Analysis and diagnosis of broken rotor bars in induction motors based on maxwell

Lv, Yuegang; Zhang, Wenyuan; Liu, Juncheng

doi:10.1109/chicc.2014.6897130

Cited by 2 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For the binary number obtained by formula (10), the LBP value of the window is obtained by calculating the weighted sum of pixels at different positions by formula (11):…”

Section: The Proposed Fault Identification Methodsmentioning

confidence: 99%

“…e method based on process modeling usually establishes a mathematical model of faulty motor and converts the fault detection problem into the identification problem of corresponding parameters. For broken rotor bar (BRB) fault, the finite element method was used to establish IM models in [7][8][9][10][11] and the fault detection was realized by analyzing and comparing the changes of various physical quantities in the motor. e detection of BRB fault was realized by analyzing the changes of motor currents and gap flux density in [7].…”

Section: Introductionmentioning

confidence: 99%

“…e simulation results of motor models with stable and variable speed were compared and the speed oscillation was used for fault detection in [11]. A faulty IM model was established based on multiloop theory and the currents were analyzed to detect the BRB fault in [12].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Method for Identifying Stator and Rotor Faults of Induction Motors Based on Machine Vision

Lipeng

Xiang

Wang

et al. 2021

Mathematical Problems in Engineering

View full text Add to dashboard Cite

The detection results need to be analyzed and distinguished by professional technicians in the fault detection methods for induction motors based on signal processing and it is difficult to realize the automatic identification of stator and rotor faults. A method for identifying stator and rotor faults of induction motors based on machine vision is proposed to solve this problem. Firstly, Park’s vector approach (PVA) is used to analyze the three-phase currents of the motor to obtain Park’s vector ring (PVR). Then, the local binary patterns (LBP) and gray level cooccurrence matrix (GLCM) are combined to extract the image features of PVR. Finally, the vectors of image features are used as input and the types of induction motor faults are identified with the help of a random forest (RF) classifier. The proposed method has achieved high identification accuracy in both the Maxwell simulation experiment and the actual motor experiment, which are 100% and 95.83%, respectively.

show abstract

“…For the binary number obtained by formula (10), the LBP value of the window is obtained by calculating the weighted sum of pixels at different positions by formula (11):…”

Section: The Proposed Fault Identification Methodsmentioning

confidence: 99%