JP2017181441A - State determination device and state determination method of rotary bearing - Google Patents

State determination device and state determination method of rotary bearing Download PDF

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JP2017181441A
JP2017181441A JP2016072700A JP2016072700A JP2017181441A JP 2017181441 A JP2017181441 A JP 2017181441A JP 2016072700 A JP2016072700 A JP 2016072700A JP 2016072700 A JP2016072700 A JP 2016072700A JP 2017181441 A JP2017181441 A JP 2017181441A
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bearing
skewness
value
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state
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JP6460030B2 (en
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崇仁 鈴木
Takahito Suzuki
崇仁 鈴木
建太 苅部
Kenta Karibe
建太 苅部
岡田　邦明
Kuniaki Okada
邦明 岡田
達彰 井上
Tatsuaki Inoue
達彰 井上
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JFE Steel Corp
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Abstract

PROBLEM TO BE SOLVED: To provide a technology of state determination of a rotary bearing capable of determining an abnormality of a bearing using a simple criterion.SOLUTION: The state determination device includes: a vibration detection sensor 4 for detecting the vibration of a bearing 3 for supporting a rotation shaft 2; a skewness calculation unit 5A for calculating a skewness β1 of a vibration waveform occurring in the bearing 3 every predetermined sampling time on the basis of a detection value of the vibration detection sensor 4; and an abnormality determination unit 5B for determining an abnormality of the bearing 3 on the basis of the amount of change or the rate of change of the absolute value of the skewness β1 calculated by the skewness calculation unit 5A.SELECTED DRAWING: Figure 1

Description

本発明は、軸回転する回転軸を支承する軸受の状態判定を行う技術である。特に、ハースロールなどの低速（例えば２００ｒｐｍ以下）で回転する回転体に接続した回転軸を支承する軸受の状態判定に好適な技術である。   The present invention is a technique for determining the state of a bearing that supports a rotating shaft that rotates. In particular, this is a technique suitable for determining the state of a bearing that supports a rotating shaft connected to a rotating body that rotates at a low speed (for example, 200 rpm or less) such as a hearth roll.

回転機その他の回転体の回転軸を支承する軸受の診断装置としては、例えば特許文献１に記載の装置がある。
特許文献１には、軸受の振動波形の標準偏差、尖度、歪度算出結果の平均値および標準偏差という複数種類の統計値から異常診断することが記載されている。 An example of a diagnostic apparatus for a bearing that supports a rotating shaft of a rotating machine or other rotating body is, for example, an apparatus described in Patent Document 1.
Patent Document 1 describes that abnormality diagnosis is performed from a plurality of types of statistical values such as standard deviation, kurtosis, average value of skewness calculation results, and standard deviation of a bearing vibration waveform.

特開２０１２−８０３０号公報（請求項５参照）JP 2012-8030 A (refer to claim 5)

しかし、特許文献１では、複数種類の統計値に基づき判定するため、診断処理が複雑になるおそれがある。また特許文献１には具体的な判定方法、特に歪度を用いた具体的な判定方法について示されておらず、判定基準として採用することが困難である。   However, in Patent Document 1, since the determination is made based on a plurality of types of statistical values, there is a possibility that the diagnosis processing becomes complicated. Further, Patent Document 1 does not describe a specific determination method, particularly a specific determination method using the skewness, and it is difficult to adopt as a determination standard.

本発明は、上記のような点に着目してなされたもので、簡易な判断基準で軸受の異常判定が可能な回転軸受の状態判定の技術を提供することを目的とする。   The present invention has been made paying attention to the above points, and an object of the present invention is to provide a technique for determining the state of a rotating bearing capable of determining a bearing abnormality with a simple determination criterion.

課題を解決するために、本発明の一態様は、回転軸を支承する軸受の振動を検出する振動検出センサと、上記振動検出センサの検出値に基づき軸受に発生している振動波形の歪度を所定サンプリング時間毎に算出する歪度算出部と、上記歪度算出部が算出した歪度の絶対値の変化量若しくは変化率に基づき、上記軸受の異常を判定する異常判定部と、を備える。   In order to solve the problem, an aspect of the present invention includes a vibration detection sensor that detects vibration of a bearing that supports a rotating shaft, and a skewness of a vibration waveform that is generated in the bearing based on a detection value of the vibration detection sensor. A skewness calculation unit that calculates the bearing at a predetermined sampling time, and an abnormality determination unit that determines an abnormality of the bearing based on a change amount or a change rate of the absolute value of the skewness calculated by the skewness calculation unit. .

