JP7306926B2 - Vibration test equipment - Google Patents

Description

The present invention relates to vibration test equipment.

A vibration test apparatus includes, for example, a vibrator that vibrates a specimen and a controller that controls the vibrator. Generally, the controller detects the response of the vibration exciter with a sensor and performs control to feed back the detected response to control the vibration exciter. Since the hydraulic servo system to be applied has a phase delay in the response and has non-linear characteristics, it is difficult to apply vibration to the specimen according to the test conditions with simple feedback control.

Therefore, in such a vibration test apparatus, a random noise signal is given to the vibration exciter after the test piece is mounted, and the acceleration acting on the vibration exciter is detected by a sensor provided in the vibration exciter. Obtain the relationship between the signal to be given to and the sensor output as a transfer function matrix, and use the inverse matrix of this transfer function matrix to convert the acceleration data indicated by the test conditions into the excitation signal to be input to the shaker. is performed (see Patent Document 1, for example). In other words, in conventional vibration test equipment, the controller stores the inverse characteristic of the response of the shaker to the control signal as a gain table for frequency, and multiplies the target command by the gain obtained from the table to generate the control command. to control the shaker. In this way, conventional vibration test equipment generates control commands to eliminate waveform disturbances caused by response delays and non-linear characteristics of the shaker, controls the shaker, and vibrates the specimen according to the test conditions. is giving

JP 2013-167557 A

However, if the vibration test equipment vibrates the same product but different specimens, the characteristics of the entire system consisting of the vibration exciter and the specimen will change, and the table prepared in advance will not produce the optimum control command. may no longer be generated.

That is, in the vibration test apparatus described above, the inverse characteristic is obtained in advance from the response characteristic of the vibrator when the specimen is vibrated by the vibrator, and the control command is generated using this inverse characteristic. Therefore, if the characteristics of the specimen change, the response characteristics of the vibrator will also change, making it difficult to generate the optimum control command.

In addition, in conventional vibration test equipment, noise may remain in the table of the inverse characteristics of the vibration exciter. Noise is superimposed on the vibration given by the vibrator and distortion occurs due to the influence of .

As described above, the conventional vibration tester may not be able to generate the optimum control command, and there is a demand for a vibration tester that can apply vibrations to the specimen under the test conditions.

SUMMARY OF THE INVENTION Accordingly, it is an object of the present invention to provide a vibration testing apparatus capable of applying vibrations to a specimen under test conditions.

In order to achieve the above object, the damper vibration testing apparatus of the present invention comprises a vibrator that vibrates a test piece, and a controller that controls the vibrator based on a target command. A correction unit that corrects the target command based on the inverse characteristics of the response characteristics obtained by the identification unit to identify the response characteristics of the shaker to the target command using and a control unit for generating a control command based on the vibration exciter and controlling the vibration exciter. The vibration test apparatus configured in this way identifies the response characteristics of the vibrator by means of the identification unit using the neural network model, constantly optimizing the response characteristics referred to for correcting the target command, and You can control the oscillator. Therefore, according to the vibration test equipment, even if the product is the same but different specimens are vibrated, even if the characteristics of the entire system consisting of the vibrator and the specimen change, the optimum control commands can be generated. , the ideal vibration that matches the test conditions is applied to the specimen. In addition, the response characteristics referred to by the correction unit are optimized by identifying the response characteristics of the shaker using a neural network model, which prevents noise from remaining in the response characteristics. There is no fear that noise will be superimposed on the vibration given by the vessel or distortion will occur.

Further, the vibration test apparatus includes a detector that detects the response of the vibration exciter, and a feedback section that obtains an operation command based on the deviation between the response of the vibration exciter detected by the detector and the correction command. , has a reference model unit that simulates and outputs the response of the shaker to the input of the control command given to the shaker, and the response of the shaker detected by the detector and the excitation simulated by the reference model unit A control command is obtained based on the difference from the response of the device and the operation command. The vibration test apparatus configured in this manner simulates the response of the vibration exciter in the reference model section, corrects the operation command based on the difference between the response of the vibration exciter and the simulated response, and obtains the control command. , the control command can be modified so as to adjust the difference between the response of the actual vibrator and the response simulated by the reference model unit, and the response of the vibrator can follow the target command with higher accuracy.

Furthermore, the vibration test apparatus includes a vibration exciter response simulating section in which the reference model section simulates the response of the vibration exciter, and a specimen response simulation section in which the response simulated by the vibration exciter response simulating section is input to simulate the response of the specimen. and the vibrator response simulating part may simulate and output the response of the vibrator by inputting the control command and the response of the test object simulated by the test object response simulating part. In the vibration test apparatus configured as described above, the reference model section simulates the response of the vibrator and further simulates the response of the test piece that received the simulated response. The response can be obtained by simulating the system of Therefore, according to the vibration test apparatus configured in this way, it is possible to obtain a reference response of the vibration exciter in accordance with the actual system, and the vibration exciter accurately follows the control command for the test piece. will be able to give the vibration of

In the vibration test apparatus, the vibration exciter response simulating section obtains the response of the vibration exciter using the physical model of the vibration exciter based on the control command and the response of the specimen simulated by the specimen response simulating section. A vibration exciter physics model unit and a vibration exciter physics model unit that is connected in parallel to the vibration exciter physics model unit and uses a neural network model based on the control command and the response of the test object simulated by the test object response simulating unit. and a shaker nonlinear section for determining a nonlinear response of the shaker to be added to the response determined by. According to the vibration test apparatus configured in this way, since the response of the vibrator can be obtained by simulating the vibrator with high accuracy through learning, the vibrator can more accurately follow the control command for the test piece. will be able to give the vibration of

Furthermore, the vibration test equipment is parallel to the shaker physical model section and the shaker nonlinear section, and uses a neural network model to perform the vibration based on the control command and the response of the specimen simulated by the specimen response simulating section. and a shaker linear unit that obtains a linear response to be added to the response obtained by the shaker physics model unit. According to the vibration test apparatus configured in this manner, the response can be obtained by simulating the vibration exciter with high accuracy through learning, so that the vibration exciter gives the test piece vibration according to the control command with high precision. will be available. In addition, according to the vibration test apparatus configured as described above, by providing the vibration exciter linear section, it is possible to learn the component due to the response characteristics of the vibration exciter. It can shorten the learning time to get a matching simulated response.

