摘要
车辆运行状态安全测试设备的一致性、准确性是铁路智能运输系统中防止车辆超载引发事故的关键。文中提出了一种新的车辆运行状态测试设备间相对误差率分析方法,克服了现有随机抽样法所引起的数据局限性,获得了蕴含丰富现场工况的数据源,运用最大熵原理导出了相对误差率的分布模型;实现了多系统数据的匹配校验,纠正了系统中的误传数据,同时评定了速度、天气、车种各因素对相对误差率的影响。实验和实际应用的结果表明,该法解决了目前车辆运行状态安全测试设备间相对误差率分析方法的匮乏问题,从理论上验证了设备的一致性、可靠性。
The reliability and uniformity of the machinery for the safety monitoring devices of vehicle operation is a key to keep vehicle from overloading to cause the trouble in the railway intelligent traffic system （RITS）. A new analysis method, the method of distribution-oriented sample, Verify and match and Decision-tree Test （DVDT）, for relative error is put forward. The DVDT method can not only overcome defect in current sample methods and obtain data that contains the rich information of practical situation and educes the distributed model of relative error rate with maximum entropy theory, but realize the verify and match among multi-system data through a verifiable match algorithm and verify the wrong data in system transmission. At same time it can evaluate the effect on relative error rate of speed, weather, train kind and train type through statistical test on samples decision-tree classified. The results of experiment and the actual application show that DVDT method solves the problem of lacking judge and data analysis of the safety monitoring devices of vehicle operation estate, and proves theoretically the reliability and uniformity among them.
出处
《计量学报》
CSCD
北大核心
2006年第1期91-96,共6页
Acta Metrologica Sinica
基金
国家自然科学基金(60174051)
