TWI665051B - Method of detecting cutter wear for machine tools - Google Patents
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Abstract
本發明用於工具機之刀具磨損之檢測方法,其包含有備具步驟、 量測步驟、計算步驟、繪製步驟、建立模型步驟及判斷步驟;其係透過工具機之夾具上貼附有一加速規,並且將該加速規所測得之訊號分別透過一僕系統、主系統進行混沌同步訊號處理,以產生動態誤差訊號後,運用上述動態誤差繪製動態誤差之各狀態重心點分布圖,並且依據各刀具磨損情形之特徵製作成物元模型,以供後續運轉時所產生之重心點分布圖能與該物元模型進行比對,即可判斷出該刀具之狀態;是以,如此只需透過單一加速規感測器,即可減少計算量及快速分析出結果,達到良好之準確率,以及有效降低檢測所需之成本功效。 The method for detecting tool wear of a machine tool according to the present invention includes a preparation step, Measurement steps, calculation steps, drawing steps, model building steps, and judgment steps; it is through an acceleration gauge attached to the fixture of the machine tool, and the signals measured by the acceleration gauge are performed through a slave system and the main system, respectively. Chaotic synchronization signal processing to generate a dynamic error signal, use the above dynamic error to draw the distribution map of the center of gravity points of each state of the dynamic error, and create a matter-element model based on the characteristics of each tool wear situation for the center of gravity generated during subsequent operations The point distribution map can be compared with the matter element model to determine the status of the tool; therefore, only a single accelerometer sensor can be used to reduce the calculation amount and quickly analyze the results to achieve a good result. Accuracy, and the cost-effectiveness required to effectively reduce detection.
Description
本發明是有關於一種檢測方法,特別是一種用於工具機之刀具磨損之檢測方法。 The invention relates to a detection method, in particular to a method for detecting tool wear of a machine tool.
工具機是一種切削工件的自動化工具,在長時間的運轉狀態下,用於切削之刀具的損壞磨損是無可避免的,而當刀具磨損後,會導致刀具切削面與工具之接觸面增加,除了使阻力增加外,同時也會造成工件成品將不符合原始設計之規格,導致報廢品的產生;而為了降低此種狀況,一般主要是透過作業人員以人工方式檢視加工成品,若發現成品不符合規格時,將可判斷出目前刀具已經磨損,進而更換新的刀具。 A machine tool is an automated tool for cutting workpieces. Under long-term operating conditions, the damage and wear of cutting tools is unavoidable. When the tool is worn, the contact surface between the cutting surface and the tool will increase. In addition to increasing the resistance, at the same time, the finished product will not meet the original design specifications, leading to the generation of scrap products. In order to reduce this situation, generally, the finished product is mainly inspected by the operator manually. When it meets the specifications, it can be judged that the current tool is worn, and then a new tool is replaced.
然而,透過人力隨時檢視成品的作法,不僅提高人力成本,且若當人員未即時檢出不良品時,將造成許多不必要的浪費,以及成本提高,實有需改善,因此,如果能即時自動偵測、監控刀具磨損情形,將可有效降低不良品產生,同時也可以降低監控所需之人力成本,進而提高工具機之效率與生產良率,故如何讓工具機之刀具磨損能透過即時偵測而得知刀具磨損情形,且能快速、正確診斷刀具磨損程度,為眾所努力之目標。 However, the practice of inspecting finished products at any time through human labor not only increases labor costs, but also causes unnecessary waste when personnel do not detect defective products in real time, and costs increase, and there is a need for improvement. Therefore, if the Detecting and monitoring tool wear can effectively reduce the occurrence of defective products, and can also reduce the labor costs required for monitoring, thereby improving the efficiency and production yield of the machine tool. Therefore, how to make the tool wear of the machine tool detect in real time It is the goal of everyone's efforts to know the tool wear situation and quickly and correctly diagnose the degree of tool wear.
因此,本發明之目的,是在提供一種用於工具機之刀具磨損之檢測方法,其僅需使用單一感測器進行監測,即可快速分析出結果,達到良好之準確率,並降低監測所需之成本。 Therefore, an object of the present invention is to provide a method for detecting tool wear of a machine tool, which only needs to use a single sensor for monitoring, can quickly analyze the results, achieve a good accuracy rate, and reduce the monitoring facility. Required cost.
