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Extension of durability theory through correlation of wear with acoustic emission to the characteristic values of the ball screw drive

通过将磨损与声发射与滚珠丝杠传动装置的特征值相关联来扩展耐用性理论

基本信息

批准号：
388141462
负责人：
Professor Dr.-Ing. Jürgen Fleischer
金额：
--
依托单位：
Institut für Produktionstechnik (WBK)
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2017
资助国家：
德国
起止时间：
2016-12-31 至 2020-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/388141462?language=en
关键词：
Extension durability theory through correlation

项目摘要

Ball screw drives are currently used in the vast majority of all metal cutting machine tools as the essential drive element. Therefore, the precise knowledge of service life and assurance of availability of the ball screw drive is of decisive economic importance. Currently, the dimensioning of ball screw drives only takes into account fatigue life. This is due to the fact that it is unknown how fatigue life, wear mechanisms and the mechanical behavior of the ball screw drive are correlated.Ball screw drives are subjected to complex and combined wear mechanisms due to the complex movement and the return of the ball. This results in complex presences of wear such as abrasion, adhesion and fatigue. This influences distinctively the service life of the ball screw drive. Additionally the wear mechanisms influence the mechanical characteristics of the ball screw drive e.g. the nut preload or stiffness of the nut. Current methods for wear diagnostics only focus on individual presences of wear and on individual mechanical characteristics. Therefore an integrated understanding of wear mechanisms, wear presences and the mechanical characteristics of the ball screw drive is currently not available. Acoustic Emission is a measurement method with which wear mechanisms can be observed. Acoustic Emission allows better feature extraction because of the higher information density, leading to the observation of the formation of wear. This is currently used for diagnostics in gear boxes and bearings.Objective of this research proposal is an integrated approach correlating wear mechanisms, presences of wear and the mechanical characteristics of the ball screw drive over time with the use of Acoustic Emission. In addition to the established characteristic values for condition monitoring, acoustic emission constitutes a method to more precisely identify signs of wear (e.g. pitting) over time and to spatially assign them to the track of nut and screw or ball and therefore create a depiction of damage progression. This allows to draw conclusions on the effective wear mechanisms. This research attains the goal of correlating the depiction of damage progression received with Acoustic Emission with the mechanical characteristics and the presence of wear (structure-borne noise, temperature, frictional torque, nut preload and characteristic curve of stiffness). By matching these observations a conclusion on the chronological sequence of effective wear mechanism can be drawn. Additionally the effective service and fatigue life of the ball screw drive is quantified by identifying static and dynamic properties as a function of wear development. As a result more precise predictions of the effective service and fatigue life can be derived.

滚珠丝杠传动是目前绝大多数金属加工机床中使用的基本传动元件。因此，准确了解滚珠丝杠传动的使用寿命和保证其可用性具有决定性的经济意义。目前，滚珠丝杠传动的尺寸设计只考虑疲劳寿命。这是因为目前尚不清楚滚珠丝杠传动的疲劳寿命、磨损机制和机械行为之间的关系。由于滚珠丝杠传动的运动和回弹复杂，滚珠丝杠传动受到复杂的组合磨损机制的影响。这会导致复杂的磨损现象，如磨损、粘着和疲劳。这对滚珠丝杠传动的使用寿命有明显的影响。此外，磨损机制影响滚珠丝杠传动的机械特性，例如螺母预紧力或螺母的硬度。目前的磨损诊断方法只关注磨损的个体存在和个体的机械特性。因此，目前还不能对滚珠丝杠传动的磨损机理、磨损存在和机械特性有一个完整的了解。声发射是一种可以观察磨损机理的测量方法。声发射可以更好地提取特征，因为它具有更高的信息密度，从而可以观察到磨损的形成。这项研究的目标是一种综合的方法，利用声发射将磨损机制、磨损存在和滚珠丝杠传动随时间变化的机械特性联系起来。除了已建立的用于状态监测的特征值之外，声发射还构成了一种方法，可以更准确地识别随时间推移的磨损迹象(例如点蚀)，并在空间上将它们分配给螺母、螺丝或球的轨迹，从而创建损伤进程的描述。这使得可以得出关于有效磨损机制的结论。这项研究的目的是将声发射接收到的损伤进程的描述与机械特性和磨损的存在(结构噪声、温度、摩擦扭矩、螺母预紧力和刚度特征曲线)相关联。通过匹配这些观察结果，可以得出有效磨损机制的时间顺序的结论。此外，通过确定静态和动态特性作为磨损发展的函数，量化了滚珠丝杠传动的有效使用寿命和疲劳寿命。因此，可以更准确地预测有效使用寿命和疲劳寿命。

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Autoconfiguration of a Vibration-Based Anomaly Detection System with Sparse a-priori Knowledge Using Autoencoder Networks

DOI：
10.1007/978-3-662-62138-7_52
发表时间：
2020
期刊：
2016 International Conference on Signal Processing and Communications (SPCOM)
影响因子：
0
作者：
J. Hillenbrand;J. Fleischer
通讯作者：
J. Hillenbrand;J. Fleischer

Unsupervised Detection of State Changes During Operation of Machine Elements

机器元件运行期间状态变化的无监督检测