In the vibration test apparatus, the test object physical model unit obtains the response of the test object by using the physical model of the test object based on the response of the vibrator simulated by the vibration exciter response simulating unit. and, based on the response of the vibrator simulated by the vibration exciter response simulating section in parallel with the physical model section of the specimen, add it to the response obtained by the physical model section of the specimen using the neural network model. and a nonlinear specimen section for obtaining a nonlinear response. According to the vibration test apparatus configured as described above, the response of the test object is learned and the response is obtained by simulating the test object with high accuracy. Since the response of the vibrator can be obtained by simulating the entire system of the specimen and the vibrator, the vibrator can give vibrations to the specimen with higher accuracy according to the control command. In addition, since it is equipped with a test object physical model part that obtains a response according to a known physical model and a test object nonlinear part that obtains a nonlinear response simulating the nonlinear noise and distortion components appearing in the response of an actual test object, According to the vibration tester, even if the product is the same but different specimens are tested, it is sufficient to learn the nonlinear part of the specimen to make fine adjustments. can shorten the learning time of

Further, the vibration test apparatus includes a cylinder, a piston movably inserted into the cylinder and partitioning the inside of the cylinder into an expansion-side chamber and a compression-side chamber, and a piston movably inserted into the cylinder and connected to the piston. and a servo valve for selectively supplying hydraulic oil discharged from the pump to the expansion-side chamber and the compression-side chamber, wherein the identification unit determines the frequency of the vibrator and the valve opening of the servo valve. A response characteristic of the shaker with respect to degrees may be identified. In this way, when the identification unit identifies the frequency of the target command and the response characteristics of the vibration exciter with respect to the valve opening of the servo valve, a more optimal correction command that takes into account the influence of the valve opening of the servo valve can be obtained in controlling the vibration exciter. can be obtained, the vibrator can be controlled with higher accuracy, and the specimen can give vibrations with higher accuracy according to the test conditions.

Also, the identification unit may identify the response characteristics of the vibrator with respect to the frequency of the target command, the degree of valve opening of the servo valve, and the temperature of the specimen. In this way, if the identification unit identifies the frequency of the target command, the valve opening of the servo valve, and the response characteristics of the vibrator to the temperature of the test piece, the control of the vibrator will be more optimal, taking into account the effect of the temperature of the test piece. It is possible to obtain a correct correction command, control the vibration exciter with higher accuracy, and apply vibrations according to the test conditions with higher accuracy using the test piece.

According to the vibration testing apparatus of the present invention, it is possible to apply vibrations to the specimen according to the test conditions.

It is a control block diagram of the controller of the vibration test apparatus in one embodiment. 1 is a specific configuration diagram of a vibration test apparatus according to an embodiment; FIG. 4 is a map showing the gain characteristics of the shaker response; 4 is a map showing the phase characteristics of the shaker response; It is the figure which showed the structure of the identification part. 4 is a map showing the inverse characteristics of the gain characteristics of the shaker response; It is a control block diagram of the controller of the vibration test apparatus in the first modified example of one embodiment. FIG. 11 is a control block diagram of a vibration exciter response simulating section of the vibration test apparatus in the first modified example of one embodiment; (a) is a diagram showing a displacement generated by a shaker physical model unit. (b) is a diagram showing a linear response generated by the shaker linear section. (c) is a diagram showing a nonlinear response generated by the shaker nonlinear section. (d) is a diagram showing a response simulated by the shaker response simulating unit. FIG. 11 is a control block diagram of a test object response simulating section of the vibration test apparatus in the first modified example of one embodiment; (a) is a diagram showing a displacement generated by a test piece physical model section. (b) is a diagram showing a nonlinear response generated by the nonlinear portion of the test piece. (c) is a diagram showing a response simulated by the test object response simulating section.

BEST MODE FOR CARRYING OUT THE INVENTION The present invention will be described below based on embodiments shown in the drawings. As shown in FIG. 1, a damper vibration testing apparatus 1 according to one embodiment includes a vibration exciter E that vibrates a telescopic damper D as a specimen, and a displacement X that is detected as a response of the vibration exciter E. and a controller C that generates a control command Uc based on the target command Uref and controls the vibration exciter E.

Each part of the vibration test apparatus 1 will be described in detail below. A damper D as a test piece is a telescopic type damper having a cylinder 8 and a rod 9 that moves in and out of the cylinder 8. demonstrate.

On the other hand, as shown in FIG. 2, the vibration exciter E includes a pedestal 10, a holding portion 11 provided on the pedestal 10 and movable in the horizontal direction in FIG. and is connected to the other end of the damper D to apply vibration to the damper D;

The actuator 13 includes a cylinder 13a, a piston 13b that is movably inserted into the cylinder 13a and partitions the inside of the cylinder 13a into an expansion side chamber R1 and a compression side chamber R2, and a piston 13b that is movably inserted into the cylinder 13a. It has a connected rod 13c and a servo valve 13d that selectively feeds pressurized oil supplied from the pump P into the growth side chamber R1 and the pressure side chamber R2.

Although not shown in detail, the servo valve 13d includes a hollow housing, a spool that is movably inserted into the housing, a solenoid that drives the spool, a spring that positions the spool at a neutral position, and a spring that positions the spool at a neutral position. and a drive circuit that receives an input and drives the solenoid. The solenoid can change the thrust applied to the spool according to the amount of current supplied from the drive circuit, and can adjust the position of the spool. Depending on the position of the spool, the servo valve 13d has a position that supplies pressure oil to the expansion side chamber, a position that supplies pressure oil to the compression side chamber, and a position that cuts off the supply of pressure oil to both. , and at the position where pressure oil is supplied to the expansion side chamber or the pressure side chamber, the valve opening degree is changed according to the amount of current supplied to the solenoid to adjust the flow rate.

In this embodiment, when the servo valve 13d receives a control command Uc as an input, it adjusts the thrust of the solenoid, adjusts the position of the spool with respect to the housing, and either the expansion side chamber or the compression side chamber is instructed by the input. The chamber is supplied with pressurized oil at the flow indicated by the input. The actuator 13 expands the chamber to which the pressurized oil is supplied from the servo valve 13d and contracts the chamber to which the pressurized oil is not supplied among the expansion-side chamber and the compression-side chamber, thereby performing expansion and contraction driving. In this way, the vibration exciter E, upon receiving an input from the controller C, causes the actuator 13 to expand and contract, vibrates one end of the damper D, and vibrates the damper D. As shown in FIG. The drive circuit has a current sensor that detects current flowing through the solenoid, feeds back the current detected by the current sensor, and supplies the current to the solenoid according to the control command Uc input from the controller C. The drive circuit may be included in the controller C instead of the servo valve 13d side.

The stroke sensor 2 as a detector detects the relative displacement X of the rod 13c with respect to the cylinder 13a of the actuator 13 as a response of the vibrator E and inputs it to the controller C in this embodiment. In the case of this embodiment, the displacement X is detected as the response of the vibration exciter E, so the detector is the stroke sensor 2. A suitable sensor may be used as the detector depending on the target.

The controller C, as shown in FIG. a correction unit 4 for obtaining a correction command Ua by correcting the target command Uref for the vibration exciter E; and a control unit 5 for controlling the vibration exciter E by generating a control command Uc based on the correction command Ua. there is The target command Uref is a command to repeatedly apply sinusoidal vibration of a predetermined frequency to the damper D, which is a test piece. to control.

