TIANENLU(CHINA) ENTERPRISE GROUP COMPANY

 TianEnLu (China) Enterprise Group

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©2018  TianEnLu (China) Enterprise Group  Copyright​   Power by:300.cn  Dalian     辽ICP备17009061号-1
Add:No.26 Digital 3rd Road, Double D Port, Jinzhou District, Dalian
Tel:86-411-82767308

POWER QUALITY OPTIMIZATION AND

SAFETY GUARANTEE IN THE GROUP AND PARK 

On-line Detection Device for Motor Safety

没有此类产品
Description

  Product introduction   

The terminal equipment safety on-line monitoring device has the capability of self-learning to adapt to the operation parameters of the equipment, can record the working electric quantity parameters of the equipment in real time, and runs the environmental parameters and the key parameters of the equipment. It is provided with the functions of intelligent analysis equipment operation status, monitoring alarm and the like, and comprehensively records and analyzes any abnormal state of the monitoring object. And can be networked through the on-line experts in the cloud and the peer-to-peer device for statistics, and the health state of the equipment operation is detected, and the early warning and protection are put forward. The energy-saving plan of the equipment can also be put forward through the electric-effect benchmarking analysis, and the operation efficiency of the equipment can be improved.

    Product function    

  • Motor temperature on-line monitoring: the advanced motor model algorithm is used to automatically calculate the actual temperature rise of the internal winding of the motor.
  • Motor vibration monitoring: 8 axis acceleration sensor is used to monitor the vibration state of the motor and alarm beyond the limit. Through vibration analysis, the wear state of motor bearing, rotor dynamic balance, shafting running line, mechanical load fault and other mechanical problems can be found in time.
  • Motor on-line insulation monitoring: the insulation state of the motor can be monitored before the leakage current is formed. (for three-wire three-phase system)

   Technological superiority   

  • Self-learning function: cooperate with the state logic of the motor (such as the starting and stopping of the motor and the the process state) to automatically learn the normal working parameters of the equipment.
  • Motor parameters cross-line alarm function: when the real-time detection parameters of the motor exceed the range of self-learning, the recorder automatically forms alarm records and issues field and remote warnings.
  • Motor start curve report: automatically analyze the starting mode of the motor, form a separate current start curve, the corresponding voltage start curve, the power factor start curve, complete the motor start analysis, start the curve to the motor, Transmission and load state have very accurate analysis.
  • Motor energy efficiency report: analyze the energy efficiency state of the motor in work, calculate copper loss and iron loss according to the loss model. Calculate the instantaneous efficiency, hour efficiency, daily average efficiency and other energy efficiency data of the motor, and provide data support for energy saving and efficiency improvement. The device supports the remote upload of energy consumption data.
  • Motor health status report: according to the preset testing items, inquire and send motor health status report, provide a separate report for abnormal data, easy to maintain diagnosis, form motor big data.

    Characteristic of Product    

  • Online-no need to stop monitoring remote;

  • There is no need to approach the motor for induction motor;

  • Synchronous motor, DC motor, generator, VFD

  • Current, vibration, temperature a variety of data acquisition and analysis;

  • High accuracy in online fault diagnosis;

  • Determination of severity and state change self-learning function, improve diagnostic accuracy。

  • Online-no need to stop monitoring remote;

  • There is no need to approach the motor for induction motor;

  • Synchronous motor, DC motor, generator, VFD;

  • Current, vibration, temperature a variety of data acquisition and analysis;

  • High accuracy in online fault diagnosis;

  • Determination of severity and state change self-learning function, improve diagnostic accuracy。

Corresponding parameter set not found, please add it in property template of background
暂未实现,敬请期待
暂未实现,敬请期待
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