CN113255220B - Gear pump maintenance method based on digital twinning - Google Patents
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Abstract
The disclosure discloses a gear pump maintenance method based on digital twinning, which comprises the following steps: measuring and receiving working condition parameters of the gear pump in real time, calculating the volumetric efficiency and the limiting rotation speed of the gear pump based on the working condition parameters to evaluate the running state of the gear pump and estimate failure, calculating the central positions of a driving gear and a driven gear of the gear pump and the abrasion loss of a friction pair, establishing a pressure pulsation model of the gear pump based on a centralized parameter method in an internal flow field of the gear pump, establishing a digital twin model of the gear pump, and taking the pressure pulsation at the outlet of the gear pump as a monitoring signal for predicting and maintaining the model.
Description
Technical Field
The invention belongs to the field of gear pump operation and maintenance, and particularly relates to a gear pump maintenance method based on digital twinning.
Background
The gear pump has compact structure, small volume, light weight, low price, low sensitivity to oil pollution and good self-absorption performance, and is widely applied to mechanical industries such as electric power, automobiles, metallurgy, military industry, aviation, aerospace, chemical engineering and the like. The most significant failure mode of gear pumps during use is the reduction in volumetric efficiency caused by leakage. Gear pump leaks include internal and external leaks, external leaks being visible to the naked eye and which can be addressed by replacing seals; the leakage causing the reduction of the volume efficiency is mainly internal leakage, is a process that oil in a high-pressure cavity flows to a low-pressure cavity through a friction pair gap, and mainly comprises end surface leakage between a gear end surface and a side plate, radial leakage between a tooth top and a shell and meshing leakage at the meshing position of two gears.
In the past, the fault monitoring and performance degradation research of the gear pump mainly adopts the diagnosis and prediction technology of multi-source signal fusion. However, the early weak fault of the gear pump cannot be well diagnosed and predicted, and meanwhile, the performance degradation of the gear pump cannot be evaluated and predicted in time, so that the pressure and the flow of the whole hydraulic system are insufficient, the overall performance of the system is seriously influenced, and especially when the gear pump is used in an aircraft engine fuel system, the insufficient pressure and the insufficient flow are fatal faults, so that a digital twin model of the gear pump based on physical knowledge is established, the degradation performance and the faults of the gear pump are mirrored in time, and the self vital signs of the gear pump in the life cycle are dynamically reflected. The method has great potential in gear pump fault monitoring and predictive maintenance.
The above information disclosed in this background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is well known to those of ordinary skill in the art.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a gear pump maintenance method based on digital twins.
The purpose of the invention is realized by the following technical scheme.
In one aspect of the invention, a predictive maintenance method based on a digital twin gear pump comprises the following steps:
measuring and receiving gear pump working condition parameters in real time, wherein the working condition parameters comprise working pressureFlow rate ofRotational speed of the motorTorque of the motorAnd temperature;
Calculating volumetric efficiency and limit speed of the gear pump based on the operating condition parameters to assess the operating condition of the gear pump and make a prediction of failure, wherein,,in the formula:is the limit rotation speed;is the working pressure;the dynamic viscosity of the oil is adopted;the clearance between the bearing and the bearing bush;is the bearing radius;is volume efficiency;is the displacement at the working pressure;displacement at no load pressure;is the flow at the working pressure;is the flow at no load pressure;is the rotation speed under the working pressure;is the rotation speed at the no-load pressure,
calculating the central positions of a driving gear and a driven gear of the gear pump and the abrasion loss of a friction pair, wherein the central positions are as follows:
in the formula:is the mass of the gear 1;is the bearing counter force borne by the gear 1;is the pressure to which the gear 1 is subjected;the meshing force applied to the gear;is the moment of inertia of gear 1;is the angle of rotation of gear 1;torque generated by the pressure to which the gear 1 is subjected;torque generated for the motor;is the radius of the meshing point of the gear 1;is the mass of the gear 2;bearing counter force borne by the gear 2;by pressure exerted on gear wheel 2;Is the moment of inertia of gear 2;is the angle of rotation of the gear 2;torque generated by the pressure to which the gear 2 is subjected;is the radius of the meshing point of the gear 2,
