基于PVDF聚合物传感材料的机电冷镦设备钢球冲压在线监测

IF 2.4 Q2 ENGINEERING, MECHANICAL
Xing Wang, Mingming Wu, Jianglong Wang
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引用次数: 1

摘要

摘要为了探讨基于聚偏氟乙烯(PVDF)聚合物传感材料的冷镦设备对钢球冲压成形的影响,提出了一种利用载荷信号反映钢球冷镦成形缺陷的新方法。采用PVDF压电薄膜作为传感器,设计了钢球冷镦力与支撑结构的机电传感器模型。采用PVDF压电薄膜力传感器进行结构优化和仿真。利用MATLAB软件对结构参数对固有频率的影响进行了数值分析。利用ANSYS软件获得传感器外部载荷与输出载荷的映射关系,并将传感器固有频率的仿真曲线与理论曲线进行对比,验证影响固有频率的因素。结果表明,传感器的非线性误差是指测量曲线和拟合线与满量程输出百分比之间的最大偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On-line monitoring of steel ball stamping by mechatronics cold heading equipment based on PVDF polymer sensing material
Abstract In order to explore the influence of cold heading equipment based on polyvinylidene fluoride (PVDF) polymer sensing material on steel ball stamping, a new method was proposed to reflect the defects of cold heading forming of steel ball by load signal. PVDF piezoelectric film is used as the sensor design of force and support structure of steel ball cold heading electromechanical sensor model. PVDF piezoelectric thin film force sensor is used for the structural optimization and simulation. The structural parameters affecting the natural frequency are numerically analyzed by MATLAB software. The mapping relationship between the external load and the output load of the sensor is obtained by using ANSYS software, and the simulation curve of the natural frequency of the sensor is compared with the theoretical curve to verify the factors affecting the natural frequency. The results show that the nonlinear error of sensors refers to the measured curve and the maximum deviation between the fitting line and the percentage of full-scale output.
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来源期刊
CiteScore
6.20
自引率
3.60%
发文量
49
审稿时长
44 weeks
期刊介绍: The Journal of Nonlinear Engineering aims to be a platform for sharing original research results in theoretical, experimental, practical, and applied nonlinear phenomena within engineering. It serves as a forum to exchange ideas and applications of nonlinear problems across various engineering disciplines. Articles are considered for publication if they explore nonlinearities in engineering systems, offering realistic mathematical modeling, utilizing nonlinearity for new designs, stabilizing systems, understanding system behavior through nonlinearity, optimizing systems based on nonlinear interactions, and developing algorithms to harness and leverage nonlinear elements.
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