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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