This invention relates to a method, apparatus, equipment, and medium for predicting deformation during the
assembly of
diesel engine connecting rods, belonging to the field of mechanical
assembly technology. The method acquires multi-dimensional
assembly data during the assembly process of marine
diesel engine connecting rods. Based on assembly
process knowledge, the multi-dimensional assembly data is weighted to obtain a weighted input vector set. A pre-trained
Bayesian network model is used to infer the deformation
prediction probability distribution from the weighted input vector set.
Statistical analysis is performed on the deformation
prediction probability distribution to obtain deformation trend characteristics and distribution dispersion characteristics. Key deformation risk factors are identified based on these characteristics. A
diesel engine connecting rod assembly deformation prediction report is generated based on the deformation
prediction probability distribution, deformation trend characteristics, distribution dispersion characteristics, and key deformation risk factors. This invention improves the assembly quality and product reliability of marine diesel engine connecting rods.