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Mustafa, Mohammed Obaid
Publications (10 of 24) Show all publications
Mustafa, M. O., Nikolakopoulos, G., Gustafsson, T. & Kominiak, D. (2016). A Fault Detection Scheme Based on Minimum Uncertainty Bounds Violation for Broken Rotor Bars in Induction Motors (ed.). Paper presented at . Control Engineering Practice, 48, 63-77
Open this publication in new window or tab >>A Fault Detection Scheme Based on Minimum Uncertainty Bounds Violation for Broken Rotor Bars in Induction Motors
2016 (English)In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 48, p. 63-77Article in journal (Refereed) Published
Abstract [en]

In this article, a novel method for broken bars fault detection in the case of three-phase induction motors and under different payloads will be presented and experimentally evaluated. In the presented approach, the cases of a partially or full broken rotor bars is being also considered, caused by: a) drilling 4mm and 8mm out of the $13$mm thickness of the same rotor bar, and b) fully drilled (13mm) one, two and three broken bars. The proposed fault detection method is based on the Set Membership Identification (SMI) technique and a novel proposed minimum boundary violation fault detection scheme, applied on the identified motor's parameters. The system identification procedure is being carried out on the simplified equivalent model of the induction motor, during the steady-state operation (non-fault case), while at the same time the proposed scheme is able to calculate on-line the corresponding safety bounds for the identified variables, based on a priori knowledge of the measuring corrupting noise (worst case encountered). The efficiency, the robustness and the overall performance of the established fault detection scheme is being extensively evaluated in multiple experimental studies and under various time instances of faults and load conditions.

Keywords
Information technology - Automatic control, Informationsteknik - Reglerteknik
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-11834 (URN)10.1016/j.conengprac.2015.12.008 (DOI)000370906700006 ()2-s2.0-84953383905 (Scopus ID)ada0a4d1-9bf7-4529-851f-9f0defb39235 (Local ID)ada0a4d1-9bf7-4529-851f-9f0defb39235 (Archive number)ada0a4d1-9bf7-4529-851f-9f0defb39235 (OAI)
Note
Validerad; 2016; Nivå 2; 20150115 (mohoba)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Mustafa, M. O., Varagnolo, D., Nikolakopoulos, G. & Gustafsson, T. (2016). Detecting broken rotor bars in induction motors with model-based support vector classifiers (ed.). Paper presented at . Control Engineering Practice, 52, 15-23
Open this publication in new window or tab >>Detecting broken rotor bars in induction motors with model-based support vector classifiers
2016 (English)In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 52, p. 15-23Article in journal (Refereed) Published
Abstract [en]

We propose a methodology for testing the sanity of motors when both healthy and faulty data are unavailable. More precisely, we consider a model-based Support Vector Classification (SVC) method for the detection of broken bars in three phase asynchronous motors at full load conditions, using features based on the spectral analysis of the stator's steady state current (more specifically, the amplitude of the lift sideband harmonic and the amplitude at fundamental frequency). We diverge from the mainstream focus on using SVCs trained from measured data, and instead derive a classifier that is constructed entirely using theoretical considerations. The advantage of this approach is that it does not need training steps (an expensive, time consuming and often practically infeasible task), i.e., operators are not required to have both healthy and faulty data from a system for checking it. We describe what are the theoretical properties and fundamental limitations of using model based SVC methodologies, provide conditions under which using SVC tests is statistically optimal, and present some experimental results to prove the effectiveness of the suggested scheme.

