{"id":"W2898381741","doi":"10.1109/icelmach.2018.8507176","title":"Vold-Kalman Filtering Order Tracking Based Rotor Flux Linkage Monitoring in PMSM","year":2018,"lang":"en","type":"article","venue":"","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Control theory (sociology); Flux linkage; Torque ripple; Torque; Rotor (electric); Direct torque control; Kalman filter; Computer science; Tracking (education); Noise (video); Ripple; Flux (metallurgy); Engineering; Physics; Induction motor; Artificial intelligence; Mechanical 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":[0.000631485,0.0003704087,0.0005617809,0.0005472901,0.0003305442,0.0005134656,0.0004297071,0.0004742368,0.0005156214],"category_scores_gemma":[0.001592812,0.0002903092,0.0003185885,0.0004660724,0.000225091,0.0005869225,0.0002965777,0.0003384944,0.0001640187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000542046,"about_ca_system_score_gemma":0.0005733031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008559557,"about_ca_topic_score_gemma":0.007599473,"domain_scores_codex":[0.9996798,0.00004967535,0.00002968566,0.00008433896,0.0001268449,0.00002969109],"domain_scores_gemma":[0.999656,0.0001308368,0.00006814038,0.00002990146,0.0001019827,0.00001310176],"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":[0.0004392746,0.0001305263,0.008839515,0.0003342241,0.00008783084,0.0001047537,0.0001516938,0.5705825,0.02179776,0.0028204,0.0009999255,0.3937117],"study_design_scores_gemma":[0.00001020695,0.00005132595,0.002206289,0.00001000122,0.000009304585,0.00003428949,0.000008513714,0.9917105,0.004902835,0.0005660622,0.0004787795,0.00001187238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06249245,0.0006206831,0.9343452,0.00009132311,0.00006471154,0.00004252025,0.00008803011,0.000625187,0.001629928],"genre_scores_gemma":[0.9359953,0.0003247489,0.0618977,0.00003383493,0.00001813086,0.00005908124,0.0001287979,0.00002314546,0.001519257],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008559557,"threshold_uncertainty_score":0.01701945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01608219760616048,"score_gpt":0.2902644477365161,"score_spread":0.2741822501303556,"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."}}