Operational transfer path analysis with regularized total least-squares method

被引:11
|
作者
Tang, Zhonghua [1 ]
Zan, Ming [1 ]
Zhang, Zhifei [1 ]
Xu, Zhongming [1 ]
Xu, Enyong [2 ]
机构
[1] Chongqing Univ, Coll Mech & Vehicle Engn, Chongqing 400030, Peoples R China
[2] Dongfeng Liuzhou Motor CO LTD, Liuzhou 545005, Peoples R China
基金
中国国家自然科学基金;
关键词
Operational transfer path analysis; Ill-conditioning; Total least-squares method; Tikhonov regularization; BORNE TRANSMISSION PATHS; TIKHONOV REGULARIZATION; INVERSE METHODS; QUANTIFICATION;
D O I
10.1016/j.jsv.2022.117130
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Operational transfer path analysis (OTPA) uses only operational responses to characterize the paths, so it is efficient and widely used in various engineering fields. However, the operational responses are inevitably contaminated by errors, which seriously reduce the accuracy of OTPA. To reduce the influence of errors and improve the accuracy of OTPA, a Tikhonov regularized total least-squares method (RTLSM) which is based on the Tikhonov regularized least-squares method (RLSM) is used to estimate the transmissibility matrix, and then the individual contributions are calculated. The total least-squares method takes into account not only the influence of the errors in the target point responses but also the influence of the errors in the indicator point responses. Tikhonov regularization is introduced to regularize the total least-squares method to improve the ill-conditioning of the indicator point response matrix in the process of estimating the transmissibility matrix. An OTPA simulation on a lumped mass model and an OTPA experiment on an aluminum plate are studied to test the performance of the RLSM and RTLSM. Both simulation and experimental results show that the RTLSM is better than the RLSM in OTPA, and improved the accuracy of OTPA effectively.
引用
收藏
页数:16
相关论文
共 50 条
  • [41] ANALYSIS AND SOLUTION OF THE NONGENERIC TOTAL LEAST-SQUARES PROBLEM
    VANHUFFEL, S
    VANDEWALLE, J
    SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS, 1988, 9 (03) : 360 - 372
  • [42] Analysis of regularized least-squares in reproducing kernel Kreĭn spaces
    Fanghui Liu
    Lei Shi
    Xiaolin Huang
    Jie Yang
    Johan A. K. Suykens
    Machine Learning, 2021, 110 : 1145 - 1173
  • [43] ASYMPTOTIC ANALYSIS OF THE TOTAL LEAST-SQUARES ESPRIT ALGORITHM
    OTTERSTEN, B
    VIBERG, M
    KAILATH, T
    ADVANCED ALGORITHMS AND ARCHITECTURES FOR SIGNAL PROCESSING IV, 1989, 1152 : 146 - 157
  • [44] PERFORMANCE ANALYSIS OF THE TOTAL LEAST-SQUARES ESPRIT ALGORITHM
    OTTERSTEN, B
    VIBERG, M
    KAILATH, T
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1991, 39 (05) : 1122 - 1135
  • [45] MODIFICATION OF LEAST-SQUARES METHOD IN STRUCTURE ANALYSIS
    DVORYANK.VF
    BRUSENTS.FA
    SOVIET PHYSICS CRYSTALLOGRAPHY, USSR, 1965, 9 (04): : 455 - &
  • [46] Displacements Transfer in Static Aeroelastic Analysis Using Least-Squares Fitting Method
    Cheng, Yunhe
    Sun, Qin
    2020 3RD WORLD CONFERENCE ON MECHANICAL ENGINEERING AND INTELLIGENT MANUFACTURING (WCMEIM 2020), 2020, : 722 - 727
  • [47] A convergent least-squares regularized blind deconvolution approach
    Cornelio, Anastasia
    Porta, Federica
    Prato, Marco
    APPLIED MATHEMATICS AND COMPUTATION, 2015, 259 : 173 - 186
  • [48] QR FACTORIZATION FOR THE REGULARIZED LEAST-SQUARES PROBLEM ON HYPERCUBES
    ZHU, JP
    PARALLEL COMPUTING, 1993, 19 (08) : 939 - 948
  • [49] CONVERGENCE OF AN INERTIAL PROXIMAL METHOD FOR L1-REGULARIZED LEAST-SQUARES
    Johnstone, Patrick R.
    Moulin, Pierre
    2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP), 2015, : 3566 - 3570
  • [50] CALCULATION OF THE SOLUTIONS OF INCORRECT STOCHASTIC ALGEBRAIC EQUATIONS BY THE REGULARIZED METHOD OF LEAST-SQUARES
    ZHDANOV, AI
    DOKLADY AKADEMII NAUK SSSR, 1989, 306 (02): : 324 - 327