Research Areas
![Research Area 1](/cnerc-rail/-/media/department/cnerc-rail/content/research/research-area-1.jpg?bc=ffffff&h=181&w=344&hash=688D34AE42416B145E8A277FD66F8DE3)
Research Area 1: Advanced Sensing Technology
- Vision-based online monitoring for rail conditions
- PZT-FBG hybrid sensing for rail track damage detection
- Ultrasonic guided waves for SHM in Railway
- Railway condition monitoring and damage prediction
- Electromagnetic Interference Test for Maglev Train
- Online monitoring for Maglev, High-speed Rail and Metro
![Research Area 2](/cnerc-rail/-/media/department/cnerc-rail/content/research/research-area-2.jpg?bc=ffffff&h=181&w=344&hash=E5FCC1E0D80CAAFA1A53FC2F891CF326)
Research Area 2: Smart Dampers for Vibration/Noise Control
- Smart suspension system for high-speed trains
- Semi-active vibration control using smart MR suspension
- Railway noise sources and mitigation measures
- Rail particle dampers for vibration/noise control
- Configurable rail dynamic testbed at PolyU Shenzhen Research Institute
- Collaboration with local industry on Rail Noise Control
![Research Area 3](/cnerc-rail/-/media/department/cnerc-rail/content/research/research-area-3.png?bc=ffffff&h=181&w=344&hash=1DF6EE0F45BD9CAACF4172F67F68C4AF)
Research Area 3: Energy Harvesters for Sensors/Dampers
- Devised energy harvesters
- Rolling tests of a train bogie equipped with devised energy harvester
- Online monitoring on metro for testing of devised energy harvesters
- Smart sensing, absorption, and harvesting technologies for railway electrification system
- Tailor-made sensors made of smart materials
- Facilities in CNERC-Rail for smart sensor fabrication
![Research Area 4](/cnerc-rail/-/media/department/cnerc-rail/content/research/research-area-4.jpg?bc=ffffff&h=181&w=344&hash=DF04E70CD8C10037EF4A3313CB4E93B3)
Research Area 4: Machine Learning for Diagnosis/Prognosis
- Transfer learning for crack and deterioration diagnosis of rail
- Adversarial domain adaptation for wheel defect detection
- Adaptive deep learning for compressive sensing of HSR
- CNN-based damage detection of maglev rail joints