Ramin Moghaddass

Assistant Professor

  • 476 Citations
20112019
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Fingerprint Dive into the research topics where Ramin Moghaddass is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Degradation Engineering & Materials Science
Condition monitoring Engineering & Materials Science
Multi-state Mathematics
Repair Engineering & Materials Science
Health Engineering & Materials Science
Maintenance Mathematics
Repairable System Mathematics
Availability Engineering & Materials Science

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Research Output 2011 2019

  • 476 Citations
  • 18 Article
  • 6 Conference contribution
  • 4 Chapter

An anomaly detection framework for dynamic systems using a Bayesian hierarchical framework

Moghaddass, R. & Sheng, S., Apr 15 2019, In : Applied Energy. 240, p. 561-582 22 p.

Research output: Contribution to journalArticle

Dynamical systems
anomaly
Sensors
sensor
Wind turbines
9 Citations (Scopus)

A hierarchical framework for smart grid anomaly detection using large-scale smart meter data

Moghaddass, R. & Wang, J., Nov 1 2018, In : IEEE Transactions on Smart Grid. 9, 6, p. 5820-5830 11 p., 7908945.

Research output: Contribution to journalArticle

Smart meters
Monitoring
Experiments

A Hybrid State Particle Filter for Failure Prognosis in Deteriorating Systems

Skordilis, E. & Moghaddass, R., Sep 11 2018, 2018 Annual Reliability and Maintainability Symposium, RAMS 2018. Institute of Electrical and Electronics Engineers Inc., Vol. 2018-January. 8463033

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Prognosis
Particle Filter
Learning systems
Health
Extreme Learning Machine

Joint optimization of ordering and maintenance with condition monitoring data

Moghaddass, R. & Ertekin, Ş., Jan 4 2018, (Accepted/In press) In : Annals of Operations Research. p. 1-40 40 p.

Research output: Contribution to journalArticle

Replacement
Condition monitoring
Lead time
Optimality
Degradation
1 Citation (Scopus)

A condition monitoring approach for real-time monitoring of degrading systems using Kalman filter and logistic regression

Skordilis, E. & Moghaddass, R., Apr 13 2017, (Accepted/In press) In : International Journal of Production Research. p. 1-18 18 p.

Research output: Contribution to journalArticle

Condition monitoring
Kalman filters
Logistics
Degradation
Monitoring