Lifetime prediction of self-lubricating spherical plain bearings based on physics-of-failure model and accelerated degradation test

Wang, Yashun; Fang, Xin; Zhang, Chunhua; Chen, Xun; Lu, Jinzhong

doi:10.17531/ein.2016.4.7

Cited by 19 publications

(20 citation statements)

References 26 publications

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“…13 Wang et al comprehensively analyzed the wear characteristics, structure and operation parameters of self-lubricating spherical plain bearings; furthermore, they presented lifetime prediction method, based on physics-of-failure model and ADT. 14 A succinct method with the advantages of a short time and a small sample size was proposed in order to realize a fast and precise life prediction of the woven self-lubricating liners. Firstly, the life tests of heavyload self-lubricating liners were carried out and the wear degradation curves were fitted by support vector regression.…”

Section: Introductionmentioning

confidence: 99%

Life prediction of heavy-load self-lubricating liners

Hao

Wang

Pan

2021

Advances in Mechanical Engineering

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To address the issues of long testing periods and small sample sizes while evaluating the service life of heavy-load self-lubricating liners, we propose a succinct method based on Monte Carlo simulation that is significantly fast and requires a small sample size. First, the support vector regression algorithm was applied to fit the degradation trajectories of the wear depth, and the first and second characteristic parameter vectors of the wear depth as well as the corresponding distribution models were obtained. Next, sample expansion was performed using Monte Carlo simulation and the inverse transform method. Finally, based on the failure criterion of the self-lubricating liner, the service lives and distribution models of the expanded samples were obtained; subsequently, the corresponding reliability life indices were provided. Our results indicate that when the expanded sample was large enough, the proposed prediction method exhibited a relatively high prediction accuracy. Therefore, these results provide theoretical support for shortening the testing cycle used to evaluate the service life of self-lubricating liners and for accelerating the research and development of self-lubricating spherical plain bearing products.

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Section: Introductionmentioning

confidence: 99%

Life prediction of heavy-load self-lubricating liners

Hao

Wang

Pan

2021

Advances in Mechanical Engineering

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“…Numerous approaches have been proposed, and many of them were successfully applied in the industry. 4, 5 However, model-based prognosis needs to constantly improve the model through an in-depth understanding of health degradation mechanism where the fault type in question is frequently unique and varies from component to component. Establishing an accurate physical model to prognosticate the health of complex industrial system is very difficult and expensive, not meet the development of intelligent manufacturing.…”

Section: Introductionmentioning

confidence: 99%

Health prognosis approach for manufacturing systems based on quality state task network

Cui

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part B:

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Previous studies on health prognosis are exceedingly dependence on the failure data and sensor data of a single component of manufacturing systems, and the holistic health prognosis techniques applicable to whole manufacturing systems still remain a challenge due to its increasingly physical and functional complexity. Therefore, a generalized health prognosis method is presented based on the deep fusion of quality-oriented big data of operational process of manufacturing systems. First, the generalized connotation of manufacturing system health is explained from the aspects of the physical composition and functional characteristics of manufacturing systems, and the quality state task network is proposed to organize quality-oriented big operational data, which improve the state transparency of the manufacturing system and lay the foundation of holistic health prognosis. Second, key characterization parameters in quality state task network are defined. Specifically, the performance state is analyzed based on multistate characteristics by considering the effects of stochastic degradation processes; the product quality state is quantified by using a process model that is established based on monitoring and inspection data; and the task execution state is quantitatively described by analyzing the evolution of task demand among machines. Third, an integrated model is built by integrating the three above-mentioned states as two key indicators, namely, qualified degree and mission reliability, for the comprehensive prognosis of the health of manufacturing systems. Finally, the effectiveness of the proposed approach is verified with a case study on the health prognosis of a cylinder head manufacturing system.

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“…Therefore, under such extreme and complex conditions, spherical plain bearings likely experience severe wear because of the agglutination or undergo kinetic characteristics loss because of the overlarge clearances between the bearing inner ring and outer ring. 3…”

Section: Introductionmentioning

confidence: 99%

Investigation on surface morphology and tribological property generated by vibration assisted strengthening on aviation spherical plain bearings

Yuan

Qin

Cheng

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part C:

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The extreme and complex working conditions require aviation spherical plain bearings not only to have high machining accuracy and low surface roughness, but also to possess high surface microhardness and lubricant retaining capability. This paper presents a vibration assisted strengthening approach to achieving the synergistic effects of the surface property-improving and appearance-improving. The research attempts to answer how vibration assisted strengthening technique can improve the surface tribological properties of aviation spherical plain bearing components particularly in light of proposing the flat-headed asperity distribution model and the corresponding elastic–plastic contact modelling for the special processed surface morphology. Subsequently, the models are corroborated by the experimental results of characterizing the surface morphology produced by vibration assisted strengthening with different parameters such as rolling times and rolling static force. The surface tribological properties of spherical plain bearing specimens were studied by employing the UMT-TriboLab platform. The theoretical analysis and experimental results indicate that the surface asperities of spherical plain bearing components processed with repeated high frequency strikes present a flat-headed distribution but not Gauss distribution. It characterizes with a marked majority of produced small asperities with similar height, which is beneficial to frictional couple contacts and a lot of original valleys retaining lubricants. The processing technique contributes to increasing the surface microhardness by 20% and decreasing the surface roughness from about Ra 0.4 µm to below Ra 0.1 µm. The ball-on-flat friction tests demonstrate that both the special flat-headed surface structure and the elevated microhardness can attribute the improvement of tribological properties and wear resistance performance of spherical plain bearings.

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Lifetime prediction of self-lubricating spherical plain bearings based on physics-of-failure model and accelerated degradation test

Abstract: WAng Y, FAng X, ZhAng C, Chen X, Lu J. Lifetime prediction of self-lubricating spherical plain bearings based on physics-of-failure model and accelerated degradation test. eksploatacja i niezawodnosc -Maintenance and Reliability 2016; 18 (4): 528-538, http://dx.doi.

Cited by 19 publications

References 26 publications

Life prediction of heavy-load self-lubricating liners

Life prediction of heavy-load self-lubricating liners

Health prognosis approach for manufacturing systems based on quality state task network

Investigation on surface morphology and tribological property generated by vibration assisted strengthening on aviation spherical plain bearings

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