Keywords
Information technology - Signal processing, Technology - Electrical engineering, electronics and photonics, Informationsteknik - Signalbehandling, Teknikvetenskap - Elektroteknik, elektronik och fotonik
National Category
Control Engineering
Research subject
Control Engineering; Smart machines and materials (AERI); Intelligent industrial processes (AERI)
Identifiers
urn:nbn:se:ltu:diva-13826 (URN)10.1016/j.conengprac.2016.03.019 (DOI)000377740300002 ()2-s2.0-84963631019 (Scopus ID)d1db56af-3d1e-4740-97d3-06aa8f9187a7 (Local ID)d1db56af-3d1e-4740-97d3-06aa8f9187a7 (Archive number)d1db56af-3d1e-4740-97d3-06aa8f9187a7 (OAI)
Projects
Fault Detection in Bearings, Feldetektering i elektriska maskiner
Note
Validerad; 2016; Nivå 2; 20160408 (damvar)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Georgoulas, G., Nikolakopoulos, G. & Mustafa, M. O. (2015). A Data Fusion Approach to Bearing Fault Detection and Diagnosis (ed.). In: (Ed.), (Ed.), IEEE International Conference on Power Engineering, Energy and Electrical Drives, POWERENG 2015, May 11-13, Riga, Latvia, 2015: (pp. 109-113). Piscataway, NJ: IEEE Communications Society
Open this publication in new window or tab >>A Data Fusion Approach to Bearing Fault Detection and Diagnosis
2015 (English)In: IEEE International Conference on Power Engineering, Energy and Electrical Drives, POWERENG 2015, May 11-13, Riga, Latvia, 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 109-113Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a data fusion approach for the diagnosis of bearing faults under different seeded fault scenarios. The approach is based on the extraction of three simple and intuitive features that fuse the information that comes from two accelerometers placed at two different sites of the test bed. The analysis shows that in the case of the occurrence of a fault even in an early stage the “footprint” left at the scatter plot of the measurements coming from the two accelerometers can effectively turned into features/descriptors by simple statistical measures such as the elements of the covariance matrix. Those features when fed to a k-nearest neighbor classifier or an ensemble of one class detectors can lead to a remarkably high detection/diagnostic performance.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2015
Keywords
Information technology - Automatic control, Informationsteknik - Reglerteknik
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-28091 (URN)1bf7727f-a780-4543-a885-b69d6206aa3e (Local ID)1bf7727f-a780-4543-a885-b69d6206aa3e (Archive number)1bf7727f-a780-4543-a885-b69d6206aa3e (OAI)
Note
Godkänd; 2015; 20150419 (geonik)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved
Mustafa, M. O., Nikolakopoulos, G. & Gustafsson, T. (2015). Broken Bars Fault Diagnosis Based on Uncertainty Bounds Violation for Three Phase Induction Motors (ed.). International Studies in Religion and Society, 304-325
Open this publication in new window or tab >>Broken Bars Fault Diagnosis Based on Uncertainty Bounds Violation for Three Phase Induction Motors
2015 (English)In: International Studies in Religion and Society, ISSN 1530-1311, E-ISSN 2050-7038, p. 304-325Article in journal (Refereed) Published
Abstract [en]

In this article, a novel fault diagnosis scheme, based on uncertainty bounds violation, is being presented for the case of broken bars in squirrel–cage Three Phase Induction Motors. The fault diagnosis is done in two steps. Firstly the parameters of the healthy induction motor are identified using a set member- ship identification (SMI) approach, where corresponding uncertainty bounds are also being provided. Secondly the proposed uncertainty bounds violation conditions for the fault diagnosis are evaluated on–line, on the converged identified model, during a sliding time window. Multiple simulation results are presented that demonstrate the efficacy of the proposed scheme towards fault detection and diagnosis among different number of broken bars.

Keywords
Information technology - Automatic control, Informationsteknik - Reglerteknik
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-11096 (URN)10.1002/etep.1843 (DOI)000348497600007 ()2-s2.0-84921326058 (Scopus ID)a00abceb-8bff-42b4-8bc3-c8fdd4147b46 (Local ID)a00abceb-8bff-42b4-8bc3-c8fdd4147b46 (Archive number)a00abceb-8bff-42b4-8bc3-c8fdd4147b46 (OAI)
Projects
Feldetektering i elektriska maskiner
Note

