Aiming　at　the　misdiagnosis　caused　by　extracting　the　non-fault　features　using　Lempel-Ziv　algorithm,　a　quantitative　trend　fault　diagnosis　method　of　a　rolling　bearing　based　on　Sparsogram　and　Lempel-Ziv　is　proposed　in　this　paper.　The　approximate　linear　relationships　between　Lempel-Ziv　and　the　fault　sizes　of　inner　and　outer　races　are　simulated　with　a　theoretical　model　of　rolling　bearings.　Then,　the　fault　characteristic　of　experimental　signal　of　bearing　inner　and　outer　race　in　different　severity　is　extracted　by　Sparsogram　algorithm,　and　the　frequency　band　is　selected　which　reflects　the　fault　characteristic　mostly,　and　the　Lempel-Ziv　complexity　index　of　the　frequency　band　is　calculated.　This　method　can　avoid　the　misdiagnosis　caused　by　extracting　non-fault　features.　Comparing　with　direct　calculation　of　Lempel-Ziv　value,　the　performance　is　much　better　on　the　quantitative　diagnosis　of　a　defective　bearing.　The　experimental　results　show　that　the　proposed　method　can　realize　the　quantitative　trend　diagnosis　on　defective　bearings.