CN104657529A - Method for designing helicopter aerodynamic layout parameter on flight performance point of view - Google Patents

Abstract

The invention belongs to the helicopter design technical field, and in particular relates to a method for designing helicopter aerodynamic layout parameter on flight performance point of view. The method improves the particle swarm optimization and the aerodynamic layout parameter design technological process, the method is different from the conventional method that a plurality of recommended parameter combinations are used, one feasible region of the aerodynamic layout parameter can be obtained by the given flight performance goal, the flight performance is not lower than the goal for the aerodynamic layout parameter combination selected and modified in the region.

Description

A kind of method of carrying out helicopter aerodynamic arrangement parameter designing from flying quality angle

Technical field

The invention belongs to technology of helicopter design field, particularly relate to a kind of method of carrying out helicopter aerodynamic arrangement parameter designing from flying quality angle.

Background technology

For design and the amendment of helicopter aerodynamic parameter in the past, main dependence designer experience, the data statistics of organic type are determined, or marking is weighted to the flying quality of limited Ji Zu aerodynamic arrangement parameter, obtains corresponding scoring, determine parameter combinations according to scoring quality.But this classic method increases personnel's burden, time-consuming effort, and dependence experience and data statistics accurately can not determine parameter; Scoring is relied on to weigh, limited aerodynamic arrangement's parameter combinations can only be analyzed, and actual parameter interval is continuous print, and aerodynamic arrangement's parameter designing also will consider the requirement of the specialty such as flight quality, aerodynamic loading, aerodynamic arrangement's parameter combinations for best performance differs and meets the requirement of other specialty surely, when contradiction appears in demand of specialty time, be difficult to coordination parameter and select.

Summary of the invention

Object of the present invention:

The present invention is by improve PSO algorithm and pneumatic layout parameter design cycle, providing several recommended parameter from classic method combines different, can by given flying quality target, obtain a feasible region of aerodynamic arrangement's parameter, the aerodynamic arrangement's parameter combinations selected in this region and revise, makes gained flying quality be not less than target.

Technical scheme of the present invention:

Carry out a method for helicopter aerodynamic arrangement parameter designing from flying quality angle, this method comprises the following steps:

The first step, by carrying out Flight to existing or prototype helicopter, obtain the following flying quality of this helicopter, include but not limited to: maximumly have hover out of ground effect weight, have hover out of ground effect ceiling, maximum perpendicular climbing speed, the maximum oblique climb rate, ultimate run boat time, service ceiling and maximum cruise; And the test flight data utilizing Flight to obtain is calibrated the performance software for calculation that this method will be used, make the result of calculation of performance software for calculation suitable with test flight data;

Second step, aerodynamic arrangement's parameter according to existing or prototype helicopter, the physical restriction of the parameter of the parameter area of the wind tunnel experiment of existing or prototype helicopter, existing or prototype helicopter, and other helicopter aerodynamic arrangement parametric statistics data, after determined the impact of the aerodynamic interference between different helicopter component by wind tunnel experiment, determine the design bound newly designing helicopter aerodynamic arrangement parameter, following design procedure should carry out in this given design bound parameter area;

3rd step, according to the main task mission of new design helicopter and needed for the mission requirements taken into account, the flying quality that is existing or prototype helicopter obtained in the first step is adjusted, is newly designed the flying quality target of helicopter;

4th step, the flying quality target of new design helicopter obtained based on the 3rd step, in performance software for calculation, the feasible zone of the aerodynamic arrangement's parameter using feasible zone derivation algorithm to solve new design helicopter in the given design bound parameter area of second step, when solving, according to the similarity of aerodynamic arrangement's parameter requirements, flying quality target is classified, solves each flying quality target feasible zone border separately respectively;

5th step, all feasible zones to be put together, overlapping region is exactly the feasible zone newly designing helicopter aerodynamic arrangement parameter, if feasible zone does not have overlapping explanation may not meet the parameter combinations of all flying quality targets simultaneously, need to get back to the 3rd step and flying quality target is redefined;

6th step, consider flight quality, hub moment, size restriction and structural limitations, progressively improve flying quality target, feasible zone is reduced gradually, after successive ignition reduces, finally determine one group of feasible aerodynamic arrangement's parameter being positioned at feasible zone, this group aerodynamic arrangement parameter can meet the requirement of flying quality target;

7th step, according to this group aerodynamic arrangement parameter, aerodynamic arrangement's parameter that is existing or prototype helicopter is modified, and Flight is carried out to amended helicopter, be aerodynamic arrangement's parameter of new design helicopter by the aerodynamic arrangement's parameter after checking.

Feasible zone derivation algorithm method for solving described in 4th step is as follows:

The known parameters set in this method is as follows:

M flying quality target of new design helicopter, is expressed as vectorial G=[g ₁g ₂g _jg _m] ^t, wherein, g _jrepresent a jth flying quality target, 1≤j≤M;

N number of aerodynamic arrangement parameter of new design helicopter, is expressed as vectorial X=[x ₁x ₂x _ix _n] ^t, wherein, x _irepresent i-th aerodynamic arrangement's parameter, 1≤i≤N;

The design bound parameter area of new design helicopter, the upper limit is expressed as X _max=[x _max1x _max2x _maxN] ^t, lower limit is expressed as X _min=[x _min1x _min2x _minN] ^t, make for 1≤i≤N, x _maxi> x _i> x _mini;

This method solution procedure is as follows:

