JP2020064021A - Vibration tester for damper - Google Patents

Vibration tester for damper Download PDF

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JP2020064021A
JP2020064021A JP2018197264A JP2018197264A JP2020064021A JP 2020064021 A JP2020064021 A JP 2020064021A JP 2018197264 A JP2018197264 A JP 2018197264A JP 2018197264 A JP2018197264 A JP 2018197264A JP 2020064021 A JP2020064021 A JP 2020064021A
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damper
expansion
contraction
actuator
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JP7228180B2 (en
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恵太 増田
Keita Masuda
恵太 増田
一志 眞田
Kazushi Sanada
一志 眞田
悠太 中村
Yuta Nakamura
悠太 中村
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Yokohama National University NUC
Kayaba System Machinery Co Ltd
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Kayaba System Machinery Co Ltd
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Abstract

To provide a vibration tester for a damper capable of causing damper vibrations to coincide with a target command with high accuracy.SOLUTION: According to the present invention, a vibration tester 1 for a damper includes: an actuator A for giving vibrations to a telescopic damper D; a detector S for detecting two pieces of information having a phase shift of 90 degrees among three pieces of information of the expansion and contraction displacement x, expansion and contraction velocity v, and expansion and contraction acceleration α of the damper D; a correction device 6 for using a neural network model by inputting information obtained by detecting a target command Uby the detector, and acquiring a correction value R for canceling reaction force of the damper D; and a controller C for giving a correction command U acquired by correcting the target command Uby the correction device 6 to the actuator A to control the actuator A.SELECTED DRAWING: Figure 2

Description

本発明は、ダンパの振動試験装置に関する。   The present invention relates to a vibration test device for a damper.

一般に、プラントに対して指令を入力して、プラントの出力を目標波形通りに制御するシステムとしては、プラントの出力を検知して、この出力をフィードバックして目標波形が指示する指示値との偏差を求め、ＰＩ補償やＰＩＤ補償を行ってプラントへ与える指令を求めるものがある。このように、フィードバック制御を行うシステムとしては、たとえば、ダンパに油圧アクチュエータで振動を与えてダンパの疲労耐久性をテストするダンパの振動試験装置がある。   Generally, as a system that inputs a command to the plant and controls the output of the plant according to the target waveform, the output of the plant is detected and this output is fed back to obtain the deviation from the indicated value indicated by the target waveform. , And PI compensation and PID compensation are performed to obtain a command to be given to the plant. Thus, as a system for performing feedback control, for example, there is a damper vibration test apparatus that tests the fatigue durability of the damper by applying vibration to the damper with a hydraulic actuator.

ダンパに対して油圧アクチュエータで正弦波振動を与えて振動試験を行う振動試験機における油圧アクチュエータは、内部にピストンで区画される伸側室と圧側室とを有するシリンダと、ピストンに連結されてシリンダ内に挿入されてシリンダに対して軸方向に移動可能なロッドと、伸側室と圧側室を油圧源とタンクとに連通可能なサーボ弁とを備えている。このような、油圧アクチュエータを備えた振動試験装置は、油圧アクチュエータの変位、速度或いは加速度をフィードバックするフィードバック制御を行って、サーボ弁を駆動して油圧アクチュエータのストロークと推力を制御する（たとえば、特許文献１参照）。   A hydraulic actuator in a vibration tester that applies a sinusoidal vibration to a damper by a hydraulic actuator to perform a vibration test includes a cylinder having an expansion side chamber and a compression side chamber which are partitioned by a piston, and a cylinder connected to the piston. A rod that is inserted into the cylinder and can move in the axial direction with respect to the cylinder; Such a vibration test apparatus including a hydraulic actuator performs feedback control that feeds back displacement, speed, or acceleration of the hydraulic actuator to drive a servo valve to control the stroke and thrust of the hydraulic actuator (for example, Patent Document 1). Reference 1).

