【摘要】：隨著中國(guó)“智能制造”創(chuàng)新戰(zhàn)略的深入推進(jìn),傳統(tǒng)制造業(yè)的轉(zhuǎn)型升級(jí)面臨巨大的機(jī)遇與挑戰(zhàn)。焊接作為傳統(tǒng)制造業(yè)中不可或缺的材料加工方法,實(shí)現(xiàn)焊接智能創(chuàng)新升級(jí)及全自動(dòng)化已成為當(dāng)前行業(yè)發(fā)展的必然趨勢(shì)。大梁是現(xiàn)今重型裝備行業(yè)中最普遍的焊接結(jié)構(gòu)件形式之一,廣泛應(yīng)用于橋梁、軌道交通、運(yùn)輸集裝箱、起重機(jī)械、房屋建筑等領(lǐng)域。目前,由于大梁工件在焊接生產(chǎn)線的變位機(jī)械裝夾或中心翻轉(zhuǎn)過程中,存在由人工操作引起的垂直方向高度及偏轉(zhuǎn)角度隨機(jī)誤差,難以實(shí)現(xiàn)焊縫起始點(diǎn)自主尋位;同時(shí),大梁工件上隨機(jī)分布流水槽、加強(qiáng)板、輔助上翼板等障礙物,具有尺寸多變性、結(jié)構(gòu)多元化等特點(diǎn),難以通過傳統(tǒng)的視覺識(shí)別算法實(shí)現(xiàn)大梁工件的障礙物識(shí)別聚類及智能規(guī)避。本文針對(duì)大梁焊接全自動(dòng)化尚存的幾大技術(shù)難點(diǎn),對(duì)傳統(tǒng)半自動(dòng)化大梁生產(chǎn)線進(jìn)行智能改造和創(chuàng)新升級(jí),深入研究大梁自動(dòng)焊起始點(diǎn)定位及障礙物識(shí)別的關(guān)鍵技術(shù)。提出一種復(fù)合檢測(cè)式雙渦流定位傳感的焊接起始點(diǎn)自動(dòng)定位方法。依據(jù)渦流傳感器的影響因素及規(guī)律,闡述渦流檢測(cè)高度及面積的機(jī)理。建立雙渦流定位系統(tǒng)模型,通過電感計(jì)算及等效分析,探究得到復(fù)阻抗的變化規(guī)律。搭建簡(jiǎn)易定位數(shù)據(jù)采集試驗(yàn)平臺(tái),優(yōu)化采樣策略,獲取雙探頭輸出特征值。采用加權(quán)最小二乘法擬合探頭1輸出特征值與高度函數(shù),基于響應(yīng)面法分離變量,代入探頭1高度值,得出探頭2輸出特征值與偏轉(zhuǎn)角度的擬合函數(shù)。根據(jù)復(fù)合檢測(cè)式雙渦流定位傳感器焊接起始點(diǎn)定位方案及三個(gè)主要定位特征參數(shù),計(jì)算焊槍橫縱方向距離偏差值。提出一種折線式線陣激光傳感器障礙物實(shí)時(shí)聚類識(shí)別方法。根據(jù)三角法原理,設(shè)計(jì)折線式激光傳感器光路平面布局及光路系統(tǒng)參數(shù)。基于dsPIC30f4012單片機(jī)實(shí)現(xiàn)激光傳感器硬件電路設(shè)計(jì)。簡(jiǎn)要分析激光視覺傳感器信號(hào)采集成像機(jī)理,設(shè)計(jì)線激光有效長(zhǎng)度自適應(yīng)統(tǒng)一化優(yōu)化方案確保障礙物識(shí)別穩(wěn)定可靠。針對(duì)傳統(tǒng)FCM應(yīng)用于大梁障礙物實(shí)時(shí)聚類識(shí)別過程中存在的缺陷,引入實(shí)時(shí)聚類策略,替換距離函數(shù),全局快速優(yōu)化,得到一種優(yōu)化模糊C均值實(shí)時(shí)聚類算法。通過MATLAB平臺(tái)仿真對(duì)比分析,證明該算法能實(shí)時(shí)獲取聚類數(shù)及障礙物類型屬性。在大梁自動(dòng)焊模擬平臺(tái)進(jìn)行焊接起始點(diǎn)定位試驗(yàn),結(jié)果表明動(dòng)態(tài)響應(yīng)快,適用范圍廣,橫向及縱向定位精度高。在某公司大梁自動(dòng)焊生產(chǎn)線平臺(tái)進(jìn)行障礙物實(shí)時(shí)識(shí)別試驗(yàn),結(jié)果表明實(shí)時(shí)性優(yōu)良,聚類數(shù)與實(shí)際相符,障礙物規(guī)避動(dòng)作精準(zhǔn)。
[Abstract]:With the development of innovation strategy of intelligent manufacturing in China, the transformation and upgrading of traditional manufacturing industry is faced with great opportunities and challenges. Welding, as an indispensable material processing method in traditional manufacturing industry, has become an inevitable trend of current industry development. Beam is one of the most common welding structures in heavy equipment industry. It is widely used in bridge, rail transit, transportation container, lifting machinery, housing construction and so on. At present, due to the random errors of vertical height and deflection angle caused by manual operation, it is difficult to realize the self-locating of the starting point of the weld due to the random errors of vertical height and deflection angle caused by manual operation in the process of mechanical clamping or center flipping of the beam workpiece in the welding production line; at the same time, The obstacles such as randomly distributed flow flume, stiffening plate and auxiliary upper wing plate on the workpiece of beam have the characteristics of variable size and diversified structure, so it is difficult to realize obstacle identification clustering and intelligent evasion by traditional visual