また、本発明の他の一態様は、回転軸を支承する軸受の振動を検出する振動検出センサと、上記振動検出センサの検出値に基づき軸受に発生している振動波形の歪度を所定サンプリング時間毎に算出する歪度算出部と、上記歪度算出部が算出した各歪度について、正値若しくは負値が、予め設定した数以上連続して検出した場合に上記軸受が異常と判定する異常判定部と、を備える。   According to another aspect of the present invention, a vibration detection sensor that detects vibration of a bearing that supports a rotating shaft, and a degree of distortion of a vibration waveform generated in the bearing based on a detection value of the vibration detection sensor are predetermined sampling. For each skewness calculated by the skewness calculation unit calculated every time and the skewness calculation unit, the bearing is determined to be abnormal when positive values or negative values are continuously detected for a predetermined number or more. An abnormality determination unit.

本発明によれば、軸受の振動波形の歪度から簡易な判断基準で軸受の異常を診断することが可能となる。   According to the present invention, it is possible to diagnose a bearing abnormality based on the degree of distortion of the vibration waveform of the bearing based on a simple determination criterion.

本発明に基づく実施形態に係る回転軸受の状態判定装置を説明する模式図である。It is a schematic diagram explaining the state determination apparatus of the rotary bearing which concerns on embodiment based on this invention. 検出した歪度の時系列な変化の例を示す図である。It is a figure which shows the example of the time series change of the detected skewness. 図３の歪度を絶対値で示した図である。It is the figure which showed the skewness of FIG. 3 by the absolute value. 閾値として絶対値を使用した場合を例示する図である。It is a figure which illustrates the case where an absolute value is used as a threshold value. 閾値として平均値の定数倍を使用した場合を例示する図である。It is a figure which illustrates the case where the constant multiple of an average value is used as a threshold value. 歪度の時系列な変化の例を示す図であり、（ａ）は正常時の状態を、（ｂ）は異常時の状態をそれぞれ例示する図である。It is a figure which shows the example of the time-sequential change of a skewness, (a) is a figure which illustrates the state at the time of normal, (b) is a figure which illustrates the state at the time of abnormality, respectively. 変形例に係る回転軸受の状態判定装置を説明する模式図である。It is a schematic diagram explaining the state determination apparatus of the rotary bearing which concerns on a modification. 実施例１を説明する図である。FIG. 3 is a diagram illustrating Example 1. 実施例２を説明する図である。FIG. 6 is a diagram illustrating Example 2.

次に、本発明の実施形態について図面を参照しつつ説明する。
＜第１実施形態＞
本実施形態は、図１に示すように、モータ等の回転体１の回転軸２を支承する軸受３の状態を判定する装置である。軸受３は、ころ軸受などの転がり軸受や滑り軸受などであって回転軸２を軸回転可能に支持（支承）可能な軸受であれば、本発明の状態判定装置は適用可能である。回転軸２は、駆動軸である必要はなく、被駆動軸側の回転軸であっても対象となる。 Next, embodiments of the present invention will be described with reference to the drawings.
<First Embodiment>
As shown in FIG. 1, the present embodiment is a device that determines the state of a bearing 3 that supports a rotating shaft 2 of a rotating body 1 such as a motor. If the bearing 3 is a rolling bearing such as a roller bearing, a sliding bearing, or the like and can support (support) the rotary shaft 2 so as to be rotatable, the state determination device of the present invention is applicable. The rotary shaft 2 does not need to be a drive shaft, and is a target even if it is a rotary shaft on the driven shaft side.

（構成）
本実施形態の回転軸受の状態判定装置は、図１に示すように、振動検出センサ４と、診断部５とを備える。符号１は回転軸２を回転駆動するモータ等の回転機を、符号２は回転軸を、符号３は軸受をそれぞれ表す。
振動検出センサ４は、軸受３の振動を検出して検出値を診断部５に出力する。振動検出センサ４は、例えば、軸受３の振動の加速度や速度を検出する。振動検出センサ４は、図１のように軸受３のハウジングに取り付けられる。 (Constitution)
As shown in FIG. 1, the rotary bearing state determination device of the present embodiment includes a vibration detection sensor 4 and a diagnosis unit 5. Reference numeral 1 denotes a rotating machine such as a motor that rotationally drives the rotary shaft 2, reference numeral 2 denotes a rotary shaft, and reference numeral 3 denotes a bearing.
The vibration detection sensor 4 detects the vibration of the bearing 3 and outputs the detected value to the diagnosis unit 5. The vibration detection sensor 4 detects, for example, acceleration and speed of vibration of the bearing 3. The vibration detection sensor 4 is attached to the housing of the bearing 3 as shown in FIG.