the abrasion loss of the friction pair comprises the abrasion loss between the end surface of the gear and the floating shaft sleeve, between the tooth top and the inner wall of the pump shell, the abrasion loss between the end surface of the gear and the floating shaft sleeve determines the size of a gap hf between the end surface of the gear and the floating shaft sleeve, and the abrasion loss between the tooth top and the inner wall of the pump shell determines the size of a gap hi between the pump shell of the gear pump and the tooth top of the gear; the abrasion loss of the friction pair is as follows:,in the formula:the abrasion loss of the friction pair is obtained;the energy consumed for wear on each stroke;the number of strokes;a sliding distance for each stroke;is the wear system constant;the maximum shear force to which the part is subjected;
obtaining a flow rate through the gap based on the pressure differential and the size of the gap, and obtaining a pressure for each chamber based on a relationship between the gap and the flow rate, wherein,
in the formula:is the tooth width;the gear pump rotating speed;is the addendum circle radius;is the tooth height;is the average tooth height;the dynamic viscosity of the oil is adopted;the tooth crest thickness;the tooth thickness of the pitch circle;is as followsA cavity pressure;is as followsIndividual chamber pressure;the tooth crest clearance flow is obtained;is the tooth flank clearance flow;
under adiabatic, isentropic conditions, andthe pressure in the ith control body can be obtained according to the continuity equation:
in the formula:is the bulk modulus of elasticity;the gear pump rotating speed;is the ith control volume;is the gear rotation angle;is the amount of change in the flow in the ith control fluid;the flow rate of the ith +1 th control body flowing into the ith control body through the gap is set;the flow rate of the ith control body flowing out through the gap is measured;
the inlet control body, the isometric control body, the outlet control body and the closed cavity control body are sequentially modeled by utilizing the above formula, so that the pressure of the whole internal flow field is obtained, and the model is as follows:
in the formula:the pressure of the nth chamber of the gear 1;pressure of the mth cavity of the gear 2;the pressure of a sealed cavity of the gear pump;is the gear pump outlet pressure;is the gear pump inlet pressure;
in an external flow field of the gear pump, fourier expansion of a pressure pulsation signal at a measuring point is as follows:
in the formula:is a direct current component;is the fundamental component of the frequency conversion;is a harmonic component of the frequency conversion; n =1 …;is a constant;generating a pressure pulsation signal amplitude for the tooth frequency;is an amplitude modulation coefficient;is a frequency modulation coefficient;is a phase angle;is the tooth frequency; m =1 …;is an amplitude-modulated signal;in order to be a frequency-modulated signal,
and establishing a digital twin model of the gear pump, and taking the outlet pressure pulsation of the gear pump as a monitoring signal of the predictive maintenance model.
In the method, during the expansion of the pressure pulsation signal at the measuring point of the gear pump external flow field, time domain analysis, frequency domain analysis, wavelet analysis, functional analysis or matrix analysis is carried out on the measured data and the simulation data.
In the method, the time domain analysis comprises time domain statistical analysis or correlation analysis, and the frequency domain analysis comprises FFT, coherent analysis, cepstrum analysis or autoregressive spectrum analysis.
In the method, the central positions of the driving gear and the driven gear and the abrasion loss of the friction pair are calculated by solving a differential equation system.
In the method, a differential equation set of pressure pulsation is solved through a Runge-Kutta single-step algorithm of four orders and five orders in an internal flow field of the gear pump.
In the method, in the external flow field of the gear pump, a homogeneous turbulence spectrum analysis method is adopted, energy distribution of vortexes of various scales in turbulence at a measuring point of the gear pump under different working conditions is learned through a neural network, and a basis function coefficient of a heuristic function space is corrected, so that parameters of a pressure pulsation mathematical model are optimized.
In the method, the flow between the gear pump end surface gap and the gear crest gap is equivalent to the Couett-Poiseuille flow between the flat plates, and the flow passing through the gap is as follows:
in the formula:is the tooth width;the gear pump rotating speed;is the addendum circle radius;is the tooth height;is the average tooth height;the dynamic viscosity of the oil is adopted;the tooth crest thickness;the tooth thickness at the pitch circle;is as followsA cavity pressure;is a firstIndividual chamber pressure;the tooth top gap flow is measured;is the tooth flank clearance flow.
The above description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly apparent, and to make the implementation of the content of the description possible for those skilled in the art, and to make the above and other objects, features and advantages of the present invention more obvious, the following description is given by way of example of the specific embodiments of the present invention.
Drawings
Various other advantages and benefits of the present invention will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. It is obvious that the drawings described below are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. Also, like parts are designated with like reference numerals throughout the drawings.
