基于机器视觉的船舶吃水线自动检测方法分析

Remote control method of ship operating modal parameters in shallow water based on wireless network

传统的船舶吃水线自动检测方法自动化水平较低,无法获取精准的检测结果。为了解决该问题,提出基于机器视觉的船舶吃水线自动检测方法。从机器视觉系统提取吃水异常数据,在采用修正思想对船舶吃水异常数据进行补偿,在此基础上,应用定量分析表,设置船舶吃水线自动检测标准,待完成上述操作步骤后,对船舶吃水线进行自动检测,由此完成基于机器视觉的船舶吃水线自动检测方法的设计。实验选择在水质较为清晰的水域,并随机选取8个实验参数,对2种检测方法进行实验对比,实验结果表明,所提方法的自动检测结果更精准。

Traditional automatic detection methods for ship draught lines have low automation level and can not obtain accurate detection results.In order to solve this problem,an automatic detection method for ship draught lines based on machine vision is proposed.Drainage abnormal data are extracted from machine vision system and compensated by using correction idea.On this basis,quantitative analysis table is used to set the automatic detection standard of ship draught line.After the above operation steps are completed,the automatic detection of ship draught line is carried out,thus the design of automatic detection method of ship draught line based on machine vision is completed.The experiment chooses clear water and randomly chooses eight experimental parameters to compare the two detection methods.The experimental results show that the automatic detection results of the proposed method are more accurate.