診断部５は、図１に示すように、歪度算出部５Ａと異常判定部５Ｂとを有する。
歪度算出部５Ａは、振動検出センサ４の検出値を入力し、その検出値に基づき軸受３に発生している振動波形の歪度β１を所定サンプリング時間毎に算出する処理を行う。
例えばサンプリング周期３３ｋＨｚで１０秒測定することで、歪度β１を算出するデータを取得する。
なお、歪度β１の算出間隔は特に制限は無いが、例えば５分間隔で求める。 As shown in FIG. 1, the diagnosis unit 5 includes a skewness calculation unit 5A and an abnormality determination unit 5B.
The skewness calculation unit 5A inputs the detection value of the vibration detection sensor 4, and performs a process of calculating the skewness β1 of the vibration waveform generated in the bearing 3 based on the detection value at every predetermined sampling time.
For example, data for calculating the skewness β1 is acquired by measuring for 10 seconds at a sampling period of 33 kHz.
Note that the calculation interval of the skewness β1 is not particularly limited, but is calculated at intervals of 5 minutes, for example.

ここで、歪度β１とは、分布の左右非対称性を表す値であり、データの分布が平均値を軸にどの程度対称となっているかを示す統計量である。歪度β１は、次の（１）式で求めることが出来る。   Here, the skewness β1 is a value representing the left-right asymmetry of the distribution, and is a statistic indicating how symmetric the data distribution is about the average value. The skewness β1 can be obtained by the following equation (1).

Figure 2017181441
Figure 2017181441

ここで、
ｎ：データの個数
ｘ：データ全体の平均値
ｓ：データ全体の標準偏差
である。 here,
n: number of data x: average value of entire data s: standard deviation of entire data

本実施形態の歪度算出部５Ａは、振動検出センサ４から入力したｎ個の検出値毎に、そのｎ個の検出値（データ）で表現される振動分布の歪度β１を上記の（１）式によって算出する。算出した歪度β１の値は、例えば記憶部に順次記憶される。   For each n detection values input from the vibration detection sensor 4, the skewness calculation unit 5 </ b> A of the present embodiment calculates the skewness β <b> 1 of the vibration distribution expressed by the n detection values (data) (1 ). The calculated value of skewness β1 is sequentially stored, for example, in the storage unit.

異常判定部５Ｂは、歪度算出部５Ａが算出した歪度β１を連続的に入力し、入力した各歪度β１の絶対値化処理を行い、その後、その歪度β１の絶対値が予め設定した閾値を越えた場合に軸受３が異常状態と判定する。   The abnormality determination unit 5B continuously inputs the skewness β1 calculated by the skewness calculation unit 5A, performs absolute value processing of each input skewness β1, and then sets the absolute value of the skewness β1 in advance. If the measured threshold value is exceeded, the bearing 3 is determined to be in an abnormal state.

ここで、閾値は、例えば軸受３が正常と推定されるときに検出した歪度β１の絶対値の最大値とする。若しくは閾値として、最低値、標準偏差、平均値の各定数倍の値を採用しても良い。更には、そのような値に所定の余裕代分を加算した値を閾値としてもよい。   Here, the threshold value is, for example, the maximum absolute value of the skewness β1 detected when the bearing 3 is estimated to be normal. Alternatively, a value that is a constant multiple of the minimum value, standard deviation, and average value may be employed as the threshold value. Furthermore, a value obtained by adding a predetermined margin to such a value may be used as the threshold value.

（動作その他）
軸受３の振動から算出した歪度β１の値は、正値、負値の値が不規則に出力されるため、単独に判定基準として用いることが困難であるとされてきた。この点について、発明者らは、歪度β１による振動異常を判定する方法について検討したところ、歪度β１の絶対値の変化量や変化率によって判定可能との知見を得た。 (Operation other)
Since the value of the skewness β1 calculated from the vibration of the bearing 3 is irregularly outputted as positive and negative values, it has been difficult to use it alone as a criterion. With regard to this point, the inventors examined a method of determining vibration abnormality based on the skewness β1, and obtained knowledge that it can be determined based on a change amount and a change rate of the absolute value of the skewness β1.

