孙梦丹,汪雪良,吴国庆,姚骥,蒋镇涛.基于实船结构监测数据的异常检测及处理方法[J].装备环境工程,2023,20(9):152-159. SUN Meng-dan,WANG Xue-liang,WU Guo-qing,YAO Ji,JIANG Zhen-tao.Anomaly Detection and Processing Method Based on Real Ship Structure Monitoring Data[J].Equipment Environmental Engineering,2023,20(9):152-159.
基于实船结构监测数据的异常检测及处理方法
Anomaly Detection and Processing Method Based on Real Ship Structure Monitoring Data
投稿时间:2023-07-19  修订日期:2023-09-06
DOI:10.7643/issn.1672-9242.2023.09.017
中文关键词:  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  统计值计算中图分类号:TP39 文献标识码:A 文章编号:1672-9242(2023)09-0152-08
英文关键词:real ship structure monitoring data  Z-score anomaly detection  average method  error analysis  accuracy verification  calculation of statistical values
基金项目:
作者单位
孙梦丹 中国船舶科学研究中心, 江苏 无锡 214082 
汪雪良 中国船舶科学研究中心, 江苏 无锡 214082 
吴国庆 中国船舶科学研究中心, 江苏 无锡 214082 
姚骥 中国船舶科学研究中心, 江苏 无锡 214082 
蒋镇涛 中国船舶科学研究中心, 江苏 无锡 214082 
AuthorInstitution
SUN Meng-dan China Ship Scientific Research Center, Jiangsu Wuxi 214082, China 
WANG Xue-liang China Ship Scientific Research Center, Jiangsu Wuxi 214082, China 
WU Guo-qing China Ship Scientific Research Center, Jiangsu Wuxi 214082, China 
YAO Ji China Ship Scientific Research Center, Jiangsu Wuxi 214082, China 
JIANG Zhen-tao China Ship Scientific Research Center, Jiangsu Wuxi 214082, China 
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中文摘要:
      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。
英文摘要:
      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.
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