Sparse Optimal Design of an Ultrasonic Sensor Array for Fast TFM Based on a Discrete Slime Mold Algorithm

The total focusing method (TFM) is an ultrasonic phased array imaging algorithm used in ultrasonic nondestructive testing (NDT) that processes large amounts of data from full matrix capture (FMC). This limits its application in some industrial fields with real-time requirements. To solve this proble...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE sensors journal Jg. 24; H. 8; S. 12207 - 12216
Hauptverfasser:	Zhu, Wenfa, Wei, Zhengbo, Xiang, Yanxun, Chai, Xiaodong, Liu, Sihao, Fan, Guopeng, Zhang, Haiyan, Zhang, Hui, Qi, Weiwei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 15.04.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Acoustics Algorithms Antenna arrays Arrays Convergence Discrete slime mold algorithm (DSMA) Genetic algorithms Imaging Mold Nondestructive testing Optimization Particle swarm optimization Phased arrays Real numbers Sensor arrays Sidelobe reduction Sidelobes Signal to noise ratio Slime sparse array optimization total focusing method (TFM) ultrasonic phased array Ultrasonic testing
ISSN:	1530-437X, 1558-1748
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	The total focusing method (TFM) is an ultrasonic phased array imaging algorithm used in ultrasonic nondestructive testing (NDT) that processes large amounts of data from full matrix capture (FMC). This limits its application in some industrial fields with real-time requirements. To solve this problem, a sparse array optimization method is applied to FMC-TFM that can reduce time consumption and improve imaging efficiency. However, conventional intelligent optimization methods, such as genetic algorithm (GA), use binary encoding, which require intensive computation and are easily trapped in local optima. This article proposes a discrete slime mold algorithm (DSMA), in which the slime mold position is coded in real numbers instead of binary. In the optimization process, a mapping model between the slime mold and ultrasonic array is established. A fitness function with a narrow main lobe and low sidelobe is constructed to obtain the sparse array position with the best performance. In experiments, the proposed method reduces the imaging time by more than 50% compared with conventional TFM, without affecting imaging quality. Compared with a GA and binary particle swarm optimization (BPSO), the proposed method improves array performance indicator (API) and signal-to-noise ratio (SNR) performance.
AbstractList	The total focusing method (TFM) is an ultrasonic phased array imaging algorithm used in ultrasonic nondestructive testing (NDT) that processes large amounts of data from full matrix capture (FMC). This limits its application in some industrial fields with real-time requirements. To solve this problem, a sparse array optimization method is applied to FMC-TFM that can reduce time consumption and improve imaging efficiency. However, conventional intelligent optimization methods, such as genetic algorithm (GA), use binary encoding, which require intensive computation and are easily trapped in local optima. This article proposes a discrete slime mold algorithm (DSMA), in which the slime mold position is coded in real numbers instead of binary. In the optimization process, a mapping model between the slime mold and ultrasonic array is established. A fitness function with a narrow main lobe and low sidelobe is constructed to obtain the sparse array position with the best performance. In experiments, the proposed method reduces the imaging time by more than 50% compared with conventional TFM, without affecting imaging quality. Compared with a GA and binary particle swarm optimization (BPSO), the proposed method improves array performance indicator (API) and signal-to-noise ratio (SNR) performance.