In the drawings:
FIG. 1 is a schematic step diagram of a digital twin gear pump based predictive maintenance method according to one embodiment of the present invention;
FIG. 2 is a schematic diagram of a human-machine interaction control screen based on a digital twin gear pump predictive maintenance method according to one embodiment of the invention;
FIG. 3 is a time domain diagram of pressure pulsation based on a digital twin gear pump predictive maintenance method according to one embodiment of the invention;
FIG. 4 is a frequency domain plot of pressure pulsations for a digital twin gear pump based predictive maintenance method in accordance with one embodiment of the present invention.
The invention is further explained below with reference to the figures and examples.
Detailed Description
Specific embodiments of the present invention will be described in more detail below with reference to the accompanying drawings fig. 1 to 4. While specific embodiments of the invention are shown in the drawings, it should be understood that the invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
It should be noted that certain terms are used throughout the description and claims to refer to particular components. As one skilled in the art will appreciate, various names may be used to refer to a component. This specification and claims do not intend to distinguish between components that differ in name but not function. In the following description and in the claims, the terms "include" and "comprise" are used in an open-ended fashion, and thus should be interpreted to mean "include, but not limited to. The description which follows is a preferred embodiment of the invention, but is made for the purpose of illustrating the general principles of the invention and not for the purpose of limiting the scope of the invention. The scope of the present invention is defined by the appended claims.
For the purpose of facilitating understanding of the embodiments of the present invention, the following description will be made by taking specific embodiments as examples with reference to the accompanying drawings, and the drawings are not to be construed as limiting the embodiments of the present invention.
For better understanding, fig. 1 is a schematic diagram of a digital twin based gear pump predictive maintenance, and as shown in fig. 1, a digital twin based gear pump maintenance method comprises the following steps:
measuring and receiving gear pump working condition parameters in real time, wherein the working condition parameters comprise working pressureFlow rate ofRotational speed of the motorTorque of the motorTemperature of;
Calculating volumetric efficiency and limit speed of the gear pump based on the operating condition parameters to assess the operating condition of the gear pump and make a prediction of failure, wherein,,in the formula:is the limit rotation speed;is the working pressure;the dynamic viscosity of the oil is adopted;the clearance between the bearing and the bearing bush;is the bearing radius;is volume efficiency;displacement at operating pressure;displacement at no load pressure;is the flow at the working pressure;is the flow at no load pressure;is the rotation speed under the working pressure;is the rotation speed at the no-load pressure,
calculating the central positions of a driving gear and a driven gear of the gear pump and the abrasion loss of a friction pair, wherein the central positions are as follows:
in the formula:is the mass of the gear 1;bearing counter force borne by the gear 1;is the pressure to which the gear 1 is subjected;the meshing force applied to the gear;is the moment of inertia of gear 1;is the angle of rotation of the gear 1;torque generated by the pressure to which the gear 1 is subjected;torque generated for the motor;is the radius of the meshing point of the gear 1;is the mass of the gear 2;is the bearing counter force borne by the gear 2;is the pressure to which the gear 2 is subjected;is the moment of inertia of gear 2;is the angle of rotation of the gear 2;torque generated by the pressure to which the gear 2 is subjected;is the radius of the meshing point of the gear 2,
the friction pair abrasion loss comprises abrasion between the end face of the gear and the inner walls of the floating shaft sleeve, the tooth top and the pump shell, and the friction pair abrasion loss is as follows:,
in the formula:the abrasion loss of the friction pair is obtained;the energy consumed for wear on each stroke;the number of strokes;a sliding distance for each stroke;is the wear system constant;the maximum shear force to which the part is subjected;
in the internal flow field of the gear pump, a gear pump pressure pulsation model is established based on a centralized parameter method, an inlet control body, an isovolumetric control body, an outlet control body and a closed cavity control body are respectively modeled,
in the formula:the pressure of the nth chamber of the gear 1;pressure of the mth cavity of the gear 2;the pressure of a sealed cavity of the gear pump;is the gear pump outlet pressure;is the gear pump inlet pressure;
in the gear pump external flow field, the Fourier expansion of the pressure pulsation signal at the measuring point is as follows:
in the formula:is a direct current component;is the fundamental component of the frequency conversion;is a harmonic component of the frequency conversion; n =1 …;is a constant;generating a pressure pulsation signal amplitude for the tooth frequency;is an amplitude modulation coefficient;is a frequency modulation coefficient;is a phase angle;is the tooth frequency; m =1 …;is an amplitude-modulated signal;is a frequency modulated signal.
