JP2005074545A - Condition monitoring device for machine tool - Google Patents

Condition monitoring device for machine tool Download PDF

Info

Publication number
JP2005074545A
JP2005074545A JP2003305721A JP2003305721A JP2005074545A JP 2005074545 A JP2005074545 A JP 2005074545A JP 2003305721 A JP2003305721 A JP 2003305721A JP 2003305721 A JP2003305721 A JP 2003305721A JP 2005074545 A JP2005074545 A JP 2005074545A
Authority
JP
Japan
Prior art keywords
spindle
vibration
event rate
machine tool
bearing
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
JP2003305721A
Other languages
Japanese (ja)
Inventor
Shihou Katsumata
志芳 勝又
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Okuma Corp
Original Assignee
Okuma Corp
Okuma Machinery Works Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Okuma Corp, Okuma Machinery Works Ltd filed Critical Okuma Corp
Priority to JP2003305721A priority Critical patent/JP2005074545A/en
Publication of JP2005074545A publication Critical patent/JP2005074545A/en
Pending legal-status Critical Current

Links

Images

Landscapes

  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
  • Machine Tool Sensing Apparatuses (AREA)

Abstract

<P>PROBLEM TO BE SOLVED: To accurately detect the abnormal or degraded condition of a spindle by sensing with an AE sensor to determine the damage of the spindle and to display an alarm. <P>SOLUTION: Upon receiving a spindle rotation command 57 and a feed shaft driving command 56, vibration data is measured using the AE sensor 51, an amplifier 52 and a band-pass filter 53. The number of the data exceeding the threshold obtained from spindle rotation information 41 is counted by a level counting circuit. The count number and an alarm level are compared to determine the condition of the spindle, and if necessary, the alarm is displayed on an alarm display 55. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

この発明は、工作機械において、回転する主軸の状態を監視する状態監視装置に関する。   The present invention relates to a state monitoring device that monitors the state of a rotating spindle in a machine tool.

工作機械において、回転する主軸の状態を監視する装置として、一般的なものの一つに、軸受部近傍の温度を計測する装置がある。この装置では、あらかじめ主軸の軸受部近傍に温度を計測するセンサを固定し、主軸が回転することによって発生する軸受発熱による温度上昇をそのセンサで読み取る。   As a general device for monitoring the state of a rotating spindle in a machine tool, there is a device for measuring the temperature in the vicinity of a bearing portion. In this apparatus, a sensor for measuring the temperature is fixed in the vicinity of the bearing portion of the main shaft in advance, and the temperature rise due to bearing heat generated by the rotation of the main shaft is read by the sensor.

別の監視装置としては、主軸の振動を計測する装置がある。この装置では、主軸の任意の位置に振動を計測するための振動センサを固定し、主軸が回転することによって発生する振動をそのセンサで読み取る。   As another monitoring device, there is a device for measuring the vibration of the main shaft. In this apparatus, a vibration sensor for measuring vibration is fixed at an arbitrary position of the main shaft, and vibration generated by the rotation of the main shaft is read by the sensor.

このような監視装置において、主軸の状態を正確に判断するには様々な問題点があった。   In such a monitoring device, there are various problems in accurately determining the state of the spindle.

まず、軸受部近傍の温度を計測する装置であるが、軸受の発熱量は、軸受の潤滑状態に大きく左右される。そのため、軸受潤滑のために外部から供給される油の量やその供給方法、あるいは軸受にあらかじめ封入されている潤滑用グリースの軸受への付着状態によって、油の攪拌抵抗に大きな違いが現れ、その結果、温度上昇に差が出る。   First, a device for measuring the temperature in the vicinity of the bearing portion. The amount of heat generated by the bearing is greatly influenced by the lubrication state of the bearing. Therefore, a large difference appears in the oil agitation resistance depending on the amount of oil supplied from the outside for bearing lubrication, its supply method, or the state of adhesion of the lubricating grease sealed in the bearing to the bearing. As a result, there is a difference in temperature rise.

また、温度の計測そのものにおいても限界がある。軸受において発熱を起こすのは、転動体と内輪・外輪との接触部である。しかし、実際に発熱を起こしている転動体接触部の温度は直接計測出来ないため、どうしても介在物をとおして温度を計測することとなる。そのため、軸受が発熱してから温度計測する場所に温度が伝わってくるまでに時間的な遅れが出る。合わせて、発熱部から温度計測部まで熱が伝わってくる間に熱が周辺に拡散してしまい、計測部での温度変化はゆるやかになる。結果、実際の発熱状態と計測される温度変化に違いが生じる。   There is also a limit in the temperature measurement itself. It is the contact portion between the rolling elements and the inner and outer rings that generates heat in the bearing. However, since the temperature of the rolling element contact portion that actually generates heat cannot be directly measured, the temperature is inevitably measured through the inclusions. Therefore, there is a time delay until the temperature is transmitted to the place where the temperature is measured after the bearing generates heat. In addition, while heat is transmitted from the heat generating part to the temperature measuring part, the heat is diffused to the surroundings, and the temperature change at the measuring part becomes gentle. As a result, a difference occurs between the actual heat generation state and the measured temperature change.

そのため、軸受がかなりダメージを受け、発熱量がかなり多くなった状態では、初期状態からの違いを捉えることが出来るが、軸受異常の初期で発熱がわずかな状態では、その変化を捉えることが出来ない。   Therefore, when the bearing is significantly damaged and the amount of heat generation is considerably large, the difference from the initial state can be detected, but when the heat generation is slight at the initial stage of the bearing abnormality, the change can be detected. Absent.

次に、振動の計測による状態監視についての問題点を示す。   Next, problems concerning state monitoring by vibration measurement will be described.

