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Personal profile


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


  • 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
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Signal analysis Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 1996 2019

Open Access
Naive Bayes Classifier

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 journalArticle

Bearings (structural)
White noise

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 journalArticle

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 journalConference article

Reciprocating compressors
Condition monitoring
Spectrum analysis
11 Citations
Bearings (structural)
Condition monitoring
Fault detection
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 typesOral presentation