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基于LSTM的炉用冷却风机滤网积灰预测

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为解决风机滤网积灰难以识别的问题,综合分析滤网积灰时的故障电流信号具有一定时序性的特点,提出了基于LSTM的炉用冷却风机滤网积灰预测方法.实验结果表明,LSTM网络能够有效预测风机滤网积灰状态,高效判断滤网积灰的演化趋势,且可避免一定突发故障等造成的因机组联锁降低风机输出功率的干扰,具有一定工程实用性.
Prediction of Ash Accumulation in Filter Screen of Furnace Cooling Fan Based on LSTM
The cooling fan for the furnace is used for temperature control during the continuous annealing unit's strip steel production process.The cold air sucked in from the filter is blown to the surface of the strip steel and then discharged.The heat of the strip steel is carried away by the circulating air,causing the strip steel to drop to a certain temperature.If the filter screen accumulates dust,it will affect the heat transfer efficiency and even cause quality problems with the strip steel.Moreover,the dust accumulation on the filter screen is not easily detected,and abnormalities often occur during the production process.To solve the problem of difficult identification of dust accumulation in fan filters,a predictive method for dust accumulation in furnace cooling fan filters based on LSTM is proposed by comprehensively analyzing the temporal characteristics of fault current signals during dust accumulation.The experimental results show that the LSTM model can effectively predict the dust accumulation status of the fan filter screen,efficiently judge the evolution trend of the dust accumulation in the filter screen,and avoid interference caused by unit interlocking to reduce the output power of the fan due to certain sudden faults.It has certain engineering practicality.

cooling fanash accumulation in filter screenLSTM

张茹军、牛锐祥

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山西太钢不锈钢股份有限公司硅钢事业部,山西 太原 030002

炉用冷却风机 滤网积灰 CNN 带钢表面 缺陷识别

2024

机械管理开发
山西省机械工程学会

机械管理开发

影响因子:0.273
ISSN:1003-773X
年,卷(期):2024.39(12)