A5079347204- Machine Fault Diagnosis Techniques
- Non-Destructive Testing Techniques
- Fault Detection and Control Systems
- Covalent Organic Framework Applications
- Machine Learning and ELM
- Gear and Bearing Dynamics Analysis
- Structural Integrity and Reliability Analysis
- Analytical chemistry methods development
- Phytochemicals and Antioxidant Activities
- Bayesian Modeling and Causal Inference
- Advanced Decision-Making Techniques
- Multi-Criteria Decision Making
- Target Tracking and Data Fusion in Sensor Networks
- Molecular Sensors and Ion Detection
Jimei University
2024
Shanghai University
2021-2023
Shandong Normal University
2009
Abstract Transfer learning technology has been successfully applied to address the domain adaptation (DA) problem in machinery fault diagnosis. However, partial DA is more suitable for industrial applications, where target data only covers a subset of source classes, which makes it difficult know transfer data. To overcome this problem, novel game theory enhanced network (GT-DAN) proposed paper. Based on different metrics, including maximum mean discrepancy, Jensen–Shannon divergence and...
Artificial intelligence technology is widely used in mechanical system fault diagnosis as an effective means, but there are few samples practice, which seriously restricts the industrial application of Al model to high-precision diagnosis. In order overcome lack samples, a method composed Gaussian cloud and domain-invariant features extraction proposed for expanding training this paper. The include three steps. Firstly, limited measured obtained by calculating time-domain feature indexes...