一般的に使用される振動センサにおいて計測できる振動周波数は、数十kHz以下の振動である。軸受に生じたキズや異物のかみ込みによる振動、アンバランスやミスアライメントなど、比較的振動が大きく出て、発生する周波数もそれほど高くない主軸振動は、このような振動センサを用いて計測を行なうことが出来る。   A vibration frequency that can be measured in a vibration sensor that is generally used is vibration of several tens of kHz or less. The main shaft vibration that generates relatively large vibrations such as vibrations caused by scratches and foreign object biting in the bearing, imbalance and misalignment, and the generated frequency is not so high, is measured using such a vibration sensor. I can do it.

それに対し、発生する振動が非常に微小でしかも超高周波の振動を計測するためにはAEセンサを用いる。このセンサを用いれば、物体どうしが接触した時に発生する超高周波のAE振動が検知でき、潤滑不良などの状態変化も捉えることが可能となる。   On the other hand, an AE sensor is used in order to measure a very high frequency vibration that is very small. By using this sensor, it is possible to detect AE vibration of super-high frequency that occurs when objects come into contact with each other, and it is also possible to capture state changes such as poor lubrication.

しかし、AE振動はごく微弱な超高周波振動として発生するため、軸受部以外の部分から発生する別のAE振動レベルが大きいと、計測される振動は軸受部以外から生じた振動に隠れてしまう。また、AE振動そのものは非常に不規則で、レベルも変動し、また転動体回転速度によっても振動の大きさが変わるため、計測された振動データの評価が難しい。   However, since the AE vibration is generated as a very weak super-high frequency vibration, if another AE vibration level generated from a portion other than the bearing portion is large, the measured vibration is hidden by the vibration generated from other than the bearing portion. Further, the AE vibration itself is very irregular, the level fluctuates, and the magnitude of the vibration changes depending on the rotational speed of the rolling element, so that it is difficult to evaluate the measured vibration data.

実際の工作機械主軸の軸受損傷は、軸受異常が比例的に進行して破壊に至るわけではなく、潤滑不良を伴う初期の軽微な異常が緩やかに続き、ある時急激に損傷が激化し破壊に至るケースが多い。そのため、主軸の状態を監視し、損傷の進行および寿命を予測する上では、ダメージが大きくなる前の、初期の異常状態をなるべく正確に把握できる監視装置が必要とされる。   In actual machine tool spindle bearing damage, the bearing abnormality does not progress proportionally and does not lead to destruction, but the initial minor abnormality with poor lubrication continues slowly, and at some point the damage suddenly intensifies and breaks down. There are many cases. Therefore, in order to monitor the state of the spindle and predict the progress and life of the damage, a monitoring device that can grasp the initial abnormal state as accurately as possible before the damage increases is required.

上記したように、温度センサや一般的な振動センサを用いた主軸の状態監視では、潤滑不良など軸受のわずかな状態変化を捉えることが出来ないために、軸受の劣化を早期段階で検知することが出来ない。また、AEセンサを用いた単純な計測では、主軸軸受以外から発生するAE振動のせいで軸受の状態変化が観測できなかったり、発生するAE振動のレベルが不安定なために軸受の状態変化が判断できなかったりと、使用上不便な点が多い。   As described above, since the spindle state monitoring using temperature sensors and general vibration sensors cannot detect slight changes in the bearing state such as poor lubrication, it is possible to detect bearing deterioration at an early stage. I can't. In simple measurement using an AE sensor, the change in the state of the bearing cannot be observed due to the AE vibration generated from other than the main shaft bearing, or the change in the state of the bearing occurs because the level of the generated AE vibration is unstable. There are many inconveniences in use, such as being unable to judge.

AEを用いた工作機械の状態監視装置としては、工具の折損などを監視するものが知られているが(特許文献1、特許文献2)、これを、主軸軸受の異常を検出するために適用することはできない。
特許第2583185号公報 特開平6−218655号公報
As a machine tool state monitoring device using AE, a device for monitoring breakage of a tool or the like is known (Patent Document 1, Patent Document 2), and this is applied to detect an abnormality of a spindle bearing. I can't do it.
Japanese Patent No. 2583185 JP-A-6-218655

そこで、本発明は上記課題を解決し、工作機械の状態監視装置において、軸受の状態変化を早期段階から正確に観測し、その劣化の進行度合いを正確に判断できるようにすることを目的とする。   SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to solve the above-described problems and to accurately observe a change in the state of a bearing from an early stage and accurately determine the degree of progress of the deterioration in a state monitoring device for a machine tool. .

上記課題を解決するため、請求項1の発明は、主軸の状態を監視する手段として、主軸のあらかじめ設定された位置に取り付けられたAE振動計測用のセンサを用いる。   In order to solve the above problems, the invention of claim 1 uses, as means for monitoring the state of the main shaft, an AE vibration measurement sensor attached to a preset position of the main shaft.

また、微弱な振動信号を、より信頼性が高く、なるべく外乱の影響を受けない状態で測定するには、切削加工中で加工振動が発生している状態や、主軸回転開始直後で潤滑が安定していない時の計測を避けたほうが好ましい。そこで、請求項2または3の発明は、主軸は安定して回転しているが切削加工は行われていない状態を機械の制御装置で判断し、その時のAE振動データを計測値として取り込む。   Also, in order to measure weak vibration signals with higher reliability and as little influence as possible from disturbances, lubrication is stable when machining vibration occurs during cutting or immediately after the start of spindle rotation. It is better to avoid measurement when not. Therefore, in the invention of claim 2 or 3, the state in which the main shaft is stably rotated but the cutting process is not performed is judged by a machine control device, and the AE vibration data at that time is taken in as a measured value.

主軸は回転しているが送り軸は動いていない状態とは、一日の始めに機械を立ち上げて主軸の暖気運転を行っている状態や、加工終了後に主軸を停止させる直前などを示す。このような状態での計測を行うために、主軸の回転指令、停止指令、送り軸の切削送り指令を認識し、さらに、主軸の回転開始からの経過時間をカウントさせる。   The state in which the main shaft is rotating but the feed shaft is not moving indicates a state in which the machine is started up at the beginning of the day and the main shaft is warmed up, or just before the main shaft is stopped after machining. In order to perform measurement in such a state, a spindle rotation command, a stop command, and a feed axis cutting feed command are recognized, and an elapsed time from the start of rotation of the spindle is counted.

