TW202405591A - A spindle temperature measurement and compensation system - Google Patents
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Abstract
Description
本發明涉及一種工具機精度補償手段，尤其涉及一種主軸熱溫升量測遠端溫升修模補償系統與優化方法。The invention relates to a machine tool accuracy compensation method, and in particular to a spindle thermal temperature rise measurement remote end temperature rise mold repair compensation system and optimization method.
現有的熱溫升補償技術，是金屬桿安裝於主軸，再配合金屬桿的主球周圍設置多個探測頭，接著啟動工具機台運作，在機台於不同溫度時，以多個探測頭逐次探測金屬桿的主球的方式，獲得主軸相應主軸因熱而溫度上升時造成的位移。The existing thermal temperature rise compensation technology is to install a metal rod on the spindle, and then set multiple probe heads around the main ball of the metal rod. Then the machine tool is started to operate. When the machine table is at different temperatures, multiple probe heads are used one after another. By detecting the main ball of the metal rod, the displacement of the corresponding spindle caused by the temperature rise due to heat is obtained.
藉由上述的量測，專業人員能夠以獲得的數據，補償工具機因熱溫度上升所造成的偏移。但上述的方法有一些缺點存在，例如此種方式無法預測未知溫度時，機台因熱溫度升高後產生的誤差，需要安裝多個探測頭的方式也造成量測的裝置安裝的不便，有待進一步的改良。Through the above-mentioned measurements, professionals can obtain accurate data to compensate for the deviation of the machine tool caused by the increase in thermal temperature. However, the above method has some shortcomings. For example, when this method cannot predict the unknown temperature, the error caused by the increase in thermal temperature of the machine, and the need to install multiple probe heads also cause inconvenience in the installation of the measurement device. This needs to be done further improvements.
由於現有熱溫升補償技術無法預測未知溫度時主軸的偏移，本發明藉由雲端收集不同工具機的溫度補償模型，藉此整合、提取不同溫度補償模型的特徵資料建立預測精度更佳的模型更新至各工具機，達到主軸熱溫補優化的功效。Since the existing thermal temperature rise compensation technology cannot predict the deflection of the spindle at an unknown temperature, the present invention collects temperature compensation models of different machine tools through the cloud, thereby integrating and extracting the characteristic data of different temperature compensation models to establish a model with better prediction accuracy. Updated to each machine tool to achieve the effect of spindle thermal compensation optimization.
為達到上述創作目的，本發明提供一種主軸熱溫升量測遠端溫升修模補償系統，包括一位於遠端的雲端運算單元、兩個以上位於本地端的工具機，以及分別安裝於各工具機的一多軸光學檢測裝置、一個以上的溫度感測器以及一訊號處理模組，其中：In order to achieve the above creative purpose, the present invention provides a spindle thermal temperature rise measurement and remote temperature rise mold repair compensation system, which includes a remote cloud computing unit, two or more locally located machine tools, and a machine tool installed on each tool respectively. A multi-axis optical detection device, more than one temperature sensor and a signal processing module of the machine, including:
各工具機具有一控制器以及分別受該控制器運作的一平台以及一位於各平台上方的主軸，於各主軸安裝一刀把；Each machine tool has a controller, a platform operated by the controller, and a spindle above each platform, and a tool handle is installed on each spindle;
各多軸光學檢測裝置包括一球形透鏡裝置以及一感測頭模組，各球形透鏡裝置結合於各工具機的刀把並且於自由端形成一球形透鏡，各感測頭模組具有一固定於各平台上的固定座，於各固定座的頂部設有一支架，於各支架設有一光學非接觸式的感測器組，於該感測器組的中央形成一量測點；當各工具機將各球形透鏡移動至各量測點後，能量測各工具機的主軸與各球形透鏡因主軸運作產生的熱而造成的位移變化數據；Each multi-axis optical detection device includes a spherical lens device and a sensing head module. Each spherical lens device is combined with the tool handle of each machine tool and forms a spherical lens at the free end. Each sensing head module has a sensor fixed on each machine tool. The fixed base on the platform has a bracket on the top of each fixed base, and an optical non-contact sensor group is installed on each bracket to form a measurement point in the center of the sensor group; when each machine tool After each spherical lens moves to each measurement point, the displacement change data of the main shaft of each machine tool and each spherical lens caused by the heat generated by the operation of the main shaft is measured;
