The　appearance　of　repetitive　transients　in　a　vibration　signal　is　one　typical　feature　of　faulty　rolling　element　bearings.　However,　accurate　extraction　of　these　fault-related　characteristic　components　has　always　been　a　challenging　task,　especially　when　there　is　interference　from　large　amplitude　impulsive　noises.　A　frequency　domain　multipoint　kurtosis　(FDMK)-based　fault　diagnosis　method　is　proposed　in　this　paper.　The　multipoint　kurtosis　is　redefined　in　the　frequency　domain　and　the　computational　accuracy　is　improved.　An　envelope　autocorrelation　function　is　also　presented　to　estimate　the　fault　characteristic　frequency,　which　is　used　to　set　the　frequency　hunting　zone　of　the　FDMK.　Then,　the　FDMK,　instead　of　kurtosis,　is　utilized　to　generate　a　fast　kurtogram　and　only　the　optimal　band　with　maximum　FDMK　value　is　selected　for　envelope　analysis.　Negative　interference　from　both　large　amplitude　impulsive　noise　and　shaft　rotational　speed　related　harmonic　components　are　therefore　greatly　reduced.　The　analysis　results　of　simulation　and　experimental　data　verify　the　capability　and　feasibility　of　this　FDMK-based　method.