What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Mechanical engineering
- Electrical engineering
Peter W. Tse mainly focuses on Algorithm, Wavelet, Fault, Vibration and Signal processing.
As a part of the same scientific study, Peter W. Tse usually deals with the Algorithm, concentrating on Electronic engineering and frequently concerns with Hilbert–Huang transform and Diesel engine.
His Wavelet study integrates concerns from other disciplines, such as Control theory, Condition monitoring and Bearing.
The concepts of his Fault study are interwoven with issues in Vibration based, Recurrent neural network, Expert system and Spare part.
His Vibration research is multidisciplinary, incorporating perspectives in Singular value decomposition, Singular spectrum analysis, Mathematical optimization, Entropy and Noise reduction.
His Signal processing research incorporates elements of Artificial intelligence and Pattern recognition.
His most cited work include:
- A comparison study of improved Hilbert–Huang transform and wavelet transform: Application to fault diagnosis for rolling bearing (582 citations)
- An improved Hilbert Huang transform and its application in vibration signal analysis (345 citations)
- Wavelet Analysis and Envelope Detection For Rolling Element Bearing Fault Diagnosis—Their Effectiveness and Flexibilities (333 citations)
What are the main themes of his work throughout his whole career to date?
Acoustics, Fault, Algorithm, Vibration and Signal are his primary areas of study.
His research in the fields of Guided wave testing and Ultrasonic sensor overlaps with other disciplines such as Materials science.
His work carried out in the field of Fault brings together such families of science as Bearing and Artificial intelligence.
His studies in Algorithm integrate themes in fields like Electronic engineering and Wavelet.
His Vibration research is multidisciplinary, incorporating elements of Blind equalization, Control theory, Impeller, Slurry pump and Kurtosis.
His works in Signal processing, Hilbert–Huang transform and Noise are all subjects of inquiry into Signal.
He most often published in these fields:
- Acoustics (21.24%)
- Fault (21.24%)
- Algorithm (17.62%)
What were the highlights of his more recent work (between 2017-2021)?
- Acoustics (21.24%)
- Materials science (13.99%)
- Nonlinear system (9.84%)
In recent papers he was focusing on the following fields of study:
Peter W. Tse spends much of his time researching Acoustics, Materials science, Nonlinear system, Lamb waves and Rayleigh wave.
His work on Guided wave testing and Ultrasonic sensor as part of general Acoustics study is frequently connected to Nondestructive testing, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Ultrasonic sensor study combines topics from a wide range of disciplines, such as Wavelet and Finite element method.
His Nonlinear system research integrates issues from Amplitude, Mechanics and Harmonics.
His Signal study incorporates themes from Control theory, Condition monitoring and Spectrogram.
His Sample entropy research includes elements of Fault and Algorithm.
Between 2017 and 2021, his most popular works were:
- Order spectrogram visualization for rolling bearing fault detection under speed variation conditions (27 citations)
- Modeling of a horizontal asymmetric U-shaped vibration-based piezoelectric energy harvester (U-VPEH) (23 citations)
- Kurtogram manifold learning and its application to rolling bearing weak signal detection (22 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mechanical engineering
- Statistics
Peter W. Tse spends much of his time researching Acoustics, Lamb waves, Nonlinear system, Materials science and Algorithm.
Peter W. Tse has researched Acoustics in several fields, including Energy, Electric potential energy, Resonance, Mechanical energy and Harmonic balance.
His Lamb waves research is multidisciplinary, relying on both Reflection, Waveform, Longitudinal wave and Second-harmonic generation.
His research in Nonlinear system intersects with topics in Amplitude, Frequency band, Mathematical analysis and Vibration.
His research integrates issues of Fault, Fault recognition, Permutation entropy and Support vector machine in his study of Algorithm.
His work deals with themes such as Instantaneous phase, Control theory, Condition monitoring and Spectrogram, which intersect with Fault.
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