Author	Zhang, Hui Wei, Zhengbo Xiang, Yanxun Chai, Xiaodong Qi, Weiwei Liu, Sihao Fan, Guopeng Zhang, Haiyan Zhu, Wenfa
Author_xml	– sequence: 1 givenname: Wenfa orcidid: 0000-0002-9889-1168 surname: Zhu fullname: Zhu, Wenfa email: wf-zhu@sues.edu.cn organization: School of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China – sequence: 2 givenname: Zhengbo orcidid: 0009-0000-5310-6405 surname: Wei fullname: Wei, Zhengbo email: wzb000102@163.com organization: School of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China – sequence: 3 givenname: Yanxun orcidid: 0000-0003-0871-4748 surname: Xiang fullname: Xiang, Yanxun email: yxxiang@ecust.edu.cn organization: School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, China – sequence: 4 givenname: Xiaodong surname: Chai fullname: Chai, Xiaodong email: cxdyj@163.com organization: School of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China – sequence: 5 givenname: Sihao surname: Liu fullname: Liu, Sihao email: liusihao255@126.com organization: School of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China – sequence: 6 givenname: Guopeng surname: Fan fullname: Fan, Guopeng email: phdfanry@sina.com organization: School of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China – sequence: 7 givenname: Haiyan surname: Zhang fullname: Zhang, Haiyan email: hyzh@shu.edu.cn organization: School of Communication and Information Engineering, Shanghai University, Shanghai, China – sequence: 8 givenname: Hui surname: Zhang fullname: Zhang, Hui email: zh6154@126.com organization: School of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China – sequence: 9 givenname: Weiwei surname: Qi fullname: Qi, Weiwei email: weiwei_qi@sues.edu.cn organization: School of Urban Railway Transportation, Shanghai University of Engineering Science, Shanghai, China
BookMark	eNp9kDtPwzAUhS0EEuXxA5AYLDGn2IkTx2OBlocoHQISW-Q4N8VVahfbHfrvcdQOiIHpHumecx_fGTo21gBCV5SMKSXi9qWavo1TkrJxlvE05-IIjWielwnlrDwedEYSlvHPU3Tm_YoQKnjOR0hXG-k84MUm6LXs8QN4vTTYdlga_NEHJ701WuEKjLcOT5yTO9xFNZM-4PfZHN9JDy22Bkv8oL1yEABXvV4Dntu-xZN-aZ0OX-sLdNLJ3sPloZ6jj9n0_f4peV08Pt9PXhOVChaSRrCMFRJICwCpaJVouhwkpKxspaAgy6LsFKVFF_uMNTwlksmCKapE0QDPztHNfu7G2e8t-FCv7NaZuLLOCCMkQhFldPG9SznrvYOuVjrIoK2JL-u-pqQeuNYD13rgWh-4xiT9k9y4iM7t_s1c7zM6Hv3Lz4oiT3n2AwXHhiA
CODEN	ISJEAZ
CitedBy_id	crossref_primary_10_1109_TIM_2025_3571150 crossref_primary_10_1109_JIOT_2024_3488723 crossref_primary_10_3390_rs17142423 crossref_primary_10_1134_S1061830924602083 crossref_primary_10_1016_j_ymssp_2025_113181 crossref_primary_10_1080_10589759_2024_2440820
