伸缩臂式起重机力矩限制器功能参数算法研究

发布时间：2018-01-02 08:33

本文关键词：伸缩臂式起重机力矩限制器功能参数算法研究　出处：《中南大学》2013年硕士论文　论文类型：学位论文

【摘要】：摘要：伸缩臂式起重机是一种广泛应用于国民经济建设各个领域的移动式起重机,而力矩限制器则是起重机安全监控系统的核心部分,直接影响着起重机的作业安全,随着伸缩臂式起重机的作业安全性及可靠性要求越来越高,力矩限制器的精度要求也越来越高。本文针对伸缩臂式起重机力矩限制器算法及实现进行相关研究。综述了目前国内外伸缩臂式起重机力矩限制器的发展及研究现状,在分析伸缩臂式起重机力矩限制器工作原理的基础上,完成了起重机额定起重性能表回归模型的建立,并对力矩限制器器的核心力矩算法进行了深入分析。结合伸缩臂式起重机臂架的受力分析,建立了基于变幅缸压力的起重机力矩计算模型,提出了一种新的主臂自重标定算法,重点研究了伸缩臂的变形补偿算法,并运用matlab对算法进行了仿真研究,验证了算法的可行性。针对神经网络应用于伸缩臂式起重机力矩计算进行了相关研究,比较了采用单纯BP神经网络、遗传算法和粒子群优化的BP神经网络的训练效率和预测误差。结果表明采用粒子群算法优化的BP神经网络对力矩限制器的算法模型具有很好的拟合能力,经过训练后的神经网络的预测误差控制在3%以内。搭建了基于DSP的力矩限制器硬件平台,以CodeWarrior集成开发环境为软件平台,开发了主机控制器相应的DSP程序,并完成了力矩限制器显示器人机界面的开发。基于labviEW开发了数据采集系统,以SWTC50伸缩臂式起重机为实验平台进行了实验研究,结果表明本文建立的基于变幅缸压力的检测算法精度满足国标GB12602-2009起重机械超载保护装置中规定要求,为下一步的工程应用打下了基础。
[Abstract]:Abstract: the telescopic crane mobile crane is a widely used in various fields of national economic construction, and the torque limiter is a core part of crane safety monitoring system, directly affects the operating safety of the crane, with the requirement of safety and reliability of telescopic crane is more and more high, the precision of the torque limiter more and more is also high. This paper researches and Realization of telescopic crane torque limiter algorithm.
Reviews the current development and research status at home and abroad telescopic crane torque limiter, based on analyzing the working principle of telescopic crane torque limiter, completed the crane to establish heavy performance regression model, and the torque limiter for core moment algorithm are analyzed.
Stress analysis of telescopic crane arm frame combination, established the calculation model of crane luffing cylinder pressure based on torque, presents a new self calibration algorithm for the main arm, focuses on the research of deformation compensation algorithm of telescopic arm, and use matlab to simulate the algorithm, verify the feasibility of the algorithm.
The neural network is applied to the telescopic crane torque calculation was studied, compared with simple BP neural network, genetic algorithm and particle swarm optimization BP neural network training efficiency and prediction error. The results show that the BP neural network particle swarm optimization algorithm model of torque limiter has good fitting ability the prediction error through the trained neural network control in less than 3%.
The hardware platform of torque limiter based on DSP is built. Taking the CodeWarrior integrated development environment as software platform, the corresponding DSP program of the host controller is developed, and the development of the man-machine interface of the torque limiter displays is completed.
LabviEW has developed a data acquisition system based on the experimental research on SWTC50 telescopic crane as the experimental platform, the result shows that the precision detection algorithm of luffing cylinder pressure to meet the national standard GB12602-2009 crane overload protection device based on the requirements for the engineering application, the next step to lay the foundation.

【学位授予单位】：中南大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TH21

【参考文献】