Method and device for determining inherent frequency of equipment and electronic equipment

Abstract

The invention provides a method and device for determining the inherent frequency of equipment and electronic equipment. The method comprises the following steps: acquiring vibration response data acquired by a sensor, and calculating an initial inherent frequency of a to-be-tested device according to the vibration response data; according to a corresponding relation between the first inherent frequency and the second inherent frequency, determining an influence factor of the mass of the vibration sensor of the target test point on the initial inherent frequency; wherein the first inherent frequency is the inherent frequency obtained by performing modal simulation on the to-be-tested equipment model without adding the sensor mass; the second inherent frequency is an inherent frequency obtained by performing modal simulation on the to-be-tested equipment model added with sensor masses to a plurality of different test points; and according to the correction result of the influence factor on the initial inherent frequency, determining the final inherent frequency of the to-be-tested equipment without the sensor on the target test point. The accuracy and the measurement efficiency of the inherent frequency can be greatly improved.

Description

Technical Field

[0001] The present disclosure relates to the field of mechanical detection technology, and in particular to a method, device, and electronic device for determining the natural frequency of a device. Background Art

[0002] Modal testing is a method of determining the natural frequency and modal vibration shape of mechanical equipment by analyzing and measuring its vibration response. Through this test, the vibration characteristics, natural frequency and modal distribution of mechanical equipment can be understood, providing a basis for optimizing system design, improving structural strength and vibration reduction measures.

[0003] There are two main measurement methods for modal testing: contact and non-contact. Contact measurement requires the placement of acceleration sensors on the equipment components of mechanical equipment to measure the dynamic response of the structure, and has stable performance; non-contact measurement uses a laser vibrometer to obtain the displacement and velocity of the components. Non-contact measurement is costly and has high requirements for the test environment and objects, so contact measurement is the most common method used in the industry.

[0004] When using accelerometers for contact modal testing, for devices with small mass and stiffness, the additional mass of the accelerometer will cause changes in the structural characteristics of the device, resulting in measurement errors of the natural frequency. The more accelerometer layouts deployed on the device, the more serious the impact of the additional mass of the accelerometer on the measurement error. For devices with large mass and stiffness, although the additional mass of the accelerometer is much different from the mass of the device, it is not the total mass of the device that participates in the response, but the effective mass of the device (the mass of the device component where the accelerometer is deployed). The ratio of the mass of the accelerometer to the total mass of the device may be very small, but the ratio of the mass of the accelerometer to the effective mass may be very large. At this time, the additional mass of the accelerometer will also have a great impact on the mode and interfere with the measurement of the natural frequency. Summary of the invention

[0005] The technical problem to be solved by the present disclosure is to overcome the above-mentioned defects in the prior art and to provide a method, device and electronic device for determining the natural frequency of a device.

[0006] The present invention solves the above technical problems through the following technical solutions:

[0007] In a first aspect, a method for determining a natural frequency of a device is provided, comprising:

[0008] Acquiring vibration response data collected by a sensor, and calculating the initial natural frequency of the device under test according to the vibration response data; the sensor is installed at a target test point of the device under test;

[0009] According to the corresponding relationship between the first natural frequency and the second natural frequency, determining the influence factor of the mass of the vibration sensor at the target test point on the initial natural frequency; wherein the first natural frequency is the natural frequency obtained by modal simulation of the device model to be tested without adding the sensor mass; and the second natural frequency is the natural frequency obtained by modal simulation of the device model to be tested with adding the sensor mass at multiple different test points;

[0010] According to the correction result of the initial natural frequency by the influencing factor, the final natural frequency of the device to be tested without the sensor installed at the target test point is determined.

