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</noscript> <script> function stop(){ return false; } document.oncontextmenu=stop; </script> <!-- nav --> <nav class="navbar navbar-default navbar-fixed-top"> <div class="container"> <div class="navbar-header"> <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false" aria-controls="navbar"> <span class="sr-only">高速雕銑機_精雕機_石墨機_加工中心_鉆攻中心-宇匠數控</span> <span class="icon-bar"></span> <span class="icon-bar"></span> <span class="icon-bar"></span> </button> <div class="top-nav-right navbar-right"> <ul> <li id="fat-menu" class="dropdown"> <a class="dropdown-toggleglyphicon glyphicon glyphicon-globe" data-toggle="dropdown" role="button" aria-haspopup="true" aria-expanded="false"></a> <ul class="dropdown-menu" aria-labelledby="drop3"> <li><a id="StranLink" name="StranLink">繁體</a></li><li><a href="http://www.www.htspipe.com.cn/" target="_blank">公司網站</a></li> </ul> </li> <li class="glyphicon glyphicon-search" data-toggle="modal" 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bodyBgs[2] = "/images/banner/s3.jpg"; bodyBgs[3] = "/images/banner/s4.jpg"; bodyBgs[4] = "/images/banner/s5.jpg"; var randomBgIndex = Math.round( Math.random() * 4 ); //輸出隨機的背景圖 document.write('<style>.banner{background:url(' + bodyBgs[randomBgIndex] + ') no-repeat 50% bottom}</style>'); //]]> </script> <section> <div class="banner" style="height:160px;"> </div> </section> <!-- 面包屑導航開始 --> <div class="container "> <nav class="sub_menu"> <ol class="breadcrumb"><span class="glyphicon glyphicon-list"></span> <li><a href="/">網站首頁</a></li> <li><a title="數控文章" href="/bethel/news">數控文章</a></li> </ol> </nav> </div> <!--/sub_menu--><!-- 面包屑導航結束 --> <!-- 頁面標題開始 --> <div class="title"> <h3><a>基于LS-SVM和神經網絡的五軸加工中心誤差補償策略<small></small></a></h3> </div> <!-- 頁面標題結束 --> <hr class="featurette-divider"> <!-- 中部開始 --> <div class="container"> <!-- 正文 --> <div class="lead" id="print"> <p><span style="font-size: small;"> <span style="line-height: 12.95pt; background-color: transparent;">引言</span> </span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:23.0pt;line-height:12.95pt;mso-line-height-rule: exactly;background:transparent"><span style="font-size: small;"><span class="4"><a href='http://www.www.htspipe.com.cn/' target='_blank'>加工中心</a>誤差檢測的方法主要有單項誤差檢測和 對角線誤差檢測，五軸<a href='http://www.www.htspipe.com.cn/' target='_blank'>加工中心</a>的誤差至少有40多 項。一般采用單項誤差檢測法，即需要對每個坐標軸 進行校準和測量，時間長，效率低，且由于數據時間間 隔過長，采集誤差的隨機性會影響數據的連續性和關 聯性，使得數據的有效性降低。而且<a href='http://www.www.htspipe.com.cn/' target='_blank'>加工中心</a>單項誤 差的變化情況并不能與最終加工誤差有效映射，甚至 有時的變化趨勢截然相反，導致最終對單項誤差采用 的補償效果不理想，數據偏差較大。對于多軸加工中 心，經綜合考慮，采用空間誤差檢測方法能夠比較客觀 地反映刀具相對于工件的加工真實誤差，進而實施有 效的誤差補償。</span></span></p> <p class="40" align="left" style="margin: 0cm 0cm 0.0001pt; line-height: 12.95pt; background: transparent;"><span style="font-size: small;"><span class="4">1<a href='http://www.www.htspipe.com.cn/' target='_blank'>五軸加工中心</a>運動鏈構型與誤差檢測方案設計</span></span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:23.0pt;line-height:12.95pt;mso-line-height-rule: exactly;background:transparent"><span style="font-size: small;"><span class="4"><a href='http://www.www.htspipe.com.cn/' target='_blank'>五軸加工中心</a>如圖1所示，其從加工功能上可看 作是車削中心和銑鏜中心組合的產物。