{"id":"https://openalex.org/W7147219813","doi":"https://doi.org/10.1109/cnml68938.2026.11452549","title":"Comprehensive Investigation of Multiscale Signal Processing Methodologies for Enhanced Structural Health Monitoring in Underground Infrastructures","display_name":"Comprehensive Investigation of Multiscale Signal Processing Methodologies for Enhanced Structural Health Monitoring in Underground Infrastructures","publication_year":2026,"publication_date":"2026-01-30","ids":{"openalex":"https://openalex.org/W7147219813","doi":"https://doi.org/10.1109/cnml68938.2026.11452549"},"language":null,"primary_location":{"id":"doi:10.1109/cnml68938.2026.11452549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11452549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-article"},"type":"article","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/A5072353979","display_name":"Jianjun Wang","orcid":"https://orcid.org/0000-0001-7039-7136"},"institutions":[{"id":"https://openalex.org/I4210107208","display_name":"China Railway Fifth Survey and Design Institute Group","ror":"https://ror.org/01rb6gh35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210107208"]},{"id":"https://openalex.org/I4210130035","display_name":"China Communications Construction Company (China)","ror":"https://ror.org/03q3een69","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210130035"]},{"id":"https://openalex.org/I4210149087","display_name":"Xi'an Railway Survey and Design Institute","ror":"https://ror.org/04emf4852","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210149087"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junyi Wang","raw_affiliation_strings":["Communications Construction Company Ltd.,The First Highway Survey and Design Institute of China,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"Communications Construction Company Ltd.,The First Highway Survey and Design Institute of China,Xi’an,China","institution_ids":["https://openalex.org/I4210130035","https://openalex.org/I4210107208","https://openalex.org/I4210149087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5132665552","display_name":"Xiangxing Kong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210107208","display_name":"China Railway Fifth Survey and Design Institute Group","ror":"https://ror.org/01rb6gh35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210107208"]},{"id":"https://openalex.org/I4210130035","display_name":"China Communications Construction Company (China)","ror":"https://ror.org/03q3een69","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210130035"]},{"id":"https://openalex.org/I4210149087","display_name":"Xi'an Railway Survey and Design Institute","ror":"https://ror.org/04emf4852","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210149087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangxing Kong","raw_affiliation_strings":["Communications Construction Company Ltd.,The First Highway Survey and Design Institute of China,Xi’an,China"],"affiliations":[{"raw_affiliation_string":"Communications Construction Company Ltd.,The First Highway Survey and Design Institute of China,Xi’an,China","institution_ids":["https://openalex.org/I4210130035","https://openalex.org/I4210107208","https://openalex.org/I4210149087"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5072353979"],"corresponding_institution_ids":["https://openalex.org/I4210107208","https://openalex.org/I4210130035","https://openalex.org/I4210149087"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.9195722,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"521","last_page":"525"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.1858000010251999,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.1858000010251999,"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/T13018","display_name":"Seismology and Earthquake Studies","score":0.14399999380111694,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10161","display_name":"Rock Mechanics and Modeling","score":0.1363999992609024,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/structural-health-monitoring","display_name":"Structural health monitoring","score":0.5777999758720398},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5662999749183655},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5063999891281128},{"id":"https://openalex.org/keywords/shield","display_name":"Shield","score":0.47749999165534973},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4526999890804291},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.412200003862381},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.40380001068115234},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.3296000063419342}],"concepts":[{"id":"https://openalex.org/C2776247918","wikidata":"https://www.wikidata.org/wiki/Q1423713","display_name":"Structural health