[0011] Optionally, the corresponding relationship represents the error percentage between the first natural frequency and the second natural frequency; wherein the corresponding relationship is obtained by fitting simulation data; the simulation data includes simulation results of modal simulation of the device model under test without adding sensor mass and simulation results of modal simulation of the device model under test with adding sensor mass at multiple different test points;

[0012] Determining the influence factor of the mass of the vibration sensor of the target test point on the initial natural frequency according to the corresponding relationship between the first natural frequency and the second natural frequency includes:

[0013] Determining the influencing factor according to the error percentage between the first natural frequency and the second natural frequency corresponding to the target test point;

[0014] Determining the final natural frequency of the device under test without the sensor installed at the target test point according to the correction result of the initial natural frequency by the influencing factor includes:

[0015] The product of the influencing factor and the initial natural frequency is determined as the correction result, or the product of the influencing factor and the polynomial fitting result of the initial natural frequency is determined as the correction result, and the correction result is determined as the final natural frequency.

[0016] Optionally, the number of the test points is positively correlated with the mass deviation; wherein the mass deviation is the deviation between the mass of the sensor and the mass of the device.

[0017] Optionally, the first natural frequency is a natural frequency obtained by performing modal simulation on a model of the device to be tested without adding sensor mass and using a subspace algorithm;

[0018] And / or, the second natural frequency is a natural frequency obtained by performing modal simulation on a model of the device to be tested with sensor masses added to a plurality of different test points and using a subspace algorithm.

[0019] In a second aspect, a device for determining a natural frequency of a device is provided, comprising:

[0020] An acquisition module, used to acquire vibration response data collected by a sensor, and calculate the initial natural frequency of the device under test according to the vibration response data; the sensor is installed on a target test point of the device under test;

[0021] A determination module, used to determine the influence factor of the mass of the vibration sensor of the target test point on the initial natural frequency according to the corresponding relationship between the first natural frequency and the second natural frequency; wherein the first natural frequency is the natural frequency obtained by modal simulation of the device model to be tested without adding the sensor mass; the second natural frequency is the natural frequency obtained by modal simulation of the device model to be tested with adding the sensor mass at multiple different test points;

[0022] The correction module is used to determine the final natural frequency of the device to be tested at the target test point where the sensor is not installed according to the correction result of the initial natural frequency by the influencing factor.

[0023] Optionally, the corresponding relationship represents the error percentage between the first natural frequency and the second natural frequency; wherein the corresponding relationship is obtained by fitting simulation data; the simulation data includes simulation results of modal simulation of the device model under test without adding sensor mass and simulation results of modal simulation of the device model under test with adding sensor mass at multiple different test points;

[0024] The determination module is specifically used to: determine the error percentage between the first natural frequency and the second natural frequency corresponding to the target test point as the influencing factor;

[0025] The correction module is specifically used to: determine the product of the influencing factor and the initial natural frequency as the correction result or determine the product of the influencing factor and the polynomial fitting result of the initial natural frequency as the correction result, and determine the correction result as the final natural frequency.

[0026] Optionally, the number of the test points is positively correlated with the mass deviation; wherein the mass deviation is the deviation between the mass of the sensor and the mass of the device.

[0027] Optionally, the first natural frequency is a natural frequency obtained by performing modal simulation on a model of the device to be tested without adding sensor mass and using a subspace algorithm;

[0028] And / or, the second natural frequency is a natural frequency obtained by performing modal simulation on a model of the device to be tested with sensor masses added to a plurality of different test points and using a subspace algorithm.

[0029] In a third aspect, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and used to run on the processor, wherein when the processor executes the computer program, the method for determining the natural frequency of the device described in any one of the first aspects is implemented.

[0030] In a fourth aspect, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the method for determining the natural frequency of the device described in any one of the first aspects is implemented.

[0031] On the basis of being in accordance with the common sense in the art, the above-mentioned preferred conditions can be arbitrarily combined to obtain the preferred embodiments of the present disclosure.

