CN115060503B - A method for evaluating the operating state of aircraft engine rotors based on state information entropy - Google Patents

Abstract

The invention discloses an aircraft engine rotor running state evaluation method based on state information entropy, which comprises the steps of firstly measuring an initial amplitude-rotating speed curve of the operation of an aircraft engine rotor; re-measuring run t _b Amplitude after time-rotation speed curve; next, an amplitude-rotation speed curve A is calculated _b (n) corresponding aircraft engine rotor state information entropy Z _b The method comprises the steps of carrying out a first treatment on the surface of the Repeating the calculation to obtain an operation t _c 、t _d 、t _e … amplitude-rotating speed curve and state information entropy thereof, and amplitude-rotating speed curve and state information entropy of the aero-engine when reaching the life limit moment; arranging the state information entropy values obtained at each moment on a state information entropy value-use time chart according to the use time sequence; all points are connected from small to large according to the service time, and an aeroengine rotor full life state information entropy value-service time diagram is obtained; finally, the service life of the aeroengine rotor with the same model in subsequent operation is evaluated. The invention quantitatively reflects the running state and stability of the rotor, and has actual physical significance and actual operability.

Description

A method for evaluating the operating state of aeroengine rotors based on state information entropy

Technical Field

The invention belongs to the technical field of aero-engines, and in particular relates to a method for evaluating the operating state of an aero-engine rotor.

Background technique

In the field of aircraft engine fault diagnosis and life prediction, various methods based on different principles have emerged so far. In the application process, it is often not to take only one method in isolation, but to tend to reflect the problem more comprehensively through multiple indicators.

Thermodynamic entropy in thermodynamics is, from a macroscopic point of view, a state parameter. Any irreversible factor will lead to an increase in entropy. The formula is: From a microscopic point of view, it is used to describe the disorder of molecular thermal motion. Information entropy in informatics is proposed by Shannon (CE Shannon) using the concept of thermodynamic entropy to describe the uncertainty of information sources. The formula is: I = -∑P _i log ₂ P _i .

As shown in Figure 2, by analogy with the T-S diagram in thermodynamics, a P-Z diagram of the aircraft engine rotor is made, where the power P is analogous to the temperature T in thermodynamics, and the state information entropy Z is analogous to the thermodynamic entropy S in thermodynamics.

The aircraft engine rotor is used as the control body, which is an open system. It only transfers energy with the outside world, but not mass. Under the ideal reversible state, when the aircraft engine rotor system is working, the four cycles shown in Figure 2 can be obtained. The explanations are as follows:

(1) A→B. The rotor turbine extracts energy from high-temperature and high-pressure gas. Under the reversible assumption, it is assumed that the power provided by the high-temperature and high-pressure gas is equal to the power required by the turbine, that is, the two transfer energy under the same power supply and demand conditions, so the power is a certain value P _2. For the rotor system, the energy input from the outside world increases its own energy, and the state becomes unstable, so the state information entropy increases. In summary, under stable working conditions, A→B is a horizontal line.

(2) C→D. The rotor compressor end transfers energy to the low-temperature, low-pressure gas. Under the reversible assumption, it is considered that the power required by the low-temperature, low-pressure gas is equal to the power provided by the compressor, that is, the two transfer energy under the same power supply and demand conditions, so the power is a certain value P1. For the rotor system, when it outputs energy to the outside world, its own energy decreases, and the state becomes stable, so the state information entropy decreases. In summary, under stable working conditions, C→D is a horizontal line.

(3) and (4) B→C, D→A. They are respectively the gas leaving the turbine and flowing to the tail nozzle and the gas entering the intake duct. These two processes are considered to have no effect on the rotor system, so the state information entropy of the rotor is unchanged. So they are two vertical lines.

But in actual working conditions, it is an irreversible state, as shown in Figure 3. In actual conditions, under normal working conditions, the power that the high-temperature and high-pressure gas can provide is greater than the power required by the turbine, and the remaining power is used to overcome losses, which is the origin of the upper half of the curve. Similarly, the power that the compressor can provide is greater than the power required by the low-temperature and low-pressure gas, and the remaining power is used to overcome losses, which is the origin of the lower half of the curve.

Here, by analogy with the thermal efficiency in thermodynamics, the physical quantity η _z is defined as the efficiency of the rotating shaft in overcoming the rolling friction of the bearing under running conditions.