車削中心具有 8個控制軸，其中4個為聯動軸，可實現車鉆鏜復雜零 件加工；銑鏜中心比車削中心多出一個旋轉軸</span><span class="4MingLiU"><span lang="EN-US">B</span></span><span class="4">軸， 共計9個控制軸，因此可實現5軸聯動，這使得五軸加 工中心能加工出表面曲線更復雜的零件。</span></span></p> <div><span style="font-size: small;"><br /> </span></div> <p><span style="font-size: small;"> <!--[if !supportTextWrap]--> <!--[endif]--> </span></p> <p class="40" align="left" style="margin: 0cm 0cm 0.0001pt; line-height: 12.95pt; background: transparent;"><span style="font-size: small;"><span class="4"><span style="font-family: SimSun;">1.1</span></span><span class="4">五軸加工中心運動鏈構型</span></span></p> <p><span style="font-size: small;"><span class="4">針對本文試驗用五軸加工中心的構型，設計滿足 空間誤差和熱誤差整體補償方案。主要依據五軸加工 中心</span><span class="4">傳動鏈的結構特點，在車主軸、銑主軸、旋轉軸、工 作臺、刀架等主要機構安裝16個檢測傳感器，通過合 理布置使所檢測的誤差更全面和有效。</span></span></p> <p><span style="font-size: small;"><span class="4" style="line-height: 12.95pt; background-color: transparent;"><span style="font-family: SimSun;">1.2</span></span><span class="4" style="line-height: 12.95pt; background-color: transparent;">誤差檢測方案設計</span></span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:23.0pt;line-height:12.95pt;mso-line-height-rule: exactly;background:transparent"><span style="font-size: small;"><span class="4">誤差檢測方案具體如下：</span></span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:23.0pt;line-height:12.95pt;mso-line-height-rule: exactly;mso-list:l0 level1 lfo1;tab-stops:41.3pt;background:transparent"><span style="font-size: small;"><!--[if !supportLists]--><span style="font-family: SimSun;">(1)<span style="font-stretch: normal; line-height: normal; font-family: 'Times New Roman';"> </span></span><!--[endif]--><span class="4">在車主軸床身和銑主軸工作臺之間，可以采 用激光多普勒干涉儀測量得到3個定位誤差、4個體 對角線誤差、個垂直度誤差以及6個直線度誤差。</span></span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:23.0pt;line-height:12.95pt;mso-line-height-rule: exactly;mso-list:l0 level1 lfo1;tab-stops:41.3pt;background:transparent"><span style="font-size: small;"><!--[if !supportLists]--><span style="font-family: SimSun;">(2)<span style="font-stretch: normal; line-height: normal; font-family: 'Times New Roman';"> </span></span><!--[endif]--><span class="4">通過實時數據檢測可以得到主軸溫度及5個 熱漂移數據信息。</span></span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:23.0pt;line-height:12.95pt;mso-line-height-rule: exactly;background:transparent"><span style="font-size: small;"><span class="4">采用分步對角線誤差和熱漂移誤差的綜合檢測方 案設計，可以較為直觀地獲取刀具與工件運動鏈系統 的實際誤差，完整地描述五軸加工中心的空間誤差特 性，從而進行有效的誤差補償。</span></span></p> <p class="40" align="left" style="margin: 0cm 0cm 0.0001pt; line-height: 12.95pt; background: transparent;"><span style="font-size: small;"><span class="4">2神經網絡誤差補償模型</span></span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:23.0pt;line-height:12.95pt;mso-line-height-rule: exactly;background:transparent"><span style="font-size: small;"><span class="4">五軸加工中心綜合誤差具有多樣性和不確定性， 而誤差檢測方案包含空間誤差檢測和熱誤差檢測，由 于誤差產生的原理和方式不同，這兩種誤差變化規律 大相徑庭。因此可以利用神經網絡算法，在對五軸加 工中心誤差補償的過程中自動識別系統的特性，包括 輸入空間誤差數組、熱誤差數組、預留數組，從而自動 適應系統隨時間的特性變異，以達到對誤差系統的最 優控制。