TWI759720B

TWI759720B - Monitoring device, monitoring method, servo amplifier, industrial controller, and machine tool

Info

Publication number: TWI759720B
Application number: TW109113040A
Authority: TW
Inventors: 周広斌; 中村明博; 出口見多; 金子悟; 岩路善尚
Original assignee: 日商日立產機系統股份有限公司
Priority date: 2019-04-18
Filing date: 2020-04-17
Publication date: 2022-04-01
Also published as: JP7194069B2; TW202040918A; JP2020178454A; WO2020213265A1

Abstract

本發明之課題在於提供一種基於複數個驅動馬達之電流資訊而感度良好地判定機器狀態之異常之監視裝置及監視方法。監視裝置具備：電流感測器，其對複數個驅動馬達之各者檢測二相之電流資訊；馬達資訊運算部，其根據電流資訊，運算對應之驅動馬達之轉矩電流或旋轉速度；特徵量運算部，其運算複數個驅動馬達中之與轉矩電流或旋轉速度相關之特徵量；狀態推定部，其基於複數個驅動馬達中處於相關關係之驅動馬達之特徵量，推定機器狀態；資料記憶部，其記錄基準值資料；及異常判定部，其基於所推定之機器狀態與基準值資料，判定異常狀態。An object of the present invention is to provide a monitoring device and a monitoring method for determining an abnormality of a machine state with good sensitivity based on current information of a plurality of drive motors. The monitoring device includes: a current sensor that detects two-phase current information for each of the plurality of drive motors; a motor information calculation unit that calculates the torque current or rotational speed of the corresponding drive motor based on the current information; a characteristic quantity A calculation unit that calculates feature quantities related to torque current or rotational speed among the plurality of drive motors; a state estimation unit that estimates a machine state based on the feature quantities of the drive motors that are in a correlated relationship among the plurality of drive motors; Data memory A part that records reference value data; and an abnormality determination part that determines an abnormal state based on the estimated machine state and the reference value data.

Description

監視裝置、監視方法、伺服放大器、產業用控制器及工具機Monitoring device, monitoring method, servo amplifier, industrial controller, and machine tool

本發明係關於一種監視之技術，尤其關於監視工具機等之機器狀態之裝置。 The present invention relates to a monitoring technology, especially to a device for monitoring the state of a machine tool or the like.

綜合加工機等工具機具有工具自動更換功能，可結合目的實施於1台中進行銑削、搪孔、開孔、攻絲等異種機加工之數值控制。又，工具機因於工具庫中收納多個切削工具，且可根據電腦數值控制之指令自動地進行加工，故用於各種零件加工。 Machine tools such as comprehensive processing machines have the function of automatic tool replacement, and can implement numerical control of different types of machining such as milling, boring, drilling, tapping, etc. in one set according to the purpose. In addition, the machine tool is used for processing various parts because a plurality of cutting tools are stored in the tool magazine, and processing can be performed automatically according to the instructions of the computer numerical control.

然而，工具機中使用之工具存在隨著加工使用時間經過，刀尖磨耗，切削阻力增加，最終導致破損之情形。 However, the tool used in the machine tool has a situation in which the tool tip wears and the cutting resistance increases with the passage of processing time, which eventually leads to breakage.

於專利文獻1中揭示有如下技術，即，推定、算出作用於主軸馬達或Z軸(進給軸)馬達之電流之擾動轉矩ys與yz並記錄於資料表中，繼而，對ys與yz求出現狀推定值與移動變動閾值，將其等進行比較，判定工具之異常。 Patent Document 1 discloses a technique of estimating and calculating the disturbance torques ys and yz of the current acting on the spindle motor or the Z-axis (feed axis) motor, and recording them in a data table, and then comparing ys and yz. The estimated status value and the movement fluctuation threshold value are obtained, and they are compared to determine the abnormality of the tool.

[先前技術文獻] [Prior Art Literature] [專利文獻] [Patent Literature]

[專利文獻1] 日本專利特開2003-326438 [Patent Document 1] Japanese Patent Laid-Open No. 2003-326438

於專利文獻1之段落號0033中記載有「基於主軸馬達之速度信號與對主軸馬達之轉矩指令值，推定作用於主軸馬達之擾動轉矩ys」、及「基於進給軸馬達之速度信號與進給軸馬達之轉矩指令值，推定作用於進給軸馬達之擾動轉矩yz」。 Paragraph No. 0033 of Patent Document 1 describes "estimating disturbance torque ys acting on the spindle motor based on the speed signal of the spindle motor and the torque command value to the spindle motor" and "based on the speed signal of the feed axis motor". Based on the torque command value of the feed axis motor, the disturbance torque yz acting on the feed axis motor is estimated.

即，判定工具之異常需要驅動馬達之速度信號或轉矩指令值之類馬達控制資訊。因此，於專利文獻1中，因必須以某些構件提供馬達控制資訊，故於現有裝置之情形時，存在產生追加佈線等作業之課題。因此，要求基於馬達之電流資訊進行監視之技術，以避免追加佈線等，能夠使用現有裝置。 That is, to determine the abnormality of the tool, motor control information such as a speed signal of the drive motor or a torque command value is required. Therefore, in Patent Document 1, since some components must be used to provide motor control information, in the case of the conventional device, there is a problem that operations such as additional wiring are generated. Therefore, a technique for monitoring based on the current information of the motor is required to avoid additional wiring and the like, and to allow the use of existing devices.

又，於工具機中，自大徑工具至小徑工具以相同之構成(驅動馬達)實施加工。於大徑工具之加工之情形時，加工負載較大，驅動馬達之電流亦較大。另一方面，於小徑工具之加工之情形時，加工負載較小，驅動馬達之電流亦較小。 Moreover, in the machine tool, machining is performed with the same structure (drive motor) from the large diameter tool to the small diameter tool. In the case of machining a large diameter tool, the machining load is larger, and the current of the driving motor is also larger. On the other hand, in the case of machining small-diameter tools, the machining load is small, and the current of the driving motor is also small.

如專利文獻1所示，若對每一進給軸馬達等各馬達推定擾動轉矩，則尤其於小徑工具之加工之情形時，於驅動主軸之主軸馬達(轉軸馬達)之電流中，由加工引起之馬達電流變化變小。因此，亦淹沒於空轉(不加工)時之電流中，難以進行感度較佳之計測。 As shown in Patent Document 1, if the disturbance torque is estimated for each motor such as a feed axis motor, especially in the case of machining a small diameter tool, the electric power of the spindle motor (spindle motor) that drives the spindle is During the flow, the motor current change caused by machining becomes small. Therefore, it is also submerged in the current during idling (not processing), making it difficult to perform measurement with better sensitivity.

本發明之目的在於提供一種基於複數個驅動馬達之電流資訊，感度較佳地判定機器狀態之異常之監視裝置及監視方法。 An object of the present invention is to provide a monitoring device and a monitoring method for determining an abnormality of a machine state with better sensitivity based on current information of a plurality of driving motors.

本發明之較佳一例係一種監視裝置，其具備：電流感測器，其對複數個驅動馬達之各者，檢測二相之電流資訊；馬達資訊運算部，其根據上述電流資訊，運算對應之上述驅動馬達之轉矩電流或旋轉速度；特徵量運算部，其運算複數個上述驅動馬達中之與上述轉矩電流或上述旋轉速度相關之特徵量；狀態推定部，其基於複數個上述驅動馬達中處於相關關係中之上述驅動馬達之上述特徵量，推定機器狀態；資料記憶部，其記錄基準值資料；及異常判定部，其基於所推定之上述機器狀態與上述基準值資料，判定異常狀態。 A preferred example of the present invention is a monitoring device comprising: a current sensor for detecting two-phase current information for each of a plurality of driving motors; a motor information calculation unit for calculating corresponding current information according to the above-mentioned current information a torque current or rotational speed of the above-mentioned drive motor; a feature quantity calculation unit that calculates a feature quantity related to the above-mentioned torque current or the above-mentioned rotational speed in a plurality of the above-mentioned drive motors; a state estimation unit based on the plurality of the above-mentioned drive motors a data storage unit that records reference value data; and an abnormality determination unit that determines an abnormal state based on the estimated machine state and the reference value data .

本發明之較佳之另一例係一種監視方法，其係對複數個驅動馬達之各者，檢測二相之電流資訊，根據上述電流資訊，運算對應之上述驅動馬達之轉矩電流或旋轉速度，運算複數個驅動馬達中之與上述轉矩電流或上述旋轉速度相關之特徵量，基於複數個上述驅動馬達中處於相關關係中之上述驅動馬達之上述特徵量，推定機器狀態，基於預先記錄之基準值資料與所推定之上述機器狀態，判定異常狀態。 Another preferred embodiment of the present invention is a monitoring method, which detects two-phase current information for each of a plurality of driving motors, and calculates the torque current or rotational speed of the corresponding driving motor according to the current information, Calculate the characteristic quantity related to the above-mentioned torque current or the above-mentioned rotational speed among the plurality of drive motors, estimate the machine state based on the above-mentioned characteristic quantity of the above-mentioned drive motor in the correlation relationship among the plurality of the above-mentioned drive motors, based on the pre-recorded reference The value data and the estimated state of the above-mentioned equipment are used to determine the abnormal state.

根據本發明，可基於複數個驅動馬達之電流資訊，感度較佳地判定機器狀態之異常。 According to the present invention, based on the current information of a plurality of driving motors, the sensitivity can better determine the abnormality of the machine state.

