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首页> 外文会议>Vibration Institute National Technical Training Symposium and Twenty-Seventh Annual Meeting Jul 9-11, 2003 New Orleans, Louisiana >THE USE OF PEAKVUE~(~R) FOR FAULT DETECTION AND SEVERITY ASSESSMENT: DEMONSTRATED THROUGH REPRESENTATIVE CASE STUDIES
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THE USE OF PEAKVUE~(~R) FOR FAULT DETECTION AND SEVERITY ASSESSMENT: DEMONSTRATED THROUGH REPRESENTATIVE CASE STUDIES

机译：PEAKVUE〜（〜R）在故障检测和严重性评估中的使用：通过代表性的案例研究进行了演示

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摘要

The primary focus in this paper is to demonstrate through several case studies the usefulness of incorporating stress wave analysis into the overall machine condition monitoring program for fault detection, identification, and severity assessment. The analysis methodology employed is the peak value (Peak Vue~(~R)) analysis methodology implemented in the CSI hardware. Emphasis are placed on measurement setup, sensor selection and placement, importance of trending, and severity assessment. Common defects which generate stress waves are pitting in antifriction bearings causing the rollers to impact, fatigue cracking in bearing raceways or gear teeth (generally at the root), scuffing or scoring on gear teeth or antifriction bearing components and others. Each event generally introduces a short term (microseconds to milliseconds) burst of stress wave activity which propagates away from the initiation site at the speed of sound in the medium. The dominate frequency within each burst of activity is inversely related to the duration of the event (short term events, microseconds, excite higher frequencies than long term events, milliseconds). The duration of events is dependent on the initiating source, mass, and speed. The general nature of stress wave activity versus initiating source are briefly discussed in this paper. Case studies are presented which encompass a large variation in stress wave activity. The emphasis will be placed on fault detection, fault classification, severity assessment, measurement setup, sensor selection, and sensor location. The case studies will demonstrate that stress wave analysis provide meaningful backup to normal analysis in some situations and (2) the only means for fault detection, classification, and severity assessment for other situations.
机译：本文的主要重点是通过几个案例研究来证明将应力波分析并入整个机器状态监测程序中以进行故障检测，识别和严重性评估的有用性。所采用的分析方法是在CSI硬件中实现的峰值（Peak Vue〜（R））分析方法。重点放在测量设置，传感器选择和放置，趋势的重要性以及严重性评估上。产生应力波的常见缺陷包括：减摩轴承上的凹痕，导致滚子撞击；轴承滚道或齿轮齿（通常在根部）的疲劳裂纹；齿轮或减摩轴承组件等的擦伤或划痕。每个事件通常都会引入一个短期（微秒至毫秒）的应力波活动爆发，该爆发以介质中的声音速度从起始位置传播开。每个活动爆发中的主要频率与事件的持续时间成反比（短期事件，微秒，比长期事件，毫秒激发的频率更高）。事件的持续时间取决于启动源，质量和速度。本文简要讨论了应力波活动与引发源的一般性质。案例研究涵盖了应力波活动的巨大变化。重点将放在故障检测，故障分类，严重性评估，测量设置，传感器选择和传感器位置上。案例研究将表明，应力波分析在某些情况下为正常分析提供了有意义的备份，并且（2）在其他情况下为故障检测，分类和严重性评估的唯一方法。

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