Search Results - guangxing+niu

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Lebesgue-Sampling-based Deep Learning for Battery Diagnosis and Prognosis

Reference #: 01603 The University of South Carolina is offering licensing opportunities for Lebesgue-Sampling-based Deep Learning for Battery Diagnosis and Prognosis Background: Accurate and efficient modeling of battery degradation is of great challenge and is becoming more and more complex for batteries in modern applications. Traditional degradation...

Published: 5/16/2023 | Inventor(s): Bin Zhang, Guangxing Niu

Keywords(s): Deep belief network, Diagnosis and prognosis, Fault dynamic model, Lebesgue sampling, Lithium-ion battery, Particle filter, Uncertainty management

Category(s): Engineering and Physical Sciences, Energy

Hybrid Rotating Machinery Fault Diagnosis and Prognosis

Reference #: 01570 The University of South Carolina is offering licensing opportunities for Hybrid Rotating Machinery Fault Diagnosis and Prognosis Background: Bearing faults are the top contributor to the failure of rotating machinery systems. In wind energy systems, about 80% of gearbox failures are caused by bearing faults. According to verified...

Published: 8/22/2024 | Inventor(s): Guangxing Niu, Bin Zhang

Keywords(s): Continuous wavelet transform, convolutional neural network, Fault model selection, Particle filter, Rotating machinery systems, STP estimation

Category(s): Engineering and Physical Sciences

DRCNN for Multi-task Bearing Fault Diagnosis with Information Fusion

Reference #: 01571 The University of South Carolina is offering licensing opportunities for DRCNN for Multi-task Bearing Fault Diagnosis with Information Fusion Background: First, most industrial systems are working in variable operating conditions and environments. The information of operating conditions, such as load profile, rotating speed, and...

Published: 8/22/2024 | Inventor(s): Guangxing Niu, Bin Zhang

Keywords(s): Bearing, Deep residual convolutional neural network, Discriminate Feature Learning, Information Fusion, Multi-task Fault Diagnosis

Category(s): Engineering and Physical Sciences

Lithium-ion battery health management based on single particle model

Reference #: 01494 The University of South Carolina is offering licensing opportunities for Lithium-ion battery health management based on single particle model Background: A single particle model is used in simulating the behavior of lithium-ion battery. Particle swarm optimization is used to identify the parameters of the single particle model....

Published: 9/3/2022 | Inventor(s): Guangxing Niu, Bin Zhang

Keywords(s): Bayesian approach, Lebesgue sampling, Particle swarm optimization, Single particle model, State of charge, State of health

Category(s): Energy, Engineering and Physical Sciences