本文關(guān)鍵詞：基于多信息融合的溫室黃瓜肥水一體化灌溉系統(tǒng)研究　出處：《南京農(nóng)業(yè)大學(xué)》2016年博士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： 多信息融合 溫室黃瓜 灌溉施肥 機(jī)器視覺(jué) 營(yíng)養(yǎng)液 圖像分割 蒸騰 電導(dǎo)率

【摘要】：肥水一體化灌溉施肥是將灌溉和施肥有效結(jié)合的現(xiàn)代農(nóng)業(yè)技術(shù),具有可控性,可以精確控制肥水濃度、灌溉量和灌溉時(shí)間,不但提高肥水利用率,而且具有節(jié)水、節(jié)肥、增產(chǎn)及減少環(huán)境污染等優(yōu)勢(shì),對(duì)我國(guó)設(shè)施農(nóng)業(yè)發(fā)展具有重要的意義�，F(xiàn)階段我國(guó)肥水一體化灌溉技術(shù)還不夠成熟,多數(shù)肥水一體化灌溉設(shè)備仍然根據(jù)經(jīng)驗(yàn)采用定階段、定時(shí)和定量的控制方式,沒(méi)有將溫室環(huán)境信息、作物生長(zhǎng)信息和肥水信息融合到肥水灌溉控制系統(tǒng)中,導(dǎo)致肥水濃度和灌溉量無(wú)法精確變量控制。至今我國(guó)尚未研制出基于溫室環(huán)境信息、作物生長(zhǎng)信息和肥水信息的智能化肥水一體化灌溉系統(tǒng)。為了我國(guó)設(shè)施栽培實(shí)現(xiàn)智能化肥水一體化灌溉,本文以溫室黃瓜為作業(yè)對(duì)象,研究基于多信息融合的溫室黃瓜肥水一體化灌溉系統(tǒng),探尋溫室環(huán)境信息融合方法與黃瓜群體生長(zhǎng)信息檢測(cè)方法,設(shè)計(jì)多通道肥水一體化灌溉施肥機(jī)以及建立基于多信息融合的肥水電導(dǎo)率和灌溉量智能化控制模型。主要研究?jī)?nèi)容及結(jié)論如下:(1)綜合考慮溫室環(huán)境信息分布不均性問(wèn)題,以ECO-WATCH數(shù)據(jù)采集器為核心,設(shè)計(jì)了溫室環(huán)境信息檢測(cè)系統(tǒng)。對(duì)多點(diǎn)同源環(huán)境信息采用自適應(yīng)加權(quán)融合算法,將環(huán)境信息融合值作為肥水一體化灌溉系統(tǒng)的決策輸入量,從而提高系統(tǒng)輸入的可信度、容錯(cuò)性和可靠性。本研究為了驗(yàn)證自適應(yīng)加權(quán)融合算法和平均融合算法的多傳感器信息融合性能,選用3個(gè)評(píng)價(jià)參數(shù)分別為平均絕對(duì)誤差、標(biāo)準(zhǔn)差和變異系數(shù)評(píng)價(jià)信息融合性能,結(jié)果表明自適應(yīng)加權(quán)融合算法明顯優(yōu)于平均融合算法。(2)為了實(shí)現(xiàn)在線(xiàn)無(wú)損檢測(cè)溫室黃瓜群體生長(zhǎng)參數(shù),為肥水一體化灌溉系統(tǒng)提供具有代表性的黃瓜生長(zhǎng)信息。采用機(jī)器視覺(jué)技術(shù),捕獲自然光環(huán)境下黃瓜群體冠層圖像,通過(guò)超綠色-超紅色分割算法、超綠色分割算法和歸一化差異分割算法,分割黃瓜群體冠層區(qū)域圖像,提取黃瓜群體冠層圖像特征參數(shù)(冠層覆蓋率、冠層幅長(zhǎng)和冠層幅寬),并結(jié)合人工測(cè)量的黃瓜群體植株參數(shù)(莖稈高度、莖稈直徑、葉面數(shù)量和坐果數(shù)量),構(gòu)建黃瓜群體生長(zhǎng)參數(shù)反演模型,實(shí)現(xiàn)在線(xiàn)無(wú)損檢測(cè)溫室黃瓜群體生長(zhǎng)參數(shù),并構(gòu)建新的黃瓜群體驗(yàn)證圖對(duì)反演模型性能進(jìn)行驗(yàn)證。結(jié)果表明:在栽培方式為4行X4列、4行X3列和4行X2列時(shí),反演模型反演值與測(cè)量值間線(xiàn)性相關(guān)達(dá)極顯著水平,能夠準(zhǔn)確反演不同栽培方式的黃瓜群生長(zhǎng)參數(shù),其反演性能穩(wěn)定。(3)為了多通道營(yíng)養(yǎng)液與水源在線(xiàn)高效精準(zhǔn)混合,實(shí)現(xiàn)肥水灌溉量與電導(dǎo)率精準(zhǔn)控制,采用可編程控制器與HMI觸控系統(tǒng)結(jié)合,設(shè)計(jì)了多通道肥水一體化灌溉施肥機(jī)。以溫室黃瓜為作業(yè)對(duì)象,根據(jù)黃瓜營(yíng)養(yǎng)液配方配制營(yíng)養(yǎng)液,建立營(yíng)養(yǎng)液稀釋模型,為肥水混合控制提供依據(jù)。針對(duì)肥水混合時(shí)存在的長(zhǎng)時(shí)滯性及均勻性問(wèn)題,采用比例-模糊控制算法,實(shí)現(xiàn)肥水高效精準(zhǔn)混合。結(jié)果表明:肥水混合控制算法穩(wěn)定,變異系數(shù)小于2.5%,Ec值控制誤差小于0.05 mS·cm-1;肥水灌溉均勻性指標(biāo)表明:各通道Ec值和pH值的變異系數(shù)最大值分別為2.49 %和0.98 %,均勻度大于為98.16 %,整體肥水分布均勻系數(shù)大于97.98%,表明肥水灌溉系統(tǒng)的肥水混合均勻。(4)針對(duì)溫室黃瓜肥水灌溉量在線(xiàn)智能控制問(wèn)題,分別建立溫室黃瓜蒸騰速率預(yù)測(cè)模型和椰糠日水分蒸發(fā)模型,并構(gòu)建基于多信息融合的溫室黃瓜灌溉量控制模型。本文提出一種基于小波變換和非線(xiàn)性自回歸神經(jīng)網(wǎng)絡(luò)的黃瓜蒸騰速率時(shí)間序列非線(xiàn)性預(yù)測(cè)模型,采用溫室環(huán)境參數(shù)與蒸騰速率的歷史時(shí)間序列,建立各小波分解重構(gòu)的低頻和高頻時(shí)間序列NARX子網(wǎng)絡(luò)預(yù)測(cè)模型,其預(yù)測(cè)值合成可以準(zhǔn)確預(yù)測(cè)蒸騰速率。結(jié)果表明:2層小波分解重構(gòu)的時(shí)間序列的NARX子網(wǎng)絡(luò)預(yù)測(cè)值合成值和未小波分解重構(gòu)的原時(shí)間序列的NARX預(yù)測(cè)值與蒸騰速率測(cè)量值間相關(guān)性決定系數(shù)R2分別為0.974和0.856,平均絕對(duì)誤差分別為4.42和10.09 g·h-1。WT-NARX預(yù)測(cè)性能優(yōu)于相同網(wǎng)絡(luò)結(jié)構(gòu)的NAR和BP神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)性能。