JP5879214B2 - Abnormality diagnosis method, abnormality diagnosis device, and passenger conveyor equipped with abnormality diagnosis device - Google Patents
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本発明は、機械設備の異常を診断する異常診断方法、異常診断装置および異常診断装置を備えた乗客コンベアに関する。 The present invention relates to an abnormality diagnosis method for diagnosing an abnormality in mechanical equipment, an abnormality diagnosis device, and a passenger conveyor provided with the abnormality diagnosis device.
機械設備、例えば乗客コンベアの一種であるエスカレータの異常を発見するために、エスカレータの異常診断装置が種々提案されている（例えば特許文献１〜３）。エスカレータに異常振動が発生している場合、異常発生あるいはその前触れであることが多く、異常振動の検出によりエスカレータの故障等に早期に対応することができる。異常を診断するための方法としては、音を用いる方法や振動を用いる方法がある。 Various escalator abnormality diagnosis devices have been proposed in order to discover abnormalities in escalators, which are a type of passenger equipment, for example, a passenger conveyor (for example, Patent Documents 1 to 3). When abnormal vibration is generated in the escalator, it is often the case that an abnormality has occurred or the front is touched, and it is possible to cope with an escalator failure or the like at an early stage by detecting the abnormal vibration. As a method for diagnosing an abnormality, there are a method using sound and a method using vibration.
エスカレータの異常を、振動を検出することによって発見する場合、エスカレータの周辺には多様な振動が発生しており、測定された振動がエスカレータの異常振動でない場合は、異常ではないものを異常であると誤検知してしまう可能性がある。また、エスカレータの設置場所によっては、例えばビル内の空調機器、換気ファン、電源ファン、振動を発生する周囲の他の機械設備等の周囲の環境による振動である環境振動が計測データに混じることで誤検知してしまう可能性がある。 When detecting escalator abnormalities by detecting vibrations, there are various types of vibrations around the escalator. If the measured vibrations are not abnormal escalator vibrations, it is abnormal that is not abnormal. May be misdetected. In addition, depending on the location of the escalator, environmental vibration, which is vibration due to the surrounding environment, such as air conditioning equipment in a building, ventilation fan, power supply fan, and other surrounding mechanical equipment that generates vibration, may be mixed with measurement data. There is a possibility of false detection.
また、特許文献１では、エスカレータのハンドレールについて、稼動部の稼働音と稼動部から隔離した周囲音を収集し、それらの周波数スペクトルを求めて、その差異から乖離度を計算し、乖離度により異常の有無を判定している。しかしながら、この手法では、振動ではなく音を測定しているため、稼動部から隔離した場所で周囲音を稼動音と同時に収集することとなるが、両者は離れた場所であるため稼動部において聞こえる周囲音とは異なっている可能性が高い。 Moreover, in patent document 1, about the escalator handrail, the operation sound of an operation part and the ambient sound isolated from the operation part are collected, those frequency spectra are calculated | required, and a divergence degree is calculated from the difference. The presence or absence of abnormality is judged. However, with this method, sound is measured instead of vibration, so ambient sounds are collected at the same time as the operating sound in a place isolated from the operating part, but both are heard in the operating part because they are separated. It is likely that it is different from the ambient sound.
特許文献２では、エスカレータの稼働時のステップに加わる振動データを計測し、正常時の振動データと比較して異常の有無を判定する。しかしながら、この手法では、経年などにより環境振動が変化した場合に、診断時に計測する振動データに含まれる環境振動と正常時の振動データに含まれる環境振動とが異なってしまう可能性があり、誤検知する可能性がある。 In Patent Literature 2, vibration data applied to a step during operation of the escalator is measured, and the presence / absence of an abnormality is determined by comparison with normal vibration data. However, in this method, when the environmental vibration changes due to aging, the environmental vibration included in the vibration data measured at the time of diagnosis may differ from the environmental vibration included in the normal vibration data. There is a possibility of detection.
