{"id":"https://openalex.org/W4412985149","doi":"https://doi.org/10.1109/ccdc65474.2025.11091208","title":"An Innovative Wavelet Transform Convolutional Approach for Multi-Step Cutterhead Torque Prediction in Shield Tunneling Machines","display_name":"An Innovative Wavelet Transform Convolutional Approach for Multi-Step Cutterhead Torque Prediction in Shield Tunneling Machines","publication_year":2025,"publication_date":"2025-05-16","ids":{"openalex":"https://openalex.org/W4412985149","doi":"https://doi.org/10.1109/ccdc65474.2025.11091208"},"language":"en","primary_location":{"id":"doi:10.1109/ccdc65474.2025.11091208","doi":"https://doi.org/10.1109/ccdc65474.2025.11091208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccdc65474.2025.11091208","pdf_url":null,"source":{"id":"https://openalex.org/S4363607715","display_name":"Chinese Control and Decision Conference (CCDC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 37th Chinese Control and Decision Conference (CCDC)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100394015","display_name":"Sheng Zhang","orcid":"https://orcid.org/0000-0002-3698-2806","observed_orcids":["https://orcid.org/0000-0002-3698-2806","https://orcid.org/0000-0001-6163-7417"]},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Zhang","raw_affiliation_strings":["College of Mechanical Engineering, Donghua University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechanical Engineering, Donghua University,Shanghai,China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101298759","display_name":"Zhuoyang Song","orcid":"https://orcid.org/0009-0001-7013-3488","observed_orcids":["https://orcid.org/0009-0001-7013-3488"]},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuoyang Song","raw_affiliation_strings":["College of Mechanical Engineering, Donghua University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechanical Engineering, Donghua University,Shanghai,China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112411707","display_name":"Xiaoli Yue","orcid":"https://orcid.org/0009-0002-1900-651X","observed_orcids":["https://orcid.org/0009-0002-1900-651X"]},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoli Yue","raw_affiliation_strings":["College of Mechanical Engineering, Donghua University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechanical Engineering, Donghua University,Shanghai,China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shuliang Zhou","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuliang Zhou","raw_affiliation_strings":["General Institute of Design and Research,China Railway Engineering Equipment Group Co., LTD,Zhengzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"General Institute of Design and Research,China Railway Engineering Equipment Group Co., LTD,Zhengzhou,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100334606","display_name":"Liang Chen","orcid":"https://orcid.org/0000-0002-3767-3546","observed_orcids":["https://orcid.org/0000-0002-3767-3546"]},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Chen","raw_affiliation_strings":["College of Mechanical Engineering, Donghua University,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mechanical Engineering, Donghua University,Shanghai,China","institution_ids":["https://openalex.org/I181326427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22438851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"720","last_page":"725"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12482","display_name":"Tunneling and Rock Mechanics","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12482","display_name":"Tunneling and Rock Mechanics","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/shield-tunneling-machine","display_name":"shield tunneling machine","score":0.9139999747276306},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"wavelet transform","score":0.9100000262260437},{"id":"https://openalex.org/keywords/convolutional-transformer","display_name":"convolutional transformer","score":0.9120000004768372},{"id":"https://openalex.org/keywords/attention-mechanism","display_name":"attention mechanism","score":0.5690000057220459},{"id":"https://openalex.org/keywords/multi-step-forecasting","display_name":"multi-step forecasting","score":0.7419999837875366},{"id":"https://openalex.org/keywords/geological-strata","display_name":"geological strata","score":0.5659999847412109},{"id":"https://openalex.org/keywords/high-frequency-noise-suppression","display_name":"high-frequency noise suppression","score":0.7730000019073486},{"id":"https://openalex.org/keywords/baseline-drift","display_name":"baseline drift","score":0.7599999904632568},{"id":"https://openalex.org/keywords/multi-scale-temporal-dependencies","display_name":"multi-scale temporal dependencies","score":0.8159999847412109}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6182910203933716},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5512571334838867},{"id":"https://openalex.org/C144171764","wikidata":"https://www.wikidata.org/wiki/Q48103","display_name":"Torque","level":2,"score":0.5351439714431763},{"id":"https://openalex.org/C120398109","wikidata":"https://www.wikidata.org/wiki/Q175751","display_name":"Quantum