Identification of unbalance faults in rotors with unknown input observers using classical and LMI based approaches

Ramakrishnan Ambur; Raja Sangili Vadamalu; Stephan Rinderknecht

doi:10.1109/ECC.2016.7810569

Identification of unbalance faults in rotors with unknown input observers using classical and LMI based approaches

Ramakrishnan Ambur, Raja Sangili Vadamalu, Stephan Rinderknecht

Electronic, Electrical and Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

Fault diagnosis in rotating machines have been attempted by researchers with many different techniques. The common fault occurring in a rotor system is the unbalance. Different techniques exist to determine their magnitude and location in circumferential and axial direction. In this paper, an attempt is made to identify and locate unbalance faults on a rotor system using an Unknown Input Observer (UIO). Its matrices are constructed by two methods, first is a classical method by solving the algebraic Riccatti equations and other by solving a set of Linear Matrix Inequality (LMI) equations. This has the advantage of designing a stable observer without facing the problem of pole placement. Both the methods have been simulated with the model of a rotor test bench. The results are found to be accurate in a simulation environment.

Original language	English
Title of host publication	2016 European Control Conference (ECC 2016)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1904-1908
Number of pages	5
ISBN (Electronic)	978-1-5090-2591-6
ISBN (Print)	978-1-5090-2592-3 (PoD)
DOIs	https://doi.org/10.1109/ECC.2016.7810569
Publication status	Published - 9 Jan 2017
Event	2016 European Control Conference, ECC 2016 - Aalborg, Denmark Duration: 29 Jun 2016 → 1 Jul 2016

Conference

Conference	2016 European Control Conference, ECC 2016
Country/Territory	Denmark
City	Aalborg
Period	29/06/16 → 1/07/16

Keywords

Mathematical model
Rotors
Observers
Solid modeling
Fault diagnosis
Linear matrix inequalities
Fault detection

ASJC Scopus subject areas

Control and Systems Engineering
Control and Optimization

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10.1109/ECC.2016.7810569Licence: None: All rights reserved

Cite this

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title = "Identification of unbalance faults in rotors with unknown input observers using classical and LMI based approaches",

abstract = "Fault diagnosis in rotating machines have been attempted by researchers with many different techniques. The common fault occurring in a rotor system is the unbalance. Different techniques exist to determine their magnitude and location in circumferential and axial direction. In this paper, an attempt is made to identify and locate unbalance faults on a rotor system using an Unknown Input Observer (UIO). Its matrices are constructed by two methods, first is a classical method by solving the algebraic Riccatti equations and other by solving a set of Linear Matrix Inequality (LMI) equations. This has the advantage of designing a stable observer without facing the problem of pole placement. Both the methods have been simulated with the model of a rotor test bench. The results are found to be accurate in a simulation environment.",

keywords = "Mathematical model, Rotors, Observers, Solid modeling, Fault diagnosis, Linear matrix inequalities, Fault detection",

author = "Ramakrishnan Ambur and Vadamalu, {Raja Sangili} and Stephan Rinderknecht",

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pages = "1904--1908",

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publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

note = "2016 European Control Conference, ECC 2016 ; Conference date: 29-06-2016 Through 01-07-2016",

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Ambur, R, Vadamalu, RS & Rinderknecht, S 2017, Identification of unbalance faults in rotors with unknown input observers using classical and LMI based approaches. in 2016 European Control Conference (ECC 2016)., 7810569, Institute of Electrical and Electronics Engineers (IEEE), pp. 1904-1908, 2016 European Control Conference, ECC 2016, Aalborg, Denmark, 29/06/16. https://doi.org/10.1109/ECC.2016.7810569

Identification of unbalance faults in rotors with unknown input observers using classical and LMI based approaches. / Ambur, Ramakrishnan; Vadamalu, Raja Sangili; Rinderknecht, Stephan.
2016 European Control Conference (ECC 2016). Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 1904-1908 7810569.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Ambur, Ramakrishnan

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AU - Rinderknecht, Stephan

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N2 - Fault diagnosis in rotating machines have been attempted by researchers with many different techniques. The common fault occurring in a rotor system is the unbalance. Different techniques exist to determine their magnitude and location in circumferential and axial direction. In this paper, an attempt is made to identify and locate unbalance faults on a rotor system using an Unknown Input Observer (UIO). Its matrices are constructed by two methods, first is a classical method by solving the algebraic Riccatti equations and other by solving a set of Linear Matrix Inequality (LMI) equations. This has the advantage of designing a stable observer without facing the problem of pole placement. Both the methods have been simulated with the model of a rotor test bench. The results are found to be accurate in a simulation environment.

AB - Fault diagnosis in rotating machines have been attempted by researchers with many different techniques. The common fault occurring in a rotor system is the unbalance. Different techniques exist to determine their magnitude and location in circumferential and axial direction. In this paper, an attempt is made to identify and locate unbalance faults on a rotor system using an Unknown Input Observer (UIO). Its matrices are constructed by two methods, first is a classical method by solving the algebraic Riccatti equations and other by solving a set of Linear Matrix Inequality (LMI) equations. This has the advantage of designing a stable observer without facing the problem of pole placement. Both the methods have been simulated with the model of a rotor test bench. The results are found to be accurate in a simulation environment.

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KW - Observers

KW - Solid modeling

KW - Fault diagnosis

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KW - Fault detection

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Identification of unbalance faults in rotors with unknown input observers using classical and LMI based approaches

Abstract

Conference

Keywords

ASJC Scopus subject areas

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Cite this