Abstract
Accurately diagnosing the cause of the failure type of the automatic sorter equipment is the basis for accelerating the efficiency of logistics sorting operations. Based on the research on the diagnosis problem of the parcel sorter equipment, based on the analysis of the fault text data, a method of parcel sorter equipment fault diagnosis based on association rules is proposed. First, build a two-layer fault diagnosis model based on the fault text information and expert experience; use the TF-IDF method to extract the semantic features of the fault text, and propose an improved Apriori algorithm on the basis of the traditional Apriori algorithm to mine the fault text information. The law of association between. The research results show that the evaluation indexes of the improved Apriori algorithm are higher than those of the Apriori algorithm, which proves the feasibility of the method.
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Zu, Q., Gong, J. (2022). Fault Diagnosis Method of Automatic Sorter Equipment Based on Association Rules. In: Zu, Q., Tang, Y., Mladenovic, V., Naseer, A., Wan, J. (eds) Human Centered Computing. HCC 2021. Lecture Notes in Computer Science, vol 13795. Springer, Cham. https://doi.org/10.1007/978-3-031-23741-6_26
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DOI: https://doi.org/10.1007/978-3-031-23741-6_26
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