基于多源数据融合的智能化起锚机健康监测平台研究
Research on Health Monitoring Platform of Intelligent Windlass Based on Multi-Source Data Fusion

传统锚绞机由于数据利用率低、设备故障处理滞后而导致作业效率低下，为此，本文提出了一种基于多源数据融合的智能化起锚机健康监测平台。该平台架构涵盖数据采集层、传输层、处理层、应用层，实现数据采集、状态监测、历史数据查询等功能。针对数据采集层的多源数据，系统利用主成分分析和高斯混合模型进行健康状态评估，识别异常数据并及时预警，提高了起锚机故障处理的响应度。该平台能极大地满足未来船海设备信息化、智能化、高效化的发展需求。
Due to the low utilization rate of data and the lag in handling equipment failures, traditional anchor windlasses have low operating efficiency. For this reason, an intelligent anchor windlass health monitoring platform based on multi-source data fusion has been proposed in this paper. The platform architecture covers the data acquisition layer, transmission layer, processing layer, and application layer, realizing functions such as data acquisition, status monitoring, and historical data query. For the multi-source data in the data acquisition layer, the system uses principal component analysis and Gaussian mixture models to conduct health status assessments, identify abnormal data and issue timely warnings, improving the responsiveness in handling anchor windlass failures. This platform can greatly meet the development needs of informatization, intelligence, and high efficiency of future marine equipment.