Core fucosylation (CF) is a special glycosylation pattern of proteins that has a strong relationship with cancer. The Food and Drug Administration (FDA) has approved the core fucosylated α-fetoprotein as a biomarker for the early diagnosis of hepatocellular carcinoma (HCC). The technology for identifying core fucosylated proteins has significant practical value. The major method for core fucosylated glycoprotein/glycopeptide analysis is neutral loss-based MS(3) scanning under collision-induced dissociation (CID) by ion trap mass spectrometry. However, due to the limited speed and low resolution of the MS(3) scan mode, it is difficult to achieve high-throughput, with only dozens of core fucosylated proteins identified in a single run. In this work, we developed a novel strategy for the identification of CF glycopeptides at a large scale, integrating the stepped fragmentation function, one novel feature of quadrupole-orbitrap mass spectrometry, with "glycan diagnostic ion"-based spectrum optimization. By using stepped fragmentation, we were able to obtain both highly accurate glycan and peptide information of a simplified CF glycopeptide in one spectrum. Moreover, the spectrum could be recorded with the same high speed as the conventional MS(2) scan. By using the "glycan diagnostic ion"-based spectrum refinement method, the efficiency of the CF glycopeptide discovery was significantly improved. We demonstrated the feasibility and reproducibility of our method by analyzing CF glycoproteomes of mouse liver tissue and HeLa cell samples spiked with standard CF glycoprotein. In total, 1364 and 856 CF glycopeptides belonging to 702 and 449 CF glycoproteins were identified, respectively, within a 78-min gradient analysis, which was approximately a 7-fold increase in the identification efficiency of CF glycopeptides compared to the currently used method. In this work, we took core fucosylated glycopeptides as a practical example to demonstrate the great potential of our novel method for use in glycoproteome analysis, and we also anticipate using the flexible novel method in other research fields.