[0032] The positive and progressive effect of the present disclosure is that the present disclosure corrects the initial natural frequency through the correspondence between the predetermined first natural frequency and the second natural frequency, thereby eliminating the measurement error caused by the additional mass of the sensor on the natural frequency in the contact modal test, and can greatly improve the accuracy and measurement efficiency of the natural frequency. Moreover, the correspondence is obtained based on modal simulation, and the test points can be deployed at any position of the device under test model without being restricted by the test environment, thereby obtaining the correspondence between the first natural frequency and the second natural frequency at any position of the device under test, supporting the correction of the initial natural frequency at any position of the device under test, and realizing that the natural frequency with higher accuracy can be obtained by performing modal tests on the device under test based on fewer sensors. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A flowchart of a method for determining the natural frequency of a device provided by an exemplary embodiment of the present disclosure;

[0034] Figure 2 A schematic diagram of a modal simulation result of a first natural frequency of a ram model in a process of determining a natural frequency provided by an exemplary embodiment of the present disclosure;

[0035] Figure 3 A schematic diagram of the effect of dividing the main shaft model according to the test point positions in the process of determining the natural frequency provided by an exemplary embodiment of the present disclosure;

[0036] Figure 4 A schematic diagram of a modal simulation result of a second natural frequency of a ram model in a process of determining a natural frequency provided by an exemplary embodiment of the present disclosure;

[0037] Figure 5 A schematic diagram of a module of a device for determining a natural frequency of a device provided by an exemplary embodiment of the present disclosure;

[0038] Figure 6 The present invention provides a schematic structural diagram of an electronic device according to an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0039] The present disclosure is further described below by way of examples, but the present disclosure is not limited to the scope of the examples.

[0040] Prefixes such as "first" and "second" are used in the embodiments of the present disclosure only to distinguish different description objects, and have no limiting effect on the position, order, priority, quantity or content of the described objects. The use of prefixes such as ordinal numbers to distinguish description objects in the embodiments of the present disclosure does not constitute a limitation on the described objects. For the statement of the described objects, please refer to the description in the context of the embodiments, and no unnecessary limitation should be constituted due to the use of such prefixes. In addition, in the description of the present embodiment, unless otherwise specified, the meaning of "plurality" is two or more.

[0041] Figure 1 A flowchart of a method for determining the natural frequency of a device provided by an exemplary embodiment of the present disclosure, the method for determining the natural frequency comprises the following steps:

[0042] Step 101: Obtain vibration response data collected by a sensor, and calculate the initial natural frequency of the device under test according to the vibration response data.

[0043] In step 101, a modal test is performed using a sensor installed at a target test point of the device under test to obtain an initial natural frequency of the device under test. The specific implementation method is described in the relevant technology and will not be described in detail here.

[0044] Taking the device to be tested as a machine tool as an example, the sensor can be installed on the slide and / or spindle of the machine tool. The sensor can be, for example, a motion sensor or an acceleration sensor. Since the acceleration sensor is used, the dynamic characteristics of the device to be tested can be obtained by performing only one external excitation, which is simple and efficient. In this embodiment, the acceleration sensor is preferably used.

[0045] The number and deployment method of the target test points deployed on the device under test can be set according to the actual situation. It can be understood that the more the number of target test points, the higher the accuracy of the initial natural frequency calculated based on the vibration response data in theory. However, the increase in target test points means that the number of sensors installed on the device under test increases, and the additional mass of the sensor will have a great impact on the mode, resulting in errors in the calculated initial natural frequency, which needs to be corrected.

[0046] Step 102: Determine the influence factor of the mass of the vibration sensor at the target test point on the initial natural frequency according to the corresponding relationship between the first natural frequency and the second natural frequency.

[0047] Among them, the first natural frequency is the natural frequency obtained by modal simulation of the device model under test without adding sensor mass; the second natural frequency is the natural frequency obtained by modal simulation of the device model under test with sensor mass added at multiple different test points.

