Assessing Total Average Service Life for Crankshafts under Routine Operating Conditions

IF 0.3 Q4 ENGINEERING, MECHANICAL

Journal of Machinery Manufacture and Reliability Pub Date : 2026-10-03 DOI:10.1134/S1052618826700676

S. A. Velichko, E. A. Anashkin, N. V. Rakov, P. A. Ionov, I. A. Mikheychev, A. V. Razumkov

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引用次数: 0

Abstract

Crankshafts operate under severe conditions, experiencing periodic loads from gas pressure and the inertial forces originating from translational and rotational motion. Up to 40% of crankshafts are replaced annually, underutilizing up to 50% of their repairing sizes owing to the absence of a reliable method for estimating service life parameters. This paper is devoted to testing a method for determining the probability of failure-free operation and the total average crankshaft service life under routine operating conditions. Comparative calculation results are presented for crankshaft service life based on regrinding from the ith to the jth repairing sizes and applying a metal coating while maintaining the rated and repairing sizes. It is proven that the resulting total average service life of crankshafts under routine operating conditions calculated with the use of the new method by the example of the YaMZ-238NB, is more reliable than the average service life calculated based on the Weibull law.

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评估曲轴在常规操作条件下的总平均使用寿命

曲轴在恶劣的条件下工作，承受来自气体压力的周期性载荷以及来自平移和旋转运动的惯性力。每年更换的曲轴高达40%，由于缺乏可靠的估算使用寿命参数的方法，其维修尺寸的利用率高达50%。本文致力于试验一种在常规工况下确定曲轴无故障运行概率和总平均使用寿命的方法。给出了在保持额定尺寸和修复尺寸的情况下，从第i到第j个修复尺寸再磨削并涂金属涂层的曲轴使用寿命的对比计算结果。以YaMZ-238NB为例，计算得到的曲轴在常规工况下的总平均使用寿命比基于威布尔定律计算的平均使用寿命更可靠。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Machinery Manufacture and Reliability ENGINEERING, MECHANICAL-

CiteScore

0.80

自引率

33.30%

发文量

期刊介绍： Journal of Machinery Manufacture and Reliability is devoted to advances in machine design; CAD/CAM; experimental mechanics of machines, machine life expectancy, and reliability studies; machine dynamics and kinematics; vibration, acoustics, and stress/strain; wear resistance engineering; real-time machine operation diagnostics; robotic systems; new materials and manufacturing processes, and other topics.