数据挖掘技术的激光雷达硬件故障数据检测方法

Detection method of lidar hardware fault data based on Data Mining Technology

为了提高激光雷达硬件故障数据检测正确率,提出数据挖掘技术的激光雷达硬件故障数据检测方法,激光雷达系统接收模块包括光学系统、APD探测器、放大器与混频器,其满足高采样频率与多采样点要求,能够获取高精度回波数据;根据硬件故障造成回波数据波形与强度等产生突发性剧烈波动,利用数据挖掘技术中检测接收模块采集的回波数据,以相邻回波数据强度变化均值绝对差与连续正常回波数据均值的比值和相邻回波数据相关系数为检测指标,获取回波数据为硬件故障数据的概率,当概率超过设定阈值时即可确定该回波数据为硬件故障数据。实验结果显示该方法硬件故障数据的检测率为97.0%。

In order to improve the accuracy of fault data detection of lidar hardware,a method of fault data detection of lidar hardware based on data mining technology is proposed.The receiving module of the lidar system includes an optical system,APD detector,amplifier and mixer,which can meet the requirements of high sampling frequency and multiple sampling points and can obtain high-precision echo data.The number of echoes caused by hardware fault According to the sudden and violent fluctuation of waveform and intensity,the echo data collected by the detection and reception module in data mining technology is used.The ratio of the absolute difference of the mean value of the intensity change of adjacent echo data to the mean value of continuous average echo data and the correlation coefficient of adjacent echo data are used as the detection indicators to obtain the probability that the echo data is the hardware fault data.When the probability exceeds the set threshold value,it can be used to confirm that the echo data is hardware fault data.Experimental results show that the detection rate of hardware fault data is 97.0%.