Automated Excavator Activity Diagnosis Via a Topology and Statistical Information Based Classifier
Year: 2025
Type: article
Abstract: For automated diagnosis of excavator activities, a Topology and Statistical Information based Classifier (TSIC) is put forward, and it employs topology and statistical information of excavator activity samples. Specifically, a small sensor network is built on the excavator for its activity data acquisition. Distance metric learning is improved to explore sample features, making the same-class samples closer and different-class ones further. An improved mountain function is employed to construct covers for topology feature extraction, and then a weighted linear classifier is designed to diagnose (or classify) excavator activities. Generalization performance of TSIC is discussed. Experiments on excavator construction datasets and public datasets demonstrate competitive performance of TSIC.
Authors: Mushu Wang, YuKui Qin, Tiepeng Bi, Weigang Pan
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4411566361