JPS5863832A - Monitoring method for periodically moving body - Google Patents
Monitoring method for periodically moving bodyInfo
- Publication number
- JPS5863832A JPS5863832A JP56163806A JP16380681A JPS5863832A JP S5863832 A JPS5863832 A JP S5863832A JP 56163806 A JP56163806 A JP 56163806A JP 16380681 A JP16380681 A JP 16380681A JP S5863832 A JPS5863832 A JP S5863832A
- Authority
- JP
- Japan
- Prior art keywords
- calculator
- value
- moment
- bicoherence
- variance
- 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.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
- G01M13/02—Gearings; Transmission mechanisms
- G01M13/021—Gearings
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Rolling Contact Bearings (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
- Transmission Devices (AREA)
Abstract
Description
【発明の詳細な説明】
本発明はベアリング、歯車等のように周期運動を行う物
体即ち周期運動体及びこnを備えた機器の監視方法に関
する。DETAILED DESCRIPTION OF THE INVENTION The present invention relates to objects that perform periodic motion such as bearings, gears, etc., that is, periodic moving bodies, and a method for monitoring equipment equipped with the same.
一般にベアリング、歯車等の周期運動体及びこハらを備
えた機器において、部品の傷、回転軸の偏心、潤滑の不
良等の異常が発生した場合には、こnを放置するとベア
リング、山車等の部品的破損のみならず、こnを備えた
轡械全体の故障、破壊を惹起する。従ってこのような異
常を正確に把握することはベアリング、山車等をイイす
る機器の保守・び埋土、極めて21(装な諌頭である。In general, if abnormalities such as scratches on parts, eccentricity of rotating shaft, poor lubrication, etc. occur in equipment equipped with periodic moving bodies and parts such as bearings and gears, if this problem is left untreated, bearings, floats, etc. This can cause not only damage to the parts, but also failure and destruction of the entire machine equipped with this. Therefore, accurately grasping such abnormalities is extremely difficult to maintain, such as maintenance of equipment such as bearings and floats, and soil burial.
従来このような異常を正fに把握するためVC周Jul
運動体にセンサを取り付け、その出力信号から得られる
1時系列データより、その実効値即ち下記(1)式に示
すRMS (Root Mean Squ、are )
値を求め、その解析によってベアリング、歯車等の周期
運動体、更にはこれらを備えた機器も含めた被監視体の
診断、監視が行わn、ていた。Conventionally, in order to accurately grasp such abnormalities, VC Zhou Jul.
A sensor is attached to a moving object, and from one time series data obtained from its output signal, its effective value, that is, RMS (Root Mean Squ, are) shown in the following equation (1) is calculated.
The values were determined and analyzed to diagnose and monitor objects to be monitored, including periodic moving objects such as bearings and gears, as well as equipment equipped with these objects.
但し、x(t) :時系列データ(t = 1.2 ・
N)N :データ数
i:時系列データガt)の平均値
この方法はその長所として被監視体の劣化度を全体的[
把握するのに有利であることがあげられるが、RMS値
が被監視体のサイズ、負荷の大小、回転速度等によって
区々に異なり、普遍的なモ」新基準を設けることができ
な°いので、個々の正常時のデータを蓄積しておく必要
があった。捷た微妙な異常を判定する場合vcは周波数
成分間のゆらぎはあっても信号全体のRMEI値は変化
しないという感度の低さが間枳であった。However, x(t): time series data (t = 1.2 ・
N) N: Number of data i: Average value of time series data
However, the RMS value varies depending on the size of the object to be monitored, the magnitude of the load, the rotation speed, etc., and it is not possible to establish a new universal standard. Therefore, it was necessary to accumulate individual normal data. When determining subtle abnormalities such as distortion, VC has a low sensitivity in that even though there may be fluctuations between frequency components, the RMEI value of the entire signal does not change.
