메뉴 건너뛰기




Volumn 4, Issue 2, 2014, Pages 77-90

Emerging data technology in structural health monitoring: Compressive sensing technology

Author keywords

Acoustic emission; Compressive sensing; Damage identification; Lost data recovery; Moving load distribution; Structural health monitoring; Wireless sensor

Indexed keywords

ACOUSTIC EMISSION TESTING; ACOUSTIC EMISSIONS; DAMAGE DETECTION; DATA ACQUISITION; DATA HANDLING; INFORMATION MANAGEMENT; INVERSE PROBLEMS; LINEAR ALGEBRA; LINEAR EQUATIONS; STRUCTURAL HEALTH MONITORING;

EID: 84896322382     PISSN: 21905452     EISSN: 21905479     Source Type: Journal    
DOI: 10.1007/s13349-013-0064-1     Document Type: Article
Times cited : (40)

References (46)
  • 1
    • 77951566656 scopus 로고    scopus 로고
    • Structural health monitoring in mainland China: review and future trends
    • Ou J, Li H (2010) Structural health monitoring in mainland China: review and future trends. Struct Health Monit 9(3): 219-232.
    • (2010) Struct Health Monit , vol.9 , Issue.3 , pp. 219-232
    • Ou, J.1    Li, H.2
  • 2
    • 5444265148 scopus 로고    scopus 로고
    • Structural health monitoring of innovative Canadian civil engineering structures
    • Mufti AA (2002) Structural health monitoring of innovative Canadian civil engineering structures. Struct Health Monit 1(1): 89-103.
    • (2002) Struct Health Monit , vol.1 , Issue.1 , pp. 89-103
    • Mufti, A.A.1
  • 3
    • 23844557791 scopus 로고    scopus 로고
    • Technology developments in structural health monitoring of large-scale bridges
    • Ko JM, Ni YQ (2005) Technology developments in structural health monitoring of large-scale bridges. Eng Struct 27(12): 1715-1725.
    • (2005) Eng Struct , vol.27 , Issue.12 , pp. 1715-1725
    • Ko, J.M.1    Ni, Y.Q.2
  • 6
    • 31744440684 scopus 로고    scopus 로고
    • Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
    • Candès EJ, Romberg J, Tao T (2006) Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans Inform Theory 52(2): 489-509.
    • (2006) IEEE Trans Inform Theory , vol.52 , Issue.2 , pp. 489-509
    • Candès, E.J.1    Romberg, J.2    Tao, T.3
  • 9
  • 18
    • 70350270032 scopus 로고    scopus 로고
    • A single-pixel imaging system for remotes sensing by two-step iterative curvelet thresholding
    • Ma J (2009) A single-pixel imaging system for remotes sensing by two-step iterative curvelet thresholding. IEEE Geosci Remote Sens Lett 6(4): 676-680.
    • (2009) IEEE Geosci Remote Sens Lett , vol.6 , Issue.4 , pp. 676-680
    • Ma, J.1
  • 19
    • 85032752258 scopus 로고    scopus 로고
    • Fighting the curse of dimensionality: compressive sensing in exploration seismology
    • Herrmann FJ, Friedlander MP, Yi{dotless}lmaz Ö (2012) Fighting the curse of dimensionality: compressive sensing in exploration seismology. IEEE Signal Process Mag 29(3): 88-100.
    • (2012) IEEE Signal Process Mag , vol.29 , Issue.3 , pp. 88-100
    • Herrmann, F.J.1    Friedlander, M.P.2    Yilmaz, Ö.3
  • 21
    • 79955714252 scopus 로고    scopus 로고
    • Compressive sampling for accelerometer signals in structural health monitoring
    • Bao Y, Beck JL, Li H (2011) Compressive sampling for accelerometer signals in structural health monitoring. Struct Health Monit 10(3): 235-246.