In the irreversible state, since both the turbine end and the compressor end of the rotor system have to overcome the resistance of the power transfer process in the reversible ideal state, the resistance used to overcome the rolling friction of the bearing is greatly reduced.

In the reversible state, since the turbine end and the compressor end are equal power energy exchanges, these two ends do not need to overcome the resistance from the power transfer process. At this time, all the energy obtained by the shaft is used to overcome the resistance from the rolling friction of the bearing. At this time, the efficiency is the highest, recorded as: η _Z.re. There are:

From the above analysis, it is obvious that: η _Z.re ＞η _Z.ir . Substitute [1] and [2] into the equation. And record the work _W2 flowing into the rotor system as positive, and the work _W1 flowing out of the rotor system as negative. After sorting, we can get:

Adding up each infinitesimal process, we have:

Then make the discrete process continuous, that is:

The above formula is: the Clausius integral inequality of analog thermodynamics under the operation state of aircraft engines. It shows that: when any engine rotor system works in an ideal reversible cycle at both ends, the cyclic integral of the ratio of the infinitesimal work transfer to the supply and demand power during work transfer is equal to 0; when the two ends work in an actual irreversible cycle, the cyclic integral of the ratio of the infinitesimal work transfer to the supply and demand power during work transfer is less than 0.

Obviously, As a state quantity, it is defined as the state entropy of the aircraft engine by analogy with the definition of entropy in thermodynamics. This is to combine the "irreversible factors lead to entropy increase" in thermodynamics to derive the necessity of the existence of the state information entropy of the aircraft engine rotor.

By further analogy, we can also deduce the state information entropy flow and state information entropy production. Among them, the state information entropy flow is the impact of power inflow and outflow on the state of the aircraft engine rotor. The state information entropy production is due to the internal irreversible conditions of the rotor, such as the friction between the shaft and the rolling bearing, the friction between the rotor and the stator, etc., which can affect the rotor state.

In the invention with application number CN202110348056.6, a turbine rotor life assessment and maintenance indication system is proposed. This patent calculates, verifies and simulates the fatigue strength problems of the rotor of a large steam turbine generator set under various startup and operation conditions. The fatigue life of the steam turbine during operation is quantitatively calculated. By giving maintenance suggestions, accurate unit life assessment and reasonable maintenance arrangements can greatly extend the life of the steam turbine. Good results have been achieved. However, this patent only focuses on temperature field stress and fatigue strength, and does not quantitatively describe the operating state of the rotor from the perspective of changes in the rotor caused by energy input and output.

In the invention with application number CN200910195881.6, a life assessment method for generator rotors and rotor guard rings is proposed. The patent analyzes the finite element model of the temperature field and stress field to perform life damage analysis. It can effectively assess the service life of the generator rotor and rotor guard ring, and then improve the life assessment technology of the entire steam turbine generator set. Good results have been achieved. However, the patent only focuses on the temperature field and stress field, and does not quantitatively describe the operating state of the rotor from the perspective of changes in the rotor caused by energy input and output.

Summary of the invention

In order to overcome the shortcomings of the prior art, the present invention provides an aircraft engine rotor operation state evaluation method based on state information entropy. First, the initial amplitude-speed curve A _a (n) of the aircraft engine rotor is measured; then the amplitude-speed curve after the operation time t _b is measured; next, points are taken and the aircraft engine rotor state information entropy Z _b corresponding to the amplitude-speed curve A _b (n) is calculated; the amplitude-speed curve A c (n), A _d (n), A _e (n) ... and its state information entropy Z c , Z d , _Ze at the operation time t _c , t _d , t _e ... are calculated repeatedly to obtain the amplitude-speed curve A _c (n), A d (n), A e (n) ... and its state information entropy Z _c , Z _d , Ze at the _operation time t c , t d , t e ..., and ...>t _e >t _d >t _c >t _b , as well as the amplitude-speed curve Z _finish (n) and state information entropy Z _finish of the aircraft engine when the life limit t finish is reached; the state information entropy values obtained at each time are arranged in the order of use time on the state information entropy value-use time diagram; each point is connected from small to large according to the use time to obtain the aircraft engine rotor full life state information entropy value-use time diagram; finally, the life evaluation is performed on the aircraft engine rotor of the same model that is subsequently operated. The invention quantitatively reflects the state and stability of rotor operation and has real physical significance and practical operability.