10:馬達 10: Motor

10-1~10-N:馬達 10-1~10-N: Motor

14:旋轉軸 14: Rotary axis

16:工具 16: Tools

20:驅動裝置 20: Drive device

22:變頻器 22: Inverter

24:電流感測器 24: Current sensor

30:控制部 30: Control Department

32:指令產生部 32: Instruction generation part

33:偏差運算部 33: Deviation calculation section

34:向量控制部 34: Vector Control Department

36:dq/3Φ轉換部 36: dq/3Φ conversion part

38:3Φ/dq轉換部 38:3Φ/dq conversion section

40,150,160,170,190,210,220,230,250:監視裝置 40, 150, 160, 170, 190, 210, 220, 230, 250: Monitoring devices

41:電流感測器 41: Current sensor

42:馬達資訊運算部 42: Motor Information Calculation Department

42-1~42-N:馬達資訊運算部 42-1~42-N: Motor Information Calculation Department

44:特徵量運算部 44: Feature calculation section

45:狀態推定部 45: State Estimation Section

46:資料記憶部 46: Data Memory Department

47:異常判定部 47: Abnormal Determination Department

52:3Φ/αβ轉換器 52:3Φ/αβ Converter

54:反正切轉換器 54: Arctangent Converter

56:減法器 56: Subtractor

60:相位運算器 60: Phase Calculator

62:乘法器 62: Multiplier

64:乘法器 64: Multiplier

66:積分器 66: Integrator

68:加法器 68: Adder

70:旋轉座標轉換器 70: Rotation Coordinate Converter

72:積分器 72: Integrator

74:乘法器 74: Multiplier

101:馬達控制系統 101: Motor Control System

102:馬達控制系統 102: Motor Control System

103:馬達控制系統 103: Motor Control System

104:馬達控制系統 104: Motor Control System

105:馬達控制系統 105: Motor Control System

106:馬達驅動伺服放大器 106: Motor drive servo amplifier

107:馬達驅動伺服放大器 107: Motor drive servo amplifier

108:產業用控制器 108: Industrial Controllers

109:工具機 109: Machine Tool

180:驅動．監視裝置 180: Drive. monitoring device

240:資訊收集部 240: Information Collection Department

τ*:轉矩指令值 τ*: Torque command value

I_α,I_β:交流電流 I _α ,I _β : AC current

I_d:激磁電流檢測值 I _d : Excitation current detection value

I_q:轉矩電流檢測值 I _q : Torque current detection value

I_r1,I_r2:馬達轉矩電流 I _r1 ,I _r2 : motor torque current

I_rN:轉矩電流 I _rN : torque current

ω_1s:頻率信號 ω _1s : frequency signal

ω_rs:機械頻率 ω _rs : mechanical frequency

ω_rs1,ω_rs2:機械頻率 ω _rs1 ,ω _rs2 : mechanical frequency

I_d*:激磁電流指令值 I _d *: Excitation current command value

I_q*:轉矩電流指令值 I _q *: Torque current command value

I_r:直流量 I _r : DC amount

I_U,I_W:電流檢測值 I _U ,I _W : Current detection value

I_U1,I_W1:電流檢測值 I _U1 ,I _W1 : Current detection value

I_U2,I_W2:電流檢測值 I _U2 , I _W2 : Current detection value

I_Us:電流檢測值 I _Us : Current detection value

I_UN:電流檢測值 I _UN : Current detection value

I_WN:電流檢測值 I _WN : Current detection value

I_Ws:電流檢測值 I _Ws : Current detection value

KiPLL:積分增益 KiPLL: Integral Gain

KpPLL:比例增益 KpPLL: proportional gain

M₀:工具磨耗度之極限 M ₀ : Limit of tool wear

PLL_I:積分信號 PLL_I: Integral signal

PLL_P:比例信號 PLL_P: proportional signal

V_d*:激磁電壓指令值 V _d *: Excitation voltage command value

V_q*:轉矩電壓指令值 V _q *: Torque voltage command value

θ_i:交流電流相位角 θ _i : AC current phase angle

θ_i*:交流電流相位角檢測值 θ _i *: AC current phase angle detection value

圖1係實施例1中之馬達控制系統之方塊圖。 FIG. 1 is a block diagram of the motor control system in the first embodiment.

圖2係實施例1中之監視裝置之方塊圖。 FIG. 2 is a block diagram of the monitoring device in Embodiment 1. FIG.

圖3係實施例1中之馬達資訊運算部之方塊圖。 FIG. 3 is a block diagram of a motor information computing unit in Embodiment 1. FIG.

圖4係表示實施例1中之工具機之構成例之圖。 FIG. 4 is a diagram showing a configuration example of the machine tool in the first embodiment.

圖5係表示實施例1中之因工具磨耗導致之加工品質下降及工具破損產生之機制之圖。 FIG. 5 is a diagram showing the mechanism of the deterioration of processing quality due to tool wear and the occurrence of tool breakage in Example 1. FIG.

圖6係表示實施例1中之伴隨工具磨耗之馬達電流變化之圖。 FIG. 6 is a graph showing changes in motor current accompanying tool wear in Example 1. FIG.

圖7係實施例1中之來自馬達資訊之特徵量擷取之概略圖。 FIG. 7 is a schematic diagram of feature extraction from motor information in Embodiment 1. FIG.

圖8係實施例1中之關於根據馬達電流資訊推定工具磨耗之方法之圖。 FIG. 8 is a diagram of a method for estimating tool wear based on motor current information in Embodiment 1. FIG.

圖9係實施例1中之工具磨耗偵測例行程序之流程圖。 FIG. 9 is a flowchart of the tool wear detection routine in Example 1. FIG.

圖10係實施例2中之馬達控制系統之方塊圖。 FIG. 10 is a block diagram of the motor control system in the second embodiment.

圖11係實施例2中之監視裝置之方塊圖。 FIG. 11 is a block diagram of the monitoring device in the second embodiment.

圖12係實施例2中使用複數個加工軸馬達之情形時之特徵量擷取之概略圖。 FIG. 12 is a schematic diagram of feature value extraction when a plurality of machining axis motors are used in the second embodiment.

圖13係實施例3中之馬達控制系統之方塊圖。 FIG. 13 is a block diagram of the motor control system in the third embodiment.

圖14係實施例4中之馬達控制系統之方塊圖。 FIG. 14 is a block diagram of the motor control system in the fourth embodiment.

圖15係實施例5中之馬達控制系統之方塊圖。 FIG. 15 is a block diagram of the motor control system in the fifth embodiment.

圖16係實施例6中之馬達驅動伺服放大器之方塊圖。 FIG. 16 is a block diagram of a motor-driven servo amplifier in Embodiment 6. FIG.

圖17係實施例7中之馬達驅動伺服放大器之方塊圖。 FIG. 17 is a block diagram of a motor-driven servo amplifier in Embodiment 7. FIG.

圖18係實施例8中之產業用控制器之方塊圖。 FIG. 18 is a block diagram of the industrial controller in Embodiment 8. FIG.

圖19係實施例9中之工具機之概略圖。 FIG. 19 is a schematic view of the machine tool in the ninth embodiment.

以下，按照圖式對實施例進行說明。再者，於與各實施例對應之圖式中，相同構成物標註相同之數字編號。 Hereinafter, the embodiment will be described with reference to the drawings. Furthermore, in the drawings corresponding to the respective embodiments, the same components are marked with the same numerals.

[實施例1] [Example 1]

圖1係實施例1之驅動工具機等裝置之工具之雙軸之馬達控制系統101之方塊圖。此處之雙軸馬達係設想鑽孔加工時之加工負載中存在相關關係之主軸馬達與進給軸馬達(Z軸馬達)。 FIG. 1 is a block diagram of a two-axis motor control system 101 for driving a tool of a machine tool and the like according to the first embodiment. The dual-axis motor here is a spindle motor and a feed-axis motor (Z-axis motor) that are assumed to have a correlation in the machining load during drilling.

於圖1中，馬達控制系統101具備馬達1之10-1、馬達2之10-2、驅動裝置20、監視裝置40及電流感測器41。驅動裝置20具備變頻器22、電流感測器24及控制部30。 In FIG. 1 , the motor control system 101 includes 10 - 1 of the motor 1 , 10 - 2 of the motor 2 , a drive device 20 , a monitoring device 40 , and a current sensor 41 . The drive device 20 includes an inverter 22, a current The sensor 24 and the control unit 30 .

馬達10-1之旋轉軸14經由齒輪或滾珠螺桿等機械零件(未圖示)或直接連接地連接於工具16。又，馬達2亦直接或經由機構驅動工具16(未圖示)。各變頻器22基於各控制部30之控制，對馬達1之10-1或馬達2之10-2施加三相交流電壓。 The rotating shaft 14 of the motor 10-1 is connected to the tool 16 via a mechanical part (not shown) such as a gear or a ball screw, or directly. In addition, the motor 2 also drives the tool 16 (not shown) directly or via a mechanism. Each inverter 22 applies a three-phase AC voltage to 10-1 of the motor 1 or 10-2 of the motor 2 based on the control of each control unit 30 .

控制部30具備CPU(Central Processing Unit，中央處理單元)、DSP(Digital Signal Processor，數位信號處理器)、RAM(Random Access Memory，隨機存取記憶體)、ROM(Read Only Memory，唯讀記憶體)等作為普通電腦之硬體，且ROM中儲存有由CPU執行之控制程式、由DSP執行之微程式及各種資料等。 The control unit 30 includes a CPU (Central Processing Unit), a DSP (Digital Signal Processor), a RAM (Random Access Memory), and a ROM (Read Only Memory) ), etc. as the hardware of a common computer, and the ROM stores the control program executed by the CPU, the microprogram executed by the DSP, and various data.

於圖1中，控制部30之內部係以方塊表示由控制程式及微程式等實現之功能。即，控制部30具備指令產生部32、偏差運算部33、向量控制部34、dq/3Φ轉換部36及3Φ/dq轉換部38。 In FIG. 1 , the inside of the control unit 30 is represented by a block to represent functions realized by a control program, a microprogram, and the like. That is, the control unit 30 includes a command generation unit 32 , a deviation calculation unit 33 , a vector control unit 34 , a dq/3Φ conversion unit 36 , and a 3Φ/dq conversion unit 38 .

控制部30係藉由該等構成對馬達10進行向量控制，從而使馬達10-1之響應性提昇。 The control part 30 performs vector control of the motor 10 by these structures, and improves the responsiveness of the motor 10-1.

變頻器22對馬達10-1輸出U相、V相、W相之交流電流。電流感測器24檢測其中之二相之電流。即，於圖示之例中，檢測U相、W相之電流，並將其結果作為電流檢測值I_us、I_ws輸出。 The inverter 22 outputs U-phase, V-phase, and W-phase alternating currents to the motor 10-1. The current sensor 24 detects the current of the two phases. That is, in the example shown in the figure, the currents of the U-phase and the W-phase are detected, and the results are output as the current detection values _Ius and _Iws .

此處，設想以頻率f旋轉之旋轉座標，將該旋轉座標中正交之軸稱為d軸及q軸，將供給至馬達10-1之電流表現為該旋轉座標中之直流量。 Here, a rotation coordinate rotating at a frequency f is assumed, and the axes orthogonal to the rotation coordinate are referred to as the d-axis and the q-axis, and the current supplied to the motor 10-1 is expressed as a DC amount in the rotation coordinate.

q軸中之電流係決定馬達10-1之轉矩之電流分量，以下，將其稱為轉矩電流。又，d軸中之電流係成為馬達10-1之激磁電流之成分，以下，將其稱為激磁電流。 The current in the q-axis is the current component that determines the torque of the motor 10-1, and is hereinafter referred to as torque current. In addition, the current in the d-axis is a component of the excitation current of the motor 10-1, and is hereinafter referred to as an excitation current.