tunnelling","level":2,"score":0.522809624671936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4990663528442383},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.46330171823501587},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45687663555145264},{"id":"https://openalex.org/C138081364","wikidata":"https://www.wikidata.org/wiki/Q852013","display_name":"Shield","level":2,"score":0.4395812451839447},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.395820677280426},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3616522550582886},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.22186842560768127},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1703273057937622},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.14715877175331116},{"id":"https://openalex.org/C49040817","wikidata":"https://www.wikidata.org/wiki/Q193091","display_name":"Optoelectronics","level":1,"score":0.12140998244285583},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C5900021","wikidata":"https://www.wikidata.org/wiki/Q163082","display_name":"Petrology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccdc65474.2025.11091208","doi":"https://doi.org/10.1109/ccdc65474.2025.11091208","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccdc65474.2025.11091208","pdf_url":null,"source":{"id":"https://openalex.org/S4363607715","display_name":"Chinese Control and Decision Conference (CCDC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 37th Chinese Control and Decision Conference (CCDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8970999717712402,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G7447975031","display_name":null,"funder_award_id":"61633019,62173297,62203464","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2794556472","https://openalex.org/W2902508499","https://openalex.org/W2947870163","https://openalex.org/W2967982296","https://openalex.org/W3014482273","https://openalex.org/W3101546351","https://openalex.org/W3174871970","https://openalex.org/W3195996253","https://openalex.org/W3197949786","https://openalex.org/W4205260918","https://openalex.org/W4206357525","https://openalex.org/W4210268250","https://openalex.org/W4214874572","https://openalex.org/W4214931975","https://openalex.org/W4313530556","https://openalex.org/W4313531415","https://openalex.org/W4315433559","https://openalex.org/W4317651618","https://openalex.org/W4393333715","https://openalex.org/W4400933947"],"related_works":["https://openalex.org/W4406519806","https://openalex.org/W6925003398","https://openalex.org/W3174871970","https://openalex.org/W4224250179","https://openalex.org/W7140323462","https://openalex.org/W7125794243","https://openalex.org/W4399369413","https://openalex.org/W4390612404","https://openalex.org/W4393333715","https://openalex.org/W3101546351"],"abstract_inverted_index":{"Accurate":[0],"prediction":[1,35,130],"of":[2,41],"cutterhead":[3],"torque,":[4],"which":[5],"serves":[6],"as":[7],"a":[8,58],"critical":[9],"operational":[10],"parameter":[11],"for":[12,34,65,144],"shield":[13],"tunneling":[14],"machines,":[15],"is":[16],"paramount":[17],"to":[18,38,137],"ensuring":[19],"safe":[20],"excavation":[21],"processes.":[22],"However,":[23],"complex":[24],"geological":[25,122,138],"conditions":[26],"induce":[27],"substantial":[28],"torque":[29,50],"fluctuations,":[30],"posing":[31],"significant":[32],"challenges":[33],"accuracy":[36,131],"due":[37],"the":[39,124],"coexistence":[40],"high-frequency":[42,95],"noise":[43,114],"interference":[44],"and":[45],"low-frequency":[46,99],"baseline":[47],"drift":[48],"in":[49,148],"signals.":[51],"To":[52],"address":[53],"this":[54],"challenge,":[55],"we":[56],"propose":[57],"hybrid":[59],"Wavelet":[60],"Transform-Convolutional":[61],"Transformer":[62,102],"(WTCT)":[63],"model":[64,125],"time":[66],"series":[67],"prediction.":[68],"The":[69,134],"WTCT":[70],"framework":[71],"innovatively":[72],"integrates":[73],"wavelet":[74],"decomposition":[75],"with":[76,129],"attention":[77],"mechanisms:":[78],"Input":[79],"parameters":[80],"are":[81],"decomposed":[82],"into":[83],"distinct":[84],"frequency":[85],"components,":[86],"enabling":[87],"targeted":[88],"feature":[89],"extraction":[90],"through":[91],"convolutional":[92],"operations":[93],"on":[94],"details":[96],"while":[97,112],"preserving":[98],"trends":[100],"via":[101],"layers.":[103],"This":[104],"dual-path":[105],"architecture":[106],"effectively":[107],"captures":[108],"multi-scale":[109],"temporal":[110],"dependencies":[111],"suppressing":[113],"contamination.":[115],"Validated":[116],"against":[117],"real-world":[118],"datasets":[119],"spanning":[120],"diverse":[121],"strata,":[123],"achieves":[126],"superior":[127],"performance":[128],"reaching":[132],"98.52%.":[133],"demonstrated":[135],"robustness":[136],"variations":[139],"confirms":[140],"its":[141],"practical":[142],"value":[143],"intelligent":[145],"control":[146],"systems":[147],"tunnel":[149],"boring":[150],"operations.":[151]},"counts_by_year":[],"updated_date":"2026-10-05T09:50:58.205359","created_date":"2025-10-10T00:00:00"}