本発明は斯かる事情に鑑みてなされたものであり、被監
視体の劣化度を全体的に把握することができる上に普遍
的な判断基準にてW+価でき、更には微妙な異常に対し
ても感度よく判定できる周期運動体の監視方法を提供す
ることを目的とする。The present invention has been made in view of the above circumstances, and it is possible to grasp the overall degree of deterioration of the monitored object, and also to evaluate the W+ rating based on universal judgment criteria, and also to detect subtle abnormalities. It is an object of the present invention to provide a method for monitoring periodic moving objects that can be determined with high sensitivity even when the object is moving.
本発明に係る周期運動体の監視方法は、周期運動体の振
動を一定周期でサンプリングして得た時系列データを基
に、その実効値と、その確率密度関数の4次モーメント
をその分散にて除して正規化した指標と、任意に選択し
た周波数に関して求めたパイコヒーレンスとを求め、こ
nらを組み会わせて周期運動体の劣化度を総合的に判定
することによりその異常を検知することを%徴とする。The method for monitoring a periodic body according to the present invention is based on time series data obtained by sampling the vibrations of a periodic body at a constant period, and calculates its effective value and the fourth moment of its probability density function as its variance. The index normalized by dividing by It is a percentage mark.
上述した各値のうち、実効値は前述した如く被監視体の
劣化度を全体的に把握するのに有利であり、また時系列
データの確率密度関数の4次モーメントを時系列データ
の分散にて除して正規化した指標は被監視体のサイズ、
負荷の大小、回転速度等に左右さfl、ない普遍的な異
常判定基準を設けることができ、史に任意に選択した周
波数に曲して求めたパイコヒーレンスは時系列データ中
に弁別しにぐい雑音が含捷A、る場合であっても異常が
検出できる。従ってそn、らの夫々の411点全有効に
組み合わせて周期運動体の劣化度を総合的に判定するの
が本発明に係る周期運動体の監視方法であるO
以下本発明方法を図面f基いて詳述する。第1図はその
実施に使用する装置1v(71略示ブロック図であって
振動発生体1vCはその撮動を検出して電気信号に変換
する眼@検出装置2が取り付けられている0この]辰動
+東出装置2の出力はザンプリング装膚3へ人力さnl
そこで一定周期にてサンプリングさハ1、アナログデー
タからディジタルデータへ変侠されて記憶装置4ヘスド
アされていく。この記憶装置t 4にストアされた時系
列データx (t)はRMS値計算装置5、パイコヒー
レンス計算装置6及びに値計算装置7に夫々取り込まれ
て、各計算装置により以下に述べる演算処理が行わ几る
。Among the above-mentioned values, the effective value is advantageous in understanding the overall degree of deterioration of the monitored object as described above, and the fourth moment of the probability density function of time-series data can be used to calculate the variance of time-series data. The normalized index is the size of the monitored object,
It is possible to establish a universal abnormality judgment criterion that is independent of load size, rotation speed, etc., and the pi coherence obtained by bending to an arbitrarily selected frequency in history is difficult to distinguish in time series data. Abnormalities can be detected even when noise is present. Therefore, the method for monitoring a periodic moving body according to the present invention is to effectively combine all of the 411 points to comprehensively determine the degree of deterioration of the periodic moving body. This will be explained in detail. FIG. 1 is a schematic block diagram of a device 1v (71) used for the implementation, in which the vibration generator 1vC is attached with an eye detection device 2 that detects the imaging and converts it into an electrical signal. The output of the Shindo+Higashide device 2 is transferred to the Zampling skin 3 by human power.
Therefore, the data is sampled at regular intervals and converted from analog data to digital data and stored in the storage device 4. The time series data x (t) stored in the storage device t4 is taken into the RMS value calculation device 5, the pi coherence calculation device 6, and the value calculation device 7, respectively, and the calculation processing described below is performed by each calculation device. Do it.
