Online multichannel forging tonnage monitoring and fault pattern discrimination using principal curve
Online multichannel forging tonnage monitoring and fault pattern discrimination using principal curve
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DOI：
10.1115/1.2193552
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发表时间：
2006-11-01
影响因子：
4
通讯作者：
Chang, Tzyy-Shuh
中科院分区：
文献类型：
--
作者：
Kim, Jihyun;Huang, Qiang;Chang, Tzyy-Shuh
由于对工艺条件变化的反应较晚，锻造过程通常会接触到大量的缺陷产品。为了实现在线过程监控，通常从压力机采集多通道吨位信号，因为吨位信号包含关于产品和工艺条件的大量实时信息。本文提出了一种用于锻造过程监测的多通道吨位信号轮廓变化检测和故障模式分类的方法。这些变化包括全局或局部轮廓偏差，它们分别对应于一个周期内整个过程周期或过程段(S)的偏差。采用Al曲线法对吨位信号进行特征提取和判别。用曲轴锻造工艺的工业数据验证了所提出的方法。
Due to the late response to process condition changes, forging processes are normally exposed to a large number of defective products. To achieve online process monitoring, multichannel tonnage signals are often collected from the for in press The tonnage signals contain significant amount of real time information regarding the product and the, process conditions. In this paper a methodology is developed to detect profile changes of multichannel tonnage signals for forging process monitoring and to classify fault patterns. The changes include global or local profile deviations, which correspond to deviations of a whole process cycle or process segment(s) within a cycle, respectively. The al curve method is used to conduct feature extraction and discrimination of tonnnage signals. The developed methodology is demonstrated with industry data from a crankshaft forging processes.