於是,本發明用於工具機之刀具磨損之檢測方法,其包含有備具步驟、量測步驟、計算步驟、繪製步驟、建立模型步驟及判斷步驟;其中,該備具步驟,係於該夾具上貼附有一加速規,且該加速規內可分設有一主系統與一僕系統;另,該量測步驟則利用該加速規針對該夾具上之刀具振動進行量測,使該主系統可接收該加速規偵測該主軸初始轉動產生之初始振動訊號,以及該刀具切削第一刀所產生之車削振動訊號,至於該僕系統則可接收該加速規偵測該主軸持續轉動之轉動振動訊號,以及該刀具持續切削產生之切削振動訊號;另,該計算步驟具有一與該加速規訊號連接之處理裝置,該處理裝置可將輸入之該初始振動訊號、該車削振動訊號、該轉動振動訊號及該切削振動訊號等加以計算,採分數階混沌自我同步方式而陸續得到一動態誤差訊號,且針對該每一動態誤差訊號狀態之重心點予以標示出後,再將該每一動態誤差訊號狀態之重心點陸續顯示,而形成該每一動態誤差狀態之重心點分佈圖形(即繪製步驟),而後將前述該重心點分佈圖形建立一物元模型後,再備具不同刀具型態架設,且重覆前述該量測步驟、該計算步驟及該繪製步驟,以建立不同之物元模型,而前述該等物元模型可儲存於該處理裝置中(建立模型步驟);最後,該判斷步驟備具另一刀具於該工具機上進行切削處理,前述該刀具經該量測步驟、該計算步驟及該繪製步驟等,而得到一重心點分佈圖形,且該重心點分佈圖形再與該等物元模型 於該處理裝置進行比對,以判別該刀具使用狀態;是以,如此只需透過單一加速規感測器,即可減少計算量及快速分析出結果,達到良好之準確率,以及有效降低檢測所需之成本功效。 Therefore, the method for detecting tool wear of a machine tool according to the present invention includes a preparation step, a measurement step, a calculation step, a drawing step, a model creation step, and a judgment step; wherein the preparation step is tied to the fixture An accelerometer is attached to the accelerometer, and the accelerometer can be divided into a main system and a slave system. In addition, the measurement step uses the accelerometer to measure the vibration of the tool on the fixture, so that the main system can be used. Receive the initial vibration signal generated by the acceleration gauge to detect the initial rotation of the spindle, and the turning vibration signal generated by the tool when cutting the first cutter; as for the slave system, it can receive the rotation vibration signal that the acceleration gauge detects the continuous rotation of the spindle. And the cutting vibration signal generated by the tool's continuous cutting; in addition, the calculation step has a processing device connected to the acceleration gauge signal, and the processing device can input the initial vibration signal, the turning vibration signal, and the rotation vibration signal. And the cutting vibration signal are calculated, and a fractional-order chaotic self-synchronization method is used to successively obtain a dynamic error signal. After the center of gravity points of each dynamic error signal state are marked, the center of gravity points of each dynamic error signal state are successively displayed to form a distribution pattern of the center of gravity points of each dynamic error state (that is, a drawing step), and then After establishing a matter-element model of the aforementioned center-of-gravity point distribution pattern, different tool types are erected, and the aforementioned measurement steps, calculation steps, and drawing steps are repeated to establish different matter-element models. The iso-element model can be stored in the processing device (model establishment step); finally, the judgment step is provided with another tool for cutting processing on the machine, and the aforementioned tool undergoes the measurement step, the calculation step and the Drawing steps, etc. to obtain a center-of-gravity point distribution pattern, and the center-of-gravity point distribution pattern is then combined with the matter element models Compare with the processing device to determine the use status of the tool; therefore, only a single accelerometer sensor can be used to reduce the amount of calculation and quickly analyze the results, achieve good accuracy, and effectively reduce detection Required cost effectiveness.
圖1是本發明一較佳實施例之流程方塊圖。 FIG. 1 is a flow block diagram of a preferred embodiment of the present invention.