3Φ/dq轉換部38基於電流檢測值I_us、I_ws，輸出激磁電流檢測值I_d與轉矩電流檢測值I_q。指令產生部32自未圖示之上位裝置接收轉矩指令值τ*，並基於轉矩指令值τ*產生激磁電流指令值I_d*與轉矩電流指令值I_q*。 The 3Φ/dq conversion unit 38 outputs the field current detection value I _d and the torque current detection value I _q based on the current detection values I _us and I _ws . The command generation unit 32 receives the torque command value τ* from the upper device (not shown), and generates the excitation current command value I _d * and the torque current command value I _q * based on the torque command value τ*.

偏差運算部33基於電流指令值I_d*、I_q*及電流檢測值I_d、I_q，輸出偏差I_d*-I_d、I_q*-I_q。向量控制部34基於偏差I_d*-I_d、I_q*-I_q等，輸出激磁電壓指令值V_d*與轉矩電壓指令值V_q*。 The deviation calculation unit 33 outputs deviations I _d *-I _d and I _q *-I _q based on the current command values I _d * and I _q * and the current detection values I _d and I _q . The vector control unit 34 outputs the excitation voltage command value V _d * and the torque voltage command value V _q * based on the deviations I _d *-I _d , I _q *-I _q and the like.

對向量控制部34之動作更詳細地進行說明，向量控制部34係對偏差I_d*-I_d、I_q*-I_q進行比例積分控制，求出相同速度之指令值即頻率指令ω1(未圖示)。 The operation of the vector control unit 34 will be described in more detail. The vector control unit 34 performs proportional and integral control on the deviations I _d *-I _d and I _q *-I _q , and obtains the frequency command ω1 (the command value of the same speed). not shown).

進而，向量控制部34藉由將頻率指令ω1進行積分運算而求出相位指令θ1(未圖示)。進而，向量控制部34對電流指令值I_d*、I_q*構成之向量乘以馬達10-1之阻抗之向量，作為其結果，計算電壓指令值V_d*、V_q*。 Furthermore, the vector control unit 34 obtains the phase command θ1 (not shown) by integrating the frequency command ω1 . Further, the vector control unit 34 multiplies the vector of the current command values I _d * and I _q * by the vector of the impedance of the motor 10 - 1 , and as a result calculates the voltage command values V _d * and V _q *.

dq/3Φ轉換部36基於旋轉座標系統之電壓指令值V_d*、V_q*，輸出用以驅動變頻器22之PWM(Pulse Width Modulation，脈寬調變)信號。變頻器22基於所供給之PWM信號，切換所供給之直流電壓(未圖示)，對馬達10-1輸出U相、V相、W相之電壓。 The dq/3Φ conversion unit 36 outputs a PWM (Pulse Width Modulation) signal for driving the inverter 22 based on the voltage command values V _d * and V _q * of the rotating coordinate system. The inverter 22 switches the supplied DC voltage (not shown) based on the supplied PWM signal, and outputs U-phase, V-phase, and W-phase voltages to the motor 10 - 1 .

<監視裝置40之構成> <Configuration of Monitoring Device 40 >

圖2係監視裝置40之方塊圖。監視裝置40係與上述控制部30同樣地具備CPU、DSP、RAM、ROM等作為普通電腦之硬體，且ROM中儲存有由CPU執行之控制程式、由DSP執行之微程式及各種資料等。 FIG. 2 is a block diagram of the monitoring device 40 . The monitoring device 40 is provided with CPU, DSP, RAM, ROM, etc. as hardware of an ordinary computer like the control unit 30 described above, and the ROM stores a control program executed by the CPU, a microprogram executed by the DSP, various data, and the like.

於圖2中，監視裝置40之內部係以方塊表示由控制程式及微程式等實現之功能。即，監視裝置40具備馬達資訊運算部42、特徵量運算部44、狀態推定部45、資料記憶部46及異常判定部47。 In FIG. 2 , the inside of the monitoring device 40 is represented by blocks as functions realized by the control program, the microprogram, and the like. That is, the monitoring device 40 includes a motor information calculation unit 42 , a feature value calculation unit 44 , a state estimation unit 45 , a data storage unit 46 , and an abnormality determination unit 47 .

馬達資訊運算部42自分別對應之電流感測器41獲取馬達1之10-1之U相之電流檢測值I_u1、W相之電流檢測值I_w1、馬達2之10-2之U相之電流檢測值I_u2及W相之電流檢測值I_w2。 The motor information calculation unit 42 obtains the current detection value I _u1 of the U-phase of the 10-1 of the motor 1, the current detection value I _w1 of the W-phase, and the U-phase of the 10-2 of the motor 2 from the corresponding current sensors 41 . The current detection value I _u2 and the current detection value I _w2 of the W-phase.

繼而，馬達資訊運算部42基於該等檢測值，輸出各馬達轉矩電流(實部電流)I_r1、I_r2及機械頻率ω_rs1、ω_rs2(旋轉速度)。 Then, the motor information calculation unit 42 outputs each of the motor torque currents (real part currents) I _r1 and I _r2 and the mechanical frequencies ω _rs1 and ω _rs2 (rotational speeds) based on the detected values.

此處，參照圖3，對自該等馬達資訊運算部42輸出之信號之意義進行說明。圖3係馬達資訊運算部42之方塊圖。 Here, referring to FIG. 3 , the meanings of the signals outputted from the motor information computing units 42 will be discussed. illustrate. FIG. 3 is a block diagram of the motor information computing unit 42 .

馬達資訊運算部42具備3Φ/αβ轉換器52、反正切轉換器54(相位檢測部)、減法器56(PLL(Phase Locked Loop，鎖相迴路)運算部)、相位運算器60(PLL運算部、旋轉速度運算部、旋轉速度運算過程)、旋轉座標轉換器70、積分器72(PLL運算部)及乘法器74。進而，相位運算器60具備乘法器62、64、積分器66及加法器68。 The motor information computing unit 42 includes a 3Φ/αβ converter 52 , an arctangent converter 54 (phase detection unit), a subtractor 56 (Phase Locked Loop (PLL) computing unit), and a phase computing unit 60 (PLL computing unit) , rotation speed calculation part, rotation speed calculation process), rotation coordinate converter 70 , integrator 72 (PLL calculation part) and multiplier 74 . Furthermore, the phase calculator 60 includes multipliers 62 and 64 , an integrator 66 , and an adder 68 .

3Φ/αβ轉換器52將電流檢測值I_u、I_w轉換為正交之二相之交流電流I_α、I_β。反正切轉換器54基於該等交流電流I_α、I_β，計算交流電流相位角檢測值θ_i*。 The Φ/αβ converter 52 converts the detected current values I _u , I _w into alternating currents I _α , I _β of two quadrature phases. The arctangent converter 54 calculates the AC current phase angle detection value θ _i * based on the AC currents I _α and I _β .

減法器56自交流電流相位角θ_i(詳情下文敍述)中減去交流電流相位角檢測值θ_i*。於相位運算器60，乘法器62對差值「θ_i*-θ_i」乘以特定之比例增益KpPLL。 The subtractor 56 subtracts the AC current phase angle detection value θ _i * from the AC current phase angle θ _i (described in detail later). In the phase operator 60, the multiplier 62 multiplies the difference "θ _i *-θ _i " by a specific proportional gain KpPLL.

乘法器62中之乘法結果成為上述比例信號PLL_P。又，乘法器64對差值「θ_i*-θ_i」乘以特定之積分增益KiPLL，積分器66將該乘法結果進行積分運算。 The multiplication result in the multiplier 62 becomes the above-mentioned proportional signal PLL_P. In addition, the multiplier 64 multiplies the difference "θ _i *-θ _i " by a predetermined integral gain KiPLL, and the integrator 66 integrates the multiplication result.

將積分器66中之積分結果稱為積分信號PLL_I。加法器68將比例信號PLL_P與積分信號PLL_I進行加法運算，將加法結果作為頻率信號ω_1s輸出。 The integration result in the integrator 66 is referred to as the integration signal PLL_I. The adder 68 adds the proportional signal PLL_P and the integral signal PLL_I, and outputs the addition result as the frequency signal ω _1s .

積分器72將頻率信號ω_1s進行積分運算，輸出交流電流相位角θ_i。將交流電流相位角θ_i供給至減法器56，並且亦供給至旋轉座標轉換器70。 The integrator 72 integrates the frequency signal ω _1s and outputs the AC current phase angle θ _i . The alternating current phase angle θ _i is supplied to the subtractor 56 and also to the rotary coordinate converter 70 .

又，乘法器74將頻率信號ω_1s乘以「2/P」(此處，P為馬達10之極數)，將乘法結果作為機械頻率ω_rs輸出。此處，機械頻率ω_rs成為與馬達10(參照圖1)之實際速度(於感應馬達之情形時包含轉差[slip]之速度)對應之信號。 In addition, the multiplier 74 multiplies the frequency signal ω _1s by "2/P" (here, P is the number of poles of the motor 10 ), and outputs the multiplication result as the mechanical frequency ω _rs . Here, the mechanical frequency ω _rs is a signal corresponding to the actual speed of the motor 10 (refer to FIG. 1 ) (speed including slip in the case of an induction motor).

旋轉座標轉換器70將二相之交流電流I_α、I_β轉換為以頻率信號ω_1s旋轉之旋轉座標系統中之二軸之直流量I_r、I_i。 The rotary coordinate converter 70 converts the two-phase alternating currents I _α and I _β into two-axis direct currents I _r and I _i in the rotating coordinate system rotating with the frequency signal ω _1s .

以此方式，減法器56、相位運算器60及積分器72作為PLL(Phase Locked Loop)運算部發揮功能，輸出如減法器56輸出之差值「θ_i*-θ_i」接近「0」之類的頻率信號ω_1s及交流電流相位角θ_i。 In this way, the subtractor 56, the phase calculator 60, and the integrator 72 function as a PLL (Phase Locked Loop) calculation unit, and output the difference "θ _i *-θ _i " that is close to "0" as the output of the subtractor 56 is close to "0". Class frequency signal ω _1s and AC current phase angle θ _i .

特徵量運算部44擷取馬達之轉矩電流I_r之最大值、平均值、FFT(fast Fourier transform，快速傅立葉轉換)及馬達旋轉速度ω_rs之最大值、平均值、FFT等特徵量。 The characteristic quantity computing unit 44 extracts characteristic quantities such as the maximum value, average value, FFT (fast Fourier transform) of the torque current I _r of the motor, and the maximum value, average value, and FFT of the motor rotational speed ω _rs .

