Suzhou Electric Appliance Research Institute
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電磁繼電器剩余電壽命智能預(yù)測(cè)研究

來(lái)源:電工電氣發(fā)布時(shí)間:2020-12-19 13:19 瀏覽次數(shù):674
電磁繼電器剩余電壽命智能預(yù)測(cè)研究
 
喬維德
(無(wú)錫開放大學(xué) 科研與質(zhì)量控制處,江蘇 無(wú)錫 214011)
 
    摘 要:針對(duì)以往繼電器剩余電壽命實(shí)際預(yù)測(cè)方法存在的不足,建立一種用于電磁繼電器剩余電壽命預(yù)測(cè)的BP神經(jīng)網(wǎng)絡(luò)模型,該模型采取繼電器的吸合時(shí)間和超程時(shí)間作為輸入量,繼電器剩余電壽命作為輸出量,通過粒子群- 蛙跳算法優(yōu)化網(wǎng)絡(luò)結(jié)構(gòu)初始參數(shù),利用改進(jìn)BP算法訓(xùn)練BP神經(jīng)網(wǎng)絡(luò),并加以測(cè)試驗(yàn)證。實(shí)驗(yàn)結(jié)果表明,經(jīng)過粒子群- 蛙跳算法優(yōu)化的BP神經(jīng)網(wǎng)絡(luò)模型能快速、準(zhǔn)確地實(shí)現(xiàn)電磁繼電器剩余電壽命預(yù)測(cè)。
    關(guān)鍵詞:電磁繼電器;BP神經(jīng)網(wǎng)絡(luò);粒子群- 蛙跳算法;剩余電壽命預(yù)測(cè)
    中圖分類號(hào):TM581.3     文獻(xiàn)標(biāo)識(shí)碼:A     文章編號(hào):1007-3175(2020)12-0030-05
 
Research on Intelligent Prediction of Residual Electrical Life of Electromagnetic Relay
 
QIAO Wei-de
(Scientific Research and Quality Control Department, Wuxi Open University, Wuxi 214011, China)
 
    Abstract: Aiming at the shortcomings of the previous actual prediction methods of the remaining electrical life of the relay, a BP neural network model for the prediction of the remaining electrical life of the electromagnetic relay was established. The model takes the pull-in time and overtravel time of the relay as the input, and the remaining electrical life of the relay as the output. The initial parameters of the network structure are optimized by the particle swarm-frog leaping algorithm, and the BP neural network is trained by the improved BP algorithm, and tested and verified. Experimental results show that the BP neural network model optimized by the particle swarm-frog leaping algorithm can quickly and accurately predict the remaining electrical life of the electromagnetic relay.
    Key words: electromagnetic relay; BP neural network; particle swarm-frog leaping algorithm; residual electrical life prediction
 
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