特開平１１−１０１７０８号公報JP, 11-101708, A

ダンパは伸縮すると減衰力と称される反力を発生するため、油圧アクチュエータをフィードバック制御する場合、ダンパが出力する減衰力の影響を加味してやらないとダンパに目標指令通りに振動を与えられない。   When the damper expands and contracts, a reaction force called damping force is generated. Therefore, when the hydraulic actuator is feedback-controlled, the damper cannot be vibrated according to the target command unless the influence of the damping force output by the damper is taken into consideration.

フィードバック制御によって油圧アクチュエータを制御する場合、ダンパの反力を外乱と看做して、ダンパの反力を伝達関数でモデル化して目標指令から差し引いてやれば、ダンパに目標指令通りに振動を与えられるようにも思える。   When controlling a hydraulic actuator by feedback control, if the reaction force of the damper is regarded as a disturbance and the reaction force of the damper is modeled by a transfer function and subtracted from the target command, the damper will be vibrated according to the target command. It seems to be possible.

しかしながら、ダンパ内に充填される作動油には気体が含まれており、ダンパが伸縮する速度に対して出力する減衰力の特性は、図４に示すように、ヒステリシスを持つとともに、速度に対して減衰力が非線形となる特性となる。したがって、伝達関数モデルでは非線形なダンパの減衰力を表現するのは不可能であり、モデル無しでは発生する反力を考慮した制御をすることができないので、目標指令通りにダンパへ振動を与えるのは難しい。   However, since the hydraulic oil filled in the damper contains gas, the characteristic of the damping force output with respect to the speed at which the damper expands and contracts has hysteresis as shown in FIG. The damping force has a non-linear characteristic. Therefore, it is impossible to express the nonlinear damping force of the damper with the transfer function model, and it is not possible to control without considering the reaction force generated without the model. Is difficult

非線形特性を学習し得るニューラルネットワークモデルを利用した油圧アクチュエータの動作の学習およびシステム同定では、目標指令の入力から油圧アクチュエータの出力までのモデルの逆モデルを学習し、目標指令から油圧アクチュエータへ与える操作量を得ることも考えられる。しかしながら、油圧アクチュエータの応答には油圧系やサーボ弁由来の大きな時間遅れがあって、単に畳み込み系のニューラルネットワークモデルを利用しただけでは時間遅れに対応できず、やはり、目標指令にダンパの振動を精度よく追従させるのは難しい。   In learning the operation of hydraulic actuators and system identification using a neural network model that can learn non-linear characteristics, the inverse model of the model from the input of the target command to the output of the hydraulic actuator is learned, and the operation to give to the hydraulic actuator from the target command. It is also possible to get a quantity. However, there is a large time delay in the response of the hydraulic actuator due to the hydraulic system and the servo valve, and it is not possible to deal with the time delay simply by using the convolutional neural network model. It is difficult to make it follow accurately.

そこで、本発明の目的は、ダンパの振動を目標指令に精度よく一致させ得るダンパの振動試験装置の提供である。   Then, the objective of this invention is providing the vibration test apparatus of a damper which can match the vibration of a damper with a target command accurately.

上記した目的を達成するため、本発明のダンパの振動試験装置は、テレスコピック型のダンパに振動を与えるアクチュエータと、ダンパの伸縮変位、伸縮速度および伸縮加速度の三つの情報のうち９０度位相がずれた二つ情報を検知する検知器と、目標指令を前記検知器で検知した情報の入力によってニューラルネットワークモデルを利用してダンパの反力を打ち消す補正値を求める補正器を有し、補正器で目標指令を補正して得た補正指令をアクチュエータへ与えてアクチュエータを制御するコントローラとを備えている。このように構成されたコントローラは、アクチュエータを制御するにあたってダンパの反力を補正器で学習し、ダンパの反力を打ち消す補正値を求め得る。   In order to achieve the above-mentioned object, the vibration test apparatus for a damper of the present invention is configured such that the actuator for giving vibration to the telescopic damper and the three information of the expansion / contraction displacement, expansion / contraction speed and expansion / contraction acceleration of the damper are out of phase by 90 degrees. There is a detector for detecting two different information and a corrector for obtaining a correction value for canceling the reaction force of the damper by using the neural network model by inputting the information detected by the detector for the target command. And a controller for controlling the actuator by giving a correction command obtained by correcting the target command to the actuator. The controller thus configured can learn the reaction force of the damper with the corrector when controlling the actuator, and obtain a correction value that cancels the reaction force of the damper.

