Matches in SemOpenAlex for { <https://semopenalex.org/work/W2188045237> ?p ?o ?g. }
Showing items 1 to 95 of
95
with 100 items per page.
- W2188045237 abstract "A scheme for diagnosis and identification of mechanical unbalances and shaft misalignment on machines driven by induction motors is presented in this work. Fault identification is performed using unsupervised artificial neural networks: the so-called Self-Organizing Maps (SOM). The information of the motor phase current is used for feeding the network, in order to perform the fault diagnosis. The network is trained using data generated through the simulation of a motor- load system model. Such model allows including the effects of load unbalance and shaft misalignment. Experimental data are later applied to the SOM in order to validate the proposal. It is demonstrated that the strategy is able to correctly identify both unbalanced and misaligned cases. Predictive maintenance attempts to avoid unexpected faults in the industry, which cause great economic losses due to interruptions in continuous production processes. Hence arises the need and interest for the industry to develop strategies for on-line detection and diagnosis of incipient faults in electrical machines. In this way, process interruptions can be planned and machines maintenance can be performed during programmed stops. This allows reducing the maintenance time and the associated economic losses. Among these strategies, those based on measurement of motor voltages and currents allows detecting different types of faults by measuring from the switchboard, thus reducing the risks for the operator in hazardous environments or difficult to access. Such strategies have also been used for detecting problems associated to the load driven by the motor. The detection and diagnosis of electrical or mechanical faults on induction motor implies, in most cases, the interpretation of the frequency spectrum of the motor current, power, Park's vector, among others (1). This requires an expert who performs the task, based on the information obtained from the processed signals. At present the study of different alternatives, such as Artificial Intelligence (AI) techniques, have taken great importance because they require a minimal interpretation of the studied system. Thus, the diagnosis task is simplified (2). Unsupervised Neural Networks (UNN) was proposed for fault diagnosis on electric drives in (3). The application of UNN for the diagnosis of load unbalances and shaft misalignment problems in electric drives is presented in this work. A Self-Organizing Map (SOM) - a type of UNN - is implemented and trained using simulation data obtained from a motor-load model, which allows considering load unbalance and shaft misalignment. This network is later used to obtain an automatic diagnosis of such problems, from data obtained from measurements made on real cases." @default.
- W2188045237 created "2016-06-24" @default.
- W2188045237 creator A5001516180 @default.
- W2188045237 creator A5024996191 @default.
- W2188045237 creator A5034062478 @default.
- W2188045237 creator A5056014895 @default.
- W2188045237 creator A5066545085 @default.
- W2188045237 date "2010-01-01" @default.
- W2188045237 modified "2023-09-27" @default.
- W2188045237 title "Fault Diagnosis on Induction Motors Using" @default.
- W2188045237 cites W1500685872 @default.
- W2188045237 cites W1679913846 @default.
- W2188045237 cites W2094177794 @default.
- W2188045237 cites W2129695894 @default.
- W2188045237 cites W2139853183 @default.
- W2188045237 cites W2418807858 @default.
- W2188045237 hasPublicationYear "2010" @default.
- W2188045237 type Work @default.
- W2188045237 sameAs 2188045237 @default.
- W2188045237 citedByCount "0" @default.
- W2188045237 crossrefType "journal-article" @default.
- W2188045237 hasAuthorship W2188045237A5001516180 @default.
- W2188045237 hasAuthorship W2188045237A5024996191 @default.
- W2188045237 hasAuthorship W2188045237A5034062478 @default.
- W2188045237 hasAuthorship W2188045237A5056014895 @default.
- W2188045237 hasAuthorship W2188045237A5066545085 @default.
- W2188045237 hasConcept C111919701 @default.
- W2188045237 hasConcept C116834253 @default.
- W2188045237 hasConcept C119599485 @default.
- W2188045237 hasConcept C127313418 @default.
- W2188045237 hasConcept C127413603 @default.
- W2188045237 hasConcept C133731056 @default.