圖2本發明一較佳實施例之Chen-Lee混沌系統二維圖。 FIG. 2 is a two-dimensional diagram of a Chen-Lee chaotic system according to a preferred embodiment of the present invention.
圖3本發明一較佳實施例之Chen-Lee混沌系統三維圖。 FIG. 3 is a three-dimensional view of a Chen-Lee chaotic system according to a preferred embodiment of the present invention.
圖4本發明一較佳實施例之各狀態之經典域及節域圖。 FIG. 4 is a classic domain and node domain diagram of each state of a preferred embodiment of the present invention.
圖5本發明一較佳實施例之誤差值e1變化量。 FIG. 5 shows the variation of the error value e1 in a preferred embodiment of the present invention.
圖6本發明一較佳實施例之差值e2變化量。 FIG. 6 shows a variation of the difference e2 of a preferred embodiment of the present invention.
圖7本發明一較佳實施例之分數階(0.1階)各狀態動態軌跡圖。 FIG. 7 is a dynamic trajectory diagram of each state of a fractional order (order 0.1) according to a preferred embodiment of the present invention.
圖8本發明一較佳實施例之分數階(0.2階)各狀態動態軌跡圖。 FIG. 8 is a dynamic trajectory diagram of each state of a fractional order (0.2 order) according to a preferred embodiment of the present invention.
圖9本發明一較佳實施例之分數階(0.3階)各狀態動態軌跡圖。 FIG. 9 is a dynamic trajectory diagram of each state of a fractional order (0.3 order) according to a preferred embodiment of the present invention.
圖10本發明一較佳實施例之分數階(0.4階)各狀態動態軌跡圖。 FIG. 10 is a dynamic trajectory diagram of each state of a fractional order (0.4 order) according to a preferred embodiment of the present invention.
圖11本發明一較佳實施例之分數階(0.5階)各狀態動態軌跡圖。 FIG. 11 is a dynamic trajectory diagram of each state of a fractional order (0.5 order) according to a preferred embodiment of the present invention.
圖12本發明一較佳實施例之分數階(0.6階)各狀態動態軌跡圖。 FIG. 12 is a dynamic trajectory diagram of each state of a fractional order (order 0.6) according to a preferred embodiment of the present invention.
圖13本發明一較佳實施例之分數階(0.7階)各狀態動態軌跡圖。 FIG. 13 is a dynamic trajectory diagram of each state of a fractional order (0.7 order) according to a preferred embodiment of the present invention.
圖14本發明一較佳實施例之分數階(0.8階)各狀態動態軌跡圖。 FIG. 14 is a dynamic trajectory diagram of each state of a fractional order (0.8 order) according to a preferred embodiment of the present invention.
圖15本發明一較佳實施例之分數階(0.9階)各狀態動態軌跡圖。 FIG. 15 is a dynamic trajectory diagram of each state of a fractional order (order 0.9) according to a preferred embodiment of the present invention.
圖16本發明一較佳實施例之整數階各狀態動態軌跡圖。 FIG. 16 is a dynamic trajectory diagram of each state of an integer order according to a preferred embodiment of the present invention.
圖17狀態監測系統辦別訊號為正常狀態顯示圖。 Fig. 17 shows the signal of the status monitoring system as normal.
圖18狀態監測系統辦別訊號為輕微磨損顯示圖。 Figure 18 shows the signal of the condition monitoring system to show a slight wear.
圖19狀態監測系統辦別訊號為中度磨損狀態顯示圖。 Figure 19 shows the signal of the state monitoring system showing moderate wear.
圖20狀態監測系統辦別訊號為重度磨損狀態顯示圖。 Figure 20 shows the signal of the state monitoring system for severe wear.
有關本發明之前述及其他技術內容、特點與功效,在以下配合參考圖式之較佳實施例的詳細說明中,將可清楚的明白。 The foregoing and other technical contents, features, and effects of the present invention will be clearly understood in the following detailed description of the preferred embodiments with reference to the accompanying drawings.