</span></span></p> <p class="40" align="left" style="margin: 0cm 0cm 0.0001pt; line-height: 12.95pt; background: transparent;"><span style="font-size: small;"><span class="4"><span style="font-family: SimSun;">2.1</span></span><span class="4">神經網絡的構建</span></span></p> <p><span style="font-size: small;"><span class="4MingLiU"><span lang="EN-US">BP</span></span><span class="4">網絡結構如圖2所示，輸入層、隱含層和輸出 </span><span class="42pt">層分別有個單元節點；輸入層與隱含層之間的 權值為輸出層與隱含層之間權值為</span><span class="4MingLiU"><span lang="EN-US">w</span></span><span class="42pt"><span style="font-family: SimSun;">; </span></span><span class="42pt">分別</span><span class="4" style="line-height: 12.95pt; text-align: justify; background-color: transparent;">表示若干層級神經單元?？臻g誤差和熱誤差需要運用 生物遺傳學、最優控制、支持向量機等方法建立相應的 數學模型，其輸出為五軸加工中心坐標軸的補償值。如 需補償誤差增益，則按減少期望輸出與實際輸出間誤差 的原則，運用</span><span class="4MingLiU" style="line-height: 12.95pt; text-align: justify; background-color: transparent;"><span lang="EN-US">BP</span></span><span class="4" style="line-height: 12.95pt; text-align: justify; background-color: transparent;">神經網絡拓撲關系，從輸出層經各隱含 層，最后返回輸入端，并調整該輸入層的權重數值。</span></span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:0cm;line-height:13.2pt;mso-line-height-rule: exactly;mso-list:l0 level2 lfo1;tab-stops:26.4pt;background:transparent"><span style="font-size: small;"><!--[if !supportLists]--><span style="font-family: SimSun;">2.2<span style="font-stretch: normal; line-height: normal; font-family: 'Times New Roman';"> </span></span><!--[endif]--><span class="4MingLiU"><span lang="EN-US">LS</span></span><span class="4"><span style="font-family: SimSun;">-</span></span><span class="4MingLiU"><span lang="EN-US">SVM</span></span><span class="4">誤差補償模型</span></span></p> <p><span style="font-size: small;"> <span class="4">本文的誤差辨識建模采用最小二乘支持向量機建 模。該方法是在基于</span><span class="4MingLiU"><span lang="EN-US">BP</span></span><span class="4">神經網絡模型的基礎上，采 用最小二乘線性系統作為損失函數，將原問題轉化為 線性方程，從而簡化了計算，使收斂速度加快。 </span></span></p> <p class="40" align="left" style="margin: 0cm 0cm 0.0001pt; line-height: 13.2pt; background: transparent;"><span style="font-size: small;"><span class="42pt">3加工中心誤差傳感器布置 </span><span class="42pt"><span style="font-family: SimSun;">3.1</span></span><span class="42pt">測量裝置與靶標布置</span></span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:24.0pt;line-height:13.2pt;mso-line-height-rule: exactly;background:transparent"><span style="font-size: small;"><span class="4">選用光動公司</span><span class="4MingLiU"><span lang="EN-US">LDDM</span></span><span class="4">激光多普勒干涉儀對某五 軸加工中心進行了分步體對角線空間誤差檢測 </span><span class="4MingLiU5">。 </span><span class="4">首先 建立坐標系，確定一個立方體的空間作為檢測區域，然 后安裝激光干涉儀測量裝置，包括激光頭、反射鏡、傳 感器等</span><span class="4MingLiU5">。</span><span class="4">在安裝時將激光頭固定安裝于床身，同時要 將反射鏡固定安裝在</span><span class="4MingLiU"><span lang="EN-US">Y</span></span><span class="4">軸對應的驅動絲杠的滑塊上</span><span class="4MingLiU5">。 </span><span class="42pt"><span style="font-family: SimSun;">3.2</span></span><span class="42pt">傳感器布置方案</span></span></p> <p><span style="font-size: small;"> <span class="42pt">將16個傳感器分成4組</span><span class="4MingLiU4">，</span><span class="4">圖3示出了部分傳感器 的具體位置</span><span class="4MingLiU5">。