RESEARCH PAPER
Remaining useful life prediction of cylinder liner based on nonlinear degradation model
Yongfang Zhang
2,3
1
Xi’an University of Technology, School of Mechanical and Precision Instrument Engineering, Xi’an 710048, PR China
2
Xi’an Jiaotong University, State Key Laboratory for Manufacturing Systems Engineering, Xi’an 710049, PR China
3
Xi’an University of Technology, School of Printing, Packaging Engineering and Digital Media Technology, Xi’an 710054, PR China
Publication date: 2022-03-31
Eksploatacja i Niezawodność – Maintenance and Reliability 2022;24(1):62-69
HIGHLIGHTS
- A nonlinear degradation model is established to predict the RUL.
- The off-line and on-liner data are used to estimate the unknow parameters adaptively.
- The proposed model has a high evaluation accuracy
KEYWORDS
remaining useful lifecylinder liner wearnonlinear degradationmaximum likelihoodestimationadaptive PDF
ABSTRACT
In order to effectively monitor the wear and predict the life of cylinder liner, a nonlinear degradation model with multi-source uncertainty based on Wiener process is established to evaluate the remaining useful life (RUL) of cylinder liner wear. Due to complex service performance of cylinder liner, the uncertainty of operational environment and working conditions of cylinder liner wear are considered into the model by a random function. The probability density function (PDF) formula of RUL is derived, and the maximum likelihood estimation method is adopted to estimate the unknown parameters of PDF. Considering the evaluated parameters as the initial values, the model parameters are updated adaptively, and an adaptive PDF is obtained. Furthermore, the proposed model is compared with two classical degradation models. The results show that the proposed model has a good performance for predicting the life, and the error is within 5%. The method can provide a reference for condition monitoring of cylinder liner wear.
REFERENCES (33)
1.
Baker C, Theodossiades S, Rahmani R, Rahnejat H, Fitzsimons B. On the transient three-dimensional tribodynamics of internal combustion engine top compression ring. Journal of Engineering for Gas Turbines and Power 2017; 139(6): 062801, https://doi.org/10.1115/1.4035....
2.
Cousseau T, Serbino E, Rejowski E, Sinatora A. Influence of steadite on the tribological behavior of cylinder liners. Industrial Lubrication and Tribology 2019; 71(2): 324-332, https://doi.org/10.1108/ILT-05....
3.
Deulgaonkar V, Joshi K, Jawale P, Bhutada S, Fernandes S. Failure analysis of timing device piston and supply pump vanes in fuel injection system for transport utility vehicles. Journal of Failure Analysis and Prevention 2020; 21(1): 172-178, https://doi.org/10.1007/s11668....
4.
Ellefsen AL, Bjorlykhaug E, Aesoy V, Ushakov S, Zhang HX. Remaining useful life predictions for turbofan engine degradation using semisupervised deep architecture. Reliability Engineering and System Safety 2019; 183: 240-251, https://doi.org/10.1016/j.ress....
5.
Grabon W, Pawlus P, Wos S, Koszela W, Wieczorowski M. Effects of cylinder liner surface topography on friction and wear of liner-ring system at low temperature. Tribology International 2018; 121: 148-160, https://doi.org/10.1016/j.trib....
6.
Gao JX, Yuan YP. Probabilistic modeling of stiffness degradation for fiber reinforced polymer under fatigue loading. Engineering Failure Analysis 2020; 116: 104733, https://doi.org/10.1016/j.engf....
7.
Gao JX, Yuan YP, Xu RX. A framework for fatigue life prediction of materials under the multi-level cyclic loading. Engineering Failure Analysis 2021; 127: 105496, https://doi.org/10.1016/j.engf....
8.
Giorgio M, Guida M, Pulcini G. A state-dependent wear model with an application to marine engine cylinder liners. Technometrics 2010; 52(2): 172-187, https://doi.org/10.1198/TECH.2....
9.
Gao ZY, Li J, Wang RX. Prognostics uncertainty reduction by right-time prediction of remaining useful life based on hidden Markov model and proportional hazard model. Eksploatacja i Niezawodnosc-Maintenance and Reliability 2021; 23 (1): 154–164, http://dx.doi.org/10.17531/ein....
10.
Huynh KT. An adaptive predictive maintenance model for repairable deteriorating systems using inverse Gaussian degradation process. Reliability Engineering and System Safety 2021; 213: 107695, https://doi.org/10.1016/j.ress....
11.
Jin Y, Shan C, Wu Y, Xia YM, Zhang YT, Zeng L. Fault diagnosis of hydraulic seal wear and internal leakage using wavelets and wavelet neural network. IEEE Transactions on Instrumentation and Measurement 2019; 68(4): 1026-1034, https://doi.org/10.1109/TIM.20....
12.
Kim ES, Kim SM, Lee YZ. The effect of plateau honing on the friction and wear of cylinder liners. Wear 2018; 400: 207-212, https://doi.org/10.1016/j.wear....
13.
Kang JX, Lu YJ, Luo HB, Li J, Hou YT, Zhang YF. Wear assessment model for cylinder liner of internal combustion engine under fuzzy uncertainty. Mechanics & Industry 2021; 22: 29, https://doi.org/10.1051/meca/2....
14.
Lyu F, Zhang JH, Sun GM, Xu B, Pan M, Huang XC, Xu HG. Research on wear prediction of piston/cylinder pair in axial piston pumps. Wear 2020; 456: 203338, https://doi.org/10.1016/j.wear....