具体的には、主軸の回転指令と送り軸の切削送り指令を検知し、主軸回転開始からの時間をカウントしておいて、あらかじめ設定してあるカウント時間が経過しているかどうかをみる。それにより、主軸が安定して回転しているが切削加工は行われていないことが判断されれば計測を行う。また、送り軸の切削送り指令が実施されている状態においても、次に主軸停止指令が来るのであれば、その直前には実際の切削は完了しているので、主軸停止指令が実行させる前に計測を行う。   Specifically, the spindle rotation command and the feed shaft cutting feed command are detected, the time from the start of the spindle rotation is counted, and it is checked whether a preset count time has elapsed. As a result, if it is determined that the spindle rotates stably but no cutting is performed, measurement is performed. Even when the feed axis cutting feed command is being executed, if the next spindle stop command comes, the actual cutting has been completed immediately before that, so before the spindle stop command is executed, Measure.

このような状態で取り込まれたデータを時系列で比較し、そのレベルの変化によって主軸の劣化度合いを判定する。   Data captured in such a state is compared in time series, and the degree of deterioration of the spindle is determined by the change in the level.

また、取り込まれたデータのレベルにより主軸の劣化度合いを判定するためには、請求項4の発明のように、AE振動の事象率を計測し、その計測には回転数毎にしきい値電圧を設ける。   In order to determine the degree of deterioration of the spindle based on the level of the acquired data, as in the invention of claim 4, the event rate of AE vibration is measured, and the threshold voltage is set for each revolution. Provide.

軸受の状態が同じでも回転している回転数が異なれば、発生するAE振動のレベルも違ってくる。常に同じ回転数で回っている状態で振動データが計測出来れば、単純にそのデータを比較すれば軸受の劣化状態を判断することが出来る。しかし、毎回計測を行なう際の回転数が異なる場合、直接計測されたデータどうしを比較することが出来ない。そこで、あらかじめ設定してある回転数ごとのしきい値電圧からその状態における事象率をカウントすれば、どの回転数で計測しても一連の結果として主軸の劣化度合いの判定に使用できるようになる。   Even if the state of the bearing is the same, if the number of rotations is different, the level of AE vibration that occurs is also different. If vibration data can be measured while always rotating at the same rotational speed, the deterioration state of the bearing can be determined by simply comparing the data. However, if the number of rotations when measuring each time is different, the directly measured data cannot be compared. Therefore, if the event rate in that state is counted from a preset threshold voltage for each rotation speed, it can be used to determine the deterioration degree of the spindle as a series of results regardless of the rotation speed. .

さらに、計測されたデータによる判定を正確に行うために、請求項5の発明のように、計測されたAE振動結果を計測時間と合わせて記録しておき、データの比較を行う。その際、軸受異常かどうかを判断させるために、最新のAE振動事象率測定結果と、現在から過去にさかのぼって測定された設定回数分のAE振動事象率測定結果の平均値を用い、異常判断用の評価値と比べることで異常の判断を行う。1回の測定結果だけで判断を行わないのは、突発的な潤滑異常などを検知した場合、それだけで軸受寿命だと判断してしまわないためである。   Further, in order to accurately perform the determination based on the measured data, the measured AE vibration result is recorded together with the measurement time as in the invention of claim 5 and the data is compared. At that time, in order to determine whether or not the bearing is abnormal, the latest AE vibration event rate measurement result and the average value of the AE vibration event rate measurement result for the set number of times measured from the present to the past are used to determine the abnormality. The abnormality is judged by comparing with the evaluation value. The reason for not making a judgment based on a single measurement result is that if a sudden lubrication abnormality or the like is detected, it is not possible to judge that the bearing life is alone.

軸受の異常が徐々に進行してくると、平均事象率もだんだん上がってくる。そして、その値が異常判断用の評価値を超えた場合、軸受寿命と判断し、それを外部にアラームとして表示させ、加工の停止や主軸の回転停止などの措置を取る。また、平均値は評価値を超えていないが最新の計測においてのみ計測結果が評価値を超える場合は、寿命ではなくて主軸潤滑ユニットの故障など突発的な異常の可能性があるため、その旨を外部にアラームとして表示させる。作業者はその表示を受け、機械の点検などを行うこととなる。   As bearing abnormalities gradually progress, the average event rate also increases. If the value exceeds the evaluation value for abnormality determination, it is determined that the bearing life is reached, and this is displayed externally as an alarm, and measures such as machining stop and spindle rotation stop are taken. Also, if the average value does not exceed the evaluation value but the measurement result exceeds the evaluation value only in the latest measurement, there is a possibility of a sudden abnormality such as a failure of the spindle lubrication unit, not the life, so that Is displayed externally as an alarm. The worker receives the display and inspects the machine.

以上詳述したように、請求項1の発明によれば、切削中など主軸以外からの振動が多く発生する状態ではない、安定した主軸回転状態でのみ振動を計測することにより、主軸の状態を判断するための信頼性のあるデータ取りを行なうことが出来る。また請求項2の発明によれば、データを取るために主軸を同じ回転数で回さなくても、回転数毎に設定されたしきい値と比較することで、どの回転数で計測されたデータも同じように判断に使用することが出来る。さらに請求項3の発明によれば、計測されたデータを平均化させることで、突発的な異常か軸受寿命による劣化かを見極め、主軸の状態変化を適確に判断することが出来るようになる。   As described in detail above, according to the first aspect of the present invention, the state of the main shaft is determined by measuring the vibration only in a stable main shaft rotation state, not in a state in which a large amount of vibration is generated from other than the main shaft such as during cutting. Reliable data collection for determination can be performed. Further, according to the invention of claim 2, even if the main shaft is not rotated at the same rotational speed in order to take data, it is measured at any rotational speed by comparing with a threshold value set for each rotational speed. Data can be used for judgment in the same way. Further, according to the invention of claim 3, by averaging the measured data, it is possible to determine whether a sudden abnormality or deterioration due to the bearing life and to accurately determine the change in the state of the spindle. .

