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Dynamic failure rate model of an electric motor comparing the Military Standard and Svenska Kullagerfabriken (SKF) methods

机译:电动机动态故障率模型与军用标准和Svenska Kullagerfabriken(SKF)方法比较

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Electric motors are industrial systems’ components widely diffused enabling all productive processes and safety equipment. They are affected by aging effect with a contribution based on the environmental condition on which they work. In order to design efficient maintenance plans, the behaviour of their main components, such as bearings and winding, has to be predicted. Therefore, a model-based methodology is applied aiming at codifying the failure rate of an electric engine, taking into account the thermal aging and relevant environment boundary conditions in which bearings and winding operate. The winding failure mode is coded by means of the Military standard technique while the bearings one is simulated comparing the Military Standard and the Svenska Kullagerfabriken (SKF) techniques. While the former predicts more conservative behaviours, the latter, taking into account lubrication conditions, dynamic loads and a better knowledge of materials quality, enables to capture the evolution of the operative conditions. The proposed reliability model can capture both the deterministic and stochastic behaviour of the electric motor: it belongs to the field of hybrid automaton application; the model is coded by means of the emerging software framework called SHYFTOO. The proposed model and the Monte Carlo simulation process that performs its evolution can support the development of a new class of electric motors: a cyber-physical oriented electric motor.
机译:电动机是工业系统的组件广泛扩散,可实现所有生产工艺和安全设备。它们受到衰老效应的影响,基于其工作的环境条件的贡献。为了设计高效的维护计划,必须预测其主要部件的行为,例如轴承和绕组。因此,考虑到轴承和绕组操作的热老化和相关环境边界条件,应用基于模型的方法。绕组故障模式通过军事标准技术进行编码,而轴承是在比较军事标准和SVENSKA KULLAGERFABRIKEN(SKF)技术的模拟中。虽然前者预测更保守的行为,后者,考虑到润滑条件,动态载荷和更好的材料质量知识,可以捕获操作条件的演变。所提出的可靠性模型可以捕获电动机的确定性和随机行为:它属于混合自动化应用领域;该模型通过名为Shyftoo的新兴软件框架进行编码。拟议的模型和蒙特卡罗模拟过程,执行其进化可以支持新型电动机的开发:一种网络地定向电动机。

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