</span><span class="4">測量主軸運動及工作臺滑塊采用9號</span><span class="4"><span style="font-family: PMingLiU;">?</span></span><span class="4"> 16號傳感器；測量主軸溫度為1號</span><span class="4"><span style="font-family: PMingLiU;">?</span></span><span class="4">4號傳感器；測量 <a href='http://www.www.htspipe.com.cn/' target='_blank'>機床</a>床身溫度為5號</span><span class="4"><span style="font-family: PMingLiU;">?</span></span><span class="4">6號傳感器；測量<a href='http://www.www.htspipe.com.cn/' target='_blank'>機床</a>內部環 </span><span class="42pt">境溫度為7號</span><span class="42pt"><span style="font-family: PMingLiU;">?</span></span><span class="42pt">8號傳感器</span><span class="4MingLiU5">。</span><span class="4">加工中心連續空載運</span><span class="4" style="line-height: 13.2pt; text-align: justify; text-indent: 24pt; background-color: transparent;">行 6 </span><span class="4MingLiU" style="line-height: 13.2pt; text-align: justify; text-indent: 24pt; background-color: transparent;"><span lang="EN-US">h</span></span><span class="4MingLiU3" style="line-height: 13.2pt; text-align: justify; text-indent: 24pt; background-color: transparent;"><span lang="EN-US">，</span></span><span class="4" style="line-height: 13.2pt; text-align: justify; text-indent: 24pt; background-color: transparent;">采集這16處溫度值以及主軸的軸</span><span class="4MingLiU3" style="line-height: 13.2pt; text-align: justify; text-indent: 24pt; background-color: transparent;">、</span><span class="4" style="line-height: 13.2pt; text-align: justify; text-indent: 24pt; background-color: transparent;">徑向熱變形位 移。然后每隔</span><span class="4" style="line-height: 13.2pt; text-align: justify; text-indent: 24pt; background-color: transparent;"><span style="font-family: SimSun;">6 </span></span><span class="4MingLiU" style="line-height: 13.2pt; text-align: justify; text-indent: 24pt; background-color: transparent;"><span lang="EN-US">mm</span></span><span class="4" style="line-height: 13.2pt; text-align: justify; text-indent: 24pt; background-color: transparent;">采集一組數據并記錄，前后可以 獲得60組數據用于基于</span><span class="4MingLiU" style="line-height: 13.2pt; text-align: justify; text-indent: 24pt; background-color: transparent;"><span lang="EN-US">LS-SVM</span></span><span class="4" style="line-height: 13.2pt; text-align: justify; text-indent: 24pt; background-color: transparent;">方法的熱誤差數據 建模計算。</span></span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;line-height:12.95pt;mso-line-height-rule:exactly; background:transparent"><span style="font-size: small;"><span class="42pt"><span style="font-family: SimSun;">3.3</span></span><span class="42pt">空間誤差檢測與補償</span></span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:25.0pt;line-height:12.95pt;mso-line-height-rule: exactly;background:transparent"><span style="font-size: small;"><span class="4">進行空間誤差檢測時，首先使銑主軸的</span><span class="4MingLiU"><span lang="EN-US">X</span></span><span class="4"><span lang="EN-US">、</span></span><span class="4MingLiU"><span lang="EN-US">Y</span></span><span class="4"><span lang="EN-US">、</span></span><span class="4MingLiU"><span lang="EN-US">Z </span></span><span class="4">三坐標軸聯動，檢測出4個體對角線的空間位移誤差。 