In this embodiment, the identification unit 3 identifies in advance the response characteristics of the shaker E with respect to the target command Uref. In order to identify the response characteristics of the vibration exciter E, the identification unit 3 controls the stroke when the controller C gives the control command Uc to the vibration exciter E in response to the input of the sweep signal to vibrate the damper D, which is a test piece. Inputs of the displacement X detected by the sensor 2, the sweep signal given to the vibration exciter E by the controller C, and the valve opening degree of the servo valve 13d are applied to the vibration exciter E using a neural network model. The gain and phase of the displacement X, which is the response of the vibration exciter E to the frequency of the control command and the valve opening degree of the servo valve 13d, is obtained by multiplying the frequency and the valve opening degree. Identify as a characteristic.

Since the sweep signal is a command indicating the amplitude and frequency, the identification unit 3 can grasp the frequency for expanding and contracting the vibration exciter E indicated by the sweep signal. Further, since there is a one-to-one relationship between the amount of current supplied to the servo valve 13d and the degree of opening of the servo valve 13d, the valve opening degree of the servo valve 13d is obtained from the amount of current supplied to the servo valve 13d indicated by the sweep signal. Therefore, the identification unit 3 can grasp the valve opening degree of the servo valve 13d by inputting the sweep signal.

As shown in FIG. 3, when the frequency of the vibration instructed by the command input to the controller C increases, the response of the vibrator E tends to decrease, that is, the amplitude of the displacement X tends to decrease. That is, as the frequency becomes higher, the gain in the displacement X of the vibrator E becomes smaller. Further, as shown in FIG. 4, when the frequency of vibration instructed by the command input to the controller C increases, the response of the vibration exciter E tends to be delayed, that is, the displacement X tends to be delayed with respect to the command.

Furthermore, as shown in FIG. 3, when the valve opening degree of the servo valve 13d becomes smaller, the drop in the gain of the displacement X becomes smaller when the vibration frequency becomes higher. That is, when the valve opening degree of the servo valve 13d increases, the gain of the displacement X decreases even at the same frequency. Further, as shown in FIG. 4, when the valve opening indicated by the command input to the controller C increases, the response of the vibration exciter E tends to be delayed, that is, the displacement X tends to be delayed with respect to the command.

The identification unit 3 uses a neural network model to identify a weighting factor for obtaining the gain of the displacement X with the frequency and the valve opening as inputs, using the gain and phase characteristics of the response of the vibration exciter E as the response characteristics. .

Specifically, as shown in FIG. 5, the identification unit 3 uses the frequency and valve opening indicated by the sweep signal as information to be input to the input layer, and the output layer as the gain of the displacement X detected by the stroke sensor 2. , weighting coefficients W11, W12, . . . W1n, W21, W22, . W32, . Similarly, as shown in FIG. 5, the identification unit 3 uses the frequency and valve opening indicated by the sweep signal as information to be input to the input layer, and the phase of the displacement X detected by the stroke sensor 2 as the output layer. Weighting coefficients W11, W12, . . . W1n, W21, W22, . . . . Identify W3n so that the phase of the displacement X can be obtained with respect to the input of the frequency of the input layer and the degree of opening of the valve.

The weighting coefficients identified in this manner are coefficients for obtaining the gain and phase of the displacement X when the frequency of the vibration exciter E and the valve opening degree are input. It is a coefficient that characterizes response characteristics. The response characteristic of the vibration exciter E is the response characteristic of the entire system including the damper D characteristic. For learning by the identification unit 3, various learning rules other than Adam's learning rule can be used.

Then, when the inverse characteristics of the response characteristics of the vibration exciter E identified by the identification unit 3 are obtained, the controller C generates By correcting the target command Uref using the above-mentioned inverse characteristic, the displacement X, which is the response of the vibration exciter E, can be controlled according to the target command Uref.

Note that the damping characteristic of the damper D changes when the temperature of the hydraulic oil in the cylinder 8 changes. Specifically, when the temperature of the hydraulic oil in the damper D increases, the viscosity of the hydraulic oil decreases and the damping coefficient of the damper D decreases, so the damping force of the damper D decreases. When dealing with such a change in damping characteristic of the damper D, the temperature of the damper D is detected by a temperature sensor, and the temperature of the damper D detected by the temperature sensor is input to the identification unit 3 together with the frequency and valve opening. A weighting coefficient for obtaining gain and phase may be identified as the response characteristic of the shaker E. FIG. In the neural network model, even if the amount of information increases, the weighting coefficients can be optimized through learning, so the response characteristics of the shaker E required for control can be identified.

In addition, the identification unit 3 constantly receives the input of the target command Uref and the displacement X during the vibration test, identifies the response characteristics of the displacement X with respect to the frequency and the valve opening degree by learning, and continues to update the response characteristics. In this embodiment, in order to shorten the learning time, the controller C controls the vibration exciter E by inputting the sweep signal to vibrate the damper D, which is the test piece, and the identification unit 3 Identifies the response characteristics of E. However, even if the response characteristics are not identified in advance in the vibration test, the identification unit 3 can learn the response characteristics of the vibration exciter E as the vibration test based on the input of the target command Uref progresses, and can sequentially update and optimize the response characteristics. .

The correction unit 4 receives the input of the target command Uref, and based on the inverse characteristics of the response characteristics identified by the identification unit 3, corrects the target command Uerf to obtain the correction command Ua. Here, the gain and phase obtained by identifying the response characteristics of the identification unit 3 are z=r(cos θ+i·sin θ) when a point z on the complex plane is expressed using polar coordinates, where r is the gain and θ is the phase. can be shown as Since the gain r and the phase θ are identified for a certain frequency and valve opening, the correction unit 4 obtains the inverse characteristic, Fourier-transforms the point indicated by the target command, and maps it onto the complex plane. Correction is performed in the same complex plane using the inverse characteristic, and the point after correction is mapped onto the Euclidean plane by inverse Fourier transform to obtain the target command Ua after correction.

Note that the correction unit 4 prepares a map of the inverse characteristics of the response characteristics using the frequency and valve opening indicated by the target command Uref as parameters, performs gain compensation and phase compensation by map calculation, and performs target command The correction command Ua may be obtained by correcting Uref.

In this way, the inverse characteristic of the gain characteristic of the response of the vibration exciter E to the target command Uref becomes a three-dimensional map as shown in FIG. Since this map has the inverse characteristics of the response characteristics of the displacement X of the vibration exciter E with respect to both the frequency and the valve opening, as shown in FIG. The map is such that the gain is increased as the is increased. Although not shown, if the inverse characteristic of the phase characteristic is also shown as a map, it becomes a three-dimensional map.

