{"id":"W1982500216","doi":"10.1260/0309-524x.34.4.375","title":"Vibration Analysis of 2.3 MW Wind Turbine Operation Using the Discrete Wavelet Transform","year":2010,"lang":"en","type":"article","venue":"Wind Engineering","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Turbine; Vibration; Wind power; Wavelet; Discrete wavelet transform; Downtime; Tower; Rotor (electric); Daubechies wavelet; Energy (signal processing); Engineering; Continuous wavelet transform; Wavelet transform; Computer science; Acoustics; Structural engineering; Mathematics; Reliability engineering; Mechanical engineering; Electrical engineering; Artificial intelligence; Statistics; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001686135,0.0002461202,0.0001980608,0.0004629735,0.0001022908,0.0001695833,0.000112296,0.0002200637,0.001039781],"category_scores_gemma":[0.0004248623,0.00007767139,0.000155342,0.0005426704,0.0001155858,0.0001669286,0.00009767404,0.0001938025,0.0002270044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007304286,"about_ca_system_score_gemma":0.0001084865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007548465,"about_ca_topic_score_gemma":0.0007554978,"domain_scores_codex":[0.9999162,0.000007845028,0.000004173678,0.00001378462,0.00004985546,0.000008129566],"domain_scores_gemma":[0.9998949,0.00003851329,0.00001283272,0.00001013599,0.00003640097,0.000007212463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004565469,0.0001081629,0.008151649,0.0001295897,0.0000308496,0.0005199053,0.0002296338,0.0132256,0.8099592,0.0005371373,0.0008936836,0.1657581],"study_design_scores_gemma":[0.00005795314,0.001424789,0.4074295,0.00004407312,0.00006509077,0.00190316,0.0003866187,0.395714,0.1861247,0.001202262,0.005549859,0.00009802727],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.871152,0.0001716219,0.1263301,0.00007673546,0.00002757994,0.00003729776,0.0004009795,0.0002965465,0.001507087],"genre_scores_gemma":[0.9729073,0.0001103276,0.02577976,0.0000108567,0.000009561638,0.00001991775,0.000342168,0.00002621647,0.0007939134],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001039781,"threshold_uncertainty_score":0.003478408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01074470437520319,"score_gpt":0.2540157516184873,"score_spread":0.2432710472432841,"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."}}