本文選題：貫流風葉 + 激光��； 參考：《江蘇大學》2017年碩士論文

【摘要】：貫流風葉作為空調(diào)等風力輸送設(shè)備的重要部件,其結(jié)構(gòu)完整性對風力輸送過程中的噪聲水平控制和氣流輸送平穩(wěn)性有直接影響。貫流風葉通常采用注塑工藝生產(chǎn),由于模具磨損或注塑過程控制參數(shù)變化等原因,會造成貫流風葉葉片邊角缺料缺陷,如果不能及時檢測并剔除這些不合格產(chǎn)品,將導致產(chǎn)品不合格率上升,嚴重影響產(chǎn)品質(zhì)量。目前,貫流風葉缺料缺陷主要是通過人工目視檢測,由于生產(chǎn)批量大,生產(chǎn)線對產(chǎn)品檢測速度要求高,人員在長時間目視檢測會產(chǎn)生視覺疲勞,導致誤判時有發(fā)生。另外,人工目視檢測還存在易受人為主觀因素影響的弊端,進一步導致誤判率上升。為解決上述問題,本課題組設(shè)計了第一代貫流風葉注塑缺料缺陷在線監(jiān)測系統(tǒng),由于采用單一類型的紅外傳感器對缺料缺陷進行檢測,還存在檢測準確率不穩(wěn)定和無法有效檢出小缺料缺陷的不足。為此,本論文在第一代紅外監(jiān)測系統(tǒng)的基礎(chǔ)上,改進了檢測方案,采用激光與紅外復合陣列對產(chǎn)品進行監(jiān)測,并提取了新的信號特征,采用了特征參數(shù)融合算法和基于支持向量機的缺陷識別算法,并增加了產(chǎn)品自動放置識別功能,完善了人機交互功能。同時,為了提高檢測系統(tǒng)的檢測穩(wěn)定性和抗干擾能力,改善了電路的設(shè)計。并且完成了第二代樣機的制作和調(diào)試工作,通過對實際產(chǎn)品的檢測,其性能指標優(yōu)于第一代設(shè)備。其檢測準確率、穩(wěn)定性和對小缺陷(缺陷面積≤1mm~2)的檢出率均得到了提高。在實驗室條件下,第二代樣機對缺料缺陷的檢出率超過99.9%,其中對小缺陷的檢出率超過99%,而第一代樣機對大缺陷的檢出率約為97%,且無法有效檢出小缺陷。本文的主要研究內(nèi)容如下:(1)在分析第一代監(jiān)測系統(tǒng)性能特點的基礎(chǔ)上,針對其存在的不足,提出了新的檢測原理方案,采用了基于激光與紅外復合式檢測方法,并進行了第二代監(jiān)測系統(tǒng)總體方案設(shè)計;(2)設(shè)計了激光與紅外復合式檢測電路,主要包括信號激勵電路、接收電路、模擬信號處理電路、上位機通訊電路;并且設(shè)計了激光與紅外復合陣列布設(shè)方案與機械結(jié)構(gòu),進一步完善了第一代樣機的電路設(shè)計,提高了電路抗干擾能力和長時間檢測穩(wěn)定性;并增加了產(chǎn)品自動放置識別功能;(3)設(shè)計了基于C8051F020單片機的主控電路;(4)研究和分析了貫流風葉缺料缺陷的光學信號特征,提取了缺陷的特征參數(shù);提出了缺陷特征參數(shù)融合方法,并研究了基于支持向量機的缺陷識別算法;(5)編寫監(jiān)測系統(tǒng)軟件,主要包括初始化程序、產(chǎn)品放置識別程序、數(shù)據(jù)采集程序、特征參數(shù)提取與融合程序、基于支持向量機的缺陷識別程序、檢測結(jié)果輸出程序、以及人機交互程序等;(6)制作監(jiān)測系統(tǒng)樣機,進行調(diào)試和試驗,驗證監(jiān)測系統(tǒng)的性能。
[Abstract]:As an important part of air conditioning and other wind transport equipment, the structural integrity of tubular blade has a direct impact on the noise level control and airflow smoothness in the process of wind transport.The tubular vane is usually produced by injection molding process. Because of the wear of mould or the change of injection process parameters, it will cause defects in the edge and corner of the blade. If these unqualified products can not be detected and eliminated in time,Will cause the product nonconformity rate to rise, seriously affects the product quality.At present, the defects of material shortage in the tubular blade are mainly detected by manual visual inspection. Because of the large production lot, the production line requires high testing speed of the product, and the personnel will produce visual fatigue in the long time visual inspection, which leads to the misjudgment occurring from time to time.In addition, artificial visual detection is vulnerable to human subjective factors, resulting in a further increase in the rate of miscarriage of justice.In order to solve the above problems, the first generation of on-line monitoring system for defects in injection molding of tubular vane was designed. Because of the use of a single type of infrared sensor to detect the defects of missing materials,There are also some shortcomings such as unstable detection accuracy and inability to effectively detect small defects.Therefore, based on the first generation infrared monitoring system, this paper improves the detection scheme, uses the laser and infrared composite array to monitor the product, and extracts the new signal features.The feature parameter fusion algorithm and the defect recognition algorithm based on support vector machine are adopted, and the function of automatic product placement and identification is added to improve the human-computer interaction function.At the same time, in order to improve the detection stability and anti-interference ability of the detection system, the circuit design is improved.The second generation prototype is made and debugged, and its performance index is better than the first generation equipment by testing the actual product.The detection accuracy, stability and detection rate of small defects (defect area 鈮，

本文編號：1769391