狀態推定部45基於馬達轉矩電流I_r之最大值、平均值、FFT及馬達旋轉速度ω_rs之最大值、平均值、FFT等特徵量，推定機器狀態。 The state estimating unit 45 estimates the machine state based on characteristic quantities such as the maximum value, average value, FFT of the motor torque current Ir, and the maximum value, average value, and _{FFT of the motor rotational speed ωrs} _.

推定狀態量與記錄於資料記憶部46之基準值資料進行比較，由異常判定部47檢測該狀態量是否異常。又，異常判定部47向外部輸出各種警報信號。 The estimated state quantity is compared with the reference value data recorded in the data storage unit 46, and the abnormality determination unit 47 detects whether or not the state quantity is abnormal. In addition, the abnormality determination unit 47 outputs various alarm signals to the outside.

再者，警報信號為燈之點亮、警報器之鳴叫、或無線通信方法之電波發送等能夠通知管理者之方法即可。 Furthermore, the warning signal may be a method that can notify the administrator, such as lighting of a lamp, sounding of an alarm, or transmission of radio waves by wireless communication.

本實施例中之監視裝置40於設置於苛刻之環境之情形時，較佳為收納於已實施防塵防水對策之監視裝置殼體。進而，將監視裝置40設置於變頻器22等產生雜訊之裝置之附近之情形時，較佳為對監視裝置40實施雜訊對策。 When the monitoring device 40 in this embodiment is installed in a harsh environment, it is preferable to be accommodated in a monitoring device casing that has implemented dust-proof and waterproof measures. Furthermore, when the monitoring device 40 is installed in the vicinity of a device that generates noise, such as the inverter 22 , it is preferable to implement noise countermeasures for the monitoring device 40 .

如上所述，監視裝置40可使用獨自之座標，僅根據流入存在相關關係之驅動馬達之電流資訊，藉由簡單之演算法，由交流轉換為直流，因此，用於判斷為異常之邊緣處理亦可於監視裝置內執行。藉此，其結果，資料量可大幅度削減，分析/診斷作業亦變得容易。 As described above, the monitoring device 40 can use its own coordinates to convert the AC into the DC through a simple algorithm based only on the current information flowing into the related drive motors. Therefore, the edge processing for judging abnormality can also be performed. It can be executed in the monitoring device. As a result, the amount of data can be greatly reduced, and analysis/diagnosis work can be facilitated.

<工具磨耗度之推定> <Estimation of Tool Wear Degree>

圖4表示綜合加工機等工具機之工具驅動軸之一例。綜合加工機之種類根據主軸(轉軸)之方向大致分為臥式與立式，臥式係主軸安裝於水平方向上，立式係主軸安裝於垂直方向上。 FIG. 4 shows an example of a tool drive shaft of a machine tool such as a general processing machine. The types of comprehensive processing machines are roughly divided into horizontal and vertical types according to the direction of the main shaft (rotating shaft).

主軸係安裝實施加工之加工品或工具且使之旋轉之該上具機中最主要之軸。基本構造之立式綜合加工機一般進行3軸加工。 The main shaft system is the main part of the upper tool that installs the processed product or tool for processing and rotates it. The axis you want. The basic structure of the vertical integrated processing machine generally performs 3-axis processing.

動作與自正面觀察機械時主軸於上下方向(Z軸)上動作且固定有加工品之工作台朝前後(Y軸)與左右(X軸)動作的床式之銑床相同。 The operation is the same as that of a bed-type milling machine in which the spindle moves in the vertical direction (Z axis) when the machine is viewed from the front, and the table on which the workpiece is fixed moves forward and backward (Y axis) and left and right (X axis).

進給軸因加工種類而變。例如，於鑽孔加工之情形時，Z軸成為進給軸，於銑削加工之情形時，不僅Z軸，而且X軸或Y軸亦成為進給軸。另一方面，5軸加工之立式綜合加工機可使用除了XYZ之3軸之軸向動作以外亦帶有工作台之旋轉(C軸)與傾斜角(B軸)的分度台，進行5軸加工(未圖示)。 The feed axis varies depending on the type of machining. For example, in the case of drilling, the Z-axis becomes the feed axis, and in the case of milling, not only the Z-axis but also the X-axis or the Y-axis become the feed-axis. On the other hand, a 5-axis machining vertical machine can use an indexing table with table rotation (C-axis) and inclination (B-axis) in addition to the axial motion of the 3-axis XYZ. Shaft machining (not shown).

即，加工中存在相關關係之馬達數因機器或加工內容而變。例如，於鑽孔加工之情形時，存在相關關係之馬達為主軸馬達與進給軸馬達(Z軸馬達)，於銑削加工之情形時，存在相關關係之馬達為主軸馬達、進給軸馬達(X軸馬達、Y軸馬達、Z軸馬達)。 That is, the number of motors with which there is a correlation in machining varies depending on the machine or machining content. For example, in the case of drilling, the related motors are the spindle motor and the feed axis motor (Z-axis motor), and in the case of milling, the related motors are the spindle motor and the feed axis motor ( X-axis motor, Y-axis motor, Z-axis motor).

圖5表示伴隨工具磨耗之加工品質下降及工具破損產生之過程。存在工具隨著加工時間經過而刀尖磨耗，切削阻力增加，最終導致破損之情形。又，若工具磨耗繼續進行則加工精度變差，無法維持加工品所要求之特定之加工精度。 FIG. 5 shows the process of the deterioration of machining quality and the occurrence of tool breakage accompanying tool wear. There is a case where the tool tip wears over the machining time, and the cutting resistance increases, which eventually leads to breakage. In addition, if the tool wear continues, the machining accuracy will deteriorate, and the specific machining accuracy required for the processed product cannot be maintained.

圖6係伴隨工具磨耗之主軸及進給軸之力與各軸中之馬達轉矩電流之變化。隨著工具磨耗繼續進行，工具之刀刃變得容易打滑，因此，主軸馬達之負載減少，其結果，主軸馬達之轉矩電流減少。另一方面，工具之刀刃變得難以切入，因此，進給軸馬達之負載增大，其結果，進給軸馬達之轉矩電流增大。即，若監視主軸及進給軸馬達電流之變化，則可推定工具磨耗狀態。 FIG. 6 shows the change of the force of the main shaft and the feed shaft and the motor torque current in each shaft with tool wear. As tool wear continues, the blade of the tool becomes prone to slipping, so the spindle The load to be reached is reduced, and as a result, the torque current of the spindle motor is reduced. On the other hand, the cutting edge of the tool becomes difficult to cut, so that the load on the feed shaft motor increases, and as a result, the torque current of the feed shaft motor increases. That is, by monitoring changes in the motor currents of the spindle and the feed axis, the tool wear state can be estimated.

圖7係擷取每一特定之加工區間中之主軸及進給軸之馬達轉矩電流及馬達旋轉速度之特徵量之概略圖。例如，隨著加工時間經過，擷取每一加工區間中之特定加工區間之轉矩電流之最大值、標準偏差、平均值、FFT及馬達旋轉速度之最大值、標準偏差、平均值、FFT等特徵量。 FIG. 7 is a schematic diagram of extracting the characteristic quantities of the motor torque current and the motor rotational speed of the main shaft and the feed shaft in each specific machining section. For example, the maximum value, standard deviation, average value, FFT and the maximum value, standard deviation, average value, FFT, etc. Feature amount.

又，將特定1台馬達或存在相關關係之複數台馬達之轉矩電流值或旋轉速度值設為特徵量擷取之觸發點，運算指定區間之特徵量，藉此，可視需要調整取樣頻率或運算量。藉此，其結果，資料量可大幅度削減，分析/診斷作業亦變得容易。進而，可根據進給軸馬達之電流波形，判別加工動作種類，因此，可進行更準確之特徵量擷取。 In addition, the torque current value or rotational speed value of a specific motor or a plurality of related motors is set as the trigger point for feature extraction, and the feature in the specified interval is calculated, thereby adjusting the sampling frequency or Computation. As a result, the amount of data can be greatly reduced, and analysis/diagnosis work can be facilitated. Furthermore, the type of machining action can be discriminated according to the current waveform of the feed axis motor, so that more accurate feature quantity extraction can be performed.

進而，若根據工具徑或加工負載之變化，改變基於主軸馬達電流資訊及進給軸馬達電流資訊推定工具磨耗度之特徵量之組合，則可更準確地推定工具磨耗度。 Furthermore, by changing the combination of the feature quantities for estimating the tool wear degree based on the spindle motor current information and the feed shaft motor current information according to changes in the tool diameter or machining load, the tool wear degree can be estimated more accurately.

圖8係對使用一般線性模型方法之工具磨耗度(上述機器狀態量)之推定方法進行說明之圖。作為一例，對磨耗度為工具刀刃之磨耗寬度之情形時之推定方法進行說明。 FIG. 8 is a diagram illustrating a method of estimating the degree of tool wear (the above-mentioned machine state quantity) using a general linear model method. As an example, an estimation method in the case where the wear degree is the wear width of the tool blade will be described.

可對於計測工具磨耗寬度，基於自上述馬達電流資訊中擷取之特徵量，利用多變量分析等方法構築推定模型式。此處，推定模型式係表示複數個驅動馬達之上述中例示之特徵量與工具磨耗度之對應關係之運算式。一般線性模型所示之推定模型之一例如以下之(式1)所述。 For the measurement tool wear width, an estimation model expression can be constructed by a method such as multivariate analysis based on the feature quantity extracted from the above-mentioned motor current information. Here, the estimated model expression is an arithmetic expression representing the correspondence between the characteristic quantities of the plurality of drive motors and the tool wear degree exemplified above. One of the estimated models represented by the general linear model is, for example, as described in the following (Equation 1).

Y=a+b×進給軸馬達轉矩電流之平均值+c×進給軸馬達旋轉速度之最大值+d×主軸馬達轉矩電流之平均值+e×主軸馬達旋轉速度之標準偏差…(式1) Y=a+b×the average value of the torque current of the feed shaft motor+c×the maximum value of the rotational speed of the feed shaft motor+d×the average value of the torque current of the spindle motor+e×the standard deviation of the rotational speed of the spindle motor… (Formula 1)

此處，Y為根據推定模型式推定之工具磨耗度，a、b、c、d、e為常數。即，可基於存在相關關係之馬達電流資訊，推定工具磨耗度Y。 Here, Y is the tool wear degree estimated from the estimated model expression, and a, b, c, d, and e are constants. That is, the tool wear degree Y can be estimated based on the motor current information having the correlation.

