A system that calculates the stress concentration factor of the crankpin fillet from six characteristic dimensions of the crankshaft was developed using an artificial neural network. The learning database was constructed based on the finite element analysis, and an “adaptive transfer function algorithm” was used for the learning calculations. The calculation errors of the stress concentration factors applied to crankshafts of small utility engines and outboard motors were found to be within -6.9 to +6.3% of the measured values. With this system, designers can calculate the stress concentrated at crankpin fillets precisely in a short time.
Stress Calculation of Crankshaft Using Artificial Neural Network
Sae Technical Papers
Small Engine Technology Conference & Exposition ; 1995
1995-09-01
Conference paper
English
Stress calculation of crankshaft using artificial neural network
Automotive engineering | 1995
|Enhanced crankshaft stress calculation method and fatigue life evaluation
Automotive engineering | 1998
|A convenient calculation method on bending stress of crankshaft
Automotive engineering | 1980
|Dynamic crankshaft stress calculation using a combination of MSS and FEA
Automotive engineering | 2000
|Crankshaft Load Calculation an Indeterminate Method
British Library Conference Proceedings | 1992
|