CN113255220A - Gear pump maintenance method based on digital twinning - Google Patents
Gear pump maintenance method based on digital twinning Download PDFInfo
- Publication number
- CN113255220A CN113255220A CN202110605998.8A CN202110605998A CN113255220A CN 113255220 A CN113255220 A CN 113255220A CN 202110605998 A CN202110605998 A CN 202110605998A CN 113255220 A CN113255220 A CN 113255220A
- Authority
- CN
- China
- Prior art keywords
- gear
- gear pump
- pressure
- tooth
- flow
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
- F04B51/00—Testing machines, pumps, or pumping installations
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04C—ROTARY-PISTON, OR OSCILLATING-PISTON, POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; ROTARY-PISTON, OR OSCILLATING-PISTON, POSITIVE-DISPLACEMENT PUMPS
- F04C2/00—Rotary-piston machines or pumps
- F04C2/08—Rotary-piston machines or pumps of intermeshing-engagement type, i.e. with engagement of co-operating members similar to that of toothed gearing
- F04C2/12—Rotary-piston machines or pumps of intermeshing-engagement type, i.e. with engagement of co-operating members similar to that of toothed gearing of other than internal-axis type
- F04C2/14—Rotary-piston machines or pumps of intermeshing-engagement type, i.e. with engagement of co-operating members similar to that of toothed gearing of other than internal-axis type with toothed rotary pistons
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/28—Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/08—Fluids
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/08—Thermal analysis or thermal optimisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Computation (AREA)
- General Physics & Mathematics (AREA)
- Computing Systems (AREA)
- Software Systems (AREA)
- Artificial Intelligence (AREA)
- Mathematical Physics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biophysics (AREA)
- Geometry (AREA)
- Molecular Biology (AREA)
- General Health & Medical Sciences (AREA)
- Mechanical Engineering (AREA)
- Data Mining & Analysis (AREA)
- Computational Linguistics (AREA)
- Computer Hardware Design (AREA)
- Biomedical Technology (AREA)
- Health & Medical Sciences (AREA)
- Algebra (AREA)
- Fluid Mechanics (AREA)
- Medical Informatics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Rotary Pumps (AREA)
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 limit rotating speed of the gear pump based on the working condition parameters to evaluate the running state of the gear pump and predict 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 gear pump pressure pulsation model 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 outlet pressure pulsation 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 already known in this country to a person 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 working condition parameters of the gear pump in real time, wherein the working condition parameters comprise working pressure p, flow Q, rotating speed n and torque MpAnd a temperature T;
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: omegaminIs the limit rotation speed; p is the working pressure; mu is the dynamic viscosity of the oil liquid; c is the clearance between the bearing and the bearing bush; raIs the bearing radius; etaVIs volume efficiency; v2,eIs the displacement at the working pressure; v2,iDisplacement at no load pressure; q. q.sV2,eIs the flow at the working pressure; q. q.sV2,IIs the flow at no load pressure; n iseIs the rotation speed under the working pressure; n isiIs 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: m is1Is the mass of the gear 1; f. ofb1Is the bearing counter force borne by the gear 1; f. ofp1Is the pressure to which the gear 1 is subjected; f. ofmgThe meshing force applied to the gear; j. the design is a square1Is the moment of inertia of gear 1; theta1Is the angle of rotation of the gear 1; mp1Torque generated by the pressure to which the gear 1 is subjected; mmTorque generated for the motor; r isb1Is the radius of the meshing point of the gear 1; m is2Is the mass of the gear 2; f. ofb2Is the bearing counter force borne by the gear 2; f. ofp2Is the pressure to which the gear 2 is subjected; j. the design is a square2Is the moment of inertia of gear 2; theta2Is the angle of rotation of the gear 2; mp2Torque generated by the pressure to which the gear 2 is subjected; r isb2Is the radius of the meshing point of the gear 2,
the wear amount of the friction pair comprises the end face of the gear and the floatingThe abrasion loss among the movable shaft sleeve, 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 determine 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 determine 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: q is the abrasion loss of the friction pair; e is the energy consumed by wear per stroke; n is the number of strokes; s is the sliding distance of each stroke; c is the wear system constant; tau ismaxThe 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: b is the tooth width; omega is the gear pump rotating speed; r isextIs the addendum circle radius; bfIs the tooth height; r ismIs the average tooth height; mu is dynamic viscosity of oil liquid; ltThe tooth crest thickness; lfThe tooth thickness of the pitch circle; p is a radical ofiIs the ith chamber pressure; p is a radical ofi-1Is the i-1 th chamber pressure; qh,iThe tooth crest clearance flow is obtained; qf,iIs the tooth flank clearance flow;
under adiabatic, isentropic conditions, and pi+1>piThe pressure in the ith control body can be obtained according to the continuity equation:
