CN110242732B - Planetary gearbox vibration measuring point optimization method based on virtual simulation and LLE - Google Patents
Planetary gearbox vibration measuring point optimization method based on virtual simulation and LLE Download PDFInfo
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Abstract
The planetary gearbox vibration measurement point optimization method based on virtual simulation and LLE comprises the following steps: establishing a planetary gearbox dynamic model under the working state of a normal working condition; selecting several representative fault states in the service process of the planetary gearbox, and respectively establishing a planetary gearbox dynamic model under the working states of the faults; the method comprises the steps that the internal structure of the planetary gearbox and the installation conditions of a surface sensor of a box body are comprehensively considered, and a plurality of vibration sensor measuring points are selected in advance; obtaining vibration simulation signals of each measuring point under various working states and executing first measuring point optimization; and after the optimization of the first measuring points in all the selected working states is completed, determining the comprehensive ranking of the importance of the vibration measuring points by a weighting calculation method. The invention aims to provide a planetary gearbox vibration measuring point optimization method based on virtual simulation and LLE, which can greatly reduce the test times and the test cost and lay a foundation for the subsequent actual measurement test.
Description
Technical Field
The invention relates to a planetary gearbox vibration measuring point optimization method based on virtual simulation and LLE.
Background
The planetary gearbox of a certain type is a three-freedom planetary gearbox with three shaft type clutch gear shifting, has the advantages of large transmission ratio, compact mechanism, high transmission efficiency and the like, and is widely applied to a certain type of tank. When working in a harsh environment, gear faults often occur, and if the faults cannot be found and effectively treated in time, the faults are further worsened, so that the functions of the planetary gearbox are seriously influenced. Therefore, the method has great significance in fault diagnosis, and a great deal of work is done at home and abroad. The test tests necessary for the fault diagnosis research require the use of a large amount of equipment and equipment, are time-consuming and labor-consuming, and are not suitable for large-scale implementation. The virtual test technology is a new technology, not only can prepare for the early work of the actual simulation test, but also can replace the traditional test to a certain extent, greatly reduces the test times and reduces the actual test cost. In "virtual test technique and its application in tank gearbox failure mechanism research [ D ]. beijing: the method comprises the steps of adopting ADAMS software in the institute of Engineers engineering, 2012:10-49, establishing a certain type of virtual prototype model of the gearbox in a computer, simulating signals under typical faults of the gearbox by setting various working conditions and faults, replacing actual signals with simulation signals for research, verifying the rationality of the virtual prototype model according to actual measurement tests, and partially replacing actual tests to carry out research. In the analysis of impact characteristics of a large-scale wind turbine generator gear transmission system based on a virtual prototype in Chenshaojun [ D ]. Beijing, North China electric university, 2008,33-50 ], a dynamic model of the large-scale wind turbine generator gear transmission system is established based on a virtual test technology, the impact characteristics of the transmission system are analyzed, and a basis is provided for the next research.
In a fault diagnosis system of a rotary machine, a vibration signal is a carrier of gear state information, whether the vibration signal contains state information of a planetary gearbox is directly determined by the suitability of measuring point selection, and whether the collected vibration signal can really cover the real situation of the gearbox is directly determined by the success of fault feature extraction. And certain type planet gearbox structure is complicated, and sensor measurement station arranges and receives box structure and real car environment influence, can arrange that vibration sensor quantity and position are limited. In the existing gearbox test, the vibration sensor arrangement method is based on experience, and useful information or redundant information can be missed or generated without reasonably planning the sensor arrangement, so that the test times need to be increased, the test cost is increased, and therefore, the optimization of the number and the positions of the sensors is necessary.
Disclosure of Invention
In order to solve the problems, the invention provides a planetary gearbox vibration measuring point optimization method based on virtual simulation and LLE, which can greatly reduce the test times and the test cost and lay a foundation for the subsequent actual measurement test.