特許文献３では、エスカレータの複数の踏段に取り付けた加速度センサの計測データと予め求めておいた正常時のデータとの差分をとり、差分が予め設定された値以上になった踏段位置を異常発生位置として求める。しかしながら、この手法でも、特許文献２の場合と同様に、経年などにより環境振動が変化した場合に誤検知する可能性がある。 In Patent Document 3, the difference between the measured data of the acceleration sensor attached to the plurality of steps of the escalator and the normal data obtained in advance is taken, and the step position where the difference is equal to or greater than a preset value is abnormally generated. Find as position. However, even in this method, as in the case of Patent Document 2, there is a possibility of erroneous detection when environmental vibration changes due to aging or the like.
そこで、本発明の目的は、機械設備の異常を振動により診断する際に、学習時と診断時とで環境振動が変化した場合でも環境振動の影響を低減して誤検知を低減することができる異常診断方法および装置を提供することにある。 Accordingly, an object of the present invention is to reduce the influence of environmental vibrations and reduce false detections even when environmental vibrations change between learning and diagnosis when diagnosing abnormalities in mechanical equipment by vibrations. An object of the present invention is to provide an abnormality diagnosis method and apparatus.
この課題を解決するために、本発明は、例えば、機械設備に設置された振動センサで収集した振動値に基づいて前記機械設備の異常を診断する際に、前記振動センサにより学習時に収集した第１の運転状態に対応する第１の学習振動値と前記振動センサにより学習時に収集した前記第１の運転状態とは異なる第２の運転状態に対応する第２の学習振動値とから、それぞれの特徴量の差分である学習値特徴量差分値を計算し、前記振動センサにより診断時に収集した前記第１の運転状態に対応する第１の学習振動値と前記振動センサにより診断時に収集した前記第２の運転状態に対応する第２の学習振動値とから、それぞれの特徴量の差分である診断値特徴量差分値を計算し、前記学習値特徴量差分値と前記診断値特徴量差分値とを比較して前記機械設備の異常の有無を判定する。 In order to solve this problem, the present invention, for example, when diagnosing abnormalities in the mechanical equipment based on vibration values collected by a vibration sensor installed in the mechanical equipment, A first learning vibration value corresponding to one driving state and a second learning vibration value corresponding to a second driving state different from the first driving state collected at the time of learning by the vibration sensor. A learning value feature value difference value, which is a difference between feature values, is calculated, and the first learning vibration value corresponding to the first driving state collected at the time of diagnosis by the vibration sensor and the first value collected at the time of diagnosis by the vibration sensor. A diagnostic value feature value difference value, which is a difference between the respective feature values, is calculated from the second learning vibration value corresponding to the two driving states, and the learned value feature value difference value and the diagnosis value feature value difference value are Compare before It determines the presence or absence of abnormality of machinery and equipment.
本発明によれば、機械設備の異常を振動により診断する際に、学習時と診断時とで環境振動が変化した場合でも環境振動の影響を低減して誤検知を低減することができる。 According to the present invention, when diagnosing abnormalities in mechanical equipment by vibration, even if environmental vibration changes between learning and diagnosis, the influence of environmental vibration can be reduced and false detection can be reduced.
図１は、本発明の異常診断装置の概要を示すブロック図である。また、図２は、エスカレータに振動センサを設置した概要図である。ここでは、異常診断の対象となる機械設備の一例として、乗客コンベアの一種であるエスカレータ２００を例示して説明する。 FIG. 1 is a block diagram showing an outline of the abnormality diagnosis apparatus of the present invention. Moreover, FIG. 2 is the schematic which installed the vibration sensor in the escalator. Here, the escalator 200 which is a kind of passenger conveyor will be exemplified and described as an example of the mechanical equipment to be subjected to abnormality diagnosis.
図１に示すように、異常診断装置１００は、学習値記憶部Ｂ１０、診断値記憶部Ｂ２０、差分比較部Ｂ３０、警報発生部８０を有する。異常診断装置１００は、学習用の振動値である学習振動値Ｓ１０と、診断用の振動値である診断振動値Ｓ２０が入力され、診断の結果が異常であった場合には異常であることを示すアラーム信号Ｓ３０を出力する。 As illustrated in FIG. 1, the abnormality diagnosis apparatus 100 includes a learning value storage unit B10, a diagnostic value storage unit B20, a difference comparison unit B30, and an alarm generation unit 80. The abnormality diagnosis apparatus 100 receives a learning vibration value S10 that is a vibration value for learning and a diagnosis vibration value S20 that is a vibration value for diagnosis, and indicates that the abnormality is abnormal when the diagnosis result is abnormal. The alarm signal S30 shown is output.
