基于CAN总线的船舶机舱危险行为智能视觉监控系统

传统船舶机舱监控采用人工记录的方法,不仅费时费力并且容易出现数据差错,为解决这一问题,对基于CAN总线的船舶机舱危险行为智能视觉监控系统设计进行研究。系统设计主要从硬件与软件两方面进行研究,通过对系统硬件整体设计,从而确定数字量输出通道。以硬件为基础,对软件进行整体设计,通过CAN通信任务设计,实现系统对船舶机舱危险行为智能视觉的监控。根据模拟实验证明,基于CAN总线的船舶机舱危险行为智能视觉监控系统与传统监控方式相比,机舱监控准确率提高10%。     

Monotonicity Evaluation Method of Monitoring Feature Series Based on Ranking Mutual Information

As a prerequisite for effective prognostics, the goodness of the features affects the complexity of the prognostic methods. Comparing to features quality evaluation in diagnostics, features evaluation for prognostics is a new problem. Normally, the monotonic tendency of feature series can be used as the visual representation of equipment damage cumulation so that forecasting its future health states is easy to implement. Through introducing the concept of ranking mutual information in ordinal case, a monotonicity evaluation method of monitoring feature series is proposed. Finally, this method is verified by the simulating feature series and the results verify its effectivity. For the specific application in industry, the evaluation results can be used as the standard for selecting prognostic feature.