Cites_doi	10.1007/s11045-023-00877-9 10.1016/j.sna.2020.112086 10.1109/3M-NANO46308.2019.8947365 10.1016/j.ultras.2006.05.131 10.1016/j.ndteint.2017.05.002 10.1016/S0165-2125(98)00039-0 10.1109/TIM.2019.2937532 10.1016/j.ndteint.2012.06.005 10.1109/TTHZ.2016.2544142 10.1016/j.ndteint.2011.08.008 10.1016/j.ultras.2020.106215 10.1016/j.ndteint.2006.03.006 10.1109/58.753023 10.1016/j.ndteint.2008.10.004 10.1016/j.ngib.2019.01.017 10.1109/TAP.2021.3076256 10.1007/s11554-016-0563-5 10.1016/j.future.2020.03.055 10.1109/JSEN.2008.2004574 10.1016/j.ultras.2019.02.011 10.1109/TIM.2020.2980447 10.1016/j.gendis.2019.04.003 10.1016/j.ymssp.2020.107149 10.1016/j.ultras.2011.10.001 10.1109/TAP.2004.841324 10.1109/ACCESS.2020.3001947 10.1016/j.measurement.2022.112360 10.17762/converter.258 10.1109/EDCT.2018.8405055 10.1016/j.measurement.2020.108466 10.1109/8.768787 10.1016/j.ndteint.2005.04.002 10.1080/00207217.2019.1636297 10.1016/j.measurement.2022.110895 10.1049/cp.2015.1300 10.1155/2014/987140 10.1109/TITS.2018.2882202 10.1109/FENDT54151.2021.9749663 10.1088/1742-6596/2242/1/012001 10.1109/JSEN.2020.3020578 10.1002/j.1538-7305.1943.tb01306.x 10.1109/JSEN.2021.3100615
ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024
Copyright_xml	– notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024
DBID	97E RIA RIE AAYXX CITATION 7SP 7U5 8FD L7M
DOI	10.1109/JSEN.2024.3372579
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEL CrossRef Electronics & Communications Abstracts Solid State and Superconductivity Abstracts Technology Research Database Advanced Technologies Database with Aerospace
DatabaseTitle	CrossRef Solid State and Superconductivity Abstracts Technology Research Database Advanced Technologies Database with Aerospace Electronics & Communications Abstracts
DatabaseTitleList	Solid State and Superconductivity Abstracts
Database_xml	– sequence: 1 dbid: RIE name: IEL url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Geography Engineering
EISSN	1558-1748
EndPage	12216
ExternalDocumentID	10_1109_JSEN_2024_3372579 10466527
Genre	orig-research
GrantInformation_xml	– fundername: National Key Research and Development Program of China grantid: 2022YFF0605604 funderid: 10.13039/501100012166 – fundername: National Natural Science Foundation of China grantid: 12004240; U1930202; 12104290; 12374443 funderid: 10.13039/501100001809
GroupedDBID	-~X 0R~ 29I 4.4 5GY 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFO ACGFS ACIWK AENEX AGQYO AHBIQ AJQPL AKJIK AKQYR ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 EBS F5P HZ~ IFIPE IPLJI JAVBF LAI M43 O9- OCL P2P RIA RIE RNS TWZ AAYXX CITATION 7SP 7U5 8FD L7M
ID	FETCH-LOGICAL-c294t-b94346ae0deee29dc9bf5eae248da91ea868fc116feee44b720a4a64c1c96be73
IEDL.DBID	RIE
ISICitedReferencesCount	9
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001279547600001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1530-437X
IngestDate	Mon Jun 30 10:23:48 EDT 2025 Sat Nov 29 06:39:57 EST 2025 Tue Nov 18 22:18:44 EST 2025 Wed Aug 27 02:17:04 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	8
Language	English
License	https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-037
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c294t-b94346ae0deee29dc9bf5eae248da91ea868fc116feee44b720a4a64c1c96be73
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0002-9889-1168 0000-0003-0871-4748 0009-0000-5310-6405
PQID	3040055898
PQPubID	75733