monitoring","level":2,"score":0.5777999758720398},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5662999749183655},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5063999891281128},{"id":"https://openalex.org/C138081364","wikidata":"https://www.wikidata.org/wiki/Q852013","display_name":"Shield","level":2,"score":0.47749999165534973},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4526999890804291},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42570000886917114},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.412200003862381},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.40380001068115234},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.37290000915527344},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.3571000099182129},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.3296000063419342},{"id":"https://openalex.org/C91528185","wikidata":"https://www.wikidata.org/wiki/Q520952","display_name":"Maxima","level":3,"score":0.3296000063419342},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.32199999690055847},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2904999852180481},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C193867417","wikidata":"https://www.wikidata.org/wiki/Q6889814","display_name":"Modulus","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C15627037","wikidata":"https://www.wikidata.org/wiki/Q541961","display_name":"Classification of discontinuities","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25940001010894775},{"id":"https://openalex.org/C21141959","wikidata":"https://www.wikidata.org/wiki/Q657936","display_name":"Shear stress","level":2,"score":0.25519999861717224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cnml68938.2026.11452549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11452549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W4390791228","https://openalex.org/W4390839073","https://openalex.org/W4402197958","https://openalex.org/W4402921875","https://openalex.org/W4406559873","https://openalex.org/W4410414863","https://openalex.org/W4414442537"],"related_works":[],"abstract_inverted_index":{"The":[0,134,165],"evolution":[1],"of":[2,24,58,98,190],"wavelet":[3,65,73],"theory":[4],"has":[5],"furnished":[6],"the":[7,22,37,68,82,115,120,148,184,191],"engineering":[8,185],"diagnostics":[9],"community":[10],"with":[11,109],"a":[12,54,96,174],"sophisticated":[13],"mathematical":[14,84],"apparatus":[15],"for":[16,30,118,177,196],"interrogating":[17],"complex,":[18],"non-stationary":[19],"signals.":[20],"Within":[21],"domain":[23],"structural":[25,43],"health":[26],"monitoring":[27,144],"(SHM),":[28],"particularly":[29],"critical":[31,124],"underground":[32],"infrastructures":[33],"like":[34],"shield":[35,142],"tunnels,":[36],"imperative":[38],"to":[39],"discriminate":[40],"between":[41],"authentic":[42],"responses":[44],"and":[45,76,101,130,157,187],"spurious":[46],"measurement":[47],"noise":[48,163],"remains":[49],"paramount.":[50],"This":[51],"investigation":[52],"undertakes":[53],"rigorous,":[55],"comparative":[56],"examination":[57],"three":[59],"advanced":[60],"denoising":[61],"paradigms":[62],"rooted":[63],"in":[64,152],"multiresolution":[66],"analysis:":[67],"modulus":[69,121,193],"maxima":[70,122,194],"propagation":[71],"technique,":[72],"packet":[74],"synthesis,":[75],"coefficient":[77],"thresholding":[78],"strategies.":[79],"We":[80],"delineate":[81],"foundational":[83],"principles":[85],"governing":[86],"each":[87],"methodology,":[88],"subsequently":[89],"establishing":[90],"their":[91],"respective":[92],"operational":[93],"domains":[94],"through":[95],"synthesis":[97],"theoretical":[99],"analysis":[100],"empirical":[102],"validation.":[103],"A":[104],"synthetic":[105],"signal,":[106],"deliberately":[107],"imbued":[108],"Gaussian":[110],"white":[111],"noise,":[112],"serves":[113],"as":[114],"primary":[116],"testbed":[117],"calibrating":[119],"algorithm's":[123],"parameters,":[125],"including":[126],"scale-dependent":[127],"threshold":[128],"functions":[129],"Lipschitz":[131],"exponent":[132],"estimation.":[133],"optimized":[135],"protocol":[136],"is":[137],"then":[138],"deployed":[139],"on":[140],"field-acquired":[141],"tunnel":[143],"datasets.":[145],"Results":[146],"corroborate":[147],"method's":[149],"superior":[150],"efficacy":[151],"isolating":[153],"geotechnical":[154],"deformation":[155],"signatures":[156],"mechanical":[158],"stress":[159],"waveforms":[160],"from":[161],"ambient":[162],"contamination.":[164],"refined":[166],"signals,":[167],"exhibiting":[168],"significantly":[169],"enhanced":[170],"signal-to-noise":[171],"ratios,":[172],"furnish":[173],"reliable":[175],"substrate":[176],"subsequent":[178],"quantitative":[179],"integrity":[180],"assessment,":[181],"thereby":[182],"validating":[183],"robustness":[186],"practical":[188],"applicability":[189],"proposed":[192],"framework":[195],"infrastructure":[197],"diagnostics.":[198]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}