学習値記憶部Ｂ１０は、運転状態Ａ学習振動値記憶部１０と運転状態Ｂ学習振動値記憶部２０とを有し、学習振動値Ｓ１０が入力される。運転状態Ａ学習振動値記憶部１０には、エスカレータの運転状態Ａに対応する学習振動値Ｓ１０が記憶され、運転状態Ｂ学習振動値記憶部２０には、運転状態Ａとは異なる運転状態である運転状態Ｂに対応する学習振動値Ｓ１０が記憶される。そして、運転状態Ａ学習振動値記憶部１０および運転状態Ｂ学習振動値記憶部２０に記憶された学習振動値は、学習値特徴量差分計算部５０へ出力される。 The learning value storage unit B10 includes a driving state A learning vibration value storage unit 10 and a driving state B learning vibration value storage unit 20, and a learning vibration value S10 is input thereto. The driving state A learning vibration value storage unit 10 stores a learning vibration value S10 corresponding to the driving state A of the escalator, and the driving state B learning vibration value storage unit 20 is a driving state different from the driving state A. A learned vibration value S10 corresponding to the driving state B is stored. Then, the learning vibration values stored in the driving state A learning vibration value storage unit 10 and the driving state B learning vibration value storage unit 20 are output to the learning value feature amount difference calculation unit 50.
ここで、学習振動値Ｓ１０は、基準となる正常なエスカレータに設置された振動センサから取得された学習用の振動値であり、診断に先立って予め取得しておく。尚、学習振動値Ｓ１０は、診断対象のエスカレータそのものを用いて正常な状態である設置時などに取得しておいても良いし、診断対象のエスカレータそのものではなく同型の正常な学習用エスカレータを用いて取得しても良い。 Here, the learning vibration value S10 is a learning vibration value acquired from a vibration sensor installed on a normal escalator as a reference, and is acquired in advance prior to diagnosis. The learning vibration value S10 may be acquired at the time of installation in a normal state using the diagnosis target escalator itself, or the normal learning escalator is used instead of the diagnosis target escalator itself. You may get it.
また、運転状態Ａと運転状態Ｂとは互いに異なった運転状態とする。ここで、運転状態には、動いている場合だけでなく、停止している場合も含まれ、エスカレータの運転方向（昇り、下り、停止など）、運転速度（高速、通常速度、低速、停止など）などのうち少なくとも１つが異なっていれば良い。例えば、運転状態Ａが昇り運転で運転状態Ｂが下り運転である場合や、運転状態Ａが高速の昇り運転で運転状態Ｂが低速の昇り運転である場合や、運転状態Ａが昇り運転で運転状態が暗騒運転の場合などが考えられる。ここで、暗騒運転とは、エスカレータの電源は入っているが、ステップは停止した（動いていない）状態をいう。 The driving state A and the driving state B are different driving states. Here, the driving state includes not only the case where the vehicle is moving, but also the case where the vehicle is stopped, the escalator driving direction (ascending, descending, stopping, etc.), the operating speed (high speed, normal speed, low speed, stopping, etc.) ) Etc., at least one of them may be different. For example, when operation state A is ascending operation and operation state B is descending operation, when operation state A is ascending operation at high speed and operation state B is ascending operation at low speed, or when operation state A is ascending operation It may be the case that the state is a quiet driving. Here, the silent operation means a state where the escalator is turned on but the step is stopped (not moving).
