{"id":"W2976739695","doi":"10.1016/j.measurement.2019.107069","title":"Incipient fault detection for the planetary gearbox in rotorcraft based on a statistical metric of the analog tachometer signal","year":2019,"lang":"en","type":"article","venue":"Measurement","topic":"Gear and Bearing Dynamics Analysis","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; University of Manitoba","funders":"National Natural Science Foundation of China","keywords":"Tachometer; Fault (geology); Feature (linguistics); SIGNAL (programming language); Fault detection and isolation; Engineering; Noise (video); Vibration; Transmission (telecommunications); Pattern recognition (psychology); Artificial intelligence; Analog signal; Computer science; Acoustics; Telecommunications; Actuator","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":[],"consensus_categories":[],"category_scores_codex":[0.0005910659,0.00008313913,0.00012001,0.0001461002,0.00002714933,0.00001244207,0.0001194916,0.00003319738,0.00003953818],"category_scores_gemma":[0.00004560956,0.00004916801,0.00007388044,0.000300586,0.00001006327,0.000008938838,0.00001130553,0.0001205206,0.000006637132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001225632,"about_ca_system_score_gemma":0.00001481712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001749877,"about_ca_topic_score_gemma":0.0007033742,"domain_scores_codex":[0.9991049,0.00003618228,0.0001678907,0.0001065099,0.0004483256,0.0001361741],"domain_scores_gemma":[0.9995971,0.000112375,0.00002532022,0.0002005417,0.00004505895,0.00001965371],"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":[0.00003566124,0.00004774109,0.01348957,0.00005584934,0.0000792341,3.112443e-7,0.0000319702,0.9734645,0.00794481,0.00001370895,0.00002273821,0.004813835],"study_design_scores_gemma":[0.0002940459,0.00008079419,0.1564455,0.00001717933,0.00004647717,1.297108e-7,0.000009554028,0.8403267,0.002439344,0.00001555067,0.000268978,0.00005574362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6921476,0.00014418,0.3052615,0.00008823731,0.0004324515,0.001337983,0.00006075244,0.00003786223,0.0004895022],"genre_scores_gemma":[0.9996718,0.000001338029,0.0002127554,0.00002971556,0.00001548023,0.00004268236,0.000004295752,0.00001002734,0.00001190038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3075242,"threshold_uncertainty_score":0.2005013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01399406940728466,"score_gpt":0.1947938683490806,"score_spread":0.1807997989417959,"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."}}