Abstract: To improve the efficiency of durability testing and verification of harvesting machinery in laboratory scenarios, this study investigated the accelerated editing method of load spectrum using the operating loads of combine harvester components as an example. The aim was to further improve testing efficiency and reduce testing costs while ensuring consistency in load spectrum loading effects between field tests and laboratory bench tests. Based on the traditional wavelet decomposition-based accelerated editing method, the impact of different wavelet component selections on acceleration effects was discussed. The pseudo-damage ratio threshold was used to filter wavelet components, and the high damage contribution segments in wavelet components were identified using the extreme difference method. Among them, the proposed extreme value difference method extracted peak and valley values from the reconstructed wavelet components, calculated differences between adjacent extreme values, and applied a threshold to discriminate the results, enabling the extraction of specific damage segments. An accelerated load spectrum editing method based on optimized wavelet components was developed. Using the torque load of the feeding system's operating components in a combine harvester as an example, this method was compared with the wavelet decomposition and time-domain damage retention methods. The results indicated that, in traditional wavelet decomposition -based acceleration editing methods, the signal frequency components and statistical characteristics represented by different wavelet components varied. Therefore, indiscriminate damage segment identification for each wavelet component possibly had a negative impact on the acceleration results. The exclusion of specific high-frequency wavelet components from the damage segment calculation was found to have potentially improved the acceleration editing effect. Using the pseudo-damage ratio between each wavelet component and the original load to filter wavelet components is an effective improvement. Compared with the time-domain window damage identification method and the envelope damage segment identification method, the damage segment identification method based on extreme differences proposed in this paper is more precise and flexible in identifying damage segment boundaries. This method ensures the periodicity of load cycles within the extracted load segments while further enhancing the accuracy of damage segment identification. Under the condition where the pseudo-damage retention ratios were nearly consistent, the accelerated editing method based on optimized wavelet components achieved more concise acceleration results. Taking the header auger load as an example, under 95% and 98% pseudo-damage retention ratios, the proposed method improved acceleration effects by 11.95% and 15.72% compared to the traditional wavelet decomposition method. The acceleration editing method based on the optimized wavelet components also demonstrated good applicability to the load of drive shafts in other critical operating components of the feeding system. Compared to traditional methods, the proposed approach increased the signal compression ratios for the reel, header, and conveyor loads by 6.77%, 12.44%, and 20.19%, respectively, under relatively consistent pseudo-damage retention levels. This demonstrated that the processing procedure of the load spectrum accelerated editing method proposed in this study was reasonable and exhibited certain versatility for different operational component loads. The method described in this paper also has potential applications in structural durability accelerated testing scenarios in other industrial fields.