摘要
港口装卸起重机工作环境恶劣,起动制动频繁。为了检测港口起重机动态运行时的起重质量,研制了一种基于动态模型辨识原理的自适应滤波器,有效地克服了起制动过程的加速度干扰和动量冲击干扰;建立了模型参数离线预估计算法,提高了实时检测速度;设计了零速空载零位自辨识跟踪技术,消除了检测系统的零点漂移影响。应用结果表明,新技术提高了起重质量检测的准确性。
Port handling crane starts or brakes frequently, running in bad condition. In order to detect the dynamic lifted load of the port crane, self-adaptive filter is developed, based on the identification of dynamic model. The self-adaptive filter can eliminate efficiently the signal of acceleration interference when the crane starts or brakes, and the signals of momentum impact interference. The off-line pre-estimating algorithm for model parameters is founded, and the on-line detecting speed is raised. When the crane is in the zero-speed, zero-load, the self zero-tracking will act, and zero drift of the detecting system can be corrected. The applying results show that the new technique has raised the accuracy of detecting lifted load.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2006年第1期187-190,共4页
Journal of Mechanical Engineering
基金
上海市重点学科(T0603)上海市教委科技基金(04FB10)资助项目。
关键词
自适应
检测
动态模型
辨识
起重质量
Self-daptive Detection Dynamic model Identification Lifted load