各溫度感測器分別固定於各工具機，用以量測溫度變化數據；Each temperature sensor is fixed on each machine tool to measure temperature change data;
各訊號處理模組與安裝於同一工具機的各感測頭模組以及各溫度感測器訊號連接，各訊號處理模組並與各工具機的控制器訊號連接，當各工具機的主軸運作時，各訊號處理模組抓取對應各工具機的多組位移變化數據以及溫度變化數據輸入模型，建置一溫度補償模型傳輸至該雲端運算單元；Each signal processing module is connected with signals of each sensing head module and each temperature sensor installed on the same machine tool. Each signal processing module is also connected with a signal of the controller of each machine tool. When the spindle of each machine tool operates, At this time, each signal processing module captures multiple sets of displacement change data and temperature change data corresponding to each machine tool and inputs the data into the model, builds a temperature compensation model and transmits it to the cloud computing unit;
該雲端運算單元收集各工具機的溫度補償模型，整合提取各溫度補償模型的特徵資料建立一更新溫度補償模型，將該更新溫度補償模型傳回各訊號處理模組並更新至各工具機的控制器進行補償。The cloud computing unit collects the temperature compensation models of each machine tool, integrates and extracts the characteristic data of each temperature compensation model to create an updated temperature compensation model, and transmits the updated temperature compensation model back to each signal processing module and updates it to the control of each machine tool. device to compensate.
為達到上述創作目的，本發明提供一種主軸熱溫升量測遠端溫升修模補償優化方法，其方法的步驟包括：In order to achieve the above creative purpose, the present invention provides a spindle thermal temperature rise measurement remote end temperature rise mold repair compensation optimization method. The steps of the method include:
於兩個以上本地端的工具機分別架設一光學檢測裝置以及結合一個以上的溫度感測器，各光學檢測裝置包括一結合於各工具機主軸的球形透鏡裝置以及一結合於各工具機的平台的感測頭模組，該球形透鏡裝置設有一球形透鏡，該感測頭模組設有一光學非接觸式的感測器組，於該感測器組的中央形成一量測點；An optical detection device and one or more temperature sensors are respectively installed on more than two local machine tools. Each optical detection device includes a spherical lens device combined with the main axis of each machine tool and a platform combined with each machine tool. A sensing head module, the spherical lens device is provided with a spherical lens, the sensing head module is provided with an optical non-contact sensor group, forming a measurement point in the center of the sensor group;
各工具機將各球形透鏡移動至各量測點後，各工具機的主軸開始旋轉，在各主軸旋轉的過程中，各感測頭模組量測該球形透鏡因其所在主軸旋轉升高溫度而產生的位移變化數據，各工具機的各溫度感測器量測溫度變化數據，以軟體抓取各工具機的位移變化數據以及溫度變化數據輸入模型，建置一本地端的溫度補償模型；以及After each machine tool moves each spherical lens to each measurement point, the main shaft of each machine tool begins to rotate. During the rotation of each main shaft, each sensor head module measures the temperature increase of the spherical lens due to the rotation of the main shaft. The generated displacement change data is measured by each temperature sensor of each machine tool, and software is used to capture the displacement change data and temperature change data of each machine tool and input it into the model to build a local temperature compensation model; and
將各工具機的溫度補償模型傳輸至一位於遠端的雲端運算單元，該雲端運算單元收集各工具機的溫度補償模型，整合提取各溫度補償模型的特徵資料建立一更新溫度補償模型，將該更新溫度補償模型傳回本地端的各工具機進行補償。The temperature compensation model of each machine tool is transmitted to a remote cloud computing unit. The cloud computing unit collects the temperature compensation model of each machine tool, integrates and extracts the characteristic data of each temperature compensation model to establish an updated temperature compensation model, and integrates the temperature compensation model of each machine tool. The updated temperature compensation model is sent back to each local machine tool for compensation.
