【摘要】：隨著經(jīng)濟和技術(shù)的發(fā)展,機器視覺技術(shù)已經(jīng)代替人眼深入到了社會的方方面面,徹底改變了人們的生活環(huán)境。機器視覺檢測綜合了機器視覺和自動化技術(shù),廣泛應(yīng)用于制造行業(yè)的產(chǎn)品缺陷檢測,例如產(chǎn)品的裝配過程檢測與定位、產(chǎn)品的包裝檢測、產(chǎn)品的外觀質(zhì)量檢測、物流行業(yè)的貨物分揀或水果分揀等,機器視覺能夠代替人工快速、準確地完成各項工作。本文針對老齡飛機蒙皮缺陷不易檢測問題,分析現(xiàn)有檢測技術(shù)的優(yōu)缺點,采用機器視覺、DSP、模式識別等技術(shù),在機器人平臺上完成了老齡飛機蒙皮缺陷檢測系統(tǒng)的構(gòu)造,本系統(tǒng)通過無線傳輸技術(shù)將采集的實時、動態(tài)蒙皮損傷信息傳遞給地面健康監(jiān)測平臺進行分析,可在線得到缺陷檢測結(jié)果,實現(xiàn)了飛機蒙皮缺陷圖像分類和鉚釘連接關(guān)鍵部位腐蝕圖像分類。老齡飛機蒙皮缺陷監(jiān)控系統(tǒng),主要包括圖像采集、無線通訊、圖像存儲、圖像處理、特征提取、模式識別六個模塊。根據(jù)系統(tǒng)的要求,完成了圖像采集模塊、無線通訊模塊、圖像存儲的硬件設(shè)計和圖像處理模塊、特征提取模塊、模式識別模塊的軟件設(shè)計。針對飛機蒙皮缺陷特征提取,建立了飛機蒙皮圖像樣本庫,采用了灰度矩陣法提取飛機蒙皮缺陷圖像特征值,提取的特征值精度滿足系統(tǒng)要求；針對鉚釘連接部位腐蝕圖像特征提取,給出了一種改進的鉚釘中心定位算法確定腐蝕鉚釘?shù)闹行呐c半徑,改進的算法提高了鉚釘中心確定的準確度,進而提高了鉚釘連接部位腐蝕圖像特征值的精確度。在模式識別模塊,闡述了一般線性支持向量機、一般非線性支持向量機和模糊支持向量機的原理與分類應(yīng)用,本系統(tǒng)選擇了模糊支持向量機進行模式識別,在基于樣本中心距離FSVM方法的基礎(chǔ)上,給出了基于樣本間距FSVM方法進行飛機蒙皮圖像和鉚釘連接部位腐蝕等級進行分類,通過仿真實驗對比發(fā)現(xiàn)該算法-定程度地提高飛機蒙皮缺陷圖像和鉚釘腐蝕蒙皮圖像的識別分類率�；跈C器視覺的飛機蒙皮缺陷監(jiān)控系統(tǒng)與目前的檢測設(shè)備相比,無需專業(yè)操作人員就可在計算機前完成檢測,具有良好的擴展性,應(yīng)用前景廣闊,對提高老齡飛機的可靠性有較大的應(yīng)用意義。
[Abstract]:With the development of economy and technology, machine vision technology has taken the place of human eyes to go deep into all aspects of society and completely changed people's living environment. Machine vision inspection, which integrates machine vision and automation technology, is widely used in product defect detection in manufacturing industry, such as product assembly process detection and positioning, product packaging testing, product appearance quality testing, Goods sorting or fruit sorting in the logistics industry, machine vision can replace manual fast, accurate completion of the work. Aiming at the problem that it is difficult to detect the skin defects of the aged aircraft, this paper analyzes the advantages and disadvantages of the existing detection techniques, and uses machine vision, DSP, pattern recognition and other technologies to complete the construction of the skin defect detection system of the aged aircraft on the robot platform. Through wireless transmission technology, the real-time and dynamic skinning damage information is transmitted to the ground health monitoring platform for analysis, and the defect detection results can be obtained online. Aircraft skin defect image classification and rivet joint key part corrosion image classification are realized. The skin defect monitoring system of aging aircraft mainly includes six modules: image acquisition, wireless communication, image storage, image processing, feature extraction and pattern recognition. According to the requirements of the system, the software design of image acquisition module, wireless communication module, image storage hardware and image processing module, feature extraction module, pattern recognition module is completed. Aiming at the feature extraction of aircraft skin defect, the sample database of aircraft skin image is established, and the gray matrix method is used to extract the feature value of aircraft skin defect image, and the accuracy of the extracted feature value meets the requirements of the system. An improved rivet center location algorithm is presented to determine the center and radius of rivets. The improved algorithm improves the accuracy of rivet center determination. Furthermore, the accuracy of the characteristic value of the corrosion image of rivet joint is improved. In the pattern recognition module, the principle and classification application of general linear support vector machine, general nonlinear support vector machine and fuzzy support vector machine are expounded. Based on the FSVM method of sample center distance, the aircraft skin image and the corrosion grade of rivet connection are classified based on sample spacing FSVM method. The simulation results show that the algorithm can improve the recognition rate of aircraft skin defect image and riveted skin image to a certain extent. The aircraft skin defect monitoring system based on machine vision can complete the inspection in front of the computer without professional operators, compared with the current testing equipment. It has good expansibility and broad application prospect. It has great application significance to improve the reliability of aging aircraft.
【學(xué)位授予單位】：長春工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TP391.41

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