又，藉由根據加工負載之變化調整上述常數b、c、d、e(加權：貢獻度)，可改變對目標變數Y之支配度，因此，可提昇推定精度。 In addition, by adjusting the above-mentioned constants b, c, d, and e (weighting: contribution degree) according to changes in the machining load, the degree of dominance over the target variable Y can be changed, so that the estimation accuracy can be improved.

例如，於圖7之鑽孔加工中，於大徑鑽孔器(加工負載大)之情形時，主軸馬達之轉矩電流及旋轉速度明顯地呈現磨耗之程度。因此，於大徑鑽孔器(加工負載大)之情形時，對主軸馬達之轉矩電流及旋轉速度進一步附進行加權(貢獻度)。 For example, in the drilling process of FIG. 7 , in the case of a large-diameter drill (with a large processing load), the torque current and rotational speed of the spindle motor are obviously worn out. Therefore, in the case of a large-diameter drill (with a large machining load), the torque current and rotational speed of the spindle motor are further weighted (contribution).

另一方面，於小徑鑽孔器(加工負載小)之情形時，進給軸馬達電流及旋轉速度明顯地呈現磨耗之程度。因此，於小徑鑽孔器(加工負載小)之情形時，若對進給軸馬達電流及旋轉速度進一步進行加權(貢獻度)，則可更高精度地推定鑽孔器磨耗。以此方式，根據作為對象機器之鑽孔器改變推定模型式，藉此，可感度較佳地推定機器之狀態。 On the other hand, in the case of a small diameter drill (with a small processing load), the motor current and rotation speed of the feed shaft are obviously worn out. Therefore, in the case of a small-diameter drill (with a small machining load), if the feed shaft motor current and rotation speed are further weighted (contribution), the Estimate drill wear with high accuracy. In this way, the estimation model formula is changed according to the drill as the target machine, whereby the state of the machine can be estimated with a good sensitivity.

若將推定模型之(式1)改寫為一般之函數式，則成為以下之(式2)。 When (Expression 1) of the estimated model is rewritten into a general functional expression, the following (Expression 2) is obtained.

Y(I、w、L)=g₁(I₁、w₁)×k₁(L)+g₂(I₂、w₂)×k₂(L)+…(式2) Y(I, w, L)=g ₁ (I ₁ , w ₁ )×k ₁ (L)+g ₂ (I ₂ , w ₂ )×k ₂ (L)+…(Formula 2)

此處，I為馬達轉矩電流，w為馬達旋轉速度，L為加工負載，g₁為將馬達1之轉矩電流及旋轉速度設為變數之函數，g₂為將馬達2之轉矩電流及旋轉速度設為變數之函數，k₁為將加工負載設為變數之馬達1之函數，k₂為將加工負載設為變數之馬達2之函數。 Here, I is the torque current of the motor, w is the rotational speed of the motor, L is the machining load, g ₁ is a function of the torque current and the rotational speed of the motor 1 as variables, and g ₂ is the torque current of the motor 2 And the rotation speed is a function of a variable, k ₁ is a function of the motor 1 with the machining load as a variable, and k ₂ is a function of the motor 2 with the machining load as a variable.

可使用基於存在相關關係之複數個馬達之電流資訊之複數個特徵量及根據負載L改變之係數(貢獻度)，精度較佳地推定機器狀態。 By using a plurality of characteristic quantities based on current information of a plurality of motors having a correlation and a coefficient (contribution degree) changed according to the load L, the machine state can be estimated with high accuracy.

又，此處之k₁(L)、k₂(L)、…亦可根據機器加工負載或加工模式，預先計測後保存於資料記憶部；根據機械學習等累積之資料提昇精度。 In addition, k ₁ (L), k ₂ (L), . . . can also be pre-measured and stored in the data memory according to the machining load or machining mode, and the accuracy can be improved based on accumulated data such as machine learning.

於實際運用時，工具磨耗度之極限M₀由加工品質等決定。若不存在推定誤差或偏差，則推定工具磨耗度Y之上限成為與M₀對應之Y₁，若考慮推定偏差，則推定工具磨耗度之上限成為Y₂。 In actual use, the limit M ₀ of the tool wear degree is determined by the processing quality and so on. If there is no estimation error or deviation, the upper limit of the estimated tool wear degree Y is Y ₁ corresponding to M ₀ , and when the estimated deviation is considered, the upper limit of the estimated tool wear degree is Y ₂ .

即，若推定工具磨耗度Y超過Y₂，則加工品成為不良品。藉由監視該推定工具磨耗度Y，可準確地掌握工具更換時期。又，此處，以一般線性模型方法為例進行了說明。只要為表示工具磨耗度與自馬達電流中擷取之特徵量之關係之模型構築方法，則不必限於使用統計方法之模型等一般線性模型方法。 That is, when the estimated tool wear degree Y exceeds Y ₂ , the processed product becomes a defective product. By monitoring the estimated tool wear degree Y, the tool replacement timing can be accurately grasped. Here, the general linear model method has been described as an example. As long as it is a method for constructing a model that expresses the relationship between the tool wear degree and the feature quantity extracted from the motor current, it is not necessarily limited to a general linear model method such as a model using a statistical method.

進而，藉由對累積所得之資料導入機械學習等，可實現更準確之工具磨耗度推定。根據以上內容，可基於存在相關關係之馬達電流資訊推定工具磨耗度，因此，可更準確地掌握工具之更換時期。又，藉由監視工具磨耗度，亦可防止工具破損之產生。 Furthermore, by introducing machine learning or the like to the accumulated data, more accurate tool wear degree estimation can be realized. According to the above, the tool wear degree can be estimated based on the motor current information with the correlation, and therefore, the replacement time of the tool can be more accurately grasped. In addition, by monitoring the tool wear degree, the occurrence of tool breakage can also be prevented.

<實施例1之動作> <Operation of Example 1>

圖9係監視裝置40中執行之工具磨耗偵測例行程序之流程圖。該工具磨耗偵測例行程序係於每一特定之取樣週期執行。 FIG. 9 is a flow diagram of a tool wear detection routine executed in monitoring device 40 . The tool wear detection routine is executed every specific sampling period.

於圖9中，工具磨耗偵測例行程序開始(START)，執行馬達電流計測之處理(步驟S2)。繼而，監視裝置40(參照圖2)之馬達資訊運算部42自主軸等各軸之馬達之電流感測器41(參照圖1)獲取第1軸之馬達之電流檢測值I_U1、I_W1及第2軸之馬達之電流檢測值I_U2、I_W2。 In FIG. 9, the tool wear detection routine is started (START), and the process of measuring the motor current is performed (step S2). Then, the motor information calculation unit 42 of the monitoring device 40 (refer to FIG. 2 ) acquires the current detection values I _U1 , I _W1 and Current detection values I _U2 and I _W2 of the motor of the second axis.

繼而，收到第1軸之馬達及第2軸之馬達之電流檢測值，馬達資訊運算部42運算對應之第1軸之馬達10-1之轉矩電流I_r1及旋轉速度ω_rs1、第2軸之馬達10-2之轉矩電流I_r2及旋轉速度ω_rs2。 Then, receiving the current detection values of the motor of the first axis and the motor of the second axis, the motor information calculation unit 42 calculates the torque current I _r1 and the rotational speed ω _rs1 of the motor 10-1 of the first axis corresponding to the second axis. The torque current I _r2 and the rotational speed ω _rs2 of the shaft motor 10-2.

即，將各軸之馬達之轉矩電流I_r、機械頻率ω_rs輸出(步驟S3)。 That is, the torque current I _r and the mechanical frequency ω _rs of the motors of each axis are output (step S3 ).

繼而，特徵量運算部44擷取特定區間之轉矩電流之最大值、標準偏差、平均值、FFT及馬達旋轉速度之最大值、標準偏差、平均值、FFT等特徵量(步驟S4)。 Then, the feature value calculation unit 44 extracts the maximum value and standard deviation of the torque current in the specific section. Difference, average value, FFT, and maximum value of motor rotation speed, standard deviation, average value, FFT and other characteristic quantities (step S4).

繼而，狀態推定部45基於上述之推定模型，使用自資料記憶部46獲取之特徵量及與負載對應之相關馬達之貢獻度，執行(式1)之運算，算出工具磨耗度。(步驟S5) Next, the state estimation unit 45 uses the feature quantity acquired from the data storage unit 46 and the contribution degree of the relevant motor corresponding to the load, based on the estimation model described above, to perform the calculation of (Equation 1) to calculate the tool wear degree. (step S5)

將狀態推定部45之推定時使用之與負載對應之相關馬達之貢獻度或異常判定部47中使用之基準值預先記憶於資料記憶部46(步驟S6)。貢獻度或基準值亦可基於轉矩電流Ir進行更新。 The contribution degree of the relevant motor corresponding to the load used in the estimation by the state estimation unit 45 or the reference value used by the abnormality determination unit 47 is stored in the data storage unit 46 in advance (step S6 ). The contribution degree or the reference value may also be updated based on the torque current Ir.

進而，異常判定部47與基準值資料進行比較，判定轉矩電流I_r較設定極限值I_r0更低，且判定處於馬達旋轉狀態(ω_rs>0)時(步驟S7為是)，異常判定部47將表示工具為破損狀態之警報信號輸出至外部(步驟S9)。 Further, the abnormality determination unit 47 compares the reference value data, determines that the torque current I _r is lower than the set limit value I _r0 , and determines that the motor is in the rotating state (ω _rs > 0) (YES in step S7 ), and determines the abnormality The section 47 outputs an alarm signal indicating that the tool is in a broken state to the outside (step S9).

異常判定部47判定磨耗度Y超過設定極限值Y₂，且判定處於馬達旋轉狀態(ω_rs>0)時(步驟S8為是)，異常判定部47將表示工具為磨耗狀態之警報信號輸出至外部(步驟S10)。 When the abnormality determination unit 47 determines that the degree of wear Y exceeds the set limit value Y ₂ and determines that the motor is in a rotating state (ω _rs > 0) (YES in step S8 ), the abnormality determination unit 47 outputs an alarm signal indicating that the tool is in a worn state to outside (step S10).

又，於與兩者中之任一者均不相符之情形(步驟S7或步驟S8為否)時，本例行程序之處理結束(END)。 In addition, in the case where it does not correspond to either of the two (NO in step S7 or step S8), the processing of this routine is terminated (END).