詰!lJ RMS値計算装置5においては、時系列デー
タx (t) vcついて前記+1j式による演算が行
われて、実効値即ちRMS値が求められる。またパイコ
ヒーレンス計算装置6においては、下記(2)式による
演算が行われて、パイコヒーレンスBie、 XXX(
fl +f2)が求められる。Tsume! In the lJ RMS value calculation device 5, the time series data x (t) vc is computed using the above +1j formula to obtain an effective value, that is, an RMS value. In addition, in the pi-coherence calculation device 6, the calculation according to the following equation (2) is performed, and the pi-coherence Bie, XXX(
fl + f2) is obtained.
但し、fl、f2:係り合いを調べたい2つの周波数B
XXx(fl、f2)二時係列データx(t)から得ら
れる3次相関関数をフーリエ変
換したパイスペクトル。However, fl, f2: two frequencies B whose relationship is to be investigated
XXx (fl, f2) Pi spectrum obtained by Fourier transforming the cubic correlation function obtained from the two-time series data x(t).
T′
5XX(f)二部波数f[おけるパワースペクトル即ち
5XX(f)=〒X(f)・X寥(f)T:データ取得
期間
X(f) :原系列データx (t)のフーリエ変換部
チx(f)=丁:x(the−j2?l’f″dt*:
共役複素数
更にに値計算装置7においては下記(3)式による演算
が行われ、時系列データx(t)の確率重度関数の4次
モーメントを時系列データx (t)の分故にて除して
正規化した指標即ちに値が求めら1.る。なおモーメン
トとしてfd中心モーメントを用いる。T' 5XX(f) Power spectrum at bipartite wave number f [i.e. 5XX(f) = 〒X(f)・X寥(f) T: Data acquisition period X(f): Fourier of original sequence data x(t) Conversion part x(f) = d:x(the-j2?l'f″dt*:
Conjugate complex number Further, in the value calculation device 7, calculation is performed according to the following formula (3), and the fourth moment of the probability severity function of time series data x (t) is divided by the factor of time series data x (t). The normalized index, that is, the value is found.1. Ru. Note that the fd center moment is used as the moment.
但し、P(x) :時系列データx (t)の確率密度
関数μ4:4次モーメント
σ2:時系列テータx (t)の分散
斯<L、CqDうn、たRMS4fα、パイコヒーレン
ス及びに値に関するデータは、基準データ記憶装置8に
記憶されている正常レベル及ヒ寿命レベルvc1.31
]するデータと共に比較(ロ)路9へ入力され、そこで
比較さt″した結果、被監視体が異常と総合判定される
と誓報装置に10へ信号が送られ、ν報が発せられるよ
うKなっている。However, P(x): Probability density function of time series data x (t) μ4: Fourth moment σ2: Dispersion of time series theta x (t) The data regarding the normal level and the lifespan level vc1.31 stored in the reference data storage device 8
] is input to the comparison (b) path 9 together with the data, and as a result of the comparison t'' there, if the monitored object is comprehensively determined to be abnormal, a signal is sent to the alarm device 10 so that a ν alarm is issued. It's K.