The first step, initialization population, this population includes L particle altogether, is expressed as: Swarm ₁, Swarm ₂... Swarm _kswarm _l, wherein, 1≤k≤L, to aerodynamic arrangement's parameter of each particle this particle of stochastic generation in the design bound parameter area of new design helicopter, a kth particle Swarm _kaerodynamic arrangement's parameter that initialization generates is X _k;

Second step, calculate the flying quality vector sum multiple goal fitness of each particle, calculation procedure is as follows:

A kth particle Swarm _kflying quality be f (X _k), multiple goal fitness is Fitness (X _k), wherein, f (X _k)=[f ₁(X _k) f ₂(X _k) ... f _m(X _k)] ^t, for described flying quality f (X _k), if right 1≤j≤M, meets f _j(X _k) > g _j, this aerodynamic arrangement parameter X is called feasible solution, and the aerodynamic arrangement's parameter sets be made up of all feasible solutions is called the feasible zone of aerodynamic arrangement's parameter, in order to weigh current flight performance f (X _k) and the difference of flying quality target G, definition multiple goal fitness when time, X _kfor feasible zone Boundary Solutions, ε is the threshold value preset;

3rd step, solve the non-dominant collection in current particle group, solving of non-dominant collection is as follows:

In order to weigh the difference of each particle aerodynamic arrangement parameter, define the distance between l particle and a kth particle wherein, be i-th aerodynamic arrangement's parameter of l particle, for i-th aerodynamic arrangement's parameter of a kth particle, for each particle, find out all particles being less than predetermined threshold R with its distance, for a kth particle Swarm _ks the particle being less than predetermined threshold R with its distance is expressed as Swarm ₁, Swarm ₂... Swarm _s, Swarm _s, 1≤s≤S, Swarm ₁for Swarm _kparticle self, the optimal particle Swarm of a definition kth particle _bestfor: particle Swarm _s, its multiple goal fitness is Fitness _s, as particle Swarm _bestwith particle Swarm _sbetween distance distance _{best, s}during < R, meet particle Swarm _bestmultiple goal fitness Fitness _best< Fitness _s; The set of all optimal particle compositions is non-dominant collection;

4th step, saves as the first outside collection by the non-dominant set that the 3rd step is tried to achieve.

5th step, is set to particle self by the individual extreme value of each particle, and aerodynamic arrangement's parameter of the individual extreme value of a kth particle is designated as X _{k, Pbest}, the multiple goal fitness of the individual extreme value of a kth particle is designated as Fitness (X _{k, Pbest});

6th step, is set to global optimum particle Gbest by particle minimum for multiple goal fitness in population, aerodynamic arrangement's parameter of global optimum particle Gbest is designated as X _gbest, the multiple goal fitness of global optimum particle Gbest is designated as Fitness (X _gbest).

7th step, upgrades the flying speed of each particle in population and pneumatic layout parameter the 1st time by following method;

In population, the dynamic layout parameter that a kth particle generates when first step initialization is designated as X _k, the flying speed upgraded for the 1st time of a kth particle is designated as $V_k^1={{\left(\begin{array}{cccccc}{v}_1& v_2& ...& v_i& ...& v_N\end{array}\right)}_k}^1,$ The aerodynamic arrangement's parameter upgraded for 1st time of a kth particle is designated as wherein:

$V_k^1=c_1(X_{k,\mathrm{Pbest}}-X_k)+c_2(X_{\mathrm{Gbest}}-X_k)$

$X_k^1=X_k+V_k^1$

Wherein, c ₁and c ₂being Studying factors, is the random number between 0 to 1.

If beyond the design bound parameter area of new design helicopter, then aerodynamic arrangement's parameter of this particle of stochastic generation again in the design bound parameter area of new design helicopter and ${V_k}^1=\left[\begin{array}{ccc}0& ...& 0\end{array}\right].$

8th step, according to the method for second step, calculates flying quality and the multiple goal fitness of each particle after upgrading;

9th step, according to the method for the 3rd step, solves the non-dominant collection in current particle group;

Tenth step, the first outside non-dominant set of current particle group being put into the 4th step is concentrated, and the particle of deduplication, to the obtain second outside collection, obtaining the second outside concentrated non-dominant collection by the method for the 3rd step, is the 3rd outside collection with this non-dominant collection.

11 step, upgrade the individual extreme value of each particle: each particle in population has oneself an individual extreme value, to the kth particle repeatedly upgraded, the each multiple goal fitness upgraded of record, obtain multiple multiple goal fitness, aerodynamic arrangement's parameter of getting a kth particle corresponding to wherein minimum multiple goal fitness is updated to individual extreme value X _{k, Pbest}.

12 step, upgrades global optimum particle: calculate the 3rd outside concentrated each interparticle distance that the tenth step obtains, concentrate the particle that non-dominant distribution of particles is the most sparse to be updated to new global optimum particle X around the 3rd outside _gbest.

13 step, upgrades the flying speed of each particle in population and pneumatic layout parameter by following method, gets back to the 8th step;

In population, aerodynamic arrangement's parameter that a kth particle upgraded in last time is with flying speed be this flying speed upgraded of a kth particle is designated as aerodynamic arrangement's parameter is designated as this flying speed upgraded of a kth particle with pneumatic layout parameter for:

$V_k^r=w{V}_k^{r-1}+c_1(X_{k,\mathrm{Pbest}}-{X_k}^{r-1})+c_2(X_{\mathrm{Gbest}}-{X_k}^{r-1})$

$X_k^r=X_k^{r-1}+V_k^r$

Wherein w is inertia weight coefficient, generally gets 0.8; c ₁and c ₂being Studying factors, is the random number between 0 to 1.