診断値記憶部Ｂ２０は、運転状態Ａ診断振動値記憶部３０と運転状態Ｂ診断振動値記憶部４０とを有し、診断振動値Ｓ２０が入力される。運転状態Ａ診断振動値記憶部３０には、エスカレータの運転状態Ａに対応する診断振動値Ｓ２０が記憶され、運転状態Ｂ診断振動値記憶部４０には、運転状態Ｂに対応する診断振動値Ｓ２０が記憶される。そして、運転状態Ａ診断振動値記憶部３０および運転状態Ｂ診断振動値記憶部４０に記憶された診断振動値は、診断値特徴量差分計算部６０へ出力される。 The diagnostic value storage unit B20 includes an operation state A diagnosis vibration value storage unit 30 and an operation state B diagnosis vibration value storage unit 40, and receives a diagnosis vibration value S20. The driving state A diagnostic vibration value storage unit 30 stores a diagnostic vibration value S20 corresponding to the driving state A of the escalator, and the driving state B diagnostic vibration value storage unit 40 stores the diagnostic vibration value S20 corresponding to the driving state B. Is memorized. The diagnostic vibration values stored in the driving state A diagnostic vibration value storage unit 30 and the driving state B diagnostic vibration value storage unit 40 are output to the diagnostic value feature quantity difference calculation unit 60.
ここで、診断振動値Ｓ２０を取得する際の運転状態Ａ、運転状態Ｂは、それぞれ学習振動値Ｓ１０を取得する際の運転状態Ａ、運転状態Ｂと同じ運転状態に設定する。 Here, the driving state A and the driving state B when acquiring the diagnostic vibration value S20 are set to the same driving state as the driving state A and the driving state B when acquiring the learning vibration value S10.
差分比較部Ｂ３０は、学習値特徴量差分計算部５０、診断値特徴量差分計算部６０、比較判定部７０を有し、運転状態Ａ学習振動値記憶部１０、運転状態Ｂ学習振動値記憶部２０、運転状態Ａ診断振動値記憶部３０、運転状態Ｂ診断振動値記憶部４０からの振動値を入力とし、アラーム信号Ｓ３０のトリガーを警報発生部８０へ出力する。 The difference comparison unit B30 includes a learning value feature value difference calculation unit 50, a diagnosis value feature value difference calculation unit 60, and a comparison determination unit 70, and includes a driving state A learning vibration value storage unit 10 and a driving state B learning vibration value storage unit. 20. The vibration value from the driving state A diagnosis vibration value storage unit 30 and the driving state B diagnosis vibration value storage unit 40 is input, and the trigger of the alarm signal S30 is output to the alarm generation unit 80.
学習値特徴量差分計算部５０は、学習時における運転状態Ａと運転状態Ｂの振動値を入力とし、この２つの運転状態の振動値の特徴量の差分を計算して、学習時の振動値の特徴量の差分値（学習値特徴量差分値）を比較判定部７０へ出力する。２つの運転状態の特徴量の差分値を計算することで、２つの運転状態の振動値の両方に含まれているエスカレータ設置環境における環境振動の振動値を取り除くことができ、環境振動の影響を取り除いた２つの運転状態の振動値の特徴量の差分だけが残る。 The learning value feature amount difference calculation unit 50 receives the vibration values of the driving state A and the driving state B at the time of learning, calculates the difference between the characteristic values of the vibration values of the two driving states, and calculates the vibration value at the time of learning. The feature value difference value (learned value feature value difference value) is output to the comparison determination unit 70. By calculating the difference value between the feature values of the two operating states, the vibration value of the environmental vibration in the escalator installation environment included in both of the two operating state vibration values can be removed, and the influence of the environmental vibration can be reduced. Only the difference between the feature values of the vibration values of the two removed operating states remains.
尚、２つの運転状態の振動値の特徴量の差分を計算する方法としては、運転状態Ａと運転状態Ｂの特徴量としてオーバーオール値（Ｏ.Ａ.値）（二乗した値を合計してルートを取った値）を各々計算し、運転状態Ａと運転状態ＢのＯ.Ａ.値の差分を求める方法が考えられる。また、運転状態Ａと運転状態Ｂの特徴量として振動値の周波数成分を各々計算して、周波数成分毎に特徴量の差分を計算することが考えられる。ここで、周波数成分毎に特徴量の差分を計算する際には、予め所定の周波数帯域を設定しておき、この所定の周波数帯域のみで差分を計算するようにしても良いし、主成分分析を行って差分を計算する所定の周波数帯域を決定し、この所定の周波数帯域のみで差分を計算してもよい。 In addition, as a method of calculating the difference between the feature values of the vibration values of the two driving states, as a feature amount of the driving state A and the driving state B, an overall value (OA value) (the sum of squared values is added to the route. The difference between the operating state A and the operating state B can be calculated. Further, it is conceivable to calculate the frequency component of the vibration value as the feature amount of the driving state A and the driving state B and calculate the difference of the feature amount for each frequency component. Here, when calculating the difference in feature amount for each frequency component, a predetermined frequency band may be set in advance, and the difference may be calculated only in this predetermined frequency band, or principal component analysis It is also possible to determine a predetermined frequency band for calculating the difference and calculate the difference only in this predetermined frequency band.
