A5023579262- Industrial Vision Systems and Defect Detection
- Surface Roughness and Optical Measurements
- Fault Detection and Control Systems
- Advanced Measurement and Detection Methods
- Welding Techniques and Residual Stresses
- Non-Destructive Testing Techniques
- Machine Fault Diagnosis Techniques
- Mineral Processing and Grinding
- Anomaly Detection Techniques and Applications
- Manufacturing Process and Optimization
- Thermography and Photoacoustic Techniques
- Advanced Neural Network Applications
Xi'an Jiaotong University
2021-2024
Surface damage detection is vital for diagnosis and monitoring of aeroengine blade. At present, borescope inspection the dominant technology. Several inspectors hold to inspect blades one by through naked eyes on apron. The turbine even requires drilling into narrow tail nozzle. manual visual high cost low efficiency. To improve efficiency economic benefit, we propose an intelligent method in this article. Facing problem weak information caused background noise unsatisfactory illumination,...
Aero-engine is the core component of aircraft and other spacecraft. The high-speed rotating blades provide power by sucking in air fully combusting, various defects will inevitably occur, threatening operation safety aero-engine. Therefore, regular inspections are essential for such a complex system. However, existing traditional technology which borescope inspection labor-intensive, time-consuming, experience-dependent. To endow this with intelligence, novel superpixel perception graph...
Condition monitoring is one of the key tasks for intelligent maintenance high-end equipment. Facing challenge its changing working conditions, models that are built upon constant conditions not qualified this task. To solve problem, a syncretic self-regression variational auto-encoder (SSR-VAE) model proposed to realize parallel training distribution learning and regression machine anomaly detection. Among them, plays an auxiliary role in learning. Furthermore, multi-sensor information...