The invention relates to a planetary gearbox vibration measurement point optimization method based on virtual simulation and LLE, which comprises the following steps:
establishing a planetary gearbox dynamic model under a working state of a normal working condition: the gear-box rigid-flexible coupling model is formed by two parts, namely a gear multi-rigid-body model and a box flexible-body model, and is coupled through a bearing to form a gear-box rigid-flexible coupling model;
injecting a gear fault: selecting several representative fault states in the service process of the planetary gearbox, and respectively establishing a planetary gearbox dynamic model under the working states of the faults;
primary selection of measuring points: comprehensively considering the internal structure of the planetary gearbox and the installation conditions of the surface sensor of the box body, and selecting a plurality of vibration sensor measuring points in advance in a region with larger vibration response in modal analysis;
using a planetary gearbox dynamic model corresponding to a working state, acquiring vibration simulation signals of all measuring points in the working state and executing first measuring point optimization;
after the optimization of the first measuring points in all the selected working states is completed, the comprehensive ranking of the importance of the vibration measuring points is determined by a weighting calculation method, and the comprehensive ranking of the importance of each measuring point is determined by the following formula:
Pifor measuring the importance comprehensive ranking value of point i, PiThe smaller the value, the stronger the importance, and the more forward the ranking; n represents a certain working state, N represents the number of selected working states, LiArranging sequence values of the measuring points i from large to small in sensitivity under a certain working state; lambda represents a weighting coefficient, which is determined by the importance of each state, and the sum of the weighting coefficients of all selected working states is 1;
selecting 3-8 measuring points with the front comprehensive ranking of importance as optimized measuring points, eliminating 1-3 measuring points which are insensitive to fault vibration characteristics at the tail, and taking the rest measuring points as auxiliary references, thereby completing the optimization of the planetary gearbox vibration measuring points;
wherein the first station optimization comprises:
a) introducing characteristic parameters to evaluate the effectiveness of the measuring points, calculating the corresponding characteristic parameters of the vibration simulation signals of the measuring points, and constructing a measuring point characteristic vector space;
b) and reducing the dimension of the characteristic vector space of the measuring points by adopting a local linear embedding algorithm, calculating the 2-norm of the low-dimensional vector of each measuring point after dimension reduction, and expressing the sensitivity of the measuring point by using the 2-norm of the low-dimensional vector of the measuring point, wherein the higher the 2-norm of the low-dimensional vector of the measuring point is, the more sensitive the measuring point is.
According to one embodiment of the invention, the planetary gearbox dynamics model modeling process is as follows:
(1) according to the structure and the transmission principle of the planetary gearbox, the model of the planetary gearbox is reasonably simplified, the three-dimensional model of each part is established by using ProE software, the parts are assembled without interference, and the assembly body is stored in a Paracolid format;
(2) the method comprises the steps of introducing a three-dimensional model of the planetary gearbox by using a ProE interface of ADAMS software, adding a fixed pair to a fixed piece, adding a rotating pair to a rotating piece, adding a collision contact force to a gear pair, adding a rotary drive to a driving shaft, adding a loading torque to an output shaft according to the working condition of each part when the planetary gearbox runs, and establishing a multi-rigid-body dynamic model of a transmission part;
(3) calculating the mode of the box body by using ANSYS software, acquiring a mode neutral file of the box body, and importing the mode neutral file to make a rigid body model of the box body flexible by adopting an ANSYS interface of ADAMS software; and coupling the multi-rigid-body dynamic model of the transmission part with the flexible-body model of the box body through a bearing, and finally establishing a rigid-flexible coupling dynamic model of the gear-box body.
According to one embodiment of the present invention, the characteristic parameters include a peak-to-peak value, a root mean square value, a side value, a kurtosis index, a waveform index, a peak index, a pulse index, a margin index, and a sample entropy, which can measure energy and intensity of the vibration signal, and are more sensitive to impulse shock.
According to an embodiment of the present invention, when the local linear embedding algorithm is adopted, the number of neighbor points is taken as 5, and the low-dimensional space dimension is taken as 3.
