Vibration simulation apparatus and vibration simulation method

Abstract

To provide a vibration simulation apparatus capable of highly accurate vibration prediction of a rotary machine.SOLUTION: A vibration simulation apparatus includes: a measurement data acquisition unit that acquires vibration waveform data of a rotating shaft of a rotary machine 30; a feature extraction unit that calculates a rotation-synchronous vibration component from the vibration waveform data acquired by the measurement data acquisition unit; a characteristic parameter input unit that inputs characteristic parameters of respective parts of the rotary machine; a vibration prediction data creation unit that creates an analysis model in accordance with the characteristic parameters input to the characteristic parameter input unit; a vibration prediction unit that analyzes vibration of the analysis model created by the vibration prediction data creation unit by physical simulation and calculates a vibration prediction value; a parameter identification unit that compares a vibration measurement value of the rotary machine with the vibration prediction value calculated by the vibration prediction unit and estimates the characteristic parameters; and an output unit that outputs a result of characteristic parameter identification and the vibration prediction value calculated by the vibration prediction unit. All or part of the characteristic parameters are associated with predetermined indices.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a configuration of a vibration simulation device and a method for predicting vibration characteristics, and in particular to a technique that is effective when applied to predicting vibrations of rotating machines such as induction motors. [Background technology]

[0002] Unbalance is the main cause of vibration in rotating machinery such as induction motors. In order to predict excessive vibration due to this unbalance, vibration evaluation is performed through analysis at the design stage, but because unbalance is an unknown parameter, there can be discrepancies between the vibration measurements and the calculation results obtained through simulation using an analytical model.

[0003] Furthermore, in bearings that support rotary machinery, for example, depending on how the rotor is seated, there is a possibility that a discrepancy may occur between the vibration measurements and the characteristics obtained by analysis.

[0004] Therefore, there is a data identification method that uses actual vibration measurements to estimate and identify parameters such as imbalance and bearing characteristics of the analysis model, thereby improving the accuracy of the analysis model.

[0005] Background art in this technical field includes, for example, the technology described in Patent Document 1. Patent Document 1 discloses a method for accurately predicting the characteristics of a rotating machine using actual vibration measurements.

[0006] Patent Document 1 describes a method for predicting vibration eigenvalues ​​as including "a parameter estimation unit that estimates model parameters from the motor rotation speed and torque command, and a vibration determination unit that determines whether vibration occurs in the model." [Prior art documents] [Patent documents]

[0007] [Patent Document 1] International Publication No. 2019 / 239791 Summary of the Invention [Problem to be solved by the invention]

[0008] In rotating machines such as induction motors that are supported by plain bearings, multiple parameters (generally eight parameters) interact with each other and appear as the bearing characteristics (vibration characteristics) of the rotating machine.

[0009] Therefore, unless parameter estimation is performed while maintaining the relationships between multiple parameters, it is not possible to obtain a physically valid analytical model of bearing characteristics, which results in a problem of reduced analytical accuracy.

[0010] In the above-mentioned Patent Document 1, the interaction of a plurality of parameters is not taken into consideration, and there is room for improvement in predicting vibration characteristics, which are an index of the reliability of rotating machinery.

[0011] SUMMARY OF THE INVENTION It is therefore an object of the present invention to provide a vibration simulation device and a vibration simulation method that are capable of predicting vibrations of a rotating machine with high accuracy. [Means for solving the problem]

[0012] In order to solve the above problems, the present invention provides a rotary machine having a rotational speed controller, comprising: a measurement data acquisition unit that acquires vibration waveform data of a rotating shaft of a rotary machine; a feature extraction unit that calculates rotation-synchronous vibration components from the vibration waveform data acquired by the measurement data acquisition unit; a characteristic parameter input unit that inputs characteristic parameters of each unit of the rotary machine; a vibration prediction data creation unit that creates an analytical model in accordance with the characteristic parameters input to the characteristic parameter input unit; a vibration prediction unit that analyzes vibrations based on the analytical model created by the vibration prediction data creation unit by physical simulation and calculates a vibration prediction value; a parameter identification unit that compares vibration measurement values ​​of the rotary machine with the vibration prediction value calculated by the vibration prediction unit and estimates characteristic parameters; and an output unit that outputs the characteristic parameter identification results of the parameter identification unit and the vibration prediction value calculated by the vibration prediction unit, wherein all or some of the characteristic parameters are associated with predetermined indexes.

