The　boom　is　the　key　load-bearing　component　of　the　crane,　and　its　health　seriously　threatens　the　service　performance　of　the　crane.　In　order　to　ensure　the　safe　production　of　cranes,　nondestructive　testing　(NDT)　and　structural　health　monitoring　(SHM)　of　boom　become　more　and　more　urgent　and　important.　In　this　paper,　the　intelligent　defect　location　algorithm　based　on　helical　guided　waves　is　applied　to　the　weld　defect　detection　of　U-shaped　boom.　Intelligent　defect　location　algorithm　is　an　imaging　algorithm　that　combines　ellipse　imaging　principle,　evolutionary　algorithm　and　K-means　clustering　algorithm.　This　paper　verifies　the　effectiveness　of　this　algorithm　for　weld　defect　location　of　U-shaped　boom　through　experimental　research.　Firstly,　the　propagation　regularity　of　helical　guided　waves　in　the　U-shaped　boom　structure　is　studied.　In　addition,　the　elliptical　imaging　algorithm　is　used　to　image　and　analyze　the　weld　defects　in　the　U-shaped　boom,　and　the　location　of　the　defects　is　preliminarily　determined.　The　defect　location　analysis　of　weld　defects　is　carried　out　by　using　the　intelligent　defect　location　algorithm.　By　comparing　the　imaging　results　of　the　two　methods,　it　is　found　that　the　intelligent　defect　location　algorithm　has　higher　resolution　and　can　effectively　improve　the　defect　location　accuracy.　This　algorithm　provides　a　tool　for　health　monitoring　of　special-shaped　structures　based　on　guided　waves.