本發明藉由上述的系統與方法，在各工具機處訓練對應各工具機的溫度補償模型後，能收集來自各種環境、參數條件產生的模型至遠端的雲端運算單元，經由雲端運算單元整合、提取不同溫度補償模型的特徵資料建立預測精度更佳的模型更新至各工具機，達到主軸熱溫補優化的功效，同時由於在遠端的雲端運算單元僅提取各溫度補償模型的特徵資料，沒有接觸原始的位移變化數據以及溫度變化數據，因此各工具機本地端的數據具備隱私性。Through the above-mentioned system and method, after training the temperature compensation model corresponding to each machine tool at each machine tool, the present invention can collect the models generated from various environments and parameter conditions to the remote cloud computing unit, and integrate them through the cloud computing unit. , extract the characteristic data of different temperature compensation models to build models with better prediction accuracy and update them to each machine tool to achieve the effect of spindle thermal compensation optimization. At the same time, because the remote cloud computing unit only extracts the characteristic data of each temperature compensation model, There is no contact with the original displacement change data and temperature change data, so the local data of each machine tool is private.
為能詳細瞭解本發明的技術特徵及實用功效，並可依照說明書的內容來實施，進一步以如圖式所示的較佳實施例，詳細說明如下。In order to understand the technical features and practical effects of the present invention in detail and implement it according to the content of the description, the preferred embodiments as shown in the drawings are further described in detail as follows.
如圖2至圖7所示的較佳實施例，本發明提供一種主軸熱溫升量測遠端溫升修模補償系統，用以實施如圖1所示的主軸熱溫升量測遠端溫升修模補償優化方法；請參看圖2至圖4以及圖7所示，該系統包括一設於網際網路的雲端運算單元100以及兩個以上的工具機10，該雲端運算單元100所在處稱為遠端，各工具機10所在處稱為本地端，較佳的，各工具機10位於異地，於各工具機10安裝一多軸光學檢測裝置Ａ、多個溫度感測器40以及一訊號處理模組50，設於各工具機10的訊號處理模組50透過網際網路與該雲端運算單元100訊號連接，其中：As shown in the preferred embodiments shown in Figures 2 to 7, the present invention provides a spindle thermal temperature rise measurement remote end temperature rise mold repair compensation system to implement the spindle thermal temperature rise measurement remote end as shown in Figure 1 Temperature rise mold repair compensation optimization method; please refer to Figures 2 to 4 and Figure 7. The system includes a
請參看圖3至圖6所示，各工具機10可以是X軸、Y軸的工具機或多軸工具機，在本較佳實施例中是設有三部分別具有X軸、Y軸、Z軸、A軸以及C軸且型號相同的五軸工具機，相同型號的工具機10更適用於相同的補償模型。各工具機10設有一底座11，於各底座上設有一個可沿X軸、Y軸移動的滑座12，於各滑座12的頂部設有一可沿A軸擺動的搖擺座13，於各搖擺座13的頂部設有一可沿C軸旋轉的平台14，於各底座11後側的頂部設有一立柱15，於各立柱15的前面結合可沿Z軸移動的刀頭16，各刀頭16位於各平台14的正上方，於各刀頭16設有一主軸17，於各主軸17的底部安裝一刀把171，於各工具機10還設有一控制器18，用於數值控制各滑座12、各搖擺座13、各平台14各刀頭16以及各主軸17的動作。Please refer to FIGS. 3 to 6 . Each
