000			02281cam a2200337 a 4500
003			EG-GiCUC
005			20250223031223.0
008			150504s2014 ua e f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.13.07.M.Sc.2014.Hu.C
100	0		_aHussein Adel Taha Hussein
245	1	0	_aCondition monitoring and fault diagnosis of induction motor using neuro fuzzy logic / _cHussein Adel Taha Hussein ; Supervised Mohamed Ahmed Moustafa Hassan , Mohammed Elsayed Ammar
246	1	5	_aتحديد و رصد أخطاء المحرك الحثى باستخدام المنطق الضبابى ذى الخلايا العصبية
260			_aCairo : _bHussein Adel Taha Hussein , _c2014
300			_a91 P. : _bplans ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electrical Power and Machines
520			_aThe Induction machine is one of mostly common machine. It is almost used for all industrial applications, wind energy generation and recently it has been proposed for applications of hybrid electrical vehicle and electrical air craft. Fault monitoring and control becomes high priority for induction machine. This thesis discusses the fault diagnosis and monitoring of the induction motor, starting with the machine different faults and the different algorithms to detect these faults (intelligent control, parameter estimation{u2026}). The scope of this research is the fault with high occurrence percentage, which is stator turns faults. It is built on objects of: a) Three phase induction motor modeling in both the symmetric healthy and asymmetric faulty cases using of dq frames instead of ABC. b) An algorithm of on - line fault detection based on the motor fault response and motor electrical parameters change. c) The efficient design of an adaptive neuro fuzzy system
530			_aIssued also as CD
653		4	_aANFIS
653		4	_aDq modeling
653		4	_aInduction motor
700	0		_aMohamed Ahmed Moustafa Hassan , _eSupervisor
700	0		_aMohammed Elsayed Ammar , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aNazla _eRevisor
905			_aSamia _eCataloger
942			_2ddc _cTH
999			_c50754 _d50754