A cosine similarity-based negative selection algorithm for time series novelty detection

2006 ◽  
Vol 20 (6) ◽  
pp. 1461-1472 ◽  
Author(s):  
Yonggui Dong ◽  
Zhaoyan Sun ◽  
Huibo Jia
Keyword(s):  
Time Series ◽  
Negative Selection ◽  
Novelty Detection ◽  
Cosine Similarity ◽  
Selection Algorithm ◽  
Negative Selection Algorithm

A Biological Immunity-Inspired Novelty Detection Algorithm for Rotor System Monitoring

2005 ◽  
Vol 293-294 ◽  
pp. 71-78 ◽  
Author(s):  
Yong Gui Dong ◽  
Ensheng Dong ◽  
Huibo Jia ◽  
Wener Lv
Keyword(s):  
Time Series ◽  
Negative Selection ◽  
Time Series Data ◽  
Detection Efficiency ◽  
Novelty Detection ◽  
Rotor System ◽  
Series Data ◽  
Selection Algorithm ◽  
Detection Techniques ◽  
Negative Selection Algorithm

In case of mechanical system health monitoring, a need to develop normal-knowledge based novelty detection techniques is increasing. The negative selection algorithm, which is inspired from the operation mechanism of human immune system, is one of such approaches. Our approach is to apply the idea for the anomaly detection in the vibration time series of the rotor system. A real-valued negative selection algorithm based on Euclidean distance, as well as cosine similarity, has been implemented. By means of adding the corresponding coverage radius to each antibody elements, the detection efficiency of each antibody element is increased. The detection efficiency is evaluated with simulated data as well as vibration signal sampled from one rotor system. The results indicate that the algorithm can efficiently detect the anomaly in time series data. Moreover, the number of detectors in antibody set is less enough for potential application in online signal monitoring.

Negative Selection Algorithm Using Natural Frequency for Novelty Detection under Temperature Variations

2010 ◽  
Vol 163-167 ◽  
pp. 2747-2750
Author(s):  
Miao Li ◽  
Wei Xin Ren
Keyword(s):  
Natural Frequency ◽  
Negative Selection ◽  
Euclidean Distance ◽  
Natural Frequencies ◽  
Novelty Detection ◽  
Selection Algorithm ◽  
Temperature Variations ◽  
Negative Selection Algorithm ◽  
Environment Effects ◽  
Anomalous Condition

The vibration features are affected by damage in structure and environmental conditions while the bridges are in the operation. Environment effects should not be ignored in making correct diagnoses of structures. Negative selection algorithm inspired by immune system has the capability for self-nonself discrimination. Temperature effect on natural frequency is analyzed in the paper, and the algorithm based on Euclidean distance is applied to natural frequencies of structures under temperature variations. The results indicate that negative selection algorithm using natural frequency passes the false-positive tests, and effectively detect the anomalous condition of structure under varying temperature.

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