安裝於各工具機10的多軸光學檢測裝置Ａ包括一球形透鏡裝置20以及一感測頭模組30，各球形透鏡裝置20設有一插桿21，各插桿21是直桿體並且豎直地***結合於各工具機10的刀把171，於各插桿21底部的自由端形成一球形透鏡22，各球形透鏡裝置20配合各感測頭模組30組成一多軸光學檢測裝置Ａ。各感測頭模組30設有一固定座31，用於固定在該工具機10的平台14上，在本較佳實施例中各固定座31是磁力座並以磁吸的方式結合固定於各平台14上，於各固定座31的頂部設有一環繞設置的支架32，於各支架32設有一光學非接觸式的感測器組33，各感測器組33是在各支架32對應X軸方向的相反兩側設有一第一雷射頭331與一第一光點位移感測器333，於各支架32對應Y軸方向的相反兩側設有一第二雷射頭332與一第二光點位移感測器334，於各第一雷射頭331與各第一光點位移感測器333連線與各第二雷射頭332與各第二光點位移感測器334連線的交叉點形成一量測點Ｂ，各量測點Ｂ位於各感測器組33的中央。The multi-axis optical detection device A installed on each
當各工具機10將所在處的球形透鏡22移動至各感測頭模組30的量測點Ｂ，並將此座標設定為座標原點後，若該主軸17因旋轉而受熱升高溫度產生偏移，使得該球形透鏡22移動至座標原點時也產生相同程度的偏移時，由於原本從各感測頭模組30的第二雷射頭332以及第二雷射頭332分別射出穿過各球形透鏡22中心的雷射光不再穿過各球形透鏡22的中心，使得同一感測頭模組30的第一光點位移感測器333以及第二光點位移感測器334能分別偵測到穿過各球形透鏡22的兩道雷射光產生了偏離，藉由各道雷射光偏離的程度，該多軸光學檢測裝置Ａ可計算出各工具機10的主軸17與結合於該主軸17的球形透鏡22因主軸17運作產生的熱而造成的位移變化數據。When each
安裝於各工具機10的多個溫度感測器40分別是能感測溫度，並將溫度數據無線向外發送的裝置。於各溫度感測器40設有一磁吸底座41，以各磁吸底座41能將安裝於同一工具機10的多個溫度感測器40磁吸固定在該工具機10的不同位置量測溫度，於各磁吸底座41上設有一天線42，透過各天線42可將各溫度感測器40所量測到的同一工具機10不同處的溫度變化數據向外無線輸出；在本較佳實施例中，安裝於同一工具機10的多個溫度感測器40分別結合在該工具機10的立柱15、刀頭16以及主軸17的不同位置。The plurality of
在本發明的其他實施例中，可僅於一工具機10僅設有一個或數個的溫度感測器40，但至少有一個溫度感測器40安裝在該主軸17，例如僅於該主軸17安裝一個溫度感測器40，或在該主軸17、該刀頭16各設有一個以上不等數量的溫度感測器40；於同一工具機40設置的溫度感測器40越多表示取得該工具機40不同位置的溫度變化數據越多，不限於本較佳實施例設置位置的例示，甚至可設於各工具機40本地端的環境中；並且各溫度感測器40除了選用具有無線傳輸功能的溫度感測器以外，各溫度感測器40也可以是有線傳輸訊號的溫度感測器。In other embodiments of the present invention, a
請參看圖3、圖7所示，安裝於各工具機10的訊號處理模組50可安裝在該工具機10內或可拆卸地設置於該工具機10的外部。各訊號處理模組50包括一通訊模組51以及一資料擷取卡52，在本較佳實施例中該訊號處理模組50是以通訊模組51透過網際網路與該雲端運算單元100訊號連接，各資料擷取卡52是以無線的方式與其所在工具機10的各溫度感測器40訊號連接，接收各溫度感測器40量測到的溫度變化數據，各資料擷取卡52以有線或無線的方式與該感測頭模組30訊號連接，用以接收該主軸17的位移變化數據，各資料擷取卡52並與其所在工具機10的控制器18電連接。當各溫度感測器40改設為有線傳輸訊號的溫度感測器時，各工具機10的訊號處理模組50的資料擷取卡52是以有線的方式與各溫度感測器40訊號連接。Referring to FIGS. 3 and 7 , the
各訊號處理模組50能在該工具機10的主軸17旋轉運作的過程中，接收各多軸光學檢測裝置Ａ的感測頭模組30感測到的主軸17的位移變化數據，以及對應各位移變化時由各溫度感測器40接收的該工具機10各處的溫度變化數據，如此以軟體持續抓取多組位移變化數據與溫度變化數據輸入模型，例如類神經網路的模型，建置本地端可用於預測不同溫度變化時產生位移變化的溫度補償模型A1，可將溫度補償模型A1輸入各訊號處理模組50其所在工具機10的控制器18進行補償，各訊號處理模組50將其所在工具機10處訓練出的溫度補償模型A1傳輸至該雲端運算單元100進行聯盟式學習。Each
遠端的雲端運算單元100收集位於不同工具機10處訓練出的溫度補償模型A1進行聯盟式學習，收集各工具機10的溫度補償模型A1並整合、提取各溫度補償模型A1的特徵資料，例如趨勢、梯度、方程式等特性，整合所有本地端的溫度補償模型A1建立一具高強度、高預測補償精度的更新溫度補償模型A2，再將更新溫度補償模型A2傳回各訊號處理模組50，各訊號處理模組50將該更新溫度補償模型A2更新至其所在的工具機10的控制器18進行補償。The remote
由於各工具機10於本地端是在不同條件下建立模型，因此配合該雲端運算單元100參與聯盟式學習的工具機10越多，能使該雲端運算單元100進行聯盟式學習後所產生的更新溫度補償模型A2的預測結果更加強健精準，回傳至各工具機10更新校正後能提升工具機10的加工精度。此外，由於該雲端運算單元100只提取各本地端的溫度補償模型A1的特徵資料，故本地端的數據具備隱私性。Since each
