基于 FTA-AK-SS 的无线传能尿道阀可靠性分析

doi:10.1007/s12204-024-2704-5

摘要/Abstract

摘要： 针对现有尿道阀可靠性分析计算效率低的问题，提出一种基于主动学习Kriging（active learning Kriging, AK）代理模型与子集模拟（subset simulation, SS）算法并结合故障树分析（fault tree analysis, FTA）的无线传能尿道阀高效可靠性分析方法，即FTA-AK-SS。根据FTA原理，建立无线传能尿道阀故障树模型，确定其最小割集及底事件，进而确定影响其可靠性的随机变量；利用U学习函数选择性添加随机变量样本点更新初始Kriging代理模型；同时结合SS算法，实现无线传能尿道阀的可靠性与可靠性灵敏度分析。仿真结果表明：与传统的蒙特卡罗模拟（MCS）和FTA-Kriging-SS方法相比，所提方法在保证计算精度的前提下，显著提高了无线传能尿道阀可靠性计算效率；橡胶垫老化、接收线圈腐蚀与位置偏移对无线传能尿道阀可靠性影响显著。本研究可为实现尿道阀高效可靠性计算分析提供一种新思路。

关键词: 尿道阀，可靠性，主动学习Kriging，故障树分析，子集模拟

Abstract: Aimed at the problem of the low computational efficiency of the existing urethral-valve reliability analysis, an efficient reliability analysis method of the wireless energy-transmitting urethral-valve (WETUV) was proposed. The method is called FTA-AK-SS, based on the active learning Kriging (AK) model, subset simulation (SS) algorithm, and fault tree analysis (FTA). According to the principle of FTA, we established the fault tree model of the WETUV to determine its minimum cut set and bottom events. Then we defined the random variables affecting its reliability. The U learning function was used to selectively add the sample points of random variables to update the initial Kriging surrogate model. At the same time, combined with the SS algorithm, the reliability and sensitivity analyses of the WETUV were realized. The result shows that compared with the traditional Monte Carlo simulation and FTA-Kriging-SS methods, the proposed method significantly improves the calculation efficiency of the WETUV under the premise of ensuring calculation accuracy. The reliability of the WETUV is greatly affected by the rubber pad’s aging, the receiver coil’s corrosion, and the position deviation. This study can provide a new way to realize a high-efficiency reliability calculation and analysis for urethral valves.

Key words: urethral-valve, reliability, active learning Kriging (AK), fault tree analysis (FTA), subset simulation (SS)

中图分类号:

TH137R318.6

. 基于 FTA-AK-SS 的无线传能尿道阀可靠性分析[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(4): 815-824.

Yin Mao, Li Xiao. Reliability Research of Wireless Energy Transmitting Urethral Valve Based on FTA-AK-SS[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(4): 815-824.