recognition algorithm. In this paper, aiming at the remaining technical difficulties of full automation of beam welding, the traditional semi-automatic beam production line is innovated and upgraded intelligently, and the key technologies of locating the starting point of automatic welding and identifying obstacles are deeply studied. This paper presents an automatic welding starting point location method based on compound detecting dual eddy current positioning sensor. According to the influencing factors and rules of eddy current sensor, the mechanism of eddy current measuring height and area is expounded. The model of dual eddy current positioning system is established, and the variation law of complex impedance is obtained by inductance calculation and equivalent analysis. Set up a simple location data acquisition test platform, optimize the sampling strategy, and obtain the output eigenvalue of double probe. The weighted least square method is used to fit the eigenvalue and height function of probe 1. Based on the method of response surface, the fitting function of eigenvalue and deflection angle of probe 2 is obtained by separating variables and replacing the height of probe 1 with the method of response surface. According to the location scheme of welding starting point and three main positioning characteristic parameters of the compound detecting dual-eddy current positioning sensor, the deviation value of the distance between transverse and longitudinal direction of the welding torch is calculated. A real-time clustering method for obstacle recognition of linear laser sensor is presented. According to the triangulation principle, the optical path layout and optical path system parameters of the broken line laser sensor are designed. The hardware circuit of laser sensor is designed based on dsPIC30f4012 single chip computer. The principle of laser vision sensor signal acquisition and imaging is analyzed briefly, and an adaptive unified optimization scheme of line laser effective length is designed to ensure the stability and reliability of obstacle identification. Aiming at the defects of traditional FCM application in the real-time clustering identification of beam obstacles, a fuzzy C-means real-time clustering algorithm is obtained by introducing the real-time clustering strategy, replacing the distance function, and rapidly optimizing the whole world. The simulation results of MATLAB platform show that the algorithm can obtain clustering number and obstacle type attributes in real time. The results show that the dynamic response is fast, the range of application is wide, and the accuracy of transverse and longitudinal positioning is high. A real-time obstacle identification test was carried out on the platform of a company's automatic beam welding production line. The results show that the real-time performance is good, the clustering number is consistent with the actual situation, and the obstacle avoidance action is accurate.
【學(xué)位授予單位】：湘潭大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TG409

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