The invention relates to a gearbox vibration measuring point optimization method integrating virtual simulation and a local linear embedding algorithm, which comprises the steps of firstly establishing a gear-box rigid-flexible coupling model and injecting faults; then, considering the operability of the measuring points comprehensively, preliminarily selecting measuring points of the box body surface sensor, and obtaining vibration simulation signals of the measuring points; and finally, calculating corresponding characteristic parameters of vibration signals of the measuring points, optimally selecting the measuring points by adopting a local linear embedding algorithm, obtaining measuring point sensitivity sequences in different gear states, and finally obtaining the comprehensive importance sequence of the vibration measuring points by adopting a weighting calculation method. The method can not only prepare for the early stage work of the actual measurement test, but also replace the traditional test to a certain extent, greatly reduce the test times, reduce the actual test cost and lay the foundation for the subsequent actual measurement test.
The following describes in further detail embodiments of the present invention with reference to the accompanying drawings. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
Drawings
FIG. 1 is a schematic view of a planetary transmission of the type shown;
FIG. 2 is a flow chart of the planetary transmission vibration measurement point optimization method integrating virtual simulation and LLE algorithm of the present invention;
FIG. 3a Z30 is a graph of vibration simulation signals for sun gear broken tooth fault condition test point 2;
FIG. 3b Z30 is a graph of vibration simulation signals for sun gear broken tooth fault condition test point 5;
FIG. 3c Z30 is a graph of vibration simulation signals for sun gear broken tooth fault condition test point 7;
FIG. 4 is a view of a low-dimensional vector distribution diagram of measurement points when a gear of a Z30 sun gear is broken;
FIG. 5 is a view of a low-dimensional vector distribution diagram of the measurement points under normal operating conditions;
FIG. 6 is a low-dimensional vector distribution diagram of measuring points when a planet gear of Z15 is broken.
Detailed Description
The use process of the planetary gearbox measuring point optimization method integrating virtual simulation and local linear embedding algorithm is explained by taking a planetary gearbox which is commonly used in a tank as an example. The schematic diagram of the internal structure is shown in fig. 1, and because the meshing relationship of the gears in the spatial three-dimensional structure cannot be completely expressed in a plan view, a dotted line is used for connecting two actually meshed gears in fig. 1. The planetary gear train consists of a driving shaft, an intermediate shaft, a driven shaft and a planetary gear system. The planetary gear system has three planet rows, namely a K1 compound planet row, a K2 planet row and a K3 planet row.
1. Establishing a planetary gearbox dynamic model under a working state of a normal working condition
When the planetary gearbox runs under external drive, the gear meshing force of the planetary gearbox changes along with the change of the meshing rigidity, so that a shaft system where the gear is located vibrates, bearing seat support reaction force changes correspondingly, and finally dynamic response is generated in a gearbox body. The gear box dynamic model built by the invention consists of a gear multi-rigid-body model and a box body flexible-body model, and is coupled through a bearing to form a gear-box body rigid-flexible coupling model. The planetary gearbox dynamics modeling process is as follows:
(1) according to the structure and the transmission principle of the planetary gearbox, the gearbox model is reasonably simplified, the three-dimensional model of each part is established by using ProE software, the parts are assembled without interference, and the assembly body is stored in a Paracolid format.
(2) A three-dimensional model of the gearbox is introduced by using a ProE interface of ADAMS software, a fixed pair is added to a fixed piece, a rotating pair is added to a rotating piece, a collision contact force is added to a gear pair, a rotary drive is added to a driving shaft, a loading torque is added to an output shaft according to the working condition of each part when the gearbox runs, and a multi-rigid-body dynamic model of a transmission part is established.
(3) And calculating the mode of the box body by using ANSYS software, and acquiring a mode neutral file of the box body. And (3) importing a modal neutral file to make the rigid body model of the box body flexible by adopting an ANSYS interface of ADAMS software. And coupling the multi-rigid-body dynamic model of the transmission part with the flexible-body model of the box body through a bearing, and finally establishing a rigid-flexible coupling dynamic model of the gear-box body.
2. Gear fault injection
The planetary gearbox dynamics model established through the steps is strong in universality, and various fault points can be conveniently injected into the model for fault simulation so as to research the fault mechanism of the model and lay a foundation for subsequent measurement point optimization. In the embodiment, the most representative fault of tooth breakage of the sun gear and the planet gear of the K3 planet row is selected as a fault injection point. The fault of broken teeth of the sun gear is arranged on the Z30 sun gear of the K3 planet row, and certain teeth of the sun gear are cut off. And replacing the broken gear with the normal gear for reassembly. And establishing a dynamic model of the tooth breaking fault of the Z15 planet wheel with the K3 planet row by using the same method.