<實施例1之效果> <Effect of Embodiment 1>

如上所述，根據本實施例，可基於存在相關關係之複數個馬達之至少各2相之電流值I_U、I_W偵測工具磨耗狀態。即，可延長工具平均使用壽命而不追加加速度感測器或AE(Acoustic Emission，聲頻發射)感測器等。 As described above, according to the present embodiment, the tool wear state can be detected based on the current values _IU and _IW of at least two phases of a plurality of motors having a correlation relationship. That is, the average service life of the tool can be extended without adding an acceleration sensor or an AE (Acoustic Emission, acoustic emission) sensor or the like.

又，藉由使工具磨耗度可視化，可一面實現工具維護之人工節省化，一面防止工具破損於未然。又，異常判定部47偵測到工具磨耗狀態時，輸出警報信號。藉此，可對管理者報告各種異常。 In addition, by visualizing the tool wear degree, it is possible to save labor for tool maintenance and prevent tool breakage in advance. Moreover, when the abnormality determination part 47 detects a tool wear state, it outputs an alarm signal. Thereby, various abnormalities can be reported to the manager.

根據實施例1，可基於複數個驅動馬達之電流資訊，感度較佳地判定機器狀態之異常。 According to the first embodiment, based on the current information of a plurality of driving motors, the sensitivity can better determine the abnormal state of the machine.

又，若工具之磨耗繼續進行則加工精度變差，從而無法維持加工品所要求之特定之加工精度，因此，切削加工中使用之工具因其個體差異導致甚至破損之壽命變動較大。因此，如將平均壽命設為目標以固定之加工數進行更換之類先前之壽命管理方法般，存在若為較平均壽命短之工具，則因加工性能降低導致產生製品不良之情形，但於本實施例中，可避免此種製品不良。 In addition, if the wear of the tool continues, the machining accuracy will deteriorate, and the specific machining accuracy required for the machined product cannot be maintained. Therefore, the tool used in the cutting process varies greatly due to individual differences and even breakage. Therefore, as in the conventional life management method in which the average life is set as the target and replaced with a fixed number of machining operations, if the tool life is shorter than the average life, there are cases in which the product is defective due to the deterioration of the machining performance. In the embodiment, such product defects can be avoided.

又，於本實施例中，若為較平均壽命長之工具，則可防止達到壽命之前進行更換導致之損失成本。 In addition, in this embodiment, if the tool has a longer life than the average, the loss cost caused by the replacement before reaching the end of the life can be prevented.

又，於馬達設置場所存在尺寸限制之情形或苛刻之環境條件下，難以追加設置偵測工具磨耗之加速度感測器或AE(Acoustic Emission)感測器等，但根據本實施例，可不需要此種感測器。 In addition, it is difficult to additionally install an acceleration sensor or AE (Acoustic Emission) sensor for detecting tool wear when the motor installation site has size restrictions or harsh environmental conditions. sensor, etc., but according to this embodiment, such a sensor may not be needed.

進而，存在感測器之數量越增加，越難確保感測器群之可靠性，從而監視精度下降之問題，但根據本實施例，因不使用感測器，故可解決此種問題。 Furthermore, as the number of sensors increases, it becomes more difficult to ensure the reliability of the sensor group, thereby reducing the monitoring accuracy. However, according to this embodiment, since no sensors are used, this problem can be solved.

又，因不使用感測器，故維護性、可靠性大幅度提昇。具體而言，不僅可削減感測器之保養檢查作業，而且可防止伴隨感測器故障之系統失效於未然。又，可削減感測器用系統裝配佈線，因此，可削減作業成本，而且可消除佈線干擾等困擾。 In addition, since no sensor is used, maintainability and reliability are greatly improved. Specifically, not only the maintenance and inspection work of the sensor can be reduced, but also the system failure accompanying the sensor failure can be prevented. In addition, since the sensor system assembly wiring can be reduced, the operating cost can be reduced, and troubles such as wiring interference can be eliminated.

[實施例2] [Example 2]

圖10係實施例2之馬達控制系統102之方塊圖。再者，於以下之說明中，存在對與上述其他實施例之各部對應之部分標註相同之符號，且省略其說明之情形。 FIG. 10 is a block diagram of the motor control system 102 of the second embodiment. In addition, in the following description, the part corresponding to each part of the above-mentioned other embodiment is marked with the same code|symbol, and the description is abbreviate|omitted.

於圖10中，馬達控制系統102具備N台(N為3以上之自然數)馬達10-1~10-N、及經由旋轉軸14結合於該等馬達10-1~10-N之工具16。 In FIG. 10 , the motor control system 102 includes N (N is a natural number greater than or equal to 3) motors 10-1 to 10-N, and a tool 16 coupled to the motors 10-1 to 10-N via the rotating shaft 14 .

又，於各馬達10-1~10-N之U相、W相安裝各2個(合計2N個)電流感測器41，其等之電流檢測值I_u1~I_uN、I_w1~I_wN供給至監視裝置150(工具磨耗度之監視裝置)。 In addition, two current sensors 41 (2N in total) are installed in the U-phase and W-phase of each motor 10-1 to 10-N, and the current detection values I _u1 to I _uN and I _w1 to I _wN are equal to each other. It is supplied to a monitoring device 150 (a monitoring device for tool wear).

對於監視裝置150之構成，如圖11所示，與實施例1之監視裝置40(參照圖2)中設置N個存在相關關係之馬達資訊運算部代替2個存在相關關係之馬達資訊運算部42之構成相同。 As for the configuration of the monitoring device 150, as shown in FIG. 11, the monitoring device 40 (refer to FIG. 2) of the first embodiment is provided with N motor information computing units having a correlation relationship instead of two motor information computing units 42 having a correlation relationship. The composition is the same.

例如，亦存在將上述銑削加工之情形時之作為進給軸之Z軸、X軸或Y軸中之驅動馬達設為存在相關關係之驅動馬達之情形。 For example, there is also a case where the drive motor in the Z-axis, X-axis, or Y-axis, which is the feed axis in the case of the above-mentioned milling process, is a drive motor that has a related relationship.

又，可將5軸加工之立式綜合加工機中之工作台之旋轉(C軸)與傾斜角(B軸)之驅動馬達包含於存在相關關係之驅動馬達中。本實施例之上述以外之構成及動作與實施例1大致相同。 In addition, the drive motors for the rotation (C axis) and the inclination angle (B axis) of the table in the 5-axis machining vertical machine can be included in the drive motors that are related. The configuration and operation of the present embodiment other than the above are substantially the same as those of the first embodiment.

圖12係對自複數個馬達之電流資訊中擷取與機器狀態相關之特徵量之情形進行說明之圖。與實施例1之圖8同樣地，例如可推定利用特徵量之一般線性模型等方法之機器狀態。於複雜加工之情形時，藉由使用存在利於加工負載之相關關係之複數個馬達電流資訊，可提昇機器狀態之推定精度。 FIG. 12 is a diagram illustrating a state of extracting feature quantities related to machine states from current information of a plurality of motors. As in FIG. 8 of the first embodiment, the machine state can be estimated by a method such as a general linear model of feature quantities, for example. In the case of complex machining, the estimation accuracy of the machine state can be improved by using a plurality of motor current information having a correlation that is beneficial to the machining load.

[實施例3] [Example 3]

圖13係實施例3之馬達控制系統103之方塊圖。再者，於以下之說明中，存在對與上述其他實施例之各部對應之部分標註相同之符號，且省略其說明之情形。 FIG. 13 is a block diagram of the motor control system 103 of the third embodiment. In addition, in the following description, the part corresponding to each part of the above-mentioned other embodiment is marked with the same code|symbol, and the description is abbreviate|omitted.

於圖13中，馬達控制系統103具備監視裝置160(機器狀態之監視裝置)代替實施例1之監視裝置40(參照圖2)。監視裝置160之構成與監視裝置40之構成大致相同，但異常判定部47輸出工具磨耗警報信號(參照圖2)，並且對驅動裝置20內之指令產生部32視需要輸出控制指令。 In FIG. 13, the motor control system 103 includes a monitoring device 160 (a monitoring device for the state of the machine). device) in place of the monitoring device 40 of the first embodiment (refer to FIG. 2). The configuration of the monitoring device 160 is substantially the same as that of the monitoring device 40 , but the abnormality determination unit 47 outputs a tool wear alarm signal (see FIG. 2 ), and outputs a control command to the command generation unit 32 in the drive device 20 as necessary.

此處，控制指令係例如指示馬達10-1之停止或加速減速者，藉此，例如可實施最適合工具使用壽命延長或加工品質維持之運轉。 Here, the control command is, for example, one that instructs the motor 10-1 to stop or accelerate and decelerate, whereby, for example, an operation that is most suitable for prolonging the service life of the tool or maintaining the machining quality can be implemented.

以此方式，根據本實施例，異常判定部47偵測到機器狀態之異常(工具之過度磨耗、破損等)後，對控制部30輸出使控制狀態變更之控制指令。作為該情形時之控制指令，存在驅動馬達之停止或降低旋轉速度之類控制指令。藉此，可將控制部30中之控制狀態變更為合適之狀態。 In this way, according to the present embodiment, the abnormality determination unit 47 outputs a control command to change the control state to the control unit 30 after detecting the abnormality of the machine state (excessive wear of the tool, breakage, etc.). As the control command in this case, there is a control command such as stopping the drive motor or reducing the rotational speed. Thereby, the control state in the control part 30 can be changed to an appropriate state.

[實施例4] [Example 4]

圖14係實施例4之馬達控制系統104之方塊圖。再者，於以下之說明中，存在對與上述其他實施例之各部對應之部分標註相同之符號並省略其說明之情形。 FIG. 14 is a block diagram of the motor control system 104 of the fourth embodiment. In addition, in the following description, the part corresponding to each part of the above-mentioned other embodiment is marked with the same code|symbol, and the description is abbreviate|omitted.

於圖14中，馬達控制系統104具備監視裝置170(機器狀態之監視裝置)代替實施例2之監視裝置40(參照圖11)。監視裝置170之構成與監視裝置150之構成大致相同，但異常判定部47輸出機器狀態異常警報信號(參照圖11)，並且對驅動裝置20內之指令產生部32視需要輸出控制指令。 In FIG. 14 , the motor control system 104 includes a monitoring device 170 (a device state monitoring device) in place of the monitoring device 40 of the second embodiment (see FIG. 11 ). The configuration of the monitoring device 170 is substantially the same as that of the monitoring device 150 , but the abnormality determination unit 47 outputs a machine state abnormality alarm signal (see FIG. 11 ), and outputs a control command to the command generation unit 32 in the drive device 20 as necessary.

此處，控制指令係例如指示馬達10-1之停止或加速減速者，藉此，可實施最適合工具使用壽命延長或加工品質維持之運轉。 Here, the control command is, for example, instructing the motor 10-1 to stop or accelerate and decelerate, whereby, It is possible to implement the operation that is most suitable for prolonging the tool life or maintaining the machining quality.

