本文選題：橋式起重機(jī)　切入點(diǎn)：吊裝路徑規(guī)劃　出處：《太原科技大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：近年來,隨著各個(gè)行業(yè)的自動(dòng)化、智能化水平不斷提高所帶來的便利與高效的驅(qū)動(dòng),大型工程機(jī)械也在向此方向發(fā)展。而智能路徑規(guī)劃作為一個(gè)重要的研究方向,在機(jī)器人領(lǐng)域已經(jīng)比較成熟且得到廣泛應(yīng)用,但在大型工程機(jī)械如起重機(jī)方面研究相對(duì)較少。因此,本文針對(duì)橋式起重機(jī)的特點(diǎn)和目前研究文獻(xiàn)中存在的不足,融合柵格法、蟻群算法,并將粒子群算法應(yīng)用于動(dòng)態(tài)環(huán)境中,提出了在靜態(tài)和動(dòng)態(tài)環(huán)境下的橋式起重機(jī)吊裝路徑規(guī)劃方法,主要內(nèi)容如下:首先,針對(duì)智能橋式起重機(jī)系統(tǒng),提出基于改進(jìn)的蟻群算法的吊裝路徑規(guī)劃方法。研究在障礙物已知的靜態(tài)環(huán)境中,忽略橋式起重機(jī)的吊鉤升降,將其環(huán)境簡化為二維柵格模型,對(duì)蟻群算法的啟發(fā)函數(shù)、揮發(fā)系數(shù)等進(jìn)行改進(jìn),且考慮到橋式起重機(jī)的運(yùn)行特點(diǎn),為避免大小車頻繁制動(dòng),將原有的斜線路徑改為直線,并引入代價(jià)函數(shù)來評(píng)價(jià)仿真的效果。仿真結(jié)果表明算法的可行性。其次,建立靜態(tài)且環(huán)境已知的橋式起重機(jī)三維作業(yè)環(huán)境模型,利用柵格法劃分空間,將橋式起重機(jī)所吊重物最大擺動(dòng)距離與其安全通過障礙物的距離之和設(shè)為安全距離,將蟻群算法的啟發(fā)函數(shù)、揮發(fā)系數(shù)以及適應(yīng)度函數(shù)等進(jìn)行改進(jìn)并應(yīng)用于橋式起重機(jī)三維環(huán)境的吊裝路徑規(guī)劃。在MATLAB中進(jìn)行仿真研究,結(jié)果證明了方案的可行性與有效性。最后,針對(duì)動(dòng)態(tài)變化的吊裝環(huán)境,提出在動(dòng)態(tài)環(huán)境中的橋式起重機(jī)吊裝路徑規(guī)劃。仍由柵格法建模,通過將優(yōu)先選擇的思想、敏感粒子根據(jù)適應(yīng)度值改變來探測(cè)環(huán)境并根據(jù)閾值觸發(fā)響應(yīng)機(jī)制、及對(duì)動(dòng)態(tài)粒子群算法的適應(yīng)度值的改變,來進(jìn)行規(guī)劃。為避免大小車頻繁制動(dòng),仍采用直線路徑。仿真結(jié)果表明此方法不僅可用于動(dòng)態(tài)環(huán)境且效果有保障,安全性高。
[Abstract]:In recent years, with the automation of various industries, intelligent level of continuous improvement of the convenience and efficiency of driving, large-scale construction machinery is also in this direction, and intelligent path planning as an important research direction, It has been mature and widely used in the field of robot, but the research on large-scale construction machinery such as cranes is relatively few. Therefore, in view of the characteristics of bridge cranes and the shortcomings of the present research literature, the fusion grid method is used in this paper. Ant colony algorithm and particle swarm optimization (PSO) algorithm are applied to dynamic environment. A method of crane hoisting path planning in static and dynamic environment is proposed. The main contents are as follows: firstly, aiming at intelligent bridge crane system, A method of hoisting path planning based on improved ant colony algorithm is proposed. In the static environment with known obstacles, the lifting hooks of bridge cranes are ignored, and their environment is simplified as a two-dimensional grid model, which is a heuristic function for ant colony algorithm. The volatilization coefficient is improved, and considering the operation characteristics of the bridge crane, in order to avoid frequent braking of the trolley, the original diagonal path is changed into a straight line. The cost function is introduced to evaluate the simulation effect. The simulation results show that the algorithm is feasible. Secondly, a static and known three-dimensional operating environment model of bridge crane is established, and the space is divided by grid method. In this paper, the sum of the maximum swing distance and the distance between the weight hoisted by the bridge crane and the distance from which the crane can safely pass through the obstacle is set as the safe distance, and the heuristic function of the ant colony algorithm is put forward. The volatilization coefficient and fitness function are improved and applied to the hoisting path planning of bridge crane in 3D environment. The simulation results in MATLAB show that the scheme is feasible and effective. In view of the dynamic changing hoisting environment, the hoisting path planning of bridge crane in dynamic environment is put forward. The sensitive particle detects the environment according to the change of fitness value, triggers the response mechanism according to the threshold, and changes the fitness value of the dynamic particle swarm optimization algorithm. The simulation results show that this method not only can be used in dynamic environment, but also has high security.
【學(xué)位授予單位】：太原科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TH215;TP18

