{"id":"W2902838804","doi":"10.1109/ias.2018.8544679","title":"Experimental Investigation of Machine Learning Based Fault Diagnosis for Induction Motors","year":2018,"lang":"en","type":"article","venue":"","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Stator; Induction motor; Fault (geology); Computer science; Feature extraction; Vibration; Wavelet; SIGNAL (programming language); Discrete wavelet transform; Wavelet transform; Control engineering; Signal processing; Artificial intelligence; Pattern recognition (psychology); Engineering; Digital signal processing; Voltage; Acoustics; Mechanical engineering; Electrical engineering","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":[0.0006726973,0.000396908,0.0003809669,0.0005058756,0.0002640832,0.0001673453,0.000562102,0.0006429789,0.001158002],"category_scores_gemma":[0.002049772,0.0001520717,0.0001665989,0.0003373491,0.0004450222,0.000440406,0.0002298021,0.0003096354,0.000182401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002314713,"about_ca_system_score_gemma":0.0001230155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005025929,"about_ca_topic_score_gemma":0.0005881116,"domain_scores_codex":[0.9995453,0.00009442191,0.0000467065,0.0000697054,0.0002009129,0.00004301508],"domain_scores_gemma":[0.9987122,0.000572068,0.000146593,0.0001631632,0.0003581936,0.00004776624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001340896,0.0007012165,0.005783942,0.0008836211,0.00005574584,0.0003537856,0.0002351397,0.0171939,0.8950911,0.0006465666,0.0003525803,0.0773614],"study_design_scores_gemma":[0.0001327616,0.005830561,0.02013012,0.00005227256,0.00006108066,0.0005696327,0.0001469598,0.1400026,0.8305283,0.0005576115,0.001951787,0.00003625835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.930521,0.0003736989,0.0670984,0.0001096754,0.00008219448,0.0001004537,0.0001684729,0.000420515,0.001125681],"genre_scores_gemma":[0.9865427,0.0001022057,0.01274777,0.00001775877,0.000008750561,0.00003339408,0.0001120954,0.000009769808,0.0004256626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001158002,"threshold_uncertainty_score":0.003873885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01864834895362084,"score_gpt":0.2843638345876554,"score_spread":0.2657154856340346,"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."}}