Abstract: A method for accelerated editing of random load spectra based on multi-domain information fusion is proposed. The energy distribution, damage distribution and peak distribution of the load spectra can serve as important sources of evidence for accelerated durability editing. Based on the Dempster-Shafer's evidence theory, the multi-domain information of load spectra is fused to obtain a belief function that can make decisions on whether to retain or delete load points. Taking the compression ratio of the load spectra before and after editing as the objective function, the threshold of the belief function as the design variable, and the errors of statistical parameters (root mean square and kurtosis coefficient) and the damage retention amount as the constraint conditions, the genetic algorithm is used to optimize and solve the threshold of the fused belief function. By taking the load points exceeding the threshold as a benchmark and using the envelope damage segment identification method, the signal segments that contribute more to the damage are identified, so as to obtain an edited load spectrum with basically the same effect as the original load spectrum. Taking the service load spectrum of the rear mount of the powertrain as the object, the accelerated durability editing process is carried out. By comparing the relevant parameters of the load spectra before and after editing, the results show that: the proposed accelerated editing method for random load spectra based on multi-domain information fusion can ensure that the statistical parameter errors of the load spectra before and after editing do not exceed 10% and the damage parameters are greater than 95%. Compared with traditional methods, the obtained edited load spectrum has advantages in terms of the deviations of statistical parameters (root mean square and kurtosis coefficient) and the damage retention amount.