{"id":"W4249499863","doi":"10.1115/1.4049778","title":"Novel Cyclo-Nonstationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions","year":2021,"lang":"en","type":"article","venue":"Journal of Engineering for Gas Turbines and Power","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Cyclostationary process; Vibration; Frequency domain; Rolling-element bearing; Condition monitoring; Computer science; Realization (probability); Process (computing); Engineering; Channel (broadcasting); Mathematics; Acoustics; Electrical engineering; Telecommunications; Statistics; Physics","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":[0.0003198253,0.0005408994,0.0003790286,0.002174952,0.0001544357,0.0005789486,0.0002867745,0.0005245356,0.0008699031],"category_scores_gemma":[0.0008262375,0.0001156017,0.0002261317,0.001267194,0.0002086518,0.0005049071,0.0002701039,0.0003619091,0.0003850425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001476407,"about_ca_system_score_gemma":0.0001389094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005294681,"about_ca_topic_score_gemma":0.0006061791,"domain_scores_codex":[0.9997337,0.00003592638,0.00001604029,0.00006761181,0.0001206558,0.00002594911],"domain_scores_gemma":[0.999534,0.000122813,0.0001373906,0.00003107899,0.00014885,0.0000258722],"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":[0.001758678,0.0005424782,0.05876762,0.0009878189,0.0002450307,0.001130072,0.0004183337,0.07374815,0.3402254,0.004907447,0.007063355,0.5102057],"study_design_scores_gemma":[0.00003517379,0.000685592,0.09570799,0.00007714452,0.0001716237,0.0006786336,0.0002190006,0.8325688,0.0626637,0.001797219,0.005303522,0.00009159234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4679974,0.002942388,0.5191419,0.0002535506,0.0004290464,0.0001350086,0.001073834,0.001427836,0.006599206],"genre_scores_gemma":[0.9724606,0.0006735706,0.02515281,0.00005231806,0.000122022,0.00004019709,0.0003897186,0.00002766173,0.001081062],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002174952,"threshold_uncertainty_score":0.002910078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01011012809886813,"score_gpt":0.2767523482400129,"score_spread":0.2666422201411448,"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."}}