What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Electrical engineering
Qingbo He focuses on Stochastic resonance, Noise, Artificial intelligence, Pattern recognition and Fault.
His studies deal with areas such as Background noise, Control theory, Noise, Electronic engineering and Bearing as well as Stochastic resonance.
His Noise study is related to the wider topic of Signal.
His work in Wavelet and Feature extraction is related to Artificial intelligence.
His Pattern recognition research is multidisciplinary, incorporating perspectives in Feature and Condition monitoring.
His Fault study integrates concerns from other disciplines, such as Vibration, Engineering drawing and Bistability.
His most cited work include:
- Energy-Fluctuated Multiscale Feature Learning With Deep ConvNet for Intelligent Spindle Bearing Fault Diagnosis (167 citations)
- A review of stochastic resonance in rotating machine fault detection (124 citations)
- Multiscale noise tuning of stochastic resonance for enhanced fault diagnosis in rotating machines (107 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Signal, Fault, Bearing, Acoustics and Artificial intelligence.
His work on Noise, Microphone and Signal-to-noise ratio as part of general Signal study is frequently linked to Short-time Fourier transform, therefore connecting diverse disciplines of science.
In his study, which falls under the umbrella issue of Fault, Structural engineering and Resonator is strongly linked to Vibration.
He combines subjects such as Control theory, Resampling, Embedded system, Electronic engineering and Transient with his study of Bearing.
The various areas that he examines in his Control theory study include Interference and Stochastic resonance.
His Artificial intelligence research is multidisciplinary, relying on both Condition monitoring, Computer vision and Pattern recognition.
He most often published in these fields:
- Signal (32.45%)
- Fault (30.46%)
- Bearing (28.48%)
What were the highlights of his more recent work (between 2019-2021)?
- Vibration (21.85%)
- Fault (30.46%)
- Acoustics (27.15%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Vibration, Fault, Acoustics, Artificial intelligence and Condition monitoring.
His Fault research is multidisciplinary, incorporating elements of Algorithm, Signal and Feature.
His Signal research includes elements of Distortion and Re sampling.
His Acoustics research includes themes of Deconvolution, Aliasing and Signal processing.
His research in Artificial intelligence intersects with topics in Embedded system and Pattern recognition.
His study in the fields of Feature extraction and Linear discriminant analysis under the domain of Pattern recognition overlaps with other disciplines such as Electrolyte.
Between 2019 and 2021, his most popular works were:
- Fault diagnosis of rotating machines based on the EMD manifold (21 citations)
- In Situ Motor Fault Diagnosis Using Enhanced Convolutional Neural Network in an Embedded System (12 citations)
- Vibration Characteristics of Rolling Element Bearings with Different Radial Clearances for Condition Monitoring of Wind Turbine (10 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Electrical engineering
His primary areas of investigation include Vibration, Artificial intelligence, Metamaterial, Resonator and Proton exchange membrane fuel cell.
His research integrates issues of Turbine, Structural engineering, Radial clearance and Condition monitoring in his study of Vibration.
His studies link Embedded system with Artificial intelligence.
The concepts of his Metamaterial study are interwoven with issues in Vibration isolation and Bandwidth.
His Resonator research incorporates themes from Acoustics, Band gap, Encoding and Identification.
Proton exchange membrane fuel cell is integrated with Inference system, State, Neural fuzzy, Reliability engineering and Energy transformation in his research.
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