However, when the three-dimensional map is used, the storage capacity of the controller C is compressed. Without a dimensional map, as described above, the target command is mapped in the complex plane by the Fourier transform, and based on the inverse characteristics corresponding to the vibration frequency indicated by the target command Uref and the valve opening degree of the servo valve 13d. The map of the lever is corrected, and the corrected map is subjected to inverse Fourier transform to obtain the correction command Ua.

In this embodiment, the correction unit 4 obtains the correction command Ua without using a map, which leads to a reduction in the storage capacity of the controller C. FIG. When the correction unit 4 corrects the target command Uerf based on the inverse characteristics in this way, the correction command Ua after correction causes the vibration exciter E to respond in accordance with the target command Uref based on the response characteristics of the vibration exciter E. It is a suitable directive for

Here, the target command Uref is a command for vibrating the vibration exciter E in a sine wave, and is a command for instructing displacement in which the actuator 13 expands and contracts in an ideal sine wave. When the target command Uref is input to the vibrator E, the gain and phase change depending on the frequency and valve opening due to the response characteristics of the vibrator E to which the characteristics of the damper D are added. deviates from the displacement indicated by . Therefore, if the correction unit 4 multiplies the target command Uref based on the inverse characteristics of the response characteristics of the vibration exciter E generated by the identification unit 3 to correct the displacement X of the vibration exciter E as indicated by the target command Uref. is obtained.

When the correction unit 4 corrects the target command Uref and obtains the correction command Ua in this manner, the correction unit 4 inputs the correction command Ua to the control unit 5 . The control unit 5 receives an input of the correction command Ua, generates a control command Uc based on the correction command Ua, and inputs the control command Uc to the vibrator E.

The control unit 5 is a PID compensator that obtains the deviation between the correction command Ua output by the correction unit 4 that corrects the target command Uref and the displacement X detected by the stroke sensor 2, performs PID compensation, and generates the control command Uc. The vibration exciter E is feedback-controlled. Although the controller 5 is a PID compensator in this embodiment, it may be a PI compensator or an H∞ controller.

The vibration test apparatus 1 configured in this way operates as follows. When a target command Uref is input to the controller C, the vibration exciter E gives vibration to the damper D, which is a test piece, and the stroke sensor 2 detects the displacement X of the vibration exciter E at a predetermined sampling period. input. The identification unit 3 learns the response characteristics of the vibration exciter E while the vibration exciter E is vibrating by inputting the target command Uref and the displacement X of the vibration exciter E, and identifies and sequentially updates the response characteristics. The correction unit 4 generates the correction command Ua by referring to the weighting coefficient as the response characteristic and correcting the target command Uref based on the inverse characteristic thereof, and the control unit 5 calculates the deviation between the correction command Ua and the displacement X by PID. A control command Uc is generated by compensation, and the control command Uc is given to the servo valve 13d of the vibration exciter E. The servo valve 13d to which the control command Uc is input adjusts the position of the spool as instructed by the control command Uc, and expands and contracts the actuator 13. As shown in FIG. The expansion and contraction of the actuator 13 is monitored by the stroke sensor 2, and the displacement X is constantly input to the controller C, and the identification of the response characteristics of the vibration exciter E in the identification unit 3 and the control of the vibration exciter E are performed in parallel. The response characteristic, which is performed and referred to for correcting the target command Uref, is continuously optimized.

As described above, the vibration test apparatus 1 of the present embodiment includes the vibrator E that vibrates the damper (specimen) D, and the controller C that controls the vibrator E based on the target command Uref. , the controller C uses a neural network model to identify the response characteristics of the vibration exciter E with respect to the target command Uref, and corrects the target command Uref based on the inverse characteristics of the response characteristics obtained by the identification unit 3. and a control unit 5 for controlling the vibration exciter E based on the correction command Ua. The vibration test apparatus 1 configured in this manner identifies the response characteristics of the vibration exciter E by the identification unit 3 using a neural network model, and continuously optimizes the response characteristics referred to for correcting the target command Uref. The vibration exciter E can be controlled while Therefore, according to the vibration test apparatus 1, even if the product is the same but a different damper (specimen) D is vibrated, the characteristics of the entire system consisting of the vibrator E and the damper (specimen) D do not change. Optimal control command Uc is generated even at the maximum, and ideal vibration that matches the test conditions is given to the damper (specimen) D. In addition, since the response characteristics referred to by the correction unit 4 are identified and optimized by the identification unit 3 using a neural network model, it is possible to prevent noise from remaining in the response characteristics. There is no fear that noise will be superimposed on the applied vibration or distortion will occur. As described above, according to the vibration test apparatus 1 of the present embodiment, vibration can be applied to the damper (test) D according to the test conditions.

In addition, since the identification unit 3 uses a neural network model, the response characteristics of the shaker E can be identified no matter how much information is input. to correct the target command Uref.

Furthermore, since the identification unit 3 identifies the response characteristics of the vibration exciter E using a neural network model, the response characteristics can be identified more easily than identification using state equations and transfer functions.

The identification unit 3 uses the neural network model to obtain the response characteristics of the shaker E instead of obtaining the control command directly using the neural network model. The controllability of the vibrator E can be improved by identifying response characteristics in which data values change continuously instead of using a continuous table.

Furthermore, in the vibration test apparatus 1 of the present embodiment, the vibrator E is a cylinder 13a, and a piston 13b that is movably inserted into the cylinder 13a and partitions the inside of the cylinder 13a into the expansion side chamber R1 and the compression side chamber R2. , a rod 13c that is movably inserted into the cylinder 13a and connected to the piston 13b, and a servo valve 13d that selectively supplies hydraulic oil discharged from the pump P to the expansion side chamber R1 and the compression side chamber R2. In the actuator 13, the identification unit 3 identifies the response characteristics of the vibration exciter E with respect to the frequency of the vibration exciter E and the valve opening degree of the servo valve 13d. In this way, when the identification unit 3 identifies the frequency of the target command Uref and the response characteristic of the vibration exciter E with respect to the opening degree of the servo valve 13d, the influence of the valve opening degree of the servo valve 13d is taken into account in controlling the vibration exciter E. Therefore, the optimum correction command Ua can be obtained, the vibration exciter E can be controlled with higher accuracy, and the damper (specimen) D can give vibrations according to the test conditions with higher accuracy.

Further, the identification unit 3 may identify the response characteristics of the vibrator E with respect to the frequency of the target command Uref, the degree of valve opening of the servo valve 13d, and the temperature of the damper (specimen) D. In this way, when the identification unit 3 identifies the response characteristics of the vibration exciter E with respect to the frequency of the target command Uref, the valve opening degree of the servo valve 13d, and the temperature of the damper (specimen) D, in controlling the vibration exciter E, the damper ( It is possible to obtain a more optimal correction command Ua that takes into account the influence of the temperature of the test piece D, and to control the vibration exciter E with higher accuracy. Given.