ΔQi=Qi+1-Qi,
in the formula: b isoilIs the bulk modulus of elasticity; omega is the gear pump rotating speed; viIs the ith control volume; theta is a gear rotation angle; delta QiIs the amount of change in the flow in the ith control fluid; qi+1The flow rate of the ith +1 th control body flowing into the ith control body through the gap is set; qiThe 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, and obtaining the pressure of the whole internal flow field by using M, wherein the model is as follows:
in the formula: p is a radical ofn(θ)|1The pressure of the nth chamber of the gear 1; p is a radical ofm(θ)|2Pressure of the mth cavity of the gear 2; p is a radical oft(theta) is the pressure of the gear pump sealed cavity; p is a radical ofout(θ) is gear pump outlet pressure; p is a radical ofin(θ) is 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: a. theoLIs a direct current component; a. the1Lcos(ωoLt+ψ1) Is the fundamental component of the frequency conversion; n is not less than 2, AnLcos(nωoLt+ψn) Is a harmonic component of the frequency conversion; n-1 … 6; a. theoHIs a constant; a. themHGenerating a pressure pulsation signal amplitude for the tooth frequency; k is a radical ofamIs an amplitude modulation coefficient; k is a radical offmIs a frequency modulation coefficient; zetamIs a phase angle; omegaoHIs the tooth frequency; m is 1 … 6; p'outL(t) is an amplitude modulated signal; p ″)outL(t) is 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 four-order and five-order Runge-Kutta single-step algorithm 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: b is the tooth width; omega is the gear pump rotating speed; r isextIs the addendum circle radius; bfIs the tooth height; r ismIs the average tooth height; mu is dynamic viscosity of oil liquid; ltThe tooth crest thickness; lfThe tooth thickness of the pitch circle; p is a radical ofiIs the ith chamber pressure; p is a radical ofi-1Is the i-1 th chamber pressure; qh,iThe tooth crest clearance flow is obtained; qf,iIs the 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 by 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 present 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 working condition parameters of the gear pump in real time, wherein the working condition parameters comprise working pressure p, flow Q, rotating speed n and torque MpThe temperature T;
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: omegaminIs the limit rotation speed; p is the working pressure; mu is the dynamic viscosity of the oil liquid; c is the clearance between the bearing and the bearing bush; raIs the bearing radius; etaVIs volume efficiency; v2,eIs the displacement at the working pressure; v2,iDisplacement at no load pressure; q. q.sV2,eIs the flow at the working pressure; q. q.sV2,IIs the flow at no load pressure; n iseIs the rotation speed under the working pressure; n isiIs 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: m is1Is the mass of the gear 1; f. ofb1Is the bearing counter force borne by the gear 1; f. ofp1Is the pressure to which the gear 1 is subjected; f. ofmgThe meshing force applied to the gear; j. the design is a square1Is the moment of inertia of gear 1; theta1Is the angle of rotation of the gear 1; mp1Torque generated by the pressure to which the gear 1 is subjected; mmTorque generated for the motor; r isb1Is the radius of the meshing point of the gear 1; m is2Is the mass of the gear 2; f. ofb2Is the bearing counter force borne by the gear 2; f. ofp2Is the pressure to which the gear 2 is subjected; j. the design is a square2Is the moment of inertia of gear 2; theta2Is the angle of rotation of the gear 2; mp2Torque generated by the pressure to which the gear 2 is subjected; r isb2Is the radius of the meshing point of the gear 2,
the abrasion loss of the friction pair comprises abrasion among the gear end, the floating shaft sleeve, the tooth top and the inner wall of the pump shell, and the abrasion loss of the friction pair is as follows:
in the formula: q is the abrasion loss of the friction pair; e is the energy consumed by wear per stroke; n is the number of strokes; s is the sliding distance of each stroke; c is the wear system constant; tau ismaxThe 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 isometric control body, an outlet control body and a closed cavity control body are respectively modeled,
in the formula: p is a radical ofn(θ)|1The pressure of the nth chamber of the gear 1; p is a radical ofm(θ)|2Pressure of the mth cavity of the gear 2; p is a radical oft(theta) is the pressure of the gear pump sealed cavity; p is a radical ofout(θ) is gear pump outlet pressure; p is a radical ofin(θ) is 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: a. theoLIs a direct current component; a. the1Lcos(ωoLt+ψ1) Is the fundamental component of the frequency conversion; n is not less than 2, AnL cos(nωoLt+ψn) Is a harmonic component of the frequency conversion; n-1 … 6; a. theoHIs a constant; a. themHGenerating a pressure pulsation signal amplitude for the tooth frequency; k is a radical ofamIs an amplitude modulation coefficient; k is a radical offmIs a frequency modulation coefficient; zetamIs a phase angle; omegaoHIs the tooth frequency; m is 1 … 6; p'outL(t) is an amplitude modulated signal; p ″)outLAnd (t) 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 simulation 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 differential equation system of the pressure pulsation is solved by ODE45 in the gear pump internal flow field.