The technical solution adopted by the present invention to solve the technical problem includes the following steps:

Step 1: Measure the initial amplitude-speed curve of the aircraft engine rotor;

The amplitude-speed curve A _a (n) of the aircraft engine rotor accelerating from a stationary state is obtained by measurement; the abscissa of the amplitude-speed curve A _a (n) is the speed in rpm, and the ordinate is the vibration amplitude of the aircraft engine rotor at the corresponding speed in μm; the amplitude-speed curve A _a (n) is used as a benchmark for measuring the deviation of the aircraft engine rotor from the initial state after operation;

Step 2: Measure the amplitude-speed curve of the aircraft engine rotor after running for t _b time;

The amplitude-speed curve A _b (n) of the aircraft engine rotor accelerating from a stationary state after running for t _b time is obtained by measurement, wherein the abscissa of the amplitude-speed curve A _b (n) is the speed in rpm, and the ordinate is the vibration amplitude of the aircraft engine rotor at the corresponding speed in μm;

Step 3: Select points according to the following rules and calculate the aircraft engine rotor state information entropy Z _b corresponding to the amplitude-speed curve A _b (n);

Place the amplitude-speed curve A _a (b) in step 1 and the amplitude-speed curve A _b (n) in step 2 in an amplitude-speed coordinate system;

In the amplitude-speed coordinate system, the vertical axis is the amplitude, the unit is μm, and the horizontal axis is the speed, the unit is rpm; on the horizontal axis, determine the interval [Vmin, Vmax] used to calculate the state information entropy; within this interval, take s horizontal coordinates with equal steps: _n1 , _n2 ... _ns , and accordingly, obtain the vertical coordinate values corresponding to these s horizontal coordinates on the amplitude-speed curve _Aa (n) and the amplitude-speed curve _Ab (n): _Aa ( _n1 ), _Aa ( _n2 )... _Aa ( _ns ) and _Ab ( _n1 ), _Ab ( _n2 )... _Ab ( _ns ); let the error rate of the measuring instrument be w%, there are i _Ab ( _nx ) values, x=1,2...i falls within the interval [ _Aa ( _nx ) _-Aa ( _nx )·w%, _Aa ( _nx )+ _Aa ( _nx )·w%], there are si _Ab ( _ny ) value, y＝1,2…si falls outside the interval [ _Aa ( _ny ) _-Aa ( _ny )·w％, _Aa ( _ny )+ _Aa ( _ny )·w％]; then according to the formula:

Calculate the information entropy Z _b of the rotor state of the aircraft engine after the rotor runs for t _b time;

Step 4: Repeat steps 2 and 3 to obtain the amplitude-speed curves A _c (n), A _d (n), A _e (n) ... and their state information entropies Z _c , Z _d , _Ze ... of the aircraft engine rotor during operation t _c , t _d , t _e ... and ... > t _e > t _d > t _c > t _b , as well as the amplitude-speed curve A _finish (n) and the state information entropy Z _finish of the aircraft engine rotor when the life limit t _finish is reached; the t _c , t _d , t _e ... refer to the moments before the life of the aircraft engine rotor is completely exhausted, that is, before the use time t _finish , for calculating the state information entropy of the aircraft engine at the corresponding moment;

Step 5: Arrange the state information entropy values obtained at each moment in the order of usage time on the state information entropy value-usage time graph;

The state information entropy value-usage time graph is as follows: the horizontal axis is the usage time, the unit is s, and the vertical axis is the state information entropy value, the unit is bit·μm;

The coordinates of point A are recorded as ( _ta , _Za ), where _ta = 0, _Za = 0, indicating that when the aircraft engine is just shipped, the working time is 0s, and the state information entropy of the aircraft engine rotor is 0 bit·μm. The coordinate point A ( _ta , _Za ) is marked in the state information entropy value-use time diagram;

The state information entropy value measured after the aircraft engine rotor has been working for t _b time from leaving the factory is Z _b , and the coordinate point B (t _b , Z _b ) is marked in the state information entropy value-use time diagram;

The measured state information entropy value after the aircraft engine rotor has been working for t _c time from leaving the factory is Z _c , and the coordinate point C (t _c , Z _c ) is marked in the state information entropy value-use time diagram;