また、検知器が伸縮変位、伸縮速度および伸縮加速度の三つの情報の全部を検知し、補正器が伸縮変位、伸縮速度および伸縮加速度の三つの情報を利用して目標指令を補正する補正値を得るようにダンパの振動試験装置を構成してもよく、このようにするとダンパの反力を精度よく打ち消す補正値を得ることができる。   In addition, the detector detects all three pieces of information on expansion / contraction displacement, expansion / contraction speed, and expansion / contraction acceleration, and the corrector uses the three pieces of information on expansion / contraction displacement, expansion / contraction speed, and expansion / contraction acceleration to set the correction value for correcting the target command. The vibration test device for the damper may be configured to obtain the correction value. By doing so, it is possible to obtain a correction value that cancels the reaction force of the damper with high accuracy.

本発明のダンパの振動試験装置によれば、ダンパの振動を目標指令に精度よく一致させ得る。   According to the damper vibration test apparatus of the present invention, the vibration of the damper can be accurately matched with the target command.

一実施の形態におけるダンパの振動試験装置の構成図である。It is a block diagram of the vibration test apparatus of the damper in one embodiment. 一実施の形態におけるダンパの振動試験装置のコントローラの制御ブロック図である。It is a control block diagram of a controller of a vibration testing device of a damper in one embodiment. 補正器の構成を示した図である。It is the figure which showed the structure of the corrector. ダンパの伸縮速度に対する反力である減衰力の特性を示した図である。It is the figure which showed the characteristic of the damping force which is a reaction force with respect to the expansion-contraction speed of a damper.

以下、図に示した実施の形態に基づき、本発明を説明する。図１に示すように、一実施の形態におけるダンパの振動試験装置１は、テレスコピック型のダンパＤに振動を与えるアクチュエータＡと、ダンパＤの伸縮変位、伸縮速度および伸縮加速度の三つの情報を検知する検知器Ｓと、前記三つの情報をフィードバックしてアクチュエータＡを制御するコントローラＣとを備えている。   The present invention will be described below based on the embodiments shown in the drawings. As shown in FIG. 1, a damper vibration test apparatus 1 according to an embodiment detects three pieces of information of an actuator A that vibrates a telescopic damper D, and an expansion / contraction displacement, expansion / contraction speed, and expansion / contraction acceleration of the damper D. And a controller C that controls the actuator A by feeding back the above three pieces of information.

ダンパＤは、テレスコピック型のダンパであって、一端がアクチュエータＡに連結されるとともに他端はダンパの振動試験装置１の門型フレームＦに対して上下動可能に装着されるクランプ２に連結される。   The damper D is a telescopic type damper, one end of which is connected to the actuator A, and the other end of which is connected to a clamp 2 which is vertically movable with respect to the portal frame F of the vibration test apparatus 1 of the damper. It

アクチュエータＡは、本実施の形態では、図１に示すように、直動型の油圧シリンダとされており、コントローラＣからの指令の入力によって、指令が指示する伸縮方向と速度に応じて伸縮する。本実施の形態では、ダンパＤの伸縮方向は、アクチュエータＡの伸縮方向に一致させており、アクチュエータＡが伸縮するとダンパＤの同様に伸縮してダンパＤに振動が与えられる。なお、本実施の形態では、ダンパＤの伸縮方向とアクチュエータＡの伸縮方向とを一致させているが、ダンパＤとアクチュエータＡとを回転可能に連結して、アクチュエータＡに対してダンパＤを斜めに連結して、ダンパＤに伸縮方向の振動の他に横方向の振動を負荷するようにして試験を行ってもよい。   In the present embodiment, as shown in FIG. 1, the actuator A is a direct-acting hydraulic cylinder, and when a command is input from the controller C, the actuator A expands / contracts in accordance with the expansion / contraction direction and speed instructed by the command. . In the present embodiment, the expansion / contraction direction of the damper D is made to coincide with the expansion / contraction direction of the actuator A, and when the actuator A expands / contracts, the damper D expands / contracts in the same manner and vibration is applied to the damper D. In the present embodiment, the expansion / contraction direction of the damper D and the expansion / contraction direction of the actuator A are made to coincide with each other. However, the damper D and the actuator A are rotatably connected to each other so that the damper D is oblique to the actuator A. The test may be carried out by connecting the damper D with the vibration in the lateral direction in addition to the vibration in the expansion / contraction direction.