In the preferred embodiment of the method, in the gear pump external flow field, a homogeneous turbulence spectrum analysis method is adopted, and 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, so that a basis function coefficient of a tentative function space is corrected, and parameters of a 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 the pressure sensor, the flow sensor and the rotating speed-torque sensor are arranged on the physical experiment table, and the temperature sensor respectively obtains the pressure p, the flow Q, the rotating speed n and the torque MpTemperature T, etc.
Constructing a state evaluation module, wherein the volumetric efficiency eta of the gear pump is calculated according to the actually measured flow of the flow sensorVAnd obtaining the limit rotation speed omega by an expression between the pressure and the rotation speedminAnd 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 (2) 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 the differential equation set of pressure pulsation is solved through ODE45 to obtain the 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 module, wherein a gear pump performance test bench is constructed according to the requirements of the gear pump performance test with reference to national standards.
FIG. 2 is a schematic diagram of a human-computer interaction interface based on the digital twin gear pump prediction maintenance method, as shown in FIG. 2, a working condition parameter module on the interface constantly reflects parameters such as pressure p, flow Q, rotating speed n, temperature T and the like of the operation of the gear pump; the performance evaluation module mainly displays the volumetric efficiency eta of the gear pumpVLimit rotation speed omegaminThe 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 graph of characteristic signal pressure pulsation based on the digital twin gear pump predictive maintenance method according to the present invention, in which the gear pump speed was 2466.6r/min, the load was 10MPa, the temperature was 22 ℃, and the flow rate was 9866.4 mL/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 plot of the characteristic signal pressure pulsation of the predictive maintenance method based on the digital twin gear pump according to the present invention, the gear pump speed was 2466.6r/min, the load was 10MPa, the temperature was 22 deg.C, and the flow rate was 9866.4mL/min during the experiment. 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 technical solutions of the present disclosure are not limited to two operating conditions of different rotation speeds and different loads, and 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 (7)
1. A method of digital twinning based gear pump maintenance, the method comprising the steps of:
measuring and receiving working condition parameters of the gear pump in real time, wherein the working condition parameters comprise working pressure p, flow Q, rotating speed n and torque MpAnd a temperature T;
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: omegaminIs the limit rotation speed; p is the working pressure; mu is the dynamic viscosity of the oil liquid; c is the clearance between the bearing and the bearing bush; raIs the bearing radius; etaVIs volume efficiency; v2,eIs the displacement at the working pressure; v2,iDisplacement at no load pressure; q. q.sV2,eIs the flow at the working pressure; q. q.sV2,IIs the flow at no load pressure; n iseIs the rotation speed under the working pressure; n isiIs 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: m is1Is the mass of the gear 1; f. ofbx1The component of the bearing reaction force borne by the gear 1 in the direction of the x axis; f. ofpx1The component force of the pressure applied on the gear 1 in the direction of the x axis; f. ofby1The component of the bearing reaction force borne by the gear 1 in the y-axis direction; f. ofpy1The component force of the pressure applied on the gear 1 in the y-axis direction; f. ofmgThe meshing force applied to the gear; j. the design is a square1Is the moment of inertia of gear 1; theta1Is the angle of rotation of the gear 1; mp1Torque generated by the pressure to which the gear 1 is subjected; mmTorque generated for the motor; r isb1Is the radius of the meshing point of the gear 1; m is2Is the mass of the gear 2; f. ofbx2The component of the bearing reaction force borne by the gear 2 in the direction of the x axis; f. ofpx2The component force of the pressure applied on the gear 2 in the direction