{"id":"W2045790067","doi":"10.1016/j.ymssp.2014.03.006","title":"Damage detection method for wind turbine blades based on dynamics analysis and mode shape difference curvature information","year":2014,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":101,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Turbine blade; Finite element method; Structural engineering; Modal analysis; Aerodynamics; Lift (data mining); Turbine; Normal mode; Blade (archaeology); Curvature; Engineering; Modal; Acoustics; Computer science; Vibration; Mechanical engineering; Aerospace engineering; Materials science; Mathematics; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003597419,0.0001580439,0.0002741433,0.0001591373,0.0001571995,0.000161496,0.00006269395,0.000175083,8.118988e-7],"category_scores_gemma":[0.00004285703,0.0001286184,0.00003508603,0.0002326605,0.00001003407,0.0001995028,0.00001356155,0.0001847694,1.140202e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007454109,"about_ca_system_score_gemma":0.000006557779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007063127,"about_ca_topic_score_gemma":0.00001790673,"domain_scores_codex":[0.9991823,0.00004934166,0.0002753083,0.0001617689,0.0001514794,0.0001798473],"domain_scores_gemma":[0.9995136,0.0001633178,0.00008119056,0.00008770245,0.00006749461,0.00008670576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008130926,0.000007113998,0.0002367712,0.002568259,0.00005449097,2.568636e-7,0.0001489884,0.04646321,0.009469162,0.0007878776,0.000002715553,0.9401798],"study_design_scores_gemma":[0.0001750972,0.0001229172,0.002299414,0.0001636095,0.00008415559,0.000001859617,0.00002331986,0.9932349,0.003017803,0.0006912783,0.00003694403,0.0001487131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2586805,0.00004902246,0.7407772,0.00001844948,0.00006318239,0.0002014701,0.0000110571,0.0001854994,0.00001368359],"genre_scores_gemma":[0.9836976,0.000003512079,0.01610363,0.00002826196,0.00009870972,0.00003315591,0.00001843286,0.00001409872,0.00000258422],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9467717,"threshold_uncertainty_score":0.5244907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01079491307568693,"score_gpt":0.2711246177177527,"score_spread":0.2603297046420658,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}