人工智能和数据挖掘在人机工程PHM中的应用

Artificial intelligence and data mining applied in PHM

人工智能和数据挖掘是构建在认知科学、神经心理学、机器学习、数据科学和统计学上的交叉学科。它为人机工程问题的研究与分析,尤其是对复杂人机系统的性能预测与健康管理提供了强有力的计算与分析工具。文中首先分别给出了人工智能与数据挖掘的发展简史以及主要的研究领域和研究途径,而后给出了三个典型算例,分别对矿井作业的安全问题采用小波神经网络方法进行评价,对某系统的性能用模糊神经网络进行预测,对飞行员的脑力负荷用Bayes判别函数法,从主观评价、作业绩效和多项生理指标的角度进行了综合测评。上述典型算例表明:智能算法和数据挖掘技巧,可以有效地处理人机工程中的PHM问题。

Artificial intelligence(AI)and Data Mining(DM)are interdisciplinary sciences based on cognitive science,neuropsychology,machine learning,data science and statistics.It serves as powerful computational and analytical tools for research and analysis of ergonomics problems,especially for prognostics and health management(PHM)in complex human-machine systems.This article briefly introduces the developing history,main approaches,and research areas of AI and DM.The article then discusses three typical examples:Using wavelet neural network method to evaluate the safety issues in mine operations;using fuzzy neural network to predict system performance;using Bayes discriminant function method to comprehensively assess the mental workload of pilots in terms of subjective evaluation,job performance,and multiple physiological indicators.Such typical examples indicate that AI and DM can effectively solve PHM problems in ergonomics.