A5100391562- Machine Fault Diagnosis Techniques
- Fault Detection and Control Systems
- Gear and Bearing Dynamics Analysis
- Structural Health Monitoring Techniques
- Advanced machining processes and optimization
- Reliability and Maintenance Optimization
- Non-Destructive Testing Techniques
- Advanced Battery Technologies Research
- Engineering Diagnostics and Reliability
- Simulation and Modeling Applications
- Industrial Vision Systems and Defect Detection
- Advanced Surface Polishing Techniques
- Industrial Technology and Control Systems
- Advanced Algorithms and Applications
- Advancements in Battery Materials
- Advanced Machining and Optimization Techniques
- Ultrasonics and Acoustic Wave Propagation
- Advanced Sensor and Control Systems
- Mobile Agent-Based Network Management
- Recommender Systems and Techniques
- Service-Oriented Architecture and Web Services
- RFID technology advancements
- Advanced Measurement and Detection Methods
- Advanced Decision-Making Techniques
- Thermography and Photoacoustic Techniques
Shanghai Jiao Tong University
2016-2025
Fudan University
2025
Nanchang University
2024-2025
Beijing Institute of Technology
2025
Shanghai Dianji University
2024
Liaoning Technical University
2012-2024
State Key Laboratory of Mechanical System and Vibration
2022-2024
Tsinghua University
2004-2024
Dalian University
2024
Dalian University of Technology
2001-2024
Lithium-ion batteries are critical components to provide power sources for commercial products. To ensure a high reliability of lithium-ion batteries, prognostic actions should be prepared. In this paper, method is proposed predict the remaining useful life (RUL) batteries. A state-space model battery capacity first constructed assess degradation. Then, spherical cubature particle filter (SCPF) introduced solve model. The major idea SCPF adapt integration-based Kalman an importance function...
State-of-charge (SOC), which indicates the remaining capacity at current cycle, is key to driving range prediction of electric vehicles and optimal charge control rechargeable batteries. In this paper, we propose a combined convolutional neural network (CNN) - long short-term memory (LSTM) infer battery SOC from measurable data, such as current, voltage, temperature. The proposed shares merits both CNN LSTM networks can extract spatial temporal features input data. trained using data...
As a breakthrough in the field of machine fault diagnosis, deep learning has great potential to extract more abstract and discriminative features automatically without much prior knowledge compared with other methods, such as signal processing analysis-based methods shallow architectures. One most important aspects measuring extracted is whether they can explore information inputs avoid redundancy be representative. Thus, stacked sparse autoencoder (SAE)-based diagnosis method proposed this...
Recently, various fault diagnosis methods based on domain adaptation (DA) have been explored to solve the problem of discrepancy between source and target domains. However, given complex industrial scenarios, DA-based usually fail when working conditions machines are unseen, i.e., data unavailable during model training. In this article, a generic domain-regressive framework for diagnosis, namely, adversarial domain-invariant generalization (ADIG), is proposed. ADIG leverages multiple...
The effective remaining useful life (RUL) prediction of rolling bearings could guarantee mechanical equipment reliability and stability. hybrid physical data-driven prognosis model (HPDM) is recently receiving increasing attention. However, HPDM approaches suffer from two significant challenges that limit their applicability to complex scenarios: (1) the reality gap between simulation measurement data (2) limited generality accommodate different working conditions machines. From perspective...
Aqueous metal-ion batteries are considered next-generation energy storage devices with improved safety. However, they suffer from sluggish kinetics and side reactions. This work presents a zinc-ion encapsulation strategy based on the poloxamer pre-solvation sheath for realization of efficient zinc anode–electrolyte interfaces. The poloxamers can reversibly self-assemble into by electron-donating effect effectively shield ions surrounding water. also lowers activation desolvation, endowing...