{"id":"https://openalex.org/W3108701224","doi":"https://doi.org/10.1109/tim.2020.3041905","title":"TScatNet: An Interpretable Cross-Domain Intelligent Diagnosis Model With Antinoise and Few-Shot Learning Capability","display_name":"TScatNet: An Interpretable Cross-Domain Intelligent Diagnosis Model With Antinoise and Few-Shot Learning Capability","publication_year":2020,"publication_date":"2020-12-03","ids":{"openalex":"https://openalex.org/W3108701224","doi":"https://doi.org/10.1109/tim.2020.3041905","mag":"3108701224"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2020.3041905","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.3041905","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-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/A5100697046","display_name":"Chao Liu","orcid":"https://orcid.org/0000-0001-7540-8092"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chao Liu","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021977927","display_name":"Chengjin Qin","orcid":"https://orcid.org/0000-0002-5200-3241"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengjin Qin","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060711016","display_name":"Xi Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Shi","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050556840","display_name":"Zengwei Wang","orcid":"https://orcid.org/0000-0003-4867-4795"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zengwei Wang","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082635468","display_name":"Gang Zhang","orcid":"https://orcid.org/0000-0001-9262-7836"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033929602","display_name":"Yunting Han","orcid":"https://orcid.org/0000-0003-2062-6177"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunting Han","raw_affiliation_strings":["School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100697046"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":3.0895,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.9176091,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"70","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9991000294685364,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T11343","display_name":"Power Transformer Diagnostics and Insulation","score":0.975600004196167,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7018725275993347},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6960874795913696},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6813808679580688},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5788606405258179},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5295356512069702},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.49863719940185547},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.4786575734615326},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.469854474067688},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44557052850723267},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.43773454427719116},{"id":"https://openalex.org/keywords/morlet-wavelet","display_name":"Morlet wavelet","score":0.41372671723365784},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.25998175144195557},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2373533546924591},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.21511989831924438}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7018725275993347},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6960874795913696},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6813808679580688},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5788606405258179},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5295356512069702},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.49863719940185547},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.4786575734615326},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.469854474067688},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44557052850723267},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.43773454427719116},{"id":"https://openalex.org/C2778280487","wikidata":"https://www.wikidata.org/wiki/Q3505077","display_name":"Morlet wavelet","level":5,"score":0.41372671723365784},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.25998175144195557},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2373533546924591},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.21511989831924438},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2020.3041905","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.3041905","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1964511482","https://openalex.org/W1994906459","https://openalex.org/W2033800551","https://openalex.org/W2072072671","https://openalex.org/W2093231248","https://openalex.org/W2261689926","https://openalex.org/W2317595875","https://openalex.org/W2556013418","https://openalex.org/W2744790985","https://openalex.org/W2763583057","https://openalex.org/W2794869810","https://openalex.org/W2799620499","https://openalex.org/W2803884688","https://openalex.org/W2810292802","https://openalex.org/W2891319189","https://openalex.org/W2900935771","https://openalex.org/W2901639182","https://openalex.org/W2902985761","https://openalex.org/W2904218127","https://openalex.org/W2908062660","https://openalex.org/W2910881901","https://openalex.org/W2915423430","https://openalex.org/W2927744156","https://openalex.org/W2945551885","https://openalex.org/W2945834994","https://openalex.org/W2981037163","https://openalex.org/W2995758361","https://openalex.org/W2997092256","https://openalex.org/W2998506103","https://openalex.org/W2999309480","https://openalex.org/W3090982778","https://openalex.org/W3101546351","https://openalex.org/W3106050203"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4390569940","https://openalex.org/W2888392564","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4206951940","https://openalex.org/W4293868382","https://openalex.org/W4382602594","https://openalex.org/W4387850423"],"abstract_inverted_index":{"In":[0],"a":[1,70,79],"real":[2],"industrial":[3],"scenario,":[4],"domain":[5,29,33,66,117,121],"shift":[6,34,118],"frequently":[7],"occurred":[8],"due":[9],"to":[10,88,145,178],"working":[11,52,163,209],"loads":[12,164],"variation,":[13,16],"operation":[14,169],"speeds":[15],"and":[17,74,107,133,139,165,188,206],"environmental":[18],"noise":[19],"interference,":[20],"severely":[21],"degrading":[22],"intelligent":[23],"fault":[24],"diagnosis":[25,81],"models'":[26],"performance.":[27],"Currently,":[28],"adaptation-based":[30,67],"models":[31,46,68],"eliminate":[32],"by":[35],"calibrating":[36],"unlabeled":[37,55],"target-domain":[38,56],"data":[39,57,141],"using":[40,96],"labeled":[41],"source-domain":[42],"data.":[43],"Nevertheless,":[44],"these":[45,90],"may":[47],"fail":[48],"when":[49],"encountering":[50],"unseen":[51],"conditions,":[53],"lacking":[54],"for":[58],"learning":[59,72,126],"domain-invariant":[60,94],"features.":[61],"Besides,":[62,195],"the":[63,100,129,137,147,174],"existing":[64],"deep":[65],"lack":[69],"few-shot":[71,125],"capability":[73],"interpretability.":[75,135],"This":[76,113],"article":[77],"develops":[78],"cross-domain":[80],"model":[82],"named":[83],"time-scattering":[84],"convolutional":[85,102],"network":[86],"(TScatNet)":[87],"remedy":[89],"gaps.":[91],"TScatNet":[92,124,153,180,196],"extracts":[93],"features":[95],"Morlet":[97],"wavelet":[98],"as":[99,105,110],"predefined":[101,114],"kernel,":[103],"modulus":[104],"nonlinearity,":[106],"scaling":[108],"averaging":[109],"pooling":[111],"layer.":[112],"architecture":[115],"eliminates":[116],"without":[119],"any":[120],"adaptation,":[122],"endows":[123],"capability,":[127],"simplifies":[128],"hyperparameter":[130],"tuning":[131],"process,":[132],"brings":[134],"Both":[136],"CWRU":[138],"DDS":[140],"sets":[142],"are":[143],"used":[144],"verify":[146],"proposed":[148],"model,":[149],"which":[150],"shows":[151],"that":[152],"could":[154],"stably":[155],"realize":[156],"100%":[157,166,199],"accuracy":[158,167,183,190,200],"on":[159,184,191],"transfer":[160],"tasks":[161,187],"across":[162,168],"speeds.":[170],"Moreover,":[171],"even":[172],"though":[173],"SNR":[175],"value":[176],"descends":[177],"-4,":[179],"achieved":[181,197],"96%":[182],"ten":[185],"categories":[186,193],"99.8%":[189],"four":[192],"tasks.":[194],"nearly":[198],"both":[201],"under":[202],"training":[203],"samples'":[204],"sparsity":[205,207],"of":[208],"conditions.":[210]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}