- W2188045237 hasConcept C152745839 @default.
- W2188045237 hasConcept C154945302 @default.
- W2188045237 hasConcept C165205528 @default.
- W2188045237 hasConcept C165801399 @default.
- W2188045237 hasConcept C172707124 @default.
- W2188045237 hasConcept C175551986 @default.
- W2188045237 hasConcept C200601418 @default.
- W2188045237 hasConcept C2775846686 @default.
- W2188045237 hasConcept C41008148 @default.
- W2188045237 hasConcept C50644808 @default.
- W2188045237 hasConcept C59822182 @default.
- W2188045237 hasConcept C70452415 @default.
- W2188045237 hasConcept C80962145 @default.
- W2188045237 hasConcept C86803240 @default.
- W2188045237 hasConcept C98045186 @default.
- W2188045237 hasConceptScore W2188045237C111919701 @default.
- W2188045237 hasConceptScore W2188045237C116834253 @default.
- W2188045237 hasConceptScore W2188045237C119599485 @default.
- W2188045237 hasConceptScore W2188045237C127313418 @default.
- W2188045237 hasConceptScore W2188045237C127413603 @default.
- W2188045237 hasConceptScore W2188045237C133731056 @default.
- W2188045237 hasConceptScore W2188045237C152745839 @default.
- W2188045237 hasConceptScore W2188045237C154945302 @default.
- W2188045237 hasConceptScore W2188045237C165205528 @default.
- W2188045237 hasConceptScore W2188045237C165801399 @default.
- W2188045237 hasConceptScore W2188045237C172707124 @default.
- W2188045237 hasConceptScore W2188045237C175551986 @default.
- W2188045237 hasConceptScore W2188045237C200601418 @default.
- W2188045237 hasConceptScore W2188045237C2775846686 @default.
- W2188045237 hasConceptScore W2188045237C41008148 @default.
- W2188045237 hasConceptScore W2188045237C50644808 @default.
- W2188045237 hasConceptScore W2188045237C59822182 @default.
- W2188045237 hasConceptScore W2188045237C70452415 @default.
- W2188045237 hasConceptScore W2188045237C80962145 @default.
- W2188045237 hasConceptScore W2188045237C86803240 @default.
- W2188045237 hasConceptScore W2188045237C98045186 @default.
- W2188045237 hasLocation W21880452371 @default.
- W2188045237 hasOpenAccess W2188045237 @default.
- W2188045237 hasPrimaryLocation W21880452371 @default.
- W2188045237 hasRelatedWork W1520942344 @default.
- W2188045237 hasRelatedWork W1607178765 @default.
- W2188045237 hasRelatedWork W1665402297 @default.
- W2188045237 hasRelatedWork W2036277235 @default.
- W2188045237 hasRelatedWork W2107301166 @default.
- W2188045237 hasRelatedWork W2488793338 @default.
- W2188045237 hasRelatedWork W2546805651 @default.
- W2188045237 hasRelatedWork W2774330391 @default.
- W2188045237 hasRelatedWork W2896983250 @default.
- W2188045237 hasRelatedWork W2898675613 @default.
- W2188045237 hasRelatedWork W2906578288 @default.
- W2188045237 hasRelatedWork W2906592384 @default.
- W2188045237 hasRelatedWork W2988533417 @default.
- W2188045237 hasRelatedWork W3002317338 @default.
- W2188045237 hasRelatedWork W3021544019 @default.
- W2188045237 hasRelatedWork W3039486067 @default.
- W2188045237 hasRelatedWork W3112955596 @default.
- W2188045237 hasRelatedWork W3187554634 @default.
- W2188045237 hasRelatedWork W1738702672 @default.
- W2188045237 hasRelatedWork W2740800227 @default.
- W2188045237 isParatext "false" @default.
- W2188045237 isRetracted "false" @default.
- W2188045237 magId "2188045237" @default.
- W2188045237 workType "article" @default.