診断値特徴量差分計算部６０は、診断時における運転状態Ａと運転状態Ｂの振動値を入力とし、この２つの運転状態の振動値の特徴量の差分を計算して、診断時の振動値の特徴量の差分値（診断値特徴量差分値）を比較判定部７０へ出力する。２つの運転状態の特徴量の差分値を計算することで、２つの運転状態の振動値の両方に含まれているエスカレータ設置環境における環境振動の振動値を取り除くことができる。ここで、エスカレータに異常がある場合は、環境振動の影響を取り除いた２つの運転状態の振動値の特徴量の差分と、環境振動の影響を取り除いた２つの運転状態の異常振動値の特徴量の差分が残る。また、エスカレータに異常がない場合は、環境振動の影響を取り除いた２つの運転状態の振動値の特徴量の差分だけが残る。尚、２つの振動値の特徴量の差分を計算する方法は必ず学習値特徴量差分計算部５０と同じ方法に設定しておく。 The diagnosis value feature amount difference calculation unit 60 receives the vibration values of the driving state A and the driving state B at the time of diagnosis, calculates the difference between the feature values of the vibration values of the two driving states, and calculates the vibration value at the time of diagnosis. The feature value difference value (diagnostic value feature value difference value) is output to the comparison determination unit 70. By calculating the difference value between the feature values of the two operation states, the vibration value of the environmental vibration in the escalator installation environment included in both of the vibration values of the two operation states can be removed. Here, when there is an abnormality in the escalator, the difference between the characteristic values of the vibration values of the two operating states excluding the influence of the environmental vibration and the characteristic amount of the abnormal vibration values of the two operating states excluding the influence of the environmental vibration The difference of remains. Further, when there is no abnormality in the escalator, only the difference between the feature values of the vibration values of the two operating states from which the influence of the environmental vibration is removed remains. Note that the method for calculating the difference between the feature values of the two vibration values is always set to the same method as the learning value feature value difference calculation unit 50.
比較判定部７０は、学習値特徴量差分計算部５０と診断値特徴量差分計算部６０から、それぞれ学習時の運転状態Ａと運転状態Ｂの振動値の特徴量の差分値と、診断時の運転状態Ａと運転状態Ｂの振動値の特徴量の差分値を入力とし、この２つの特徴量の差分値を比較して、異常の有無を判定し、異常があると判定した場合には警報発生手段８０へアラーム信号Ｓ３０のトリガーを出力する。 The comparison / determination unit 70 obtains the difference between the feature values of the vibration values of the driving state A and the driving state B during the learning from the learning value feature amount difference calculating unit 50 and the diagnostic value feature amount difference calculating unit 60, respectively. The difference value of the feature value of the vibration value between the driving state A and the driving state B is input, and the difference value of the two feature values is compared to determine the presence or absence of an abnormality. The trigger of the alarm signal S30 is output to the generating means 80.