The state information entropy value measured after the aircraft engine rotor has been working for t _d from the factory is Z _d , and the coordinate point D (t _d , Z _d ) is marked in the state information entropy value-use time diagram;

The measured state information entropy value is _Ze after the aircraft engine rotor has been working for t _e time since leaving the factory, and the coordinate point E (t _e , _Ze ) is marked in the state information entropy value-use time diagram;

The state information entropy value measured after the aircraft engine rotor leaves the factory for t _finish is Z _finish , and the coordinate point Finish (t _finish , Z _finish ) is marked in the state information entropy value-use time diagram;

After the time t _finish of the aircraft engine rotor leaving the factory, it can no longer be used and its service life ends;

Step 6: Connect the points in step 5 from small to large according to the usage time to obtain the full life state information entropy value of the aircraft engine rotor - usage time diagram;

The full life state information entropy value of the aircraft engine rotor - the usage time diagram includes the state information entropy values of the aircraft engine rotor measured at intervals from the time the aircraft engine rotor leaves the factory to the end of its life;

Step 7: Using the full life state information entropy value of the aircraft engine obtained in step 6, the time diagram is used to perform life assessment on the rotor of the aircraft engine of the same model to be used subsequently;

After the same type of aircraft engine has been working for a period of time, the state entropy measured by the method of steps 1 and 2 is According to the full life state information entropy value of this model of aircraft engine obtained in step 6 - usage time diagram, find the vertical coordinate The horizontal coordinate corresponding to the time is recorded as/> At this time, the estimated time since it was shipped is/> The remaining life is

The beneficial effects of the present invention are as follows:

The present invention quantitatively describes the operating state of the rotor from the perspective of the changes brought to the rotor by energy input and output, and proposes the parameter and calculation formula of state information entropy. By calculating the state information entropy of the amplitude-speed curve in the speed range compared with the initial amplitude-speed curve, the state and stability of the rotor operation are quantitatively reflected, not only focusing on a specific fault point but also comprehensively evaluating the state at all speeds; the present invention spans the two disciplines of thermodynamics and informatics, crosses the two, and is applied to the evaluation of the operating state of aircraft engines. It is a brand-new perspective and has real physical significance and practical operability.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 is a design flow chart of the present invention.

FIG. 2 is a P-Z diagram of an aircraft engine rotor in an ideal state.

FIG. 3 is a P-Z diagram of the rotor of an aircraft engine in an actual irreversible state.

FIG. 4 is an amplitude-speed curve A _a (n) measured on a test bench for a sleeve gear coupling having a matching clearance of 0 mm and a matching surface roughness of 0.8 in an embodiment of the present invention.

FIG. 5 is an amplitude-speed curve A _b (n) measured on a test bench for a sleeve gear coupling with a clearance of 0.01 mm and a mating surface roughness of 0.8 according to an embodiment of the present invention.

FIG. 6 is an amplitude-speed curve of each gear coupling obtained in steps 1/2/4 of an embodiment of the present invention.

FIG. 7 is a diagram showing the state information entropy at each moment measured by an embodiment of the present invention, marked on a state information entropy value-usage time diagram.

FIG8 is a diagram showing the full life state information entropy value of the sleeve gear coupling versus usage time in an embodiment of the present invention.

FIG. 9 is a schematic diagram of an evaluation sleeve gear coupling according to an embodiment of the present invention.

Detailed ways

The present invention is further described below in conjunction with the accompanying drawings and embodiments.

In order to overcome the defect in the prior art that the rotor operation state is not quantitatively described from the perspective of the changes brought about by energy input and output to the rotor, the present invention proposes an aircraft engine rotor operation state evaluation method based on state information entropy, as shown in Figure 1.

Step 1: Measure the initial amplitude-speed curve of the aircraft engine rotor;

The amplitude-speed curve A _a (n) of the aircraft engine rotor accelerating from a stationary state is obtained by measurement; the abscissa of the amplitude-speed curve A _a (n) is the speed in rpm, and the ordinate is the vibration amplitude of the aircraft engine rotor at the corresponding speed in μm; the amplitude-speed curve A _a (n) is used as a benchmark for measuring the deviation of the aircraft engine rotor from the initial state after operation;

Step 2: Measure the amplitude-speed curve of the aircraft engine rotor after running for t _b time;

