{"id":"W4386825461","doi":"10.1109/tim.2023.3316705","title":"Synchro-Reassigned Extracting Transform: An Effective Tool for Rotating Machinery Fault Diagnosis Under Varying Speed Condition","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Science Foundation of Hubei Province; National Natural Science Foundation of China","keywords":"Synchro; Time–frequency analysis; Vibration; Fault (geology); Energy (signal processing); Noise (video); Instantaneous phase; Computer science; Bearing (navigation); Signal processing; Condition monitoring; Engineering; Turbine; Control theory (sociology); Electronic engineering; Artificial intelligence; Acoustics; Computer vision; Mathematics","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":[0.0006329404,0.0002938724,0.0002348876,0.0003564775,0.000399557,0.0001167112,0.00007644669,0.0001082878,0.00005530512],"category_scores_gemma":[0.00001905094,0.0003161788,0.0001096187,0.0003005078,0.00002839197,0.0006122271,7.532294e-7,0.0002184378,0.000009974295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003107496,"about_ca_system_score_gemma":0.00001869266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000679726,"about_ca_topic_score_gemma":0.00009958286,"domain_scores_codex":[0.9983805,0.00009040279,0.0004156002,0.0003450902,0.0004456681,0.0003227566],"domain_scores_gemma":[0.9993217,0.0002423141,0.00006949245,0.0001512025,0.0001025584,0.0001127417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008623749,0.0001946986,0.0002650693,0.0003086974,0.0001984493,0.000001969574,0.0009529477,0.1590878,0.0890653,0.00005071851,0.0001675192,0.7496206],"study_design_scores_gemma":[0.003017199,0.0005593318,0.005305395,0.0003838754,0.000227822,0.000009995719,0.000572337,0.3323322,0.6563657,0.0004401164,0.000136182,0.0006498361],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5265073,0.00001536162,0.4700107,0.0001219898,0.0004085528,0.001689752,0.00008919547,0.001005074,0.0001520849],"genre_scores_gemma":[0.993121,0.0001340643,0.003624241,0.0001276051,0.00005380393,0.00278312,0.00007517137,0.00007131093,0.000009647868],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7489707,"threshold_uncertainty_score":0.999929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03097183954556576,"score_gpt":0.3090988167432182,"score_spread":0.2781269771976524,"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."}}