{"id":"W3158497246","doi":"10.1109/access.2021.3076149","title":"Fault Diagnosis for Variable Frequency Drive-Fed Induction Motors Using Wavelet Packet Decomposition and Greedy-Gradient Max-Cut Learning","year":2021,"lang":"en","type":"article","venue":"IEEE Access","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Stator; Induction motor; Wavelet packet decomposition; Control theory (sociology); Computer science; Wavelet; Fault (geology); Wavelet transform; Algorithm; Artificial intelligence; Pattern recognition (psychology); Engineering; Voltage","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006753535,0.0005583335,0.0005794007,0.0008011578,0.0002405156,0.0004546774,0.0006649554,0.000632556,0.0004774909],"category_scores_gemma":[0.001701467,0.0002505677,0.0003810574,0.0004418893,0.0003399101,0.000628506,0.0003361313,0.0005371466,0.0001604191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004392662,"about_ca_system_score_gemma":0.0004470047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001619953,"about_ca_topic_score_gemma":0.001505897,"domain_scores_codex":[0.9997018,0.00004906484,0.00002023652,0.00007033887,0.0001262331,0.00003233772],"domain_scores_gemma":[0.9993269,0.0002864896,0.000107194,0.00005095201,0.0002053505,0.00002309246],"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":[0.0002977326,0.0001519573,0.004420826,0.0001528057,0.00006254179,0.0002344527,0.0001161722,0.2949703,0.02983654,0.002517695,0.001650659,0.6655883],"study_design_scores_gemma":[0.00000454854,0.00004285571,0.0008150485,0.000003776458,0.000005104073,0.00005144279,0.00001205359,0.9936032,0.004457534,0.0008135509,0.0001867775,0.000004046543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0382636,0.00009052323,0.9608345,0.00005707111,0.00001114893,0.00002749997,0.0000237296,0.0004037476,0.0002881125],"genre_scores_gemma":[0.6456882,0.0001001237,0.3531474,0.00004617936,0.00001259545,0.00005620395,0.0001729811,0.00005655084,0.0007196558],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001619953,"threshold_uncertainty_score":0.00357163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02479463900561484,"score_gpt":0.3208666518037185,"score_spread":0.2960720127981037,"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."}}