[0048] The number and deployment method of the test points on the device model under test can be set according to the actual situation. However, it must be satisfied that: the number of test points on the device model under test is greater than or equal to the number of target test points, and the set of target test points is a subset of the test points on the device model under test. The order of the first natural frequency and the second natural frequency can be set according to the actual situation, for example, both are set to 6th order. In this regard, the embodiments of the present disclosure are not particularly limited.

[0049] The model of the device under test can be, but is not limited to, a simplified finite element model. In this embodiment, by simplifying the structural model of the device under test, taking the device under test as a machine tool ram and spindle structure as an example, that is, simplifying the structural model of the machine tool ram and spindle structure, removing features such as rounded corners and circular holes, and establishing a finite element model to prepare for subsequent modal simulation. Using a simplified finite element model can reduce the complexity of the model, thereby improving calculation efficiency, while maintaining sufficient accuracy to simulate the actual structure of the device under test.

[0050] The following is a brief introduction to the modeling process of the device under test model: (1) Geometric modeling: Establish a geometric model of the structure or system contained in the device under test; (2) Meshing: Discretize the geometric model into a series of finite sub-regions; (3) Define material properties: Specify material properties for each sub-region, such as elastic modulus, Poisson's ratio, etc.; (4) Apply boundary conditions: Define boundary conditions such as fixed constraints, forces, pressures, etc. (5) Solve: Use numerical methods to solve and obtain node displacement, stress, strain and other results; (6) Post-processing: Analyze and visualize the results.

[0051] Modal tests usually consist of two parts: excitation points and response points. The excitation point is the location where force or vibration is applied to the device under test. The response point is the location where sensors are deployed to measure the vibration response of the structure. In order to conduct modal tests effectively, the layout of the excitation points and response points needs to be reasonably planned. Based on the requirements of modal tests, excitation points and response points need to be deployed on the device under test model. The test points of the device under test model include excitation points and response points.

[0052] In one embodiment, the modal simulation uses full modal testing: in this case, the excitation points and the response points are almost distributed throughout the entire device under test model to obtain the modal information as comprehensively as possible.

[0053] In one embodiment, the number of test points is positively correlated with the mass deviation. The mass deviation is the deviation between the mass of the sensor and the mass of the device. The mass deviation can be characterized by the difference between the mass of the sensor and the mass of the device, or by the ratio of the mass of the sensor to the mass of the device.

[0054] It can be understood that the smaller the deviation between the mass of the sensor and the mass of the device, the greater the impact of the mass of the sensor on the mode. The number of test points can be increased to obtain as much modal information as possible and improve the accuracy of the natural frequency estimation. The greater the deviation between the mass of the sensor and the mass of the device, the smaller the impact of the mass of the sensor on the mode. A more accurate natural frequency can be estimated with fewer test points, which is simple and efficient.

[0055] In one implementation, before modal simulation, the model of the equipment to be tested is segmented according to the test points. Taking the machine tool spindle as an example, the machine tool spindle model is divided into 4 sections and 5 cross sections are obtained. The 4 vertices of each cross section are used as test points, and sensor masses are added respectively, which is equivalent to arranging 1 sensor on each section.

[0056] The natural frequency determination method of this embodiment is applicable to determining the natural frequency of any device, and is particularly applicable to determining the natural frequency of a device with a small mass deviation. A small mass deviation means that the deviation between the mass of the sensor and the mass of the device is less than or equal to a deviation threshold. The deviation threshold can be set according to actual conditions.

[0057] Step 103: Determine the final natural frequency of the device under test without installing a sensor at the target test point according to the correction result of the initial natural frequency by the influencing factor.

[0058] The final natural frequency is the result of correcting the initial natural frequency by the added mass of the sensor.