以下、この発明の実施形態を、図を参照して説明する。   Embodiments of the present invention will be described below with reference to the drawings.

図1はAEセンサを取り付けた主軸の例である。図1において、主軸1の周囲下方4カ所と上方後部1カ所に転がり軸受6a〜6d、7が設けられ、固定された円筒状の固定ハウジング2と3内に回転支持され、固定ハウジング2と3は主軸頭4に固定され、主軸頭4は主軸台などの機械本体5に固定されている。尚、前側の転がり軸受は、例えば深溝玉軸受、アンギュラ玉軸受、円錐ころ軸受等、ラジアル荷重と少なくとも一方向のスラスト荷重が受けられるもの、後ろ側の軸受はラジアル荷重が受けられるコロ軸受や深溝玉軸受などが用いられている。   FIG. 1 shows an example of a main shaft to which an AE sensor is attached. In FIG. 1, rolling bearings 6 a to 6 d, 7 are provided at four lower positions around the main shaft 1 and one upper rear portion, and are rotatably supported in fixed cylindrical fixed housings 2 and 3. Is fixed to the spindle head 4, and the spindle head 4 is fixed to a machine body 5 such as a spindle head. The front rolling bearings are, for example, deep groove ball bearings, angular ball bearings, tapered roller bearings, etc. that can receive radial load and at least one direction of thrust load, and the rear bearings are roller bearings or deep grooves that can receive radial load. Ball bearings are used.

前側の転がり軸受6a〜6dと後ろ側の転がり軸受7の間には、主軸1を回転させるための駆動装置としてビルトイン型の電動機9が設けられ、この電動機9は主軸1の外周に設けられたロータ9aと、その周囲の主軸頭4の内周に設けられたステータ9bとから構成されている。   Between the front rolling bearings 6 a to 6 d and the rear rolling bearing 7, a built-in type electric motor 9 is provided as a driving device for rotating the main shaft 1, and the electric motor 9 is provided on the outer periphery of the main shaft 1. The rotor 9a and a stator 9b provided on the inner periphery of the spindle head 4 around the rotor 9a.

また、主軸1内部にはドローバー8が設けられ、ドローバー8は圧縮バネ12の引き込み力によりホルダ把持具13を介してホルダ10を主軸1に引き込んで固定保持されている。そして、ホルダ10先端には、工具11が取り付き、この工具によってワークが加工される。   In addition, a draw bar 8 is provided inside the main shaft 1, and the draw bar 8 is fixedly held by pulling the holder 10 into the main shaft 1 via the holder gripping tool 13 by the pulling force of the compression spring 12. A tool 11 is attached to the tip of the holder 10, and a workpiece is machined by this tool.

そして、AEセンサ15は、固定ハウジング2に取り付けられている。また、14は軸受6a〜6dの外輪を抑えている蓋である。AEセンサを取り付ける場所として一番良いのは軸受そのものである。しかし実際にはスペースの関係上などから軸受に直接AEセンサを固定することは難しい。よって、軸受を固定しているハウジングなどに取り付けることとなる。   The AE sensor 15 is attached to the fixed housing 2. Reference numeral 14 denotes a lid that holds the outer rings of the bearings 6a to 6d. The best place to install the AE sensor is the bearing itself. However, in practice, it is difficult to fix the AE sensor directly to the bearing because of space limitations. Therefore, it attaches to the housing etc. which are fixing the bearing.

図2は、AE振動計測実行タイミングのフローチャートである。主軸の回転が安定している状態で、なおかつ切削を行っていない状態での計測を行うために、次のように計測タイミングを決定する。   FIG. 2 is a flowchart of AE vibration measurement execution timing. In order to perform measurement in a state in which the rotation of the main shaft is stable and no cutting is performed, the measurement timing is determined as follows.

最初に、加工する機械の電源が入れられた状態で、主軸の起動を判別する。主軸が起動された場合、あらかじめ求めてある設定された時間の間、タイマーを働かせる。この時間によって、主軸が回転を開始してから潤滑が安定し、定常状態になるのを待つ。実際の計測においては回転数によっても異なるが、タイマーの設定時間としては数分程度になる。   First, the start of the spindle is determined with the machine to be machined turned on. When the spindle is activated, the timer is activated for a preset time that has been obtained in advance. This time waits for the lubrication to stabilize and to reach a steady state after the main shaft starts rotating. In actual measurement, although it depends on the number of rotations, the set time of the timer is about several minutes.

設定されたタイマー時間が経過した後に、切削送りが行われていなければ、AEの計測を開始する。そして計測された1回分のデータは保存され、次の計測に入る。基本的にはこれを繰り返し計測を行っていく。   If cutting feed is not performed after the set timer time has elapsed, AE measurement is started. Then, the measured data for one time is stored, and the next measurement is started. Basically, this is repeated.

それに対し、切削送り指令が入った場合は、加工が行われていると判断し、計測は行わない。そして、切削送り指令停止後、まだ主軸が回っていれば、その状態でのAEの計測を行う。しかし、主軸回転停止指令が入るようならば、主軸停止指令が実行される直前に1回だけ計測を行う。この状態では、指令的には切削送りが終了していない状態があるが、実際の加工ではワークから少し離れた位置まで軸を動かしてから主軸を止めるため、最後の数秒は工具とワークは接触していない。よって、実質的に主軸だけが回っている状態での計測になる。   On the other hand, when a cutting feed command is entered, it is determined that machining is being performed and measurement is not performed. If the spindle is still rotating after the cutting feed command is stopped, AE is measured in that state. However, if a spindle rotation stop command is entered, measurement is performed only once just before the spindle stop command is executed. In this state, there is a state that cutting feed is not finished in command, but in actual machining, the spindle is stopped after moving the axis to a position slightly away from the workpiece, so the tool and the workpiece are in contact for the last few seconds. Not done. Therefore, the measurement is performed in a state where only the main shaft is rotating.