The amplitude-speed curve A _b (n) of the aircraft engine rotor accelerating from a stationary state after running for t _b time is obtained by measurement, wherein the abscissa of the amplitude-speed curve A _b (n) is the speed in rpm, and the ordinate is the vibration amplitude of the aircraft engine rotor at the corresponding speed in μm;

Step 3: Select points according to the following rules and calculate the aircraft engine rotor state information entropy Z _b corresponding to the amplitude-speed curve A _b (n);

Place the amplitude-speed curve A _a (n) in step 1 and the amplitude-speed curve A _b (n) in step 2 in an amplitude-speed coordinate system;

In the amplitude-speed coordinate system, the vertical axis is the amplitude, the unit is μm, and the horizontal axis is the speed, the unit is rpm; on the horizontal axis, determine the interval [Vmin, Vmax] used to calculate the state information entropy; within this interval, take s horizontal coordinates with equal steps: _n1 , _n2 ... _ns , and accordingly, obtain the vertical coordinate values corresponding to these s horizontal coordinates on the amplitude-speed curve _Aa (n) and the amplitude-speed curve _Ab (n): _Aa ( _n1 ), _Aa ( _n2 )... _Aa ( _ns ) and _Ab ( _n1 ), _Ab ( _n2 )... _Ab ( _ns ); let the error rate of the measuring instrument be w%, there are i _Ab ( _nx ) values, x=1,2...i falls within the interval [ _Aa ( _nx ) _-Aa ( _nx )·w%, _Aa ( _nx )+ _Aa ( _nx )·w%], there are si _Ab ( _ny ) value, y＝1,2…si falls outside the interval [ _Aa ( _ny ) _-Aa ( _ny )·w％, _Aa ( _ny )+ _Aa ( _ny )·w％]; then according to the formula:

Calculate the information entropy Z _b of the rotor state of the aircraft engine after the rotor runs for t _b time;

Step 4: Repeat steps 2 and 3 to obtain the amplitude-speed curves A _c (n), A _d (n), A _e (n)… and their state information entropies Z _c , Z _d , _Ze … of the aircraft engine rotor during operation t _c , t _d , t _e …times and …> t _e > t _d > t _c > t _b , as well as the amplitude-speed curve A _finish (n) and state information entropy Z _finish of the aircraft engine rotor when the life limit t _finish is reached; the t _c , t _d , t _e … refers to the time before the life of the aircraft engine rotor is completely exhausted, that is, before the use time is t _finish , for calculating the aircraft engine state information entropy at the corresponding time. For the t _c , t _d , t _e …times, if the time interval is shorter, the full life state information entropy value of the aircraft engine rotor—the use time diagram obtained in step 6 will be more accurate;

Step 5: Arrange the state information entropy values obtained at each moment in the order of usage time on the state information entropy value-usage time graph;

The state information entropy value-usage time graph is as follows: the horizontal axis is the usage time, the unit is s, and the vertical axis is the state information entropy value, the unit is bit·μm;

The coordinates of point A are recorded as ( _ta , _Za ), where _ta = 0, _Za = 0, indicating that when the aircraft engine is just shipped, the working time is 0s, and the state information entropy of the aircraft engine rotor is 0 bit·μm. The coordinate point A ( _ta , _Za ) is marked in the state information entropy value-use time diagram;

The state information entropy value measured after the aircraft engine rotor has been working for t _b time from leaving the factory is Z _b , and the coordinate point B (t _b , Z _b ) is marked in the state information entropy value-use time diagram;

The measured state information entropy value after the aircraft engine rotor has been working for t _c time from leaving the factory is Z _c , and the coordinate point C (t _c , Z _c ) is marked in the state information entropy value-use time diagram;

The state information entropy value measured after the aircraft engine rotor has been working for t _d from the factory is Z _d , and the coordinate point D (t _d , Z _d ) is marked in the state information entropy value-use time diagram;

The measured state information entropy value is _Ze after the aircraft engine rotor has been working for t _e time since leaving the factory, and the coordinate point E (t _e , _Ze ) is marked in the state information entropy value-use time diagram;

The state information entropy value measured after the aircraft engine rotor leaves the factory for t _finish is Z _finish , and the coordinate point Finish (t _finish , Z _finish ) is marked in the state information entropy value-use time diagram;

After the time t _finish of the aircraft engine rotor leaving the factory, it can no longer be used and its service life ends;