[0013] The present invention also provides a method for identifying characteristic parameters by comparing the vibration measurement values ​​of a rotating machine with the vibration prediction values ​​of the rotating machine, the method comprising: (a) acquiring vibration measurement values ​​of the rotating machine; (b) inputting characteristic parameters of each part of the rotating machine; (c) creating a combination of characteristic parameters of an analytical model; (d) creating an analytical model vibration calculation input file in accordance with the combination of characteristic parameters created in step (c); (e) performing vibration analysis using the analytical model the number of times equal to the number of combinations of characteristic parameters; and (f) comparing the vibration measurement values ​​acquired in step (a) with the vibration prediction values ​​acquired in step (e) to identify characteristic parameters, wherein all or some of the characteristic parameters are associated with predetermined indices. [Effects of the Invention]

[0014] According to the present invention, it is possible to realize a vibration simulation device and a vibration simulation method that are capable of predicting vibrations of a rotating machine with high accuracy.

[0015] This contributes to suppressing vibrations and improving reliability of the rotating machine.

[0016] Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a diagram showing a schematic configuration of a vibration simulation device according to a first embodiment of the present invention. [Figure 2] 1 is a flowchart showing a method for calculating the bearing dynamic characteristics of a sliding bearing. [Figure 3] FIG. 2 is a diagram schematically illustrating the relationship between the load direction and rotation direction of a shaft in a sliding bearing in a coordinate system. [Figure 4A] FIG. 1 is a diagram showing the relationship between the Sommerfeld number and the dimensionless spring constant. [Figure 4B] FIG. 1 is a diagram showing the relationship between the Sommerfeld number and the dimensionless damping coefficient. [Figure 5A] FIG. 10 is a diagram showing the relationship between rotation speed and spring constant. [Figure 5B] FIG. 10 is a diagram illustrating the relationship between rotation speed and damping coefficient. [Figure 6] 3 is a flowchart showing a parameter identification processing method according to the first embodiment of the present invention. [Figure 7A] FIG. 10 is a diagram showing the relationship between rotation speed and spring constant. [Figure 7B] FIG. 10 is a diagram illustrating the relationship between rotation speed and damping coefficient. DETAILED DESCRIPTION OF THE INVENTION

[0018] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In the drawings, the same components are designated by the same reference numerals, and detailed description of overlapping parts will be omitted. [Example]

[0019] A vibration simulation device and a vibration simulation method according to a first embodiment of the present invention will be described with reference to FIGS. 1 to 7B.

[0020] Fig. 1 is a diagram showing a schematic configuration of a vibration simulator 10 according to a first embodiment of the present invention. Fig. 1 also shows a plain bearing 20, the vibration of which is to be detected, and a rotating machine 30 supported by the plain bearing 20.

[0021] The rotating machine 30 has a rotating shaft 31, and the left and right sides of the shaft 31 are supported by plain bearings 20. The rotation speed of the rotating machine 30 (i.e., the rotation speed of the shaft 31) changes during operation. The rotating machine 30 is provided with vibration detection units 19 on the left and right sides of the shaft 31 to detect vibrations of the rotating shaft 31.

[0022] The vibration simulator 10 mainly comprises a vibration measurement unit 22, a characteristic parameter input unit 13, a vibration prediction data creation unit 14, a vibration prediction unit 15, a parameter identification unit 16, and an output unit 17, and is connected to a data logger 18. The vibration simulator 10 is connected to a vibration detection unit 19 via the data logger 18.

[0023] The vibration measurement unit 22 is made up of a measurement data acquisition unit 11 and a feature extraction unit 12. The measurement data acquisition unit 11 acquires vibration waveform data of the rotating shaft 31 detected by the vibration detection unit 19. The feature extraction unit 12 obtains rotation-synchronous vibration components and the like from the vibration waveform data acquired by the measurement data acquisition unit 11.

[0024] The characteristic parameters of each part of the rotating machine 30 are input to the characteristic parameter input unit 13. The input characteristic parameters are initial values ​​or values ​​corrected based on the estimation results.

[0025] The vibration prediction data creation unit 14 creates an analysis model in accordance with the characteristic parameters input to the characteristic parameter input unit 13 .

[0026] The vibration prediction unit 15 analyzes the vibrations based on the analysis model created by the vibration prediction data creation unit 14 by physical simulation, and calculates a vibration prediction value.

