The　performance　of　singular　value　decomposition　(SVD)　mainly　relies　on　selection　of　the　effective　singular　values.　However,　most　of　the　existing　methods　for　selecting　the　effective　singular　values　have　some　problems　such　as　unsatisfactory　performance　of　denoising.　For　selecting　the　effective　singular　values　more　accurately,　a　novel　energy　diagram　(Egram)　based　SVD　method　is　proposed.　Novelties　of　the　proposed　method　are　divided　into　two　parts.　Firstly,　the　form　of　the　effective　singular　values　is　determined　by　selection　criteria　of　embedding　dimension　of　Hankel　matrix　in　SVD.　The　selection　criteria　are　defined　based　on　the　special　relationship　between　the　form　of　the　effective　singular　values　and　the　embedded　dimension　of　Hankel　matrix　for　the　amplitude　modulation-frequency　modulation　(AM-FM)　signal,　and　the　special　relationship　is　found　that,　when　appropriate　embedding　dimension　is　selected,　the　AM-FM　signal　is　mainly　decomposed　into　two　adjacent　singular　values　with　approximately　equal　numerical　magnitude,　which　are　called　singular　value　pairs　(SVP).　Secondly,　the　Egram　is　developed　to　adaptively　locate　effective　SVP　by　estimating　the　energy　of　frequency　band　and　to　detect　gear　fault.　The　Egram-based　SVD　method　is　verified　using　the　simulated　signal　and　experiment　signal　that　measured　from　the　gearbox　test　bench,　and　analysis　results　show　that　the　form　and　location　of　the　effective　singular　values　that　contains　gear　fault　can　be　determined.　Comparisons　with　the　difference　spectrum,　relative　change　rate　of　singular　values,　relative　change　rate　of　singular　kurtosis　and　fast　Kurtogram　show　that　the　Egram-based　SVD　has　much　better　ability　to　detect　gear　fault.