Step 6: Connect the points in step 5 from small to large according to the usage time to obtain the full life state information entropy value of the aircraft engine rotor - usage time diagram;

The full life state information entropy value of the aircraft engine rotor - the usage time diagram includes the state information entropy values of the aircraft engine rotor measured at intervals from the time the aircraft engine rotor leaves the factory to the end of its life;

Step 7: Using the full life state information entropy value of the aircraft engine obtained in step 6, the time diagram is used to perform life assessment on the rotor of the aircraft engine of the same model to be used subsequently;

After the same type of aircraft engine has been working for a period of time, the state entropy measured by the method of steps 1 and 2 is According to the full life state information entropy value of the aircraft engine of this model obtained in step 6 - the usage time diagram, find the vertical coordinate as/> The horizontal coordinate corresponding to the time is recorded as/> At this time, the estimated time since it was shipped is/> The remaining life is

Specific embodiment:

The sleeve gear coupling in the aircraft engine rotor is used to simulate the operation of the aircraft engine rotor to verify the method of the present invention.

Step 1: Take a certain type of sleeve gear coupling, with a clearance of 0 mm and a surface roughness of 0.8. Measure its initial amplitude-speed curve A _a (n)

Take a certain type of sleeve gear coupling with a matching clearance of 0mm and a matching surface roughness of 0.8, and measure the amplitude-speed curve _Aa (n) of the sleeve gear coupling when it accelerates from a stationary state to a certain speed value. The horizontal coordinate of the amplitude-speed curve _Aa (n) is the speed unit in rpm, and the vertical coordinate is the vibration amplitude of the sleeve gear coupling at the corresponding speed, in μm. The amplitude-speed curve _Aa (n) is used as a benchmark to measure the deviation from the initial state after the sleeve gear coupling has been running for a period of time. See Figure 4.

Step 2: Take the same type of sleeve gear coupling, with a clearance of 0.01 mm and a surface roughness of 0.8, measure its amplitude-speed curve A _b (n), and calculate the state information entropy Z _b .

Take the same model of sleeve gear coupling with a clearance of 0.01mm and a surface roughness of 0.8, and measure the amplitude-speed curve A _b (n) of the sleeve gear coupling when it accelerates from a static state to a certain speed value after running for a period of time. The horizontal axis of the amplitude-speed curve A _b (n) is the speed in rpm, and the vertical axis is the vibration amplitude of the sleeve gear coupling at the corresponding speed in μm. As shown in Figure 5.

Step 3: Select points according to certain rules and calculate the state information entropy Z _b of the gear coupling corresponding to the amplitude-speed curve A _b (n)

The amplitude-speed curve A _a (n) in step 1 and the amplitude-speed curve _Ab (n) in step 2 are placed in the amplitude-speed coordinate system. In the amplitude-speed coordinate system, the vertical axis is the amplitude in μm and the horizontal axis is the speed in rpm. On the horizontal axis, the interval [1600, 4000] for calculating the state information entropy is determined. In this interval, 481 horizontal coordinates are taken with equal steps of 5: n ₁ = 1600, n ₂ = 1605, n ₃ = 1610…n ₄₈₁ = 4000. Accordingly, the vertical coordinate values corresponding to the s horizontal coordinates on the amplitude-speed curve A _a (n) and the amplitude-speed curve _Ab (n) are obtained: A _a (n ₁ ), A _a (n ₂ )…A _a ( _ns ) and _Ab (n ₁ ), _Ab (n ₂ )… _Ab ( _ns ). The error rate of the measuring instrument is 2%. There are 8 A _b (n _x ) values, where x = 1, 2…7, 8, falling within the interval [A _a (n _x )-A _a (n _x )·2%, A _a (n _x )+A _a (n _x )·2%], and there are 473 A _b (n _y ) values, where y = 1, 2…473, falling outside the interval [A _a (n _y )-A _a (n _y )·2%, A _a (n _y )+A _a (n _y )·2%]. The formula is:

Step 4: Continue to use the sleeve gear coupling with different matching clearance and matching surface roughness to simulate the operation state of the aircraft engine rotor changing with time. Repeat steps 2 and 3 to measure the amplitude-speed curve A _c (n), A _finish (n), and calculate the state information entropy: Z _c , Z _finish ,.