[0027] The parameter identification unit 16 compares the vibration measurement value from the vibration measurement unit 22 with the vibration prediction value based on the analytical model from the vibration prediction unit 15, and estimates the characteristic parameters.

[0028] The output unit 17 can be configured with a display screen, an interface to an external device, etc., and outputs the characteristic parameter identification results and vibration prediction values ​​based on the analysis model.

[0029] The vibration simulation device 10 is a device that can be operated by a computer 21 such as a personal computer (PC). The vibration simulation device 10 may also be configured by the computer 21.

[0030] The vibration detection unit 19 is configured with, for example, an acceleration sensor, and detects the vibration of the rotating shaft 31 .

[0031] The data logger 18 is a storage device that stores data on the vibration of the rotating shaft 31 detected by the vibration detection units 19, i.e., time-domain vibration waveform data of the vibration of the rotating shaft 31. In this embodiment, the vibration detection units 19 for the rotating shaft 31 are provided near the left and right plain bearings 20, and the vibration waveform data of the rotating shaft 31 detected by the left and right vibration detection units 19 is stored separately in the storage areas of the data logger 18.

[0032] The measurement data acquisition unit 11 of the vibration measurement unit 22 acquires time domain vibration waveform data of the vibration of the rotating shaft 31 from the data logger 18 .

[0033] FIG. 2 is a flowchart showing a method for calculating the dynamic bearing characteristics of a sliding bearing.

[0034] First, in step S1, the bearing size of the plain bearing 20, shaft diameter D, rotational speed N, bearing load W, oil type, and oil film temperature T are input to the characteristic parameter input unit 13 as calculation quantities for the bearing dynamic characteristics.

[0035] Next, in step S2, as an intermediate process, the bearing width B, diametral clearance C, and viscosity μ are determined based on these input values. The bearing width B is determined from the combination of the input bearing size and shaft diameter D. The diametral clearance C is determined from the relationship between the shaft diameter D and the rotational speed N. The viscosity μ can be estimated from the oil film temperature T. The oil film temperature T can be predicted by actual measurement or by analysis using the operating conditions of the plain bearing 20 as input, or a value measured by a temperature sensor attached to the plain bearing 20 is used.

[0036] Next, in step S3, these values ​​are used to find the Sommerfeld number S from the following equation (1).

[0037]

number

[0038] Next, in step S4, the dimensionless bearing data corresponding to the Sommerfeld number S calculated by equation (1) is read. i,j , damping coefficient C i,j ) is prepared in advance.

[0039] Next, in step S5, the dimensionless bearing data read in step S4 is converted into a dimension (spring constant k i,j , damping coefficient c i,j )do.

[0040]

number

[0041]

number

[0042] Finally, in step S6, the calculations of equations (1), (2), and (3) are repeated using the rotation speed N as a parameter to obtain the dimensional dynamic characteristics (spring constant k i,j , damping coefficient c i,j ) can be obtained and used as bearing dynamic characteristic data for vibration calculation.

[0043] Here, the subscript i above indicates the direction of the applied force, j indicates the direction of the applied displacement or velocity, and the spring constant k and damping coefficient c are four parameters. Details of these parameters will be explained using Figure 3.

[0044] FIG. 3 is a diagram showing a schematic diagram of the relationship between the load direction and rotation direction of a shaft in a sliding bearing in a coordinate system.

[0045] In the coordinate system, the load direction (vertical direction) of the rotating shaft 31 is defined as x, and the direction 90 degrees counterclockwise from the load direction (horizontal direction) is defined as y. The rotation direction of the rotating shaft 31 is defined as x to y. In this case, the details of the four parameters of the bearing dynamic characteristics, namely the spring constants K and k and the damping coefficients C and c, are as follows:

[0046] K ij , k ij :i,j=x,yj-direction spring constant proportional to unit displacement in the i-direction C ij , c ij :i,j = i-direction damping coefficient proportional to unit velocity in the x, yj directions Therefore, the physical characteristic is that the value in the x direction (vertical direction) where the rotating shaft 31 receives the load is greater than the value in the y direction (horizontal direction).

[0047] 4A and 4B are diagrams showing the results of reading dimensionless bearing data corresponding to the Sommerfeld number S calculated using equation (1). At this time, the relationship between the load direction and rotation direction of the shaft 31 in the sliding bearing in the coordinate system is as shown in FIG.

