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首页> 外文期刊>NDT & E international >Statistical pattern analysis of ultrasonic signals for fatigue damage detection in mechanical structures
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Statistical pattern analysis of ultrasonic signals for fatigue damage detection in mechanical structures

机译：用于机械结构疲劳损伤检测的超声信号统计模式分析

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This paper addresses online monitoring of fatigue, damage in polycrystalline alloy structures based on statistical pattern analysis of ultrasonic sensor signals. The real-time data-driven method for fatigue damage monitoring is based on the concepts derived from statistical mechanics, symbolic dynamics and statistical pattern identification. The underlying concept is detection and identification of small changes in statistical patterns of ultrasonic data streams due to gradual evolution of anomalies (i.e., deviations from the nominal behavior) in material structures. The statistical patterns in terms of the escort distributions from statistical mechanics are derived from symbol sequences that, in turn, are generated from ultrasonic sensors installed on the structures under stress cycles. The resulting information of evolving fatigue damage would provide early warnings of forthcoming failures, possibly, due to widespread crack propagation. The damage monitoring method has been validated by laboratory experimentation in real time on a computer-controlled fatigue damage testing apparatus which is equipped with a variety of measuring instruments including an optical travelling microscope and an ultrasonic flaw detector.
机译：本文基于超声传感器信号的统计模式分析，着手在线监测多晶合金结构中的疲劳，损坏。实时数据驱动的疲劳损伤监测方法基于统计力学，符号动力学和统计模式识别得出的概念。基本概念是检测和识别由于材料结构中异常现象的逐渐演变（即与名义行为的偏差）而导致的超声数据流统计模式中的小变化。根据统计力学的护送分布，统计模式是从符号序列中得出的，而符号序列又是由在应力循环下安装在结构上的超声波传感器生成的。不断演变的疲劳损伤的结果信息可能会由于广泛的裂纹扩展而为即将发生的故障提供预警。通过在计算机控制的疲劳损伤测试设备上进行的实验室实验，实时地验证了损伤监测方法，该设备配备了包括光学旅行显微镜和超声波探伤仪在内的各种测量仪器。

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