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Use of the lognormal distribution for the coefficients of friction and wear

机译:将对数正态分布用于摩擦和磨损系数

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To predict the reliability of a system, an engineer might allocate a distribution to each input. This raises a question: how to select the correct distribution? Siddall put forward an evolutionary approach that was intended to utilise both the understanding of the engineer and available data. However, this method requires a subjective initial distribution based on the engineer's understanding of the variable or parameter. If the engineer's understanding is limited, the initial distribution will be misrepresentative of the actual distribution, and application of the method will likely fail. To provide some assistance, the coefficients of friction and wear are considered here. Basic tribology theory, dimensional issues and the central limit theorem are used to argue that the distribution for each of the coefficients will typically be like a lognormal distribution. Empirical evidence from other sources is cited to lend support to this argument. It is concluded that the distributions for the coefficients of friction and wear would typically be lognormal in nature. It is therefore recommended that the engineer, without data or evidence to suggest differently, should allocate a lognormal distribution to the coefficients of friction and wear.
机译:为了预测系统的可靠性,工程师可以为每个输入分配一个分布。这就提出了一个问题:如何选择正确的分布? Siddall提出了一种进化方法,旨在利用对工程师的理解和可用数据。但是,此方法需要基于工程师对变量或参数的理解的主观初始分布。如果工程师的理解有限,则初始分布将无法正确代表实际分布,并且该方法的应用可能会失败。为了提供一些帮助,此处考虑了摩擦系数和磨损系数。基本的摩擦学理论,尺寸问题和中心极限定理被用来争论每个系数的分布通常会像对数正态分布。引用了其他来源的经验证据来支持该论点。结论是,摩擦系数和磨损系数的分布本质上通常是对数正态的。因此,建议工程师在没有数据或证据证明不同的情况下,应为摩擦系数和磨损系数分配对数正态分布。

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