If beyond the design bound parameter area of new design helicopter, then aerodynamic arrangement's parameter of this particle of stochastic generation again in the design bound parameter area of new design helicopter and ${V_k}^r=\left[\begin{array}{ccc}0& ...& 0\end{array}\right].$

14 step, according to the 8th step to the method for the 13 step, carries out R time to population and upgrades, and the last the arrive the 3rd outside collection is exported the aerodynamic arrangement's parameter feasible zone border for new design helicopter;

15 step, in any Ge Quyizu aerodynamic arrangement of feasible zone boundaries on either side parameter, is designated as X respectively ₁and X ₂, corresponding flying quality is f (X ₁) and f (X ₂), if right 1≤j≤M, meets f _j(X ₁) > g _j, then X ₁side is feasible zone, X ₂side is infeasible territory, otherwise X ₂side is feasible zone, X ₁side is infeasible territory.

Technique effect of the present invention:

1, multiple aerodynamic arrangements parameter can be analyzed on the impact of flying quality simultaneously, determine the optimal anchor direction of aerodynamic arrangement's parameter, increase work efficiency;

2, other specialties such as flight quality, hub moment, size restriction and structural limitations can be considered to the restriction of aerodynamic parameter.

Accompanying drawing explanation

Fig. 1 is the method flow diagram carrying out helicopter aerodynamic arrangement parameter designing from flying quality angle;

Fig. 2 is the calibration result schematic diagram of embodiment performance software for calculation;

Fig. 3 is the embodiment border of trying to achieve and parameter feasible zone schematic diagram;

Fig. 4 is aerodynamic arrangement's parameter distribution schematic diagram of the initialized particle of embodiment population;

Fig. 5 is aerodynamic arrangement's parameter distribution schematic diagram of the particle of the population that embodiment the 3rd time upgrades, optimal value particle and outside collection particle;

Fig. 6 is aerodynamic arrangement's parameter distribution schematic diagram of the particle of the population that embodiment the 50th time upgrades, optimal value particle and outside collection particle;

Fig. 7 is aerodynamic arrangement's parameter distribution schematic diagram of the particle of the population that embodiment finally exports, optimal value particle and outside collection particle.

Embodiment

Carry out a method for helicopter aerodynamic arrangement parameter designing from flying quality angle, this method comprises the following steps:

The first step, by carrying out Flight to existing or prototype helicopter, obtain the following flying quality of this helicopter, include but not limited to: maximumly have hover out of ground effect weight, have hover out of ground effect ceiling, maximum perpendicular climbing speed, the maximum oblique climb rate, ultimate run boat time, service ceiling and maximum cruise; And the test flight data utilizing Flight to obtain is calibrated the performance software for calculation that this method will be used, make the result of calculation of performance software for calculation suitable with test flight data;

Second step, aerodynamic arrangement's parameter according to existing or prototype helicopter, the physical restriction of the parameter of the parameter area of the wind tunnel experiment of existing or prototype helicopter, existing or prototype helicopter, and other helicopter aerodynamic arrangement parametric statistics data, after determined the impact of the aerodynamic interference between different helicopter component by wind tunnel experiment, determine the design bound newly designing helicopter aerodynamic arrangement parameter, following design procedure should carry out in this given design bound parameter area; Because the impact of aerodynamic arrangement's parameter on helicopter performance has quite a few to come from aerodynamic interference between helicopter component, this aerodynamic interference needs to carry out wind tunnel experiment and determines;

3rd step, according to the main task mission of new design helicopter and needed for the mission requirements taken into account, the flying quality that is existing or prototype helicopter obtained in the first step is adjusted, is newly designed the flying quality target of helicopter;

4th step, the flying quality target of new design helicopter obtained based on the 3rd step, in performance software for calculation, the feasible zone of the aerodynamic arrangement's parameter using feasible zone derivation algorithm to solve new design helicopter in the given design bound parameter area of second step, when solving, according to the similarity of aerodynamic arrangement's parameter requirements, flying quality target is classified, solves each flying quality target feasible zone border separately respectively; In general, for maximumly having hover out of ground effect weight, have hover out of ground effect ceiling, these flying qualitys of maximum perpendicular climbing speed, helicopter is in lift mode, close to the requirement of aerodynamic arrangement's parameter, can classify as helicopter Vertical performance; For the maximum oblique climb rate, ultimate run boat time, these flying qualitys of service ceiling, helicopter is in medium speed and equals the state of flight flown, close to the requirement of aerodynamic arrangement's parameter, can classify as helicopter duration performance; For this flying quality of maximum cruise, helicopter is in large speed and equals the state of flight flown, close to the requirement of aerodynamic arrangement's parameter, can classify as helicopter maximal rate performance; Because this three classes flying quality is probably contradiction to the requirement of aerodynamic arrangement's parameter, when the fixed flying quality of the 3rd step is improper, the nonoverlapping situation of feasible zone may be there is, flying quality be divided into 3 classes conveniently to carry out the adjustment of flying quality target;

5th step, all feasible zones to be put together, overlapping region is exactly the feasible zone newly designing helicopter aerodynamic arrangement parameter, if feasible zone does not have overlapping explanation may not meet the parameter combinations of all flying quality targets simultaneously, need to get back to the 3rd step and flying quality target is redefined;

6th step, consider flight quality, hub moment, size restriction and structural limitations, progressively improve flying quality target, feasible zone is reduced gradually, after successive ignition reduces, finally determine one group of feasible aerodynamic arrangement's parameter being positioned at feasible zone, this group aerodynamic arrangement parameter can meet the requirement of flying quality target;

7th step, according to this group aerodynamic arrangement parameter, aerodynamic arrangement's parameter that is existing or prototype helicopter is modified, and Flight is carried out to amended helicopter, be aerodynamic arrangement's parameter of new design helicopter by the aerodynamic arrangement's parameter after checking.

