Process, Energy and Environmental Technology Station

Faculty of Engineering and the Built Environment

Websitehttps://www.uj.ac.za/faculties/engineering-the-built-environment/uj-peets

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. Our work contributes towards the following SDG(s):

SDG 2 Zero Hunger
SDG 6 Clean Water and Sanitation
SDG 7 Affordable and Clean Energy
SDG 8 Decent Work and Economic Growth
SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities
SDG 12 Responsible Consumption and Production
SDG 13 Climate Action
SDG 14 Life Below Water
SDG 17 Partnerships for the Goals

Dr Paul Adedeji
- padedejiuj.acza
- Process, Energy and Environmental Technology Station - Researcher & Research Coordinator
Person: Other (Researcher)
20182026

1279 Citations
20 h-index
35 Article
32 Conference contribution
20 Conference article
4 Review article
More
- 2 Chapter

A review of data fusion technology for fault diagnoses in wind turbine components
Owolabi, O. I., Adedeji, P. A., Olatunji, O. O. & Madushele, N., Jul 2026, In: Next Energy. 12, 100609.
Research output: Contribution to journal › Review article › peer-review

Open Access
A data-driven LSTM modelling approach for cumulative biogas yield from FFV feedstock
Olatunji, O. O., Adedeji, P. A., Van Rensburg, N. J. & Nkosinathi, N. M., 2025, IEEM 2025 - IEEE International Conference on Industrial Engineering and Engineering Management. IEEE Computer Society, p. 219-225 7 p. (IEEE International Conference on Industrial Engineering and Engineering Management).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
A hybrid framework based on Teager Energy Spectrum Correlation and Whale-optimized decision tree classifier for fault diagnosis in wind turbine drivetrain bearing
Gbashi, S. M., Olatunji, O. O., Adedeji, P. A. & Madushele, N., 2025, In: Procedia Computer Science. 274, p. 748-758 11 p.
Research output: Contribution to journal › Conference article › peer-review

Open Access
1 Citation (Scopus)

Performance enhancement in wind turbine main shafts using surface coating techniques
Adedeji, P.
14/10/25
1 item of Media coverage
Press/Media
Researchers at University of Johannesburg Have Published New Study Findings on Engineering (PSO-optimised autoencoder for fault prediction in wind turbine planet carrier bearing)
Adedeji, P. & Madushele, N.
9/06/25
1 item of Media coverage
Press/Media
University of Johannesburg Researchers Report on Findings in Engineering (Optimal feature selection for a weighted k-nearest neighbors for compound fault classification in wind turbine gearbox)
Adedeji, P. & Madushele, N.
11/03/25
1 item of Media coverage
Press/Media

Process, Energy and Environmental Technology Station

UN Sustainable Development Goals

Fingerprint

Collaborations and top research areas from the last five years

Dive into details

Dr Paul Adedeji

A review of data fusion technology for fault diagnoses in wind turbine components

A data-driven LSTM modelling approach for cumulative biogas yield from FFV feedstock

A hybrid framework based on Teager Energy Spectrum Correlation and Whale-optimized decision tree classifier for fault diagnosis in wind turbine drivetrain bearing

Performance enhancement in wind turbine main shafts using surface coating techniques

Researchers at University of Johannesburg Have Published New Study Findings on Engineering (PSO-optimised autoencoder for fault prediction in wind turbine planet carrier bearing)

University of Johannesburg Researchers Report on Findings in Engineering (Optimal feature selection for a weighted k-nearest neighbors for compound fault classification in wind turbine gearbox)

Process, Energy and Environmental Technology Station

UN Sustainable Development Goals

Fingerprint

Collaborations and top research areas from the last five years

Profiles

Dr Paul Adedeji

Research output

A review of data fusion technology for fault diagnoses in wind turbine components

A data-driven LSTM modelling approach for cumulative biogas yield from FFV feedstock

A hybrid framework based on Teager Energy Spectrum Correlation and Whale-optimized decision tree classifier for fault diagnosis in wind turbine drivetrain bearing

Press/Media

Performance enhancement in wind turbine main shafts using surface coating techniques

Researchers at University of Johannesburg Have Published New Study Findings on Engineering (PSO-optimised autoencoder for fault prediction in wind turbine planet carrier bearing)

University of Johannesburg Researchers Report on Findings in Engineering (Optimal feature selection for a weighted k-nearest neighbors for compound fault classification in wind turbine gearbox)