Validerad; 2015; Nivå 2; Bibliografisk uppgift: Tidskriften tidigare utgiven under namnet "European Transactions on Electrical Power’’; 20131024 (geonik)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-08-16Bibliographically approved
Mustafa, M. O., Nikolakopoulos, G. & Georgoulas, G. (2015). Fault classification of Broken Rotor Bars in Induction Motors Based on Envelope Current Analysis (ed.). In: (Ed.), (Ed.), IEEE 13th International Conference on Industrial Informatics (INDIN), 2015: Cambridge, United Kingdom, 22-24 July 2015. Paper presented at IEEE International Conference on Industrial Informatics : 22/07/2015 - 24/07/2015 (pp. 795-800). Piscataway, NJ: IEEE Communications Society, Article ID 7281838.
Open this publication in new window or tab >>Fault classification of Broken Rotor Bars in Induction Motors Based on Envelope Current Analysis
2015 (English)In: IEEE 13th International Conference on Industrial Informatics (INDIN), 2015: Cambridge, United Kingdom, 22-24 July 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 795-800, article id 7281838Conference paper, Published paper (Refereed)
Abstract [en]

In this article a method for the fault classification of one, two, and three broken bars in induction motors under full load condition is presented. The proposed methodology is based on the current envelope analysis, which in the past has been also widely utilized in analyzing the rotor faults at low slips. As it will be presented, the information obtained from the envelope current is valuable in manifesting and validating the presence of fault, since the current envelope and its characteristics often contains important information about the existence of a fault and the corresponding fault type. The proposed method mainly focuses on the case of steady-state operation under full load. In the established fault detection scheme, from the stator’s current six statistical features are extracted and utilized for the fault detection and classification. In more detail, three classifiers, a linear, a quadratic and a Nearest Neighbor have been investigated for the diagnosis of broken rotor bar faults of an induction motor. The presented approach have manifested promising results using experimental data.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2015
Keywords
Information technology - Automatic control, Informationsteknik - Reglerteknik
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-37863 (URN)10.1109/INDIN.2015.7281838 (DOI)84949499664 (Scopus ID)c069ac96-4859-40f9-92b7-912d1abd81d0 (Local ID)9781479966493 (ISBN)c069ac96-4859-40f9-92b7-912d1abd81d0 (Archive number)c069ac96-4859-40f9-92b7-912d1abd81d0 (OAI)
Conference
IEEE International Conference on Industrial Informatics : 22/07/2015 - 24/07/2015
Note
Validerad; 2016; Nivå 1; 20150419 (geonik)Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2017-11-25Bibliographically approved
Mustafa, M. O. (2015). On Fault Detection, Diagnosis and Monitoring for Induction Motors (ed.). (Doctoral dissertation). Paper presented at . : Luleå tekniska universitet
Open this publication in new window or tab >>On Fault Detection, Diagnosis and Monitoring for Induction Motors
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In this thesis, multiple methods and different approaches have been established and evaluated successfully, in order to detect and diagnose the faults of induction motors (IMs). The aim of this thesis is to present novel fault detection and isolation methods for the case of induction machines that would have the merit to be implemented online and being characterized by specific novel capabilities, when compared with the existing techniques. More specifically both the cases of model based and modeless (model free) fault detection and isolation methods will be considered. The proposed methods have been based on: a) Set Membership Identification, Uncertainty Bounds Violation and a minimum uncertainty boundary violation detection schemes, for multiple cases of broken bars under different load conditions and short circuits in stator windings detection having the merit of exact and fast fault detection an easy straight forward fault isolation and capabilities, b) model based Support Vector Classification for the detection of broken bars under full load conditions, using features based on the spectral analysis of the steady state stator's current, without the need of training steps (an expensive, time consuming and often practically infeasible task) and existing of a priori data sets of healthy and faulty cases, c) fault classification based on robust linear discrimination scheme in the model free case and based on novel extracted features for both short circuit and broken bar, and d) fault detection based on Principal Component Analysis (PCA) fault/anomaly detector in time domain for detecting broken rotor bars under full load conditions, e) fault classification technique for bearings based on a novel Minimum Volume Ellipsoid method for feature extraction. One of additional major contributions of this thesis is the fact that especially for the cases of broken bars, and short circuit in stator windings. All the proposed methodologies have been extensively evaluated in multiple experiments and in multiple payloads and thus it has been realistically demonstrated the merits of all the proposed fault detection and isolation schemes. Furthermore, the obtained results suggest that these novel representations can be used within condition monitoring systems.

