本文關(guān)鍵詞： 混沌信號(hào) 小波變換 信號(hào)處理 故障診斷　出處：《艦船科學(xué)技術(shù)》2016年02期 　論文類型：期刊論文

【摘要】：為對(duì)船舶結(jié)構(gòu)故障進(jìn)行實(shí)時(shí)預(yù)報(bào),本文基于小波變換理論,建立混沌振動(dòng)信號(hào)的離散、分解以及重構(gòu)模型,對(duì)船舶故障特征信號(hào)進(jìn)行提取。以某船舶振動(dòng)信號(hào)為例,在信號(hào)兩端采用軟窗域函數(shù)重構(gòu),而信號(hào)中間位置采用硬窗域函數(shù)進(jìn)行重構(gòu),然后采用本文建立的模型進(jìn)行特征信號(hào)的辨識(shí),得出子結(jié)構(gòu)特征信號(hào)。結(jié)果表明:本文建立的模型較為有效,且計(jì)算速度較快,能夠?yàn)楣こ虘?yīng)用提供參考。
[Abstract]:In order to predict ship structural faults in real time, the discrete, decomposing and reconstruction models of chaotic vibration signals are established based on wavelet transform theory, and the characteristic signals of ship faults are extracted. A ship vibration signal is taken as an example. The soft window domain function is used at the two ends of the signal, while the middle position of the signal is reconstructed by the hard window domain function, and then the characteristic signal is identified by the model established in this paper. The results show that the model established in this paper is more effective, and the calculation speed is faster, which can provide a reference for engineering application.
【作者單位】： 內(nèi)蒙古電子信息職業(yè)技術(shù)學(xué)院電子工程系;
【分類號(hào)】：U661.44
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本文編號(hào)：1501974