摘要
目的 获得高质量实船结构监测数据,减少数据因外界干扰造成的异常现象,现开发一套面向真实海况的实船结构监测数据的异常处理方法。方法 将统计学中的Z-score异常检测方法与数据处理中常用的平均值计算法相结合,实现对船舶结构应力数据的异常处理。基于正常信号创建含有异常现象的验证数据,对新的异常处理方法进行精度验证。结果 相比Hampel滤波法、Smooth平滑函数等传统的信号处理方法,Z-score异常检测及平均值计算方法的异常处理精度最高,且以此为基础计算的结构信号统计值准确度较好。结论 Z-score异常检测及平均值计算方法可实现真实海况下的实船结构监测数据的异常处理,并在结构应力数据的价值挖掘上可提供有力支撑。
To obtain high-quality real ship structure monitoring data and reduce signal errors caused by external factors,the work aims to develop a set of fast and accurate anomaly processing methods to preprocess the real ship structure monitoring data.The method combined the Z-score anomaly detection method in statistics with the commonly used average calculation method in data processing to achieve high-precision and fast anomaly processing of ship monitoring data.Based on normal signals,validation data containing abnormal phenomena was created to verify the accuracy of the new anomaly processing method.Finally,the validation data that had undergone anomaly processing were subject to structural statistical value calculations including signal filtering,signal component extraction,and signal feature value calculation,and the calculation errors were compared.Compared with traditional signal processing methods such as Hampel filter and Smooth smoothing function,the Z-score anomaly detection and average value calculation method had the highest accuracy in anomaly processing,and the structural signal statistical values calculated based on this were the most accurate,with an average calculation error of less than 10%.In conclusion,the Z-score anomaly detection and average value calculation method is suitable for anomaly handling of real ship structure monitoring data and plays an important role in mining the value of structure data.
作者
孙梦丹
汪雪良
吴国庆
姚骥
蒋镇涛
SUN Meng-dan;WANG Xue-liang;WU Guo-qing;YAO Ji;JIANG Zhen-tao(China Ship Scientific Research Center,Jiangsu Wuxi 214082,China)
出处
《装备环境工程》
CAS
2023年第9期152-159,共8页
Equipment Environmental Engineering
关键词
实船结构监测数据
Z-score异常值检测
平均值法
误差分析
精度验证
统计值计算
real ship structure monitoring data
Z-score anomaly detection
average method
error analysis
accuracy veri-fication
calculation of statistical values
