What is he best known for?
The fields of study he is best known for:
- Optics
- Electrical engineering
- Artificial intelligence
His main research concerns Optics, Acoustics, Digital imaging, Flow measurement and Coal.
Yong Yan has included themes like Visualization, Temperature measurement, Spectral density and Iterative reconstruction in his Optics study.
His research links Cross-correlation with Acoustics.
His Digital imaging study combines topics from a wide range of disciplines, such as Digital image processing, Vision based, Systems engineering and Particle size.
The Flow measurement study combines topics in areas such as Pipeline transport, Electronic engineering, Pipe flow and Two-phase flow.
His Coal research integrates issues from Ignition system, Mineralogy and Adiabatic flame temperature.
His most cited work include:
- Mass flow measurement of bulk solids in pneumatic pipelines (232 citations)
- Velocity measurement of pneumatically conveyed solids using electrodynamic sensors (176 citations)
- Impact of co-firing coal and biomass on flame characteristics and stability (107 citations)
What are the main themes of his work throughout his whole career to date?
Acoustics, Electronic engineering, Digital imaging, Mechanics and Flow measurement are his primary areas of study.
The various areas that Yong Yan examines in his Acoustics study include Particle size and Signal, Signal processing.
His Digital imaging research includes themes of Mechanical engineering, Digital image processing and Optics.
His Optics research is multidisciplinary, incorporating elements of Temperature measurement and Iterative reconstruction.
In general Mechanics, his work in Two-phase flow, Flow and Particle velocity is often linked to Electric charge linking many areas of study.
The concepts of his Flow measurement study are interwoven with issues in Pipeline transport, Mass flow rate, Mass flow and Pipe flow.
He most often published in these fields:
- Acoustics (29.81%)
- Electronic engineering (15.49%)
- Digital imaging (11.97%)
What were the highlights of his more recent work (between 2016-2021)?
- Acoustics (29.81%)
- Approximation error (7.75%)
- Mechanics (12.91%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Acoustics, Approximation error, Mechanics, Signal and Mass flow rate.
His Acoustics research is multidisciplinary, relying on both Frequency response and Signal processing.
His studies deal with areas such as Fluidized bed and Probability density function as well as Mechanics.
When carried out as part of a general Signal research project, his work on Noise is frequently linked to work in Charge, therefore connecting diverse disciplines of study.
Yong Yan has researched Mass flow rate in several fields, including Support vector machine, Flow, Flow conditions, Mass flow and Particle velocity.
The various areas that Yong Yan examines in his Flow conditions study include Thermal mass flow meter, Flow measurement and Metering mode.
Between 2016 and 2021, his most popular works were:
- Application of soft computing techniques to multiphase flow measurement: A review (47 citations)
- Application of soft computing techniques to multiphase flow measurement: A review (47 citations)
- Non-intrusive characterisation of particle cluster behaviours in a riser through electrostatic and vibration sensing (21 citations)
In his most recent research, the most cited papers focused on:
- Electrical engineering
- Optics
- Mechanical engineering
His primary areas of investigation include Approximation error, Acoustics, Mechanics, Fluidized bed and Mass flow rate.
His Acoustics research incorporates elements of Polytetrafluoroethylene, Electronic engineering and Dielectric.
His biological study spans a wide range of topics, including Electrostatic induction, Probability density function and Analytical chemistry.
His Fluidized bed research is multidisciplinary, incorporating perspectives in Scientific method and Process engineering.
His work is dedicated to discovering how Process engineering, Mixing are connected with Sensor array, Waste management, Sensitivity and Signal and other disciplines.
His research in Mass flow rate focuses on subjects like Mass flow, which are connected to Flow, Flow measurement, Porous medium, Measurement uncertainty and Two-phase flow.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
