1. Introduction to the laboratory
Focusing on the core scientific issues of monitoring-diagnosis-operation and maintenance in the whole life cycle of electromechanical equipment, the institute carries out theoretical, methodological and applied researches on failure mechanism modeling, signal processing and feature extraction, health monitoring and fault diagnosis, intelligent operation and maintenance, and health management. We have completed more than 30 projects of national 863, National Natural Science Foundation of China, provincial major scientific and technological achievements transformation projects, and more than 60 research projects entrusted by enterprises, and won 5 second and third prizes for scientific and technological progress at provincial and ministerial levels. In addition, we have published more than 200 SCI/EI papers in domestic and international high-level journals, and have authorized more than 30 invention patents, and registered more than 10 software copyrights. MFD/PFD/WFD/EMD series of condition monitoring and analysis diagnosis system, wireless vibration sensor, fault diagnosis edge calculator and other products have been successfully applied in machinery, petrochemical, metallurgy, electric power and other industries.
2. Key research directions
(1) Electromechanical equipment failure mechanism modeling: Research on multi-physics coupling modeling of force, vibration, sound and heat under fault or damage modes of electromechanical equipment rotors, bearings and structural parts, and construct multi-scale, multi-field and multi-domain failure mechanism research from micro, mesoscopic to macroscopic system.
(2) Dynamic signal processing and feature extraction: Research on modern statistical and adaptive signal processing, system modeling and identification, linear and nonlinear feature extraction and other theories and methods to form a multi-field, multi-scale signal processing and feature extraction theoretical system that integrates vibration, acoustic, thermal, force and other signals.
(3) Intelligent fault diagnosis: Research on fault diagnosis theories and methods such as deep learning, knowledge mapping, statistical learning, etc., and form a theoretical framework for intelligent fault diagnosis of electromechanical equipment based on big data analysis + knowledge mapping + artificial intelligence.
(4) Intelligent operation and maintenance of electromechanical equipment: Research on theories and methods of health monitoring, life prediction and intelligent decision-making of electromechanical equipment and its key components, and construct a management system for equipment health assessment and remaining life prediction that covers model-driven, knowledge-driven, and data-driven.
(5) Electromechanical equipment fault diagnosis, itelligent operation and maintenance platform: Research on software and hardware devices and systems related to intelligent perception of information, intelligent analysis of data, intelligent diagnosis of faults, and intelligent safeguard of operation and maintenance, and construct an integrated platform for perception-analysis-diagnosis-operation and maintenance of electromechanical equipment for the industries of machinery, petrochemicals, energy, iron and steel, and so on.
3. Laboratory members
Director: Prof. Dr. Feiyun Xu
Core members: Prof. Dr. Minping Jia, Assoc. Prof. Dr. Jianzhong Hu, Prof. Dr. Peng Huang.
4. Major instruments and equipment
5. Photographs
6. Cases
Dandong Huatong Measure and Control Co., Ltd: R&D of high vibration bandwidth wireless condition monitoring sensor
Nanjing High Accurate Marine Equipment Co., Ltd: Bearing wear monitor