[0059] In this embodiment, by correcting the initial natural frequency based on the correspondence between the predetermined first natural frequency and the second natural frequency, the measurement error caused by the additional mass of the sensor on the natural frequency in the contact modal test can be eliminated, which can greatly improve the accuracy and measurement efficiency of the natural frequency. Moreover, the correspondence is obtained based on modal simulation, and the test points can be deployed at any position of the device under test model without being restricted by the test environment, thereby obtaining the correspondence between the first natural frequency and the second natural frequency at any position of the device under test, supporting the correction of the initial natural frequency at any position of the device under test, and realizing that the natural frequency with high accuracy can be obtained by performing modal tests on the device under test based on fewer sensors.

[0060] In one embodiment, the first natural frequency is a natural frequency obtained by performing modal simulation on a model of the device to be tested without adding sensor mass and using a subspace algorithm.

[0061] The following is a brief introduction to an implementation method for calculating the first natural frequency based on the subspace algorithm:

[0062] (1) Data acquisition: Collect vibration response data, which is obtained by performing modal simulation on the device model under test.

[0063] (2) State space representation: The dynamic equations are converted into state space form, which usually involves converting the second-order differential equations into the form of a system of first-order differential equations. The dynamic equations can be expressed as: Where x is the state vector; u is the input vector; A and B are the corresponding matrices representing the state space model.

[0064] (3) Construction of the observation matrix: Based on the collected vibration response data, the observation matrix Y is constructed, which contains the output data of the device model under test. The observation matrix usually consists of continuous time series data, which can be directly measured through modal simulation.

[0065] (4) Subspace identification: The observation matrix Y is used to estimate the observable subspace of the device model under test. The subspace algorithm extracts the observable subspace by calculating the singular value decomposition of the observation matrix or other related methods. From the observable subspace, the state space models A and B can be further estimated.

[0066] (5) Modal parameter extraction: Once the state space model is obtained, the modal parameters can be extracted by calculating the eigenvalues ​​and eigenvectors. The eigenvalues ​​correspond to the square of the natural frequency, while the eigenvectors correspond to the vibration mode.

[0067] (6) Result verification: Verify the extracted modal parameters to ensure that they accurately reflect the dynamic characteristics of the device under test. The accuracy of the modal parameters can be verified by comparing theoretical predictions with experimental results.

[0068] See also Figure 2 The figure shows that the left end face of the slide model is constrained (boundary condition), its displacement and rotation in three dimensions of xyz are restricted, modal simulation is performed and the subspace algorithm is selected to solve the first 6 orders of modal simulation effects.

[0069] In this embodiment, a subspace algorithm is used in the process of calculating the natural frequency, which can effectively extract modal parameters from modal simulation data and process noise data, thereby improving the accuracy and efficiency of determining the first natural frequency.

[0070] In one embodiment, the second natural frequency is a natural frequency obtained by performing modal simulation on a model of the device under test with sensor masses added to a plurality of different test points and using a subspace algorithm.

[0071] See also Figure 3 , divide the spindle model according to the test point position, and the test point position can be divided into multiple sections. The specific division method can be selected according to the actual sensor layout plan during the modal test of the device to be tested. Usually the spindle model is divided into 1-8 sections. In order to measure a more accurate natural frequency, the spindle model is divided into 8 sections this time, and 9 sections including the root and the outside are obtained. One sensor will be arranged at each of the 4 vertices of each section, and the mass point is used to replace the additional mass of the sensor in the modal simulation. The second natural frequency can be obtained by performing modal simulation on the spindle model with added mass points and using the subspace algorithm. The simulation effect of the first 6 modes can be seen in Figure 4 shown.

[0072] It should be noted that the boundary conditions for modal simulation of the device under test model with sensor mass added to multiple different test points are also consistent with the boundary conditions for modal simulation of the device under test model without sensor mass added.

[0073] In this embodiment, a subspace algorithm is used in the process of calculating the natural frequency, which can effectively extract modal parameters from modal simulation data and process noise data, thereby improving the accuracy and efficiency of determining the second natural frequency.

