Effect assessment of electromagnetic pulse at equipment level based on bayesian method

Normally, very limited data can be collected during the electromagnetic effect experiments. So it is hard to fit effect threshold curve based on classical mathematical statistics. This paper employs Bayesian mathematical statistics to fit the data of pipeline Supervisory Control and Data Acquisition systems Master Control Set client effect experiment. We choose Weibull model and normal model as the hypothesis models, and calculate the model parameters prior distribution, likelihood function and posteriori distribution orderly. After tests of goodness of fit, we find that the Weibull model with shape parameter equals 8.87 and scale parameter equals 21.11 is more suitable for effects evaluation based on BIC calculated result, providing a more reliable threshold probability distribution for effect assessment of electromagnetic pulse at equipment level.