of the x axis; f. ofby2The component of the bearing reaction force borne by the gear 2 in the y-axis direction; f. ofpy2The component force of the pressure applied on the gear 2 in the y-axis direction; j. the design is a square2Is the moment of inertia of gear 2; theta2Is the angle of rotation of the gear 2; mp2Torque generated by the pressure to which the gear 2 is subjected; r isb2Is 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 h between the end face of the gear and the floating shaft sleevefThe abrasion amount between the tooth top and the inner wall of the pump shell determines the clearance h between the gear pump shell and the tooth top of the gear teethiThe size of (d); the abrasion loss of the friction pair is as follows:in the formula: q is the abrasion loss of the friction pair; e is the energy consumed by wear per stroke; n is the number of strokes; s is the sliding distance of each stroke; c is the wear system constant; tau ismaxThe maximum shear force to which the part is subjected;
the flow through the gap is obtained from the pressure difference and the size of the gap, wherein,
in the formula: b is the tooth width; omega is the gear pump rotating speed; r isextIs the addendum circle radius; bfIs the tooth height; r ismIs the average tooth height; mu is dynamic viscosity of oil liquid; ltThe tooth crest thickness; lfThe tooth thickness of the pitch circle; p is a radical ofiIs the ith chamber pressure; p is a radical ofi-1Is the i-1 th chamber pressure; qh,iThe tooth crest clearance flow is obtained; qf,iIs the tooth flank clearance flow;
under adiabatic, isentropic conditions, and pi+1>piThe pressure in the ith control body can be obtained according to the continuity equation:
ΔQi=Qi+1-Qi,
in the formula: b isoilIs the bulk modulus of elasticity; omega is the gear pump rotating speed; viIs the ith control volume; theta is a gear rotation angle; delta QiIs the amount of change in the flow in the ith control fluid; qi+1The flow rate of the ith +1 th control body flowing into the ith control body through the gap is set; qiThe 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: p is a radical ofn(θ)|1The pressure of the nth tooth chamber of the gear 1; p is a radical ofm(θ)|2The pressure of the mth tooth chamber of the gear 2; p is a radical oft(theta) is the pressure of the gear pump sealed cavity; p is a radical ofout(θ) is gear pump outlet pressure; p is a radical ofin(θ) is 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: a. the1Lcos(ωoLt+ψ1) Is the fundamental component of the frequency conversion; n is not less than 2, AnLcos(nωoLt+ψn) Is a harmonic component of the frequency conversion; n-1 … 6; omegaoLIs the frequency conversion; a. thenLGenerating a pressure pulsation signal amplitude for frequency conversion; c is a constant; a. themHGenerating a pressure pulsation signal amplitude for the tooth frequency; k is a radical ofamIs an amplitude modulation coefficient; k is a radical offmIs a frequency modulation coefficient; zetam,ψnIs a phase angle; omegaoHIs the tooth frequency; m is 1 … 6; p'outL(t) is an amplitude modulated signal; p ″)outL(t) is 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 according to claim 1, characterized in that preferably, the measured data and the simulation data are subjected to time domain analysis, frequency domain analysis, wavelet analysis, functional analysis or matrix analysis during the expansion of the pressure pulsation signal at the measurement point of the external flow field of the gear pump.
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.
7. The method of claim 1 wherein the flow between the gear pump face clearance and the tip clearance is equivalent to couette-poiseuille flow between the plates, the flow through the clearance being:
in the formula: b is the tooth width; omega is the gear pump rotating speed; r isextIs the addendum circle radius; bfIs the tooth height; r ismIs the average tooth height; mu is dynamic viscosity of oil liquid; ltThe tooth crest thickness; lfThe tooth thickness of the pitch circle; p is a radical ofiIs the ith chamber pressure; p is a radical ofi-1Is the i-1 th chamber pressure; qh,iThe tooth crest clearance flow is obtained; qf,iIs the flank clearance flow.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110605998.8A CN113255220B (en) | 2021-05-31 | 2021-05-31 | Gear pump maintenance method based on digital twinning |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110605998.8A CN113255220B (en) | 2021-05-31 | 2021-05-31 | Gear pump maintenance method based on digital twinning |