Penman-Monteith方程模擬值與實(shí)測(cè)值間相關(guān)性顯著,決定系數(shù)R2為0.900,標(biāo)準(zhǔn)誤差SE為0.0083 g m-2·s-1,相對(duì)平均偏差RAD為36.42 %。根據(jù)日輻熱積、日有效積溫、日平均溫度和日平均濕度,建立了椰糠日水分蒸發(fā)量回歸方程,回歸方程模擬值與測(cè)量值間相關(guān)性決定系數(shù)R2為0.956, SE為207.73 g·m--·d-1,RAD為8.15 %�；诙嘈畔⑷诤系臏厥尹S瓜灌溉量控制模型,當(dāng)時(shí)間尺度為15min和Id時(shí),預(yù)測(cè)值與實(shí)測(cè)值間的RAD分別為11.6 %和3.41 %。試驗(yàn)結(jié)果表明:在試驗(yàn)期間(10天),溫室黃瓜日耗水量實(shí)測(cè)值和模擬值間RAD為3.00 %。(5)針對(duì)溫室黃瓜肥水電導(dǎo)率在線(xiàn)智能控制問(wèn)題,綜合時(shí)間信息、溫室環(huán)境信息和肥水信息對(duì)黃瓜生長(zhǎng)信息(莖稈高度、莖稈直徑、葉面數(shù)量和坐果數(shù)量)的影響,分別構(gòu)建以黃瓜生長(zhǎng)階段、輻射積、有效積溫和肥水電導(dǎo)率累積值為影響因素的黃瓜長(zhǎng)勢(shì)指標(biāo),其應(yīng)用于標(biāo)準(zhǔn)組長(zhǎng)勢(shì)評(píng)估時(shí)產(chǎn)生的偏離平均百分比分別為3.86%、6.15 %、14.19%和6.77%。根據(jù)各個(gè)影響因素的長(zhǎng)勢(shì)指標(biāo)權(quán)重,采用加權(quán)融合方法,構(gòu)建了三因素(生長(zhǎng)階段、累積輻熱積和累積有效積溫)和四因素(生長(zhǎng)階段、累積Ec值、累積輻熱積和累積有效積溫)的溫室黃瓜長(zhǎng)勢(shì)多信息融合指標(biāo),其對(duì)標(biāo)準(zhǔn)組長(zhǎng)勢(shì)評(píng)估產(chǎn)生的偏離平均百分比分別為6.45 %和5.83 %。建立以多信息融合指標(biāo)為輸入量的電導(dǎo)率決策模型,實(shí)現(xiàn)肥水一體化灌溉施肥機(jī)電導(dǎo)率在線(xiàn)智能控制。
[Abstract]:The integration of water irrigation and fertilization is the modern agricultural technology effective combination of irrigation and fertilization, controllable, can accurately control the concentration of fertilizer, irrigation amount and time, not only to improve the utilization ratio of fertilizer, but also saving water and fertilizer, increase production and reduce environmental pollution and other advantages, has important significance for China's agricultural development. At the present stage of China's irrigation fertilizer integration technology is not mature enough, the majority of water irrigation equipment integration according to the experience of the stage still, timing and control method of quantitative, not greenhouse environment information, crop growth information and fertilizer information into fertilizer irrigation control system, resulting in the fertilizer concentration and amount of irrigation can not accurately control variables. Up to now, our country has not developed an intelligent fertilizer and water integrated irrigation system based on the information of greenhouse environment, crop growth and fertilizer. In order to realize the intelligent cultivation in China based on the integration of irrigation water fertilizer, greenhouse cucumber as the operation object, study the information fusion system based on the integration of water and Fertilizer on greenhouse cucumber irrigation, explore the greenhouse environment information fusion detection method and growth of cucumber population, design of multi channel integration and the establishment of fertilizer irrigation fertilizer fertilizer and irrigation quantity intelligent conductivity based on multi information fusion control model. The main research contents and conclusions are as follows: (1) considering the uneven distribution of greenhouse environment information, and taking the ECO-WATCH data collector as the core, the greenhouse environment information detection system is designed. The adaptive weighted fusion algorithm is applied to the multi point homologous environment information, and the environmental information fusion value is used as the decision input of the fertilizer and water integration irrigation system, so as to improve the credibility, fault tolerance and reliability of the system input. In order to study the multi-sensor information fusion algorithm and validation adaptive weighted average fusion algorithm of the fusion performance, using 3 evaluation parameters respectively, the average absolute error, standard deviation and variation coefficient to evaluate the information fusion performance, results show that the fusion algorithm is better than adaptive weighted average fusion algorithm. (2) in order to realize nondestructive testing of cucumber population growth parameters on line, it provides representative cucumber growth information for the integrated irrigation system of fertilizer and water. By using the machine vision technology, capture natural light environment of cucumber canopy image, through the super green - red, green super segmentation segmentation algorithm and normalized difference segmentation algorithm, the segmentation of cucumber canopy area image, extraction of cucumber canopy image features (canopy coverage, canopy width and canopy width, length) and parameters the cucumber group manual measuring (the number of stem height, stem diameter, leaf number and fruit), construct the cucumber population growth parameter inversion model, on-line nondestructive detection of greenhouse cucumber population growth parameters, and build on the performance of the inversion model to verify the New Cucumber population test. The results showed that when the 4 row X4 row, 4 row X3 column and 4 row X2 column were cultivated, the linear correlation between the inversion value and the measured value was very significant, which could accurately retrieve cucumber growth parameters of different cultivation methods, and the inversion performance was stable. (3) in order to achieve precise and precise control of irrigation quantity and conductivity for multi-channel nutrient solution and water source, a multi-channel fertilizer and water integrated fertilizer applicator is designed by combining programmable logic controller with HMI touch system. The greenhouse cucumber was used as the operating object, the nutrient solution was prepared according to the formula of cucumber nutrient solution, and the dilution model of the nutrient solution was established to provide the basis for the control of the mixed fertilizer and water. In order to solve the problem of long time delay and uniformity in the mixing of water and water, the proportion - fuzzy control algorithm is used to achieve high efficiency and precision mixing of water and water. The results show that the mixed fertilizer control algorithm is stable, the coefficient of variation is less than 2.5%, the Ec value control error is less than 0.05 mS cm-1; show that fertilizer irrigation uniformity index: each channel coefficient variation of Ec value and pH value of the maximum values were 2.49% and 0.98%, uniformity is more than 98.16%, the overall water distribution uniformity coefficient greater than 97.98% indicates the fertilizer mixed fertilizer irrigation system. (4) in view of online intelligent control of greenhouse cucumber water and fertilizer irrigation, greenhouse cucumber transpiration rate prediction model and coconut bran daily water evaporation model were established respectively, and a cucumber irrigation control model based on multi information fusion was built. This paper proposes a prediction model of autoregressive neural network based on wavelet transform and nonlinear time series nonlinear transpiration, the greenhouse environment parameters and transpiration rate of the historical time series, the establishment of the wavelet decomposition and reconstruction of low frequency and high frequency time series NARX network prediction model, the prediction of synthesis can accurately predict transpiration rate. The results show that the predictive value of synthetic value and wavelet decomposition and reconstruction of the original time series prediction values of NARX and transpiration rate measurement correlation coefficient of determination R2 were 0.974 and 0.856 NARX sub network time series 2 level wavelet decomposition and reconstruction, the average absolute errors are 4.42 and 10.09 G - h-1. The predictive performance of WT-NARX is better than that of NAR and BP neural networks with the same network structure. The correlation between the simulated value and the measured value of Penman-Monteith equation is significant. The coefficient R2 is 0.900, the standard error SE is 0.0083 g m-2 s-1, and the relative average deviation RAD is 36.42%. According to daily heat accumulation, daily effective accumulated temperature, daily average temperature and daily average humidity, the regression equation of daily water evaporation of coconut chaff was established. The correlation coefficient between regression equation and measured value was R2, which was 0.956, SE was 207.73 G. M-- D-1 and RAD was 8.15%. In the greenhouse cucumber irrigation control model based on multi information fusion, when the time scale was 15min and Id, the RAD between the predicted and the measured values were 11.6% and 3.41% respectively. The test results showed that during the test period (10 days), the RAD between the measured daily water consumption of greenhouse cucumber and the simulated value was 3%. (5
【學(xué)位授予單位】：南京農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：S642.2;S626
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本文編號(hào)：1341239