant tracking control schemes of Lipschitz...
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Multi-domain fusion for cargo UAV fault diagnosis knowledge graph construction
The fault diagnosis of cargo UAVs (Unmanned Aerial Vehicles) is crucial to ensure the safety of logistics distribution. In the context of smart...
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A joint deep learning model for bearing fault diagnosis in noisy environments
In practical engineering environments, rolling bearing vibration signal is often interfered by strong noise, which negatively affects the diagnostic...
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Imbalanced data fault diagnosis of rolling bearings using enhanced relative generative adversarial network
Rolling bearings, as integral components of rotating machinery, play a crucial role in ensuring the safe and stable operation of equipment. However,...
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Permutation Entropy and K-ELM in Gear Fault Diagnosis
For Learning Machine Extreme the number of hidden layer nodes artificially set and the fault classification model of the gear is of low accuracy and...
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A novel hierarchical transferable network for rolling bearing fault diagnosis under variable working conditions
The deterioration of bearing failure is a gradual process. Simultaneously identifying the fault pattern and severity is of great significance for...
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Statistical Fault Analysis of TinyJambu
The resource-constrained IoT devices have limited resources such as processing power, memory, and battery capacity. Therefore it is challenging to...
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Fault location based on FastICA and fuzzy C-means clustering for single-phase-to-ground fault in the compensated distribution network
A new method for fault location during a single-phase-to-ground fault in the compensated distribution network is proposed in this paper. The method...
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An interpretable graph convolutional neural network based fault diagnosis method for building energy systems
Due to the fast-modeling speed and high accuracy, deep learning has attracted great interest in the field of fault diagnosis in building energy...
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Fault diagnosis of HVAC system with imbalanced data using multi-scale convolution composite neural network
Accurate fault diagnosis of heating, ventilation, and air conditioning (HVAC) systems is of significant importance for maintaining normal operation,...
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A Multi-scale Attention-Based Transfer Model for Cross-bearing Fault Diagnosis
Bearings are key components of mechanical equipment, and fault diagnosis is a necessary and important measure to ensure bearing safety. Driven by...
