激光测距机缺陷智能估计方法

Research on improvement of defect estimation method for Intelligent Laser rangefinder

激光测距机的缺陷易导致设备整体运行效率低,降低激光测距的准确度,为此准确估计激光测距机的缺陷十分必要。为提高激光测距机缺陷估计的准确性,提出一种激光测距机的缺陷智能估计方法,采集并分析激光测距机的运行主机与控制服务器的运行状态特征,采用数据驱动程序进行激光测距机的故障树状态引导,对激光测距机驱动程序代码中的缺陷信息进行语义连贯性监测,结合决策树模型实现对激光测距机的动态监测和缺陷自适应定位估计,根据激光测距机的驱动函数、代码以及状态变量等的逻辑性,采用语义连贯性分析和决策数据建模方法,实现对激光测距机的缺陷自适应估计,同时进行缺陷预测中的全局收敛控制,实现激光测距机缺陷智能估计。实验结果表明,采用该方法进行激光测距机缺陷的估计准确性较高,始终高于90%,且时间消耗较少,最低为1.2 s,提高了激光测距机的可靠运行能力。

The defects of the laser rangefinder are easy to lead to the low overall operation efficiency of the equipment and reduce the accuracy of the laser ranging,so it is necessary to estimate the defect of laser rangefinder accurately.In order to improve the accuracy of defect estimation of laser rangefinder,an intelligent defect estimation method of laser rangefinder is proposed to collect and analyze the running state characteristics of the host and control server of the laser rangefinder,to use the data driver to guide the fault tree state of the laser rangefinder,to monitor the semantic coherence of the defect information in the driver code of the laser rangefinder,and to realize the dynamic monitoring and defect adaptive location estimation of the laser rangefinder combined with the decision tree model.According to the logic of driving function,code and state variables of laser rangefinder,semantic coherence analysis and decision data modeling method are used to realize the adaptive estimation of defects in laser rangefinders.At the same time,the global convergence control in defect prediction is carried out,and realization of defect intelligent estimation of laser rangefinder.The experimental results show that the accuracy of the method is higher than 90%,and the time consumption is less,the lowest is 1.2 s,which improves the reliability of the laser range finder.