    • (2011) Struct Health Monit , vol.10 , Issue.3 , pp. 235-246
    • Bao, Y.1    Beck, J.L.2    Li, H.3
  • 22
    • 84872350700 scopus 로고    scopus 로고
    • A data loss recovery approach for wireless sensor networks using a compressive sampling technique
    • Bao Y, Li H, Sun X, Yu Y, Ou J (2013) A data loss recovery approach for wireless sensor networks using a compressive sampling technique. Struct Health Monit 12: 78-95.
    • (2013) Struct Health Monit , vol.12 , pp. 78-95
    • Bao, Y.1    Li, H.2    Sun, X.3    Yu, Y.4    Ou, J.5
  • 23
    • 84861718975 scopus 로고    scopus 로고
    • Recovery of lost data for wireless sensor network used in structural health monitoring
    • 11-15 March, San Diego, California USA
    • Bao Y, Li H, Sun X, Yu Y, Ou J (2012) Recovery of lost data for wireless sensor network used in structural health monitoring. In: SPIE Smart Structures/NDE, 11-15 March, San Diego, California USA.
    • (2012) In: SPIE Smart Structures/NDE
    • Bao, Y.1    Li, H.2    Sun, X.3    Yu, Y.4    Ou, J.5
  • 24
    • 84878689002 scopus 로고    scopus 로고
    • Compressive sampling based approach for identification of moving loads distribution on cable-stayed bridges
    • 11-15 March 2013 San Diego, California USA
    • Bao Y, Li H, Zhang F, Ou J (2013) Compressive sampling based approach for identification of moving loads distribution on cable-stayed bridges. In: SPIE Smart Structures/NDE, 11-15 March 2013 San Diego, California USA.
    • (2013) In: SPIE Smart Structures/NDE
    • Bao, Y.1    Li, H.2    Zhang, F.3    Ou, J.4
  • 27
    • 80455155226 scopus 로고    scopus 로고
    • Compressive sensing of the Tohoku!Oki Mw 9.0 earthquake: frequency-dependent rupture modes
    • doi:10.1029/2011GL049223
    • Yao H, Gerstoft P, Shearer PM, Mecklenbräuker C (2011) Compressive sensing of the Tohoku!Oki Mw 9. 0 earthquake: frequency-dependent rupture modes. Geophys Res Lett 38: L20310. doi: 10. 1029/2011GL049223.
    • (2011) Geophys Res Lett , vol.38
    • Yao, H.1    Gerstoft, P.2    Shearer, P.M.3    Mecklenbräuker, C.4
  • 28
    • 84869087356 scopus 로고    scopus 로고
    • A compressive sensing framework for seismic source parameter estimation
    • Rodriguez V, Sacchi M, Gu YJ (2012) A compressive sensing framework for seismic source parameter estimation. Geophys J Int 191(3): 1226-1236.
    • (2012) Geophys J Int , vol.191 , Issue.3 , pp. 1226-1236
    • Rodriguez, V.1    Sacchi, M.2    Gu, Y.J.3
  • 32
    • 0027842081 scopus 로고
    • Matching pursuits with time-frequency dictionaries
    • Mallat SG, Zhang Z (1993) Matching pursuits with time-frequency dictionaries. IEEE Trans Signal Process 41(12): 3397-3415.
    • (1993) IEEE Trans Signal Process , vol.41 , Issue.12 , pp. 3397-3415
    • Mallat, S.G.1    Zhang, Z.2
  • 33
    • 64649083745 scopus 로고    scopus 로고
    • Signal recovery from random measurements via orthogonal matching pursuit
    • Tropp JA, Gilbert AC (2007) Signal recovery from random measurements via orthogonal matching pursuit. IEEE Trans Inform Theory 53(12): 4655-4666.
    • (2007) IEEE Trans Inform Theory , vol.53 , Issue.12 , pp. 4655-4666
    • Tropp, J.A.1    Gilbert, A.C.2
  • 34
    • 84856938223 scopus 로고    scopus 로고