Feasible zone derivation algorithm method for solving described in 4th step is as follows:

The known parameters set in this method is as follows:

M flying quality target of new design helicopter, is expressed as vectorial G=[g ₁g ₂g _jg _m] ^t, wherein, g _jrepresent a jth flying quality target, 1≤j≤M;

N number of aerodynamic arrangement parameter of new design helicopter, is expressed as vectorial X=[x ₁x ₂x _ix _n] ^t, wherein, x _irepresent i-th aerodynamic arrangement's parameter, 1≤i≤N;

The design bound parameter area of new design helicopter, the upper limit is expressed as X _max=[x _max1x _max2x _maxN] ^t, lower limit is expressed as X _min=[x _min1x _min2x _minN] ^t, make for 1≤i≤N, x _maxi> x _i> x _mini;

This method solution procedure is as follows:

The first step, initialization population, this population includes L particle altogether, is expressed as: Swarm ₁, Swarm ₂... Swarm _kswarm _l, wherein, 1≤k≤L, can be taken as 50 for this problem L, to aerodynamic arrangement's parameter of each particle this particle of stochastic generation in the design bound parameter area of new design helicopter, and a kth particle Swarm _kaerodynamic arrangement's parameter that initialization generates is X _k;

Second step, calculate the flying quality vector sum multiple goal fitness of each particle, calculation procedure is as follows:

A kth particle Swarm _kflying quality be f (X _k), multiple goal fitness is Fitness (X _k), wherein, f (X _k)=[f ₁(X _k) f ₂(X _k) ... f _m(X _k)] ^t, for described flying quality f (X _k), if right 1≤j≤M, meets f _j(X _k) > g _j, this aerodynamic arrangement parameter X is called feasible solution, and the aerodynamic arrangement's parameter sets be made up of all feasible solutions is called the feasible zone of aerodynamic arrangement's parameter, in order to weigh current flight performance f (X _k) and the difference of flying quality target G, definition multiple goal fitness multiple goal fitness is less, and show that the flying quality distance feasible zone border of particle is nearer, owing to adopting method of value solving, particle can not be positioned on border completely, when | Fitness (X _k) | during < ε, think X _kfor feasible zone Boundary Solutions, ε is the threshold value preset, and can be decided to be 0.0005 for this problem;

3rd step, solve the non-dominant collection in current particle group, solving of non-dominant collection is as follows:

In order to weigh the difference of each particle aerodynamic arrangement parameter, define the distance between l particle and a kth particle wherein, be i-th aerodynamic arrangement's parameter of l particle, for i-th aerodynamic arrangement's parameter of a kth particle, for each particle, find out all particles being less than predetermined threshold R with its distance, for a kth particle Swarm _ks the particle being less than predetermined threshold R with its distance is expressed as Swarm ₁, Swarm ₂... Swarm _s, Swarm _s, 1≤s≤S, Swarm ₁for Swarm _kparticle self, the optimal particle Swarm of a definition kth particle _bestfor: particle Swarm _s, its multiple goal fitness is Fitness _s, as particle Swarm _bestwith particle Swarm _sbetween distance distance _{best, s}during < R, meet particle Swarm _bestmultiple goal fitness Fitness _best< Fitness _s; The set of all optimal particle compositions is non-dominant collection;

4th step, saves as the first outside collection by the non-dominant set that the 3rd step is tried to achieve.

5th step, is set to particle self by the individual extreme value of each particle, and aerodynamic arrangement's parameter of the individual extreme value of a kth particle is designated as X _{k, Pbest}, the multiple goal fitness of the individual extreme value of a kth particle is designated as Fitness (X _{k, Pbest});

6th step, is set to global optimum particle Gbest by particle minimum for multiple goal fitness in population, aerodynamic arrangement's parameter of global optimum particle Gbest is designated as X _gbest, the multiple goal fitness of global optimum particle Gbest is designated as Fitness (X _gbest).

7th step, upgrades the flying speed of each particle in population and pneumatic layout parameter the 1st time by following method;

In population, the dynamic layout parameter that a kth particle generates when first step initialization is designated as X _k, the flying speed upgraded for the 1st time of a kth particle is designated as $V_k^1={{\left(\begin{array}{cccccc}{v}_1& v_2& ...& v_i& ...& v_N\end{array}\right)}_k}^1,$ The aerodynamic arrangement's parameter upgraded for 1st time of a kth particle is designated as wherein:

$V_k^1=c_1(X_{k,\mathrm{Pbest}}-X_k)+c_2(X_{\mathrm{Gbest}}-X_k)$

$X_k^1=X_k+V_k^1$

Wherein, c ₁and c ₂being Studying factors, is the random number between 0 to 1.

