Performance of wavelet analysis and neural network for detection and diagnosis of rotating machine fault

2008 ◽  
Author(s):  
Shanlin Kang ◽  
Yuzhe Kang ◽  
Jingwei Chen
Keyword(s):  
Neural Network ◽  
Wavelet Analysis ◽  
Rotating Machine ◽  
Machine Fault ◽  
Detection And Diagnosis

scholarly journals Rotor Dynamics Analysis of Rotating Machine Systems Using Artificial Neural Networks

2003 ◽  
Vol 9 (4) ◽  
pp. 255-262 ◽  
Author(s):  
M. Kalkat ◽  
Ş. Yıldırım ◽  
I. Uzmay
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Vertical Direction ◽  
Rotor Dynamics ◽  
Experimental Setup ◽  
Dynamics Analysis ◽  
Rotating Machine ◽  
Rotating Systems ◽  
Machine Systems ◽  
Vibration Parameters

Adirect-coupled rotor system was designed to analyze the dynamic behavior of rotating systems in regard to vibration parameters. The vibration parameters are amplitude, velocity, and acceleration in the vertical direction. The system consisted of a machine analyzer, shaft, disk, master-trend software, and power unit. Four different points were detected and measured by the experimental setup. The vibration parameters were found and saved from master-trend software. These parameters were employed as the desired parameters of the network. A neural network is designed for analyzing a system's vibration parameters. The results showed that the network could be used as an analyzer of such systems in experimental applications.

Development of a Master-Slave Architecture Handheld Rotating Machine Fault Diagnosis Instrument

2011 ◽  
Vol 141 ◽  
pp. 244-250
Author(s):  
Jian Wan ◽  
Tai Yong Wang ◽  
Jing Chuan Dong ◽  
Pan Zhang ◽  
Yan Hao
Keyword(s):  
Fault Diagnosis ◽  
Signal Integrity ◽  
Module Design ◽  
Time Performance ◽  
Rotating Machine ◽  
Machine Fault Diagnosis ◽  
Slave Processor ◽  
Design Idea ◽  
Machine Fault ◽  
Communication Methods

To insure that sampling signal integrity, accuracy and real-time performance can adapt to the development of rotating machine fault diagnosis technology, a master-slave architecture handheld rotating machine fault diagnosis instrument was developed based on S3C2410 ARM IC and TMS320VC5509A DSP IC. It provided an effective method for the field monitoring and diagnosis of the large rotating machine. The whole design idea and the structure of the hardware and the software were systematically introduced. The paper focused on the master-slave architecture design of the hardware, the communication methods between the master and the slave processor, and the signal pretreatment module design. Put into practice, the practicability, reliability and stability of the instrument were confirmed.

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