本文選題：渦流檢測(cè) + 復(fù)雜度��； 參考：《傳感技術(shù)學(xué)報(bào)》2017年05期

【摘要】：提出了一種多線圈渦流無(wú)損檢測(cè)方法,通過(guò)相空間模糊熵算法分析渦流信號(hào)復(fù)雜度,進(jìn)而實(shí)現(xiàn)對(duì)金屬微小缺陷形狀的辨識(shí)。為了從足夠的測(cè)量信息中獲取有效的缺陷特征,設(shè)計(jì)了多線圈傳感器模型。通過(guò)仿真實(shí)驗(yàn)選取適合的傳感器參數(shù)和激勵(lì)模式。采用相空間模糊熵算法,研究不同大小、深度、形狀的缺陷對(duì)渦流信號(hào)復(fù)雜度的影響。為了準(zhǔn)確提取渦流信號(hào)的內(nèi)在規(guī)律,獲得對(duì)缺陷敏感的信號(hào)分析結(jié)果,對(duì)渦流信號(hào)進(jìn)行相空間重構(gòu),并在重構(gòu)的相空間中計(jì)算信號(hào)的模糊熵。分析結(jié)果表明:隨著缺陷體積的增加,模糊熵增大,渦流信號(hào)的復(fù)雜度增加。根據(jù)不同形狀缺陷的模糊熵均值分布圖,可以實(shí)現(xiàn)對(duì)孔、洞、裂縫3種缺陷較精確的區(qū)分。
[Abstract]:A multi-coil eddy current nondestructive testing method is proposed in this paper. The complexity of eddy current signal is analyzed by phase space fuzzy entropy algorithm, and the shape identification of metal microdefects is realized. In order to obtain effective defect features from enough measurement information, a multi-coil sensor model is designed. The suitable sensor parameters and excitation modes are selected through simulation experiments. A phase space fuzzy entropy algorithm is used to study the effects of different sizes, depths and shapes on the complexity of eddy current signals. In order to accurately extract the inherent rule of eddy current signal and obtain the result of signal analysis which is sensitive to defect, the phase space reconstruction of eddy current signal is carried out, and the fuzzy entropy of signal is calculated in the reconstructed phase space. The results show that with the increase of defect volume, the fuzzy entropy increases and the complexity of eddy current signal increases. According to the distribution map of fuzzy entropy mean value of different shape defects, it is possible to distinguish accurately three kinds of defects: hole, hole and crack.
【作者單位】： 天津工業(yè)大學(xué)電子與信息工程學(xué)院;天津工業(yè)大學(xué)理學(xué)院;天津大學(xué)電氣與自動(dòng)化工程學(xué)院;
【基金】：國(guó)家科技支撐計(jì)劃重點(diǎn)項(xiàng)目(2013BAF06B00) 國(guó)家自然科學(xué)基金項(xiàng)目(61373104,61402330,61405143,61601324) 高等學(xué)校博士點(diǎn)專(zhuān)項(xiàng)科研基金項(xiàng)目(20131201120002) 天津市應(yīng)用基礎(chǔ)與前沿技術(shù)研究計(jì)劃項(xiàng)目(15JCQNJC01500)
【分類(lèi)號(hào)】：TG115.28

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1 李筠;祝勇;;誤差分布類(lèi)型的模糊熵判別方法[A];第七屆青年學(xué)術(shù)會(huì)議論文集[C];2005年

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