本文選題：機(jī)體損傷過(guò)渡區(qū)提取　切入點(diǎn)：機(jī)體損傷區(qū)域劃分　出處：《計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào)》2016年10期

【摘要】：為了利用機(jī)體損傷區(qū)域圖像支持飛機(jī)智能維修,提出一種改進(jìn)譜聚類的機(jī)體損傷過(guò)渡區(qū)提取方法.在分析機(jī)體損傷鄰接區(qū)域特點(diǎn)的基礎(chǔ)上,以多維灰度熵值作為相似性度量構(gòu)建樣本點(diǎn)譜圖實(shí)現(xiàn)了譜圖權(quán)重的降維運(yùn)算;并以統(tǒng)計(jì)分組中首個(gè)極小值點(diǎn)所對(duì)應(yīng)的權(quán)重為臨界進(jìn)行聚類;通過(guò)對(duì)譜聚類方法中的關(guān)鍵環(huán)節(jié)特征值計(jì)算、特征向量選取進(jìn)行改進(jìn),避免了因特征向量的取舍而造成的信息丟失.最后應(yīng)用機(jī)體損傷圖像實(shí)例驗(yàn)證了該方法的有效性.
[Abstract]:In order to support the intelligent maintenance of aircraft using the image of airframe damage region, an improved spectral clustering method for extracting the transition region of airframe damage is proposed.On the basis of analyzing the characteristics of the adjacent area of organism damage, the dimensionality reduction of the weight of the spectrum is realized by constructing the sample point spectrum with multidimensional gray entropy as similarity measure.The weight corresponding to the first minimum point in the statistical grouping is taken as the critical value for clustering, and the eigenvector selection is improved by calculating the eigenvalues of the key links in the spectral clustering method.The information loss caused by the choice of feature vectors is avoided.Finally, the effectiveness of the method is verified by an example of body damage image.
【作者單位】： 中國(guó)民航大學(xué)航空工程學(xué)院;
【基金】：航空科學(xué)基金(20151067003)
【分類號(hào)】：V267;TP391.41

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