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Reduce project lead times, rig capacity and costs during the validation of commercial truck disc brakes via strain gauge measurements

机译:通过应变仪测量验证商业卡车盘式刹车期间,减少项目交货时间,钻机容量和成本

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Typical brake validation includes the fatigue testing of major structural components such as operating shafts, carriers, bridges and housings. These components are regularly redesigned to suit different Customer applications and installations with the result of a heavy demand on test laboratory resources and rig capacity. Further to this the drive to reduce weight and cost of the final product has driven the aggressive optimisation of these components with the move from a test philosophy of limited testing with high safety factor to one with a statistical approach with accurately predicted component lives and confidence values. The former approach usually involves the testing of a relatively low quantity of products with the aim to complete a predetermined load collective. As a result these collectives, which are often derived from known usage data, will contain safety factors that take into account the low number of parts tested. The statistical approach involves the testing of a much higher number of samples to failure to determine a B10 life for each component at different load levels with known confidence. For any one component and failure mode this will need a minimum of 42 test results to failure. This paper describes how strain measurements are recorded in the areas of high stress and known fracture locations can be used to determine the most suitable test regime to provide results with statistical confidence while minimising validation resources, costs and lead times.
机译:典型的制动验证包括主要结构部件的疲劳测试,例如操作轴,载体,桥和壳体。这些组件经常重新设计,以适应不同的客户应用程序和安装,从而对测试实验室资源和钻机容量进行沉重的需求。此外,为了减少最终产品的重量和成本的驱动已经推动了这些组件的积极优化,并且从高安全系数的测试哲学的转变,具有统计方法,具有精确预测的部件生命和置信度值。前一种方法通常涉及测试相对较少量的产品,其目的是完成预定的负载集体。结果,这些通常来自已知使用数据的集体,将包含考虑到测试的零件数量的安全因素。统计方法涉及测试更高数量的样品,以便在不同的负载水平下确定每个组分的B10寿命,具有已知的置信度。对于任何一个组件和故障模式,这需要至少42个测试结果失败。本文介绍了如何在高应力和已知的骨折位置记录菌株测量的程度测量,可用于确定最合适的测试制度,以便以统计信心提供统计信心的结果,同时最小化验证资源,成本和交货时间。

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