危化品仓储中激光测距的自适应分层聚类去噪算法研究

Study on Adaptive Hierarchical Clustering De-noising Algorithm of Laser Ranging in Storage of Dangerous Chemicals

为实现危化品仓储安全预警,采用激光测距、编码器等进行库内五距的监测。针对测距数据的噪声问题,设计了一种分层去噪、反馈补偿的自适应调节阈值的聚类去噪算法。针对噪声特点及距离的不同,以被测实物为中心将其由远及近划分为3类,第一层、第二层使用峰值去噪,第三层使用夹角分段拟合,同时进行层间的反馈纠错实现闭环去噪。实验表明,与拟合去噪算法相比,所提方法的方差降低了0.83;与差值去噪算法相比,所提方法解决了小部分噪点集中出现而不能去除所带来的灾难性影响的问题,方差值降低了1.93。该算法可准确去除噪点并还原监测物体位置。

In order to realize the safety early warning of dangerous chemical products,this paper used laser ranging and encoder to monitor the five distance in the warehouse.In order to solve the noise problem of ranging data,a new algorithm was designed for reducing noise and feedback compensation.According to the characteristicing of the noise and the distance,taking the tested object as the center,objects are divided into three categories from far to near.The first layer and the second layer use peak denoising,the third layer uses piecewise fitting angle,simultaneously interlayer feedback error correction is used to realize the closed loop denoising.Experiment results show that the variance is reduced by 0.83 compared with the denoising algorithm.Compared with the comparison algorithm of difference value,this algorithm can removed catastrophie caused by a small amount of noise concentrated and the variance value is decreased by 1.93.The algorithm can remove the noise and restore the position of the object.