{"id":"W4289321238","doi":"10.18280/ejee.240304","title":"Classification of Induction Motor Bearing Failures Through Retro-Propagation Neural Network Algorithm and Adaptive Neuro-Fuzzy Inference System of Type Takagi-Sugeno","year":2022,"lang":"en","type":"article","venue":"European Journal of Electrical Engineering","topic":"Gear and Bearing Dynamics Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bearing (navigation); Artificial neural network; Induction motor; Vibration; Adaptive neuro fuzzy inference system; SIGNAL (programming language); Condition monitoring; Computer science; Control theory (sociology); Fault (geology); Fuzzy logic; Artificial intelligence; Control engineering; Engineering; Algorithm; Fuzzy control system; Acoustics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009916263,0.0005043323,0.0004207469,0.0005571581,0.0002411803,0.000404563,0.0004785218,0.0006265512,0.0004387991],"category_scores_gemma":[0.002073209,0.0002120361,0.000253437,0.0002870352,0.0002617719,0.0005389477,0.0001849817,0.000458352,0.0001173932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003095318,"about_ca_system_score_gemma":0.0003499572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003177089,"about_ca_topic_score_gemma":0.002763735,"domain_scores_codex":[0.9997831,0.00005225093,0.0000198034,0.00004781536,0.00007793106,0.0000191022],"domain_scores_gemma":[0.9993274,0.0003321311,0.0000746519,0.00003572064,0.0002085894,0.00002142469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004700213,0.0002654617,0.00802984,0.0001522732,0.00008951062,0.0001699433,0.0001953282,0.5166541,0.02703432,0.001367976,0.0006177371,0.4449536],"study_design_scores_gemma":[0.000004474982,0.00004566868,0.0007752961,0.000002916031,0.000007635483,0.00001264613,0.00000763857,0.9975529,0.001390241,0.0001416561,0.00005598304,0.000002865644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2537172,0.0003963084,0.744342,0.0001176577,0.00005305638,0.00006455671,0.00002785897,0.0004841283,0.0007972941],"genre_scores_gemma":[0.8788786,0.0001346115,0.1198694,0.0000195614,0.00001784794,0.00006329962,0.00005540406,0.00001201527,0.0009492806],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003177089,"threshold_uncertainty_score":0.006317139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01407690925227864,"score_gpt":0.1979691616468758,"score_spread":0.1838922523945971,"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."}}