ここで、歪度β１の時系列のデータの例は、図２のように算出され、正値及び負値が不規則に算出される。図２では交互に算出されているが、必ずしも交互に算出される訳ではない。
これに対し、図３のように、歪度β１の絶対値の時系列でみると、経時的に値が増加する傾向となることが分かる。 Here, an example of time-series data of the skewness β1 is calculated as shown in FIG. 2, and positive values and negative values are calculated irregularly. Although it is calculated alternately in FIG. 2, it is not necessarily calculated alternately.
On the other hand, as shown in FIG. 3, when the time series of the absolute value of the skewness β1 is viewed, it can be seen that the value tends to increase with time.

このように、歪度β１の値の絶対値化処理を行い、負値を正値に変換した後、０点を基準とした変化量、変化率を比較・監視することで、軸受３の振動異常の管理を容易にできる。   In this way, the absolute value of the value of the skewness β1 is processed, the negative value is converted into a positive value, and the amount of change and the rate of change with reference to the zero point are compared and monitored. Anomalies can be easily managed.

そして、本実施形態では、図４、図５のように、歪度β１の絶対値が予め設定した閾値を越えた場合に軸受３の異常と判定する。図４は、閾値として正常時の歪度β１の絶対値の最大値を設定した場合の例であり、図５は、閾値として正常時の歪度β１の絶対値の平均値の定数倍を設定した場合の例である。   In this embodiment, as shown in FIGS. 4 and 5, it is determined that the bearing 3 is abnormal when the absolute value of the skewness β1 exceeds a preset threshold value. FIG. 4 shows an example in which the maximum absolute value of the normal skewness β1 is set as the threshold value, and FIG. 5 shows a constant multiple of the average absolute value of the normal skewness β1 value as the threshold value. This is an example.

ここで、図５では、異常と一旦判定した後に、再度正常判定がなされ、その後再度異常判定がされている。これは、軸受３に異常が発生した後に、磨耗などによって振動が鈍って一旦正常の範囲内の値に変化したものと推定される。２回以上異常値を検出した場合に、軸受３が異常と診断しても良い。   Here, in FIG. 5, after once determining that there is an abnormality, the normality determination is performed again, and then the abnormality determination is performed again. This is presumed that after an abnormality occurred in the bearing 3, the vibration was dulled due to wear or the like and temporarily changed to a value within the normal range. If an abnormal value is detected twice or more, the bearing 3 may be diagnosed as abnormal.

以上のように、本実施形態によれば、歪度β１に基づき簡易に判定が可能である。すなわち、測定結果から、判定の熟練度に関係なく、軸受３の振動異常の判定を簡易に行うことが出来る。このため、異常状態の軸受３の早期発見が可能となり、適切な対応を取ることができる。   As described above, according to the present embodiment, it is possible to easily determine based on the skewness β1. That is, it is possible to easily determine the vibration abnormality of the bearing 3 from the measurement result regardless of the skill level of the determination. For this reason, early detection of the bearing 3 in an abnormal state is possible, and an appropriate response can be taken.

＜第２実施形態＞
次に、本発明の第２実施形態について説明する。
（構成） Second Embodiment
Next, a second embodiment of the present invention will be described.
(Constitution)

本実施形態の基本構成は、第１実施形態と同様であるが、異常判定部５Ｂの処理内容が異なる。
第２実施形態の異常判定部５Ｂでは、歪度算出部５Ａが算出した歪度β１の値の変化として、正値若しくは負値の一方の値が、予め設定した回数以上連続して検出した場合に軸受３が異常と判定する。なお、回数の検出は、例えばカウンタを用意し、正負の切替えがあるたびにカウンタを１に初期化しつつ、同符号の間、加算すれば検出出来る。 The basic configuration of this embodiment is the same as that of the first embodiment, but the processing content of the abnormality determination unit 5B is different.
In the abnormality determination unit 5B of the second embodiment, when one value of a positive value or a negative value is continuously detected more than a preset number of times as a change in the value of the skewness β1 calculated by the skewness calculation unit 5A It is determined that the bearing 3 is abnormal. The number of times can be detected, for example, by preparing a counter and initializing the counter to 1 every time there is a positive / negative switching and adding during the same sign.

