Home

Fault detection by mining association rules from house-keeping data


Author(s) : Koichi Hori Yoshikiyo Kato Takehisa Yairi, 
Publisher : N/A
Publication Date : 2001
ISSN : N/A
Abstract : house-keeping data This paper proposes a novel anomaly detection method for spacecraft systems based on data-mining techniques. This method automatically constructs a system behavior model in the form of a set of rules by applying pattern clustering and association rule mining to the time-series data obtained in the learning phase, then detects anomalies by checking the subsequent on-line data with the acquired rules. A major advantage of this approach is that it requires little a priori knowledge on the system. 1,