Ming Wan1, Jinfang Li1, Jiangyuan Yao2, *, Rongbing Wang1, 3, Hao Luo1
CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1415-1431, 2020, DOI:10.32604/cmc.2020.09692
- 30 April 2020
Abstract In process industries, the characteristics of industrial activities focus on the
integrality and continuity of production process, which can contribute to excavating the
appropriate features for industrial anomaly detection. From this perspective, this paper
proposes a novel state-based control feature extraction approach, which regards the finite
control operations as different states. Furthermore, the procedure of state transition can
adequately express the change of successive control operations, and the statistical
information between different states can be used to calculate the feature values.
Additionally, OCSVM (One Class Support Vector Machine) and BPNN (BP Neural
Network), which are More >
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