用激光干涉儀沿每一條體對角線進行正向和反向測 量，獲得2組數據曲線，如體對角線</span><span class="4MingLiU"><span lang="EN-US">B</span></span><span class="4">軸正向曲線和 </span><span class="4MingLiU"><span lang="EN-US">B</span></span><span class="4">軸反向曲線。然后根據體對角線數據和曲線，獲得 </span><span class="42pt">與體對角線相對應的三坐標軸正、反向誤差。 </span><span class="4">經過多次測量，可以獲得</span><span class="4MingLiU"><span lang="EN-US">X</span></span><span class="4"><span lang="EN-US">、</span></span><span class="4MingLiU"><span lang="EN-US">Y</span></span><span class="4"><span lang="EN-US">、</span></span><span class="4MingLiU"><span lang="EN-US">Z</span></span><span class="4">三坐標軸的定位誤 差和垂直直線度誤差。最后將多次獲取的正、反向誤 差數據取均值，獲得平均誤差。具體補償步驟如下：① 輸入向量為空間誤差數組和熱漂移數組；②輸出向量 為數控系統</span><span class="4MingLiU"><span lang="EN-US">X</span></span><span class="4"><span lang="EN-US">、</span></span><span class="4MingLiU"><span lang="EN-US">Y</span></span><span class="4"><span lang="EN-US">、</span></span><span class="4MingLiU"><span lang="EN-US">Z</span></span><span class="4">三坐標的補償值；③根據基于空 間誤差神經網絡算法確定空間誤差輸入層至中間層的 連接權重，根據熱誤差</span><span class="4MingLiU"><span lang="EN-US">LS</span></span><span class="4"><span style="font-family: SimSun;">-</span></span><span class="4MingLiU"><span lang="EN-US">SVM</span></span><span class="4">函數建模確定熱誤差 輸入層至中間層的連接權重，以及計算精度值和最大 學習次數；④重復校核以驗證機床的空間誤差數據。</span></span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:25.0pt;line-height:12.95pt;mso-line-height-rule: exactly;background:transparent"><span style="font-size: small;"><br type="_moz" /> </span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:25.0pt;line-height:12.95pt;mso-line-height-rule: exactly;background:transparent"> </p> <p><span style="font-size: small;"> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:25.0pt;line-height:12.95pt;mso-line-height-rule: exactly;background:transparent"><span class="1810pt">結果分析</span></p> <!--EndFragment--></span></p> <p> </p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:25.0pt;line-height:12.95pt;mso-line-height-rule: exactly;background:transparent"><span style="font-size: small;"><span class="4">在對五軸加工中心進行空間誤差檢測的基礎上， 通過調整對數控系統誤差進行補償，補償前、后的檢測 條件和測量方式不變，得到的補償前、后的誤差曲線分 別如圖4、圖5所示。</span></span></p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;text-indent:25.0pt;line-height:12.95pt;mso-line-height-rule: exactly;background:transparent"> </p> <p class="40" style="margin-top:.35pt;margin-right:0cm;margin-bottom:5.35pt; margin-left:0cm;text-align:justify;text-justify:inter-ideograph;text-indent: 25.0pt;line-height:12.95pt;mso-line-height-rule:exactly;background:transparent"><span style="font-size: small;"><span class="4">圖4中，補償前的誤差曲線基本是平穩向上趨勢， 綜合誤差與加工中心工作行程空間基本呈線性關系， 隨著機床運動行程距離增大，累積誤差也不斷增大，誤 差整體在</span><span class="4"><span lang="EN-US">一</span></span><span class="4"><span style="font-family: SimSun;">10 </span></span><span class="4MingLiU"><span lang="EN-US">ym</span></span><span class="4"><span style="font-family: PMingLiU;">?</span></span><span class="4">70 </span><span class="4"><span style="font-family: SimSun;">^</span></span><span class="4MingLiU"><span lang="EN-US">m</span></span><span class="4">之間。