Next, the controller 5 may be configured as shown in FIG. The control unit 5 of the vibration test apparatus 1a in the first modification of the embodiment obtains the deviation between the correction command Ua output by the correction unit 4 that corrects the target command Uref and the displacement X detected by the stroke sensor 2. A PID compensator 5a as a feedback unit that performs PID compensation and generates an operation command Ub, and a displacement Xs that is a response of the vibration exciter E to the input of the control command Uc that is given to the vibration exciter E is simulated and output. The reference model unit 5b, the adder 5c for obtaining the difference ΔX between the displacement X of the vibration exciter E detected by the stroke sensor 2 and the displacement Xs simulated by the reference model unit 5b, and the difference ΔX and the operation command Ub are added. and an adder 5d for obtaining the control command Uc.

The PID compensator 5a obtains the deviation between the correction command Ua output by the correction unit 4 that corrects the target command Uref and the displacement X detected by the stroke sensor 2, performs PID compensation, and generates the operation command Ub. It is said that Although the PID compensator 5a is a PID compensator in this embodiment, it may be a PI compensator or an H∞ controller.

As shown in FIG. 7, the reference model unit 5b includes a vibration exciter response simulating unit 5b1 that simulates the displacement Xs of the vibration exciter E, and the displacement Xs that is simulated by the vibration exciter response simulating unit 5b1. A specimen response simulating section 5b2 that simulates the load Fd as a response is provided. The vibration exciter response simulating section 5b1 simulates and outputs the displacement Xs of the vibration exciter E based on the input of the control command Uc and the load Fd of the damper D simulated by the specimen response simulating section 5b2.

Specifically, as shown in FIG. 8, the shaker response simulating unit 5b1 includes a shaker physical model unit 5b11, a shaker linear unit 5b12 parallel to the shaker physical model unit 5b11, and a vibration exciter. Shaker physics model unit 5b11 and shaker linear unit 5b12 are connected in parallel with shaker nonlinear unit 5b13, shaker physics model unit 5b11, shaker linear unit 5b12, and shaker nonlinear unit 5b13. and an adder 5b14 for adding .

The vibration exciter physical model unit 5b11 calculates the displacement X1 Ask for The physical model of the vibration exciter E expresses the system of the vibration exciter E. When the displacement indicated by the control command Uc and the load received from the damper D are input to the physical model as parameters, the displacement X1 as a response is obtained. It is what you get. The physical model can be arbitrarily designed, and design values may be used for parameter coefficients, etc., or a solution to an optimization problem based on machine learning may be input. Since the displacement X1 obtained by the shaker physical model unit 5b11 is the response of the physical model, if noise is not superimposed on the control command Uc and the load Fd, as shown in FIG. will have a sinusoidal waveform that does not contain

The vibration exciter linear section 5b12 is arranged in parallel with the vibration exciter physical model section 5b11 and the vibration exciter non-linear section 5b13, and uses a neural network model to generate the control command Uc and the damper D simulated by the specimen response simulating section 5b2. A linear response X2 is obtained based on the load Fd of . The linear response X2 is a value that is added to the displacement X1 obtained by the shaker physical model unit 5b11 to correct the phase and amplitude of the displacement X1 of the shaker physical model unit 5b11. The vibration exciter linear unit 5b12 uses a neural network model to identify weighting coefficients for obtaining the displacement X of the vibration exciter E from the inputs of the frequency, valve opening degree, and load Fd indicated by the control command Uc, and A linear response X2 is obtained from the input of the control command Uc and the load Fd using the identified weighting factor. Specifically, the vibration exciter linear section 5b12 inputs the frequency, the valve opening degree, and the load Fd of the damper D to the input layer, which are indicated by the control command Uc, and multiplies each piece of information by a weighting factor to weight it. Obtain the linear response X2 of the output layer. In this way, the vibration exciter linear unit 5b12 determines the response characteristics of the vibration exciter E by identifying the weighting coefficients for obtaining the intermediate layers from the input layers and the weighting coefficients for obtaining the output layers from the intermediate layers through learning. identify. The linear response X2 thus obtained is a signal for correcting the deviation between the displacement X1 and the displacement X caused by the response characteristics of the actual vibration exciter E, as shown in FIG. 9(b). In addition to Adam's learning rule, various learning rules can be used for learning by the vibrator linear unit 5b12.

The vibration exciter nonlinear section 5b13 is connected in parallel to the vibration exciter physical model section 5b11 and the vibration exciter linear section 5b12, and the neural network model is used to simulate the control command Uc and the test object response simulating section 5b2. Based on the load Fd of the damper D, the nonlinear response X3 of the vibrator E is obtained.

The vibration exciter nonlinear section 5b13 uses a neural network model to obtain a high-frequency nonlinear response X3 such as noise and distortion superimposed on the displacement X of the vibration exciter E from the input of the control command Uc and the load Fd. The vibration exciter nonlinear section 5b13 inputs the frequency, the valve opening degree, and the load Fd of the damper D to the input layer, which are indicated by the control command Uc, and multiplies each piece of information by a weighting coefficient to obtain the nonlinearity of the output layer. Get response X3. That is, the shaker nonlinear unit 5b13 obtains the nonlinear response X3 of the shaker E by identifying the weighting coefficient for obtaining the intermediate layer from the input layer and the weighting coefficient for obtaining the output layer from the intermediate layer through learning. . The non-linear response X3 obtained in this manner simulates the non-linear noise and distortion components appearing in the actual displacement X of the vibration exciter E that are not caused by the response characteristics of the vibration exciter E, as shown in FIG. 9(c). signal. In addition to Adam's learning rule, various learning rules can be used for learning by the vibrator nonlinear unit 5b13.

As shown in FIG. 9(d), the adder 5b14 combines the displacement X1 obtained by the shaker physical model unit 5b11, the linear response X2 obtained by the shaker linear unit 5b12, and the shaker nonlinear unit 5b13 by A displacement Xs simulating the response of the vibration exciter E is obtained by adding the obtained nonlinear response X3.

The shaker response simulating unit 5b1 obtains the displacement X1 according to a known physical model in the shaker physics model unit 5b11, and parallelizes the linear response X2 caused by the response characteristics of the shaker E to the shaker physics model unit 5b11. The nonlinear response X3 that simulates nonlinear noise and distortion components appearing in the actual displacement X of the shaker E that is not caused by the response characteristics of the shaker E is obtained by the shaker physics unit 5b12. Calculated by the shaker nonlinear unit 5b13 parallel to the model unit 5b11 and the shaker linear unit 5b12, and adding the respective outputs of the shaker physical model unit 5b11, the shaker linear unit 5b12, and the shaker nonlinear unit 5b13 to obtain the displacement Xs. Therefore, the vibration exciter response simulating section 5b1 can learn the displacement X of the vibration exciter E including the characteristics of the damper D, accurately simulate the vibration exciter E, and obtain the displacement Xs.

