{"id":"W2387352252","doi":"10.1177/0309524x16647842","title":"Condition monitoring and fault diagnosis of a small permanent magnet generator","year":2016,"lang":"en","type":"article","venue":"Wind Engineering","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Vibration; Condition monitoring; Wind power; Fault (geology); Wavelet; Turbine; Rotor (electric); Permanent magnet synchronous generator; Engineering; Fault detection and isolation; Magnet; Automotive engineering; Wavelet transform; Continuous wavelet transform; Computer science; Discrete wavelet transform; Acoustics; Mechanical engineering; Electrical engineering; Actuator","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":[0.0002312744,0.0002693623,0.0003795713,0.0004001268,0.0001468257,0.0002098807,0.000400771,0.0004224732,0.0009139887],"category_scores_gemma":[0.0006500646,0.0001245174,0.000109146,0.0001512405,0.0002645184,0.0003228241,0.0001718017,0.000174534,0.0001860495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001285138,"about_ca_system_score_gemma":0.0001188136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003387476,"about_ca_topic_score_gemma":0.0003501062,"domain_scores_codex":[0.9998431,0.00003445473,0.000006157642,0.00004293181,0.00006153571,0.00001181907],"domain_scores_gemma":[0.9995958,0.0002176737,0.00005387428,0.00004322278,0.00005172162,0.0000377313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001103784,0.0002057651,0.009590573,0.0001423979,0.00002338131,0.0008375954,0.0001228548,0.01839821,0.8758597,0.0002724237,0.0004412222,0.09300201],"study_design_scores_gemma":[0.0002378327,0.004914758,0.07982457,0.0000187702,0.00007078607,0.001474231,0.0001401129,0.4674581,0.4429032,0.0009322414,0.001972737,0.00005261227],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9324592,0.0001209321,0.065917,0.00007259394,0.00002587109,0.00005087534,0.00006832837,0.0006742456,0.0006109267],"genre_scores_gemma":[0.9948307,0.0000196722,0.004812854,0.00000526695,0.000004198274,0.000009513488,0.00002244866,0.00000520275,0.0002903695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009139887,"threshold_uncertainty_score":0.003057539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008059902277710841,"score_gpt":0.2254300225980563,"score_spread":0.2173701203203455,"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."}}