{"id":"W4284882312","doi":"10.1016/j.ress.2022.108714","title":"Attention-based multiscale denoising residual convolutional neural networks for fault diagnosis of rotating machinery","year":2022,"lang":"en","type":"article","venue":"Reliability Engineering & System Safety","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":108,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Convolutional neural network; Residual; Noise reduction; Artificial intelligence; Computer science; Fault (geology); Pattern recognition (psychology); Artificial neural network; Algorithm; Geology","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":[0.0003809074,0.0004665685,0.0004880332,0.0003711167,0.0001502343,0.0002476287,0.0005670603,0.0005557511,0.0009475356],"category_scores_gemma":[0.0009271235,0.0001656313,0.0004236593,0.0002700398,0.0001973583,0.0004546816,0.0005205686,0.0005264389,0.0001983882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003756693,"about_ca_system_score_gemma":0.0004366511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00871201,"about_ca_topic_score_gemma":0.009762583,"domain_scores_codex":[0.9998834,0.00001817115,0.000005811543,0.00003459051,0.00002947888,0.00002849563],"domain_scores_gemma":[0.9997515,0.0001028905,0.00003137599,0.000022602,0.00007816344,0.00001342872],"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":[0.0004515297,0.0001577959,0.001872189,0.000128181,0.0001073029,0.0001620025,0.00009127302,0.4193535,0.0695328,0.004330982,0.002796711,0.5010158],"study_design_scores_gemma":[0.000001844482,0.00002075585,0.000330849,0.000002010766,0.000009954711,0.000008548627,0.000002787548,0.9969206,0.002196779,0.0003957041,0.0001083712,0.000001930105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2121101,0.001362363,0.7825558,0.0003467491,0.0001036156,0.00002903032,0.0001288583,0.001009695,0.002353927],"genre_scores_gemma":[0.9451709,0.0002991961,0.05145545,0.00009394193,0.00005197316,0.00001373128,0.0001925603,0.00004787435,0.002674429],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00871201,"threshold_uncertainty_score":0.0173226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006186896598973588,"score_gpt":0.2273227308317765,"score_spread":0.2211358342328029,"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."}}