PageCount	10
ParticipantIDs	ieee_primary_10466527 crossref_citationtrail_10_1109_JSEN_2024_3372579 crossref_primary_10_1109_JSEN_2024_3372579 proquest_journals_3040055898
PublicationCentury	2000
PublicationDate	2024-04-15
PublicationDateYYYYMMDD	2024-04-15
PublicationDate_xml	– month: 04 year: 2024 text: 2024-04-15 day: 15
PublicationDecade	2020
PublicationPlace	New York
PublicationPlace_xml	– name: New York
PublicationTitle	IEEE sensors journal
PublicationTitleAbbrev	JSEN
PublicationYear	2024
Publisher	IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	ref13 ref35 ref12 ref34 ref15 ref37 ref14 ref36 ref31 ref30 ref11 ref33 ref10 ref32 ref2 ref1 ref17 ref39 ref16 ref38 ref19 ref18 ref24 ref23 ref26 ref25 ref20 ref42 ref41 ref22 ref21 ref28 ref27 ref29 ref8 ref7 ref9 ref4 ref3 ref6 ref5 ref40
References_xml	– ident: ref1 doi: 10.1007/s11045-023-00877-9 – ident: ref8 doi: 10.1016/j.sna.2020.112086 – ident: ref36 doi: 10.1109/3M-NANO46308.2019.8947365 – ident: ref33 doi: 10.1016/j.ultras.2006.05.131 – ident: ref39 doi: 10.1016/j.ndteint.2017.05.002 – ident: ref30 doi: 10.1016/S0165-2125(98)00039-0 – ident: ref21 doi: 10.1109/TIM.2019.2937532 – ident: ref17 doi: 10.1016/j.ndteint.2012.06.005 – ident: ref42 doi: 10.1109/TTHZ.2016.2544142 – ident: ref34 doi: 10.1016/j.ndteint.2011.08.008 – ident: ref9 doi: 10.1016/j.ultras.2020.106215 – ident: ref22 doi: 10.1016/j.ndteint.2006.03.006 – ident: ref37 doi: 10.1109/58.753023 – ident: ref6 doi: 10.1016/j.ndteint.2008.10.004 – ident: ref7 doi: 10.1016/j.ngib.2019.01.017 – ident: ref19 doi: 10.1109/TAP.2021.3076256 – ident: ref18 doi: 10.1007/s11554-016-0563-5 – ident: ref40 doi: 10.1016/j.future.2020.03.055 – ident: ref41 doi: 10.1109/JSEN.2008.2004574 – ident: ref5 doi: 10.1016/j.ultras.2019.02.011 – ident: ref31 doi: 10.1109/TIM.2020.2980447 – ident: ref12 doi: 10.1016/j.gendis.2019.04.003 – ident: ref14 doi: 10.1016/j.ymssp.2020.107149 – ident: ref35 doi: 10.1016/j.ultras.2011.10.001 – ident: ref25 doi: 10.1109/TAP.2004.841324 – ident: ref38 doi: 10.1109/ACCESS.2020.3001947 – ident: ref11 doi: 10.1016/j.measurement.2022.112360 – ident: ref13 doi: 10.17762/converter.258 – ident: ref28 doi: 10.1109/EDCT.2018.8405055 – ident: ref32 doi: 10.1016/j.measurement.2020.108466 – ident: ref26 doi: 10.1109/8.768787 – ident: ref4 doi: 10.1016/j.ndteint.2005.04.002 – ident: ref27 doi: 10.1080/00207217.2019.1636297 – ident: ref2 doi: 10.1016/j.measurement.2022.110895 – ident: ref23 doi: 10.1049/cp.2015.1300 – ident: ref29 doi: 10.1155/2014/987140 – ident: ref3 doi: 10.1109/TITS.2018.2882202 – ident: ref10 doi: 10.1109/FENDT54151.2021.9749663 – ident: ref15 doi: 10.1088/1742-6596/2242/1/012001 – ident: ref20 doi: 10.1109/JSEN.2020.3020578 – ident: ref24 doi: 10.1002/j.1538-7305.1943.tb01306.x – ident: ref16 doi: 10.1109/JSEN.2021.3100615
SSID	ssj0019757
Score	2.4457774
Snippet	The total focusing method (TFM) is an ultrasonic phased array imaging algorithm used in ultrasonic nondestructive testing (NDT) that processes large amounts of...
