基于认知补偿的ROV操控系统人因失误预测方法

Human Error Prediction Method of ROV Control System Based on Cognitive Compensation

针对有缆遥控机器人(ROV)水下作业过程中人因可靠性问题,建立操作员认知模型分析操作员内在认知过程,结合认知过程和任务过程构建人因可靠性串并联系统;采用改进CREAM方法论构建认知可靠性模型,通过评估认知风险水平,确定分析环境对操作员认知行为的影响程度,最终通过某型ROV取样过程人因失误预测实例,对方法进行了应用验证。结果表明,改型ROV基本满足使用要求,但预测通信、回收、监视等模块人因失误率较高,有待进一步优化。研究成果为有缆遥控机器人设计优化、任务规划、人员培训提供理论支撑和参考。

Aiming at the problem of human reliability in the underwater operation of ROV,the cognitive model of the operator is established to analyze the internal cognitive process of the operator,and the series parallel system of human reliability is constructed by combining the cognitive process and task process.The cognitive reliability model is constructed by using the improved CREAM methodology,and the cognitive behavior of the operator in the analysis environment is determined by evaluating the cognitive risk level Finally,the method is verified by an example of human error prediction in the sampling process of a ROV.The results show that the modified ROV basically meets the requirements of use,but the human error rate of prediction communication,recovery,monitoring and other modules is high,which needs further optimization.The research results provide theoretical support and reference for the design optimization,task planning and personnel training of the cable remote control robot.