Yanzhaoli头像

Yanzhaoli

Research direction: acoustic signal acquisition and processing, condition monitoring, fault diagnosis

Education: PhD

  • Department: College of Mechanical and Electrical Engineering
  • ORCID: 0000-0002-8708-9954
  • DBLP:

10 Access

  • Email: yanzl@mail.buct.edu.cn
  • Office : Technology Building

Introduction

Yan Zhaoli is a professor at the School of Electromechanical Engineering, Beijing University of Chemical Technology, Beijing, China. He worked at the Institute of Acoustics, Chinese Academy of Sciences (CAS) from June 2004 to June 2024, and received his Ph.D. degree in Physics from the Institute of Physics, Chinese Academy of Sciences. His undergraduate degree from Beijing University of Technology. He has long been engaged in the research of acoustic signal acquisition and processing, equipment condition monitoring and fault diagnosis, and other related fields of industrial intelligence. He has presided over and participated in a number of national and Enterprise projects; the developed ship noise monitoring system has been equipped with China's Navy. The crack monitoring instrument has been promoted in an industry, and small quantity produection have been completed. He has published more than sixty papers, and applied for fifteen national invention patents. He has served as a part-time professor of the China University of Petroleum (Beijing), an expert of the Army Equipment Department's man-portable equipment pre-study project, and an expert of the High Speed Railway Joint Fund. He has been the director of China Instrument Society and the chairman of the 37th International Noise Control Engineering Conference.

Education

Work Experience

Social Position

Social Activities

Research

n  Condition monitoring of running machinery and equipment

ü  Carrying out research on acoustic monitoring of the health status of hydropower station equipment based on industrial internet.

ü  Developed first set of distributed noise and vibration intelligent monitoring system for ships, realise real-time intelligent monitoring of noise and operation status of typical rotating equipment, and identify abnormal noise sources.

ü  Proposed an active transient velocity detection method of the flow field to achieve real-time analysis of fluid cavitation by continuous demodulation of ultrasonic carrier signals.

ü  Carried out a vibration-based high-speed bearing running condition assessment study;

ü  Carried out an acoustic monitoring method for underframe rattles of rail vehicles in cooperation with CNR;

n  Structural health monitoring of stressed structures

ü  Investigated the application of generalised acoustic emission technology in structural health monitoring to solve the industry crack monitoring problem;

ü  Studied the acoustic detection method of railway tunnel lining cavities;

ü  Proposed and investigated a new method of acoustic injection for leakage detection and localisation of buried gas pipelines;

ü  Studied the application of ultrasonic guided wave in rail crack monitoring.


Teaching

Postgraduates

Funding

Vertical Project

Horizontal Project

Publications

(1)     Acoustic tunnel lining cavity detection using cepstral coefficients with optimized filter bank, Measurement Science and Technology, 2024SCI

(2)     Design of frequency-invariant uniform concentric circular arrays with first-order directional microphones, signal processing, 2024SCI

(3)     Acoustic injection method based on weak echo signals for leak detection and localization in gas pipelines, Applied Acoustics, 2023SCI

(4)     Identification of Pipeline Leak Sizes Based on Chaos-Gray Wolf-Support Vector Machine, IEEE Sensors Journal, 2023SCI

(5)     A Multi-scale Attention Residual Network for End-to-End Environmental Sound Classification, Neural Processing Letters, 2023SCI

(6)     Acoustic Tunnel Lining Detection with optimized support vector machine, UNIfied Conference of DAMAS, InCoME and TEPEN Conferences, 2023.8

(7)     A novel nondestructive testing method for honeycomb structure using acoustic band gap, Mechanical Systems and Signal Processing, 2023 SCI

(8)     Abnormal Noise Monitoring of Subway Vehicles Based on Combined Acoustic Features, Applied Acoustics, 2022SCI

(9)     An Intelligent Monitoring Network for Detection of Cracks in Anvils of High-Press Apparatus, sensors, 2018SCI

(10)Pipeline leak detection based on improved stochastic resonance, 25th International Congress on Sound and Vibration 2018 (ICSV 2018), 2018 EI

(11)Use of Acoustic Emission and Pattern Recognition for Crack Detection of a Large Carbide Anvil, sensors, 2018SCI


Awards

Patent

Honor Reward

Admissions Information