TY - JOUR
T1 - Dynamic maintenance planning of a hydro-turbine in operational life cycle
AU - Li, Ruopu
AU - Arzaghi, Ehsan
AU - Abbassi, Rouzbeh
AU - Chen, Diyi
AU - Li, Chunhao
AU - Li, Huanhuan
AU - Xu, Beibei
PY - 2020/12
Y1 - 2020/12
N2 - Life cycle assessment (LCA) has been an emerging feature of modern structural health monitoring techniques that aims at evaluating equipment degradation process and it can be used for development of dynamic maintenance plans. A novel framework based on LCA is proposed in this paper for dynamic maintenance planning of hydro-turbines. Using a Hidden Markov Model (HMM) and the inspection data of hydro-turbine runner cracks from actual operations, the transition probability matrix and sojourn time of different crack states are obtained. This is utilized for predicting the expected remaining useful life (RUL) and the formulation of maintenance intervals. Moreover, maintenance plans are developed from the influence of cracks in different states leading to critical conditions. The proposed method, as demonstrated in the case study, efficiently updates the maintenance intervals and reduces the likelihood of failure events. The results of this paper provide a valid maintenance framework for achieving higher operational safety of hydropower stations with minimal resource losses.
AB - Life cycle assessment (LCA) has been an emerging feature of modern structural health monitoring techniques that aims at evaluating equipment degradation process and it can be used for development of dynamic maintenance plans. A novel framework based on LCA is proposed in this paper for dynamic maintenance planning of hydro-turbines. Using a Hidden Markov Model (HMM) and the inspection data of hydro-turbine runner cracks from actual operations, the transition probability matrix and sojourn time of different crack states are obtained. This is utilized for predicting the expected remaining useful life (RUL) and the formulation of maintenance intervals. Moreover, maintenance plans are developed from the influence of cracks in different states leading to critical conditions. The proposed method, as demonstrated in the case study, efficiently updates the maintenance intervals and reduces the likelihood of failure events. The results of this paper provide a valid maintenance framework for achieving higher operational safety of hydropower stations with minimal resource losses.
KW - Hydro-turbine
KW - Life cycle assessment
KW - Hidden Markov model
KW - Dynamic maintenance
UR - http://www.scopus.com/inward/record.url?scp=85088400415&partnerID=8YFLogxK
U2 - 10.1016/j.ress.2020.107129
DO - 10.1016/j.ress.2020.107129
M3 - Article
VL - 204
SP - 1
EP - 11
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
SN - 0951-8320
M1 - 107129
ER -