SourceID	proquest crossref ieee
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	12207
SubjectTerms	Acoustics Algorithms Antenna arrays Arrays Convergence Discrete slime mold algorithm (DSMA) Genetic algorithms Imaging Mold Nondestructive testing Optimization Particle swarm optimization Phased arrays Real numbers Sensor arrays Sidelobe reduction Sidelobes Signal to noise ratio Slime sparse array optimization total focusing method (TFM) ultrasonic phased array Ultrasonic testing
Title	Sparse Optimal Design of an Ultrasonic Sensor Array for Fast TFM Based on a Discrete Slime Mold Algorithm
URI	https://ieeexplore.ieee.org/document/10466527 https://www.proquest.com/docview/3040055898
Volume	24
WOSCitedRecordID	wos001279547600001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVIEE databaseName: IEL customDbUrl: eissn: 1558-1748 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0019757 issn: 1530-437X databaseCode: RIE dateStart: 20010101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3da9UwFD-4IagPfsyJV6ecB5-Ebk2bNMnjdLuIsKtwN7hvJWlSV-htR28n7L_3JLcbE1HwrdCckPaXnI-c5HcAPkhGk0TWIiHToxMuvUgUBT9JwclbF66WxtpYbEIuFmq10t-ny-rxLoz3Ph4-84fhMebyXV9dh62yo5CPLEQmd2BHymJ7WesuZaBlpPWkFZwmPJerKYXJUn30dXm6oFAw44d5Lmlo-jcjFKuq_KGKo32ZP_vPkT2Hp5Mjicdb5F_AA9_twZN79IJ78GiqcH558xKa5RWFsB6_kYpYk9xJPLmBfY2mw4t2HMwmkOTiksLafqBuB3OD5NDi3GxGPJ-f4Seydw77Dg2eNKRsyNvGZdusPZ71rcPj9kc_NOPleh8u5qfnn78kU5mFpMo0HxMbKOIK41NHn5VpV2lbC298xpUzmnmjClVXjBU1vefcyiw13BS8YpUurJf5K9jt-s6_BrSKeWVVIPixnFlnnMyt0CryDpL2mEF6-9_LauIgD6Uw2jLGIqkuA1RlgKqcoJrBxzuRqy0Bx78a7wds7jXcwjKDg1t0y2mNbso86C8hlFZv_iL2Fh6H3kPyiIkD2B2Ha_8OHlY_x2YzvI_T7xfZRNXX
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Nb9QwEB1BQSocCpQilhbwgRNS2jixY_tY2q4KdBek3Up7i-zYaSNlkyqbIvXfM_amVSsEErdI8SROnj0fHvsNwCdBcZCIkkdoelTEhOORxOAnyhh669yWQhsTik2I6VQuFurncFg9nIVxzoXNZ27fX4Zcvm2La79UduDzkRlPxGN44ktn0fVxrbukgRKB2BPncByxVCyGJCaN1cG32ckUg8GE7aepwM6pB2Yo1FX5QxkHCzN-8Z99ewlbgytJDtfYv4JHrtmG5_cIBrdhc6hxfnnzGqrZFQaxjvxAJbFEueOwd4O0JdENOa_7Tq88TS6ZYWDbdvjYTt8QdGnJWK96Mh9PyBe0eJa0DdHkuEJ1g_42mdXV0pFJW1tyWF-0XdVfLnfgfHwyPzqNhkILUZEo1kfGk8Rl2sUWPytRtlCm5E67hEmrFXVaZrIsKM1KvM-YEUmsmc5YQQuVGSfSN7DRtI17C8RI6qSRnuLHMGqstiI1XMnAPIj6YwTx7X_Pi4GF3BfDqPMQjcQq91DlHqp8gGoEn-9ErtYUHP9qvOOxuddwDcsI9m7RzYdZuspTr8E4l0q--4vYR9g8nU_O8rOv0--78My_yaeSKN-Djb67du_hafGrr1bdhzAUfwMg1Nke
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Sparse+Optimal+Design+of+an+Ultrasonic+Sensor+Array+for+Fast+TFM+Based+on+a+Discrete+Slime+Mold+Algorithm&rft.jtitle=IEEE+sensors+journal&rft.au=Zhu%2C+Wenfa&rft.au=Wei%2C+Zhengbo&rft.au=Xiang%2C+Yanxun&rft.au=Chai%2C+Xiaodong&rft.date=2024-04-15&rft.issn=1530-437X&rft.eissn=1558-1748&rft.volume=24&rft.issue=8&rft.spage=12207&rft.epage=12216&rft_id=info:doi/10.1109%2FJSEN.2024.3372579&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_JSEN_2024_3372579
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1530-437X&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1530-437X&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1530-437X&client=summon