3. Initial selection of measuring points
The sensor measuring point optimization selection can be considered from two aspects: on one hand, engineering practice needs to be considered, the measuring points of the sensor should have operability, the contact surface is required to be smooth and flat when the vibration sensor is installed, so that the reliability of vibration signals acquired by the sensor is guaranteed, the measuring points limited in installation conditions are eliminated, for the gearbox of the embodiment, due to the fact that the structure is complex, the dismounting process is complex, the measuring points on the surface of the gearbox body should be considered preferentially, the gearbox is prevented from being dismounted frequently, the sensor is convenient to install and dismount, the testing process is simplified, and the diagnosis cost is reduced. On the other hand, the effectiveness of the sensor measuring points is considered, the measuring points are sensitive to fault information and are as close as possible to the diagnosis part, the equipment state can be comprehensively reflected, more fault information can be obtained, the measuring points which are useless or even interfered for diagnosing faults are optimized, and the number of sensors is reduced as far as possible under the condition of meeting the test requirement.
In order to ensure the operability of the sensor measuring points, the internal structure of the gearbox and the installation conditions of the surface sensor of the box body are comprehensively considered, and 10 vibration sensor measuring points are selected in advance in a region with larger vibration response in modal analysis, as shown in table 1.
TABLE 1 sensor measurement Point description
| Measuring point sequence number | Mounting | Test direction | |
| 1 | On the right side of the box body | Axial direction of |
|
| 2 | The right side of the box body is arranged above the fixed-axis wheel train | Perpendicular to the axial direction of the gearbox | |
| 3 | The upper part of the box body is over against the K1 planet row | Perpendicular to the axial direction of the gearbox | |
| 4 | The upper part of the box body is over against the K2 planet row | Perpendicular to the axial direction of the gearbox | |
| 5 | The upper part of the box body is over against the K3 planet row | Perpendicular to the axial direction of the gearbox | |
| 6 | On the left side coupling of the box body | Perpendicular to the axial direction of the gearbox | |
| 7 | The left end of the box body is covered with | Axial direction of gearbox | |
| 8 | The bottom of the box body is over against the K1 planet row | Perpendicular to the axial direction of the gearbox | |
| 9 | The bottom of the box body is over against the K2 planet row | Perpendicular to the axial direction of the gearbox | |
| 10 | The bottom of the box body is over against the K3 planet row | Perpendicular to the axial direction of the gearbox |
4. First measurement point optimization
In this embodiment, a process of optimizing a sensor measuring point by using a Local Linear Embedding (LLE) algorithm is described by taking processing of a tooth breaking fault signal of a Z30 sun gear of a K3 planet row as an example, and other fault signal analysis processes and methods are similar. A gear of a gearbox is set to be an IV gear in an ADAMS, the input rotating speed of a driving shaft is 1500r/min, the loading torque of an output shaft is 900 N.m, the simulation time is 0.5s, the number of sampling points is 5000, and vibration simulation signals obtained at part of measuring points are shown in figures 3a, 3b and 3 c.
In order to further screen the measuring points, characteristic parameters are introduced to evaluate the effectiveness of the measuring points. The peak value, the root mean square value and the average value of the amplitude can measure the energy and the intensity of the vibration signal, and the kurtosis index, the waveform index, the peak value index, the pulse index, the margin index and the sample entropy are sensitive to pulse impact. If the gear is in failure, the more the meshing pulse is generated, the larger the impact amplitude is, namely the more the vibration signal deviates from the normal state, and the index value generally changes correspondingly. Sensitivity and stability of different indexes are different, and multiple indexes are used simultaneously to ensure index performance, so that effectiveness of a sensor measuring point is better tested. And calculating corresponding indexes of the vibration simulation signals of the measuring points, and constructing a measuring point characteristic vector space as shown in table 2.
