A5054939493- Machine Fault Diagnosis Techniques
- Structural Health Monitoring Techniques
- Advanced machining processes and optimization
- Magnetic Bearings and Levitation Dynamics
- Industrial Vision Systems and Defect Detection
- Structural Engineering and Vibration Analysis
- Wind and Air Flow Studies
- Tribology and Lubrication Engineering
- Vehicle emissions and performance
- Advanced Algorithms and Applications
- Modeling, Simulation, and Optimization
- Manufacturing Process and Optimization
- Control Systems in Engineering
- Gear and Bearing Dynamics Analysis
- Material Selection and Properties
- Quality Function Deployment in Product Design
- Time Series Analysis and Forecasting
- Advanced Measurement and Metrology Techniques
- Neural Networks and Applications
- Electric Vehicles and Infrastructure
- Aerodynamics and Fluid Dynamics Research
- Hydraulic and Pneumatic Systems
- Wind Energy Research and Development
- Mechanical Failure Analysis and Simulation
- Electric and Hybrid Vehicle Technologies
Beihang University
2020-2024
Tsinghua University
2024
Sharif University of Technology
2013-2020
The rapid development of industry results in large energy consumption and a negative impact on the environment. Pollution environment caused by conventional sources such as petrol leads to increased demand for propulsion systems with higher efficiency capable energy-saving emission reduction. usage hybrid technology is expected improve conversion efficiency, reduce environmental pollution. In this paper, simulation platform unmanned aerial vehicle (UAV) has been built establishing subsystem...
Through the advancement of Data Science methodologies, a new era in output-only identification techniques has been inaugurated, driven by integration data-driven methodologies within realm Structural Health Monitoring (SHM). This study endeavors to introduce simplified approach catering System Identification (SI) and Response Estimation (RE). is realized through utilization summation sine functions, fashioned as model harmonize with time domain vibration acoustic responses. The fidelity...
This article presents an innovative application of the frequency domain decomposition method based on acoustic and vibration response. Frequency has been frequently used for operational modal analysis testing in last decade to identify parameters in-situ case studies. For these studies, outputs response through accelerometers have employed analysis. In this article, is employed, first time, analyze both building which a novel As study, cylindrical shaped seven-story building, appears be...
Extensive studies have been conducted on joint time-frequency transforming techniques for non-stationary time series with the aim of enhancing both and frequency accuracies resolutions. These successfully applied in various research areas. However, controlling minimizing computational costs data volume by reducing complexities remained open challenges this case. This need is becoming increasingly crucial condition monitoring using Cloud-Edge computing, where these areas face a relatively...
As rotary machines have become more complicated, balancing processes been classified as a vital step in condition monitoring to ensure that operate reliably, smoothly and safely. All rotating objects will deflect during rotation all possess certain natural frequencies the absence of rotation. However, an unbalanced object can cause significant unwanted deflection created by resonant vibration at frequency (cycles/second) close rotational speeds (rotations/second), known critical speeds. This...
As rotary machines have become more complicated, balancing processes been classified as a vital step in condition monitoring to ensure operate both reliably and safely. This is especially important for flexible which normally work at rotations speeds above critical limits. Imbalance common problem rotating machinery that can lead extreme vibration noise levels. one of the major reasons studying various methods applied response machines. Recently, relation between acoustic during machine...
The application of Machine Learning methodologies has been particularly noteworthy and abundant in pattern symptom recognition across various research areas. However, Tool Condition Monitoring remains a challenging subject due to the gradual wearing out cutting tools during machining process. Such failure leads reduced accuracy quality machined surface workpiece, resulting increased costs. This proposes an innovative ML-based method clarify symptoms frequency time-frequency domains. study...