IED Electronics, Pol. Ind. Plazaola, E6, 31195 Berrioplano, Spain.
Department of Statistics, Computer Science and Mathematics, Public University of Navarre, 31006 Pamplona, Spain.
Sensors (Basel). 2021 Mar 6;21(5):1849. doi: 10.3390/s21051849.
This paper presents a new sensory system based on advanced algorithms and machine learning techniques that provides sensory gloves with the ability to ensure real-time connection of all connectors in the cabling of a cockpit module. Besides a microphone, the sensory glove also includes a gyroscope and three accelerometers that provide valuable information to allow the selection of the appropriate signal time windows recorded by the microphone of the glove. These signal time windows are subsequently analyzed by a convolutional neural network, which indicates whether the connection of the components has been made correctly or not. The development of the system, its implementation in a production industry environment and the results obtained are analyzed.
本文提出了一种基于先进算法和机器学习技术的新型感测系统,为感测手套提供了实时连接驾驶舱模块布线中所有连接器的能力。感测手套除了配备麦克风外,还包括一个陀螺仪和三个加速度计,它们提供了有价值的信息,可用于选择由手套麦克风记录的适当信号时间窗口。随后,卷积神经网络会分析这些信号时间窗口,指示组件的连接是否正确。分析了系统的开发、在生产环境中的实施以及获得的结果。