Publications (2)
Publication Number | Publication Date |
---|---|
CN113255220A true CN113255220A (en) | 2021-08-13 |
CN113255220B CN113255220B (en) | 2022-12-06 |
Family
ID=77185581
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110605998.8A Active CN113255220B (en) | 2021-05-31 | 2021-05-31 | Gear pump maintenance method based on digital twinning |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113255220B (en) |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113868837A (en) * | 2021-09-03 | 2021-12-31 | 中国核电工程有限公司 | On-line monitoring method for concrete volute pump wall surface abrasion |
CN114154360A (en) * | 2021-10-19 | 2022-03-08 | 徐州圣邦机械有限公司 | Multi-physical-field probability digital twin modeling method for high-pressure internal gear pump |
CN114491960A (en) * | 2021-12-29 | 2022-05-13 | 徐州圣邦机械有限公司 | Wear monitoring method for high-pressure internal gear pump |
CN114918976A (en) * | 2022-06-16 | 2022-08-19 | 慧之安信息技术股份有限公司 | Joint robot health state assessment method based on digital twinning technology |
CN115539378A (en) * | 2022-11-23 | 2022-12-30 | 中汽信息科技(天津)有限公司 | Fault diagnosis method, device and medium for hydraulic gear pump of automobile production line |
Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101413521A (en) * | 2008-11-28 | 2009-04-22 | 西安建筑科技大学 | Experimental apparatus and method for obtaining multi-source diagnostic information of hydraulic equipment |
CN109116751A (en) * | 2018-07-24 | 2019-01-01 | 西安西电电气研究院有限责任公司 | Digitization system and its construction method based on the twin technology of number |
US20190090840A1 (en) * | 2017-09-28 | 2019-03-28 | General Electric Company | X-ray tube bearing failure prediction using digital twin analytics |
CN110532625A (en) * | 2019-07-31 | 2019-12-03 | 西安交通大学 | Aero-engine turbine disk-twin the modeling method of rotor-bearing system number |
US20200103894A1 (en) * | 2018-05-07 | 2020-04-02 | Strong Force Iot Portfolio 2016, Llc | Methods and systems for data collection, learning, and streaming of machine signals for computerized maintenance management system using the industrial internet of things |
CN111365232A (en) * | 2020-03-27 | 2020-07-03 | 武汉理工大学 | Gear pump experiment platform and gear damage detection method |
US20200265329A1 (en) * | 2019-02-14 | 2020-08-20 | Rockwell Automation Technologies, Inc. | Ai extensions and intelligent model validation for an industrial digital twin |
AU2020102819A4 (en) * | 2020-10-16 | 2020-12-10 | Beihang University | Digital-twin-driven method and system for fault diagnosis of subsea production system of offshore oil |
US20210056244A1 (en) * | 2019-02-25 | 2021-02-25 | Dalian University Of Technology | Method of modeling, simulation and fault injection for combined high pressure gear pump for aeroengine |
-
2021
- 2021-05-31 CN CN202110605998.8A patent/CN113255220B/en active Active
Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101413521A (en) * | 2008-11-28 | 2009-04-22 | 西安建筑科技大学 | Experimental apparatus and method for obtaining multi-source diagnostic information of hydraulic equipment |
US20190090840A1 (en) * | 2017-09-28 | 2019-03-28 | General Electric Company | X-ray tube bearing failure prediction using digital twin analytics |
US20200103894A1 (en) * | 2018-05-07 | 2020-04-02 | Strong Force Iot Portfolio 2016, Llc | Methods and systems for data collection, learning, and streaming of machine signals for computerized maintenance management system using the industrial internet of things |
CN109116751A (en) * | 2018-07-24 | 2019-01-01 | 西安西电电气研究院有限责任公司 | Digitization system and its construction method based on the twin technology of number |
US20200265329A1 (en) * | 2019-02-14 | 2020-08-20 | Rockwell Automation Technologies, Inc. | Ai extensions and intelligent model validation for an industrial digital twin |
US20210056244A1 (en) * | 2019-02-25 | 2021-02-25 | Dalian University Of Technology | Method of modeling, simulation and fault injection for combined high pressure gear pump for aeroengine |
CN110532625A (en) * | 2019-07-31 | 2019-12-03 | 西安交通大学 | Aero-engine turbine disk-twin the modeling method of rotor-bearing system number |
CN111365232A (en) * | 2020-03-27 | 2020-07-03 | 武汉理工大学 | Gear pump experiment platform and gear damage detection method |
AU2020102819A4 (en) * | 2020-10-16 | 2020-12-10 | Beihang University | Digital-twin-driven method and system for fault diagnosis of subsea production system of offshore oil |
Non-Patent Citations (4)
Title |
---|