在實施誤差補償后，</span><span class="4">誤差曲線急劇波動，這反映了數控系統在用</span><span class="4MingLiU"><span lang="EN-US">G</span></span><span class="4">代碼調 整后的誤差情況?？梢娧a償后體對角線的誤差得到了 很好的改善，誤差趨勢由線性增長變為波折起伏，誤差 </span><span class="42pt">整體控制在</span><span class="42pt"><span lang="EN-US">一</span></span><span class="42pt">10 um </span><span class="42pt"><span style="font-family: PMingLiU;">?</span></span><span class="42pt">32um 之間，精度提高了</span><span class="4"><span style="font-family: SimSun;">47. </span></span><span class="4">5 %</span><span class="46pt">，</span><span class="4">這說明空間誤差補償效果明顯。</span></span><span style="font-size: small;"><br type="_moz" /> </span></p> <p class="40" style="margin-top:.35pt;margin-right:0cm;margin-bottom:5.35pt; margin-left:0cm;text-align:justify;text-justify:inter-ideograph;text-indent: 25.0pt;line-height:12.95pt;mso-line-height-rule:exactly;background:transparent"> </p> <p class="40" style="margin:0cm;margin-bottom:.0001pt;text-align:justify; text-justify:inter-ideograph;line-height:11.5pt;mso-line-height-rule:exactly; background:transparent"><span style="font-size: small;"><span class="4"> 5結論</span></span></p> <p class="40" style="margin-top:0cm;margin-right:0cm;margin-bottom:0cm; margin-left:9.0pt;margin-bottom:.0001pt;text-align:justify;text-justify:inter-ideograph; text-indent:21.0pt;line-height:11.5pt;mso-line-height-rule:exactly;tab-stops: 79.3pt;background:transparent"><span style="font-size: small;"><span class="4">本文設計了基于</span><span class="4MingLiU"><span lang="EN-US">LS-SVM</span></span><span class="42pt">和神經網絡的五軸加 </span><span class="4">工中心綜合誤差檢測方案。在綜合考慮空間誤差和熱 誤差的影響條件下，提出了五軸加工中心綜合誤差補 償方法。運用</span><span class="4MingLiU"><span lang="EN-US">LS-SVM</span></span><span class="42pt">和神經網絡算法建立了幾何 </span><span class="4">誤差和熱誤差綜合補償模型，實施整體補償之后誤差 控制在</span><span class="4"><span lang="EN-US">一</span></span><span class="4"><span style="font-family: SimSun;">10um</span></span><span class="4"><span style="font-family: PMingLiU;">?</span></span><span class="4">32 um之間，精度提高了 </span><span class="4"><span style="font-family: SimSun;">47. </span></span><span class="4">5% ,取</span><span class="4">得良好的實驗效果。</span></span></p> <p class="40" style="margin-top:0cm;margin-right:0cm;margin-bottom:0cm; margin-left:9.0pt;margin-bottom:.0001pt;text-align:justify;text-justify:inter-ideograph; text-indent:21.0pt;line-height:11.5pt;mso-line-height-rule:exactly;tab-stops: 79.3pt;background:transparent"> </p> <p class="40" style="margin-top:0cm;margin-right:0cm;margin-bottom:0cm; margin-left:9.0pt;margin-bottom:.0001pt;text-align:justify;text-justify:inter-ideograph; text-indent:21.0pt;line-height:11.5pt;mso-line-height-rule:exactly;tab-stops: 79.3pt;background:transparent"> </p> <p class="40" style="margin-top:0cm;margin-right:0cm;margin-bottom:0cm; margin-left:9.0pt;margin-bottom:.0001pt;text-align:justify;text-justify:inter-ideograph; text-indent:21.0pt;line-height:11.5pt;mso-line-height-rule:exactly;tab-stops: 79.3pt;background:transparent"><span style="font-size:9.0pt;font-family:宋體;mso-ascii-font-family: "Times New 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