ルー1−l)・る装置ドを用いて周期運動体を監視する
場合は?Xに述べるような優れた周期運動体の監視が可
能となる。即ちR,MS値割算装置5において求めらf
′したRMS値は前述の如く被監視体の劣化度を全体的
に杷握する上で有利であり、1だパイコヒーレンス計算
装置6Vこおいて求めら1′1だパイコヒーレンスは微
妙な異常を検知する・上で特に優れており、更にに値計
傳装fi 7において求められたに値は被幣視体のサイ
ズ、負荷の大小、回転速度外に匠右され々い絶対的な評
価をする上で不動であり、上述の装置を用いて不発明方
法を実施丁−る場合はこれらを組みばわぜて総合的に判
定するので、信頼性が高い同!す(運動体の監視が可能
となるOなお本実〃1q例では、RMS値計算装爵5、
パイコヒーレンス計算装置6及びK 4jn−W−1−
算装置7πて夫々演算処理が行わ几ることとしたが、1
つの計算装置にて全ての演算処理を行うようにしてもよ
い。What should I do when monitoring a periodic moving object using a device like Ru1-l)? This enables excellent monitoring of periodic moving bodies as described in Section X. That is, R, which is calculated by the MS value dividing device 5, is
As mentioned above, the RMS value obtained is useful in controlling the overall degree of deterioration of the monitored object. It is particularly excellent in detection, and furthermore, the value determined by the value meter denso fi 7 is an absolute evaluation that is influenced by the size of the target object, the magnitude of the load, and the rotation speed. When implementing the non-inventive method using the above-mentioned device, these devices are combined to make a comprehensive judgment, so the method is highly reliable. (In the 1q example, RMS value calculation 5,
Pi coherence calculation device 6 and K 4jn-W-1-
It was decided that the arithmetic processing would be performed in each calculation device 7π, but 1
All arithmetic processing may be performed by one computing device.
次にベアリングによって支承さf′lた複数のa3車を
用いて動力を減速伝達する減速機を上述の装置を用いて
監視した実施例について述べる。正冨状νに、無給油状
す、察(ケースl)、両市に小さな傷を付した状態(ケ
ース2)、歯車に中程度の錫を付した状態(ケース3)
及び歯車に太さな慟を1」シた状、軒(ケース4)の谷
状匹についてRMS値、パイコヒーレンス及びに値を夫
々糾出した結果を1とめたグラフが第2図、第3図及び
8114図である。Next, an example will be described in which the above-mentioned device is used to monitor a speed reducer that decelerates and transmits power using a plurality of A3 wheels supported by bearings. Normal condition ν with no lubrication (Case 1), small scratches on both sides (Case 2), medium amount of tin on the gear (Case 3)
Figures 2 and 3 are graphs showing the results of the RMS value, pi coherence, and value for the gear with a 1"-thick hole shape and the valley shape of the eaves (Case 4). Figure 8114.
2g2図に示すRMlllljについてみると、その絶
対値は減速機の劣化度に相応する基準かがい限り評価で
きないが、その劣化度に応じてRMSll(jが増大し
てセリ、被監視体の劣化度を全体的に杷握する上で有利
であることをよく示している。甘た第3図に示Tバイコ
ヒーレンスについてみると、+1m1Lの勃の大きさに
よる差が明瞭に表わ1ており、微妙な異常を検知する上
で荷に優1.でいることが分かる。更に第4(り1に示
すに仙についてみると、その杷対仙は正常時において3
.0となり、異常が発生すると3.0からすA、る傾向
を示し、絶対的な評価をする上で有効なことか分かる0
なおケース3.ケース4で系か劣化したにも拘らずに値
が下ったのは、減速機の歯車の捩り固有振動が犬きくな
り、パワースペクトルに著しいピークをなしたためであ
る0
パワースペクトルにピークが1個出米る正弦波であると
K Iqに1.5であり、一般に〕(ワースベクトルに
著しいピークができるような場合に1匣が引き下げらn
、るため、その適切な評価のためには原系列に適当なフ
ィルタリング全施しに値′f′算出することが必要とな
る。従って絶対的な評価?に1直によって行い、劣化度
の全体的な1巴握をRMS 4葭によって行い、微妙な
異常の検知をパイコヒーレンスによって行うことにより
、信頼性が高い周期運動体の監視が可能となる。Regarding RMllllj shown in Figure 2g2, its absolute value cannot be evaluated unless it is a standard that corresponds to the degree of deterioration of the reducer. This clearly shows that it is advantageous in controlling the overall erection.If we look at the T bicoherence shown in Figure 3, the difference depending on the size of the erection of +1ml1L is clearly shown1. It can be seen that it has an advantage of 1. in detecting subtle abnormalities.Furthermore, if we look at the sen as shown in 4.