TABLE 2Z 30 characteristic vector of each measuring point when sun gear tooth breakage
For any measuring point on the surface of the planetary gearbox body, a high-dimensional multi-parameter model for describing the overall vibration state is adopted before the dimensionality reduction of the characteristic vector, and after the dimensionality reduction of LLE is adopted, the overall information contained in each measuring point is unchanged and only becomes the visual reflection of the vibration characteristic in a low-dimensional space. And forming a 10 × 9 high-dimensional characteristic matrix by each index of different measuring points, reducing the dimension of the acceleration signal index vector by adopting an LLE algorithm, reflecting the characteristics of the multi-dimensional vector by using as few measuring points as possible, and reducing redundant information in the multi-dimensional vector. And taking the nearest neighbor point number k as 5 and the low-dimensional space dimension d as 3. Table 3 is the low-dimensional coordinate values of the measurement points calculated by LLE in table 2, and fig. 4 is a low-dimensional vector distribution diagram of the measurement points when the gear of the Z30 sun gear is broken. In table 3 and fig. 4, the low-dimensional coordinates x, y, and z of each measuring point represent the sensitivity of the measuring point in different directions, the larger the absolute value of the low-dimensional coordinates x, y, and z is, the more the measuring point can reflect the vibration characteristic, and the 2-norm of the low-dimensional vector of each measuring point represents the overall standard of the sensitivity of the measuring point.
TABLE 3Z 30 Low-dimensional coordinate value of each measuring point when the sun gear is broken
The sensitivity ranking of each measuring point in three states is shown in FIGS. 4-6 and Table 4, respectively, from which it can be seen that the sensitivity of different measuring points in the same state is different from that of the same measuring point in different states, which also indicates the necessity of measuring point optimization from another view.
TABLE 4 Low-dimensional vector 2-norm ordering for each measurement point
| State of the gearbox | Measurement station sequencing (from big to small) |
| Normal state | 3 5 4 6 2 10 8 1 9 7 |
| Gear-broken state of Z30 sun gear | 5 4 3 10 6 2 9 8 1 7 |
| Tooth breaking state of Z15 planet gear | 5 4 6 3 10 8 2 9 1 7 |
And determining the comprehensive ranking of the importance of the vibration measuring points by a weighting calculation method, wherein the comprehensive ranking value of the importance of each measuring point is determined by the following formula.
In the formula, PiFor measuring point importance comprehensive ranking value, PiThe smaller the value, the more important and the more top the ranking. n represents a normal state when n is 1, a broken tooth state of the sun gear of Z30 when n is 2, and a broken tooth state of the planet gear of Z15 when n is 3. L isiIn order to rank the sensitivities in a certain state, λ is a weighting coefficient, and it is preliminarily considered that the importance of the three states is consistent, so λ is 1/3.
Through calculation, the importance ranking values of the 10 primarily selected vibration measuring points under the three states of the gearbox can be obtained, the importance values are ranked from small to large, and the final ranking result is shown in table 5.
TABLE 5 Final ranking of Point importance
The importance ranking of the gearbox vibration measurement point after optimization is given in table 5. The importance of the measuring point 5 is arranged firstly, and the measuring point 5 is located right above the planet row where the fault gear is located, the box body is thin, the deformation degree is large, and the measuring point 5 is close to the driven shaft bearing, so that the measuring point is most sensitive to the fault vibration characteristics of the K3 gear row; although the measuring point 10 is close to the bearing, the measuring point is positioned on the reinforcing rib at the bottom of the box body and is affected by the cushioning of the reinforcing rib, so that the sensitivity to fault characteristics is reduced; the test directions of the test points 1 and the test points 7 are in the axial direction of the gearbox, the vibration amplitude is smaller relative to the radial direction of the gear perpendicular to the axial direction of the gearbox, and the test points 1 and 7 are not sensitive to fault vibration characteristics. In sum, the measuring points 5, 4, 3 and 6 can be selected as optimized measuring points, the measuring points 1 and 7 are removed, and the rest measuring points can be used for auxiliary reference.
