| Cite this article: | 陶洪飞,刘姚,陶娟琴,等.基于正交结果分析的内镶贴片式滴灌带性能优化设计[J].灌溉排水学报,0,():-. |
| TAO Hong-Fei,LIU Yao,TAO Juanqin,et al.基于正交结果分析的内镶贴片式滴灌带性能优化设计[J].灌溉排水学报,0,():-. |
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| Performance Optimization Design of In-line Patch Drip Tape Based on Orthogonal Result Ahnalysis |
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TAO Hong-Fei1, LIU Yao1, TAO Juanqin1, ZHOU Liang2, LI Qiao1, MA Hemujiang·aihemaiti1, JIANG Youwei1
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1.Xinjiang Agricultural University;2.China Construction Xinjiang Construction Engineering
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| Abstract: |
| 【Objective】To explore the influence of the irrigation uniformity and flow reduction of the laying slope, sand content and working pressure in the inner patch drip irrigation belt. 【Methods】The uniform orthogonal test were used to study the influence of the three factors, and PPR model, NSGA-II model and linear regression models were used for comparative analysis.【Result】The influence of each factor on irrigation uniformity was sorted as sand content> laying slope > working pressure. The degree of influence on the flow rate reduction was sorted as sand content> working pressure > laying slope; The results of the analytic hierarchy were consistent with the results of the range analysis, indicating that the sand content had a great influence on the uniformity of irrigation and the decrease of flow. Based on the experimental data, a linear regression model of irrigation uniformity and flow reduction was constructed, and the standard rms error of the linear regression model of irrigation uniformity was 19.81%, and the standard rms error of the flow reduction linear regression model was 14.17%, both less than 20%, then the model performance was good. The p-value of irrigation uniformity, working pressure and laying slope are greater than 0.05, and the p-value of sand content is less than 0.05, which may have a nonlinear relationship; the projection tracking regression model of irrigation uniformity and flow reduction is constructed, the standard rms error of the irrigation uniformity projection tracing regression model is 2.98%, and the standard rms error of the flow reduction projection tracing regression model is 2.42%, both less than 10%, then the model performance effect is excellent. and at the same time The the prediction effect of PPR model was better than that of multiple regression model, and the prediction results of PPR model were consistent with NSGA-II.【Conclusion】Through the prediction model to optimize the main influencing factors, tThe optimal working condition is: the laying slope is 0%, the sand content is 1 g/L, and the working pressure is 96 kPa. In this optimal condition, the value of the irrigation uniformity is 0.958 5, and the flow drop is 0.083 5(8.35%). |
| Key words: Inner patch drip irrigation belt; Irrigation uniformity; Flow reduction; SPSS; PPR; NSGA-Ⅱ |
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