2017
DOI: 10.1016/j.ymssp.2017.03.016
|View full text |Cite
|
Sign up to set email alerts
|

Comparative investigation of vibration and current monitoring for prediction of mechanical and electrical faults in induction motor based on multiclass-support vector machine algorithms

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

1
45
0
2

Year Published

2018
2018
2021
2021

Publication Types

Select...
3
3
2

Relationship

0
8

Authors

Journals

citations
Cited by 124 publications
(48 citation statements)
references
References 24 publications
1
45
0
2
Order By: Relevance
“…e authors compared the obtained results with other literature references. e acquired results were similar to other proposed techniques of vibration analysis [11,20,[34][35][36][37]. In [11], results with an error lower than 2% were obtained.…”
Section: Resultssupporting
confidence: 81%
See 1 more Smart Citation
“…e authors compared the obtained results with other literature references. e acquired results were similar to other proposed techniques of vibration analysis [11,20,[34][35][36][37]. In [11], results with an error lower than 2% were obtained.…”
Section: Resultssupporting
confidence: 81%
“…Classification rate was in the range of 85.6-95.8% [36]. Gangsar and Tiwari [37] presented vibration-based analysis for fault prediction of the induction motor. e MSVM (multiclass support vector machine) was used.…”
Section: Resultsmentioning
confidence: 99%
“…In total 30 features were extracted for the 16 signals, resulting in 480 features in total. These time and frequency domain features are standard metrics, commonly used for the condition monitoring of induction motors [11], [21], [32]. It should be noted that for all signal types, all of the above mentioned feature types were extracted.…”
Section: Implementation Of the Methodsmentioning
confidence: 99%
“…Another regularly observed fault detection problem is the varying operating conditions of the machines, which can originate from a change in the load or environmental conditions. In [21] it was concluded that the prediction performance of a Support Vector Machine-based fault detection algorithm for mechanical and electrical fault detection in induction motors is load dependent. Different severities of stator faults were monitored in induction motors under changing load torque and supply voltage unbalances in [22], finding that the performance of a multi-agent system and neural estimator depends on the severity of the fault.…”
mentioning
confidence: 99%
“…Ademais, Sotelo Junior e França (2006) mencionam a presença das vibrações em aparelhos de uso doméstico como aspiradores, secadores, máquinas de lavar etc., onde: [...] pode-se vivenciar a sensação induzida pelo movimento mecânico de alta frequência e de pequena amplitude de deslocamento, desagradável em geral, associado a ruído sonoro e que conduz à fadiga física após certo tempo de exposição (SOTELO JUNIOR;FRANÇA, 2006). Atualmente existem muitas pesquisas relacionadas a vibrações na área da Engenharia, como em projetos de máquinas, fundações, estruturas, motores, turbinas e sistemas de controle (GANGSAR; TIWARI, 2017;KUMAR et al, 2019). Há uma diversidade de relatos Usualmente as vibrações transmitidas ao corpo humano são classificadas de duas formas, de acordo com a parte do corpo atingida: vibrações de corpo inteiro e vibrações de mãos e braços.…”
Section: Fundamentação Teóricaunclassified