Take the same type of sleeve gear coupling with a clearance of 0.01 mm and a surface roughness of 1.6, and repeat steps 2 and 3. Obtain the amplitude speed curve A _c (n), and calculate Z _c = 114.0507 bit·μm.

Take the same type of sleeve gear coupling with a clearance of 0.02 mm and a surface roughness of 1.6, and repeat steps 2 and 3. Obtain the amplitude speed curve A _finish (n), and calculate Z _finish = 298.2765 bit·μm.

At this time, it is believed that when the fitting clearance of this type of sleeve coupling is 0.02mm and the fitting surface roughness is 1.6, it can no longer be used and its service life is completely exhausted.

The amplitude-speed curves obtained in steps one, two and four are shown in Figure 6.

Step 5: Arrange the state information entropy values obtained at each moment in the order of usage time on the state information entropy value-usage time graph

The state information entropy value-usage time graph is as follows: the horizontal axis is the usage time, the unit is s, and the vertical axis is the state information entropy value, the unit is bit·μm.

The coordinates of point A are recorded as ( _ta , _Za ). Among them, _ta = 0, _Za = 0. It means that when the sleeve gear coupling is just shipped, the working time is 0s, and the state information entropy at this time is 0 bit·μm. The coordinate point A ( _ta , _Za ) is marked in the state information entropy value-usage time diagram.

The state information entropy value measured after the model of sleeve gear coupling has been working for t _b since leaving the factory is the state information entropy value obtained in step 2 as Z _b , and the coordinate point B (t _b , Z _b ) is marked in the state information entropy value-usage time diagram.

The measured state information entropy value after the model of sleeve gear coupling has been working for t _c since leaving the factory is the state information entropy value Z _c obtained in steps three and four, and the coordinate point C (t _c , Z _c ) is marked in the state information entropy value-usage time diagram.

The state information entropy value measured after t _finish of this model of sleeve gear coupling leaves the factory is Z finish , and the state information entropy value obtained in steps three and four is marked as Z _finish , and the coordinate point Finish (t _finish , Z _finish ) is marked in the state information entropy value - usage time diagram.

As shown in Figure 7.

Step 6: Connect the points in step 5 from small to large according to the usage time to obtain the full life state information entropy value of this model of sleeve gear coupling - usage time diagram

The obtained figure is shown in Figure 8

Step 7: Using the full life state information entropy value of the sleeve gear coupling of this model obtained in step 6, use the time diagram to conduct life assessment on the sleeve gear coupling of this model used subsequently.

After the same set of gear couplings of this model has been working for a period of time, the state entropy measured according to steps one and two is According to the information entropy value of the whole life state of the ruler set obtained in step 6 - the usage time diagram, find the vertical coordinate as/> The horizontal coordinate corresponding to the time is recorded as/> As shown in Figure 9. At this time, it can be estimated that the time it has been used since leaving the factory is / > The remaining life is/>

Claims (1)