以此方式，根據本實施例，異常判定部47偵測到機器狀態之異常(工具之過度磨耗、破損等)後，對控制部30輸出使控制狀態變更之控制指令。藉此，可將控制部30中之控制狀態變更為合適之狀態。 In this way, according to the present embodiment, the abnormality determination unit 47 outputs a control command to change the control state to the control unit 30 after detecting the abnormality of the machine state (excessive wear of the tool, breakage, etc.). Thereby, the control state in the control part 30 can be changed to an appropriate state.

[實施例5] [Example 5]

圖15係實施例5之馬達控制系統105之方塊圖。再者，於以下之說明中，存在對與上述其他實施例之各部對應之部分標註相同之符號並省略其說明之情形。 FIG. 15 is a block diagram of the motor control system 105 of the fifth embodiment. In addition, in the following description, the part corresponding to each part of the above-mentioned other embodiment is marked with the same code|symbol, and the description is abbreviate|omitted.

於圖15中，馬達控制系統105具備驅動.監視裝置180、馬達10-1~10-N、及經由旋轉軸14結合之工具16。驅動.監視裝置180具備控制部30、變頻器22及監視裝置190(機器狀態異常之偵測)。 In FIG. 15 , the motor control system 105 includes a drive and monitoring device 180 , motors 10 - 1 to 10 -N, and a tool 16 coupled via the rotating shaft 14 . The drive-monitoring device 180 includes the control unit 30 , the inverter 22 , and the monitoring device 190 (detection of machine state abnormality).

控制部30、變頻器22之構成與實施例1(參照圖1)相同，監視裝置190之構成與實施例4之監視裝置170(參照圖14)之構成相同。因此，本實施例之驅動.監視裝置180具有將實施例4中之驅動裝置20及監視裝置170之功能合併而成之功能。再者，本實施例亦可藉由對現有之驅動裝置20(參照圖14)增設監視裝置190而構成。 The configuration of the control unit 30 and the inverter 22 is the same as that of the first embodiment (see FIG. 1 ), and the configuration of the monitoring device 190 is the same as that of the monitoring device 170 (see FIG. 14 ) of the fourth embodiment. Therefore, the driving and monitoring device 180 of this embodiment has the function of combining the functions of the driving device 20 and the monitoring device 170 in the fourth embodiment. Furthermore, the present embodiment can also be configured by adding a monitoring device 190 to the existing drive device 20 (see FIG. 14 ).

[實施例6] [Example 6]

圖16係實施例6之馬達驅動伺服放大器106之方塊圖。再者，於以下之說明中，存在對與上述其他實施例之各部對應之部分標註相同之符號並省略其說明之情形。 FIG. 16 is a block diagram of the motor-driven servo amplifier 106 of the sixth embodiment. Furthermore, in the following In the description, there are cases where the parts corresponding to the parts of the other embodiments described above are marked with the same symbols and the description thereof is omitted.

於圖16中，伺服放大器106具備馬達10-1、旋轉軸14、工具16、伺服放大器106及監視裝置210。又，對馬達10-1之U相、W相安裝電流感測器41，將其等之電流檢測值I_u1、I_w1及來自伺服放大器2之馬達10-2之電流檢測值I_u2、I_w2供給至監視裝置210(機器狀態之監視裝置)。 In FIG. 16 , the servo amplifier 106 includes the motor 10 - 1 , the rotating shaft 14 , the tool 16 , the servo amplifier 106 , and the monitoring device 210 . In addition, the current sensors 41 are attached to the U-phase and the W-phase of the motor 10-1, and the current detection values I _u1 and I _w1 of the current sensors 41 and the current detection values I _u2 and I of the motor 10-2 from the servo amplifier 2 are calculated. _w2 is supplied to the monitoring device 210 (the monitoring device of the machine state).

就監視裝置210之構成而言，與如圖2所示於實施例1之監視裝置40(參照圖2)中設置有2個馬達資訊運算部42之構成相同。本實施例之上述以外之構成及動作與實施例1大致相同。 The configuration of the monitoring device 210 is the same as that of the monitoring device 40 (refer to FIG. 2 ) of the first embodiment, as shown in FIG. 2 , in which two motor information calculation units 42 are provided. The configuration and operation of the present embodiment other than the above are substantially the same as those of the first embodiment.

又，於本實施例中，說明了於對馬達供給電流之伺服放大器中組入偵測機器狀態異常之功能之實施例，但若於對馬達供給電流之變頻器中組入偵測機器異常之功能，則可同樣地構築偵測工具磨耗狀態之變頻器(未圖示)。 In addition, in this embodiment, the embodiment in which the function of detecting machine state abnormality is incorporated into the servo amplifier that supplies current to the motor is described, but if the inverter that supplies current to the motor incorporates the function of detecting machine abnormality function, a frequency converter (not shown) for detecting tool wear status can be constructed in the same way.

根據以上內容，可基於存在相關關係之複數個馬達電流資訊推定機器狀態，因此，可更準確地掌握機器之工具之更換時期或維護時期。 According to the above, the state of the machine can be estimated based on a plurality of pieces of motor current information having a correlation, so that the replacement time or maintenance time of the tool of the machine can be grasped more accurately.

[實施例7] [Example 7]

圖17係實施例7之馬達驅動伺服放大器107之方塊圖。再者，於以下之說明中，存在對與上述其他實施例之各部對應之部分標註相同之符號並省略其說明之情形。 FIG. 17 is a block diagram of the motor-driven servo amplifier 107 of the seventh embodiment. Furthermore, in the following description, the parts corresponding to the parts of the other embodiments described above are marked with the same symbols and The case where its description is omitted.

於圖17中，伺服放大器107具備N台(N為3以上之自然數)馬達10-1~10-N、旋轉軸14、工具16、伺服放大器107及監視裝置220。 In FIG. 17 , the servo amplifier 107 includes N (N is a natural number of 3 or more) motors 10 - 1 to 10 -N, the rotating shaft 14 , the tool 16 , the servo amplifier 107 , and the monitoring device 220 .

就監視裝置220之構成而言，與如圖11所示設置N個馬達資訊運算部之構成相同。本實施例之上述以外之構成及動作與實施例1大致相同。 The configuration of the monitoring device 220 is the same as the configuration in which N motor information calculation units are provided as shown in FIG. 11 . The configuration and operation of the present embodiment other than the above are substantially the same as those of the first embodiment.

根據以上所述，可基於存在相關關係之複數個馬達之電流資訊推定機器狀態，因此，可更準確地掌握機器之工具之更換時期或維護時期。 As described above, the machine state can be estimated based on the current information of a plurality of motors having a correlation, and therefore, the replacement time or maintenance time of the machine tool can be more accurately grasped.

[實施例8] [Example 8]

圖18係實施例8之產業用控制器108之方塊圖。產業用控制器108係與網路化之工廠之生產線或設備聯合，實現機器人控制或來自各種感測器之設備機器資料之收集與上位之資訊系統之無縫之垂直整合。而且，產業用控制器108係將產業用電腦之功能與PLC(programmable logic controller，可程式化邏輯控制器)之開放整合開發環境聚合於一台。不僅控制工廠內之設備機器，而且藉由收集、分析資訊而實現工廠整體或供應鏈整體之最佳化。 FIG. 18 is a block diagram of the industrial controller 108 of the eighth embodiment. The industrial controller 108 is integrated with the production line or equipment of the networked factory to realize the seamless vertical integration of robot control or the collection of equipment and machine data from various sensors and the upper information system. Moreover, the industrial controller 108 integrates the functions of the industrial computer and the open integrated development environment of PLC (programmable logic controller, programmable logic controller) into one. It not only controls the equipment and machines in the factory, but also realizes the optimization of the entire factory or the entire supply chain by collecting and analyzing information.

再者，於以下之說明中，存在對與上述其他實施例之各部對應之部分標註相同之符號並省略其說明之情形。 In addition, in the following description, the part corresponding to each part of the above-mentioned other embodiment is marked with the same code|symbol, and the description is abbreviate|omitted.

於圖18中，產業用控制器108具備資訊收集部240與監視裝置230。又，各馬達10-1~10-N之電流檢測值I_u1~I_uN、I_w1~I_wN自變頻器或伺服放大器供給至資訊收集部240。 In FIG. 18 , the industrial controller 108 includes an information collection unit 240 and a monitoring device 230 . In addition, the current detection values I _u1 to I _uN and I _w1 to I _wN of the motors 10 - 1 to 10 -N are supplied to the information collection unit 240 from the inverter or the servo amplifier.

就監視裝置230之構成而言，與如圖11所示設置N個馬達資訊運算部之構成相同。本實施例之上述以外之構成及動作與實施例1大致相同。 The configuration of the monitoring device 230 is the same as the configuration in which N motor information calculation units are provided as shown in FIG. 11 . The configuration and operation of the present embodiment other than the above are substantially the same as those of the first embodiment.

根據以上所述，可根據連接於網路之複數個馬達之電流資訊，於產業用控制器中推定複數個機器之狀態，因此，可更有效率地實現各個工具更換時期之最佳化或維護之人工節省化。 As described above, the industrial controller can estimate the states of a plurality of machines based on the current information of a plurality of motors connected to a network, so that the optimization or maintenance of each tool replacement period can be realized more efficiently. labor saving.

[實施例9] [Example 9]

圖19係實施例9之工具機之概略圖。再者，於以下之說明中，存在對與上述其他實施例之各部對應之部分標註相同之符號並省略其說明之情形。 FIG. 19 is a schematic view of the machine tool of the ninth embodiment. In addition, in the following description, the part corresponding to each part of the above-mentioned other embodiment is marked with the same code|symbol, and the description is abbreviate|omitted.

於圖19中，工具機109係於其控制部中具備Z軸馬達伺服放大器、主軸馬達變頻器、X軸馬達伺服放大器、Y軸馬達伺服放大器、及監視裝置250。又，各軸馬達之電流檢測值自伺服放大器或變頻器供給至監視裝置。亦可自監視裝置將工具磨耗資訊輸出至工具機之控制操作畫面(面板)，顯示警報或警告訊息(未圖示)。 In FIG. 19 , the machine tool 109 includes a Z-axis motor servo amplifier, a spindle motor inverter, an X-axis motor servo amplifier, a Y-axis motor servo amplifier, and a monitoring device 250 in its control unit. In addition, the current detection value of each axis motor is supplied to the monitoring device from the servo amplifier or the inverter. The tool wear information can also be output from the monitoring device to the control operation screen (panel) of the machine tool to display an alarm or warning message (not shown).