參閱圖1,本發明的一較佳實施例,用於工具機之刀具磨損之檢測方法,其用來偵測一工具機上之刀具磨損狀態,而該工具機具有一可轉動之主軸,一受該主轉轉動之夾具,以及一被該夾具夾持之刀具,該檢測方法依序包含有有備具步驟、量測步驟、計算步驟、繪製步驟、建立模型步驟及判斷步驟;其中,該備具步驟於該夾具上貼附有一加速規(Accelerometer),例如為三軸加速規,且該加速規內可分設有一主系統與一僕系統,而本發明中所謂之主系統與僕系統是運用混沌理論進行運算。 Referring to FIG. 1, a preferred embodiment of the present invention is a method for detecting tool wear on a machine tool, which is used to detect a tool wear condition on a machine tool, and the machine tool has a rotatable spindle, The fixture rotated by the main rotation, and a tool held by the fixture, the detection method sequentially includes a preparation step, a measurement step, a calculation step, a drawing step, a model building step, and a judgment step. Among them, the An accelerometer, such as a three-axis accelerometer, is attached to the fixture step. The accelerometer can be divided into a master system and a slave system. The so-called master system and slave system in the present invention It uses chaos theory to perform calculations.
仍續前述,該量測步驟利用該加速規針對該夾具上之刀具振動進行量測,而該主系統可接收該加速規偵測該主軸初始轉動產生之初始振動訊號,以及該刀具切削第一刀所產生之車削振動訊號(即為),至於該僕系統則可接收該加速規偵測該主軸持續轉動之轉動振動訊號,以及該刀具持續切削產生之切削振動訊號。 Continuing the foregoing, the measuring step uses the acceleration gauge to measure the vibration of the tool on the fixture, and the main system can receive the initial vibration signal generated by the acceleration gauge to detect the initial rotation of the spindle, and the tool cutting first The turning vibration signal (that is,) generated by the tool, and the slave system can receive the turning vibration signal that the acceleration gauge detects the continuous rotation of the spindle, and the cutting vibration signal generated by the tool continuously cutting.
仍續前述,該計算步驟其具有一與該加速規訊號連接之處理裝置,該處理裝置可將輸入之該初始振動訊號、該車削振動訊號、該轉動振動訊號及該切削振動訊號等加以計算,採分數階混沌自我同步方式而陸續得到一動態誤差訊號,且針對該每一動態誤差訊號狀態之重心 點予以標示出;另,該繪製步驟為該每一動態誤差訊號狀態之重心點陸續顯示,而形成該每一動態誤差狀態之重心點分佈圖形(也稱為動態軌跡圖)。 Continuing the foregoing, the calculation step has a processing device connected to the acceleration gauge signal, and the processing device can calculate the input initial vibration signal, the turning vibration signal, the rotation vibration signal, the cutting vibration signal, etc., A fractional-order chaotic self-synchronization method is adopted to successively obtain a dynamic error signal, and the center of gravity for each dynamic error signal state The points are marked; in addition, the drawing step is to successively display the center of gravity points of each dynamic error signal state, and form a center of gravity point distribution pattern (also referred to as a dynamic trajectory diagram) of each dynamic error state.
仍續前述,建立模型步驟系將前述該重心點分佈圖形建立一物元模型(為特定狀態之動態軌跡圖)後,再備具不同刀具型態架設,且重覆前述該量測步驟、該計算步驟及該繪製步驟,以建立不同之物元模型,而前述該等物元模型可儲存於該處理裝置中;另,該判斷步驟則備具另一刀具於該工具機上進行切削處理,前述該刀具經該量測步驟、該計算步驟及該繪製步驟等,而得到一重心點分佈圖形,且該重心點分佈圖形再與該等物元模型於該處理裝置內進行比對,以判別該刀具使用狀態。 Continuing the foregoing, the step of establishing a model is to establish a matter-element model (a dynamic trajectory map of a specific state) of the aforementioned center-of-gravity point distribution pattern, and then prepare different tool types for erection, and repeat the aforementioned measurement steps, The calculation step and the drawing step to establish different matter-element models, and the aforementioned matter-element models can be stored in the processing device; in addition, the judgment step is provided with another tool for cutting processing on the machine tool, The aforementioned tool passes the measurement step, the calculation step, the drawing step, etc. to obtain a center-of-gravity point distribution pattern, and the center-of-gravity point distribution pattern is compared with the matter-element models in the processing device to determine The tool usage status.