Place, publisher, year, edition, pages
Luleå tekniska universitet, 2015
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Keywords
Model based fault detection and diagnosis, Model free fault detection, Set Membership Identification (SMI), Uncertainty Bounds Violation Method, Model based Support Vector Classification, Linear and Nonlinear Classification, Minimum Volume Ellipsoid method, Broken Rotor Bars, Faults of Induction Motors, Three phase induction motor, Information technology - Automatic control, Informationsteknik - Reglerteknik
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-18781 (URN)a4cf3616-c181-4543-b7b8-46c69a0992b8 (Local ID)978-91-7583-226-5 (ISBN)978-91-7583-227-2 (ISBN)a4cf3616-c181-4543-b7b8-46c69a0992b8 (Archive number)a4cf3616-c181-4543-b7b8-46c69a0992b8 (OAI)
Note
Godkänd; 2015; 20150120 (mohoba); Tillkännagivande disputation 2015-02-24 Nedanstående person kommer att disputera för avläggande av teknologie doktorsexamen. Namn: Mohammed Obaid Mustafa Ämne: Reglerteknik/Automatic Control Avhandling: On Fault Detection, Diagnosis and Monitoring for Induction Motors Opponent: Professor Mohamed El Hachemi Benbouzid, Laboratoire Brestois de Mécanique et des Systèmes, University of Brest, Brest, France Ordförande: Professor Thomas Gustafsson, Avd för signaler och system, Institutionen för system- och rymdteknik, Luleå tekniska universitet Tid: Tisdag den 17 mars kl 09.30 Plats: A109, Luleå tekniska universitetAvailable from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved
Mustafa, M. O., Georgoulas, G. & Nikolakopoulos, G. (2015). Principal Component Analysis Anomaly Detector for Rotor Broken Bars (ed.). In: (Ed.), (Ed.), IECON 2014: 40th Annual Conference of the IEEE Industrial Electronics Society, Dallas, TX, USA , Oct. 29 2014 - Nov. 1 2014. Paper presented at Annual Conference of the IEEE Industrial Electronics Society : 29/10/2014 - 01/11/2014 (pp. 3462-3467). Piscataway, NJ: IEEE Communications Society
Open this publication in new window or tab >>Principal Component Analysis Anomaly Detector for Rotor Broken Bars
2015 (English)In: IECON 2014: 40th Annual Conference of the IEEE Industrial Electronics Society, Dallas, TX, USA , Oct. 29 2014 - Nov. 1 2014, Piscataway, NJ: IEEE Communications Society, 2015, p. 3462-3467Conference paper, Published paper (Refereed)
Abstract [en]

In this article a method for the detection of broken rotor bars in asynchronous machines operating under full load is presented. Unlike most Motor Current Signature Analysis (MCSA) approaches, which operate in the frequency domain, our method operates in the time domain. The scheme is based on the use of a Principal Component Analysis (PCA) fault/anomaly detector applied on the three stator currents to calculate the Q statistic which is employed for detecting a fault. The efficiency of the proposed scheme was experimentally evaluated using different fault severity levels, ranging from 1/4 of a broken bar to three broken bars. The obtained results indicate that the method can detect the caused asymmetry with a very restricted amount of data.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2015
Keywords
Information technology - Automatic control, Informationsteknik - Reglerteknik
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-34146 (URN)84337867-8adc-4cc5-906d-be73174a0b07 (Local ID)978-1-4799-4033-2 (ISBN)84337867-8adc-4cc5-906d-be73174a0b07 (Archive number)84337867-8adc-4cc5-906d-be73174a0b07 (OAI)
Conference
Annual Conference of the IEEE Industrial Electronics Society : 29/10/2014 - 01/11/2014
Note
Godkänd; 2015; 20140623 (geonik)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved
Mustafa, M. O., Nikolakopoulos, G. & Gustafsson, T. (2014). Fault classification scheme for three phase induction motor (ed.). Paper presented at . International Journal of System Dynamics Applications, 3(1)
Open this publication in new window or tab >>Fault classification scheme for three phase induction motor
2014 (English)In: International Journal of System Dynamics Applications, ISSN 2160-9772, E-ISSN 2160-9799, Vol. 3, no 1Article in journal (Refereed) Published
Abstract [en]

