Wangyao

Wang Yao, male, doctor, postgraduate supervisor, member of the State Key Laboratory of High end Compressor and System Technology, the Key Laboratory of Engine Health Monitoring and Networking of the Ministry of Education, the Beijing Key Laboratory of High end Mechanical Equipment Health Monitoring and Self healing, the China Society of Vibration Engineering, and the China Society of Chemical Engineering. I am the main lecturer for undergraduate courses such as High Quality Undergraduate Courses in Beijing universities, including Process Equipment Control Technology and Applications, Python Language Programming, and Progress in Intelligent Monitoring Technology for Power Equipment Health. Mainly engaged in energy-saving optimization of power equipment systems, data-driven prediction of remaining life of components, decision-making for health maintenance of power equipment, and theoretical research on fault self-healing control. Multiple representative achievements have been made and engineering applications have been implemented in fields such as petroleum, chemical, natural gas transportation, and military equipment. Hosted/participated in 8 scientific research projects, published over 40 academic papers, authorized 1 international patent, authorized 14 national invention patents, applied for 8 national invention patents, and won 1 special prize for scientific and technological progress from the China Petroleum and Chemical Automation Application Association and 1 first prize for science and technology in the China Petroleum and Chemical Automation Industry. Guided undergraduate students to participate in multiple subject competitions, winning a total of 2 national second prizes, 3 third prizes, 6 provincial and ministerial level awards, and 5 school level awards. Also awarded the title of Outstanding Guidance Teacher in the 2022 China University Mechanical Engineering Innovation and Creativity Competition Zhuoran Dushun Cup Process Equipment Practice and Innovation Competition (Beijing Tianjin Hebei Regional Competition).

Mainly engaged in energy-saving optimization of power equipment systems, data-driven prediction of remaining life of components, decision-making for health maintenance of power equipment, and theoretical research on fault self-healing control. Multiple representative achievements have been made and engineering applications have been achieved in fields such as petroleum, chemical, and natural gas transportation.

Undergraduate professional courses such as Process Equipment Control Technology and Applications, Python Language Programming, and Progress in Intelligent Monitoring Technology for Power Equipment Health.