中速磨直吹式制粉系統(tǒng)是火力發(fā)電廠鍋爐運(yùn)行穩(wěn)定的一個(gè)重要環(huán)節(jié)，其磨機(jī)內(nèi)存煤量能否獲得可靠監(jiān)測(cè)對(duì)發(fā)電廠的自動(dòng)控制、經(jīng)濟(jì)運(yùn)行和安全生產(chǎn)均有十分重要的意義。通過基于工藝機(jī)理知識(shí)，分析了中速磨直吹式制粉系統(tǒng)筒內(nèi)存煤量的各相關(guān)因素，提
出了利用人工神經(jīng)網(wǎng)絡(luò)進(jìn)行存煤量軟測(cè)量的方法，給出了基于BP 改進(jìn)算法的回歸神經(jīng)網(wǎng)絡(luò)與延時(shí)神經(jīng)網(wǎng)絡(luò)綜合模型，為中速磨存煤量的檢測(cè)提供了新方法。離線訓(xùn)練與計(jì)算機(jī)仿真結(jié)果證實(shí)了軟測(cè)量方法的可行性。
關(guān)鍵詞：中速磨煤機(jī) 存煤量 軟測(cè)量 改進(jìn)算法
Abstract：Powdered system of straight blow medium speed mills is one of the important sections in fossil-fired power plants. Reliable monitoring for the quantity of reserving coal in the mills is significant to automation control，economical operation and safe production. Based on the knowledge of technique mechanism，various related factors to the quantity of reserving coal are analyzed. The method of soft-sensing by using artificial neural network is proposed and the integrated model of regressive neural network and time delay neural network based on BP improved algorithm are given. This provided a new method for detecting the reserving coal for medium speed mills. Through off-line training and computerized simulation，the results prove that the soft-sensing method is feasible.
Keywords：Medium speed mill Quantity of reserving coal Soft-sensing Improved algorithm