参考文献

[1] LIAO L M. Urodynamics[M]. Beijing: Science Press, 2019 (in Chinese). [2] MARZIALE L, LUCARINI G, MAZZOCCHI T, et al. Comparative analysis of occlusion methods for artificial sphincters [J]. Artificial Organs, 2020, 44(9): 995-1005. [3] MARZIALE L, LUCARINI G, MAZZOCCHI T, et al. Artificial sphincters to manage urinary incontinence: A review [J]. Artificial Organs, 2018, 42(9): E215-E233. [4] MAZZOCCHI T, RICOTTI L, PINZI N, et al. Magnetically controlled endourethral artificial urinary sphincter [J]. Annals of Biomedical Engineering, 2017, 45(5): 1181-1193. [5] LI Y P, LI X A, ZHANG R, et al. Modeling and performance analysis for the urethral valve used to manage severe urinary incontinence [J]. Journal of Mechanics in Medicine and Biology, 2020, 20(8): 1950013. [6] ZENG Z X. Reliability analysis of urethral valve driven by SMA based on FMECA and FTA [D]. Guangzhou: Guangdong University of Technology, 2021 (in Chinese). [7] BANAKHAR M, ALJEHANI A, ABDULSALAM A, et al. Posterior urethral valve new scoring system: Reliability and reproducibility [J]. Neurourology and Urodynamics, 2019, 38: S276-S276. [8] DELGADO-MIGUEL C, MUNOZ-SERRANO A, AMESTY V, et al. Artificial urinary sphincter in congenital neuropathic bladder: Very long-term outcomes [J]. International Journal of Urology, 2022, 29(7): 692-697. [9] SINGH J, SMITH T G III, WESTNEY O L. Artificial urinary sphincter considerations in men with prior inflatable penile prosthesis placement [J]. The Journal of Sexual Medicine, 2022, 19(10): 1495-1498. [10] BIARDEAU X, HACHED S, LOUTOCHIN O, et al. Montreal electronic artificial urinary sphincters: Our futuristic alternatives to the AMS800? [J]. Canadian Urological Association Journal, 2017, 11(10): E396-E404. [11] TANAKA M, WANG F, ABE K, et al. A closed-loop transcutaneous power transmission system with thermal control for artificial urethral valve driven by SMA actuator [J]. Journal of Intelligent Material Systems and Structures, 2006, 17(8/9): 779-786. [12] LI X, GUAN T, LIU C B, et al. Modeling and simulation of urethra valve of bladder power pump [J]. Journal of Mechanics, 2014, 30(3): 255-264. [13] HU Z, LI X, GUAN T. A study on performance and reliability of urethral valve driven by ultrasonic-vaporized steam [J]. International Journal of Automation and Computing, 2020, 17(5): 752-762. [14] XU C L. Research on reliability analysis method of structural system based on the Kriging model [D]. Harbin: Harbin Engineering University, 2021 (in Chinese). [15] THAPA A, ROY A, CHAKRABORTY S. Reliability analysis of underground tunnel by a novel adaptive Kriging based metamodeling approach [J]. Probabilistic Engineering Mechanics, 2022, 70: 103351. [16] YANG Z, PAK U, KWON C, et al. A reliability-based robust optimization design for the drum brake using adaptive Kriging surrogate model [J]. Quality and Reliability Engineering International, 2023, 39(1): 454-471. [17] LI N, HOU B W, DU X L, et al. Seismic reliability analysis of buried segmented pipelines based on active learning Kriging model [J]. Journal of Harbin Institute of Technology, 2021, 53(10): 112-121 (in Chinese). [18] TANG H S, GUO X Y, XUE S T. Time-varying reliability analysis of nonlinear stochastic dynamic systems based on generalized subset simulation and adaptive Kriging model [J]. Journal of Vibration and Shock, 2021, 40(21): 47-54 (in Chinese). [19] ZHOU C C, LI C, ZHANG H L, et al. Reliability and sensitivity analysis of composite structures by an adaptive Kriging based approach [J]. Composite Structures, 2021, 278: 114682. [20] ZHOU C C, CHANG Q, ZHOU C P, et al. Fault tree analysis of an aircraft flap system based on a non-probability model [J]. Journal of Tsinghua University (Science and Technology), 2021, 61(6): 636-642 (in Chinese). [21] QIN D T, XIE L Y. Modern mechanical design manual[M]. Beijing: Chemical Industry Press, 2019 (in Chinese). [22] ECHARD B, GAYTON N, LEMAIRE M. AK-MCS: An active learning reliability method combining Kriging and Monte Carlo simulation [J]. Structural Safety, 2011, 33(2): 145-154. [23] AU S K, BECK J L. Estimation of small failure probabilities in high dimensions by subset simulation [J]. Probabilistic Engineering Mechanics, 2001, 16(4): 263-277. [24] MORIO J. Global and local sensitivity analysis methods for a physical system [J]. European Journal of Physics, 2011, 32(6): 1577-1583. [25] WU Y T, MOHANTY S. Variable screening and ranking using sampling-based sensitivity measures [J]. Reliability Engineering & System Safety, 2006, 91(6): 634-647. [26] LI L Y, LU Z Z, FENG J, et al. Moment-independent importance measure of basic variable and its state dependent parameter solution [J]. Structural Safety, 2012, 38: 40-47. [27] FANG X, YAN Z, WANG H, et al. A shared energy storage optimal operation method considering the risk of probabilistic voltage unbalance factor limit violation [J]. Journal of Shanghai Jiao Tong University, 2022, 56(7): 827-839 (in Chinese). [28] JIANG C, QIU H B, YANG Z, et al. A gene