CORDELIA MATTUVARKUZHALI EZHILARASU ET AL.: "Understanding the role of a Digital Twin in Integrated Vehicle Health Management (IVHM)", 《2019 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS》 * |
FEI TAO ET AL.: "Digital Twin Shop-Floor: A New Shop-Floor Paradigm Towards Smart Manufacturing", 《IEEE ACCESS》 * |
吴忠强等: "基于云神经网络自适应逆系统的电力系统负荷频率控制", 《电力自动化设备》 * |
周俊杰等: "考虑空化效应的齿轮泵流量特性研究", 《兵工学报》 * |
Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113868837A (en) * | 2021-09-03 | 2021-12-31 | 中国核电工程有限公司 | On-line monitoring method for concrete volute pump wall surface abrasion |
CN113868837B (en) * | 2021-09-03 | 2024-05-17 | 中国核电工程有限公司 | Online monitoring method for wall surface abrasion of concrete volute pump |
CN114154360A (en) * | 2021-10-19 | 2022-03-08 | 徐州圣邦机械有限公司 | Multi-physical-field probability digital twin modeling method for high-pressure internal gear pump |
CN114154360B (en) * | 2021-10-19 | 2023-12-01 | 徐州圣邦机械有限公司 | Multi-physical field probability digital twin modeling method for high-pressure internal gear pump |
CN114491960A (en) * | 2021-12-29 | 2022-05-13 | 徐州圣邦机械有限公司 | Wear monitoring method for high-pressure internal gear pump |
CN114491960B (en) * | 2021-12-29 | 2023-12-01 | 徐州圣邦机械有限公司 | Wear monitoring method for high-pressure internal gear pump |
CN114918976A (en) * | 2022-06-16 | 2022-08-19 | 慧之安信息技术股份有限公司 | Joint robot health state assessment method based on digital twinning technology |
CN115539378A (en) * | 2022-11-23 | 2022-12-30 | 中汽信息科技(天津)有限公司 | Fault diagnosis method, device and medium for hydraulic gear pump of automobile production line |
Also Published As
Publication number | Publication date |
---|---|
CN113255220B (en) | 2022-12-06 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN113255220B (en) | Gear pump maintenance method based on digital twinning | |
Chen et al. | Study on coupling transient mixed lubrication and time-varying wear of main bearing in actual operation of low-speed diesel engine | |
Manring et al. | The theoretical flow ripple of an external gear pump | |
Voloshina et al. | Experimental studies of a throughput of the distribution systems of planetary hydraulic motors | |
Xu et al. | An advanced pressure pulsation model for external gear pump | |
Di Giovine et al. | Modeling and experimental validation of a triple-screw pump for internal combustion engine cooling | |
Sliwinski | The methodology of design of axial clearances compensation unit in hydraulic satellite displacement machine and their experimental verification | |
Hsieh | Dynamics analysis of the triangular rotary engine structures | |
Wang et al. | Modeling and dynamics simulation of spur gear system incorporating the effect of lubrication condition and input shaft crack | |
Śliwiński | The influence of pressure drop on the working volume of a hydraulic motor | |
CN117634241A (en) | Gear pair dynamic wear amount prediction method considering tooth surface microscopic geometry | |
Pei et al. | Numerical simulation of defective gear transmission under mixed EHL conditions | |
CN111881544A (en) | Harmonic reducer wave generator mixed lubrication analysis method | |
CN115758708A (en) | Method for predicting fatigue life of marine timing gear under three-dimensional mixed lubrication condition | |
Yang et al. | Calculation of the dynamic characteristics of ship’s aft stern tube bearing considering journal deflection | |
Sliwinski | Influence of operating pressure on the durability of a satellite hydraulic motor supplied by rapeseed oil | |
CN111075920B (en) | RV reducer cycloidal pin wheel residual stress solving method based on FFT and lubrication influence | |
Sun et al. | Coupling analysis of timing gear dynamics and three-dimensional mixed lubrication under multi-branch shafting of marine diesel engine | |
Zeng et al. | Numerical research on dynamic responses of the emulsion pump crankshaft under multiple working conditions | |
Kyurchev et al. | Experimental Evaluation of the Impact of the Diametral Clearance on Output Characteristics of a Planetary Hydraulic Motor | |
Ivanović | Design, Modeling and Simulation of Gearing for Improving Gerotor Pump Performance | |
Zhu et al. | A quasi-analytical prediction method for gear load-independent power losses for shroud approaching | |
Śliwiński | The influence of water and mineral oil on mechanical losses in a hydraulic motor for offshore and marine applications | |
Ivanović et al. | Improving gerotor pump performance trough design, modeling and simulation | |
Wahab | Analytical prediction technique for internal leakage in an external gear pump |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |