【摘要】：隨著科技的發(fā)展,機(jī)場(chǎng)在信息化數(shù)字化方面也有了長足的進(jìn)步,機(jī)場(chǎng)的各個(gè)部門也都開發(fā)或者引進(jìn)了不同類別的信息管理系統(tǒng),改善了機(jī)場(chǎng)信息化應(yīng)用的環(huán)境。但受制于當(dāng)前的科技水平、機(jī)場(chǎng)各大能源站點(diǎn)復(fù)雜的監(jiān)測(cè)環(huán)境、電子儀器的不穩(wěn)定性等因素,機(jī)場(chǎng)能源數(shù)據(jù)的采集出現(xiàn)各種各樣的困難,采集上來的能源數(shù)據(jù)廣泛存在冗余、缺失、噪聲等不良現(xiàn)象,所以研究新型的機(jī)場(chǎng)能源數(shù)據(jù)采集技術(shù),以及研究新型的機(jī)場(chǎng)能源數(shù)據(jù)處理算法尤為重要。本論文首先針對(duì)機(jī)場(chǎng)能源數(shù)據(jù)采集過程中的各種問題,利用無線傳感網(wǎng)絡(luò)技術(shù)、自動(dòng)化技術(shù)、數(shù)據(jù)庫技術(shù)等,設(shè)計(jì)了機(jī)場(chǎng)能源數(shù)據(jù)實(shí)時(shí)采集平臺(tái),然后對(duì)采集到的機(jī)場(chǎng)能源數(shù)據(jù)進(jìn)行處理與分析。根據(jù)機(jī)場(chǎng)能源數(shù)據(jù)在不同時(shí)間的不同特性提出特征權(quán)重的數(shù)據(jù)預(yù)處理方法,提出結(jié)合經(jīng)驗(yàn)?zāi)Ｊ椒纸馀c最小二乘支持向量機(jī)的聯(lián)合回歸預(yù)測(cè)方法解決能源數(shù)據(jù)缺失的問題,同時(shí)利用果蠅算法改進(jìn)最小二乘支持向量機(jī)的參數(shù)尋優(yōu)過程。將常用的預(yù)測(cè)方法與本論文提出的方法進(jìn)行對(duì)比驗(yàn)證實(shí)驗(yàn),仿真結(jié)果表明采用本論文方法預(yù)測(cè)準(zhǔn)確度有顯著提高,能夠勝任機(jī)場(chǎng)能源數(shù)據(jù)缺失的填補(bǔ)工作。最后利用已經(jīng)建立的回歸預(yù)測(cè)模型,提出基于無跡變換的機(jī)場(chǎng)能源數(shù)據(jù)的改進(jìn)型卡爾曼濾波方法,在原有卡爾曼濾波方法的基礎(chǔ)上,通過加入誤差反饋提高濾波效果。通過對(duì)改進(jìn)算法的實(shí)現(xiàn),得到更加精準(zhǔn)的機(jī)場(chǎng)能源數(shù)據(jù)。在相同站點(diǎn)條件下進(jìn)行對(duì)比實(shí)驗(yàn),對(duì)比不同濾波方法的濾波效果;在不同站點(diǎn)不同模型的條件下進(jìn)行驗(yàn)證實(shí)驗(yàn),驗(yàn)證本論文方法的適用性和有效性。結(jié)果表明,本論文方法在建立回歸預(yù)測(cè)模型的基礎(chǔ)上,通過閉環(huán)的誤差反饋控制減少誤差擴(kuò)散的影響,對(duì)于未知的非線性系統(tǒng),有很好的濾波效果,具有良好的發(fā)展與應(yīng)用前景。
[Abstract]:With the development of science and technology, the airport has made great progress in the field of information digitization. Various departments of the airport have also developed or introduced different kinds of information management systems, which have improved the environment for the application of airport information. However, due to the current level of science and technology, the complex monitoring environment of the major energy stations in the airport, the instability of electronic instruments, and so on, there are various difficulties in the acquisition of airport energy data, and there is widespread redundancy in the energy data collected. Therefore, it is very important to study the new airport energy data acquisition technology and the new airport energy data processing algorithm. In this paper, firstly, aiming at various problems in the process of airport energy data acquisition, using wireless sensor network technology, automation technology, database technology and so on, the real-time acquisition platform of airport energy data is designed. Then the collected airport energy data processing and analysis. According to the different characteristics of airport energy data at different time, the data preprocessing method of feature weight is put forward, and the joint regression prediction method based on empirical mode decomposition and least squares support vector machine is proposed to solve the problem of missing energy data. At the same time, the algorithm of Drosophila was used to improve the parameter optimization process of least squares support vector machine (LS-SVM). The simulation results show that the prediction accuracy of this method is significantly improved and can be used to fill the lack of airport energy data. Finally, an improved Kalman filtering method based on unscented energy data is proposed by using the established regression prediction model. On the basis of the original Kalman filtering method, the filtering effect is improved by adding error feedback. Through the implementation of the improved algorithm, more accurate airport energy data can be obtained. Comparing the filtering effect of different filtering methods under the same site condition, and verifying the applicability and validity of this method under the condition of different stations and different models. The results show that this method can reduce the influence of error diffusion through closed-loop error feedback control on the basis of establishing regression prediction model, and has a good filtering effect for unknown nonlinear systems. It has a good prospect of development and application.
【學(xué)位授予單位】：中國民航大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP274.2

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