検知器Ｓは、本実施の形態では、ダンパＤの伸縮加速度αを検知する加速度センサ３と、加速度センサ３で検知した伸縮加速度αを積分して伸縮速度ｖを得る積分器４と、伸縮速度ｖを積分して伸縮変位ｘを得る積分器５とを備えている。なお、検知器Ｓは、ダンパＤの伸縮変位を検知するストロークセンサと、ストロークセンサで検知したダンパＤの伸縮変位ｘを微分してダンパＤの伸縮速度ｖを得る微分器と、微分器で検知したダンパＤの伸縮速度をさらに微分してダンパＤの伸縮加速度αを得る微分器とで構成されてもよい。また、検知器Ｓは、ダンパＤの伸縮加速度αを検知する加速度センサ３と、ダンパＤの伸縮変位を検知するストロークセンサと、伸縮加速度を積分する積分器或いは伸縮変位を微分する微分器とで構成されてもよい。   In the present embodiment, the detector S includes an acceleration sensor 3 that detects the expansion / contraction acceleration α of the damper D, an integrator 4 that obtains an expansion / contraction speed v by integrating the expansion / contraction acceleration α detected by the acceleration sensor 3, and an expansion / contraction speed. and an integrator 5 for integrating v to obtain the expansion / contraction displacement x. The detector S includes a stroke sensor that detects expansion and contraction displacement of the damper D, a differentiator that differentiates the expansion and contraction displacement x of the damper D detected by the stroke sensor to obtain an expansion and contraction speed v of the damper D, and a differentiator. The expansion / contraction speed of the damper D may be further differentiated to obtain the expansion / contraction acceleration α of the damper D. The detector S includes an acceleration sensor 3 that detects the expansion / contraction acceleration α of the damper D, a stroke sensor that detects the expansion / contraction displacement of the damper D, and an integrator that integrates the expansion / contraction acceleration or a differentiator that differentiates the expansion / contraction displacement. It may be configured.

コントローラＣは、図２に示すように、ニューラルネットワークモデルを利用してダンパＤの反力を打ち消す指令を補正値Ｒとして求める補正器６と、入力される目標指令Ｕ＊から補正値Ｒを差し引いて補正指令Ｕを生成する加算器７とを備えて構成されている。 As shown in FIG. 2, the controller C uses a neural network model to obtain a command for canceling the reaction force of the damper D as a correction value R, and subtracts the correction value R from the input target command U *. And an adder 7 that generates a correction command U by means of the above.

補正器６は、目標指令Ｕ＊と、ダンパＤの伸縮変位ｘ、伸縮速度ｖ、伸縮加速度αとの入力を受けて、アクチュエータＡによって振動が入力されることによってダンパＤが出力する反力である減衰力をニューラルネットワークモデルを利用して学習し、このダンパＤの反力を打ち消すための補正値Ｒを求める。 The corrector 6 receives the target command U * , the expansion / contraction displacement x of the damper D, the expansion / contraction speed v, and the expansion / contraction acceleration α, and the vibration is input by the actuator A. A certain damping force is learned using a neural network model, and a correction value R for canceling this reaction force of the damper D is obtained.

