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09/20/2023
From Classification to Segmentation with Explainable AI: A Study on Crack Detection and Growth Monitoring
Monitoring surface cracks in infrastructure is crucial for structural he...
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09/19/2023
Graph Neural Networks for Dynamic Modeling of Roller Bearing
In the presented work, we propose to apply the framework of graph neural...
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09/08/2023
Spatial-Temporal Graph Attention Fuser for Calibration in IoT Air Pollution Monitoring Systems
The use of Internet of Things (IoT) sensors for air pollution monitoring...
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09/05/2023
A Comparison of Residual-based Methods on Fault Detection
An important initial step in fault detection for complex industrial syst...
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07/07/2023
Dynamic Graph Attention for Anomaly Detection in Heterogeneous Sensor Networks
In the era of digital transformation, systems monitored by the Industria...
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07/04/2023
Smart filter aided domain adversarial neural network: An unsupervised domain adaptation method for fault diagnosis in noisy industrial scenarios
The application of unsupervised domain adaptation (UDA)-based fault diag...
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06/19/2023
Non-contact Sensing for Anomaly Detection in Wind Turbine Blades: A focus-SVDD with Complex-Valued Auto-Encoder Approach
The occurrence of manufacturing defects in wind turbine blade (WTB) prod...
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05/31/2023
Domain knowledge-informed Synthetic fault sample generation with Health Data Map for cross-domain Planetary Gearbox Fault Diagnosis
Extensive research has been conducted on fault diagnosis of planetary ge...
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05/07/2023
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial
On top of machine learning models, uncertainty quantification (UQ) funct...
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04/30/2023
Collective Relational Inference for learning physics-consistent heterogeneous particle interactions
Interacting particle systems are ubiquitous in nature and engineering. R...
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04/26/2023
Federated Learning with Uncertainty-Based Client Clustering for Fleet-Wide Fault Diagnosis
Operators from various industries have been pushing the adoption of wire...
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04/23/2023
Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions
Limited availability of representative time-to-failure (TTF) trajectorie...
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03/24/2023
Incentive Mechanism in the Sponsored Content Market with Network Effect
We propose an incentive mechanism for the sponsored content provider mar...
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02/03/2023
Domain Adaptation via Alignment of Operation Profile for Remaining Useful Lifetime Prediction
Effective Prognostics and Health Management (PHM) relies on accurate pre...
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08/28/2022
Contrastive Feature Learning for Fault Detection and Diagnostics in Railway Applications
A railway is a complex system comprising multiple infrastructure and rol...
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08/11/2022
Multi-Agent Reinforcement Learning with Graph Convolutional Neural Networks for optimal Bidding Strategies of Generation Units in Electricity Markets
Finding optimal bidding strategies for generation units in electricity m...
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06/13/2022
Robust Time Series Denoising with Learnable Wavelet Packet Transform
In many applications, signal denoising is often the first pre-processing...
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06/01/2022
Dynaformer: A Deep Learning Model for Ageing-aware Battery Discharge Prediction
Electrochemical batteries are ubiquitous devices in our society. When th...
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02/01/2022
Learning Physics-Consistent Particle Interactions
Interacting particle systems play a key role in science and engineering....
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01/20/2022
A Prescriptive Dirichlet Power Allocation Policy with Deep Reinforcement Learning
Prescribing optimal operation based on the condition of the system and, ...
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12/20/2021
Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation units
This paper proposes a safe reinforcement learning algorithm for generati...
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06/21/2021
Artificial intelligence across company borders
Artificial intelligence (AI) has become a valued technology in many comp...
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05/03/2021
Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series
High-Frequency (HF) signal are ubiquitous in the industrial world and ar...
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04/14/2021
Maintenance scheduling of manufacturing systems based on optimal price of the network
Goods can exhibit positive externalities impacting decisions of customer...
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04/08/2021
Uncertainty-aware Remaining Useful Life predictor
Remaining Useful Life (RUL) estimation is the problem of inferring how l...
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01/07/2021
Decision Support System for an Intelligent Operator of Utility Tunnel Boring Machines
In tunnel construction projects, delays induce high costs. Thus, tunnel ...
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12/07/2020
Battery Model Calibration with Deep Reinforcement Learning
Lithium-Ion (Li-I) batteries have recently become pervasive and are used...
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11/27/2020
Distributed joint dynamic maintenance and production scheduling in manufacturing systems: Framework based on model predictive control and Benders decomposition
Scheduling the maintenance based on the condition, respectively the degr...
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09/30/2020
Improving Generalization of Deep Fault Detection Models in the Presence of Mislabeled Data
Mislabeled samples are ubiquitous in real-world datasets as rule-based o...
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08/18/2020
Transferring Complementary Operating Conditions for Anomaly Detection
In complex industrial systems, the number of possible fault types is unc...
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08/13/2020
Interpretable Partial Discharge Detection with Temporal Convolution and Pulse Activation Maps: An application to Power Lines
Partial discharge (PD) is a common indication of insulation damages in p...
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07/17/2020
Off-Policy Reinforcement Learning for Efficient and Effective GAN Architecture Search
In this paper, we introduce a new reinforcement learning (RL) based neur...
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06/07/2020
Real-Time Model Calibration with Deep Reinforcement Learning
The dynamic, real-time, and accurate inference of model parameters from ...
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05/14/2020
Anomaly Detection And Classification In Time Series With Kervolutional Neural Networks
Recently, with the development of deep learning, end-to-end neural netwo...
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05/14/2020
Time Series to Images: Monitoring the Condition of Industrial Assets with Deep Learning Image Processing Algorithms
The ability to detect anomalies in time series is considered as highly v...
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02/27/2020
Multi-agent maintenance scheduling based on the coordination between central operator and decentralized producers in an electricity market
Condition-based and predictive maintenance enable early detection of cri...
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01/07/2020
Missing-Class-Robust Domain Adaptation by Unilateral Alignment for Fault Diagnosis
Domain adaptation aims at improving model performance by leveraging the ...
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12/28/2019
Knowledge-Induced Learning with Adaptive Sampling Variational Autoencoders for Open Set Fault Diagnostics
The recent increase in the availability of system condition monitoring d...
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07/22/2019
Fully Unsupervised Feature Alignment for Critical System Health Monitoring with Varied Operating Conditions
The failure of a complex and safety critical industrial asset can have e...
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07/15/2019
Unsupervised Fault Detection in Varying Operating Conditions
Training data-driven approaches for complex industrial system health mon...
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05/15/2019
Domain Adaptive Transfer Learning for Fault Diagnosis
Thanks to digitization of industrial assets in fleets, the ambitious goa...
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10/12/2018