15.
Shi J, Ma ZH. A numerical approach for predicting the remaining useful life of an aviation hydraulic pump based on monitoring abrasive debris generation. Mechanical Systems and Signal Processing 2020; 136: 106519, https://doi.org/10.1016/j.ymss....
16.
Lyu H, Wang S, Zhang X, Yang Z, Pecht M. Reliability modeling for dependent competing failure processes with phase-type distribution considering changing degradation rate. Eksploatacja i Niezawodnosc-Maintenance and Reliability 2021; 23 (4): 627-635, http://doi.org/10.17531/ein.20....
17.
Prakash O, Samantaray AK. Prognosis of dynamical system components with varying degradation patterns using model-data-fusion. Reliability Engineering and System Safety 2021; 213: 107683, https://doi.org/10.1016/j.ress....
18.
Prakash O, Samantaray AK, Bhattacharyya R. Adaptive prognosis of hybrid dynamical system for dynamic degradation patterns. IEEE Transactions on Industrial Electronics 2020; 67(7): 5717-5728, https://doi.org/10.1109/TIE.20....
19.
Ramteke SM, Chelladurai H, Amarnath M. Diagnosis of liner scuffing fault of a diesel engine via vibration and acoustic emission analysis. Journal of Vibration Engineering & Technologies 2020; 1-19, https://doi.org/10.1007/s42417....
20.
Ravikumar KN, Kumar H, Kumar GN, Gangadharan KV. Fault diagnosis of internal combustion engine gearbox using vibration signals based on signal processing techniques. Journal of Quality in Maintenance Engineering 2020; 27(2): 385-412, https://doi.org/10.1108/JQME-1....
21.
Si XS, Wang WB, Hu CH, Zhou DH, Pecht MG. Remaining useful life estimation based on a nonlinear diffusion degradation process. IEEE Transactions on Reliability 2012; 61(1): 50-67, https://doi.org/10.1109/TR.201....
22.
Shen LJ, Wang YD, Zhai QQ, Tang YC. Degradation modeling using stochastic processes with random initial degradation. IEEE Transactions on Reliability 2019; 68(4); 1320-1329, https://doi.org/10.1109/TR.201....
23.
Wakiru JM, Pintelon L, Muchiri PN, Chemweno PK. A review on lubricant condition monitoring information analysis for maintenance decision support. Mechanical Systems and Signal Processing 2019; 118: 108-132, https://doi.org/10.1016/j.ymss....
24.
Wang D, Zhao Y, Yang FF, Tsui KL. Nonlinear-drifted Brownian motion with multiple hidden states for remaining useful life prediction of rechargeable batteries. Mechanical Systems and Signal Processing 2017; 93: 531-544, https://doi.org/10.1016/j.ymss....
25.
Wang H, Ma XB, Zhao Y. An improved Wiener process model with adaptive drift and diffusion for online remaining useful life prediction.Mechanical Systems and Signal Processing 2019; 127: 370-387, https://doi.org/10.1016/j.ymss....
26.
Wopelka T, Cihak-Bayr U, Lenauer C, Ditroi F, Takacs S, Sequard-Base J, Jech M. Wear of different material pairings for the cylinder linerpiston ring contact. Industrial Lubrication and Tribology 2018; 70(4): 687-699, https://doi.org/10.1108/ILT-07....
27.
Wu C, Sun H, Lin S, Gao S. Remaining useful life prediction of bearings with different failure types based on multi-feature and deep convolution transfer learning. Eksploatacja i Niezawodnosc-Maintenance and Reliability 2021; 23 (4): 685–694, http://doi.org/10.17531/ein.20....
28.
Xu XD, Tang SJ, Yu CQ, Xie J, Han XB, Ouyang MG. Remaining useful life prediction of lithium-ion batteries based on Wiener process under time-varying temperature condition. Reliability Engineering and System Safety 2021; 214: 107675, https://doi.org/10.1016/j.ress....
29.
Xu XJ, Zhao ZZ, Xu XB, Yang JB, Chang LL, Yan XP, Wang GD. Machine learning-based wear fault diagnosis for marine diesel engine by fusing multiple data-driven models. Knowledge-Based Systems 2020; 190: 105324, https://doi.org/10.1016/j.knos....
30.
Yu WN, Tu WB, Kim Y, Mechefske C. A nonlinear-drift-driven Wiener process model for remaining useful life estimation considering three sources of variability. Reliability Engineering and System Safety 2021; 212: 107631, https://doi.org/10.1016/j.ress....
31.
Yu WN, Shao YM, Xu J, Mechefske C. An adaptive and generalized Wiener process model with a recursive filtering algorithm for remaining useful life estimation. Reliability Engineering and System Safety 2022; 217: 108099, https://doi.org/10.1016/j.ress....
32.
Zabala B, Igartua A, Fernandez X, Pestner C, Ofner H, Knaus O, Abramczuk M, Tribotte P, Girot F, Roman E, Nevshupa R. Friction and wear of a piston ring/cylinder liner at the top dead centre: experimental study and modelling. Tribology International 2017; 106: 23-33, https://doi.org/10.1016/j.trib....
33.
Zhai QQ, Ye ZS. RUL prediction of deteriorating products using an adaptive Wiener process model. IEEE Transactions on Industrial Informatics 2017; 13(6); 2911-2921, https://doi.org/10.1109/TII.20....
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