根據以上所述，可基於工具機之存在相關關係之複數軸之馬達之電流資訊推定工具之磨耗度，因此，可更有效率地實現各個工具更換時期之最佳化或維護之人工節省化。 According to the above, the electric power of the motor of the plural axes of the machine tool can be based on the existence of the correlation The wear level of the tool is estimated from the stream information, and therefore, the optimization of each tool replacement period or the labor saving of maintenance can be realized more efficiently.

不限於上述實施例，可進行各種變化。上述實施例係為了容易理解地說明本發明而例示者，不必限於具備所說明之所有構成者。 Not limited to the above-described embodiments, various changes can be made. The above-described embodiments are exemplified in order to explain the present invention in an easy-to-understand manner, and are not necessarily limited to those having all the components described.

又，可將某實施例之構成之一部分置換為其他實施例之構成，亦可對某實施例之構成添加其他實施例之構成。又，可對各實施例之構成之一部分進行刪除或進行其他構成之追加、置換。 In addition, a part of the configuration of a certain embodiment may be replaced with the configuration of another embodiment, and the configuration of another embodiment may be added to the configuration of a certain embodiment. In addition, a part of the constitution of each embodiment may be deleted or other constitutions may be added or replaced.

又，圖中所示之控制線或資訊線係表示考慮到說明所需者，並非表示製品上所需之所有控制線或資訊線。實際上亦可考慮將幾乎所有構成相互連接。對於上述實施例而言可能之變化係例如以下所述者。 In addition, the control lines or information lines shown in the figures represent what is required for the description, and do not represent all the control lines or information lines required on the product. In fact, it is also possible to consider interconnecting almost all components. Possible variations to the above-described embodiments are, for example, those described below.

(1)上述實施例中之控制部30、監視裝置40、150、160、170、190、210、220、230、250之硬體可由普通電腦實現，因此，亦可將圖2、圖3所示之演算法、與圖9所示之流程圖對應之程式等儲存於記憶媒體或經由傳輸路徑發佈。 (1) The hardware of the control unit 30 and the monitoring devices 40, 150, 160, 170, 190, 210, 220, 230, and 250 in the above embodiment can be realized by ordinary computers. The shown algorithm, the program corresponding to the flow chart shown in FIG. 9, etc. are stored in the memory medium or distributed through the transmission path.

(2)圖2、圖3所示之演算法或圖9所示之流程圖係於各實施例中作為使用程式之軟體處理進行了說明。然而，亦可將其一部分或全部置換為使用ASIC(Application Specific Integrated Circuit(特殊應用積體電路)，面向特定用途之IC(Integrated Circuit，積體電路))或FPGA(field- programmable gate array，場域可程式化閘陣列)等之硬體處理。 (2) The algorithm shown in FIG. 2 and FIG. 3 or the flowchart shown in FIG. 9 has been described as a software process using a program in each embodiment. However, a part or all of it can also be replaced by ASIC (Application Specific Integrated Circuit), IC (Integrated Circuit) for a specific purpose) or FPGA (field- programmable gate array, field programmable gate array) and other hardware processing.

(3)於圖10等之構成中設置有複數個變頻器，但變頻器22亦可僅設置1台。 (3) In the configuration of FIG. 10 and the like, a plurality of inverters are provided, but only one inverter 22 may be provided.

於上述實施例中，主要說明了對使用工具之加工適應之情形，但不僅於工具之加工時，於進行機器人之操作之情形時，亦可有效使用於偵測包括機器人之機器之狀態之異常。 In the above-mentioned embodiment, the situation of adapting to the processing of using tools is mainly described, but not only in the processing of tools, but also in the situation of robot operation, it can also be effectively used to detect abnormal state of the machine including the robot. .

於上述實施例中，以對變頻器、伺服放大器之適應例進行了說明，但亦可適應於DCBL(Direct Current Brushless，直流無刷)控制器等之電力轉換裝置。 In the above-mentioned embodiments, the application examples of the frequency converter and the servo amplifier are described, but they can also be applied to power conversion devices such as DCBL (Direct Current Brushless, DC brushless) controllers.

40:監視裝置 40: Monitoring device

42:馬達資訊運算部 42: Motor Information Calculation Department

44:特徵量運算部 44: Feature calculation section

45:狀態推定部 45: State Estimation Section

46:資料記憶部 46: Data Memory Department

47:異常判定部 47: Abnormal Determination Department

I_r1,I_r2:馬達轉矩電流 I _r1 ,I _r2 : motor torque current

ω_rs1,ω_rs2:機械頻率 ω _rs1 ,ω _rs2 : mechanical frequency

I_U1,I_W1:電流檢測值 I _U1 ,I _W1 : Current detection value

I_U2,I_W2:電流檢測值 I _U2 , I _W2 : Current detection value

Claims

一種監視裝置，其特徵在於具備：電流感測器，其對複數個驅動馬達之各者檢測二相之電流資訊；馬達資訊運算部，其根據上述電流資訊，運算對應之上述驅動馬達之轉矩電流或旋轉速度；特徵量運算部，其運算複數個上述驅動馬達中之與上述轉矩電流或上述旋轉速度相關之特徵量；狀態推定部，其基於複數個上述驅動馬達中處於相關關係中之上述驅動馬達之上述特徵量，推定機器狀態；資料記憶部，其記錄基準值資料；及異常判定部，其基於所推定之上述機器狀態與上述基準值資料，判定異常狀態。 A monitoring device is characterized by comprising: a current sensor for detecting two-phase current information for each of a plurality of driving motors; and a motor information computing unit for computing the torque of the corresponding driving motor according to the current information electric current or rotational speed; a feature quantity calculation unit that calculates a feature quantity related to the torque current or the rotational speed among the plurality of drive motors; a state estimation unit based on a correlation relationship among the plurality of drive motors The characteristic value of the drive motor is used for estimating a machine state; a data storage unit for recording reference value data; and an abnormality determination section for judging an abnormal state based on the estimated machine state and the reference value data.

如請求項1之監視裝置，其中上述機器狀態係表示上述驅動馬達驅動之工具之磨耗度。 The monitoring device of claim 1, wherein said machine state represents the degree of wear of a tool driven by said drive motor.

如請求項1之監視裝置，其中上述特徵量係上述驅動馬達之上述轉矩電流或上述驅動馬達之上述旋轉速度之最大值、標準偏差、平均值或快速傅立葉轉換(FFT)。 The monitoring device of claim 1, wherein the characteristic quantity is the maximum value, standard deviation, average value or fast Fourier transform (FFT) of the torque current of the drive motor or the rotational speed of the drive motor.

如請求項1之監視裝置，其中上述狀態推定部係基於複數個上述驅動馬達之上述特徵量中與上述機器狀態處於相關關係中之複數個上述特徵量、及對上述特徵量進行加權之貢獻度，推定上述機器狀態。 The monitoring device of claim 1, wherein the state estimating unit is a The machine state is estimated based on a plurality of the feature amounts in the plurality of the feature amounts of the drive motors that are in a correlation with the machine state, and a contribution degree weighting the feature amounts.

如請求項4之監視裝置，其中上述驅動馬達係包含主軸馬達與進給軸馬達，上述狀態推定部係基於處於上述相關關係中之上述主軸馬達與上述進給軸馬達之上述特徵量，推定上述機器狀態。 The monitoring device according to claim 4, wherein the drive motor includes a spindle motor and a feed axis motor, and the state estimating unit estimates the state based on the feature quantities of the spindle motor and the feed axis motor in the correlation relationship. Machine state.

如請求項1之監視裝置，其中上述異常判定部係於檢測到異常之情形時，對控制上述驅動馬達之控制部輸出控制指令。 The monitoring device of claim 1, wherein the abnormality determination unit outputs a control command to a control unit that controls the drive motor when an abnormality is detected.

如請求項1之監視裝置，其中上述特徵量運算部係將1台或存在相關關係之複數台上述驅動馬達之電流值或旋轉速度值設為擷取上述特徵量之觸發點，運算指定區間之上述特徵量。 The monitoring device according to claim 1, wherein the feature quantity calculation unit sets the current value or rotational speed value of one or a plurality of related drive motors as a trigger point for extracting the feature quantity, and calculates the value of the specified interval. the above-mentioned feature quantities.

如請求項4之監視裝置，其中上述狀態推定部係將固定加工品之工作台之旋轉軸之上述驅動馬達及傾斜角之軸之上述驅動馬達之上述特徵量包括在內地推定上述機器狀態。 The monitoring device of claim 4, wherein the state estimating unit is a The above-mentioned machine state is estimated by including the above-mentioned characteristic quantities of the above-mentioned driving motor of the rotating shaft of the table for fixing the workpiece and the above-mentioned driving motor of the shaft of the inclination angle.

一種伺服放大器，其特徵在於具有：如請求項1之監視裝置，其輸入來自其他伺服放大器之上述電流資訊。 A servo amplifier is characterized by having: the monitoring device according to claim 1, which inputs the above-mentioned current information from other servo amplifiers.

一種產業用控制器，其特徵在於具有：如請求項1之監視裝置；及資訊收集部，其收集來自複數個伺服放大器或變頻器之上述電流資訊。 An industrial controller characterized by comprising: the monitoring device according to claim 1; and an information collecting section that collects the above-mentioned current information from a plurality of servo amplifiers or inverters.

一種工具機，其特徵在於：於其控制部具備：複數軸之馬達用之變頻器或伺服放大器；及如請求項1之監視裝置。 A machine tool characterized in that: a control unit is provided with: an inverter or a servo amplifier for motors of plural axes; and the monitoring device according to claim 1.

一種監視方法，其特徵在於：對複數個驅動馬達之各者，檢測二相之電流資訊，根據上述電流資訊，運算對應之上述驅動馬達之轉矩電流或旋轉速度，運算複數個上述驅動馬達中之與上述轉矩電流或上述旋轉速度相關之特徵量，基於複數個上述驅動馬達中處於相關關係中之上述驅動馬達之上述特徵量，推定機器狀態，基於預先記錄之基準值資料與所推定之上述機器狀態，判定異常狀態。 A monitoring method, which is characterized in that: for each of a plurality of driving motors, detecting two-phase current information, calculating the torque current or rotational speed of the corresponding driving motor according to the current information, and calculating among the plurality of driving motors. The characteristic quantity related to the above-mentioned torque current or the above-mentioned rotational speed, Based on the characteristic quantities of the drive motors in the correlation relationship among the plurality of drive motors, a device state is estimated, and an abnormal state is determined based on pre-recorded reference value data and the estimated device state.