異常判定部５Ｂは、例えば、同一符号の歪度β１が５回以上検出された場合に、軸受３が異常と判定する。
その他の構成は、第１実施形態と同様であるので説明を省略する。 For example, the abnormality determination unit 5B determines that the bearing 3 is abnormal when the skewness β1 of the same sign is detected five times or more.
Since other configurations are the same as those of the first embodiment, the description thereof is omitted.

（動作その他）
軸受３の振動から算出した歪度β１の値は、正負、不規則に出力されるため、単独に判定基準として用いることが困難であるとされてきた。この点について、発明者らは、歪度β１による振動異常を判定する方法について検討したところ、軸受３が異常の場合に、歪度β１の時系列データの符号が同符号の値に偏って連続して検出される傾向があり、その歪度β１の時系列データの偏りから、軸受３の振動異常を判定可能との知見を得た。 (Operation other)
Since the value of the skewness β1 calculated from the vibration of the bearing 3 is outputted positively, negatively and irregularly, it has been difficult to use it alone as a criterion. In this regard, the inventors examined a method for determining vibration abnormality due to the skewness β1. When the bearing 3 is abnormal, the sign of the time-series data of the skewness β1 is biased toward the value of the same sign. It was found that the vibration abnormality of the bearing 3 can be determined from the deviation of the time series data of the skewness β1.

そして、軸受３が正常の状態では、図６（ａ）に示すように、同符号の歪度β１が所定回数連続することは少ないが、軸受３が異常の場合には、図６（ｂ）に示すように、同じ符号の歪度β１値が所定回数連続して検出され、本実施形態の装置では、そのような場合に、軸受３の異常と判定する。   When the bearing 3 is in a normal state, as shown in FIG. 6A, the skewness β1 with the same sign is rarely continued for a predetermined number of times, but when the bearing 3 is abnormal, FIG. As shown in FIG. 5, the skewness β1 value having the same sign is detected continuously a predetermined number of times, and the apparatus of this embodiment determines that the bearing 3 is abnormal in such a case.

以上のように、本実施形態によれば、歪度β１に基づき簡易に判定が可能であることから、測定結果から、判定の熟練度に関係なく、軸受３の振動異常の判定を行うことが出来る。このため、異常状態の軸受３の早期発見が可能となり、適切な対応を取ることができる。   As described above, according to the present embodiment, since it is possible to easily determine based on the skewness β1, it is possible to determine the vibration abnormality of the bearing 3 from the measurement result regardless of the skill level of the determination. I can do it. For this reason, early detection of the bearing 3 in an abnormal state is possible, and an appropriate response can be taken.

ここで、第１実施形態での異常判定と第２実施形態での異常判定との両方を行うように異常判定部５Ｂを構成しても良い。この場合、一方の異常判定で異常と判定された場合に異常と判定しても良いし、両方で異常判定と判定された場合に、軸受３が異常状態と判定しても良い。   Here, the abnormality determination unit 5B may be configured to perform both the abnormality determination in the first embodiment and the abnormality determination in the second embodiment. In this case, it may be determined as abnormal when it is determined as abnormal in one of the abnormality determinations, or the bearing 3 may be determined as being in an abnormal state when both are determined as abnormal.

＜変形例＞
ここで、診断対象とする軸受３の特性によっては、正常状態であっても、歪度β１の時系列のデータが正値若しくは負値に偏る傾向の場合も存在する。例えば、正常時における歪度β１の時系列データが負値に偏って検出される傾向にある場合、正常時においても、歪度β１の値として連続して負の値が検出される場合が想定される。
このため、次のように異常診断の処理を行うように装置構成を設定することが好ましい。 <Modification>
Here, depending on the characteristics of the bearing 3 to be diagnosed, there is a case where the time series data of the skewness β1 tends to be positive or negative even in a normal state. For example, when the time series data of the skewness β1 at the normal time tends to be detected with a negative value, it is assumed that a negative value is continuously detected as the value of the skewness β1 even at the normal time. Is done.
For this reason, it is preferable to set the apparatus configuration so that abnormality diagnosis processing is performed as follows.