當本發明以上述的系統執行該主軸熱溫升量測遠端溫升修模補償優化方法時，是執行如圖1所示的以下步驟：When the present invention uses the above-mentioned system to perform the spindle thermal temperature rise measurement remote end temperature rise mold repair compensation optimization method, the following steps are performed as shown in Figure 1:
（S01）架設多軸光學檢測裝置與溫度感測器：於兩個以上的工具機10分別架設一光學檢測裝置A以及結合一個以上的溫度感測器40，如本較佳實施例是設有三個工具機10，並於各工具機10結合多個溫度感測器40。各光學檢測裝置A的球形透鏡裝置20結合於各工具機10的主軸17，各光學檢測裝置A的感測頭模組30結合於各工具機10的平台14上，各感測頭模組30的中央設有一量測點B，並且將多個溫度感測器40可拆卸地結合於該工具機10。(S01) Set up a multi-axis optical detection device and a temperature sensor: Set up an optical detection device A and combine more than one
（S02）各工具機的主軸旋轉：各工具機10將各球形透鏡裝置20的球形透鏡22移動至各感測頭模組30的量測點B後，各工具機10的主軸17開始旋轉。(S02) Spindle rotation of each machine tool: After each
（S03）抓取位移變化與溫度變化數據：在各主軸17旋轉的過程中，該感測頭模組30量測該球形透鏡22因該主軸17旋轉升高溫度而產生的位移變化數據，各工具機10的多個溫度感測器40則量測該工具機10各部位在此期間的溫度變化數據，以軟體抓取各工具機10的位移變化數據以及溫度變化數據。(S03) Capture displacement change and temperature change data: During the rotation of each
（S04）建立本地端模型：將由各工具機10得到的多組位移變化數據與溫度變化數據輸入模型，例如類神經網路的模型，建置本地端可用於預測不同溫度變化時產生位移變化的溫度補償模型A1。(S04) Establish a local end model: Input multiple sets of displacement change data and temperature change data obtained from each
（S05）將模型傳至雲端：將各工具機10的溫度補償模型A1傳輸至一位於遠端的雲端運算單元100進行聯盟式學習。(S05) Transmit the model to the cloud: transmit the temperature compensation model A1 of each
（S06）訓練雲端模型：遠端的該雲端運算單元100收集不同工具機10訓練出的溫度補償模型A1進行聯盟式學習，整合、提取各溫度補償模型A1的特徵資料，例如趨勢、梯度、方程式等特性，建立一具高強度、高預測補償精度的更新溫度補償模型A2。(S06) Training cloud models: The remote
（S07）更新本地端模型：將該雲端運算單元100訓練好的更新溫度補償模型A2傳回各工具機10處更新。(S07) Update the local model: Send the updated temperature compensation model A2 trained by the
（S08）補償機台誤差：各工具機10以該雲端運算單元100訓練好的更新溫度補償模型A2校正、補償加工的誤差。(S08) Compensate machine errors: Each
運用本發明的方法，能於該雲端運算單元100收集不同工具機10訓練出的溫度補償模型進行聯盟式學習，由於各工具機20其所在的環境以及加工的參數或機器的狀態不同，因此配合該雲端運算單元100參與聯盟式學習的工具機10越多，能使該雲端運算單元100進行聯盟式學習後所產生的更新溫度補償模型的預測結果更加強健精準，如此將更新溫度補償模型回傳至各工具機10更新後，利用模型校正、補償工具機10加工時主軸17誤差的效果，優於各工具機10處自行訓練的本地端的溫度補償模型。Using the method of the present invention, the temperature compensation models trained by
再者，於建立本地端模型的步驟前，可重複以軟體抓取各工具機10的位移變化數據以及溫度變化數據的操作，用以將重複抓取的多組位移變化數據與溫度變化數據輸入模型進行訓練，增強各工具機10本地端的溫度補償模型A1強健性，在不同條件下的適應性，使各本地端的溫度補償模型A1的預測精度提升，再傳至雲端運算單元100進行聯盟式學習。Furthermore, before the step of establishing the local model, the software can be used to repeatedly capture the displacement change data and temperature change data of each