ここで、学習時の差分値と診断時の差分値との差分を計算すると、２つの差分値の両方に含まれている２つの運転状態の振動値の特徴量の差分値を取り除くことができる。エスカレータに異常がある場合は、２つの運転状態の異常振動値の特徴量の差分が残る。エスカレータに異常がない場合は、差分が生じない。２つの差分値を比較して異常の有無を判定する方法として、２つの差分値の差分を計算し、その値が予め決められた閾値以上の場合に異常と判定する方法が考えられる。 Here, when the difference between the difference value at the time of learning and the difference value at the time of diagnosis is calculated, it is possible to remove the difference value between the feature values of the vibration values of the two driving states included in both of the two difference values. . When there is an abnormality in the escalator, the difference between the characteristic amounts of the abnormal vibration values of the two operating states remains. If there is no abnormality in the escalator, there will be no difference. As a method of comparing the two difference values to determine the presence or absence of an abnormality, a method of calculating the difference between the two difference values and determining that there is an abnormality when the value is equal to or greater than a predetermined threshold value can be considered.
警報発生部８０は、アラーム信号Ｓ３０のトリガーを入力し、アラーム信号Ｓ３０の出力の要否を判定し、出力要と判定した場合は、アラーム信号Ｓ３０を出力する。アラーム信号Ｓ３０のトリガーが入力されたら、すぐにアラーム信号Ｓ３０を出力する方法と、入力されたアラーム信号Ｓ３０のトリガーをカウントし、カウント数が予め決められた時間内で、予め決められた閾値以上となった場合にのみ、予め決められた頻度以上であると判定し、アラーム信号Ｓ３０を出力する方法が考えられる。 The alarm generation unit 80 inputs a trigger for the alarm signal S30, determines whether the output of the alarm signal S30 is necessary, and outputs the alarm signal S30 when it is determined that output is necessary. When the trigger of the alarm signal S30 is input, the method of outputting the alarm signal S30 immediately and the trigger of the input alarm signal S30 are counted, and the count number is equal to or greater than a predetermined threshold within a predetermined time. Only in such a case, a method of determining that the frequency is equal to or higher than a predetermined frequency and outputting the alarm signal S30 can be considered.
アラーム信号Ｓ３０は、監視センタに通報される。また、アラーム信号Ｓ３０が出力された場合に、音や光などで異常であることを知らせてもよい。 The alarm signal S30 is reported to the monitoring center. Further, when the alarm signal S30 is output, it may be informed that it is abnormal by sound or light.
図２は、エスカレータに振動センサを設置した概要図である。エスカレータ２００は、駆動装置２０５と、駆動装置２０５によって駆動される駆動ターミナルギア２０２Ａと、駆動ターミナルギア２０２Ａに巻き掛けられたステップチェーン２０４と、ステップチェーン２０４が巻き掛けられて従動する従動ターミナルギア２０２Ｂ、ステップチェーン２０４に連結され無端状に循環移動する複数のステップ２０３と、ステップ２０３に同期して駆動されるハンドレール２０６と、ハンドレール２０６を駆動するハンドレール駆動ローラ２０７とを有している。 FIG. 2 is a schematic diagram in which a vibration sensor is installed on the escalator. The escalator 200 includes a driving device 205, a driving terminal gear 202A driven by the driving device 205, a step chain 204 wound around the driving terminal gear 202A, and a driven terminal gear 202B driven by the step chain 204 being wound around. , And a plurality of steps 203 that are connected to the step chain 204 and circulate endlessly, a handrail 206 that is driven in synchronization with the step 203, and a handrail drive roller 207 that drives the handrail 206. .
異常診断装置１００による診断対象として、例えば、駆動ターミナルギア２０２Ａや従動ターミナルギア２０２Ｂに設けられたターミナルギヤベアリング２０１や、ハンドレール駆動ローラ２０７などが考えられる。図２では、ターミナルギヤベアリング２０１に振動センサ３００を設け、ハンドレール駆動ローラ２０７に振動センサ３０１を設けた例を示したが、これに限られるものではない。振動センサ３００、３０１としては、例えば加速度センサなどを用いることができる。 As a diagnosis target by the abnormality diagnosis apparatus 100, for example, a terminal gear bearing 201 provided on the drive terminal gear 202A or the driven terminal gear 202B, a handrail drive roller 207, or the like can be considered. Although FIG. 2 shows an example in which the vibration sensor 300 is provided in the terminal gear bearing 201 and the vibration sensor 301 is provided in the handrail drive roller 207, the present invention is not limited to this. As the vibration sensors 300 and 301, for example, an acceleration sensor can be used.