In a preferred embodiment of the method, time domain analysis, frequency domain analysis, wavelet analysis, functional analysis or matrix analysis is performed on the measured data and the simulated data.
In a preferred embodiment of the method, the time domain analysis comprises time domain statistical analysis or correlation analysis, and the frequency domain analysis comprises FFT, coherence analysis, cepstral analysis or autoregressive spectral analysis.
In the preferred embodiment of the method, the central positions of the driving gear and the driven gear and the abrasion amount of the friction pair are calculated by solving a differential equation system.
In the preferred embodiment of the method, the system of differential equations for the pressure pulsations is solved by the ODE45 in the gear pump internal flow field.
In the preferred embodiment of the method, in the external flow field of the gear pump, a homogeneous turbulence spectrum analysis method is adopted, and the energy distribution of various scale vortexes in turbulence at the measuring point of the gear pump under different working conditions is learned through a neural network, so that the basis function coefficient of a tentative function space is corrected, and the parameters of the pressure pulsation mathematical model are optimized.
In one embodiment, a digital twin based gear pump maintenance method comprises:
constructing a working condition parameter updating module, wherein pressure is respectively obtained by a pressure sensor, a flow sensor, a rotating speed-torque sensor and a temperature sensor which are arranged on a physical experiment tableFlow rate ofRotational speed of the motorTorque of the motorTemperature ofAnd the like.
Constructing a state evaluation module, wherein the volumetric efficiency of the gear pump is calculated according to the actually measured flow of the flow sensorAnd through between pressure and speedExpression to obtain the limit speedAnd the gear pump operation can be guided.
Constructing a model dynamic parameter calculation module, wherein a dynamic model of the gear pump is established, and the central positions of the driving gear and the driven gear are calculated by solving a differential equation set; the gear pump tooth crest and end surface abrasion mainly refers to abrasive wear, tooth crest and end surface abrasion amount is obtained according to an abrasion amount calculation formula and through combination of experimental measurement, and basic parameters of the gear pump are shown in table 1.
TABLE 1
And constructing a gear pump internal flow field module, wherein a gear pump control body pressure pulsation equation set is established by adopting a centralized parameter method, the flow of tooth tops and end surfaces is assumed to be laminar flow between plates in the model, the influence of turbulent flow is considered by an inlet, an outlet and a closed cavity control body, and then a differential equation set of pressure pulsation is solved through ODE45 to obtain a pressure pulsation value in each control body.
And constructing a gear pump outflowing flow field module, wherein a homogeneous turbulence spectrum analysis method is adopted, pressure pulsation at a measuring point is approximately considered to be a stable random process, and the pressure pulsation is considered to be the superposition of vortexes with various different scales, and the energy distribution of the vortexes with various different scales in turbulence at the measuring point of the gear pump under different working conditions is learned through a neural network to correct a basis function coefficient of a heuristic function space, so that parameters of a pressure pulsation mathematical model are optimized.
And constructing a physical entity model, wherein a gear pump performance test bench is constructed by referring to the requirements on the gear pump performance test.
FIG. 2 is a schematic diagram of a human-computer interaction interface based on a predictive maintenance method of a digital twin gear pump, as shown in FIG. 2, and a working condition parameter module on the interface constantly reflects the operating pressure of the gear pumpFlow rate ofRotational speed of the motorTemperature ofThe like; the performance evaluation module mainly displays volumetric efficiency of the gear pumpLimit rotation speedThe total working time h and the volumetric efficiency make a prediction evaluation on the failure of the gear pump, and the minimum rotating speed mainly prompts an operator to the minimum rotating speed at which the lubricating oil film of the gear pump bearing is damaged and abraded under a certain load, for example, when the load is 14MPa, the minimum rotating speed is 2000r/min, so that the abrasion of the gear pump bearing is reduced by increasing the rotating speed or reducing the load; the characteristic signal module mainly displays the information of the selected characteristic signals, such as pressure pulsation signals, flow signals, vibration signals and the like, and the change information of the characteristic signals can reflect the performance degradation and the occurrence of faults of the gear pump.