以上所述僅為本發明的較佳實施例而已，並非用以限定本發明主張的權利範圍，凡其它未脫離本發明所揭示的精神所完成的等效改變或修飾，均應包括在本發明的申請專利範圍內。The above descriptions are only preferred embodiments of the present invention and are not intended to limit the scope of rights claimed by the present invention. All other equivalent changes or modifications that do not depart from the spirit disclosed in the present invention shall be included in the present invention. within the scope of the patent application.
100:雲端運算單元 10:工具機 11:底座 12:滑座 13:搖擺座 14:平台 15:立柱 16:刀頭 17:主軸 171:刀把 18:控制器 20:球形透鏡裝置 21:插桿 22:球形透鏡 30:感測頭模組 31:固定座 32:支架 33:感測器組 331:第一雷射頭 332:第二雷射頭 333:第一光點位移感測器 334:第二光點位移感測器 40:溫度感測器 41:磁吸底座 42:天線 50:訊號處理模組 51:通訊模組 52:資料擷取卡 A:多軸光學檢測裝置 A1:溫度補償模型 A2:溫度補償模型 B:量測點 S01至S08:步驟 100:Cloud computing unit 10: Machine tools 11: Base 12:Sliding seat 13:Swing seat 14:Platform 15:Pillar 16: Knife head 17:Spindle 171: Knife handle 18:Controller 20: Spherical lens device 21:insert rod 22: Spherical lens 30: Sensor head module 31: Fixed seat 32:Bracket 33: Sensor group 331:The first laser head 332:Second laser head 333: First light point displacement sensor 334: Second light point displacement sensor 40:Temperature sensor 41:Magnetic base 42:antenna 50:Signal processing module 51:Communication module 52:Data capture card A:Multi-axis optical detection device A1: Temperature compensation model A2: Temperature compensation model B: Measuring point S01 to S08: Steps
圖1是本發明較佳實施例方法的步驟流程圖。 圖2是本發明較佳實施例的方塊示意圖。 圖3是本發明較佳實施例的工具機的立體圖。 圖4是本發明較佳實施例的感測頭模組配合球形透鏡裝置的側視圖。 圖5是本發明較佳實施例的感測頭模組配合球形透鏡裝置的立體圖。 圖6是本發明較佳實施例的感測頭模組的立體圖。 圖7是本發明較佳實施例的訊號處理模組的方塊圖。 Figure 1 is a step flow chart of the method according to the preferred embodiment of the present invention. Figure 2 is a block diagram of a preferred embodiment of the present invention. Figure 3 is a perspective view of the machine tool according to the preferred embodiment of the present invention. Figure 4 is a side view of the sensing head module and the spherical lens device according to the preferred embodiment of the present invention. FIG. 5 is a perspective view of the sensing head module and the spherical lens device according to the preferred embodiment of the present invention. FIG. 6 is a perspective view of the sensing head module according to the preferred embodiment of the present invention. FIG. 7 is a block diagram of a signal processing module according to a preferred embodiment of the present invention.
S01至S08:步驟 S01 to S08: Steps
Claims (8)
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