If beyond the design bound parameter area of new design helicopter, then aerodynamic arrangement's parameter of this particle of stochastic generation again in the design bound parameter area of new design helicopter and ${V_k}^1=\left[\begin{array}{ccc}0& ...& 0\end{array}\right].$

8th step, according to the method for second step, calculates flying quality and the multiple goal fitness of each particle after upgrading;

9th step, according to the method for the 3rd step, solves the non-dominant collection in current particle group;

Tenth step, the first outside non-dominant set of current particle group being put into the 4th step is concentrated, and the particle of deduplication, to the obtain second outside collection, the second outside non-dominant collection concentrated is obtained by the method for the 3rd step, be the 3rd outside collection with this non-dominant collection, the 3rd outside approximate feasible zone border of collection both for trying to achieve.

11 step, upgrade the individual extreme value of each particle: each particle in population has oneself an individual extreme value, to the kth particle repeatedly upgraded, the each multiple goal fitness upgraded of record, obtain multiple multiple goal fitness, aerodynamic arrangement's parameter of getting a kth particle corresponding to wherein minimum multiple goal fitness is updated to individual extreme value X _{k, Pbest}.

12 step, upgrades global optimum particle: calculate the 3rd outside concentrated each interparticle distance that the tenth step obtains, concentrate the particle that non-dominant distribution of particles is the most sparse to be updated to new global optimum particle X around the 3rd outside _gbest.

13 step, upgrades the flying speed of each particle in population and pneumatic layout parameter by following method, gets back to the 8th step;

In population, aerodynamic arrangement's parameter that a kth particle upgraded in last time is with flying speed be this flying speed upgraded of a kth particle is designated as aerodynamic arrangement's parameter is designated as this flying speed upgraded of a kth particle with pneumatic layout parameter for:

$V_k^r=w{V}_k^{r-1}+c_1(X_{k,\mathrm{Pbest}}-{X_k}^{r-1})+c_2(X_{\mathrm{Gbest}}-{X_k}^{r-1})$

$X_k^r=X_k^{r-1}+V_k^r$

Wherein w is inertia weight coefficient, generally gets 0.8; c ₁and c ₂being Studying factors, is the random number between 0 to 1.

If beyond the design bound parameter area of new design helicopter, then aerodynamic arrangement's parameter of this particle of stochastic generation again in the design bound parameter area of new design helicopter and ${V_k}^r=\left[\begin{array}{ccc}0& ...& 0\end{array}\right].$

14 step, according to the 8th step to the method for the 13 step, carries out R time to population and upgrades, and the last the arrive the 3rd outside collection is exported the aerodynamic arrangement's parameter feasible zone border for new design helicopter;

15 step, in any Ge Quyizu aerodynamic arrangement of feasible zone boundaries on either side parameter, is designated as X respectively ₁and X ₂, corresponding flying quality is f (X ₁) and f (X ₂), if right 1≤j≤M, meets f _j(X ₁) > g _j, then X ₁side is feasible zone, X ₂side is infeasible territory, otherwise X ₂side is feasible zone, X ₁side is infeasible territory.

Embodiment 1: for aerodynamic arrangement's parameter designing of certain type helicopter, the present invention is described in further detail below: a kind of method of carrying out helicopter aerodynamic arrangement parameter designing from flying quality angle, this method comprises the following steps:

The first step, by carrying out Flight to existing or prototype helicopter, obtain the following flying quality of this helicopter, include but not limited to: maximumly have hover out of ground effect weight, have hover out of ground effect ceiling, maximum perpendicular climbing speed, the maximum oblique climb rate, ultimate run boat time, service ceiling and maximum cruise; And the test flight data utilizing Flight to obtain is calibrated the performance software for calculation that this method will be used, make the result of calculation of performance software for calculation suitable with test flight data, as seen from Figure 2, after calibration, performance result of calculation is substantially suitable with result of taking a flight test;

Second step, aerodynamic arrangement's parameter according to existing or prototype helicopter, the physical restriction of the parameter of the parameter area of the wind tunnel experiment of existing or prototype helicopter, existing or prototype helicopter, and other helicopter aerodynamic arrangement parametric statistics data, after determined the impact of the aerodynamic interference between different helicopter component by wind tunnel experiment, determine the design bound newly designing helicopter aerodynamic arrangement parameter, following design procedure should carry out in this given design bound parameter area;

The design bound of table 1 rotor shaft parameter

Parameter name	Unit	Lower limit	The upper limit
				Rotor shaft height	m	-0.2	0.2
Forward tilting angle of rotor shaft	Degree	-5	5

3rd step, according to the main task mission of new design helicopter and needed for the mission requirements taken into account, the flying quality that is existing or prototype helicopter obtained in the first step is adjusted, is newly designed the flying quality target of helicopter;

The helicopter performance objective that table 2 is new

Performance title	Unit	Target
			During maximum boat	Hour	Increase 3%
Ultimate run	km	Increase 3%

4th step, the flying quality target of new design helicopter obtained based on the 3rd step, in performance software for calculation, the feasible zone of the aerodynamic arrangement's parameter using feasible zone derivation algorithm to solve new design helicopter in the given design bound parameter area of second step, when solving, according to the similarity of aerodynamic arrangement's parameter requirements, flying quality target is classified, solves each flying quality target feasible zone border separately respectively;

5th step, all feasible zones to be put together, overlapping region is exactly the feasible zone newly designing helicopter aerodynamic arrangement parameter, if feasible zone does not have overlapping explanation may not meet the parameter combinations of all flying quality targets simultaneously, need to get back to the 3rd step and flying quality target is redefined;