[0074] In one embodiment, the corresponding relationship represents the error percentage between the first natural frequency and the second natural frequency. The corresponding relationship is obtained by fitting simulation data; the simulation data includes simulation results of modal simulation of the device under test model without adding sensor mass and simulation results of modal simulation of the device under test model with adding sensor mass at multiple different test points.

[0075] In step 102, an influence factor is determined according to an error percentage between a first natural frequency and a second natural frequency corresponding to a target test point.

[0076] In step 103, the product of the influencing factor and the initial natural frequency is determined as the correction result, and the correction result is determined as the final natural frequency. The calculation formula for correcting the initial natural frequency according to the influencing factor is expressed as follows:

[0077]

[0078] Among them, Y 1 Indicates the correction result. represents the initial natural frequency. ε represents the influence factor represented by the error percentage.

[0079] For example, Figures 2 to 4 Taking as an example, the error percentages of the two groups of modal results are shown in the table below.

[0080] Degree First natural frequency The second natural frequency Percent Error First level 38.23 35.367 7.49％ Second order 38.239 35.396 7.43％ Third level 111.51 103.95 6.78％ Fourth level 158.35 158.35 0％ Level 5 209.05 208.62 0.21％ Level 6 209.49 209.05 0.21％

[0081]

[0082] in,

[0083] In this embodiment, after obtaining the initial natural frequency obtained by the modal test using the above calculation formula, a more accurate natural frequency can be obtained using a simple mathematical algorithm, which is efficient and easy to implement. In this embodiment, since only the error percentage of the first 6 orders is included, only the natural frequency of the first 6 orders of sensorless added mass can be solved.

[0084] In one embodiment, in step 103, the product of the influencing factor and the polynomial fitting result of the initial natural frequency is determined as the correction result. The polynomial can be, but is not limited to, a fifth-order polynomial. For example, the fitting result of the fifth-order polynomial is as follows:

[0085] y=-1.237x 5 +22.417x 4 -157.55x 3 +530.45x 2 -786.4x+427.68;

[0086]

[0087] Among them, function y is a quintic polynomial function fitted according to the simulation results, x represents the order, such as 1 to 6 in the above table, and y represents the natural frequency value corresponding to each order.

[0088] In this embodiment, a more accurate natural frequency can be obtained by using a polynomial fitting function and an error percentage. Since the exponent of the polynomial fitting function is relatively high, the natural frequencies after the sixth order can be predicted.

[0089] Corresponding to the aforementioned embodiment of the method for determining the natural frequency of a device, the present disclosure also provides an embodiment of an apparatus for determining the natural frequency of a device.

[0090] Figure 5 A schematic diagram of a module of a device for determining a natural frequency of a device provided by an exemplary embodiment of the present disclosure, the device comprising:

[0091] An acquisition module 51 is used to acquire vibration response data collected by a sensor and calculate the initial natural frequency of the device under test according to the vibration response data; the sensor is installed at a target test point of the device under test;

[0092] The determination module 52 is used to determine the influence factor of the mass of the vibration sensor of the target test point on the initial natural frequency according to the corresponding relationship between the first natural frequency and the second natural frequency; wherein the first natural frequency is the natural frequency obtained by performing modal simulation on the device model under test without adding the sensor mass; and the second natural frequency is the natural frequency obtained by performing modal simulation on the device model under test with adding the sensor mass at multiple different test points;

[0093] The correction module 53 is used to determine the final natural frequency of the device under test at the target test point where the sensor is not installed, according to the correction result of the initial natural frequency by the influencing factor.

[0094] Optionally, the corresponding relationship represents the error percentage between the first natural frequency and the second natural frequency; wherein the corresponding relationship is obtained by fitting simulation data; the simulation data includes simulation results of modal simulation of the device under test model without adding sensor mass and simulation results of modal simulation of the device under test model with adding sensor mass at multiple different test points; the polynomial

[0095] The determination module is specifically used to: determine the error percentage between the first natural frequency and the second natural frequency corresponding to the target test point as the influencing factor;

[0096] The correction module is specifically used to: determine the product of the influencing factor and the initial natural frequency as the correction result or determine the product of the influencing factor and the polynomial fitting result of the initial natural frequency as the correction result, and determine the correction result as the final natural frequency.

