Department of Mechanical System Engineering, School of Creative Convergence Engineering, Dongguk University-WISE Campus, Gyeongju 38066, Republic of Korea.
Sensors (Basel). 2023 Jun 6;23(12):5381. doi: 10.3390/s23125381.
This study aimed to improve the sensitivity of ferrous particle sensors used in various mechanical systems such as engines to detect abnormalities by measuring the number of ferrous wear particles generated by metal-to-metal contact. Existing sensors collect ferrous particles using a permanent magnet. However, their ability to detect abnormalities is limited because they only measure the number of ferrous particles collected on the top of the sensor. This study provides a design strategy to boost the sensitivity of an existing sensor using a multi-physics analysis method, and a practical numerical method was recommended to assess the sensitivity of the enhanced sensor. The sensor's maximum magnetic flux density was increased by around 210% compared to the original sensor by changing the core's form. In addition, in the numerical evaluation of the sensitivity of the sensor, the suggested sensor model has improved sensitivity. This study is important because it offers a numerical model and verification technique that may be used to enhance the functionality of a ferrous particle sensor that uses a permanent magnet.
本研究旨在通过测量金属对金属接触产生的铁磨损颗粒数量，提高用于发动机等各种机械系统的亚铁粒子传感器检测异常的灵敏度。现有的传感器使用永磁体收集亚铁颗粒。然而，由于它们只能测量传感器顶部收集的亚铁颗粒数量，因此它们检测异常的能力有限。本研究提供了一种设计策略，使用多物理分析方法来提高现有传感器的灵敏度，并推荐了一种实用的数值方法来评估增强型传感器的灵敏度。通过改变铁芯的形状，传感器的最大磁通密度相对于原始传感器增加了约 210%。此外，在传感器灵敏度的数值评估中，建议的传感器模型提高了灵敏度。本研究很重要，因为它提供了一种数值模型和验证技术，可用于增强使用永磁体的亚铁粒子传感器的功能。
