TY - GEN
T1 - Damped SVD for operational transfer path analysis
AU - Cheng, Wei
AU - Chu, Yapeng
AU - Lu, Yingying
AU - Zi, Yanyang
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/16
Y1 - 2017/1/16
N2 - Transfer path analysis (TPA) is a method to identify energy transfer paths based on experiment and principle of linear superposition, which is widely used to identify the source of main faults based on vibration and noise signals, thus benefiting the works of PHM. However, load identification and transfer function measurement make it complex and slow to carry out. Operational transfer path analysis (OTPA) gets rid of the load identification and transfer function measurement, has attracted more attention due to simple and fast modeling. From a theoretical perspective, OTPA belongs to an inverse problem. Conventional OTPA use truncated singular value decomposition (TSVD) to identify transmissibility function matrix, which has two main shortages. Firstly, TSVD uses 0 and 1 as filter factors, without considering smoothness of filter factors, the sudden change of filter factors will result in large rounding errors, thus aggravating the ill-conditioned degree and approximate solution distortion. Secondly, the truncating parameter is usually chosen from experience, which is one of the most important parameters in TSVD, it's obviously not precise enough to meet the requirements. DSVD uses smooth filter factors to overcome the shortage of sudden change of filter factors in TSVD. Moreover, the regularization parameter is used to calculate the filter factors, which is easy to figure out by L-curve, overcoming the shortage of choosing from experience. A simulation experiment is adopted to test the proposed OTPA which proves that the proposed OTPA is correct and effective to solve vibration and noise problems. The proposed OTPA is also compared with the conventional OTPA which proves that precision of the proposed OTPA is much higher than that of the conventional OTPA.
AB - Transfer path analysis (TPA) is a method to identify energy transfer paths based on experiment and principle of linear superposition, which is widely used to identify the source of main faults based on vibration and noise signals, thus benefiting the works of PHM. However, load identification and transfer function measurement make it complex and slow to carry out. Operational transfer path analysis (OTPA) gets rid of the load identification and transfer function measurement, has attracted more attention due to simple and fast modeling. From a theoretical perspective, OTPA belongs to an inverse problem. Conventional OTPA use truncated singular value decomposition (TSVD) to identify transmissibility function matrix, which has two main shortages. Firstly, TSVD uses 0 and 1 as filter factors, without considering smoothness of filter factors, the sudden change of filter factors will result in large rounding errors, thus aggravating the ill-conditioned degree and approximate solution distortion. Secondly, the truncating parameter is usually chosen from experience, which is one of the most important parameters in TSVD, it's obviously not precise enough to meet the requirements. DSVD uses smooth filter factors to overcome the shortage of sudden change of filter factors in TSVD. Moreover, the regularization parameter is used to calculate the filter factors, which is easy to figure out by L-curve, overcoming the shortage of choosing from experience. A simulation experiment is adopted to test the proposed OTPA which proves that the proposed OTPA is correct and effective to solve vibration and noise problems. The proposed OTPA is also compared with the conventional OTPA which proves that precision of the proposed OTPA is much higher than that of the conventional OTPA.
KW - Damped singular value decomposition
KW - Operational Transfer Path Analysis
KW - PHM
KW - Truncated singular value decomposition
KW - Vibration & noise reduction and control
UR - https://www.scopus.com/pages/publications/85015616420
U2 - 10.1109/PHM.2016.7819793
DO - 10.1109/PHM.2016.7819793
M3 - 会议稿件
AN - SCOPUS:85015616420
T3 - Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016
BT - Proceedings of 2016 Prognostics and System Health Management Conference, PHM-Chengdu 2016
A2 - Miao, Qiang
A2 - Li, Zhaojun
A2 - Zuo, Ming J.
A2 - Xing, Liudong
A2 - Tian, Zhigang
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th IEEE Prognostics and System Health Management Conference, PHM-Chengdu 2016
Y2 - 19 October 2016 through 21 October 2016
ER -