《電子技術(shù)應(yīng)用》
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基于主軸電機(jī)電流信號(hào)的表面粗糙度檢測(cè)
電子技術(shù)應(yīng)用
劉雪杰,李國(guó)富,,任潞
寧波大學(xué) 機(jī)械工程與力學(xué)學(xué)院,,浙江 寧波 315211
摘要: 針對(duì)表面粗糙度不能及時(shí)檢測(cè)造成的工件浪費(fèi)問(wèn)題,首次提出根據(jù)主軸電機(jī)電流信號(hào)進(jìn)行表面粗糙度檢測(cè)分類(lèi),。通過(guò)實(shí)驗(yàn)采集不同表面粗糙度加工時(shí)的主軸電機(jī)電流信號(hào),,采用小波包分解將電流信號(hào)分解成不同頻段,借助能量特征和裕度因子對(duì)不同頻段電流信號(hào)進(jìn)行評(píng)估,,過(guò)濾低相關(guān)性頻段,,再通過(guò)隨機(jī)森林篩選特征,降低特征的冗余性,??傊C波失真特征實(shí)現(xiàn)了積屑瘤檢測(cè),僅依賴(lài)構(gòu)建的電流信號(hào)特征工程表面粗糙度檢測(cè)準(zhǔn)確率高達(dá)95%以上,,并且檢測(cè)時(shí)間在2 s以內(nèi),,基本實(shí)現(xiàn)了工件表面粗糙度的快速準(zhǔn)確檢測(cè)。
中圖分類(lèi)號(hào):TP181 文獻(xiàn)標(biāo)志碼:A DOI: 10.16157/j.issn.0258-7998.234208
中文引用格式: 劉雪杰,,李國(guó)富,,任潞. 基于主軸電機(jī)電流信號(hào)的表面粗糙度檢測(cè)[J]. 電子技術(shù)應(yīng)用,2024,,50(2):54-59.
英文引用格式: Liu Xuejie,,Li Guofu,Ren Lu. Surface roughness detection based on spindle motor current signal[J]. Application of Electronic Technique,,2024,,50(2):54-59.
Surface roughness detection based on spindle motor current signal
Liu Xuejie,Li Guofu,,Ren Lu
College of Mechanical Engineering and Mechanics,,Ningbo University,Ningbo 315211,, China
Abstract: Workpiece waste is usually caused by delayed detection of surface roughness. A rapid surface roughness detection classification based on the current signal of the spindle motor is proposed for the first time. The current signals of the spindle motor under different surface roughness processing conditions are collected through experiments, and the current signals are decomposed into different frequency bands through wavelet packet decomposition. The current signals of different frequency bands are evaluated by the energy characteristics and the margin factors, and the low correlation frequency bands are filtered. Then the features are screened through random forest to reduce the redundancy of features. The total harmonic distortion feature achieves built-up edge detection during the machining process. The workpiece surface roughness detection accuracy is as high as 95%. And the detection time is within 2 seconds. Spindle current signal analysis basically achieves fast and accurate detection of workpiece surface roughness.
Key words : spindle motor current signal,;wavelet packet decomposition;random forest,;the total harmonic distortion,;surface roughness

引言

表面粗糙度作為工件質(zhì)量的重要評(píng)價(jià)指標(biāo),直接影響工件的耐磨性、抗腐蝕性,、密封性,、配合程度、傳動(dòng)精度[1],,因此在工件工藝設(shè)計(jì)時(shí)都會(huì)優(yōu)先考慮表面粗糙度,。表面粗糙度的及時(shí)檢測(cè)是十分必要的,當(dāng)工件表面粗糙度不滿足設(shè)計(jì)要求時(shí)需要及時(shí)調(diào)整工藝參數(shù)避免更大的損失,。表面粗糙度的檢測(cè)有多種方法,,大致分為兩類(lèi),第一類(lèi)是采用接觸式探針進(jìn)行表面粗糙度檢測(cè),;第二類(lèi)是通過(guò)傳感器采集圖像,、電流信號(hào)、振動(dòng)信號(hào)或聲發(fā)射信號(hào)進(jìn)行分析處理,,間接得到表面粗糙度值,。接觸式檢測(cè)準(zhǔn)確度很高,,但是需要等待加工完成后才能進(jìn)行檢測(cè),,影響加工效率[2]。圖像檢測(cè)容易受到切削液和切屑的影響,,另外圖像檢測(cè)需要高性能的工業(yè)攝像機(jī),,導(dǎo)致圖像檢測(cè)表面粗糙度價(jià)格昂貴。振動(dòng)信號(hào)通常安裝在刀具上,,可能會(huì)干擾機(jī)床的加工,,聲發(fā)射信號(hào)容易受到其他機(jī)床的干擾[3],而電機(jī)電流信號(hào)是機(jī)床材料去除的動(dòng)力來(lái)源,,與加工過(guò)程十分密切,,外界不易對(duì)機(jī)床電機(jī)電流信號(hào)造成干擾[4],并且主軸電流信號(hào)獲取十分方便,,距離較遠(yuǎn)也能輕松獲取電流信號(hào),。使用電機(jī)電流信號(hào)進(jìn)行表面粗糙度的檢測(cè)研究比較少,主要原因是電流信號(hào)與表面粗糙度存在較為復(fù)雜的對(duì)應(yīng)關(guān)系,。


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作者信息:

劉雪杰,,李國(guó)富,任潞

寧波大學(xué) 機(jī)械工程與力學(xué)學(xué)院,,浙江 寧波 315211


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