因此,而本發明實際運作時,使用加速規擷取振動訊號代入主、僕系統,其中,主系統(MS)為一刀具健康度理想之振動訊號,僕系統(SS)為即時擷取之振動訊號,經由主、僕系統相減可得出混沌動態誤差及其混沌吸引子,主僕混沌系統如式1所示:
其中為理想刀具狀態之振動訊號,經由混沌系統運算後之狀態向量、為即時擷取之振動訊號,經由混沌系統運算後之狀態向量、為一M×N矩陣、F(X)及F(Y)為非線性矩陣、u為非線性控制項,本專利主要取主、僕系統動態誤差作為刀具磨耗的辨識特徵,故u令為0,並將式2之混沌系統動態方程式轉換為主、僕混沌系統型式可表示
為式3:
式3中,α,β及γ為Chen-Lee系統之系統參數,經由Lyapunov exponent驗證,滿足α>0、β<0、0<α<-(β+γ)之條件,該系統便具有混沌吸引子之特性,而本實施例中將健康狀況理想之訊號代入主系統,並且僕系統代入即時擷取出之振動訊號,個別經由混沌計算後,再經由主僕混沌系統所產生之結果相減,及可得出主僕混沌動態誤差及混沌吸引子,藉由該兩項結果即可作為分類之特徵依據;而本發明實施例舉例上述參數α,β,γ為(5,-10,-3.8)時,且x,y,z初始條件為0.001時,系統產生混沌現象,如圖2、圖3,而其混沌系統主架構,X R N ,Y R N ,其中X=[x 1,x 2,x 3] T ,Y=[y 1,y 2,y 3] T ,U=[u 1,u 2,u 3] T ,其主系統與僕系統為一個3×3的系統矩陣,其主系統X如式(4)、僕系統Y如式(5):
同時本發明中為了實現僕系統自我追蹤主系統同步動態誤差,因此設計控制項u 1=u 2=u 3=0,且定義誤差狀態e=[e 1,e 2,e 3] T ,其中e 1=x 1-y 1,e 2=x 2-y 2,e 3=x 3-y 3,誤差系統經過整理後可以表示為式(5):
其參數需滿足a>0,b<0,c<0與0<a<-(b+c)之條件,則系統誤差動態方程有奇異吸子之特性。 Its parameters need to meet the conditions of a > 0, b <0, c <0 and 0 < a <-( b + c ), then the system error dynamic equation has the characteristics of singular attractors.
其參數需滿足a>0,b<0,c<0與0<a<-(b+c)之條件,則系統誤差動態方程有奇異吸子之特性。 Its parameters need to meet the conditions of a > 0, b <0, c <0 and 0 < a <-( b + c ), then the system error dynamic equation has the characteristics of singular attractors.
另外,本發明中該分數階混沌自我同步動態誤差產生動態誤差,為了能夠更精細的表示刀具振動訊號各狀態特徵,其用分數階寫成式(6),其中m為任意實數,e為動態誤差,γ可以選擇所需階數。 In addition, in the present invention, the fractional-order chaotic self-synchronized dynamic error generates a dynamic error. In order to more accurately represent the characteristics of each state of the tool vibration signal, it is written as a formula (6) in fractional order, where m is an arbitrary real number and e is a dynamic error. , Γ can choose the required order.
q為分數階階數,其中q=(1-γ)且滿足0<q<1,Γ(˙)為Gamma函數,為了使式(5)產生混沌吸引子,而將式改寫為式(7),
系統參數a',b',c'為非零常數,相位軌跡展示了分數階為q時的各種動態行為,為了使式(7)實現自我同步追蹤,其動態誤差設定為:e 1[i]=x[i]-y[i],e 2[i]=x[i+1]-y[i+1],e 3[i]=x[i+2]-y[i+2],i=1,2,3,...,n-2,則Φ1[i],Φ2[i],Φ3[i]可定義為式(8)
最後,該建立物元模型,則是採用可拓理論作為刀具損壞程度之判別法,藉由判斷經典域關聯函數大小,對照設定的物元模型,可拓理論之物元模型建立可表示為式(9)
其中R代表為事物、N為自行定義的事物名稱、C為事物的特徵、V為事物的量值,本發明使用分數階混沌系統動態誤差所產生
之混沌吸引子相平面座標系,作為建立可拓理論物元模型的量值,且而本實施例中,設定的物元模型有正常狀態、輕微磨損、中度磨損、重度磨損等四種進行判斷,其物元模型如下表:
而當物元模型建立完成後,即定義出各個狀態之分數階混沌吸引子相平面座標分部狀況,借由物元模型之相平面座標系可定義出可拓集合中的經典域及節域如圖4,並經由式10及式11運算即可得出介於-1至1之可拓關聯度。 After the matter-element model is established, the fractional chaotic attractor phase plane coordinate divisions of each state are defined. The phase plane coordinate system of the matter-element model can define the classical domain and node domain in the extension set. As shown in Fig. 4, the extension correlation degree between -1 and 1 can be obtained through the operation of Equations 10 and 11.
