Lightweight Fault Identification of Magnetic Latching Needle Selectors Based on Multistage Transient Drive Current Responses

Magnetic latching needle selectors are key actuating components that perform needle selection in circular knitting machines, and their operating states directly affect weaving reliability. To address the difficulty of online fault monitoring during large-scale deployment of needle selectors, a lightweight fault identification method based on multi-stage transient drive current response is proposed. An electromechanical coupling model is established, and single-factor perturbation analysis is used to reveal the three-stage transient current response and its variations with key parameters. Using measured currents from the normal state and five fault states, 14-dimensional features are constructed to describe stage macro characteristics, local dynamics, and equivalent electromagnetic responses. A Gated Low-Rank Cross Network (GLR-CrossNet) is then used for six-state identification. Across ten specimen-level data partitions, the proposed method achieved an Accuracy of 95.54 ± 0.55% and a Macro-F1 score of 95.55 ± 0.56%. After deployment on the needle selector control terminal, the end-to-end identification time is 3.11 ms, while continuous operation tests on a circular knitting machine achieve a single-action accuracy of 94.20% for the five fault states. The results support lightweight online state monitoring of magnetic latching needle selectors using transient drive current.