異常診断装置１００は図示しない任意の場所に設置され、様々な運転状態において振動センサ３００や振動センサ３０１から診断振動値Ｓ２０を取得し、異常診断を行う。この異常診断は、定期検査の際に行っても良いし、通常運行中に行っても良い。通常運行中に行えば、定期検査前に早期に監視センタに通報することができる。 The abnormality diagnosis apparatus 100 is installed at an arbitrary place (not shown), acquires a diagnostic vibration value S20 from the vibration sensor 300 or the vibration sensor 301 in various operating states, and performs abnormality diagnosis. This abnormality diagnosis may be performed during regular inspections or during normal operation. If this is done during normal operation, the monitoring center can be notified early before the regular inspection.
また、異常診断装置１００による診断は、乗客コンベアの一種である動く歩道に適用しても良い。また、乗客コンベアに限られず、他の機械設備に適用しても良い。 Moreover, you may apply the diagnosis by the abnormality diagnosis apparatus 100 to the moving walkway which is a kind of passenger conveyor. Moreover, you may apply not only to a passenger conveyor but to other mechanical equipment.
本実施例の異常診断装置によれば、機械設備の異常を振動により診断する際に、学習時と診断時のそれぞれで運転状態Ａと運転状態Ｂの振動値の特徴量の差分を計算しているので、学習時と診断時とでそれぞれ環境振動の影響を取り除くことができ、学習時と診断時とで環境振動が変化した場合でも環境振動の影響を低減して誤検知を低減することができる。 According to the abnormality diagnosing device of the present embodiment, when diagnosing an abnormality of a mechanical facility by vibration, the difference between the characteristic values of the vibration values of the driving state A and the driving state B is calculated at the time of learning and at the time of diagnosis. Therefore, it is possible to remove the influence of environmental vibration at the time of learning and at the time of diagnosis, and even if the environmental vibration changes between learning and at the time of diagnosis, the influence of environmental vibration can be reduced and false detection can be reduced. it can.
また、学習時と診断時とでそれぞれ環境振動の影響を取り除いているので、学習時と診断時とで同型の異なる機械設備を用いて振動値を取得しても診断が可能である。 In addition, since the influence of environmental vibration is removed at the time of learning and at the time of diagnosis, diagnosis can be performed even if vibration values are acquired using the same type of mechanical equipment at the time of learning and at the time of diagnosis.
また、１つの振動センサを用いて、診断対象の機器の位置における環境振動を含んだ振動値を計測できるので、異なる位置に設けられた別の振動センサで環境振動を計測する場合に比べて正確な診断が可能になる。 In addition, since one vibration sensor can be used to measure vibration values including environmental vibration at the position of the device to be diagnosed, it is more accurate than when environmental vibration is measured using another vibration sensor provided at a different position. Diagnosis becomes possible.
また、運転状態Ａと運転状態Ｂとのうち一方の運転状態を暗騒運転の状態とすれば、動いているときのみ発生する異常振動をより正確に検出できる。 Further, if one of the driving state A and the driving state B is set to the noise driving state, it is possible to more accurately detect abnormal vibration that occurs only when the vehicle is moving.
以上、本発明の実施例を説明してきたが、これまでの各実施例で説明した構成はあくまで一例であり、本発明は、技術思想を逸脱しない範囲内で適宜変更が可能である。また、それぞれの実施例で説明した構成は、互いに矛盾しない限り、組み合わせて用いても良い。 As mentioned above, although the Example of this invention has been described, the structure demonstrated by each Example so far is an example to the last, and this invention can be suitably changed within the range which does not deviate from a technical idea. Further, the configurations described in the respective embodiments may be used in combination as long as they do not contradict each other.
