Industrial Servo Motor New YASKAWA SERVO MOTOR 0.318-m 3000/min SGM-02A3G26

Industrial Servo Motor New YASKAWA SERVO MOTOR 0.318-m 3000/min SGM-02A3G26​

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

OTHER SUPERIOR PRODUCTS

Other techniques include vibration analysis, acoustic noise measurement, torque profile analysis, temperature analysis, and magnetic field analysis [28, 30]. These techniques require sophisticated and expensive sensors, additional electrical and mechanical installations, and frequent maintenance. Moreover, the use of a physical sensor in a motor fault identification system results in lower system reliability compared
to other fault identification systems that do not require extra instrumentation. This is due to the susceptibility of the sensor to fail added to the inherent susceptibility of the induction motor to fail.

Recently, new techniques based on artificial intelligence (AI) approaches have been introduced, using concepts such as fuzzy logic [32], genetic algorithms [28], and Bayesian classifiers [18, 34]. The AI-based techniques can not only classify the faults, but also identify the fault severity. These methods build offline signatures for each motor operating condition and an online signature for the status of a motor being monitored. A

classifier compares the previously learned signatures with the signature generated online in order to classify the motor operating condition and identify the fault severity.

However, most of these AI-based techniques require large datasets. These dataset are used to learn a signature for each motor operating condition that is being considered for classification. Thus, a large amount of data is needed to train such algorithms in order to cover the most common motor operating conditions, and obtain good motor fault classification accuracy. Moreover, AI-based techniques for motor fault classification may not be sufficiently robust to classify faults from different motors from those used in the training process. Additionally, these datasets are usually not available, involve destructive testing, and considerable time to generate.

Shenzhen Wisdomlong Technology CO.,LTD Mainly engaged in automation parts, PLCS,DCS,sensors, relays, dirves,encoder, servo drive,soft starter,touch screen,instrument,process control,electric transmission and factory automation aspects of the project design,software programming,technical service and staff training. Our company locats at the central of China,Shenzhen, Guangdong Province. With rapid development, Wisdomlong serves fields of automation in global markets, Our business covers five continents throughout the world with the basic conviction of honest, the international management of customer-centered concept and purpose of bringing convenience to customers. We have confidence to bring our customers more substantial profit with high-quality service and reasonable prices. Choosing us,you will choose a sincere friend and reliable partner. Please feel free to contact us if you are a global manufacturer of high quality brand products who desires to enter the Chinese market or who searches for a Chinese agent.We would like to create a brilliant future with friends in domestic and overseas. All goods sold have one year warranty.

The company with domestic and international numerous well-known brands supplier to build have extremely good relations of cooperation, in Japan, South Korea, southeast Asia, Africa, Europe and the United States, and formed a stable and efficient supply network. The agent and the products are widely used in machinery, equipment manufacturing, electric power, metallurgy, petrochemical, automobile manufacturing industry, paper making, chemical industry, medicine and aerospace industries.

Our Main Brand:

MITSUBISHI

YASKAWA

PANASONIC

GE FANUC

EMERSON

FISHER-ROSEMOUNT

HONEYWEL

ABB

AB

SHNEIDER MODICON

SIEMENS

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