[0048] FIG. 4A is a diagram showing the relationship between the Sommerfeld number S and the dimensionless spring constant K. It can be seen that Kxx>Kyy.

[0049] FIG. 4B is a diagram showing the relationship between the Sommerfeld number S and the dimensionless damping coefficient C. It can be seen that Cxx>Cyy.

[0050] 4A and 4B, it can be seen that the four values ​​of the dimensionless spring constant K and the dimensionless damping coefficient C are uniquely determined for the Sommerfeld number S.

[0051] 5A and 5B are diagrams showing the results of making the dimensionless spring constant K and the dimensionless damping coefficient C of FIGS. 4A and 4B dimensioned (dimensional spring constant k and dimensional damping coefficient c). The horizontal axis represents the rotation speed N.

[0052] 5A is a diagram showing the relationship between the rotation speed N and the spring constant k. It can be seen that kxx>kyy.

[0053] Fig. 5B is a diagram showing the relationship between the rotation speed N and the damping coefficient c. Here too, it can be seen that cxx>cyy.

[0054] 5A and 5B, it can be seen that the dimensional spring constant k and the dimensional damping coefficient c are uniquely determined for the rotation speed N.

[0055] Therefore, when estimating each parameter of the bearing dynamic characteristics, such as the spring constant and damping coefficient, it is possible to maintain the physical relationship between these parameters by using the Sommerfeld number S or a physical quantity that determines the Sommerfeld number S, such as the rotational speed.

[0056] Therefore, in this embodiment, as a method for estimating the bearing dynamic characteristics from the vibration measurement results detected by the vibration detection unit 19, the parameter P is estimated from the following relationship.

[0057] Real Sommerfeld number = characteristic calculation Sommerfeld number × P Here, the characteristic calculation Sommerfeld number is the Sommerfeld number S when calculating the bearing dynamic characteristics shown in Figures 4A and 4B, and the actual Sommerfeld number is the Sommerfeld number obtained by estimation. When the rotational speed N is used as an example of a physical quantity that determines the Sommerfeld number S, the following formula is obtained.

[0058] Actual rotation speed = characteristic calculation rotation speed x P Here, the characteristic calculation rotation speed is the rotation speed N when the bearing dynamic characteristics are calculated as shown in FIGS. 5A and 5B, and the actual rotation speed is the rotation speed obtained by estimation.

[0059] FIG. 6 is a flowchart showing a parameter identification processing method performed by the vibration simulator 10 of this embodiment.

[0060] First, in step S101, the vibration simulation device 10 is started and processing begins.

[0061] Next, in step S102, the measurement data acquisition unit 11 of the vibration measurement unit 22 acquires time domain vibration waveform data of the vibration of the rotating shaft 31 from the data logger 18, and the feature extraction unit 12 obtains rotation-synchronous vibration components and the like.

[0062] Next, in step S103, characteristic parameters of each part of the rotating machine 30 are input from the characteristic parameter input unit 13. Specifically, the unbalance distribution of the rotating shaft 31, the sliding bearing dynamic characteristics, etc. are input.

[0063] Next, in step S104, a combination of characteristic parameters in the analytical model is created.

[0064] Next, in step S105, an input file for vibration calculation of the analysis model is created in accordance with the combination of characteristic parameters created in step S104.

[0065] Next, in step S106, vibration analysis using the analytical model is performed as many times as the number of parameter combinations of the characteristic parameters.

[0066] Next, in step S107, vibration values ​​of the analysis results for the number of parameter combinations of the characteristic parameters are obtained.

[0067] Next, in step S108, the characteristic parameters are identified by data assimilation using a filter based on the analyzed vibration values ​​and the measured vibration values ​​for the number of parameter combinations of the characteristic parameters. The filter uses a method widely used in the field of sequential data assimilation, such as an ensemble Kalman filter.

[0068] Next, in step S109, the identification results of the characteristic parameters are obtained.

[0069] Next, in step S110, an analysis is performed using the identified characteristic parameter values ​​to obtain a vibration prediction value.

[0070] Next, in step S111, the vibration measurement value is compared with the vibration prediction value, and if it is not equal to or less than the predetermined set value (NO), the process returns to step S104. If it is equal to or less than the predetermined set value (YES), the process proceeds to step S112, where the result is output and the process ends.