The vibration exciter linear part 5b12 is omitted, the components of the response characteristics of the vibration exciter E are also simulated by the learning of the vibration exciter non-linear part 5b13, and the vibration exciter response simulation part 5b1 is replaced by the vibration exciter physical model part. 5b11, a vibrator nonlinear section 5b13 parallel to the vibrator physical model section 5b11, and an adder 5b14 that adds the displacement X1 and the nonlinear response X3. However, by providing the vibration exciter linear portion 5b12, it is possible to learn the component due to the response characteristics of the vibration exciter E. Therefore, the learning time until the displacement Xs that matches the actual displacement X of the vibration exciter E with high accuracy is obtained. can be shortened.

The displacement Xs thus simulated by the vibration exciter response simulating section 5b1 is input to the specimen response simulating section 5b2. Specifically, as shown in FIG. 10, the specimen response simulating section 5b2 includes a specimen physical model section 5b21 that obtains the load F1 as the response of the damper D, and a specimen nonlinear section 5b22 that obtains the nonlinear response F2 of the damper D. and an adder 5b23 for adding the respective outputs of the specimen physical model section 5b21 and the specimen nonlinear section 5b22.

The specimen physical model unit 5b21 obtains the load F1 of the damper D using the physical model of the damper D based on the displacement Xs simulated by the vibration exciter response simulation unit 5b1. A physical model of the damper D is a Maxwell model, a Kelvin Voigt model, a standard linear solid model, or the like, and the load F1 as a response can be obtained by inputting the displacement Xs into the physical model as a parameter. . The physical model can be arbitrarily designed, and design values may be used for parameter coefficients, etc., or a solution to an optimization problem based on machine learning may be input. Since the load F1 obtained by the specimen physical model unit 5b21 is the response of the physical model, if noise is not superimposed on the control command Uc or the load Fd, as shown in FIG. It has a sinusoidal waveform that does not

The specimen nonlinear section 5b22 obtains a high-frequency nonlinear response F2 such as noise and strain superimposed on the load of the damper D from the displacement Xs simulated by the vibration exciter response simulating section 5b1 using a neural network model. The test piece nonlinear part 5b22 inputs the displacement Xs to the input layer, uses the load F of the damper D detected by the load cell 15 provided in the vibration exciter E as the output layer, and performs weighting until the load F is obtained from the displacement Xs. Learn and identify coefficients. In other words, the specimen nonlinear section 5b22 identifies, through learning, a weighting coefficient for obtaining the intermediate layer from the input layer and a weighting coefficient for obtaining the output layer from the intermediate layer. Then, the specimen nonlinear section 5b22 obtains the nonlinear response F2 of the damper D from the displacement Xs simulated by the vibration exciter response simulating section 5b1 using the identified weighting coefficient. The nonlinear response F2 thus obtained is a signal that simulates nonlinear noise and distortion components appearing in the actual load Fd of the damper D due to the effects of hysteresis and friction of the damper D, as shown in FIG. becomes. In addition to Adam's learning rule, various learning rules can be used for learning by the test piece nonlinear part 5b22.

As shown in FIG. 11(c), the adder 5b23 adds the load F1 obtained by the specimen physical model section 5b21 and the nonlinear response F2 obtained by the specimen nonlinear section 5b22 to simulate the response of the damper D. Calculate the applied load Fd.

The test object response simulating unit 5b2 finds a load F1 according to a known physical model in the test object physical model unit 5b21, and generates a nonlinear response F2 that simulates the nonlinear noise and distortion components appearing in the actual load of the damper D through the test object physics. The load Fd is obtained by adding the outputs of the specimen physical model section 5b21 and the specimen nonlinear section 5b22, which are obtained by the specimen nonlinear section 5b22 arranged in parallel with the model section 5b21. Therefore, the specimen response simulating section 5b2 can learn the load of the damper D, accurately simulate the damper D, and obtain the load Fd. The load Fd thus simulated by the test object response simulating section 5b2 is input to the vibration exciter response simulating section 5b1 and used to generate the displacement Xs of the vibration exciter response simulating section 5b1.

Then, the reference model unit 5b simulates the displacement Xs from the control command Uc sequentially input during the test of the damper D by the vibration test apparatus 1, and inputs it to the adder 5c. The adder 5c receives input of the displacement X detected by the stroke sensor 2 in addition to the displacement Xs, and obtains the difference ΔX between the displacement X and the displacement Xs. The difference ΔX obtained by the adder 5c is input to the adder 5d together with the operation command Ub, and the adder 5d adds the difference ΔX and the operation command Ub to obtain the control command Uc. The control command Uc obtained by the adder 5d is input to both the vibration exciter E and the reference model section 5b.

The vibration test apparatus 1a configured in this way operates as follows. When a target command Uref is input to the controller C, the vibration exciter E gives vibration to the damper D, which is a test piece, and the stroke sensor 2 detects the displacement X of the vibration exciter E at a predetermined sampling period. is entered. The identification unit 3 learns, identifies, and sequentially updates the response characteristics of the vibration exciter E while the vibration exciter E is vibrating by inputting the target command Uref and the displacement X of the vibration exciter E. FIG. Correction unit 4 corrects target command Uref based on the inverse characteristic of the response characteristic to generate correction command Ua. The control unit 5 obtains the operation command Ub by PID compensation of the correction command Ua, and further corrects the operation command Ub by the difference ΔX between the displacement Xs simulated by the reference model unit 5b and the displacement X detected by the stroke sensor 2. to find the control command Uc, and give the control command Uc to the servo valve 13d of the vibration exciter E. When the control command Uc is obtained, the control unit 5 inputs it to the reference model unit 5b, sequentially learns the response characteristics and nonlinear response of the vibration exciter E, and the characteristics of the damper D, and simulates the displacement of the vibration exciter E. Find the displacement Xs. The servo valve 13d to which the control command Uc is input adjusts the position of the spool as instructed by the control command Uc, and expands and contracts the actuator 13. As shown in FIG. The expansion and contraction of the actuator 13 is monitored by the stroke sensor 2, and the displacement X is constantly input to the controller C, and the identification of the response characteristics of the vibration exciter E in the identification unit 3 and the control of the vibration exciter E are performed in parallel. The response characteristic, which is performed and referred to for correcting the target command Uref, is continuously optimized. Further, the control unit 5 learns the characteristics of the vibration exciter E and the damper D, which is a test piece, in the reference model unit 5b, obtains the displacement Xs simulating the displacement of the vibration exciter E, and simulates the displacement X. Since the control command Uc is obtained by correcting the operation command Ub with the difference ΔX from the displacement Xs, the control command Uc is adjusted so as to adjust the difference between the actual displacement X of the vibration exciter E and the displacement Xs of the reference model section 5b. Since it is corrected, the displacement X of the vibration exciter E can be made to follow the target command Uref with higher accuracy.