すなわち、診断対象の軸受３の正常状態での歪度β１のデータを所定個数採取し、その平均値を記憶しておく。この平均値を記憶する記憶部を正常値記憶部６とする。ここで、上記の平均値を求める際のデータは例えば１０個〜１５個あれば求めることが出来る。もっとも、データの個数が多いほど正確な値が算出可能となる。
但し、正常値記憶部６に記憶する平均値がゼロに近い所定値以下の場合には、平均値をゼロとして記憶しても良い。 That is, a predetermined number of data of the skewness β1 in the normal state of the bearing 3 to be diagnosed is collected, and the average value is stored. The storage unit that stores the average value is referred to as a normal value storage unit 6. Here, for example, 10 to 15 pieces of data can be obtained when obtaining the average value. However, as the number of data increases, an accurate value can be calculated.
However, when the average value stored in the normal value storage unit 6 is equal to or less than a predetermined value close to zero, the average value may be stored as zero.

この変形例の異常判定部５Ｂは、図７に示すように、歪度校正部５Ｂａと判定部本体５Ｂｂとからなる。
歪度校正部５Ｂａは、歪度算出部５Ａが算出した歪度β１の値を入力する度に、その入力値から正常値記憶部６に記憶した平均値を引いて当該歪度β１の校正処理を行う。 As shown in FIG. 7, the abnormality determination unit 5B of this modification includes a skewness correction unit 5Ba and a determination unit body 5Bb.
Each time the skewness correction unit 5Ba inputs the value of the skewness β1 calculated by the skewness calculation unit 5A, the average value stored in the normal value storage unit 6 is subtracted from the input value, and the skewness β1 is calibrated. I do.

判定部本体５Ｂｂは、歪度校正部５Ｂａで校正処理後の歪度β１に基づき、正値若しくは負値の一方の値が、予め設定した回数（例えば４回）以上連続して検出した場合に軸受３が異常と判定する。
このように、歪度β１について校正処理を行うことで、軸受３の異常検出精度が向上する。 When the determination unit body 5Bb detects one of the positive value and the negative value continuously for a preset number of times (for example, 4 times) based on the skewness β1 after the calibration processing by the skewness correction unit 5Ba. It is determined that the bearing 3 is abnormal.
Thus, the abnormality detection accuracy of the bearing 3 is improved by performing the calibration process on the skewness β1.

ここで、第１実施形態の装置においても、上記の正常値記憶部６及び歪度校正部５Ｂａを備えるようにしても良い。そして、異常判定部５Ｂにおいて、歪度校正部５Ｂａで校正後の歪度β１について絶対値化を行った後に、異常判定を行うようにしても良い。   Here, the apparatus according to the first embodiment may include the normal value storage unit 6 and the skewness calibration unit 5Ba. Then, the abnormality determination unit 5B may perform the abnormality determination after the skewness correction unit 5Ba has converted the absolute value of the corrected skewness β1.

また、上記の全実施形態において、歪度算出部５Ａが算出した歪度β１を順次、異常判定部５Ｂに入力する場合で説明しているが、これに限定されない。例えば、異常判定部５Ｂは、歪度β１を所定個数のデータ単位で入力するようにしても良い。   In all the above embodiments, the case where the skewness β1 calculated by the skewness calculation unit 5A is sequentially input to the abnormality determination unit 5B has been described, but the present invention is not limited to this. For example, the abnormality determination unit 5B may input the skewness β1 in units of a predetermined number of data.

ここで、本実施形態では、ハースロールなどの低速（例えば２００ｒｐｍ以下）で回転する回転体に接続する回転軸２の軸受３の状態判定に好適な技術であるが、高速で回転する回転体に接続する回転軸２の軸受３の状態判定にも適用可能である。   Here, in this embodiment, although it is a technique suitable for the state determination of the bearing 3 of the rotating shaft 2 connected to the rotating body rotating at a low speed (for example, 200 rpm or less) such as a hearth roll, the rotating body rotating at a high speed is used. The present invention can also be applied to state determination of the bearing 3 of the rotating shaft 2 to be connected.

次に、本発明の実施例について説明する。
「実施例１」
＜設備＞
回転機として、回転機シミュレータ（オフラインテスト）を使用して、軸受３の異常判定について確認した。 Next, examples of the present invention will be described.
"Example 1"
<Equipment>
Using a rotating machine simulator (offline test) as the rotating machine, the abnormality determination of the bearing 3 was confirmed.

