Research Output per year
Personal profile
Biography
Fengshou Gu is one of our experts in the fields of vibro-acoustics analysis and machinery diagnosis, with over 20 years of research experience. He is the author of over 200 technical and professional publications in machine dynamics, signal processing, tribology dynamic responses, condition monitoring and related fields. He has been involved in vibro-acoustics characterisation related to internal combustion engines, reciprocating compressors, centrifugal pumps, electric motors, hydraulic power systems, gearboxes, mechnical seals and rolling/journal bearings. He has experience in system modeling, various physical parameter measurements, and advanced signal processing techniques including time-frequency analysis, modulation signal bispectra, wavelet transforms, neural network algorithms and statistical analysis.
Research Expertise and Interests
- Vibro-impact modelling;
- Machine modelling and fault simulation;
- Neural network modelling;
- Time-frequency and time-scale analysis;
- Modulation and demodulation analysis;
- Complex vibro-acoustic source identification;
- Acoustic condition monitoring;
- Tribo-dynamics and lubrication
- Intelligent monitoring system;
- Powerless and wireless data sensing and transfer
Research Degree Supervision
Click Here to see all postgraduate research opportunities with Professor Fengshou Gu
Keywords
- Machine modelling
- Diagnostics
- Vibro-impact modelling
- signal processing
- Machine Dynamics
- Tribology
Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
- 5 Similar Profiles
Condition monitoring
Engineering & Materials Science
Bearings (structural)
Engineering & Materials Science
Failure analysis
Engineering & Materials Science
Fault detection
Engineering & Materials Science
Monitoring
Engineering & Materials Science
Engines
Engineering & Materials Science
Reciprocating compressors
Engineering & Materials Science
Signal analysis
Engineering & Materials Science
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 1996 2019
An Approach to Reducing Input Parameter Volume for Fault Classifiers
Smith, A., Gu, F. & Ball, A., 23 Jan 2019, In : International Journal of Automation and Computing. 14 p.Research output: Contribution to journal › Article
Open Access
Fault
Classifiers
Classifier
Naive Bayes Classifier
Harmonic
Extraction of the largest amplitude impact transients for diagnosing rolling element defects in bearings
Hu, L., Zhang, L., Gu, F., Hu, N. & Ball, A., 1 Feb 2019, In : Mechanical Systems and Signal Processing. 116, p. 796-815 20 p.Research output: Contribution to journal › Article
Bearings (structural)
Defects
Tachometers
White noise
Demodulation
A Gas Path Fault Contribution Matrix for Marine Gas Turbine Diagnosis Based on a Multiple Model Fault Detection and Isolation Approach
Yang, Q., Li, S., Cao, Y., Gu, F. & Smith, A., 1 Dec 2018, In : Energies. 11, 12, p. 1-21 21 p., 3316.Research output: Contribution to journal › Article
Open Access
Fault Detection and Isolation
Gas Turbine
Multiple Models
Fault detection
Gas turbines
An investigation into vibration response for condition monitoring of reciprocating compressor based on modulation signal spectrum analysis
Haba, U., Brethee, K., Hassin, O., Gu, F. & Ball, A. D., Jul 2018, In : International Journal of COMADEM. 21, 3, p. 31-37 7 p.Research output: Contribution to journal › Conference article
Reciprocating compressors
Condition monitoring
Spectrum analysis
Modulation
Compressors
A robust detector for rolling element bearing condition monitoring based on the modulation signal bispectrum and its performance evaluation against the Kurtogram
Tian, X., Xi Gu, J., Rehab, I., Abdalla, G. M., Gu, F. & Ball, A. D., 1 Feb 2018, In : Mechanical Systems and Signal Processing. 100, p. 167-187 21 p.Research output: Contribution to journal › Article
Bearings (structural)
Condition monitoring
Fault detection
Modulation
Frequency bands
Activities 2015 2015
- 1 Oral presentation
A Robust Fault Detection Method of Rolling Bearings Using Modulation Signal Bispectrum Analysis
Fengshou Gu (Contributor to Paper or Presentation), Andrew Ball (Contributor to Paper or Presentation), Xiange Tian (Speaker), Ibrahim.A.M Rehab (Speaker), Gaballa Abdalla (Speaker)1 Dec 2015
Activity: Talk or presentation types › Oral presentation