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Development and application of stress-wave acoustic diagnostics for roller bearings

机译:滚子轴承应力波声学诊断的开发与应用

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A powerful, innovative diagnostic technique for assessing railcar wheel health characteristics is to listen to the operating sound of a bearing. The emission of acoustic energy (sound) from a wheel bearing is a frequency-dependent and load-related phenomenon. A complementary se t of bearing health data to audible acoustic emission (AE) data, referred to as "stresswave" data, exists at an order of magnitude above traditional vibration-based (i.e., accelerometer) data and contains information about friction and shock conditions in a bearing under highly loaded conditions. These health-related symptoms of shock and friction will provide an early warning capability to prevent flat wheel failures and train derailments through condition-based maintenance (CBM). This paper describes Honeywell's recent work with applying stress-wave AE to perform CBM for today's railroad industry. A detailed description of the railcar wheel bearing problem, failure modes and effects, and technical approach are presented. The summary of a field-test effort capturing AE signatures from a 100-ton railcar truck are provided. A preliminary set of data analysis is presented.
机译:用于评估轨道车轮健康特性的强大,创新的诊断技术是倾听轴承的操作声音。来自车轮轴承的声能(声音)的发射是频率依赖性和载荷相关的现象。向可听声发射(AE)数据的额定健康数据的互补SE T称为“应力波”数据,以高于传统的基于振动(即,加速度计)数据的数量级,并包含有关摩擦和休克条件的信息在高负荷条件下的轴承中。这些与摩擦的健康相关症状将提供早期预警能力,以防止通过基于条件的维护(CBM)来防止扁平轮故障和列车脱轨。本文介绍了霍尼韦尔最近的工作,可以使用压力波AE在今天的铁路行业进行CBM。探测轨道轮轴承问题,故障模式和效果以及技术方法的详细描述。提供了捕获来自100吨铁路卡车的AE签名的现场测试努力的摘要。提出了初步的数据分析。

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