What is he best known for?
The fields of study he is best known for:
- Mechanical engineering
- Electrical engineering
- Statistics
Fengshou Gu mainly focuses on Condition monitoring, Diesel engine, Signal processing, Electronic engineering and Fault detection and isolation.
His Condition monitoring research includes themes of Acoustics, Vibration, Reliability engineering, Noise and Control engineering.
His studies deal with areas such as Waste management, Biofuel and Diesel fuel as well as Diesel engine.
His research on Electronic engineering often connects related topics like Signal.
His Fault detection and isolation study introduces a deeper knowledge of Fault.
His research investigates the connection between Fault and topics such as Induction motor that intersect with problems in Crankshaft.
His most cited work include:
- A review of numerical analysis of friction stir welding (251 citations)
- Prediction Models for Density and Viscosity of Biodiesel and their Effects on Fuel Supply System in CI Engines (143 citations)
- The measurement of instantaneous angular speed (131 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Condition monitoring, Fault, Vibration, Fault detection and isolation and Control theory.
His Condition monitoring research integrates issues from Acoustics, Control engineering, Automotive engineering, Artificial intelligence and Pattern recognition.
Fengshou Gu works mostly in the field of Acoustics, limiting it down to topics relating to Diesel engine and, in certain cases, Internal combustion engine, as a part of the same area of interest.
His work in Fault addresses issues such as Signal, which are connected to fields such as Electronic engineering and Bispectrum.
He interconnects Lubrication, Mechanical engineering, Structural engineering, Frequency domain and Nonlinear system in the investigation of issues within Vibration.
His study in Control theory is interdisciplinary in nature, drawing from both Induction motor and Rotor.
He most often published in these fields:
- Condition monitoring (32.60%)
- Fault (28.57%)
- Vibration (26.16%)
What were the highlights of his more recent work (between 2019-2021)?
- Fault (28.57%)
- Vibration (26.16%)
- Condition monitoring (32.60%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Fault, Vibration, Condition monitoring, Control theory and Bearing.
His work carried out in the field of Fault brings together such families of science as Acoustics and Signal, Noise.
His research in Signal intersects with topics in Bispectrum, Algorithm and Feature extraction.
His Vibration research also works with subjects such as
- Structural engineering that intertwine with fields like Torsional vibration,
- Automotive engineering together with Cylinder.
His Condition monitoring study combines topics in areas such as Lubrication and Convolutional neural network.
The concepts of his Control theory study are interwoven with issues in Induction motor, Modal and Rotor.
Between 2019 and 2021, his most popular works were:
- Response analysis of an accelerating unbalanced rotating system with both random and interval variables (28 citations)
- Vibration Characteristics of Rolling Element Bearings with Different Radial Clearances for Condition Monitoring of Wind Turbine (10 citations)
- Online Bearing Clearance Monitoring Based on an Accurate Vibration Analysis (10 citations)
In his most recent research, the most cited papers focused on:
- Mechanical engineering
- Electrical engineering
- Artificial intelligence
His primary areas of investigation include Control theory, Vibration, Fault, Bearing and Bispectrum.
His studies in Control theory integrate themes in fields like Modal, Parametric statistics, Interval, Optimal maintenance and Rotor.
His Vibration research is multidisciplinary, incorporating elements of Turbine, Finite element method, Condition monitoring and Nonlinear system.
His biological study spans a wide range of topics, including Reciprocating compressor and Dual detector.
His Bispectrum study combines topics from a wide range of disciplines, such as Background noise, Noise, Modulation, Fault detection and isolation and Algorithm.
In his study, Signal processing is strongly linked to Demodulation, which falls under the umbrella field of Algorithm.
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