Natalia Espinoza Sepulveda - Research output - Research Explorer The University of Manchester

8 Article
3 Chapter
2 Conference contribution
2 Paper

8 results

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2025
Optimisation of critical parameters for sustainable production of graphene-enhanced cement
Yunusa-Kaltungo, A., Alsaeed, A., Espinoza Sepulveda, N. & Su, M., 10 Jan 2025, In: Construction and Building Materials. 458, 139565.
Research output: Contribution to journal › Article › peer-review

Open Access
3 Downloads (Pure)
2024
Two-step vibration-based machine learning model for the fault detection and diagnosis in rotating machine and its blind application
Espinoza Sepulveda, N. & Sinha, J., 14 May 2024, (E-pub ahead of print) In: Structural Health Monitoring.
Research output: Contribution to journal › Article › peer-review

Open Access
2021
Blind Application of Developed Smart Vibration-Based Machine Learning (SVML) Model for Machine Faults Diagnosis to Different Machine Conditions
Espinoza Sepulveda, N. & Sinha, J., 1 Jun 2021, In: Journal of Vibrational Engineering and Technologies. 9, 4, p. 587-596 10 p.
Research output: Contribution to journal › Article › peer-review

Open Access
Mathematical Validation of Experimentally Optimised Parameters Used in a Vibration-Based Machine-Learning Model for Fault Diagnosis in Rotating Machines
Espinoza Sepulveda, N. & Sinha, J., 7 Aug 2021, In: Machines. 9, 8, 15 p., 155.
Research output: Contribution to journal › Article › peer-review

Open Access
File
91 Downloads (Pure)
Robust vibration-based faults diagnosis machine learning model for rotating machines to enhance plant reliability
Espinoza Sepulveda, N. & Sinha, J., 30 Jun 2021, In: Maintenance, reliability and condition monitoring.. 1, 1, p. 1-8 8 p.
Research output: Contribution to journal › Article › peer-review

Open Access
File
121 Downloads (Pure)
Theoretical validation of earlier developed experimental rotor faults diagnosis model
Espinoza-Sepulveda, N. F. & Sinha, J. K., 2021, In: International Journal of Hydromechatronics. 4, 3, p. 295-308 14 p.
Research output: Contribution to journal › Article › peer-review
2020
Parameters Optimisation in the Vibration-based Machine Learning Model for Accurate and Reliable Faults Diagnosis in Rotating Machines
Espinoza Sepulveda, N. & Sinha, J., 23 Oct 2020, In: Machines.
Research output: Contribution to journal › Article › peer-review

Open Access
File
142 Downloads (Pure)
2018

Centralised Condition-based Maintenance Model for Rotating Machines
Sinha, J. & Espinoza Sepulveda, N., 2018, Maintenance Management, 2018-2019, p. 16-17 2 p.
Research output: Contribution to specialist publication › Article

File

1011 Downloads (Pure)