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Engineering and Technology

D-Index
49
Citations
10964
World Ranking
4250
National Ranking
846

Overview

Peter W. Tse is a researcher affiliated with the City University of Hong Kong in China. Their primary field of study is Engineering, with significant focus on subfields such as Mechanics of Materials, Mechanical Engineering, Civil and Structural Engineering, Ocean Engineering, and Computer Vision and Pattern Recognition.

The main research topics covered by Peter W. Tse include:

  • Ultrasonics and Acoustic Wave Propagation
  • Non-Destructive Testing Techniques
  • Structural Health Monitoring Techniques
  • Geophysical Methods and Applications
  • Thermography and Photoacoustic Techniques
  • Fatigue and fracture mechanics
  • Railway Engineering and Dynamics

Peter W. Tse has contributed to several recent research papers, including:

  • "The use of ultrasonic guided waves for the inspection of square tube structures: Dispersion analysis and numerical and experimental studies," 2020, Structural Health Monitoring
  • "Non-contact detection of railhead defects and their classification by using convolutional neural network," 2022, Optik
  • "Estimation of remaining useful life of fatigued plate specimens using Lamb wave-based nonlinearity parameters," 2020, Structural Control and Health Monitoring
  • "Methodology for circumferential localisation of defects within small-diameter concrete-covered pipes based on changing of energy distribution of non-axisymmetric guided waves," 2020, Applied Acoustics
  • "Extraction of Least-Dispersive Ultrasonic Guided Wave Mode in Rail Track Based on Floquet-Bloch Theory," 2021, Shock and Vibration

Frequent collaborators with whom Peter W. Tse has co-authored multiple works include:

  • Faeez Masurkar
  • Nitesh P. Yelve
  • Javad Rostami
  • Imran Ghafoor
  • Zhou Fang

Publication venues that have frequently featured their research are:

  • Sensors
  • Structural Health Monitoring
  • Applied Acoustics
  • Measurement
  • IEEE Transactions on Instrumentation and Measurement

Best Publications

  • A comparison study of improved Hilbert–Huang transform and wavelet transform: Application to fault diagnosis for rolling bearing

    Z.K. Peng;Peter W. Tse;F.L. Chu

  • An improved Hilbert Huang transform and its application in vibration signal analysis

    Z.K. Peng;Peter W. Tse;F.L. Chu

  • Intelligent Predictive Decision Support System for Condition-Based Maintenance

    R. C. M. Yam;P.W. Tse;L. Li;P. Tu

  • Wavelet Analysis and Envelope Detection For Rolling Element Bearing Fault Diagnosis—Their Effectiveness and Flexibilities

    Peter W. Tse;Y. H. Peng;Richard Yam

  • An enhanced Kurtogram method for fault diagnosis of rolling element bearings

    Dong Wang;Peter W. Tse;Kwok Leung Tsui

  • Application of mother wavelet functions for automatic gear and bearing fault diagnosis

    J. Rafiee;M. A. Rafiee;P. W. Tse

  • Machine fault diagnosis through an effective exact wavelet analysis

    Peter W. Tse;Wen-xian Yang;H.Y. Tam

  • The design of a new sparsogram for fast bearing fault diagnosis: Part 1 of the two related manuscripts that have a joint title as “Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement – Parts 1 and 2”

    Peter W. Tse;Dong Wang

  • Fault diagnosis of rotating machinery based on the statistical parameters of wavelet packet paving and a generic support vector regressive classifier

    Changqing Shen;Changqing Shen;Dong Wang;Fanrang Kong;Peter W. Tse

  • A novel technique for selecting mother wavelet function using an intelli gent fault diagnosis system

    J. Rafiee;P. W. Tse;A. Harifi;M. H. Sadeghi

  • Prediction of Machine Deterioration Using Vibration Based Fault Trends and Recurrent Neural Networks

    P. W. Tse;D. P. Atherton

  • A novel signal compression method based on optimal ensemble empirical mode decomposition for bearing vibration signals

    Wei Guo;Peter W. Tse

  • Use of autocorrelation of wavelet coefficients for fault diagnosis

    J. Rafiee;P.W. Tse

  • Development of an advanced noise reduction method for vibration analysis based on singular value decomposition

    Wen-Xian Yang;Wen-Xian Yang;Peter W. Tse

  • Detection of the rubbing-caused impacts for rotor–stator fault diagnosis using reassigned scalogram

    Z.K. Peng;F.L. Chu;Peter W. Tse

  • EMD-based fault diagnosis for abnormal clearance between contacting components in a diesel engine

    Yujun Li;Peter W. Tse;Xin Yang;Jianguo Yang

  • Anomaly Detection Through a Bayesian Support Vector Machine

    Vasilis A Sotiris;Peter W Tse;Michael G Pecht

  • Faulty bearing signal recovery from large noise using a hybrid method based on spectral kurtosis and ensemble empirical mode decomposition

    Wei Guo;Peter W. Tse;Alexandar Djordjevich

  • Adaptive backstepping output feedback control for a class of nonlinear fractional order systems

    Yiheng Wei;Peter W. Tse;Zhao Yao;Yong Wang

  • A comprehensive reliability allocation method for design of CNC lathes

    Yiqiang Wang;Richard C. M. Yam;Ming Jian Zuo;Peter W. Tse

  • Classification of gear faults using cumulants and the radial basis function network

    Lai Wuxing;Peter W. Tse;Zhang Guicai;Shi Tielin

Frequent Co-Authors

Dong Wang
Dong Wang Peking University
Yong Wang
Yong Wang University of Science and Technology of China
Changqing Shen
Changqing Shen Soochow University
Kwok-Leung Tsui
Kwok-Leung Tsui Virginia Tech
Richard C.M. Yam
Richard C.M. Yam City University of Hong Kong
Michael Pecht
Michael Pecht University of Maryland, College Park
Fulei Chu
Fulei Chu Tsinghua University
Zhike Peng
Zhike Peng Shanghai Jiao Tong University
Fanrang Kong
Fanrang Kong University of Science and Technology of China
Enrico Zio
Enrico Zio Polytechnic University of Milan

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