In summary, the importance ranking after the gearbox vibration measuring point optimization is analyzed and calculated through the three states of virtual experimental simulation data, the three states are representative in the service process of the gearbox, and when the comprehensive ranking degree of other states is calculated, the weighting coefficient lambda value of the three states is far smaller than that of the three states, so that the method and conclusion adopting the three states have certain representativeness.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (2)
1. The planetary gearbox vibration measurement point optimization method based on virtual simulation and LLE is characterized by comprising the following steps of:
establishing a planetary gearbox dynamic model under a working state of a normal working condition: the gear-box rigid-flexible coupling model is formed by two parts, namely a gear multi-rigid-body model and a box flexible-body model, and is coupled through a bearing to form a gear-box rigid-flexible coupling model;
injecting a gear fault: selecting several representative fault states in the service process of the planetary gearbox, and respectively establishing a planetary gearbox dynamic model under the working states of the faults;
primary selection of measuring points: comprehensively considering the internal structure of the planetary gearbox and the installation conditions of the surface sensor of the box body, and selecting a plurality of vibration sensor measuring points in advance in a region with larger vibration response in modal analysis;
using a planetary gearbox dynamic model corresponding to a working state, acquiring vibration simulation signals of all measuring points in the working state and executing first measuring point optimization;
after the optimization of the first measuring points in all the selected working states is completed, the comprehensive ranking of the importance of the vibration measuring points is determined by a weighting calculation method, and the comprehensive ranking of the importance of each measuring point is determined by the following formula:
Pifor measuring the importance comprehensive ranking value of point i, PiThe smaller the value, the stronger the importance, and the more forward the ranking; n represents a certain operating state, and N represents the number of selected operating states，LiArranging sequence values of the measuring points i from large to small in sensitivity under a certain working state; lambda represents a weighting coefficient, which is determined by the importance of each state, and the sum of the weighting coefficients of all selected working states is 1;
selecting 3-8 measuring points with the front comprehensive ranking of importance as optimized measuring points, eliminating 1-3 measuring points which are insensitive to fault vibration characteristics at the tail, and taking the rest measuring points as auxiliary references, thereby completing the optimization of the planetary gearbox vibration measuring points;
wherein the first station optimization comprises:
a) introducing characteristic parameters to evaluate the effectiveness of the measuring points, calculating the corresponding characteristic parameters of the vibration simulation signals of the measuring points, and constructing a measuring point characteristic vector space;
b) reducing the dimension of the characteristic vector space of the measuring points by adopting a local linear embedding algorithm, calculating the 2-norm of the low-dimensional vector of each measuring point after the dimension reduction, and expressing the sensitivity of the measuring point by using the 2-norm of the low-dimensional vector of the measuring point, wherein the higher the 2-norm of the low-dimensional vector of the measuring point is, the more sensitive the measuring point is;
the modeling process of the planetary gearbox dynamic model is as follows:
(1) according to the structure and the transmission principle of the planetary gearbox, the model of the planetary gearbox is reasonably simplified, the three-dimensional model of each part is established by using ProE software, the parts are assembled without interference, and the assembly body is stored in a Paracolid format;
(2) the method comprises the steps of introducing a three-dimensional model of the planetary gearbox by using a ProE interface of ADAMS software, adding a fixed pair to a fixed piece, adding a rotating pair to a rotating piece, adding a collision contact force to a gear pair, adding a rotary drive to a driving shaft, adding a loading torque to an output shaft according to the working condition of each part when the planetary gearbox runs, and establishing a multi-rigid-body dynamic model of a transmission part;
(3) calculating the mode of the box body by using ANSYS software, acquiring a mode neutral file of the box body, and importing the mode neutral file to make a rigid body model of the box body flexible by adopting an ANSYS interface of ADAMS software; coupling a multi-rigid-body dynamic model of a transmission part with a flexible-body model of a box body through a bearing, and finally establishing a rigid-flexible coupling dynamic model of the gear-box body;
the characteristic parameters comprise peak-to-peak value, root mean square value and side value which can measure the energy and intensity of the vibration signal, and kurtosis index, waveform index, peak index, pulse index, margin index and sample entropy which are sensitive to pulse impact.
2. The planetary gearbox vibration measurement point optimization method based on virtual simulation and LLE as claimed in claim 1, wherein: when the local linear embedding algorithm is adopted, the number of neighbor points is taken as 5, and the low-dimensional space dimension is taken as 3.
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