上圖中,藍色框線為節域、綠色框線為重度磨耗經典域、紅色框線為中度磨耗經典域、橙色框線為為輕度磨耗經典域及黃色框線為狀態良好經典域,節域及經典域定義完成後,後續可代入其它振動訊號,經由混沌分析後取混沌吸引子,利用式10及式11計算與各狀態經 典域之關聯度值,若關聯度大於0即可定義為該狀態,反之則不為,如此,將可判別狀態符合該程度最佳之特徵,診斷其關聯函數所對照到的刀具狀態。 In the figure above, the blue frame is the nodal field, the green frame is the heavily worn classic domain, the red frame is the moderately worn classic domain, the orange frame is the lightly worn classic domain, and the yellow frame is the classic domain in good condition. After the definition of the node domain and the classical domain is completed, other vibration signals can be subsequently substituted. After chaos analysis, the chaotic attractor is taken. The equations 10 and 11 are used to calculate the states of each state. The correlation degree value of the canonical domain can be defined as the state if the correlation degree is greater than 0, otherwise it is not. In this case, it can be determined that the state meets the characteristics of the best degree, and the state of the tool compared to the correlation function is diagnosed.
因此,使用時,即經由備具步驟、量測步驟、計算步驟及建立模型步驟,以分別換上不同狀態之刀具後,本發明是以正常狀態(normal)、輕度磨損(slight wear)、中度磨損(moderate wear)以及重度磨損(severe wear)四種狀態建立物元模型做為比對之標的,因此換上刀具後利用加速規所測得知振動狀況,即該主系統訊號來源則為利用主軸開電靜止與刀具車削第一刀之振動訊號,僕系統訊號來源為當前量測之主軸與刀具訊號運轉時之振動訊號後,而輸入後至上述算式後,所產生e1,e2,e3的動差誤差軌跡圖,根據所定的四種狀態:正常狀態(normal)、輕度磨損(slight wear)、中度磨損(moderate wear)以及重度磨損(severe wear),量測該狀態下切削狀態時之訊號,透過動態誤差e1,e2繪製其動態軌跡圖,觀察其差異性,以此建立可拓理論之物元模型,作為判斷該訊號之狀態依據,最後根據不同的刀具狀態連續做切割動作,並且擷取其連續信號,最後可以得到如圖5與圖6之誤差值e1.e2變化量。 Therefore, when in use, that is, through the equipment step, measurement step, calculation step, and model building step to change the tools in different states, the present invention is in a normal state, light wear, The matter-element model is established as the target of comparison in the four states of moderate wear and severe wear. Therefore, after the tool is replaced, the vibration condition is measured by the acceleration gauge, that is, the source of the signal of the main system is is electrically opened by the spindle and the tool rest turning first knife vibration signal, the signal source for the slave system when the motion signal of the current measurement of the tool spindle and the operation signal, and to enter the above equation, the generated e 1, e The trajectory diagram of the differential error of 2, e 3, according to the four states specified: normal, slight wear, moderate wear, and severe wear. when the state signal is a state of cutting through the dynamic error e 1, e 2 in FIG plotted dynamic trajectory observed differences, in order to establish matter of extension theory, as the basis for determining the state of the signal, and finally According to the state of different tools to do continuous cutting action, and continuously capturing signal, and finally an error can be obtained as shown in FIG. 5 and 6 e1.e2 value of the amount of change.