In this article a fault classification algorithm based on a robust linear discrimination scheme, for the case of a squirrel–cage three phase induction motor, will be presented. The suggested scheme is based on a novel feature extraction mechanism from the measured magnitude and phase of current park’s vector pattern. The proposed methodology has the merit to diagnose different types of faults such as: a) broken rotor bar, and b) short circuit in stator winding. The novel feature generation technique is able to transform the problem of fault detection and diagnosis into a simpler space, where direct robust linear discrimination can be applied for solving the classification problem. Robust linear discrimination has been one of the most widely used fault detection method in real life applications, as this methodology seeks for directions that are efficient for discrimination and at the same time applies a straight forward implementation. The efficacy of the proposed scheme will be evaluated based on multiple simulation results for different fault types.

Keywords
Information technology - Automatic control, Informationsteknik - Reglerteknik
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-5711 (URN)10.4018/ijsda.2014010101 (DOI)3e1d5772-6bd8-49a2-92d2-34f7d6791c62 (Local ID)3e1d5772-6bd8-49a2-92d2-34f7d6791c62 (Archive number)3e1d5772-6bd8-49a2-92d2-34f7d6791c62 (OAI)
Projects
Feldetektering i elektriska maskiner
Note
Validerad; 2014; 20130803 (geonik)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved
Mustafa, M. O., Nikolakopoulos, G. & Gustafsson, T. (2014). Uncertainty Bounds Violation Scheme for Fault Detection in Induction Motors: Application to Broken Rotor Bars (ed.). Paper presented at Reglermöte 2014 : 03/06/2014 - 04/06/2014. Paper presented at Reglermöte 2014 : 03/06/2014 - 04/06/2014.
Open this publication in new window or tab >>Uncertainty Bounds Violation Scheme for Fault Detection in Induction Motors: Application to Broken Rotor Bars
2014 (English)Conference paper, Oral presentation only (Other academic)
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-35931 (URN)aa964331-f3f7-4e4b-9676-9e5895107d94 (Local ID)aa964331-f3f7-4e4b-9676-9e5895107d94 (Archive number)aa964331-f3f7-4e4b-9676-9e5895107d94 (OAI)
Conference
Reglermöte 2014 : 03/06/2014 - 04/06/2014
Note
Godkänd; 2014; 20141124 (andbra)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved
Mustafa, M. O., Nikolakopoulos, G. & Gustafsson, T. (2014). Uncertainty Bounds Violation Scheme for FaultDetection in Induction Motors: Application to Broken Rotor Bars (ed.). Paper presented at Reglermöte 2014 : 03/06/2014 - 04/06/2014. Paper presented at Reglermöte 2014 : 03/06/2014 - 04/06/2014.
Open this publication in new window or tab >>Uncertainty Bounds Violation Scheme for FaultDetection in Induction Motors: Application to Broken Rotor Bars
2014 (English)Conference paper, Poster (with or without abstract) (Refereed)
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-27733 (URN)14402042-667e-4a0a-99c5-227c089f905d (Local ID)14402042-667e-4a0a-99c5-227c089f905d (Archive number)14402042-667e-4a0a-99c5-227c089f905d (OAI)
Conference
Reglermöte 2014 : 03/06/2014 - 04/06/2014
Note
Godkänd; 2014; 20141124 (andbra)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved
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