このようにして、計測を繰り返してデータを蓄積していく。   In this way, measurement is repeated and data is accumulated.

図3は、AE計測で事象率をカウントする時のしきい値の決め方を示した概念図である。   FIG. 3 is a conceptual diagram showing how to determine a threshold when the event rate is counted by AE measurement.

図で、横軸が時間経過、縦軸がAEセンサからとり込まれる電圧信号である。事象率の計測においては、あらかじめ設定してある測定周期の間に取り込まれた電圧信号において、しきい値電圧を超えた電圧信号の回数をカウントし、その計測における事象率の値とする。   In the figure, the horizontal axis represents time, and the vertical axis represents a voltage signal taken from the AE sensor. In the measurement of the event rate, the number of voltage signals exceeding the threshold voltage in the voltage signal taken in during a preset measurement cycle is counted and used as the event rate value in the measurement.

その際、事象率を求めるしきい値を固定にしておくと、回転数が比較的低く、発生するAE振動レベルが小さい時は事象率は少なく、回転数が高く発生するAE振動レベルが大きい時は、事象率は多くカウントされてしまう。同じ回転数でのみ計測を行うのであればそれでも問題ないが、計測毎に回転数が違うと、データの比較が出来なくなってしまう。よって、あらかじめ回転数によるしきい値を変えておいて、例えば図のように低い回転数の時のしきい値電圧をAと設定し、高い回転数の時のしきい値電圧をBとして、Aより高い電圧に設定し、同じレベルの事象率が計測されるようにしておけば、回転数には影響されずに計測データを比較することが出来る。   At this time, if the threshold value for determining the event rate is fixed, the rotation speed is relatively low, the generated AE vibration level is small, the event rate is small, and the high rotation speed is generated and the AE vibration level is large. The event rate will be counted a lot. If the measurement is performed only at the same number of rotations, there is no problem, but if the number of rotations is different for each measurement, the data cannot be compared. Therefore, by changing the threshold value based on the rotational speed in advance, for example, as shown in the figure, the threshold voltage at the low rotational speed is set to A, and the threshold voltage at the high rotational speed is set to B. If the voltage is set higher than A and the event rate at the same level is measured, the measurement data can be compared without being influenced by the rotational speed.

図4は、実際AE振動を計測する回路を示す。   FIG. 4 shows a circuit for measuring actual AE vibration.

最初に、工作機械に対し所定の動作を実行させるためにプログラムや手動操作によって、主軸回転指令57や送り軸駆動指令56が工作機械の制御装置40に与えられる。指令が与えられると、制御装置40は指令内容に合わせ、主軸回転情報41と送り軸駆動情報42を発信する。   First, in order to cause the machine tool to execute a predetermined operation, a spindle rotation command 57 and a feed shaft drive command 56 are given to the machine tool control device 40 by a program or manual operation. When the command is given, the control device 40 transmits the spindle rotation information 41 and the feed shaft drive information 42 according to the command content.

主軸回転情報41と送り軸駆動情報42をもとに、前述した計測開始判断回路43で、主軸が安定して回転していて尚且つワークは加工していない状態を判断して、計測開始指令を発信する。   Based on the spindle rotation information 41 and the feed axis drive information 42, the measurement start determination circuit 43 described above determines whether the spindle is rotating stably and the workpiece is not processed, and a measurement start command is issued. To send.

主軸の任意位置に取り付けてあるAEセンサ51によって検知され、増幅器52によって増幅、バンドパスフィルタ53によって必要な周波数帯域のみの信号として処理された振動データは、計測開始指令を受け、振動データ取り込み回路44に入力される。   Vibration data detected by an AE sensor 51 attached to an arbitrary position of the main shaft, amplified by an amplifier 52, and processed as a signal of only a necessary frequency band by a bandpass filter 53 receives a measurement start command, and receives a vibration data capturing circuit. 44.

主軸回転情報41は、しきい値設定回路46にも送られる。しきい値設定回路46では、前述したようにあらかじめ回転数毎に設定してあるしきい値データ45と、主軸回転数情報41を受けて、現在の運転状態でのしきい値を発生させる。   The spindle rotation information 41 is also sent to the threshold setting circuit 46. The threshold value setting circuit 46 receives the threshold value data 45 set in advance for each rotational speed and the spindle rotational speed information 41 as described above, and generates a threshold value in the current operating state.

決定されたしきい値に対して、レベルカウント回路47では、振動データ取り込み回路44に入力された振動データが、あらかじめ設定してある測定周期の間に、何回しきい値を超えたかをカウントする。そしてカウント数はカウント数記録回路48の中に計測時間と合わせてデータとして記録される。   In response to the determined threshold value, the level count circuit 47 counts how many times the vibration data input to the vibration data capturing circuit 44 exceeds the threshold value during a preset measurement cycle. . The count number is recorded as data in the count number recording circuit 48 together with the measurement time.

アラームレベル比較回路49は、得られた最新のカウント数とそれ以前に計測された任意の回数分のカウント数とを合わせた平均カウント数を計算し、平均カウント数の値があらかじめ設定してあるアラームレベルより大きくなると、軸受寿命と判断する。そして、アラーム表示器55では、アラーム信号を受けて、主軸寿命であることを表示する。合わせて、加工の停止や主軸の回転停止などの措置を取る。また、平均カウント数はアラームレベルを超えていないが最新の計測においてのみカウント数がアラームレベルを超える場合は、寿命ではなくて主軸潤滑ユニットの故障など突発的な異常として、その旨をアラーム表示器55に伝える。アラーム表示器55ではそれを受けてアラーム信号を発生させる。   The alarm level comparison circuit 49 calculates the average count number obtained by combining the latest count number obtained and the count number for any number of times measured before that, and the value of the average count number is preset. When the alarm level is exceeded, it is determined that the bearing life is reached. Then, the alarm display 55 receives an alarm signal and displays that the spindle life is reached. At the same time, take measures such as stopping machining and stopping spindle rotation. Also, if the average count does not exceed the alarm level, but the count exceeds the alarm level only in the latest measurement, it is not a service life but a sudden abnormality such as a spindle lubrication unit failure. Tell 55. In response to this, the alarm display 55 generates an alarm signal.