6th step, consider flight quality, hub moment, size restriction and structural limitations, progressively improve flying quality target, feasible zone is reduced gradually, after successive ignition reduces, finally determine one group of feasible aerodynamic arrangement's parameter being positioned at feasible zone, this group aerodynamic arrangement parameter can meet the requirement of flying quality target;

The final design result of table 3 rotor shaft parameter

Parameter name	Unit	Knots modification
			Rotor shaft height	m	Reduce 0.05m
Forward tilting angle of rotor shaft	Degree	Increase 4 degree

7th step, according to this group aerodynamic arrangement parameter, aerodynamic arrangement's parameter that is existing or prototype helicopter is modified, and Flight is carried out to amended helicopter, be aerodynamic arrangement's parameter of new design helicopter by the aerodynamic arrangement's parameter after checking.

Table 4 helicopter performance objective reaches situation

Performance title	Unit	Final adjustment result
			During maximum boat	Hour	Increase 3%
Ultimate run	km	Increase 2%

Feasible zone derivation algorithm method for solving described in 4th step is as follows:

The known parameters set in this method is as follows:

2 flying quality targets of new design helicopter, when comprising maximum boat and ultimate run, are expressed as vectorial G=[1.03 1.03] ^t;

2 aerodynamic arrangement's parameters of new design helicopter, are expressed as vectorial X=[x ₁x ₂] ^t;

The design bound parameter area of new design helicopter, the upper limit is expressed as X _max=[0.2 5] ^t, lower limit is expressed as X _min=[-0.2-5] ^t;

This method solution procedure is as follows:

The first step, initialization population, this population includes 50 particles altogether, and L=50 is expressed as: Swarm ₁, Swarm ₂... Swarm _kswarm ₅₀, wherein, 1≤k≤50, to aerodynamic arrangement's parameter of each particle this particle of stochastic generation in the design bound parameter area of new design helicopter, a kth particle Swarm _kaerodynamic arrangement's parameter that initialization generates is X _k, initialized distribution of particles is as Fig. 4;

Second step, calculate the flying quality vector sum multiple goal fitness of each particle, calculation procedure is as follows:

A kth particle Swarm _kflying quality be f (X _k), multiple goal fitness is Fitness (X _k), wherein, f (X _k)=[f ₁(X _k) f ₂(X _k)] ^t, for described flying quality f (X _k), if right 1≤j≤2, meet f _j(X _k) > g _j, this aerodynamic arrangement parameter X is called feasible solution, and the aerodynamic arrangement's parameter sets be made up of all feasible solutions is called the feasible zone of aerodynamic arrangement's parameter, in order to weigh current flight performance f (X _k) and the difference of flying quality target G, definition multiple goal fitness when | Fitness (X _k) | during < ε, X _kfor feasible zone Boundary Solutions, ε is the threshold value preset, ε=0.0005;

3rd step, solve the non-dominant collection in current particle group, solving of non-dominant collection is as follows:

In order to weigh the difference of each particle aerodynamic arrangement parameter, define the distance between l particle and a kth particle wherein, be i-th aerodynamic arrangement's parameter of l particle, for i-th aerodynamic arrangement's parameter of a kth particle, for each particle, find out all particles being less than predetermined threshold R with its distance, for a kth particle Swarm _ks the particle being less than predetermined threshold R with its distance is expressed as Swarm ₁, Swarm ₂... Swarm _s, Swarm _s, 1≤s≤S, Swarm ₁for Swarm _kparticle self, the optimal particle Swarm of a definition kth particle _bestfor: particle Swarm _s, its multiple goal fitness is Fitness _s, as particle Swarm _bestwith particle Swarm _sbetween distance distance _{best, s}during < R, meet particle Swarm _bestmultiple goal fitness Fitness _best< Fitness _s; The set of all optimal particle compositions is non-dominant collection;

4th step, saves as the first outside collection by the non-dominant set that the 3rd step is tried to achieve.

5th step, is set to particle self by the individual extreme value of each particle, and aerodynamic arrangement's parameter of the individual extreme value of a kth particle is designated as X _{k, Pbest}, the multiple goal fitness of the individual extreme value of a kth particle is designated as Fitness (X _{k, Pbest});

6th step, is set to global optimum particle Gbest by particle minimum for multiple goal fitness in population, aerodynamic arrangement's parameter of global optimum particle Gbest is designated as X _gbest, the multiple goal fitness of global optimum particle Gbest is designated as Fitness (X _gbest).

7th step, upgrades the flying speed of each particle in population and pneumatic layout parameter the 1st time by following method;

In population, the dynamic layout parameter that a kth particle generates when first step initialization is designated as X _k, the flying speed upgraded for the 1st time of a kth particle is designated as $V_k^1={{\left(\begin{array}{cc}{v}_1& v_2\end{array}\right)}_k}^1,$ The aerodynamic arrangement's parameter upgraded for 1st time of a kth particle is designated as wherein:

$V_k^1=c_1(X_{k,\mathrm{Pbest}}-X_k)+c_2(X_{\mathrm{Gbest}}-X_k)$

$X_k^1=X_k+V_k^1$

Wherein, c ₁and c ₂being Studying factors, is the random number between 0 to 1.