具体的には、補正器６は、図３に示すように、目標指令Ｕ＊の他、ダンパＤの伸縮変位ｘ、伸縮速度ｖ、伸縮加速度αの情報を入力層に入力して、各情報に重みづけ係数Ｗ１１，Ｗ１２，・・・Ｗ１ｎ，Ｗ２１，Ｗ２２，・・・Ｗ２ｎ，Ｗ３１，Ｗ３２・・・Ｗ３ｎを乗て重みづけして中間層のｎ個の情報ｙ１，ｙ２，・・・，ｙｎを得る。さらに、補正器６は、これら中間層の情報ｙ１，ｙ２，・・・ｙｎにそれぞれ重みづけ係数Ｗ４１，Ｗ４２，・・・Ｗ４ｎを乗じて重みづけして出力層の補正値Ｒを得る。なお、中間層における情報の個数は、任意に設定できる。 Specifically, as shown in FIG. 3, the corrector 6 inputs information on the expansion / contraction displacement x, expansion / contraction speed v, and expansion / contraction acceleration α of the damper D to the input layer, in addition to the target command U * , and inputs each information. Are weighted by weighting factors W11, W12, ... W1n, W21, W22, ... W2n, W31, W32, ... W3n, and weighted by n pieces of information y1, y2 ,. , Yn. Further, the corrector 6 obtains the correction value R of the output layer by multiplying the information y1, y2, ... Yn of the intermediate layer by the weighting factors W41, W42 ,. The number of pieces of information in the intermediate layer can be set arbitrarily.

補正器６は、目標指令の入力からアクチュエータＡへの操作量が入力される度に、つまり、目標指令に対するダンパＤの応答である三つの情報から入力層の情報が得られる度に、出力層の補正値ＲがダンパＤの減衰力に等しくなるように、重みづけ係数Ｗ１１，Ｗ１２，・・・Ｗ４ｎを調整して、ダンパＤの反力の特性を学習していく。なお、補正器６による学習には、Ａｄａｍの学習側の他、種々の学習則を利用可能である。   The compensator 6 outputs the output layer each time the operation amount is input from the input of the target command to the actuator A, that is, every time the information of the input layer is obtained from the three information that is the response of the damper D to the target command. The weighting factors W11, W12, ..., W4n are adjusted so that the correction value R of the damper D becomes equal to the damping force of the damper D, and the characteristic of the reaction force of the damper D is learned. For learning by the corrector 6, various learning rules other than the learning side of Adam can be used.

このようにして補正器６は、ダンパＤの反力である減衰力を学習するので、ダンパＤの反力を打ち消す補正値Ｒを精度よく求め得る。ダンパＤの伸縮速度ｖと伸縮変位ｘの二つの情報或いは伸縮速度ｖと伸縮加速度αの二つの情報を利用して補正器６で学習する場合、伸縮変位ｘ或いは伸縮加速度αをダンパＤの減衰力のヒステリシスの場合分けの材料として用いることができ、ニューラルネットワークモデルの本来の特性である判別が働き、伸縮速度ｖに対してヒステリシス特性の結びつけが可能なる。また、本来であればダンパＤの反力のヒステリシスの場合分けの材料としては伸縮速度ｖに対するダンパＤの反力の微分もしくは時間微分により成されるが、反力の微分や時間微分を求めるには遅れ特性を持つフィルタを使用する必要があり、制御系に遅れと構成を持つフィルタを利用するとコントローラＣの性能低下につながってしまう。これに対して、ダンパＤの伸縮速度ｖと伸縮変位ｘの二つの情報或いは伸縮速度ｖと伸縮加速度αの二つの情報を利用する場合、ノイズの影響や計測精度が良好なデータを選択して用いることができ、補正器６は、補正値Ｒを効率的に求め得る。なお、本実施の形態では、伸縮変位ｘ、伸縮速度ｖおよび伸縮加速度αの三つの情報を補正器６に入力するようにしているので、補正値Ｒを得るまでの時間の短縮に加えて、より高精度の補正値Ｒが得られる。   In this way, the corrector 6 learns the damping force, which is the reaction force of the damper D, so that the correction value R that cancels the reaction force of the damper D can be accurately obtained. When the compensator 6 learns by using the two information of the expansion / contraction speed v and the expansion / contraction displacement x of the damper D, or the two information of the expansion / contraction speed v and the expansion / contraction acceleration α, the expansion / contraction displacement x or the expansion / contraction acceleration α is damped by the damper D. It can be used as a material for the case of force hysteresis, and the original characteristic of the neural network model is discriminated, and the hysteresis characteristic can be linked to the expansion / contraction speed v. Originally, the material for the case of the hysteresis of the reaction force of the damper D is formed by the derivative or the time derivative of the reaction force of the damper D with respect to the expansion / contraction speed v. Needs to use a filter having a delay characteristic, and if a filter having a delay and a configuration is used in the control system, the performance of the controller C will be deteriorated. On the other hand, when two pieces of information, that is, the expansion / contraction speed v and the expansion / contraction displacement x of the damper D, or the expansion / contraction speed v and the expansion / contraction acceleration α are used, data that has good influence of noise and measurement accuracy is selected. It can be used, and the corrector 6 can efficiently obtain the correction value R. In this embodiment, since three pieces of information, that is, the expansion / contraction displacement x, the expansion / contraction speed v, and the expansion / contraction acceleration α are input to the corrector 6, in addition to shortening the time until the correction value R is obtained, A more accurate correction value R can be obtained.

