{"id":"W4379389214","doi":"10.37965/jdmd.2023.231","title":"Wavelet Denoising Applied to Hardware Redundant Systems for Rolling Element Bearing Fault Detection","year":2023,"lang":"en","type":"article","venue":"Journal of Dynamics Monitoring and Diagnostics","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Noise reduction; Fault detection and isolation; Residual; Vibration; Computer science; Wavelet; Fault (geology); Noise (video); Redundancy (engineering); Reduction (mathematics); SIGNAL (programming language); Wavelet transform; Signature (topology); Bearing (navigation); Computer hardware; Artificial intelligence; Algorithm; Mathematics; Acoustics","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":[0.0002512369,0.0001237661,0.0001958383,0.000196065,0.000154509,0.0001237443,0.00007037239,0.0000597445,8.354498e-8],"category_scores_gemma":[0.000264671,0.0001263327,0.00003476804,0.0002064817,0.000005534015,0.0000997294,0.0000256476,0.0001592448,6.856592e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001604526,"about_ca_system_score_gemma":0.0000125298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004004901,"about_ca_topic_score_gemma":0.000002279459,"domain_scores_codex":[0.9991561,0.00000493501,0.0003585687,0.00009980208,0.0001638194,0.000216798],"domain_scores_gemma":[0.9992857,0.0002748106,0.000117394,0.00006671139,0.0001523434,0.0001030247],"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":[0.00001745417,0.000005442397,0.0005456473,0.000201474,0.0000347381,0.000005035845,0.0002817515,0.9777441,0.0008717751,0.00006904249,0.00001587331,0.02020765],"study_design_scores_gemma":[0.0004217113,0.000125498,0.0007529741,0.0004639863,0.00007230778,0.00001808294,0.0008395936,0.9931735,0.003253172,0.0001766292,0.0005130218,0.00018946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.277968,0.0006043253,0.7194313,0.00001935144,0.001710859,0.0001461219,0.00001020458,0.00009353197,0.00001629541],"genre_scores_gemma":[0.9811652,0.002639567,0.01547661,0.000002542209,0.0006346701,0.00001696239,0.000006517237,0.00004533637,0.00001261143],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7039546,"threshold_uncertainty_score":0.51517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0104960039154238,"score_gpt":0.2491122550408661,"score_spread":0.2386162511254423,"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."}}