一种时间序列异常检测用参数化熵滤波器  

Parameterized Entropy Filter for Time Series Anomaly Detection

作　　者：张玉飞[1] 董永贵[1] 

机构地区：[1]清华大学精密测试技术及仪器国家重点实验室,北京100084

出　　处：《机械工程学报》2011年第22期13-18,共6页Journal of Mechanical Engineering

基　　金：国家自然科学基金资助项目(60971007)

摘　　要：针对机械系统中近似高斯分布的低信噪比时间序列,设计出一种用于异常检测的参数可调熵滤波器。为检测均值漂移和方差变动这两类统计特性异常,对基于滑动窗的Shannon熵滤波器的参数设置策略进行研究。引入单调因子K1,在保证滤波器工作单调性的同时,可以获取不同的平滑效果。通过引入尺度因子K2,实现对熵滤波器正常信号容限的调节,从而实现时间序列的可变尺度异常检测。以时间序列中异常信号与正常信号统计特性重合度在滤波前后之比作为滤波器性能评价指标,利用仿真信号分析两个参数在检测均值漂移和方差变动异常时的合理取值范围。对电子清纱器颜色异纤信号的检测试验结果表明,这种带参数的熵滤波器对近似高斯分布的时间序列信号具有良好的异常检测能力。In view of the time series obtained from mechanical systems,which performs low signal-to-noise ratio and nearly Gaussian distribution,a parameter-adjustable entropy filter is designed for anomaly detection.In order to detect the statistical anomaly caused by changes of mean value and variance,the parameter setting strategies is discussed with a sliding-window based Shannon entropy filter.A monotonic factor K1 is introduced to obtain different smoothing results well the monotonicity of the filter is maintained.In order to adjust the tolerance range of normal signal,a scale factor K2 is introduced.In such a way,the anomaly detection of the time series can be implemented in a variable scaling way.With the entropy filter＇s assessment criteria which achieved by computing the improvement ratio of overlap ratio of anomaly and normal in the time series after and before being filtered,the rational value ranges of the two factors,in cases of both mean value drifting and variance variation detection,are analyzed by simulated signals.Experimental detection is performed with colored foreign yarn signals of an electronic yarn clearer.The results indicate that such a parameterized entropy filter performs good anomaly detection ability for nearly Gaussian distribution signals.

关 键 词：高斯分布 异常检测 熵滤波器 均值漂移 方差变动 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]