１０…運転状態Ａ学習振動値記憶部、２０…運転状態Ｂ学習振動値記憶部、３０…運転状態Ａ診断振動値記憶部、４０…運転状態Ｂ診断振動値記憶部、５０…学習値特徴量差分計算部、６０…診断値特徴量差分計算部、７０…比較判定部、８０…警報発生部、１００…異常診断装置、Ｂ１０…学習値記憶部、Ｂ２０…診断値記憶部、Ｂ３０…差分比較部、Ｓ１０…学習振動値、Ｓ２０…診断振動値、Ｓ３０…アラーム信号。 DESCRIPTION OF SYMBOLS 10 ... Driving state A learning vibration value memory | storage part, 20 ... Driving state B learning vibration value memory | storage part, 30 ... Driving state A diagnostic vibration value memory | storage part, 40 ... Driving state B diagnostic vibration value memory | storage part, 50 ... Learning value feature-value Difference calculation unit, 60 ... diagnosis value feature amount difference calculation unit, 70 ... comparison determination unit, 80 ... alarm generation unit, 100 ... abnormality diagnosis device, B10 ... learning value storage unit, B20 ... diagnosis value storage unit, B30 ... difference comparison Part, S10 ... learning vibration value, S20 ... diagnostic vibration value, S30 ... alarm signal.
Claims (17)
前記振動センサにより学習時に収集した第１の運転状態に対応する第１の学習振動値と前記振動センサにより学習時に収集した前記第１の運転状態とは異なる第２の運転状態に対応する第２の学習振動値とから、それぞれの特徴量の差分である学習値特徴量差分値を計算し、
前記振動センサにより診断時に収集した前記第１の運転状態に対応する第１の学習振動値と前記振動センサにより診断時に収集した前記第２の運転状態に対応する第２の学習振動値とから、それぞれの特徴量の差分である診断値特徴量差分値を計算し、
前記学習値特徴量差分値と前記診断値特徴量差分値とを比較して前記機械設備の異常の有無を判定することを特徴とする異常診断方法。 In the abnormality diagnosis method for diagnosing abnormality of the mechanical equipment based on the vibration value collected by the vibration sensor installed in the mechanical equipment,
A first learning vibration value corresponding to the first driving state collected during learning by the vibration sensor and a second driving state corresponding to a second driving state different from the first driving state collected during learning by the vibration sensor. The learning value feature value difference value, which is the difference between the respective feature values, is calculated from the learning vibration value of
From the first learning vibration value corresponding to the first driving state collected at the time of diagnosis by the vibration sensor and the second learning vibration value corresponding to the second driving state collected at the time of diagnosis by the vibration sensor, Calculate the diagnostic value feature value difference value, which is the difference between each feature value,
Comparing the learned value feature value difference value and the diagnosis value feature value difference value to determine whether there is an abnormality in the mechanical equipment.
前記振動センサにより学習時に収集した第１の運転状態に対応する第１の学習振動値と前記振動センサにより学習時に収集した前記第１の運転状態とは異なる第２の運転状態に対応する第２の学習振動値とから、それぞれの特徴量の差分である学習値特徴量差分値を計算する学習値特徴量差分計算部と、
前記振動センサにより診断時に収集した前記第１の運転状態に対応する第１の学習振動値と前記振動センサにより診断時に収集した前記第２の運転状態に対応する第２の学習振動値とから、それぞれの特徴量の差分である診断値特徴量差分値を計算する診断値特徴量差分計算部と、
前記学習値特徴量差分値と前記診断値特徴量差分値とを比較して前記機械設備の異常の有無を判定する比較判定部とを有することを特徴とする異常診断装置。 In the abnormality diagnosis device for diagnosing abnormality of the mechanical equipment based on the vibration value collected by the vibration sensor installed in the mechanical equipment,
A first learning vibration value corresponding to the first driving state collected during learning by the vibration sensor and a second driving state corresponding to a second driving state different from the first driving state collected during learning by the vibration sensor. A learning value feature value difference calculating unit that calculates a learning value feature value difference value that is a difference between the respective feature values from the learning vibration value of
From the first learning vibration value corresponding to the first driving state collected at the time of diagnosis by the vibration sensor and the second learning vibration value corresponding to the second driving state collected at the time of diagnosis by the vibration sensor, A diagnostic value feature quantity difference calculation unit that calculates a diagnostic value feature quantity difference value that is a difference between the respective feature quantities;
An abnormality diagnosis apparatus comprising: a comparison determination unit that compares the learned value feature value difference value and the diagnosis value feature value difference value to determine whether there is an abnormality in the mechanical equipment.
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