AEセンサを取り付けた主軸の例である。It is an example of the main axis | shaft which attached the AE sensor. AE振動を計測するタイミングを決めるフローチャートである。It is a flowchart which determines the timing which measures AE vibration. 回転数毎のしきい値を求める考え方を示した図である。It is the figure which showed the idea which calculates | requires the threshold value for every rotation speed. 実際に計測を行う回路を示した図である。It is the figure which showed the circuit which actually measures.

符号の説明Explanation of symbols

51…AEセンサ、52…増幅器、53…バンドパスフィルタ、40…制御装置、55…アラーム表示器、44…振動データ取り込み回路、46…しきい値設定回路、47…レベルカウント回路、49…アラームレベル比較回路 DESCRIPTION OF SYMBOLS 51 ... AE sensor 52 ... Amplifier 53 ... Band pass filter 40 ... Control device 55 ... Alarm indicator 44 ... Vibration data acquisition circuit 46 ... Threshold setting circuit 47 ... Level count circuit 49 ... Alarm Level comparison circuit

Claims (5)

工作機械の主軸において、軸受近傍にAEセンサを固定し、主軸回転中に発生するAE振動を検出する状態監視装置であって、主軸回転指令、送り軸駆動指令などの工作機械の駆動指令に基づいてAE振動の検出を行うことを特徴とする工作機械の状態監視装置。 A state monitoring device that detects an AE vibration generated during rotation of a spindle by fixing an AE sensor in the vicinity of the bearing on the spindle of the machine tool, and is based on a drive command of the machine tool such as a spindle rotation command and a feed shaft drive command. A machine tool state monitoring device characterized by detecting AE vibration. AE振動を計測するタイミングとして、主軸回転開始からの経過時間をカウントし、あらかじめ設定してある主軸回転時間経過後にAE振動の計測を開始することを特徴とする、請求項1記載の工作機械の状態監視装置。 2. The machine tool according to claim 1, wherein an elapsed time from the start of spindle rotation is counted as a timing for measuring AE vibration, and measurement of AE vibration is started after a preset spindle rotation time has elapsed. Condition monitoring device. AE振動を計測するタイミングとして、送り軸駆動指令の開始からの経過時間や移動距離、または送り軸駆動指令終了までの経過時間や移動距離を認識し、あらかじめ設定してある送り軸駆動状態でAE振動の計測を開始することを特徴とする、請求項1または2に記載の工作機械の状態監視装置。 As the timing for measuring the AE vibration, the elapsed time and movement distance from the start of the feed axis drive command, or the elapsed time and movement distance until the end of the feed axis drive command are recognized, and the AE is set in the preset feed axis drive state. 3. The machine tool state monitoring apparatus according to claim 1, wherein vibration measurement is started. 計測されたAE振動波形を事象率としてカウントする際に、主軸の回転数毎にしきい値となる電圧レベルを設け、主軸回転中に発生するAE振動を、その回転数におけるしきい値電圧と比較し事象率を計算することを特徴とする、請求項1〜3のいずれか1つに記載の工作機械の状態監視装置。 When the measured AE vibration waveform is counted as an event rate, a voltage level serving as a threshold is provided for each rotation speed of the spindle, and the AE vibration generated during the rotation of the spindle is compared with the threshold voltage at that rotation speed. 4. The machine tool state monitoring apparatus according to claim 1, wherein an event rate is calculated. 計測されたAE振動波形の事象率をカウントし、軸受の異常を判断する際、計測された事象率とそれ以前に計測された任意の回数分の事象率とを合わせた平均事象率を計算し、1回の事象率と平均事象率の値をあらかじめ設定してある軸受異常事象率レベルと比較することで、主軸の状態を判断することを特徴とする、請求項1〜4のいずれか1つに記載の工作機械の状態監視装置。
When measuring the event rate of the measured AE vibration waveform and judging the bearing abnormality, calculate the average event rate that combines the measured event rate and the event rate for any number of times measured before that. The state of the main shaft is determined by comparing the value of the single event rate and the average event rate with a preset bearing abnormal event rate level. Machine tool condition monitoring device described in 1.
JP2003305721A 2003-08-29 2003-08-29 Condition monitoring device for machine tool Pending JP2005074545A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP2003305721A JP2005074545A (en) 2003-08-29 2003-08-29 Condition monitoring device for machine tool

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
JP2003305721A JP2005074545A (en) 2003-08-29 2003-08-29 Condition monitoring device for machine tool

Publications (1)

Publication Number Publication Date
JP2005074545A true JP2005074545A (en) 2005-03-24

Family

ID=34408991

Family Applications (1)

Application Number Title Priority Date Filing Date
JP2003305721A Pending JP2005074545A (en) 2003-08-29 2003-08-29 Condition monitoring device for machine tool

Country Status (1)

Country Link
JP (1) JP2005074545A (en)

