基于曲线拟合特征信号的自主实时过程优化

M. Klingajay, Sirisorn Mitranon
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引用次数: 1

摘要

螺纹紧固操作已经使用了几十年,目的是将一个组件连接到另一个组件。它的任务很受欢迎,因为它们便于拆卸维护、搬迁和回收。螺纹紧固过程通常是手动进行的,因为它是一个很难自动化的问题。因此,很少发表关于自动螺纹紧固的研究。本文研究了螺杆插入过程的自动监控问题。监控问题是基于插入过程中产生的扭矩与插入深度曲线来预测螺纹插入的完整性。建立了自攻螺钉紧固过程中扭矩特征信号的分析模型。该策略与自动化螺纹装配系统相结合。监测任务需要从在线和优化过程中识别和拟合所需的信号。结果显示,在三种不同的紧固件上可以识别多达五个插入阶段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The optimization of an autonomous real-time process using curve fitting signature signal
The thread fastening operations have been used for decades with the purpose of joining one component to another. Its tasks are popular because they permit easy to disassembly for maintenance, relocation and recycling. The threaded fastening process is typically carried out manually since it is very difficult problem to automate. As a result, there is very little published research on automating threaded fastenings. This paper investigates the problem of automated monitoring on the screw insertion process. The monitoring problem deals with predicting integrity of a threaded insertion, based on the torque vs. insertion depth curve generated during the insertions. The authors have developed an analytical model to predict the torque signature signals during self-tapping screw fastening. The proposed strategy is integrated with the automating threaded assembly system. The monitoring task needs to be identified and fitted the required signal from the online and optimization process. Its results are shown with up-to five insertion stages can be identified over three different fasteners.
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