[0097] Optionally, the number of the test points is positively correlated with the mass deviation; wherein the mass deviation is the deviation between the mass of the sensor and the mass of the device.

[0098] Optionally, the first natural frequency is a natural frequency obtained by performing modal simulation on a model of the device to be tested without adding sensor mass and using a subspace algorithm;

[0099] And / or, the second natural frequency is a natural frequency obtained by performing modal simulation on a model of the device to be tested with sensor masses added to a plurality of different test points and using a subspace algorithm.

[0100] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only illustrative, wherein the units described as separate components may or may not be physically separated, and the components as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the disclosed solution.

[0101] Figure 6 This is a structural schematic diagram of an electronic device shown in an example embodiment of the present disclosure, the electronic device includes a memory, a processor, and a computer program stored in the memory and used to run on the processor, and when the processor executes the computer program, the method for determining the natural frequency of the device described in any of the above embodiments is implemented. Figure 6 The electronic device 60 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0102] like Figure 6 As shown, the electronic device 60 may be in the form of a general-purpose computing device, for example, it may be a server device. The components of the electronic device 60 may include, but are not limited to: at least one processor 61, at least one memory 62, and a bus 63 connecting different system components (including the memory 62 and the processor 61).

[0103] The bus 63 includes a data bus, an address bus, and a control bus.

[0104] The memory 62 may include a volatile memory, such as a random access memory (RAM) 621 and / or a cache memory 622 , and may further include a read-only memory (ROM) 623 .

[0105] The memory 62 may also include a program tool 625 (or utility) having a set (at least one) of program modules 624, such program modules 624 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0106] The processor 61 executes various functional applications and data processing by running the computer program stored in the memory 62, such as the method for determining the natural frequency of the device provided in any of the above embodiments.

[0107] The electronic device 60 may also communicate with one or more external devices 64 (e.g., keyboards, pointing devices, etc.). Such communication may be performed via an input / output (I / O) interface 65. Furthermore, the electronic device 60 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 66. As shown, the network adapter 66 communicates with other modules of the electronic device 60 via a bus 63. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 60, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.

[0108] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules to be embodied.

[0109] An embodiment of the present disclosure further provides a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the method for determining the natural frequency of the device provided in any of the above embodiments is implemented.

[0110] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0111] The embodiment of the present disclosure further provides a computer program product, including a computer program, which implements any of the above-mentioned methods for determining the natural frequency of the device when the computer program is executed by a processor.

[0112] Among them, the program code for executing the computer program product of the present disclosure can be written in any combination of one or more programming languages, and the program code can be executed completely on the user device, partially on the user device, as an independent software package, partially on the user device and partially on a remote device, or completely on the remote device.

[0113] Although the specific embodiments of the present disclosure are described above, those skilled in the art should understand that this is only an example, and the protection scope of the present disclosure is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present disclosure, but these changes and modifications all fall within the protection scope of the present disclosure.

Claims

1. A method for determining the natural frequency of a device, characterized in that: include: Acquire vibration response data collected by the sensor, and calculate the initial natural frequency of the device to be tested according to the vibration response data; The sensor is installed on a target test point of the device under test; According to the corresponding relationship between the first natural frequency and the second natural frequency, determining the influence factor of the mass of the vibration sensor at the target test point on the initial natural frequency; wherein the first natural frequency is the natural frequency obtained by modal simulation of the device model to be tested without adding the sensor mass; and the second natural frequency is the natural frequency obtained by modal simulation of the device model to be tested with adding the sensor mass at multiple different test points; According to the correction result of the initial natural frequency by the influencing factor, the final natural frequency of the device to be tested without the sensor installed at the target test point is determined.