Cited By (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2008286636A (en) * 2007-05-17 2008-11-27 Aisin Aw Co Ltd Inspection method and device
JP2010181151A (en) * 2009-02-03 2010-08-19 Okuma Corp Method and device for determining lubricated state of rolling bearing
CN103419076A (en) * 2012-05-17 2013-12-04 大隈株式会社 Machining vibration suppressing method and machining vibration suppressing apparatus for machine tool
JP2016170085A (en) * 2015-03-13 2016-09-23 日本精工株式会社 Abnormality diagnostic device and abnormality diagnostic method
DE102016005892A1 (en) 2015-05-19 2016-11-24 Fanuc Corporation Anomaly detecting device having a function of detecting an abnormality of a machine tool and an abnormality detecting method
DE102017003165A1 (en) 2016-04-08 2017-10-12 Fanuc Corporation A machine learning device and a machine learning method for learning the error prediction of a main shaft or a motor that drives the main shaft, and an error prediction device and an error prediction system comprising a machine learning device
DE102017213787A1 (en) 2016-08-09 2018-02-15 Fanuc Corporation Servo controller, spindle failure detection method using the servo controller and computer program
JP2018043317A (en) * 2016-09-14 2018-03-22 オークマ株式会社 Machine tool
DE102017122315A1 (en) 2016-09-28 2018-03-29 Fanuc Corporation MANAGEMENT SYSTEM, MANAGEMENT DEVICE, METHOD FOR DETECTING A SPINDLE FAILURE USING THE MANAGEMENT DEVICE AND COMPUTER PROGRAM
KR20180033844A (en) * 2016-09-26 2018-04-04 현대로보틱스주식회사 Fault Diagnosis System of Industrial Robot
CN109333161A (en) * 2018-09-13 2019-02-15 温州大学 A kind of intelligent bolt monitoring system for machine tool main shaft transmission part fault detection
CN109459239A (en) * 2017-08-28 2019-03-12 发那科株式会社 Motor fault diagnosis system
CN109909803A (en) * 2019-04-17 2019-06-21 北京天泽智云科技有限公司 A kind of machine tool chief axis method for detecting abnormality
CN110806724A (en) * 2019-12-12 2020-02-18 郑州科技学院 Remote monitoring device of numerical control machine tool
CN111451837A (en) * 2019-01-22 2020-07-28 发那科株式会社 Preventive maintenance system for machine tool
JP2020159752A (en) * 2019-03-25 2020-10-01 ファナック株式会社 Spindle vibration measuring system, spindle measuring method, and program
JP2020163515A (en) * 2019-03-29 2020-10-08 株式会社 神崎高級工機製作所 Gear processing device
US11520307B2 (en) 2019-01-22 2022-12-06 Fanuc Corporation Tool management system of machine tool

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0266937U (en) * 1988-11-07 1990-05-21
JPH0349849A (en) * 1989-07-17 1991-03-04 Enshu Cloth Kk Tool damage detecting device with study function
JPH07129211A (en) * 1993-11-08 1995-05-19 Fanuc Ltd Automatic correction system for varying load
JPH09285944A (en) * 1996-04-23 1997-11-04 Toshiba Mach Co Ltd Main spindle abnormality detector for air bearing type machine tool
JPH09300175A (en) * 1996-05-14 1997-11-25 Toyota Motor Corp Abnormality judging method for machining device and device therefor

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0266937U (en) * 1988-11-07 1990-05-21
JPH0349849A (en) * 1989-07-17 1991-03-04 Enshu Cloth Kk Tool damage detecting device with study function
JPH07129211A (en) * 1993-11-08 1995-05-19 Fanuc Ltd Automatic correction system for varying load
JPH09285944A (en) * 1996-04-23 1997-11-04 Toshiba Mach Co Ltd Main spindle abnormality detector for air bearing type machine tool
JPH09300175A (en) * 1996-05-14 1997-11-25 Toyota Motor Corp Abnormality judging method for machining device and device therefor

