Continuous monitoring of fatigue process with surface wave resonance: In the case of rotating bending fatigue

2016 ◽  
Vol 140 (4) ◽  
pp. 3202-3202
Author(s):  
Hirao Masahiko
Keyword(s):  
Surface Wave ◽  
Continuous Monitoring ◽  
Bending Fatigue ◽  
Fatigue Process ◽  
Wave Resonance ◽  
Rotating Bending Fatigue ◽  
Rotating Bending

Ultrasonic Fatigue of Radical Nitrided Ni-Base Superalloy

2009 ◽  
Vol 417-418 ◽  
pp. 209-212
Author(s):  
K. Yamane ◽  
Norio Kawagoishi ◽  
Kazuhiro Morino ◽  
K. Fukada
Keyword(s):  
Fatigue Strength ◽  
Fracture Surface ◽  
Fatigue Tests ◽  
Loading Frequency ◽  
Bending Fatigue ◽  
Fatigue Process ◽  
Rotating Bending Fatigue ◽  
Ultrasonic Fatigue ◽  
Rotating Bending ◽  
Base Superalloy

Ultrasonic and rotating bending fatigue tests were carried out for aged and nitrided Ni-base super alloys to investigate the effects of loading frequency and nitriding on fatigue strength. Loading frequencies were 19.5 kHz under ultrasonic and 50 Hz under rotating bending, respectively. Fatigue strength under ultrasonic was higher than that under rotating bending in both alloys. Moreover, in both tests, fatigue strength was improved by nitriding. The increase in fatigue strength by nitriding was large in ultrasonic fatigue. These results were discussed through the successive observation of fatigue process at specimen surface and fracture surface observation.

On a New Rotating Bending Fatigue Testing Machine

1966 ◽  
Vol 15 (148) ◽  
pp. 49-54
Author(s):  
Minoru KAWAMOTO ◽  
Katsumi SUMIHIRO ◽  
Koji KIDA
Keyword(s):  
Fatigue Testing ◽  
Testing Machine ◽  
Bending Fatigue ◽  
Rotating Bending Fatigue ◽  
Rotating Bending

A FAST ROTATING BENDING FATIGUE TEST MACHINE

2017 ◽  
Author(s):  
Marco Antonio Meggiolaro ◽  
Jaime T P Castro ◽  
Rodrigo de Moura Nogueira
Keyword(s):  
Fatigue Test ◽  
Test Machine ◽  
Bending Fatigue ◽  
Bending Fatigue Test ◽  
Rotating Bending Fatigue ◽  
Rotating Bending ◽  
Fast Rotating

A Study onP-S-NCurve for Rotating Bending Fatigue Test for Bearing Steel

2008 ◽  
Vol 51 (2) ◽  
pp. 166-172 ◽  
Author(s):  
Katsuji Tosha ◽  
Daisuke Ueda ◽  
Hirokazu Shimoda ◽  
Shigeo Shimizu
Keyword(s):  
Fatigue Test ◽  
Bearing Steel ◽  
Bending Fatigue ◽  
Bending Fatigue Test ◽  
Rotating Bending Fatigue ◽  
Rotating Bending

Application of ANN Back-Propagation for Fracture Design Parameters in Extra-Low Cycle Rotating Bending Fatigue

2009 ◽  
Vol 610-613 ◽  
pp. 450-453
Author(s):  
Hong Yan Duan ◽  
You Tang Li ◽  
Jin Zhang ◽  
Gui Ping He
Keyword(s):  
Neural Network ◽  
Neural Network Model ◽  
Back Propagation ◽  
Training Data ◽  
Design Parameters ◽  
Ann Model ◽  
Bending Fatigue ◽  
The Neural Network ◽  
Rotating Bending Fatigue ◽  
Rotating Bending

The fracture problems of ecomaterial (aluminum alloyed cast iron) under extra-low cycle rotating bending fatigue loading were studied using artificial neural networks (ANN) in this paper. The training data were used in the formation of training set of ANN. The ANN model exhibited excellent in results comparison with the experimental results. It was concluded that predicted fracture design parameters by the trained neural network model seem more reasonable compared to approximate methods. It is possible to claim that, ANN is fairly promising prediction technique if properly used. Training ANN model was introduced at first. And then the Training data for the development of the neural network model was obtained from the experiments. The input parameters, notch depth, the presetting deflection and tip radius of the notch, and the output parameters, the cycle times of fracture were used during the network training. The neural network architecture is designed. The ANN model was developed using back propagation architecture with three layers jump connections, where every layer was connected or linked to every previous layer. The number of hidden neurons was determined according to special formula. The performance of system is summarized at last. In order to facilitate the comparisons of predicted values, the error evaluation and mean relative error are obtained. The result show that the training model has good performance, and the experimental data and predicted data from ANN are in good coherence.

High Cycle Fatigue Behavior of Thermally Oxidized Ti6Al4V Alloy

2007 ◽  
Vol 561-565 ◽  
pp. 2179-2182 ◽  
Author(s):  
Mehmet Cingi ◽  
Onur Meydanoglu ◽  
Hasan Guleryuz ◽  
Murat Baydogan ◽  
Huseyin Cimenoglu ◽  
...  
Keyword(s):  
Fatigue Strength ◽  
Yield Strength ◽  
Thermal Oxidation ◽  
Fatigue Behavior ◽  
Surface Hardness ◽  
Ti6al4v Alloy ◽  
Bending Fatigue ◽  
Rotating Bending Fatigue ◽  
Rotating Bending ◽  
Bending Fatigue Strength

In this study, the effect of thermal oxidation on the high cycle rotating bending fatigue behavior of Ti6Al4V alloy was investigated. Oxidation, which was performed at 600°C for 60 h in air, considerably improved the surface hardness and particularly the yield strength of the alloy without scarifying the tensile ductility. Unfortunately, the rotating bending fatigue strength at 5x106 cycles decreased from about 610 MPa to about 400 MPa upon oxidation. Thus, thermal oxidation leaded a reduction in the fatigue strength of around 34%, while improving the surface hardness (HV0.1) and yield strength 85 % and 36 %, respectively.

scholarly journals Effects of Case Depth and Notch Shape on the Rotating Bending Fatigue Properties of Carburized Steel

1980 ◽  
Vol 66 (3) ◽  
pp. 410-417 ◽  
Author(s):  
Tôru FURUKAWA ◽  
Shizuyo KONUMA ◽  
Hideyasu SAKANIWA ◽  
Tadashi KASUYA
Keyword(s):  
Case Depth ◽  
Fatigue Properties ◽  
Bending Fatigue ◽  
Carburized Steel ◽  
Rotating Bending Fatigue ◽  
Rotating Bending
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