1. A method for evaluating the operating state of an aircraft engine rotor based on state information entropy, characterized in that it comprises the following steps: Step 1: Measure the initial amplitude-speed curve of the aircraft engine rotor; The amplitude-speed curve A _a (n) of the aircraft engine rotor accelerating from a stationary state is obtained by measurement; the abscissa of the amplitude-speed curve A _a (n) is the speed in rpm, and the ordinate is the vibration amplitude of the aircraft engine rotor at the corresponding speed in μm; the amplitude-speed curve A _a (n) is used as a benchmark for measuring the deviation of the aircraft engine rotor from the initial state after operation; Step 2: Measure the amplitude-speed curve of the aircraft engine rotor after running for t _b time; The amplitude-speed curve A _b (n) of the aircraft engine rotor accelerating from a stationary state after running for t _b time is obtained by measurement, wherein the abscissa of the amplitude-speed curve A _b (n) is the speed in rpm, and the ordinate is the vibration amplitude of the aircraft engine rotor at the corresponding speed in μm; Step 3: Select points according to the following rules and calculate the aircraft engine rotor state information entropy Z _b corresponding to the amplitude-speed curve A _b (n); Place the amplitude-speed curve A _a (n) in step 1 and the amplitude-speed curve A _b (n) in step 2 in an amplitude-speed coordinate system; In the amplitude-speed coordinate system, the vertical axis is the amplitude, the unit is μm, and the horizontal axis is the speed, the unit is rpm; on the horizontal axis, determine the interval [Vmin, Vmax] used to calculate the state information entropy; within this interval, take s horizontal coordinates with equal steps: _n1 , _n2 ... _ns , and accordingly, obtain the vertical coordinate values corresponding to the s horizontal coordinates on the amplitude-speed curve _Aa (n) and the amplitude-speed curve _Ab (n): _Aa ( _n1 ), _Aa ( _n2 )... _Aa ( _ns ) and _Ab ( _n1 ), _Ab ( _n2 )... _Ab ( _ns ); let the error rate of the measuring instrument be w%, there are i _Ab ( _nx ) values, x=1, 2...i falling within the interval [ _Aa ( _nx ) _-Aa ( _nx )·w%, _Aa ( _nx )+ _Aa ( _nx )·w%], there are si _Ab ( _ny) values ) value, y=1, 2...si falls outside the interval [ _Aa ( _ny ) _-Aa ( _ny )·w%, _Aa ( _ny )+ _Aa ( _ny )·w%]; then from the formula: Calculate the information entropy Z _b of the rotor state of the aircraft engine after the rotor runs for t _b time; Step 4: Repeat steps 2 and 3 to obtain the amplitude-speed curves A _c (n), A _d (n), A _e (n) ... and their state information entropies Z _c , Z _d , _Ze ... of the aircraft engine rotor during operation t _c , t _d , t _e ... and ... > t _e > t _d > t _c > t _b , as well as the amplitude-speed curve A _finish (n) and the state information entropy Z _finish of the aircraft engine rotor when the life limit t _finish is reached; the t _c , t _d , t _e ... refers to the time before the aircraft engine rotor life is completely exhausted, that is, before the use time t _finish , for calculating the aircraft engine state information entropy at the corresponding time; Step 5: Arrange the state information entropy values obtained at each moment in the order of usage time on the state information entropy value-usage time graph; The state information entropy value-usage time graph is as follows: the horizontal axis is the usage time, the unit is s, and the vertical axis is the state information entropy value, the unit is bit·μm; The coordinates of point A are recorded as ( _ta , _Za ), where _ta = 0, _Za = 0, indicating that when the aircraft engine is just shipped, the working time is 0s, and the state information entropy of the aircraft engine rotor is 0 bit·μm. The coordinate point A ( _ta , _Za ) is marked in the state information entropy value-use time diagram; The state information entropy value measured after the aircraft engine rotor has been working for t _b time from leaving the factory is Z _b , and the coordinate point B (t _b , Z _b ) is marked in the state information entropy value-use time diagram; The measured state information entropy value after the aircraft engine rotor has been working for t _c time from leaving the factory is Z _c , and the coordinate point C (t _c , Z _c ) is marked in the state information entropy value-use time diagram; The state information entropy value measured after the aircraft engine rotor has been working for t _d from the factory is Z _d , and the coordinate point D (t _d , Z _d ) is marked in the state information entropy value-use time diagram; The measured state information entropy value is _Ze after the aircraft engine rotor has been working for t _e time since leaving the factory, and the coordinate point E (t _e , _Ze ) is marked in the state information entropy value-use time diagram; The state information entropy value measured after the aircraft engine rotor leaves the factory for t _finish is Z _finish , and the coordinate point Finish (t _finish , Z _finish ) is marked in the state information entropy value-use time diagram; After the time t _finish of the aircraft engine rotor leaving the factory, it can no longer be used and its service life ends; Step 6: Connect the points in step 5 from small to large according to the usage time to obtain the full life state information entropy value of the aircraft engine rotor - usage time diagram; The full life state information entropy value of the aircraft engine rotor - the usage time diagram includes the state information entropy values of the aircraft engine rotor measured at intervals from the time the aircraft engine rotor leaves the factory to the end of its life; Step 7: Using the full life state information entropy value of the aircraft engine obtained in step 6, the time diagram is used to perform life assessment on the rotor of the aircraft engine of the same model to be used subsequently; After the same type of aircraft engine has been working for a period of time, the state entropy measured by the method of steps 1 and 2 is According to the full life state information entropy value of the aircraft engine of this model obtained in step 6 - the usage time diagram, find the vertical coordinate as/> The horizontal coordinate corresponding to the time is recorded as/> At this time, the estimated time since it was shipped is/> The remaining life is/>