Beihang University

Haopeng Wu

Ke Li

Shunkun Yang

Donghao Wang

Liping Pang

Yan Kan

Pengjiao Li

The present disclosure relates to a multi-classification non-intrusive identification and detection method for an electrical signal based on naive Bayes, including an expert database module and a signal classification module. An electrical signal training sample of a known category is built based on historical and real-time aircraft signals. Classification is performed based on a built naive Bayes model classifier, to obtain an aircraft signal classification result. P(yi) is separately calculated for each category, a conditional probability is calculated for each feature, and a classification result of a sample signal is obtained through statistic acquisition by using a probability comparison algorithm. A next status is predicted by using a time series prediction method after electrical signal data is classified and determined by using a naive Bayes algorithm.

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Beijing, China

Haopeng Wu