ここで、回転機シミュレータは、４個の軸受３により支持された主軸（回転軸２）を任意の回転数で回転させることができる。各軸受３は交換することが可能であり、内輪に傷ついている軸受３や脱脂した軸受３を使用することで、フレーキングや潤滑不良など様々な異常状態を模擬的に再現することが可能である。
軸受３としては、自動調心ころ軸受３（ＮＳＫ ２１３０７ＣＤＥ４０）を使用した。 Here, the rotating machine simulator can rotate the main shaft (rotating shaft 2) supported by the four bearings 3 at an arbitrary number of rotations. Each bearing 3 can be replaced, and various abnormal states such as flaking and poor lubrication can be simulated by using a bearing 3 damaged on the inner ring or a degreased bearing 3. is there.
As the bearing 3, a self-aligning roller bearing 3 (NSK 21307CDE40) was used.

＜試験条件＞
そして、正常状態の軸受３と、フレーキング状態（軸受３内に放電加工機で疵（５ｍｍ×２ｍｍ×３個）を与えた）の異常状態の軸受３との２つ軸受を用意して比較した。 <Test conditions>
Then, two bearings are prepared and compared, that is, a normal bearing 3 and a flaking condition (abnormality bearing 5 (5 mm × 2 mm × 3 pieces) is given in the bearing 3 by an electric discharge machine). did.

回転時は７００ｋｇの負荷を与え、回転数は１５ｒｐｍ、３０ｒｐｍ、６０ｒｐｍ、１２０ｒｐｍ、１５０ｒｐｍの順に１回ずつ測定を行い、その後、再度１５ｒｐｍ、３０ｒｐｍ、６０ｒｐｍ、１２０ｒｐｍ、１５０ｒｐｍの測定を２回行った。
この実施例では、振動の速度の歪度β１で評価した。 At the time of rotation, a load of 700 kg was applied, and the number of rotations was measured once in the order of 15 rpm, 30 rpm, 60 rpm, 120 rpm, and 150 rpm.
In this example, evaluation was made based on the degree of distortion β1 of the vibration speed.

＜評価結果＞
図８（ａ）に、正常状態の軸受３及び異常状態の軸受３における、各歪度β１の時系列データを併せて示す。更に、図８（ｂ）に、正常状態の軸受３及び異常状態の軸受３における、各歪度β１の絶対値の時系列データを併せて示す。なお、この実施例は、閾値として、正常状態の軸受３での歪度β１の最大値を採用した場合である。 <Evaluation results>
FIG. 8A also shows time-series data of each skewness β1 in the bearing 3 in the normal state and the bearing 3 in the abnormal state. Further, FIG. 8B also shows time-series data of absolute values of the skewness β1 in the bearing 3 in the normal state and the bearing 3 in the abnormal state. In this embodiment, the maximum value of the skewness β1 in the bearing 3 in the normal state is adopted as the threshold value.

図８に示されるように、歪度β１を絶対値化してその変化を観察することで、熟練者でなくても軸受３の異常判定が簡易に認識可能となることが分かる。   As shown in FIG. 8, it can be understood that the abnormality determination of the bearing 3 can be easily recognized even by an unskilled person by observing the change of the skewness β1 by making it an absolute value.

「実施例２」
実施例１と同様な設備を使用した。
そして、正常状態の軸受３と、脱脂によって潤滑不良とした異常状態の軸受３とを用意して評価した。 "Example 2"
The same equipment as in Example 1 was used.
Then, the bearing 3 in a normal state and the bearing 3 in an abnormal state in which lubrication was poor by degreasing were prepared and evaluated.

図９に、正常状態の軸受３及び異常状態の軸受３における、各歪度β１の時系列データを併せて示す。
図９から分かるように、正常状態の軸受３では正負に値が出力されているが、異常状態）の軸受３からは一方の値のみが出力されていることから異常状態では、正の値が連続して出力（５回以上）されることがわかり、軸受３が異常状態であると判断できた。このように、正常時に同一符号で出力される連続回数よりも、異常時の方が同一符号で出力される連続回数が多くなっていることが分かる。 FIG. 9 also shows time-series data of each degree of skewness β1 in the bearing 3 in the normal state and the bearing 3 in the abnormal state.
As can be seen from FIG. 9, the bearing 3 in the normal state outputs values positively and negatively, but only one value is output from the bearing 3 in the abnormal state). It was found that the output was continuous (more than 5 times), and it was possible to determine that the bearing 3 was in an abnormal state. Thus, it can be seen that the number of continuous outputs with the same code is higher in the abnormal state than the number of continuous outputs with the same code in the normal state.

