Paper Title:
Sensorless Detection and Diagnosis Method for Induction Motor and its Driven Equipment
  Abstract

The mechanical equipments driven by induction motor are widely used in manufacturing. Aiming at this type of equipment, some holes are advisedly drilled on the bars to simulate the broken bar faults of the motor, and with on-off loads changes of output circuit of the load generator, forced torsional vibration of rotor was generated. Using the above simulation test ways, the typical faults of motor and its driven equipment are tested and analyzed. In addition, an signal analysis method using Hilbert conversion envelope spectrum and real modulation zoom envelope spectrum is proposed, this method can effectively extract the faults information of stator current, reject the useless power frequency. The experimental results indicate that: this method can identify not only the faults of the motor itself, but also municipal fault types of the motor’s driven equipment. Especially, through the contrastive experiments on the unbalance and the torsional vibration of the rotor, the conclusion is made that the method is more sensitive to torsional vibration detection. Also, it develops a new direction for the application and the research of sensorless detection and diagnosis method.

  Info
Periodical
Key Engineering Materials (Volumes 392-394)
Edited by
Guanglin Wang, Huifeng Wang and Jun Liu
Pages
98-102
DOI
10.4028/www.scientific.net/KEM.392-394.98
Citation
X.J. Shi, C.X. Zhang, J. P. Shao, "Sensorless Detection and Diagnosis Method for Induction Motor and its Driven Equipment", Key Engineering Materials, Vols. 392-394, pp. 98-102, 2009
Online since
October 2008
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Shu Shang Zhao, Juan Juan Pan
Chapter 8: Modeling, Analysis, and Simulation of Manufacturing Processes
Abstract:In the rotating machinery, rolling bearing is used widespread in many places. Due to various reasons, there is great dispersion in the life...
2622
Authors: Bin Li, Yu Guo, Ting Wei Liu, Yan Gao
Chapter 3: Engineering Technology
Abstract:The traditional envelope analysis methods are usually ineffective in the fault diagnosis of Gearbox on the condition that there are...
2054
Authors: Xiao Yun Gong, Jie Han, Hong Chen, Wen Ping Lei
Chapter 5: Control and Detection Technology
Abstract:Wavelet envelope demodulation method can distinguish the fault information from complex bearing vibration signal. However, traditional signal...
873
Authors: Jing Zhong Xiang, Fu Peng Ge, Han Sun, Xian Jiang Shi
Chapter 1: Advanced Technologies in Mechanical and Manufacturing Engineering
Abstract:It is first to make Empirical Mode Decomposition (EMD) and achieve Hilbert-Hung transform (HHT) of envelope spectrum after Hilbert...
37
Authors: Yun Li, Yan Gao, Jun Guo, Xian Jun Yu, Yan Xue Liu
Chapter 3: Techniques for Measurement, Detection and Monitoring
Abstract:This paper proposed a new method of gear fault diagnosis in gearbox. Mainly it stresses on the combination of time synchronous average (TSA)...
502