    • Sparse solution of underdetermined linear equations by stagewise orthogonal matching pursuit
    • Donoho DL, Tsaig Y, Drori I, Starck JL (2012) Sparse solution of underdetermined linear equations by stagewise orthogonal matching pursuit. IEEE Trans Inform Theory 58(2): 1094-1121.
    • (2012) IEEE Trans Inform Theory , vol.58 , Issue.2 , pp. 1094-1121
    • Donoho, D.L.1    Tsaig, Y.2    Drori, I.3    Starck, J.L.4
  • 35
    • 65749110333 scopus 로고    scopus 로고
    • Subspace pursuit for compressive sensing reconstruction
    • Dai W, Milenkovic O (2009) Subspace pursuit for compressive sensing reconstruction. IEEE Trans Inform Theory 55(5): 2230-2249.
    • (2009) IEEE Trans Inform Theory , vol.55 , Issue.5 , pp. 2230-2249
    • Dai, W.1    Milenkovic, O.2
  • 36
    • 64749092799 scopus 로고    scopus 로고
    • Uniform uncertainty principle and signal recovery via regularized orthogonal matching pursuit
    • Needell D, Vershynin R (2009) Uniform uncertainty principle and signal recovery via regularized orthogonal matching pursuit. Found Comput Math 9: 317-334.
    • (2009) Found Comput Math , vol.9 , pp. 317-334
    • Needell, D.1    Vershynin, R.2
  • 37
    • 62749175137 scopus 로고    scopus 로고
    • CoSaMP: iterative signal recovery from incomplete and inaccurate samples
    • Needell D, Tropp JA (2009) CoSaMP: iterative signal recovery from incomplete and inaccurate samples. Appl Comput Harmon Anal 26: 301-321.
    • (2009) Appl Comput Harmon Anal , vol.26 , pp. 301-321
    • Needell, D.1    Tropp, J.A.2
  • 39
    • 33646365077 scopus 로고    scopus 로고
    • 1-norm solution is also the sparsest solution
    • 1-norm solution is also the sparsest solution. Commun Pur Appl Math 59(6): 797-829.
    • (2006) Commun Pur Appl Math , vol.59 , Issue.6 , pp. 797-829
    • Donoho, D.L.1
  • 40
    • 33144483155 scopus 로고    scopus 로고
    • Stable recovery of sparse over complete representations in the presence of noise
    • Donoho DL, Elad M, Temlyakov VN (2006) Stable recovery of sparse over complete representations in the presence of noise. IEEE Trans Inform Theory 52: 6-18.
    • (2006) IEEE Trans Inform Theory , vol.52 , pp. 6-18
    • Donoho, D.L.1    Elad, M.2    Temlyakov, V.N.3
  • 41
    • 39449126969 scopus 로고    scopus 로고
    • Gradlent projection for sparse reconstruction: application to compressed sensing and other inverse problems
    • Flguelredo MAT, Nowak RD, Wrlght SJ (2007) Gradlent projection for sparse reconstruction: application to compressed sensing and other inverse problems. IEEE J Sel Top Signal Process 1(4): 586-597.
    • (2007) IEEE J Sel Top Signal Process , vol.1 , Issue.4 , pp. 586-597
    • Flguelredo, M.A.T.1    Nowak, R.D.2    Wrlght, S.J.3
  • 44
    • 77955666600 scopus 로고    scopus 로고
    • A fast algorithm fro sparse reconstruction based on shrinkage, subspace optimization and continuation
    • Wen Z, Yin W, Goldfrab D, Zhang Y (2010) A fast algorithm fro sparse reconstruction based on shrinkage, subspace optimization and continuation. SIAM J Sci Comput 32(4): 1832-1857.
    • (2010) SIAM J Sci Comput , vol.32 , Issue.4 , pp. 1832-1857
    • Wen, Z.1    Yin, W.2    Goldfrab, D.3    Zhang, Y.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.