摘要
由于起重机械特殊的结构形式和运动形式,导致起重机械事故频发,为提高起重机械的本质安全,提出了一套起重机械本质安全评估体系,从本质安全的4个方面分3个层次对起重机械进行评估;为了改善在评估过程中,人为主观因素对起重机械状态评分的影响,引入LM神经网络对起重机械评价体系进行建模,通过对样本数据训练获得客观的起重机械各危险源的权重系数,测试样本的仿真结果验证了该方法的有效性。
The lifting appliances＇ special structure and movement are the source of frequent accidents of lifting appliances.In order to improve the lifting appliances＇ intrinsic safety,a set of essential safety assessment system for lifting appliances is proposed,where the lifting appliances safety evaluation is from three levels of four different aspects：in addition,to reduce the subjective factors in the evaluation process,the LM neural network is introduced into the evaluation model.The weight coefficient of each dangerous source for lifting appliances was obtained by the samples data training,and the test sample data＇s simulation verified the validity of the method.
出处
《南昌大学学报（理科版）》
CAS
北大核心
2011年第2期197-200,共4页
Journal of Nanchang University(Natural Science)
基金
国家质检总局科技计划项目(2009QK229)
关键词
起重机械
本质安全
LM神经网络
状态评估
lifting appliances
intrinsic safety
LM neural network
safety assessment
