{"id":"W3014912916","doi":"10.21595/vp.2020.21334","title":"Artificial neural network based fault diagnostics for three phase induction motors under similar operating conditions","year":2020,"lang":"en","type":"article","venue":"Vibroengineering PROCEDIA","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Indian Institute of Technology Guwahati","keywords":"Fault (geology); Stator; Rotor (electric); Vibration; Induction motor; Artificial neural network; Bearing (navigation); Engineering; Control theory (sociology); Fault indicator; Fault Simulator; Stuck-at fault; Computer science; Fault detection and isolation; Actuator; Artificial intelligence; Acoustics; Voltage; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001061469,0.0003828568,0.0003241075,0.0001092392,0.0001571527,0.0001132784,0.0002194741,0.0001683975,0.00003875663],"category_scores_gemma":[0.0004874314,0.0004336303,0.0001228579,0.0004592475,0.00002941205,0.0002712658,0.00003361871,0.0003875707,0.000009549844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007967101,"about_ca_system_score_gemma":0.00003220613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003507883,"about_ca_topic_score_gemma":0.00001098726,"domain_scores_codex":[0.9984325,0.00001120873,0.0004631959,0.0003478932,0.0002007197,0.0005445102],"domain_scores_gemma":[0.9991277,0.000289158,0.00005022325,0.0002017063,0.00009049301,0.0002407108],"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":[0.00001011791,0.0000435911,0.0002458281,0.000268962,0.00003804183,0.000004125733,0.00007590196,0.9749382,0.01172464,0.0004704441,0.01017009,0.002010043],"study_design_scores_gemma":[0.0004392827,0.0002181427,0.0003930893,0.00007244045,0.00005792613,0.00000281068,0.0000147802,0.9746249,0.02168888,0.0002770022,0.001776297,0.0004344741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1978556,0.0002340244,0.7951202,0.0009597366,0.0007956291,0.001340771,0.0001954536,0.003445961,0.00005262771],"genre_scores_gemma":[0.9733592,0.00001850536,0.02329361,0.0004406571,0.001641852,0.0008244475,0.0002519873,0.0001685111,0.000001265731],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7755036,"threshold_uncertainty_score":0.9998115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03042728128979024,"score_gpt":0.2888588415716219,"score_spread":0.2584315602818317,"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."}}