配合參閱圖7至圖17,使用分數階與整數階混沌系統處理刀具振動訊號之動態誤差軌跡圖,在0.7階至整數階可以發現較為線性變化,而0.1階至0.6階過於發散,因此首先排除0.1階至0.6階,再計算0.7階至整數階之動態誤差特徵量,並建立每一階數之物元模型,最後比較每一階數準確度,在與採用小波包分析、與離散傅立葉轉換方式進行比較,辦別故障診斷結果如下表:
仍續前述,故實驗時,可先安裝各狀態之刀具,並以相同速率與進給量運轉,擷取振動訊號建立各狀態之資料庫,並根據資料庫繪製混沌動態誤差軌跡圖,建立各狀態之可拓物元模型及各狀態可拓物元模型表:
建構好資料庫後,本發明使用建立智慧型刀具狀態監測系統之人機介面,並透過人機介面可以令使用者得知目前刀具振動訊號及 其狀態,於圖17至圖20可以看出系統能準確判斷其刀具狀態,並依所建立燈泡顯示,每個狀態都是運用各狀態之物元模型表的物元模型計算完可拓關聯函數後所得知結果,並且存取每次擷取刀具振動訊號給使用者判斷該工具機之狀態;是以,如此只需透過單一加速規感測器,即可減少計算量及快速分析出結果,達到良好之準確率,以及有效降低檢測所需之成本功效。 After the database is constructed, the present invention uses a human-machine interface for establishing a smart tool condition monitoring system, and the user can know the current tool vibration signal and For the state, it can be seen in Fig. 17 to Fig. 20 that the system can accurately judge the tool state, and according to the established light bulb display, each state is calculated by using the matter-element model of each state's matter-element model table to calculate the extension correlation function. The results are obtained afterwards, and each time the vibration signal of the tool is retrieved, the user can judge the state of the machine tool. Therefore, only a single accelerometer sensor can be used to reduce the calculation amount and quickly analyze the results. Achieve good accuracy, and effectively reduce the cost-effectiveness required for detection.
歸納前述,本發明用於工具機之刀具磨損之檢測方法,其包含有備具步驟、量測步驟、計算步驟、繪製步驟、建立模型步驟及判斷步驟;其係透過工具機之夾具上貼附有一加速規,並且將該加速規所測得之訊號分別透過一僕系統、主系統進行混沌同步訊號處理,以產生動態誤差訊號後,運用上述動態誤差繪製動態誤差之各狀態重心點分布圖,並且依據各刀具磨損情形之特徵製作成物元模型,以供後續運轉時所產生之重心點分布圖能與該物元模型進行比對,即可判斷出該刀具之狀態;是以,如此只需透過單一加速規感測器,即可減少計算量及快速分析出結果,達到良好之準確率,以及有效降低檢測所需之成本功效。 To sum up, the method for detecting tool wear of a machine tool according to the present invention includes a preparation step, a measurement step, a calculation step, a drawing step, a model building step, and a judgment step; it is affixed through the fixture of the machine tool. There is an accelerometer, and the signals measured by the accelerometer are processed through a slave system and a master system respectively to generate chaotic synchronization signals. After generating a dynamic error signal, use the above dynamic error to draw the distribution map of the center of gravity points of each state of the dynamic error. And based on the characteristics of the wear conditions of each tool, a matter-element model is created, so that the center-of-gravity point distribution map generated during subsequent operations can be compared with the matter-element model to determine the state of the tool; so, so only By using a single accelerometer sensor, the calculation amount can be reduced and the results can be quickly analyzed to achieve good accuracy and effectively reduce the cost-effectiveness required for detection.
惟以上所述者,僅為說明本發明之較佳實施例而已,當不能以此限定本發明實施之範圍,即大凡依本發明申請專利範圍及發明說明書內容所作之簡單的等效變化與修飾,皆應仍屬本發明專利涵蓋之範圍內。 However, the above are only for describing the preferred embodiments of the present invention. When the scope of implementation of the present invention cannot be limited by this, that is, the simple equivalent changes and modifications made according to the scope of the patent application and the content of the invention specification of the present invention , All should still fall within the scope of the invention patent.
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