加算器７は、目標指令Ｕ＊から補正器６で得た補正値Ｒを差し引いて補正指令Ｕを求め、補正指令Ｕを操作量としてアクチュエータＡに与える。このようにしてコントローラＣは、アクチュエータＡを制御するので、ダンパＤの反力を打ち消してダンパＤに対して目標指令通りに振動を負荷して良好な振動試験を行える。 The adder 7 subtracts the correction value R obtained by the corrector 6 from the target command U * to obtain the correction command U, and gives the correction command U as an operation amount to the actuator A. Since the controller C controls the actuator A in this manner, the reaction force of the damper D is canceled and vibration is applied to the damper D according to the target command, and a good vibration test can be performed.

以上のように、本実施の形態のダンパの振動試験装置１は、テレスコピック型のダンパＤに振動を与えるアクチュエータＡと、ダンパＤの伸縮変位ｘ、伸縮速度ｖおよび伸縮加速度αの三つの情報のうち９０度位相がずれた二つ情報を検知する検知器Ｓと、目標指令Ｕ＊を前記検知器Ｓで検知した情報の入力によってニューラルネットワークモデルを利用してダンパＤの反力を打ち消す補正値Ｒを求める補正器６を有し、補正器６で目標指令Ｕ＊を補正して得た補正指令ＵをアクチュエータＡへ与えてアクチュエータＡを制御するコントローラＣとを備えている。このように構成されたコントローラＣは、システムの非線形写像関係を部分的にニューラルネットワークに学習させることにより既存の伝達関数を用いた逆システムを利用した制御とニューラルネットワークによる補正値Ｒを推定する機械学習を組み合わせることによってアクチュエータＡを制御する。よって、コントローラＣは、アクチュエータＡを制御するにあたりダンパＤの非線形な反力を補正器６で学習してダンパＤの反力を打ち消す補正値Ｒを求め得るので、ダンパＤの振動が目標指令に精度良く一致し、良好な振動試験を行える。 As described above, the damper vibration test apparatus 1 according to the present embodiment includes the actuator A that vibrates the telescopic damper D, and the three types of information of the expansion / contraction displacement x, the expansion / contraction speed v, and the expansion / contraction acceleration α of the damper D. A detector S that detects two pieces of information that are 90 degrees out of phase with each other, and a correction value that cancels the reaction force of the damper D by using a neural network model by inputting the information that the target command U * is detected by the detector S. It has a compensator 6 for obtaining R, and a controller C for controlling the actuator A by giving a compensation command U obtained by compensating the target command U * by the compensator 6 to the actuator A. The controller C configured as described above is a machine for partially estimating the non-linear mapping relationship of the system by the neural network and performing control using the inverse system using the existing transfer function and estimating the correction value R by the neural network. Actuator A is controlled by combining learning. Therefore, the controller C can learn the non-linear reaction force of the damper D by the compensator 6 to control the actuator A, and obtain the correction value R that cancels the reaction force of the damper D, so that the vibration of the damper D becomes the target command. Accurate match and good vibration test can be performed.