FIG. 3 is a time domain diagram of the characteristic signal pressure pulsation based on the digital twin gear pump predictive maintenance method according to the present invention, in the experiment, the gear pump rotation speed is 2466.6r/min, the load is 10MPa, the temperature is 22 ℃, and the flow rate is 9866.4mL/min. The figure shows that the obvious periodic fluctuation of the pressure pulsation signal is mainly caused by the periodic motion of the gear pump, and 12 small fluctuations are included in a large fluctuation, wherein the small fluctuation represents outlet pressure pulsation caused by oil removal when one tooth is rotated, and the large fluctuation represents pulsation caused by periodic change of leakage when the gear pump rotates for one circle. The amplitude of the pulsation is influenced by the rotating speed and the outlet pressure, and if the pulsation is worn and broken, the leakage amount is increased, so that the influence factor of large fluctuation is increased.
FIG. 4 is a frequency domain graph of characteristic signal pressure pulsation based on the digital twin gear pump predictive maintenance method according to the present invention, in the experiment, the gear pump rotational speed is 2466.6r/min, the load is 10MPa, the temperature is 22 ℃, and the flow rate is 9866.4mL/min. The figure shows that obvious periodic fluctuation components of the pressure pulsation signal mainly comprise gear rotating frequency, gear pump meshing frequency (tooth frequency) and frequency multiplication of the tooth frequency. The frequency conversion component is influenced most obviously by the rotating speed, the proportion of the frequency conversion component is gradually smaller along with the increase of the rotating speed, the tooth frequency gradually becomes the main pulse frequency, but the absolute amplitude of the frequency conversion basically keeps unchanged, the relative amplitude changes obviously, and the frequency conversion is reflected in a frequency domain graph to modulate the tooth frequency.
The method establishes a digital twin model of the gear pump, and takes the outlet pressure pulsation of the gear pump as a monitoring signal of a predictive maintenance model. Firstly, establishing a pressure pulsation model of an internal flow field of the gear pump by adopting a centralized parameter method to obtain the pressure in each control body inside the gear pump; secondly, a local homogeneous turbulence pulsation model is established for the position of a pressure sensor measuring point on an outlet pipeline of the gear pump, a mathematical model of pressure pulsation at the measuring point is obtained by adopting a homogeneous turbulence spectrum analysis method, energy distribution of various scale vortexes in turbulence at the measuring point of the gear pump under different working conditions is learned through a neural network, a basis function coefficient of a heuristic function space is corrected, high-fidelity simulation of the virtual model on a physical entity model is realized, and meanwhile, the virtual model makes an instructive strategy on the operation condition of the physical entity by calculating the volumetric efficiency and the limit rotating speed of the gear pump. By adopting the method, the real-time interaction between the gear pump virtual model and the physical entity can be realized, so that the composition of turbulence at the outlet measuring point of the gear pump is disclosed, and a new thought is provided for the performance monitoring and maintenance of the gear pump.
Although the embodiments of the present disclosure are described above with reference to the drawings, the embodiments of the present disclosure are not limited to two operating conditions of different rotation speeds and different loads, and may also include other kinds of operating conditions. The particular embodiments disclosed above are illustrative and explanatory only and are not restrictive. Those skilled in the art, having the benefit of this disclosure, may effect numerous modifications thereto and changes may be made without departing from the scope of the disclosure as set forth in the claims that follow.
Claims (6)
1. A method of digital twinning based gear pump maintenance, the method comprising the steps of:
measuring and receiving gear pump working condition parameters in real time, wherein the working condition parameters comprise working pressureFlow rate ofRotational speed, torqueAnd temperature;
Calculating volumetric efficiency and limit speed of the gear pump based on the operating condition parameters to assess the operating condition of the gear pump and make a prediction of failure, wherein,
, in the formula:is the limit rotation speed;is the working pressure;the dynamic viscosity of the oil is adopted;the clearance between the bearing and the bearing bush;is the bearing radius;is volume efficiency;is the displacement at the working pressure;displacement at no load pressure;is the flow at the working pressure;is composed ofFlow at no load pressure;is the rotation speed under the working pressure;is the rotation speed at the no-load pressure,
calculating the central positions of a driving gear and a driven gear of the gear pump and the abrasion loss of a friction pair, wherein the central positions are as follows: ,
