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Models for Roller Chain Condition Monitoring

机译:滚子链状态监测模型

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摘要

One of the challenges in condition monitoring systems is the residual life time prediction. This prediction is done based on statistical methods, based on physical knowledge about the considered process or a combination of these approaches. Physical knowledge of the system is a result of long-term experience of process operators. However, it can be gained as well by analyzing appropriately designed process models. The additional benefit of such models is, that particular effects and their impact on the process behavior can be analyzed in detail and without plant operation in a shorter time. The current contribution developed in the framework of the research project Model Based Hierarchic Condition Monitoring presents such models for condition monitoring of roller chains. First, already existing high order dynamic models given by nonlinear differential equations of such chains are extended to incorporate effects that occur due to a deterioration of the chain condition. Then, a simple model is developed and compared to the high order model. Based on the two models the change in the process behavior due to a deterioration of the roller chain condition is analyzed to illustrate that these models can be used in future research in the above mentioned research project to better predict the residual life time of the considered roller chains.
机译:状态监测系统的挑战之一是残余寿命预测。基于关于考虑过程的物理知识或这些方法的组合,基于统计方法来基于统计方法来完成该预测。系统的物理知识是流程运营商长期经验的结果。但是,它也可以通过分析适当设计的过程模型来获得。这些模型的额外益处是,可以详细地分析特定的效果及其对过程行为的影响,并且在较短的时间内没有植物操作。基于研究项目模型的框架在基于研究项目模型的框架中产生的当前贡献提供了滚子链条状况监测的这种模型。首先,已经通过这种链的非线性微分方程给出的已经存在的高阶动态模型被扩展以结合由于链条状况的劣化而发生的效果。然后,开发了一个简单的模型,并与高阶模型进行了比较。基于两个模型,分析了由于滚子链条件的劣化而导致的过程行为的变化,以说明这些模型可以在上述研究项目中的未来研究中使用,以更好地预测所考虑的滚筒的剩余寿命时间链条。

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