TY - GEN
T1 - Sparse components separation-based operational reliability assessment approach
AU - Liu, Ruonan
AU - Yang, Boyuan
AU - Ma, Meng
AU - Chen, Xuefeng
AU - Meng, Guotao
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/16
Y1 - 2017/1/16
N2 - As a metric to quantize the engineering system and plants quality, reliability has developed as a scientific discipline which is mainly rely on statistical analysis and life tests. However, with the improvement of mechanical system quality and service time, access to life tests and historical failure data become more and more difficult and time-consuming. To overcome the dependence of statistical failure data, a novel operational reliability assessment approach is proposed. System vibration response varies from operational states to states. In a bearing-rotor system, the vibration response of failure system is the impulse component. Besides, the vibration caused by abrasion is the harmonic component. For impulse and harmonic components extraction, a morphological component analysis (MCA) method based on basis pursuit denoising (BPDN) is used to decompose the vibration signals and reconstruct the impulse signals. Then classical time domain indexes of impulse signals are used as the observation sequence of a corresponding Hidden Markov Models (HMM) to assessment operational reliability. Finally, BPDN, traditional time-features and the proposed method are respectively applied in the operational reliability assessment of an experiment carried out on an aerospace bearing test rig. Comparison results confirmed the effectiveness of the proposed method for operational reliability assessment in bearing-rotor system.
AB - As a metric to quantize the engineering system and plants quality, reliability has developed as a scientific discipline which is mainly rely on statistical analysis and life tests. However, with the improvement of mechanical system quality and service time, access to life tests and historical failure data become more and more difficult and time-consuming. To overcome the dependence of statistical failure data, a novel operational reliability assessment approach is proposed. System vibration response varies from operational states to states. In a bearing-rotor system, the vibration response of failure system is the impulse component. Besides, the vibration caused by abrasion is the harmonic component. For impulse and harmonic components extraction, a morphological component analysis (MCA) method based on basis pursuit denoising (BPDN) is used to decompose the vibration signals and reconstruct the impulse signals. Then classical time domain indexes of impulse signals are used as the observation sequence of a corresponding Hidden Markov Models (HMM) to assessment operational reliability. Finally, BPDN, traditional time-features and the proposed method are respectively applied in the operational reliability assessment of an experiment carried out on an aerospace bearing test rig. Comparison results confirmed the effectiveness of the proposed method for operational reliability assessment in bearing-rotor system.
KW - Bearing-rotor mechanical system
KW - Condition information
KW - Morphological component analysis
KW - Operational reliability assessment
KW - Sparse components separation
UR - https://www.scopus.com/pages/publications/85015712803
U2 - 10.1109/PHM.2016.7819796
DO - 10.1109/PHM.2016.7819796
M3 - 会议稿件
AN - SCOPUS:85015712803
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 -