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 何博;方勇純;劉海亮;孫寧;;橋式起重機(jī)精準(zhǔn)定位在線軌跡規(guī)劃方法設(shè)計(jì)及應(yīng)用[J];控制理論與應(yīng)用;2016年10期

2 閆萍;焦明海;;求解函數(shù)優(yōu)化問題的自適應(yīng)動(dòng)態(tài)粒子群算法[J];計(jì)算機(jī)仿真;2016年10期

3 王文發(fā);許淳;尹斌斌;杜智杰;;基于改進(jìn)混合蛙跳算法的動(dòng)態(tài)環(huán)境路徑規(guī)劃[J];吉林大學(xué)學(xué)報(bào)(理學(xué)版);2016年04期

4 范卿;曾楊;胡玉茹;段軍;郭芙;;起重機(jī)大型工程吊裝方案規(guī)劃系統(tǒng)設(shè)計(jì)[J];起重運(yùn)輸機(jī)械;2015年10期

5 錢森;訾斌;;多起重機(jī)協(xié)作吊裝避障路徑規(guī)劃研究[J];機(jī)械設(shè)計(jì)與制造;2015年10期

6 魏云平;強(qiáng)寶民;晁蘇全;楊必根;趙輝;;改進(jìn)路徑規(guī)劃算法在橋式起重機(jī)中的應(yīng)用[J];計(jì)算機(jī)測(cè)量與控制;2015年08期

7 屈鴻;黃利偉;柯星;;動(dòng)態(tài)環(huán)境下基于改進(jìn)蟻群算法的機(jī)器人路徑規(guī)劃研究[J];電子科技大學(xué)學(xué)報(bào);2015年02期

8 陳成;何玉慶;卜春光;韓建達(dá);;基于四階貝塞爾曲線的無人車可行軌跡規(guī)劃[J];自動(dòng)化學(xué)報(bào);2015年03期

9 孫寧;方勇純;錢_g哲;;帶有狀態(tài)約束的雙擺效應(yīng)吊車軌跡規(guī)劃[J];控制理論與應(yīng)用;2014年07期

10 鄧乾旺;高禮坤;羅正平;李梟;;基于多目標(biāo)遺傳算法的起重機(jī)吊裝路徑規(guī)劃[J];湖南大學(xué)學(xué)報(bào)(自然科學(xué)版);2014年01期

相關(guān)博士學(xué)位論文 前1條

1 孫寧;欠驅(qū)動(dòng)吊車軌跡規(guī)劃與非線性控制策略設(shè)計(jì)、分析及應(yīng)用[D];南開大學(xué);2014年

相關(guān)碩士學(xué)位論文 前2條

1 張博;橋式起重機(jī)自動(dòng)運(yùn)行控制系統(tǒng)設(shè)計(jì)[D];大連理工大學(xué);2015年

2 旦增歐珠;橋式起重機(jī)智能運(yùn)行系統(tǒng)及其路徑規(guī)劃研究[D];大連理工大學(xué);2013年

，

本文編號(hào)：1616383