基于物联网监测的起重机安全预警

Security Early Warning of Crane Based on IOT

为保障起重机安全、可靠运行,该文提出基于物联网技术监测起重机实时运行状态,对起重机危险运行进行报警并采取相应应急处理的方法。同时,为了解起重机未来运行状态,将监测数据转化为表征起重机性能的退化特征值,通过建立熵值分配和神经网络修正的灰色综合预测模型预测特征值的风险趋势,以归一化数据处理方法综合不同退化特征值实现安全预警。以某型号冶金起重机起升电机为例进行了仿真,仿真结果表明:安全预警模型高效、可靠。

In order to ensure the safety and reliable operation of the crane.This paper presented a new approach by monitoring the real-time running state of the crane based on the internet of things,then converted the monitoring data into degenerate eigenvalue of the crane performance.By establishing the entropy method and neural network modified grey comprehensive prediction model to predict the risk trend of characteristic value,then,applying normalized data processing method and combining with the different degenerate eigenvalue to realize the security early warning of the crane.Taking a certain type of metallurgical lifting motor crane as an example,the simulation and the results show that the safety early warning model is more efficient.