２ 回転軸
３ 軸受
４ 振動検出センサ
５ 診断部
５Ａ 歪度算出部
５Ｂ 異常判定部
５Ｂａ 歪度校正部
５Ｂｂ 判定部本体
６ 正常値記憶部
β１ 歪度 2 Rotating shaft 3 Bearing 4 Vibration detection sensor 5 Diagnosis unit 5A Distortion calculation unit 5B Abnormality determination unit 5Ba Distortion correction unit 5Bb Determination unit body 6 Normal value storage unit β1 Skewness

Claims (6)

回転軸を支承する軸受の状態判定装置であって、
上記軸受の振動を検出する振動検出センサと、
上記振動検出センサの検出値に基づき上記軸受に発生している振動波形の歪度を算出する歪度算出部と、
上記歪度算出部が算出した歪度の絶対値が予め設定した閾値以上の場合に、上記軸受が異常と判定する異常判定部と、
を備えることを特徴とする回転軸受の状態判定装置。 A bearing state determination device for supporting a rotating shaft,
A vibration detection sensor for detecting the vibration of the bearing;
A skewness calculation unit that calculates the skewness of the vibration waveform generated in the bearing based on the detection value of the vibration detection sensor;
An abnormality determination unit that determines that the bearing is abnormal when the absolute value of the skewness calculated by the skewness calculation unit is equal to or greater than a preset threshold;
A state determination device for a rotary bearing, comprising: 回転軸を支承する軸受の状態判定装置であって、
上記軸受の振動を検出する振動検出センサと、
上記振動検出センサの検出値に基づき軸受に発生している振動波形の歪度を所定サンプリング時間毎に算出する歪度算出部と、
上記歪度算出部が算出した歪度の値について、正値若しくは負値の一方の値が、予め設定した回数以上連続して検出した場合に上記軸受が異常と判定する異常判定部と、
を備えることを特徴とする回転軸受の状態判定装置。 A bearing state determination device for supporting a rotating shaft,
A vibration detection sensor for detecting the vibration of the bearing;
A skewness calculation unit that calculates the skewness of the vibration waveform generated in the bearing based on the detection value of the vibration detection sensor for each predetermined sampling time;
For the skewness value calculated by the skewness calculation unit, an abnormality determination unit that determines that the bearing is abnormal when one of a positive value and a negative value is detected continuously for a preset number of times,
A state determination device for a rotary bearing, comprising: 診断対象の軸受の正常状態での歪度の平均値を記憶する正常値記憶部を備え、
上記歪度算出部は、算出する歪度から上記平均値を引くことで当該歪度の校正処理を行う歪度校正部を有することを特徴とする請求項１又は請求項２に記載した回転軸受の状態判定装置。 A normal value storage unit that stores an average value of skewness in a normal state of a bearing to be diagnosed,
3. The rotary bearing according to claim 1, wherein the skewness calculation unit includes a skewness calibration unit that performs a calibration process on the skewness by subtracting the average value from the calculated skewness. State determination device. 回転軸を支承する軸受の状態判定方法であって、
上記軸受の振動波形から歪度を定期的に算出し、算出した歪度の絶対値の時系列な変化に基づき、上記軸受の異常を判定することを特徴とする回転軸受の状態判定方法。 A method for determining the state of a bearing that supports a rotating shaft,
A method for determining a state of a rotating bearing, wherein the degree of distortion is periodically calculated from a vibration waveform of the bearing, and abnormality of the bearing is determined based on a time-series change in the absolute value of the calculated degree of distortion. 回転軸を支承する軸受の状態判定方法であって、
上記軸受の振動波形から歪度を定期的に算出し、定期的に算出した歪度の値について、正値又は負値の一方が所定回数連続して出力されているか否かを監視することで異常判定を行うことを特徴とする回転軸受の状態判定方法。 A method for determining the state of a bearing that supports a rotating shaft,
By periodically calculating the skewness from the vibration waveform of the bearing and monitoring whether the positive value or the negative value is continuously output a predetermined number of times for the periodically calculated skewness value. A method for determining a state of a rotary bearing, wherein abnormality determination is performed. 診断対象の軸受の正常状態での上記歪度の平均値を予め求めておき、
上記算出した歪度を上記平均値で校正した値に基づき、上記異常判定を行うことを特徴とする請求項４又は請求項５に記載した回転軸受の状態判定方法。 Obtain the average value of the skewness in the normal state of the bearing to be diagnosed in advance,
6. The method according to claim 4, wherein the abnormality determination is performed based on a value obtained by calibrating the calculated skewness with the average value.
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