Mechanical vibration in rotating machinery.

1978 ◽  
Keyword(s):  
Mechanical Vibration ◽  
Rotating Machinery

Oscillating Stress on Viscoelastic Behavior of Thermoplastic Polymers

2000 ◽  
Vol 122 (3) ◽  
pp. 386-389 ◽  
Author(s):  
Rudolph J. Scavuzzo
Keyword(s):  
Mechanical Vibration ◽  
Viscoelastic Behavior ◽  
Tensile Tests ◽  
Rotating Machinery ◽  
Rapid Decrease ◽  
Mean Stress ◽  
Permanent Set ◽  
Cyclic Stresses ◽  
Standard Specimens ◽  
Bending Stresses

Polymers are used in many applications where they are subjected to cyclic stresses. PVC and HDPE piping are often used in systems that include rotating machinery that cause mechanical vibration. Recent testing of thermoplastics indicates that there may be a large effect on the viscoelastic strains of thermoplastics from oscillating stresses. Cyclic loading on the permanent set of cross-linked elastomers has been studied. Perhaps, as expected, the effect of the oscillating behavior is measurable. Two types of tests have been conducted. First, tensile tests on HDPE standard specimens were conducted where oscillating stresses were superimposed onto an initial static or mean stress. These measurements showed a rapid decrease in the oscillating stresses when compared to measurements when steady nonoscillating stresses are applied to the same type of specimen. In the second test series, pressurized HDPE piping was subject to oscillating bending stresses. Ratcheting of the hoop strains in the pipe occurs. Results show that these strains follow the constitutive relationships of linear viscoelasticity and experimental results imply that viscoelastic changes are accelerated by stress oscillations. These preliminary results seem to indicate that the effects of oscillating stresses on the viscoelastic behavior of thermoplastics may be significant. A systematic study is required to further understand this behavior. [S0094-9930(00)02403-3]

Research on Fault Diagnosis for Rotating Machinery Vibration of Aero-Engine Based on Wavelet Transformation and Probabilistic Neural Network

2011 ◽  
Vol 295-297 ◽  
pp. 2272-2278 ◽  
Author(s):  
Wen Jie Wu ◽  
Da Gui Huang
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Wavelet Decomposition ◽  
Wavelet Transformation ◽  
Probabilistic Neural Network ◽  
Mechanical Vibration ◽  
Rotating Machinery ◽  
Aero Engine ◽  
Network Fault ◽  
Fault Feature Extraction

Fault feature extraction using wavelet decomposition and probabilistic neural network fault diagnosis technology is presented in this paper. Fault diagnosis based on wavelet transformation and neural network data fusion is studied. The fault diagnosis in rotating machinery vibration of the aero-engine is simulated in Matlab. Our recent investigations demonstrate that using wavelet decomposition extract fault characteristics of the energy vector has strong generalization ability and anti-noise ability. Integration of the wavelet and neural network application can provide a better classification of diagnosis results, reliability and accuracy. This technique is suitable for the mechanical vibration fault diagnosis applications of steam turbine and gas turbine.

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