As described above, the vibration test apparatus 1a of the present embodiment includes a vibrator E that vibrates a damper (specimen) D, and a controller C that controls the vibrator E based on a target command Uref. C uses a neural network model to identify the response characteristics of the shaker E with respect to the target command Uref, and corrects and corrects the target command Uref based on the inverse characteristics of the response characteristics obtained by the identification unit 3. A correction unit 4 that obtains a command Ua, a control unit 5 that generates a target command Uref based on the correction command Ua and controls the vibration exciter E, and a stroke sensor (detector) 2 that detects the response of the vibration exciter E. A PID compensator (feedback unit) for obtaining an operation command Ub based on the deviation between the displacement (response) X of the vibration exciter E detected by the stroke sensor (detector) 2 by the control unit 5 and the correction command Ua 5a and a reference model unit 5b that simulates and outputs the displacement (response) Xs of the vibration exciter E in response to the input of the control command Uc given to the vibration exciter E, and is detected by the stroke sensor (detector) 2. The control command Uc is obtained based on the difference between the displacement (response) X of the vibration exciter E and the displacement (response) Xs simulated by the reference model unit 5b and the operation command Ub.

The vibration test apparatus 1a configured in this way identifies the response characteristics of the vibration exciter E by the identification unit 3 using a neural network model, and continuously optimizes the response characteristics referred to for correcting the target command Uref. The vibration exciter E can be controlled while Therefore, according to the vibration test apparatus 1a, even if vibration is applied to a different damper (specimen) D of the same product, the characteristics of the entire system consisting of the vibrator E and the damper (specimen) D do not change. Optimal control command Uc is generated even at the maximum, and ideal vibration that matches the test conditions is given to the damper (specimen) D. Further, the response characteristics referred to by the correction unit 4 are identified and optimized by the identification unit 3 using a neural network model, and noise remaining in the response characteristics can be prevented. There is no fear that noise will be superimposed or distortion will occur. As described above, according to the vibration test apparatus 1 of the present embodiment, vibration can be applied to the damper (test) D according to the test conditions.

Further, the vibration test apparatus 1a configured as described above simulates the displacement (response) Xs of the vibration exciter E in the reference model section 5b, and compares the displacement (response) X and the simulated displacement (response) Xs. Since the control command Uc is obtained by correcting the operation command Ub with the difference ΔX, the control command Uc is corrected so as to adjust the difference between the actual displacement X of the vibration exciter E and the displacement (response) Xs of the reference model section 5b. The displacement (response) X of the vibration exciter E can be made to follow the target command Uref with higher accuracy. In the reference model unit 5b, it is also possible to simulate and output the displacement Xs of the vibration exciter E using a transfer function, a state equation, or a table or map prepared in advance without using a neural network model. . However, when the vibration test apparatus 1a obtains the displacement Xs by learning using a neural network model in the reference model unit 5b, the displacement (response) Xs that matches the displacement (response) X of the vibration exciter E is obtained with higher accuracy. Therefore, the displacement X of the vibration exciter E can more effectively follow the target command Uref.

Further, in the vibration test apparatus 1a of the present embodiment, the reference model unit 5b simulates the displacement (response) Xs of the vibration exciter E, and the vibration exciter response simulation unit 5b1 simulates the displacement (response) Xs of the vibration exciter E. and a test object response simulating unit 5b2 that simulates the load (response) Fd of the damper (test object) D by inputting the displacement (response) Xs. The displacement (response) Xs of the vibration exciter E may be simulated and output by inputting the load (response) Fd of the damper (specimen) D simulated by the section 5b2. In the vibration test apparatus 1a configured as described above, the reference model unit 5b simulates the displacement (response) Xs of the vibration exciter E, and the damper (specimen ) Since the load (response) Fd of D is simulated, the displacement (response) Xs can be obtained by simulating the actual system of the vibration exciter E and the damper (specimen) D. Therefore, according to the vibration test apparatus 1a of the present embodiment, it is possible to obtain the displacement (response) Xs of the vibration exciter E as a reference in conformity with the actual system, and the vibration exciter E is a damper (specimen ) D can be accurately given a vibration according to the target command Uref.

Further, in the vibration testing apparatus 1a of the present embodiment, the vibrator response simulating unit 5b1 based on the control command Uc and the load (response) Fd of the damper (test object) D simulated by the test object response simulating unit 5b2 A vibration exciter physical model unit 5b11 that obtains the displacement (response) X1 of the vibration exciter E by using the physical model of the vibration exciter E, and a control command Uc and the specimen response that are paralleled to the vibration exciter physical model unit 5b11. A vibration exciter added to the displacement (response) X1 obtained by the vibration exciter physical model unit 5b11 using a neural network model based on the load (response) Fd of the damper (specimen) D simulated by the simulation unit 5b2 and a shaker nonlinear section 5b13 that obtains the nonlinear response X3 of E. As described above, in the vibration test apparatus 1a, the vibration exciter response simulating section 5b1 obtains the displacement (response) X1 according to a known physical model in the vibration exciter physical model section 5b11, and the actual The nonlinear response X3 that simulates the nonlinear noise and distortion components appearing in the displacement (response) X of the vibration exciter E is obtained by the vibration exciter nonlinear section 5b13 parallel to the vibration exciter physical model section 5b11. By learning the displacement (response) X of the vibration exciter E including its characteristics, the displacement (response) Xs can be obtained by simulating the vibration exciter E with high accuracy. Therefore, according to the vibration test apparatus 1a configured as described above, since the displacement (response) Xs can be obtained by accurately simulating the vibration exciter E through learning, the vibration exciter E is the damper (specimen) D can be given vibration according to the target command Uref with higher accuracy.

Furthermore, the vibration test apparatus 1a of the present embodiment is connected in parallel to the shaker physical model section 5b11 and the shaker nonlinear section 5b13, and uses the neural network model to generate the control command Uc and the test object response simulation section 5b2. and a linear response X2 added to the displacement (response) X1 obtained by the physical model unit 5b11 based on the load (response) Fd of the simulated damper (specimen) D. may be As described above, in the vibration test apparatus 1a, the vibration exciter response simulating section 5b1 obtains the displacement (response) X1 according to a known physical model in the vibration exciter physical model section 5b11, and the linear response resulting from the response characteristics of the vibration exciter E is obtained. X2 is obtained by the vibration exciter linear section 5b12 parallel to the vibration exciter physical model section 5b11, and non-linear noise and Since the nonlinear response X3 simulating the distortion component is obtained by the shaker nonlinear unit 5b13 parallel to the shaker physics model unit 5b11, the displacement X of the shaker E including the characteristics of the damper D is learned to obtain accuracy. The displacement (response) Xs can be obtained by often simulating the vibrator E. Therefore, according to the vibration test apparatus 1a configured as described above, since the displacement (response) Xs can be obtained by accurately simulating the vibration exciter E through learning, the vibration exciter E is the damper (specimen) D can be given vibration according to the target command Uref with higher accuracy. Further, according to the vibration test apparatus 1a configured as described above, by providing the vibration exciter linear portion 5b12, it is possible to learn the component due to the response characteristics of the vibration exciter E, so that the actual displacement of the vibration exciter E The learning time required to obtain simulated displacement (response) Xs that matches (response) X with high accuracy can be shortened.