.. Case 3. The reason why the value decreased in case 4 even though the system had deteriorated was because the torsional natural vibration of the gear of the reducer became sharper and a significant peak appeared in the power spectrum. 0 There was one peak in the power spectrum. For a well-produced sine wave, K Iq is 1.5, and generally]
Therefore, for proper evaluation, it is necessary to calculate the value 'f' after applying appropriate filtering to the original sequence. Therefore, is it an absolute evaluation? Highly reliable monitoring of periodic moving bodies is made possible by performing one shift at a time, determining the overall degree of deterioration using RMS 4, and detecting subtle abnormalities using pi-coherence.
以上詳述した如く本発明による場合は、時系列データを
基に、その実効仙(RMS値)と、その確率密度関数の
4次モーメントをその分散によって除して正規化した指
標(K値)と、任意に選択した周波数に関して求めたパ
イコヒーレンスとを)阻み合わせて周期運動体の劣化度
を総合的VC判定することによりその異常を検知するの
で、信頼性か高い周期運動体の監視か可能となる0従っ
て不発明は周IIJ!凍りの体の異常検知技術等の同上
に多大の貢献をなす。As detailed above, in the case of the present invention, based on time series data, its effective value (RMS value) and the index (K value) normalized by dividing the fourth moment of its probability density function by its variance Since abnormalities are detected by comprehensively determining the degree of deterioration of the periodic moving body by VC and the pi-coherence obtained for an arbitrarily selected frequency, it is possible to monitor periodic bodies with high reliability. 0 Therefore, non-invention is Zhou IIJ! He has made a great contribution to the technology for detecting abnormalities in frozen bodies.
君1図は不発明の郵施に使用する装置の略本ブロック図
、第2図は本父明方法を用いて貌出したRMSイi口を
示すグラフ、第3図に本発明方法を用いて′n出したパ
イコヒー1/ンスを示すグラフ、第4図は本発明方法を
田いて算出したに値を示すグラフである。
1・・・振4+1.1発生体 2・・・振!:?υ検出
φ°;詩5・・・RMS値計算装置fF1” 6・・・
パイコヒーレンス計算装置7・・・K値計■装fit
9・・・比較1pl路特許出朗人 住友金属工業株式
会社
代理人 弁丹士 河 野 登 夫αΣの匈
正字68 ケース1 ケース2 ケース3 ケース
4竿 3 口
正室日÷ ケース1 ケース2 ケース3ケーズ4算
4[2]
手に1・補正化(自発)
昭和57生−L、0月19日
、、、fゎ一ヶ□よ ・−L゛/ 事件の表
示 昭和56イト特許頭第163806号ノ 発明の
名称 li!j1貫連101体の曽視方法j 補正を
する者
事(L1〕との関係 特許出願人
所在地 大阪市東区北浜5丁目15番地ダ代理人
j 補正の対象Figure 1 is a schematic block diagram of the device used for the uninvented delivery, Figure 2 is a graph showing the RMS advantage developed using the method of the present invention, and Figure 3 is a graph showing the RMS advantage obtained using the method of the present invention. FIG. 4 is a graph showing the pi coherence calculated using the method of the present invention. 1... Shake 4 + 1.1 generator 2... Shake! :? υ detection φ°; Verse 5... RMS value calculation device fF1" 6...