Cited By (40)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2008286636A (en) * 2007-05-17 2008-11-27 Aisin Aw Co Ltd Inspection method and device
JP2010181151A (en) * 2009-02-03 2010-08-19 Okuma Corp Method and device for determining lubricated state of rolling bearing
CN103419076A (en) * 2012-05-17 2013-12-04 大隈株式会社 Machining vibration suppressing method and machining vibration suppressing apparatus for machine tool
JP2016170085A (en) * 2015-03-13 2016-09-23 日本精工株式会社 Abnormality diagnostic device and abnormality diagnostic method
US10024758B2 (en) 2015-05-19 2018-07-17 Fanuc Corporation Abnormality detecting device having function for detecting abnormality of machine tool, and abnormality detecting method
DE102016005892A1 (en) 2015-05-19 2016-11-24 Fanuc Corporation Anomaly detecting device having a function of detecting an abnormality of a machine tool and an abnormality detecting method
CN106168534A (en) * 2015-05-19 2016-11-30 发那科株式会社 Possess abnormal detector and the method for detecting abnormality of the abnormal detection function of lathe
JP2016215311A (en) * 2015-05-19 2016-12-22 ファナック株式会社 Abnormality detection device comprising abnormality detection function of machine tool and abnormality detection method
DE102017003165A1 (en) 2016-04-08 2017-10-12 Fanuc Corporation A machine learning device and a machine learning method for learning the error prediction of a main shaft or a motor that drives the main shaft, and an error prediction device and an error prediction system comprising a machine learning device
US11521105B2 (en) 2016-04-08 2022-12-06 Fanuc Corporation Machine learning device and machine learning method for learning fault prediction of main shaft or motor which drives main shaft, and fault prediction device and fault prediction system including machine learning device
US10493576B2 (en) 2016-08-09 2019-12-03 Fanuc Corporation Servo control device, spindle failure detection method using servo control device, and non-transitory computer readable medium encoded with computer program
CN107695790A (en) * 2016-08-09 2018-02-16 发那科株式会社 Servocontrol device, main shaft failure detection method and computer-readable medium
CN107695790B (en) * 2016-08-09 2020-08-18 发那科株式会社 Servo control device, spindle failure detection method, and computer-readable medium
DE102017213787A1 (en) 2016-08-09 2018-02-15 Fanuc Corporation Servo controller, spindle failure detection method using the servo controller and computer program
JP2018024048A (en) * 2016-08-09 2018-02-15 ファナック株式会社 Servo controller, main shaft failure detection method using the same, and computer program
DE102017213787B4 (en) 2016-08-09 2023-04-27 Fanuc Corporation Servo controller, spindle failure detection method using the servo controller, and computer program
JP2018043317A (en) * 2016-09-14 2018-03-22 オークマ株式会社 Machine tool
KR102266220B1 (en) * 2016-09-26 2021-06-16 현대중공업지주 주식회사 Fault Diagnosis System of Industrial Robot
KR20180033844A (en) * 2016-09-26 2018-04-04 현대로보틱스주식회사 Fault Diagnosis System of Industrial Robot
US10481046B2 (en) 2016-09-28 2019-11-19 Fanuc Corporation Management system, management device, spindle failure detection method using management device, and non-transitory computer readable medium encoded with computer program
DE102017122315A1 (en) 2016-09-28 2018-03-29 Fanuc Corporation MANAGEMENT SYSTEM, MANAGEMENT DEVICE, METHOD FOR DETECTING A SPINDLE FAILURE USING THE MANAGEMENT DEVICE AND COMPUTER PROGRAM
JP2019039876A (en) * 2017-08-28 2019-03-14 ファナック株式会社 Motor fault diagnosing system
US10578517B2 (en) 2017-08-28 2020-03-03 Fanuc Corporation Motor failure diagnosis system
CN109459239A (en) * 2017-08-28 2019-03-12 发那科株式会社 Motor fault diagnosis system
CN109333161A (en) * 2018-09-13 2019-02-15 温州大学 A kind of intelligent bolt monitoring system for machine tool main shaft transmission part fault detection
US11556901B2 (en) 2019-01-22 2023-01-17 Fanuc Corporation Preventive maintenance system of machine tool
CN111451837A (en) * 2019-01-22 2020-07-28 发那科株式会社 Preventive maintenance system for machine tool
JP2020116667A (en) * 2019-01-22 2020-08-06 ファナック株式会社 Preventive maintenance system of machine tool
US11520307B2 (en) 2019-01-22 2022-12-06 Fanuc Corporation Tool management system of machine tool
JP7148421B2 (en) 2019-01-22 2022-10-05 ファナック株式会社 Preventive maintenance system for machine tools
JP7053526B2 (en) 2019-03-25 2022-04-12 ファナック株式会社 Spindle vibration measurement system, spindle vibration measurement method, and program
CN111805304A (en) * 2019-03-25 2020-10-23 发那科株式会社 Spindle vibration measurement system, spindle vibration measurement method, and program
KR20200115106A (en) * 2019-03-25 2020-10-07 화낙 코퍼레이션 System for measuring vibration in spindle, method for measuring vibration in spindle and program therefor
JP2020159752A (en) * 2019-03-25 2020-10-01 ファナック株式会社 Spindle vibration measuring system, spindle measuring method, and program
KR102638086B1 (en) * 2019-03-25 2024-02-16 화낙 코퍼레이션 System for measuring vibration in spindle, method for measuring vibration in spindle and program therefor
JP2020163515A (en) * 2019-03-29 2020-10-08 株式会社 神崎高級工機製作所 Gear processing device
JP7267585B2 (en) 2019-03-29 2023-05-02 株式会社 神崎高級工機製作所 Gear processing equipment
CN109909803B (en) * 2019-04-17 2020-05-12 北京天泽智云科技有限公司 Machine tool spindle abnormity detection method
CN109909803A (en) * 2019-04-17 2019-06-21 北京天泽智云科技有限公司 A kind of machine tool chief axis method for detecting abnormality
CN110806724A (en) * 2019-12-12 2020-02-18 郑州科技学院 Remote monitoring device of numerical control machine tool

Similar Documents

Publication Publication Date Title
JP2005074545A (en) Condition monitoring device for machine tool
US10024758B2 (en) Abnormality detecting device having function for detecting abnormality of machine tool, and abnormality detecting method
JP3997528B2 (en) Rolling bearing diagnostic method and diagnostic device
US20160297043A1 (en) Machine tool having inspection function for deteriorated state of spindle
JP6499946B2 (en) Machine tool bearing diagnostic device
JP5308852B2 (en) Method and device for determining lubrication state of rolling bearing
JP5241916B2 (en) Wire running system maintenance system for wire electric discharge machine
CN101354578A (en) Numeric control device of machine tool
JP2018025450A (en) Bearing diagnostic device
TWI760442B (en) Status diagnosis system and status diagnosis method of rolling guide device
JP6616964B2 (en) State display method and apparatus of rolling bearing in machine tool
JP6735183B2 (en) Machine tool with rotating shaft
JP6495797B2 (en) Spindle abnormality detection device and spindle abnormality detection method for machine tools
JP5064978B2 (en) Operation confirmation method of bearing lubrication device
JP6637689B2 (en) Machine tool tool state determination device
JP5516839B2 (en) Spindle device abnormality detection device, spindle device abnormality detection method, spindle device, and machine tool
JPH0665189B2 (en) X-ray tube with bearing life determining device
JP6637844B2 (en) Method for determining warm-up operation time before bearing diagnosis in machine tool, machine tool
JP6873870B2 (en) Lubrication state diagnosis device and lubrication state diagnosis method for bearings in rotary shaft devices
JP2018044892A (en) Method for diagnosing abnormality in bearing of rotary shaft device and rotary shaft device
WO2021009973A1 (en) Data collection device
JP5541054B2 (en) Physical quantity measuring device for rotating members
WO2023063435A1 (en) Working machine bearing quality determining method and system
JPH03221354A (en) Abnormality predicting device for rolling bearing
US11585718B2 (en) Method and device for imbalance detection

Legal Events

Date Code Title Description
A621 Written request for application examination

Free format text: JAPANESE INTERMEDIATE CODE: A621

Effective date: 20060414

A977 Report on retrieval

Free format text: JAPANESE INTERMEDIATE CODE: A971007

Effective date: 20090326

A131 Notification of reasons for refusal

Effective date: 20090407

Free format text: JAPANESE INTERMEDIATE CODE: A131

A521 Written amendment

Effective date: 20090603

Free format text: JAPANESE INTERMEDIATE CODE: A523

A131 Notification of reasons for refusal

Effective date: 20091110

Free format text: JAPANESE INTERMEDIATE CODE: A131

A02 Decision of refusal

Effective date: 20100406

Free format text: JAPANESE INTERMEDIATE CODE: A02