また、本実施の形態のダンパの振動試験装置１では、検知器Ｓが伸縮変位ｘ、伸縮速度ｖおよび伸縮加速度αの三つの情報の全部を検知し、補正器６が伸縮変位ｘ、伸縮速度ｖおよび伸縮加速度αの三つの情報を利用して目標指令Ｕ＊を補正する補正値Ｒを得るので、ダンパＤの反力を精度よく打ち消す補正値Ｒを得ることができる。 Further, in the damper vibration test apparatus 1 of the present embodiment, the detector S detects all three pieces of information of the expansion / contraction displacement x, the expansion / contraction speed v, and the expansion / contraction acceleration α, and the corrector 6 detects the expansion / contraction displacement x, the expansion / contraction speed. Since the correction value R for correcting the target command U * is obtained using three pieces of information of v and the expansion / contraction acceleration α, the correction value R for canceling the reaction force of the damper D with high accuracy can be obtained.

以上で、本発明の実施の形態についての説明を終えるが、本発明の範囲は図示されまたは説明された詳細そのものには限定されない。   While this concludes the description of the embodiments of the present invention, the scope of the present invention is not limited to the details shown or described.

１・・・ダンパの振動試験装置、６・・・補正器、Ａ・・・アクチュエータ、Ｃ・・・コントローラ、Ｄ・・・ダンパ、Ｓ・・・検知器 1 ... Damper vibration test device, 6 ... Compensator, A ... Actuator, C ... Controller, D ... Damper, S ... Detector

Claims (2)

テレスコピック型のダンパに振動を与えるアクチュエータと、
前記ダンパの伸縮変位、伸縮速度および伸縮加速度の三つの情報のうち９０度位相がずれた二つ情報を検知する検知器と、
目標指令を前記検知器で検知した情報の入力によってニューラルネットワークモデルを利用して前記ダンパの反力を打ち消す補正値を求める補正器を有し、前記補正値で前記目標指令を補正して得た補正指令を前記アクチュエータへ与えて前記アクチュエータを制御するコントローラとを備えた
ダンパの振動試験装置。 An actuator that gives vibration to a telescopic damper,
A detector that detects two pieces of information that are 90 degrees out of phase among the three pieces of information of the expansion / contraction displacement, expansion / contraction speed, and expansion / contraction acceleration of the damper,
The target command is input by inputting the information detected by the detector, and has a corrector for obtaining a correction value for canceling the reaction force of the damper by using a neural network model. The target command is corrected by the correction value. A damper vibration test apparatus comprising: a controller that gives a correction command to the actuator to control the actuator. 前記検知器は、前記伸縮変位、前記伸縮速度および前記伸縮加速度の三つの情報の全部を検知し、
前記補正器は、前記伸縮変位、前記伸縮速度および前記伸縮加速度の三つの情報を利用して前記目標指令を補正する前記補正値を得る
ことを特徴とする請求項１に記載のダンパの振動試験装置。 The detector detects all three information of the expansion and contraction displacement, the expansion and contraction speed and the expansion and contraction acceleration,
The vibration test of the damper according to claim 1, wherein the corrector obtains the correction value for correcting the target command using three pieces of information of the expansion / contraction displacement, the expansion / contraction speed, and the expansion / contraction acceleration. apparatus.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112113755A (en) * 2020-09-02 2020-12-22 西安交通大学 Mechanical fault intelligent diagnosis method based on deep convolution-kurtosis neural network
CN117382909A (en) * 2023-12-07 2024-01-12 山西助我飞科技有限公司 Fatigue characteristic testing assembly for undercarriage

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS63163254A (en) * 1986-12-26 1988-07-06 Shimadzu Corp Control method for material testing machine

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS63163254A (en) * 1986-12-26 1988-07-06 Shimadzu Corp Control method for material testing machine

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112113755A (en) * 2020-09-02 2020-12-22 西安交通大学 Mechanical fault intelligent diagnosis method based on deep convolution-kurtosis neural network
CN117382909A (en) * 2023-12-07 2024-01-12 山西助我飞科技有限公司 Fatigue characteristic testing assembly for undercarriage
CN117382909B (en) * 2023-12-07 2024-02-09 山西助我飞科技有限公司 Fatigue characteristic testing assembly for undercarriage

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