A fault detection scheme for ship propulsion systems using randomized algorithm techniques. (December 2018)

• Record Type: Journal Article
• Authors: Zhou, Jing; Yang, Ying; Zhao, Zhengen; Ding, Steven X.
• Is Part Of: Control engineering practice. Volume 81(2018)
• Page Start: 65
• Page End: 72
• Publication Date: 2018-12
• Subjects: Fault detection -- Coprime factorization -- Randomized algorithm -- Ship propulsion system; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2018.09.008
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: This paper studies the fault detection problem in ship propulsion systems based on randomized algorithms. The nominal propulsion system model, model with uncertainties and model with additive and multiplicative faults are first addressed in the form of normalized left coprime factorization (LCF), respectively. The K -gap metric is then introduced to measure how far the system deviates from the nominal operation. To reduce the conservatism in the norm-based threshold, a threshold setting law and the estimation of fault detection rate (FDR) are formulated on the probabilistic assumption of uncertain and faulty parameters. The simulation results on the ship propulsion system show that the randomized technique is an efficient solution to deal with the fault detection issues. Highlights: The ship propulsion system is modeled by normalized left coprime factorization. The K-gap metric is adopted to measure the difference between two systems. The probabilistic properties of uncertain and faulty parameters are known previously. The threshold setting and FDR estimation are achieved by randomized algorithms.