If beyond the design bound parameter area of new design helicopter, then aerodynamic arrangement's parameter of this particle of stochastic generation again in the design bound parameter area of new design helicopter and ${V_k}^1=\left[\begin{array}{cc}0& 0\end{array}\right].$

8th step, according to the method for second step, calculates flying quality and the multiple goal fitness of each particle after upgrading;

9th step, according to the method for the 3rd step, solves the non-dominant collection in current particle group;

Tenth step, the first outside non-dominant set of current particle group being put into the 4th step is concentrated, and the particle of deduplication, to the obtain second outside collection, the second outside non-dominant collection concentrated is obtained by the method for the 3rd step, be the 3rd outside collection with this non-dominant collection, upgrade for the 3rd time and the 50th time upgrades time the 3rd outsidely to collect respectively as Fig. 5 and Fig. 6.

11 step, upgrade the individual extreme value of each particle: each particle in population has oneself an individual extreme value, to the kth particle repeatedly upgraded, the each multiple goal fitness upgraded of record, obtain multiple multiple goal fitness, aerodynamic arrangement's parameter of getting a kth particle corresponding to wherein minimum multiple goal fitness is updated to individual extreme value X _{k, Pbest}.

12 step, upgrades global optimum particle: calculate the 3rd outside concentrated each interparticle distance that the tenth step obtains, concentrate the particle that non-dominant distribution of particles is the most sparse to be updated to new global optimum particle X around the 3rd outside _gbest, the 3rd renewal and global optimum particle when upgrading for the 50th time are respectively as Fig. 5 and Fig. 6.

13 step, upgrades the flying speed of each particle in population and pneumatic layout parameter by following method, gets back to the 8th step;

In population, aerodynamic arrangement's parameter that a kth particle upgraded in last time is with flying speed be this flying speed upgraded of a kth particle is designated as aerodynamic arrangement's parameter is designated as this flying speed upgraded of a kth particle with pneumatic layout parameter for:

$V_k^r=w{V}_k^{r-1}+c_1(X_{k,\mathrm{Pbest}}-{X_k}^{r-1})+c_2(X_{\mathrm{Gbest}}-{X_k}^{r-1})$

$X_k^r=X_k^{r-1}+V_k^r$

Wherein w is inertia weight coefficient, w=0.8; c ₁and c ₂being Studying factors, is the random number between 0 to 1.s

If beyond the design bound parameter area of new design helicopter, then aerodynamic arrangement's parameter of this particle of stochastic generation again in the design bound parameter area of new design helicopter and ${V_k}^r=\left[\begin{array}{cc}0& 0\end{array}\right],$ 3rd renewal and particle when upgrading for the 50th time are respectively as Fig. 5 and Fig. 6.

14 step, according to the 8th step to the method for the 13 step, carries out R time to population and upgrades, and the last the arrive the 3rd outside collection is exported the aerodynamic arrangement's parameter feasible zone border for new design helicopter, and the finally obtain the 3rd outside collection as shown in Figure 7;

15 step, in any Ge Quyizu aerodynamic arrangement of feasible zone boundaries on either side parameter, is designated as X respectively ₁and X ₂, corresponding flying quality is f (X ₁) and f (X ₂), if right 1≤j≤M, meets f _j(X ₁) > g _j, then X ₁side is feasible zone, X ₂side is infeasible territory, otherwise X ₂side is feasible zone, X ₁side is infeasible territory, and be feasible zone on the left of the feasible zone border as calculated shown in Fig. 7, right side is infeasible territory.

Claims (2)

1. carry out a method for helicopter aerodynamic arrangement parameter designing from flying quality angle, it is characterized in that, this method comprises the following steps:

The first step, by carrying out Flight to existing or prototype helicopter, obtain the following flying quality of this helicopter, include but not limited to: maximumly have hover out of ground effect weight, have hover out of ground effect ceiling, maximum perpendicular climbing speed, the maximum oblique climb rate, ultimate run boat time, service ceiling and maximum cruise; And the test flight data utilizing Flight to obtain is calibrated the performance software for calculation that this method will be used, make the result of calculation of performance software for calculation suitable with test flight data;

Second step, aerodynamic arrangement's parameter according to existing or prototype helicopter, the physical restriction of the parameter of the parameter area of the wind tunnel experiment of existing or prototype helicopter, existing or prototype helicopter, and other helicopter aerodynamic arrangement parametric statistics data, after determined the impact of the aerodynamic interference between different helicopter component by wind tunnel experiment, determine the design bound newly designing helicopter aerodynamic arrangement parameter, following design procedure should carry out in this given design bound parameter area;

3rd step, according to the main task mission of new design helicopter and needed for the mission requirements taken into account, the flying quality that is existing or prototype helicopter obtained in the first step is adjusted, is newly designed the flying quality target of helicopter;

4th step, the flying quality target of new design helicopter obtained based on the 3rd step, in performance software for calculation, the feasible zone of the aerodynamic arrangement's parameter using feasible zone derivation algorithm to solve new design helicopter in the given design bound parameter area of second step, when solving, according to the similarity of aerodynamic arrangement's parameter requirements, flying quality target is classified, solves each flying quality target feasible zone border separately respectively;

5th step, all feasible zones to be put together, overlapping region is exactly the feasible zone newly designing helicopter aerodynamic arrangement parameter, if feasible zone does not have overlapping explanation may not meet the parameter combinations of all flying quality targets simultaneously, need to get back to the 3rd step and flying quality target is redefined;

6th step, consider flight quality, hub moment, size restriction and structural limitations, progressively improve flying quality target, feasible zone is reduced gradually, after successive ignition reduces, finally determine one group of feasible aerodynamic arrangement's parameter being positioned at feasible zone, this group aerodynamic arrangement parameter can meet the requirement of flying quality target;

7th step, according to this group aerodynamic arrangement parameter, aerodynamic arrangement's parameter that is existing or prototype helicopter is modified, and Flight is carried out to amended helicopter, be aerodynamic arrangement's parameter of new design helicopter by the aerodynamic arrangement's parameter after checking.

