A5015632300- Gear and Bearing Dynamics Analysis
- Tribology and Lubrication Engineering
- Mechanical Engineering and Vibrations Research
- Prosthetics and Rehabilitation Robotics
- Machine Fault Diagnosis Techniques
- Real-time simulation and control systems
- Transportation Safety and Impact Analysis
- Vehicle Noise and Vibration Control
- Adhesion, Friction, and Surface Interactions
- Structural Health Monitoring Techniques
- Advanced machining processes and optimization
- Muscle activation and electromyography studies
- Diabetic Foot Ulcer Assessment and Management
- Hydraulic and Pneumatic Systems
- Advanced Measurement and Detection Methods
- Electric and Hybrid Vehicle Technologies
National Science and Technology Development Agency
2024
Technical University of Munich
2017-2018
Intelligent machinery condition monitoring and damage diagnostics is becoming increasingly important: Meeting low maintenance budgets of key importance in a more globalized competitive market environment. Being able to detect gearbox early an automated way allows for extended service intervals, less standstill decreased total cost. One the know mechanisms gear failure occurrence pitting on teeth flanks. Advancing leads shift noise excitation behaviour pair. Common solution often rely...
Gearbox design must satisfy multiple demands that usually involve high power density, low energy consumption and favourable noise emission. Where the layout of loaded gears is concerned, objectives comprise a load carrying capacity, gear losses mesh design. This has become more important late since for example engine-generated levels used to mask are reduced by increasingly electrified drive trains. In order transmit loads within smallest possible space tooth micro geometry be modified from...
Lateral walking gait phase recognition and prediction are the premise of hip exoskeleton application in lateral resistance walk exercise. In this work, we presented a fusion network with stacked denoise autoencoder meta learning (SDA-NN-ML) to recognize predict percentage from IMU signals. Experiments were conducted detect four phases their 10 healthy subjects across different speeds. The performance SDA-NN-ML other widely used algorithms including Support Vector Machine (SVM), Adaptive...