Furthermore, in the vibration test apparatus 1a of the present embodiment, the test object response simulating unit 5b2 performs the damper (test object) D based on the displacement (response) Xs of the vibration exciter E simulated by the vibration exciter response simulating unit 5b1. A test object physical model unit 5b21 that obtains the load (response) F1 of the damper (test object) D using the physical model of the test object physical model unit 5b21. Specimen to obtain the nonlinear response F2 of the damper (specimen) D to be added to the load (response) F2 obtained by the specimen physics model section 5b21 using a neural network model based on the displacement (response) Xs of the shaker E. A nonlinear section 5b22 may be provided. In this way, the vibration test apparatus 1a obtains the load (response) F1 according to a known physical model in the specimen physical model section 5b21, and simulates the nonlinear noise and distortion components that appear in the actual load of the damper D. F2 is obtained by the test piece nonlinear section 5b22 parallel to the test piece physics model section 5b21, and each output of the test piece physics model section 5b21 and the test piece nonlinear section 5b22 is added to obtain the load (response) Fd. , the load (response) Fd can be obtained by simulating the damper D with high accuracy. Therefore, according to the vibration test apparatus 1a configured as described above, the load (response) Fd is obtained by learning the load of the damper (specimen) D and simulating the damper (specimen) D with high accuracy. Even if a completely different specimen is tested, the displacement (response) Xs of the shaker E can be obtained by precisely simulating the entire system of the specimen and the shaker E. Vibration according to the target command Uref can be given to the specimen with higher accuracy. In addition, a test object physical model section 5b21 that obtains a load (response) F1 according to a known physical model, and a test object that obtains a nonlinear response F2 that simulates nonlinear noise and distortion components appearing in the actual load (response) of the damper D. According to the vibration testing apparatus 1a configured as described above, even when testing dampers (specimen) D of the same product but different from each other, the nonlinear section 5b22 of the specimen is provided. Since it is sufficient for 5b22 to learn for fine adjustment, the learning time for obtaining the load (response) Fd of the damper (specimen) D can be shortened.

In the description of the vibration testing apparatus 1, 1a of the present embodiment, the test piece is the damper D, but the test pieces other than the damper D can also be tested. In that case, the design may be changed so that the response of the test piece can be simulated by the test piece response simulating section 5b2 in the reference model section 5b.

Although preferred embodiments of the invention have been described in detail above, modifications, variations, and changes are possible without departing from the scope of the claims.

1, 1a... Vibration test device, 2... Stroke sensor (detector), 3... Identification unit, 4... Correction unit, 5... Control unit, 5a... PID compensator ( feedback part), 5b... reference model part, 5b1... shaker response simulation part, 5b11... shaker physical model part, 5b12... shaker linear part, 5b13... excitation Device nonlinear part 5b2 Test object response simulating part 5b21 Test object physical model part 5b22 Test object nonlinear part 13 Actuator 13a Cylinder 13b Piston , 13c...rod, 13d...servo valve, C...controller, D...damper (specimen), E...vibrator, P...pump, R1...extension side chamber , R2... compression side chamber

Claims (7)

a vibrator for vibrating the specimen;
a detector that detects the response of the shaker;
a controller that controls the vibrator based on a target command;
The controller is
an identification unit that uses a neural network model to identify response characteristics of the shaker with respect to the target command;
a correction unit for obtaining a correction command by correcting the target command based on the inverse characteristic of the response characteristic obtained by the identification unit;
a control unit that generates a control command based on the correction command and controls the vibrator ;
The control unit
a feedback unit that obtains an operation command based on a deviation between the response of the vibration exciter detected by the detector and the correction command;
a reference model unit that simulates and outputs a response of the vibration exciter to the input of the control command given to the vibration exciter;
The control command is obtained based on the operation command and the difference between the response of the vibration exciter detected by the detector and the response simulated by the reference model unit.
A vibration test apparatus characterized by: The normative model unit includes:
a vibration exciter response simulating unit that simulates the response of the vibration exciter;
a test object response simulating unit that simulates the response of the test object by inputting the response of the vibrator simulated by the vibrator response simulating unit;
The vibration exciter response simulating section simulates and outputs the response of the vibration exciter based on the input of the control command and the response of the test piece simulated by the test piece response simulating section. 1. The vibration test apparatus according to 1 . The vibrator response simulating unit includes:
a vibration exciter physical model unit that obtains the response of the vibration exciter using the physical model of the vibration exciter based on the control command and the response of the test object simulated by the test object response simulating unit;
parallel to the shaker physics model unit, and using a neural network model based on the control command and the test object response simulated by the test object response simulating unit, the shaker physics model unit 3. The vibration test apparatus according to claim 2 , further comprising a vibrator nonlinear section for obtaining the nonlinear response of the vibrator to be added to the obtained response. In parallel with the shaker physical model section and the shaker nonlinear section, a control command given to the shaker using a neural network model and the control command and the test object response simulating section simulated 4. The vibration according to claim 3 , further comprising a vibration exciter linear section for obtaining a linear response of the vibration exciter to be added to the response obtained by the vibration exciter physical model section based on the response of the specimen. test equipment. The specimen response simulating section,
a test object physical model unit that obtains the response of the test object using the physical model of the test object based on the response of the vibrator simulated by the shaker response simulating unit;
parallel to the test object physical model unit, using a neural network model based on the response of the shaker simulated by the shaker response simulating unit, and adding to the response obtained by the test object physical model unit The vibration test apparatus according to any one of claims 2 to 4 , further comprising a test piece nonlinear section that obtains a nonlinear response of the test piece to be measured. The vibrator includes a cylinder, a piston movably inserted in the cylinder and partitioning the inside of the cylinder into an expansion side chamber and a compression side chamber, and a movably inserted in the cylinder and connected to the piston. and a servo valve that selectively supplies hydraulic oil discharged from a pump to the expansion side chamber and the compression side chamber,
The vibration test according to any one of claims 1 to 5 , wherein the identification unit identifies the response characteristic of the vibrator with respect to the frequency of the target command and the degree of valve opening of the servo valve. Device. 7. The vibration test apparatus according to claim 6 , wherein the identification unit identifies the response characteristic of the vibrator with respect to the frequency of the target command, the degree of opening of the servo valve, and the temperature of the test piece.

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