It　is　difficult　to　quantitatively　detect　defects　by　using　the　time　domain　or　frequency　domain　features　of　Lamb　wave　signals　due　to　their　dispersion　and　multimodal　characteristics.　Therefore,　it　is　important　to　discover　an　intrinsical　parameter　of　Lamb　waves　that　could　be　used　as　a　damage　sensitive　feature.　In　this　paper,　quantitative　defect　detection　in　aluminium　plates　is　carried　out　by　means　of　wavenumber　analysis　approach.　The　wavenumber　of　excited　Lamb　wave　mode　is　a　fixed　value,　given　a　frequency,　a　thickness　and　material　properties　of　the　target　plate.　When　Lamb　waves　propagate　to　the　structural　discontinuity,　new　wavenumber　components　are　created　by　abrupt　wavefield　change.　The　new　wavenumber　components　can　be　identified　in　the　frequency-wavenumber　domain.　To　estimate　spatially　dependent　wavenumber　values,　a　short-space　two-dimensional　Fourier　transform(FT)　method　is　presented　for　processing　wavefield　data　of　Lamb　waves.　The　results　can　be　used　to　determine　the　location,　size　and　depth　of　rectangular　notch.　The　analysis　techniques　are　demonstrated　using　simulation　examples　of　an　aluminium　plate　with　a　rectangular　notch.　Then,　the　wavenumber　analysis　method　is　applied　to　simulation　data　that　are　obtained　through　a　range　of　notch　depths　and　widths.　The　results　are　analyzed　and　rules　of　the　technique　with　regards　to　estimating　notch　depth　are　determined.　Based　on　simulation　results,　guidelines　for　using　the　technique　are　developed.　Finally,　experimental　wavefield　data　are　obtained　in　aluminium　plates　with　rectangular　notches　by　a　full　non-contact　transceiving　method,　i.e.,　laser-laser　method.　Band-pass　filtering　combined　with　continuous　wavelet　transform　is　used　to　extract　a　certain　frequency　component　from　the　full　laser-induced　wavefield　with　wide　band.　Short-space　two-dimensional　FT　method　is　used　for　further　processing　full　wavefield　data　at　a　certain　frequency　to　estimate　spatially　dependent　wavenumber　values.　The　consistency　of　simulation　and　experimental　results　shows　the　effectiveness　of　proposed　wavenumber　method　for　quantitative　rectangular　notch　detection.　©　2018,　Editorial　Department　of　Transactions　of　NUAA.　All　right　reserved.