[0071] 7A and 7B are diagrams showing an example of a physical quantity that determines the Sommerfeld number S, an index related to bearing dynamic characteristics, estimated using the rotational speed N. Fig. 7A shows the relationship between the rotational speed N and the spring constant k, and Fig. 7B shows the relationship between the rotational speed N and the damping coefficient c.

[0072] The actual rotation speed is the rotation speed obtained by estimation. The estimated actual rotation speed is the value obtained by multiplying the calculated rotation speed by the coefficient P along the horizontal axis and sliding it, and it can be seen that the spring constant k and damping coefficient c maintain the physical relationship that was observed when calculating the bearing characteristics.

[0073] As described above, according to the vibration simulator 10 of this embodiment, vibration prediction is performed using an analytical model of the rotating machine 30, and therefore it is possible to identify characteristic parameters of each part of the rotating machine 30 using measured vibration data of the rotating shaft 31 and analyzed vibration data obtained by the analytical model.

[0074] In particular, in the identification of bearing characteristics, the physical relationships between multiple parameters such as spring constants and damping coefficients can be maintained, improving analysis accuracy. In addition, it is also possible to identify characteristic parameters by retrofitting the device.

[0075] The present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations. [Explanation of symbols]

[0076] 10...Vibration simulation device, 11...Measurement data acquisition unit, 12...Feature extraction unit, 13...Characteristic parameter input unit, 14...Vibration prediction data creation unit, 15...Vibration prediction unit, 16...Parameter identification unit, 17...Output unit, 18...Data logger, 19...Vibration detection unit, 20...Plain bearing, 21...Computer, 22...Vibration measurement unit, 30...Rotating machine, 31...Shaft

Claims

1. a measurement data acquisition unit that acquires vibration waveform data of a rotating shaft of the rotary machine; a feature extraction unit that calculates a rotation-synchronous vibration component from the vibration waveform data acquired by the measurement data acquisition unit; a characteristic parameter input unit for inputting characteristic parameters of each part of the rotary machine; a vibration prediction data creation unit that creates an analysis model in accordance with the characteristic parameters input to the characteristic parameter input unit; a vibration prediction unit that analyzes vibrations based on the analysis model created by the vibration prediction data creation unit through physical simulation and calculates a vibration prediction value; a parameter identification unit that compares the vibration measurement value of the rotating machine with the vibration prediction value calculated by the vibration prediction unit and estimates characteristic parameters; an output unit that outputs the characteristic parameter identification result by the parameter identification unit and the vibration prediction value calculated by the vibration prediction unit, A vibration simulation device characterized in that all or some of the characteristic parameters are associated with predetermined indices.

2. 2. The vibration simulation device according to claim 1, The vibration simulation device is characterized in that the predetermined index includes the Sommerfeld number.

3. 2. The vibration simulation device according to claim 1, The vibration simulation device is characterized in that the predetermined index is calculated from an operating condition of the rotating machine.

4. 4. The vibration simulation device according to claim 3, The vibration simulation device is characterized in that the operating conditions include at least one of the bearing load, rotational speed, oil film temperature, bearing size, shaft diameter, bearing width, diametric clearance, and viscosity of the rotating machine.

5. (a) obtaining vibration measurements of a rotating machine; (b) inputting characteristic parameters of each part of the rotary machine; (c) creating a combination of characteristic parameters of the analytical model; (d) creating an analytical model vibration calculation input file in accordance with the combination of characteristic parameters created in the (c) step; (e) performing vibration analysis using the analytical model as many times as the number of combinations of the characteristic parameters; (f) comparing the vibration measurement value acquired in the step (a) with the vibration prediction value acquired in the step (e) to identify characteristic parameters; A vibration simulation method, characterized in that all or some of the characteristic parameters are associated with predetermined indices.

6. 6. The vibration simulation method according to claim 5, The vibration simulation method is characterized in that the predetermined index includes the Sommerfeld number.

7. 6. The vibration simulation method according to claim 5, A vibration simulation method, characterized in that the predetermined index is calculated from operating conditions of the rotating machine.

8. 8. The vibration simulation method according to claim 7, A vibration simulation method characterized in that the operating conditions include at least one of the bearing load, rotational speed, oil film temperature, bearing size, shaft diameter, bearing width, diametric clearance, and viscosity of the rotating machine.

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