[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Almashakbeh et al., 2017 - Google Patents

Models for electric machine reliability prediction at variation of the condition of basic structural units

Almashakbeh et al., 2017

View PDF
Document ID
13904616299666810746
Author
Almashakbeh A
Prus V
Zagirnyak M
Publication year
Publication venue
Przeglad elektrotechniczny

External Links

Snippet

Prospects of working out intelligent models of reliability of electric machines (EM) with long mean time between failures are substantiated and a method for their realization is presented. Limit conditions of basic structural units of low-and medium-power induction …
Continue reading at pe.org.pl (PDF) (other versions)

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/34Testing dynamo-electric machines
    • G01R31/343Testing dynamo-electric machines in operation

Similar Documents

Publication Publication Date Title
Almashakbeh et al. Models for electric machine reliability prediction at variation of the condition of basic structural units
Singh Induction machine drive condition monitoring and diagnostic research—a survey
Romero-Troncoso et al. FPGA-based online detection of multiple combined faults in induction motors through information entropy and fuzzy inference
Siddiqui et al. Health monitoring and fault diagnosis in induction motor-a review
Ballal et al. Adaptive neural fuzzy inference system for the detection of inter-turn insulation and bearing wear faults in induction motor
Batzel et al. Prognostic health management of aircraft power generators
Bhowmik et al. Fault diagnostic and monitoring methods of induction motor: a review
Liang et al. Condition monitoring techniques for induction motors
Alsaedi Fault diagnosis of three-phase induction motor: A review
CN110531266A (en) A kind of synchronous machinery excitation winding interturn short-circuit fault early warning method
Babak et al. Models and measures for the diagnosis of electric power equipment
Laayati et al. Smart energy management system: SCIM diagnosis and failure classification and prediction using energy consumption data
Tian et al. A review of fault diagnosis for traction induction motor
Zagirnyak et al. Models of reliability prediction of electric machine taking inTo account the state of major structural units
Zaman et al. Greedy-gradient max cut-based fault diagnosis for direct online induction motors
Dobroskok et al. Neural network based detecting induction motor defects supplied by unbalanced grid
Ranga et al. Advanced tool based condition monitoring of induction machines by using LabVIEW—A review
Mini et al. Rotor fault detection and diagnosis of induction motor using fuzzy logic
Chang et al. Fuzzy theory-based partial discharge technique for operating state diagnosis of high-voltage motor
Swędrowski et al. Use of neural networks in diagnostics of rolling-element bearing of the induction motor
Ilić et al. Artificial intelligence system for stator condition diagnostic
Ayyappan et al. Fault classification and diagnosis of industrial application motor drives using soft computing techniques
Noureddine et al. Fuzzy logic system for BRB defect diagnosis of SCIG-based wind energy system
Zagirnyak et al. The methods for accounting the degree of electric machines aging in the assessment of their reliability
Gazizulin et al. Critical rotating machinery protection by integration of a “fuse” bearing