2. The method for determining the natural frequency of a device according to claim 1, characterized in that: The corresponding relationship represents the error percentage between the first natural frequency and the second natural frequency; wherein the corresponding relationship is obtained by fitting simulation data; the simulation data includes simulation results of modal simulation of the device under test model without adding sensor mass and simulation results of modal simulation of the device under test model with adding sensor mass at multiple different test points; Determining the influence factor of the mass of the vibration sensor of the target test point on the initial natural frequency according to the corresponding relationship between the first natural frequency and the second natural frequency includes: Determining the influencing factor according to the error percentage between the first natural frequency and the second natural frequency corresponding to the target test point; Determining the final natural frequency of the device under test without the sensor installed at the target test point according to the correction result of the initial natural frequency by the influencing factor includes: The product of the influencing factor and the initial natural frequency is determined as the correction result, or the product of the influencing factor and the polynomial fitting result of the initial natural frequency is determined as the correction result, and the correction result is determined as the final natural frequency.

3. The method for determining the natural frequency of a device according to claim 1, characterized in that: The number of the test points is positively correlated with the mass deviation, wherein the mass deviation is the deviation between the mass of the sensor and the mass of the device.

4. The method for determining the natural frequency of a device according to any one of claims 1 to 3, characterized in that: The first natural frequency is a natural frequency obtained by performing modal simulation on a model of the device to be tested without adding sensor mass and using a subspace algorithm; And / or, the second natural frequency is a natural frequency obtained by performing modal simulation on a model of the device to be tested with sensor masses added to a plurality of different test points and using a subspace algorithm.

5. A device for determining the natural frequency of a device, characterized in that: include: An acquisition module, used to acquire vibration response data collected by the sensor, and calculate the initial natural frequency of the device to be tested according to the vibration response data; The sensor is installed on a target test point of the device under test; A determination module, used to determine the influence factor of the mass of the vibration sensor of the target test point on the initial natural frequency according to the corresponding relationship between the first natural frequency and the second natural frequency; wherein the first natural frequency is the natural frequency obtained by modal simulation of the device model to be tested without adding the sensor mass; the second natural frequency is the natural frequency obtained by modal simulation of the device model to be tested with adding the sensor mass at multiple different test points; The correction module is used to determine the final natural frequency of the device to be tested at the target test point where the sensor is not installed according to the correction result of the initial natural frequency by the influencing factor.

6. The device for determining the natural frequency of the device according to claim 5, characterized in that: The corresponding relationship represents the error percentage between the first natural frequency and the second natural frequency; wherein the corresponding relationship is obtained by fitting simulation data; the simulation data includes simulation results of modal simulation of the device under test model without adding sensor mass and simulation results of modal simulation of the device under test model with adding sensor mass at multiple different test points; The determination module is specifically used to: determine the error percentage between the first natural frequency and the second natural frequency corresponding to the target test point as the influencing factor; The correction module is specifically used to: determine the product of the influencing factor and the initial natural frequency as the correction result or determine the product of the influencing factor and the polynomial fitting result of the initial natural frequency as the correction result, and determine the correction result as the final natural frequency.

7. The device for determining the natural frequency of the device according to claim 5, characterized in that: The number of the test points is positively correlated with the mass deviation, wherein the mass deviation is the deviation between the mass of the sensor and the mass of the device.

8. The device for determining the natural frequency of the device according to any one of claims 5 to 7, characterized in that: The first natural frequency is a natural frequency obtained by performing modal simulation on a model of the device to be tested without adding sensor mass and using a subspace algorithm; And / or, the second natural frequency is a natural frequency obtained by performing modal simulation on a model of the device to be tested with sensor masses added to a plurality of different test points and using a subspace algorithm.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and used to run on the processor, characterized in that: When the processor executes the computer program, the natural frequency determination method of the device according to any one of claims 1 to 4 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the natural frequency determination method of the device according to any one of claims 1 to 4 is implemented.

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