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基于BP神經(jīng)網(wǎng)絡(luò)的立式離心泵導(dǎo)葉與蝸殼優(yōu)化設(shè)計
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國家自然科學(xué)基金項(xiàng)目(51979125)、江蘇省重點(diǎn)研發(fā)計劃項(xiàng)目(BE2019089)和江蘇省普通高校研究生實(shí)踐創(chuàng)新計劃項(xiàng)目(SJCX21_1682)


Optimization Design of Vane Diffuser and Volute in Vertical Centrifugal Pump Based on Back Propagation Neural Network
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    摘要:

    立式離心泵是大型灌溉和長距離調(diào)水工程的核心動力裝備,單機(jī)配套功率能夠達(dá)到40MW級。為了降低立式離心泵的運(yùn)行能耗,以效率指標(biāo)為優(yōu)化目標(biāo),基于BP(反向傳播)神經(jīng)網(wǎng)絡(luò)模型與多島遺傳算法對其多個過流部件進(jìn)行優(yōu)化設(shè)計。考慮到各過流部件的匹配性,采用Plackett-Burman試驗(yàn)設(shè)計從導(dǎo)葉與蝸殼的10個設(shè)計參數(shù)中篩選出優(yōu)化設(shè)計變量。運(yùn)用最優(yōu)拉丁超立方采樣方法設(shè)計了106組方案,并搭建了立式離心泵自動數(shù)值模擬優(yōu)化平臺?;贐P神經(jīng)網(wǎng)絡(luò)模型構(gòu)建了優(yōu)化設(shè)計變量和優(yōu)化目標(biāo)之間的高精度非線性關(guān)系,最終通過多島遺傳算法得到導(dǎo)葉與蝸殼的最優(yōu)參數(shù)組合。研究結(jié)果表明,運(yùn)用SST k-ω湍流模型能夠準(zhǔn)確地預(yù)測立式離心泵的性能參數(shù);BP神經(jīng)網(wǎng)絡(luò)是映射泵設(shè)計參數(shù)和性能參數(shù)間內(nèi)在聯(lián)系的有效方法;優(yōu)化后模型設(shè)計工況下效率達(dá)到90.21%,較原始模型提高了3.61個百分點(diǎn);優(yōu)化后的導(dǎo)葉與蝸殼對立式離心泵設(shè)計工況和小流量工況下的性能影響更為顯著;優(yōu)化后導(dǎo)葉與其他過流部件匹配性提高,導(dǎo)葉與蝸殼內(nèi)部流動特性得到明顯改善。

    Abstract:

    Vertical centrifugal pump is a high specific speed centrifugal pump, which is usually with radial vane diffuser structure. As the core power equipment for large-scale irrigation projects and long-distance water transfer, the matching motor power for vertical centrifugal pump is huge and can reach 40MW,and the efficiency directly determines its operating energy consumption. In order to reduce the energy consumption of vertical centrifugal pumps, an optimization on multi-components was proposed based on back propagation neural network (BPNN) and multi-island genetic algorithm (MIGA) . The matching of the hydraulic components was taken into account and the Plackett-Burman test design was used to screen out the optimal design variables from the 10 design parameters of the vane diffuser and the volute. Then, totally 106 sets of cases were sampled by using optimal Latin hypercube sampling (OLHS), and an automatic numerical simulation optimization platform for the vertical centrifugal pump was built to quickly obtain the optimization objective values corresponding to each set of case. The BPNN was used to construct the high-precision nonlinear relationship between the optimization variables and the optimization objective. Finally, the optimal parameter combination of vane diffuser and volute was obtained through MIGA. The results showed that the performance parameters of vertical centrifugal pump could be more accurately predicted by using SST k-ωturbulence model. BPNN was an effective method to construct high-precision nonlinear relationship between pump design parameters and performance parameters. The efficiency of the optimized model under design condition reached 90.21%, which was 3.61 percentage points higher than that of the original model. The optimized vane diffuser and volute had a more obvious influence on the performance of vertical centrifugal pumps under design condition and part-load conditions. The matching between the vane diffuser and other hydraulic components was better, and the internal flow pattern of the vane diffuser was significantly improved after optimization. The optimization method proposed could provide a certain reference for the optimization design of centrifugal pumps.

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張德勝,楊港,趙旭濤,楊雪琪,高雄發(fā).基于BP神經(jīng)網(wǎng)絡(luò)的立式離心泵導(dǎo)葉與蝸殼優(yōu)化設(shè)計[J].農(nóng)業(yè)機(jī)械學(xué)報,2022,53(4):130-139. ZHANG Desheng, YANG Gang, ZHAO Xutao, YANG Xueqi, GAO Xiongfa. Optimization Design of Vane Diffuser and Volute in Vertical Centrifugal Pump Based on Back Propagation Neural Network[J]. Transactions of the Chinese Society for Agricultural Machinery,2022,53(4):130-139.

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  • 收稿日期:2021-05-17
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  • 在線發(fā)布日期: 2021-06-30
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