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An accident causation model based on safety information cognition and its application

机译:一种基于安全信息认知及其应用的事故因果模型

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摘要

Accident causation models can provide a framework to explain how an accident occurs from various perspectives. In the past, human error has become the main cause of accidents, which is inextricably linked with safety information cognition (SIC). In this study, an accident causation model SIC-based Accident-causing Model (SICAM) is developed and then a new human reliability analysis methodology SIC-based human factor analysis (SICHFA) is provided. Three steps are followed to construct the model. First, the role of SIC in the safety information flow (SIF) has been confirmed. Secondly, the mechanism of accident causation based on SIC were addressed, the effect of negative signal noise mainly involved. Thirdly, the influence objects of signal noise on the SIC process (SICP) were classified at information home, cognitive environment, and cognitive object. To demonstrate the viability of SICAM & SICHFA, the electrical fire, which occurred frequently and resulted in serious adverse social impact in recent years, was selected as the case in this study. Results showed that the proposed accident causation model and SICHFA can provide a new approach for preventing & predicting human accidents.
机译:事故因果机模型可以提供一个框架,以解释事故是如何从各种观点发生的。在过去,人为错误已成为事故的主要原因,这与安全信息认知(SIC)有不可分割的。在这项研究中,开发了一种事故导致模型SiC的事故导致模型(SICAM),然后提供了一种新的人力可靠性分析方法SiC基人因子分析(SichFA)。遵循三个步骤来构建模型。首先,证实了SiC在安全信息流(SIF)中的作用。其次,解决了基于SIC的事故因果机制,主要涉及负信号噪声的效果。第三,SIC过程(SICP)上的信号噪声的影响对象被分类为信息家庭,认知环境和认知对象。为了证明SICAM&SICHFA的可行性,近年来经常发生并导致严重不利社会影响的电火箭,是在本研究中的情况下的。结果表明,拟议的事故因果关系和SICHFA可以为预防和预测人类事故提供一种新方法。

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