Pi coherence calculation device 7...K value meter ■fit
9...Comparison 1pl path patent author Roto Sumitomo Metal Industries Co., Ltd. agent Bentanshi Noboru Kawano AlphaΣ's Xiongzhengji 68 Case 1 Case 2 Case 3 Case 4 竿 3 Mouth lawful wife day ÷ Case 1 Case 2 Case 3 cases 4 arithmetic
4 [2] Hand 1/Correction (spontaneous) Born in 1980 - L, October 19th... fゎichiga□yo ・-L゛/ Indication of the case 1982 Itto Patent No. 163806 Invention The name of li! j1 Kanren 101 body viewing method j Relationship with the person making the amendment (L1) Patent applicant location 5-15 Kitahama, Higashi-ku, Osaka Da agent j Subject of amendment
Claims (1)
た時系列データを基に、 その実効値と、 その確率密度関数の4次モーメントをその分散にて除し
て正規化した指標と、 任意に選択した周波数に関して求めたパイコヒーレンス
とを求め、 これらを組み合わせて周期運動体の劣化ノブを総合的に
柚子することによりその異常を検知することを特徴とす
る周期運動体の監視方法。[Claims] 1. Based on the time series data obtained by sampling the vibration of a periodic body at a constant period, the effective value and the fourth moment of the probability density function are divided by its variance. A periodic motion characterized by determining a normalized index and a pi-coherence determined for an arbitrarily selected frequency, and combining these to comprehensively check the deterioration knob of a periodic motion body to detect an abnormality thereof. How to monitor your body.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP56163806A JPS5863832A (en) | 1981-10-13 | 1981-10-13 | Monitoring method for periodically moving body |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP56163806A JPS5863832A (en) | 1981-10-13 | 1981-10-13 | Monitoring method for periodically moving body |
Publications (2)
Publication Number | Publication Date |
---|---|
JPS5863832A true JPS5863832A (en) | 1983-04-15 |
JPS644611B2 JPS644611B2 (en) | 1989-01-26 |
Family
ID=15781054
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
JP56163806A Granted JPS5863832A (en) | 1981-10-13 | 1981-10-13 | Monitoring method for periodically moving body |
Country Status (1)
Country | Link |
---|---|
JP (1) | JPS5863832A (en) |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPS62270820A (en) * | 1986-05-16 | 1987-11-25 | Nippon Kokan Kk <Nkk> | Method and device for bearing failure diagnosis by vibratory sound |
JPH0666241A (en) * | 1992-08-11 | 1994-03-08 | Tokyo Electric Power Co Inc:The | Soundeness diagnostic unit for rotary machine |
WO2004076874A1 (en) * | 2003-02-28 | 2004-09-10 | Thk Co., Ltd. | Condition-detecting device, method, and program, and information-recording medium |
WO2006025404A1 (en) * | 2004-08-31 | 2006-03-09 | Thk Co., Ltd. | State detection device, state detection method, state detection program, and information recording medium; state display device, state display method, state display program, and information recording medium |
-
1981
- 1981-10-13 JP JP56163806A patent/JPS5863832A/en active Granted
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPS62270820A (en) * | 1986-05-16 | 1987-11-25 | Nippon Kokan Kk <Nkk> | Method and device for bearing failure diagnosis by vibratory sound |
JPH0666241A (en) * | 1992-08-11 | 1994-03-08 | Tokyo Electric Power Co Inc:The | Soundeness diagnostic unit for rotary machine |
WO2004076874A1 (en) * | 2003-02-28 | 2004-09-10 | Thk Co., Ltd. | Condition-detecting device, method, and program, and information-recording medium |
US7555953B2 (en) | 2003-02-28 | 2009-07-07 | Thk Co., Ltd. | Condition-detecting device, method, and program, and information-recording medium |
WO2006025404A1 (en) * | 2004-08-31 | 2006-03-09 | Thk Co., Ltd. | State detection device, state detection method, state detection program, and information recording medium; state display device, state display method, state display program, and information recording medium |
US7546211B2 (en) | 2004-08-31 | 2009-06-09 | Thk Co., Ltd. | Condition detection apparatus, condition detection method, condition detection program, information recording medium therefor, and condition display apparatus, condition display method, condition display program, information recording medium therefor |
JP4771334B2 (en) * | 2004-08-31 | 2011-09-14 | Thk株式会社 | Status detection device, status detection method, status detection program and information recording medium, status display device, status display method, status display program and information recording medium |
Also Published As
Publication number | Publication date |
---|---|
JPS644611B2 (en) | 1989-01-26 |
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