in the formula:is the mass of the gear 1;the component of the bearing reaction force borne by the gear 1 in the direction of the x axis is formed;the component force of the pressure applied on the gear 1 in the direction of the x axis;the component of the bearing reaction force borne by the gear 1 in the y-axis direction;the component of the pressure applied on the gear 1 in the y-axis direction;the gear is subjected to meshing force;is the moment of inertia of gear 1;is the angle of rotation of the gear 1;torque generated by the pressure to which the gear 1 is subjected;torque generated for the motor;the radius of the meshing point of the gear 1;is the mass of the gear 2;the component of the bearing reaction force borne by the gear 2 in the direction of the x axis;the component force of the pressure applied on the gear 2 in the direction of the x axis;the component of the bearing reaction force borne by the gear 2 in the y-axis direction;the component of the pressure applied to the gear 2 in the y-axis direction;is the moment of inertia of gear 2;is the angle of rotation of the gear 2;torque generated by the pressure to which the gear 2 is subjected;is the radius of the meshing point of the gear 2,
the abrasion loss of the friction pair comprises the abrasion loss between the end face of the gear and the floating shaft sleeve, between the tooth top and the inner wall of the pump shell, and the abrasion loss between the end face of the gear and the floating shaft sleeve determines the clearance between the end face of the gear and the floating shaft sleeveThe abrasion amount between the tooth crest and the inner wall of the pump shell determines the space between the pump shell and the tooth crest of the gear teeth of the gear pumpGapThe size of (d); the abrasion loss of the friction pair is as follows:, in the formula:the abrasion loss of the friction pair is obtained;the energy consumed for wear on each stroke;the number of strokes;a sliding distance for each stroke;is the wear system constant;the maximum shear force to which the part is subjected;
the flow between the tooth flank clearance and the tooth crest clearance is equivalent to couette-poisson flow between the plates, and the flow through the clearance is obtained according to the pressure difference and the size of the clearance, wherein,
in the formula:is the tooth width;the gear pump rotating speed;is the addendum circle radius;is the tooth height;is the average tooth height;the dynamic viscosity of the oil is adopted;the tooth crest thickness;the tooth thickness of the pitch circle;is as followsA cavity pressure;is a firstIndividual chamber pressures;the tooth top gap flow is measured;is the tooth flank clearance flow;
under adiabatic, isentropic conditions, andthe pressure in the ith control body can be obtained according to the continuity equation:
in the formula:is the bulk modulus of elasticity;the gear pump rotating speed;is the ith control volume;is the gear rotation angle;is the amount of change in the flow in the ith control fluid;for the flow rate of the (i + 1) th control body flowing into the ith control body through the gap;The flow rate of the ith control body flowing out through the gap is measured;
modeling an inlet control body, an equal-volume control body, an outlet control body and a closed cavity control body in sequence by using the above formula so as to obtain the pressure of the whole internal flow field, wherein the model is as follows:
in the formula:the pressure of the nth tooth chamber of the gear 1;the pressure of the mth tooth chamber of the gear 2;the pressure of a sealed cavity of the gear pump;is the gear pump outlet pressure;is the gear pump inlet pressure;
pressure pulsation signal P at measuring point in external flow field of gear pump out The Fourier expansion of (t) is:
in the formula: when n =1, the ratio of n to n is set to 1,is the fundamental component of the frequency conversion;is a harmonic component of the frequency conversion; n =1 …;is the frequency conversion;generating a pressure pulsation signal amplitude for frequency conversion;is a constant;generating a pressure pulsation signal amplitude for the tooth frequency;is the amplitude modulation coefficient;is a frequency modulation coefficient;is a phase angle;is the tooth frequency; m =1 …;is an amplitude-modulated signal;in order to be a frequency-modulated signal,
and establishing a digital twin model of the gear pump, and taking the outlet pressure pulsation of the gear pump as a monitoring signal of the predictive maintenance model.
2. The method of claim 1, wherein the time domain analysis, frequency domain analysis, wavelet analysis, functional analysis, or matrix analysis is performed on the measured data and the simulated data during the expansion of the pressure pulsation signal at the test point of the gear pump external flow field.
3. The method of claim 2, wherein the time domain analysis comprises time domain statistical analysis or correlation analysis, and the frequency domain analysis comprises FFT, coherence analysis, cepstral analysis, or autoregressive spectral analysis.
4. The method of claim 1, wherein the center positions of the driving and driven gears and the amount of wear of the friction pair are calculated by solving a system of differential equations.
5. The method as set forth in claim 1, wherein the differential equation set of the pressure pulsation is solved by a four-order, five-order Runge-Kutta one-step algorithm in the gear pump internal flow field.
6. The method as claimed in claim 1, wherein in the gear pump external flow field, a homogeneous turbulence spectrum analysis method is adopted to learn the energy distribution of various scale vortexes in turbulence at the gear pump measuring point under different working conditions through a neural network, so as to modify the basis function coefficient of a heuristic function space, thereby optimizing the parameters of the pressure pulsation mathematical model.
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