Low starting current cage induction motors for the offshore petrochemical industry

2002 ◽  
Author(s):  
T.A. Gallant
Keyword(s):  
Petrochemical Industry ◽  
Induction Motors ◽  
Starting Current

scholarly journals Intelligent Starting Current-Based Fault Identification of an Induction Motor Operating under Various Power Quality Issues

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 304
Author(s):  
Sakthivel Ganesan ◽  
Prince Winston David ◽  
Praveen Kumar Balachandran ◽  
Devakirubakaran Samithas
Keyword(s):  
Standard Deviation ◽  
Power Quality ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Classification Accuracy ◽  
Induction Motors ◽  
Quality Data ◽  
Starting Current ◽  
Quality Issues ◽  
Condition Monitoring System

Since most of our industries use induction motors, it is essential to develop condition monitoring systems. Nowadays, industries have power quality issues such as sag, swell, harmonics, and transients. Thus, a condition monitoring system should have the ability to detect various faults, even in the presence of power quality issues. Most of the fault diagnosis and condition monitoring methods proposed earlier misidentified the faults and caused the condition monitoring system to fail because of misclassification due to power quality. The proposed method uses power quality data along with starting current data to identify the broken rotor bar and bearing fault in induction motors. The discrete wavelet transform (DWT) is used to decompose the current waveform, and then different features such as mean, standard deviation, entropy, and norm are calculated. The neural network (NN) classifier is used for classifying the faults and for analyzing the classification accuracy for various cases. The classification accuracy is 96.7% while considering power quality issues, whereas in a typical case, it is 93.3%. The proposed methodology is suitable for hardware implementation, which merges mean, standard deviation, entropy, and norm with the consideration of power quality issues, and the trained NN proves stable in the detection of the rotor and bearing faults.

Saturistors and Low Starting Current Induction Motors

1963 ◽  
Vol 82 (66) ◽  
pp. 291-298 ◽  
Author(s):  
P. Alger ◽  
G. Angst ◽  
W. Schweder
Keyword(s):  
Induction Motors ◽  
Starting Current

Starting Current Limitation Method Using HTS for Induction Motors

2014 ◽  
Vol 28 (2) ◽  
pp. 697-700 ◽  
Author(s):  
F. B. B. Silva ◽  
C. A. Baldan ◽  
J. F. Fardin ◽  
D. S. Simonetti
Keyword(s):  
Induction Motors ◽  
Current Limitation ◽  
Starting Current ◽  
Limitation Method

DC pre-excitation starting control for induction motor base on flux identification and compensation

2019 ◽  
Vol 67 (7) ◽  
pp. 587-598
Author(s):  
Bo Fan ◽  
Leipo Liu ◽  
Zhumu Fu ◽  
Jiangtao Fu
Keyword(s):  
Vector Control ◽  
Control Strategy ◽  
Induction Motors ◽  
Fast Response ◽  
Large Power ◽  
Starting Current ◽  
System A ◽  
Output Torque ◽  
Rotor Flux ◽  
Starting Control

Abstract Vector control can not be well applied directly to the starting of large-power induction motors. The starting current is so large as to cause damage to power-conductors and the whole control system. A novel pre-excitation control strategy is proposed in this paper. A magnetic field is built in large power motor startup firstly, in which DC pre-excitation is adopted and the rotor flux orientation is set to coincide with the center line of motor’s one phase winding. With the completion of this pre-excitation, the control strategy is switched to the vector control. The excitation subsystem and the torque subsystem in the motor can be decoupled dynamically after this pre-excitation and vector control. The experimental results show that the motor’s starting current rises smoothly and its output torque has fast response. This control strategy is capable of reducing the motor’s starting current peak and improving the safety of induction motor’s startup.

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