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Safety Evaluation Method of Lifting Appliances Based on BP Neural Network

机译:基于BP神经网络的起重机械安全性评价方法。

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As the classification score of lifting security status in the traditional way, subjective factors affect the state of the score, resulting in the error between assessment and the actual situation. To avoid the impact of these factors, this study designs the neural network security for lifting assessment, using BP neural network approach. After training and simulation, the network is proved to get low training error and generalization error. The design and implementation of the safety evaluation method could help the standard management and safe use of cranes to achieve the preventive maintenance of lifting appliances, regulate the management of lifting appliances, for the protection of the safe operation and avoiding the huge catastrophic economic losses and accidents.
机译:主观因素是提升安全状况的传统方法,是对提升状态的分类评分,影响评分状态,导致评估与实际情况存在误差。为了避免这些因素的影响,本研究使用BP神经网络方法设计了用于提升评估的神经网络安全性。经过训练和仿真,证明该网络具有较低的训练误差和泛化误差。安全评估方法的设计与实施,可以帮助起重机的规范管理和安全使用,实现对起重机械的预防性维护,规范起重机械的管理,保护起重机的安全运行,避免巨额的经济损失和巨额损失。事故。

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