A5073574974- Machine Fault Diagnosis Techniques
- Infrared Target Detection Methodologies
- Air Quality Monitoring and Forecasting
- Industrial Technology and Control Systems
- Image and Object Detection Techniques
- Engineering Diagnostics and Reliability
- Advanced Measurement and Detection Methods
- Advanced Decision-Making Techniques
- Data Quality and Management
- Image Processing Techniques and Applications
- Gear and Bearing Dynamics Analysis
- Industrial Vision Systems and Defect Detection
Sichuan University
2022-2024
With the development of modernization, micro-motors are widely used in industry. The quality its core armature components directly affects performance micro-motors. Detection methods rely on manual visual inspection, with problems fluctuating accuracy and low detection efficiency. A high-precision, high-efficiency system is proposed to address these issues. Deep learning techniques applied handle complex patterns. model consists feature-extraction module, feature-fusion module classifier...
Trackside acoustic fault diagnosis is widely used for early detection in train bearings. However, signal distortion due to the Doppler Effect poses a challenge effective diagnosis. Currently, correction, mainstream solution Effect, limited by known kinematic parameters and high noise interference. In this paper, novel learning model based on Pseudo Time Domain Demodulation (PDDD) Adaptation Network (DAN) proposed. It attempts construct relationship between signals bearing under unsupervised...
With the increasing intelligence of equipment, prognostics and health management (PHM) has been rapidly developed highly valued. As more sensors are employed to track full life complicated sensor redundancy becomes a concern. However, most current deep learning-based prediction models cannot effectively perform selection, do not fully take advantage spatiotemporal interaction relationships among sensors. To address these issues, Remaining useful (RUL) estimation method based on multi-sensor...