The　identification　of　optimal　frequency　band　(OFB)　sensitive　to　faults　is　crucial　for　bearing　fault　diagnosis.　In　this　paper,　a　spectral　coherence　cyclic　periodic　index　(SCCP)　optimization-gram　(SCCPgram)　is　proposed.　First,　the　vibration　signal　is　mapped　into　a　two-dimensional　plane　containing　spectral　and　cyclic　frequencies　by　spectral　coherence　theory.　Second,　a　novel　feature　indicator　SCCP　is　developed,　which　fully　explores　the　merits　of　autocorrelation　in　revealing　the　cyclic　information　hidden　in　noise,　and　converts　the　periodic　pattern　of　cyclic　frequency　direction　in　spectral　coherence　into　a　visual　representation,　thus　unveiling　the　fault　components.　Then,　considering　SCCP　as　a　metric,　the　SCCPgram　is　designed　based　on　1/3-binary　tree　filter　bank　to　select　the　OFB.　Finally,　the　spectral　coherence　is　integrated　over　the　OFB　to　generate　improved　envelope　spectrum.　The　proposed　method　is　validated　by　simulation　and　experimental　data,　and　results　show　that　SCCPgram　has　better　performance　compared　with　other　state-of-art　methods.　©　2023