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Industrial Servo Motor Yaskawa SERVO MOTOR 200W 200V Made in Japan SGM-02A3SU11

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Industrial Servo Motor Yaskawa SERVO MOTOR 200W 200V Made in Japan SGM-02A3SU11

Large Image :  Industrial Servo Motor Yaskawa SERVO MOTOR 200W 200V Made in Japan SGM-02A3SU11

Product Details:

Place of Origin: Japan
Brand Name: Yasakawa
Model Number: SGM-02A3SU11

Payment & Shipping Terms:

Minimum Order Quantity: 1
Price: negotiable
Packaging Details: New in original box
Delivery Time: 2-3 work days
Payment Terms: T/T, Western Union
Supply Ability: 100
Detailed Product Description
Brand: Yasakawa Model: SGM-02A3SU11
Palce Of Origin: Japan Type: Servo Motor
Supply Voltage: 200V Current: 2.0A
Ins: B R/min: 3000
High Light:

ewing machine servo motor

,

electric servo motor

Industrial Servo Motor Yaskawa SERVO MOTOR 200W 200V Made in Japan SGM-02A3SU11​

 

 

 

 

The method presented in this thesis for induction motor fault diagnosis is based on the analysis of the envelope of the three phase stator current. This diagnostic method can classify two types of induction motor faults: broken rotor bars and inter-turn short circuits in the stator windings. Experimental results show that the three phase current envelope is a powerful feature for motor fault classification. The envelope signal is extracted from the experimentally acquired stator current signals and is used in conjunction with machine learning techniques based on Gaussian Mixture Models [34] (GMMs) and Reconstructed Phase Spaces (RPSs) [34-36] to identify motor faults.

 

 

SPECIFITIONS

Current: 0.89A
Volatge: 200V
Power :100W
Rated Torque: 0.318-m
Max speed: 3000rpm
Encoder: 17bit Absolute encoder
Load Inertia JL kg¡m2¢ 10−4: 0.026
Shaft: straight without key

 

 

 

 
 
 
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The method presented in this thesis for induction motor fault diagnosis is based on the analysis of the envelope of the three phase stator current. This diagnostic method can classify two types of induction motor faults: broken rotor bars and inter-turn short circuits in the stator windings. Experimental results show that the three phase current envelope is a powerful feature for motor fault classification. The envelope signal is extracted from the experimentally acquired stator current signals and is used in conjunction with machine learning techniques based on Gaussian Mixture Models [34] (GMMs) and Reconstructed Phase Spaces (RPSs) [34-36] to identify motor faults.
 
 

In addition, this diagnostic method not only classifies an induction motor as healthy or faulty, but also identifies the severity of the fault through the identification of the number of broken rotor bars or the number (or percentage) of short-circuited turns in stator windings. This constitutes a powerful means of monitoring motor fault severities, which could possibly predict the time of onset of complete failure of a motor, and thus help prevent unexpected shutdowns of industrial processes. The second advantage of this method is that the classification process needs only the three-phase stator current sensors, usually available in ac drives. Thus, extra electrical and mechanical installations, sensors,
and mathematical models of an induction motor are not required.

 

 

 

 

 

 

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E-mail: wisdomlongkeji@163.com
Cellphone: +0086-13534205279
 

 

 

 
 
 
 
 
 
 
 
 
 
 

 

 

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