2. a kind of method of carrying out helicopter aerodynamic arrangement parameter designing from flying quality angle as claimed in claim 1, it is characterized in that, the feasible zone derivation algorithm method for solving described in the 4th step is as follows:

The known parameters set in this method is as follows:

M flying quality target of new design helicopter, is expressed as vectorial G=[g ₁g ₂... g _jg _m] ^t, wherein, g _jrepresent a jth flying quality target, 1≤j≤M;

N number of aerodynamic arrangement parameter of new design helicopter, is expressed as vectorial X=[x ₁x ₂x _ix _n] ^t, wherein, x _irepresent i-th aerodynamic arrangement's parameter, 1≤i≤N;

The design bound parameter area of new design helicopter, the upper limit is expressed as X _max=[x _max1x _max2x _maxN] ^t, lower limit is expressed as X _min=[x _min1x _min2x _minN] ^t, make for 1≤i≤N, x _maxi> x _i> x _mini;

This method solution procedure is as follows:

The first step, initialization population, this population includes L particle altogether, is expressed as: Swarm ₁, Swarm ₂... Swarm _kswarm _l, wherein, 1≤k≤L, to aerodynamic arrangement's parameter of each particle this particle of stochastic generation in the design bound parameter area of new design helicopter, a kth particle Swarm _kaerodynamic arrangement's parameter that initialization generates is X _k;

Second step, calculate the flying quality vector sum multiple goal fitness of each particle, calculation procedure is as follows:

A kth particle Swarm _kflying quality be f (X _k), multiple goal fitness is Fitness (X _k), wherein, f (X _k)=[f ₁(X _k) f ₂(X _k) ... f _m(X _k)] ^t, for described flying quality f (X _k), if right 1≤j≤M, meets f _j(X _k) > g _j, this aerodynamic arrangement parameter X is called feasible solution, and the aerodynamic arrangement's parameter sets be made up of all feasible solutions is called the feasible zone of aerodynamic arrangement's parameter, in order to weigh current flight performance f (X _k) and the difference of flying quality target G, definition multiple goal fitness when time, X _kfor feasible zone Boundary Solutions, ε is the threshold value preset;

3rd step, solve the non-dominant collection in current particle group, solving of non-dominant collection is as follows:

In order to weigh the difference of each particle aerodynamic arrangement parameter, define the distance between l particle and a kth particle wherein, be i-th aerodynamic arrangement's parameter of l particle, for i-th aerodynamic arrangement's parameter of a kth particle, for each particle, find out all particles being less than predetermined threshold R with its distance, for a kth particle Swarm _ks the particle being less than predetermined threshold R with its distance is expressed as Swarm ₁, Swarm ₂... Swarm _s, Swarm _s, 1≤s≤S, Swarm ₁for Swarm _kparticle self, the optimal particle Swarm of a definition kth particle _bestfor: particle Swarm _s, its multiple goal fitness is Fitness _s, as particle Swarm _bestwith particle Swarm _sbetween distance distance _{best, s}during < R, meet particle Swarm _bestmultiple goal fitness Fitness _best< Fitness _s; The set of all optimal particle compositions is non-dominant collection;

4th step, saves as the first outside collection by the non-dominant set that the 3rd step is tried to achieve;

5th step, is set to particle self by the individual extreme value of each particle, and aerodynamic arrangement's parameter of the individual extreme value of a kth particle is designated as X _{k, Pbest}, the multiple goal fitness of the individual extreme value of a kth particle is designated as Fitness (X _{k, Pbest});

6th step, is set to global optimum particle Gbest by particle minimum for multiple goal fitness in population, aerodynamic arrangement's parameter of global optimum particle Gbest is designated as X _gbest, the multiple goal fitness of global optimum particle Gbest is designated as Fitness (X _gbest);

7th step, upgrades the flying speed of each particle in population and pneumatic layout parameter the 1st time by following method;

In population, the dynamic layout parameter that a kth particle generates when first step initialization is designated as X _k, the flying speed upgraded for the 1st time of a kth particle is designated as $V_k^1={{\left(\begin{array}{cccccc}{v}_1& v_2& ...& v_i& ...& v_N\end{array}\right)}_k}^1,$ The aerodynamic arrangement's parameter upgraded for 1st time of a kth particle is designated as wherein:

$V_k^1=c_1(X_{k,\mathrm{Pbest}}-X_k)+c_2(X_{\mathrm{Gbest}}-X_k)$

$X_k^1=X_k+V_k^1$

Wherein, c ₁and c ₂being Studying factors, is the random number between 0 to 1;

If beyond the design bound parameter area of new design helicopter, then aerodynamic arrangement's parameter of this particle of stochastic generation again in the design bound parameter area of new design helicopter and ${V_k}^1=\left[\begin{array}{ccc}0& ...& 0\end{array}\right];$

8th step, according to the method for second step, calculates flying quality and the multiple goal fitness of each particle after upgrading;

9th step, according to the method for the 3rd step, solves the non-dominant collection in current particle group;

Tenth step, the first outside non-dominant set of current particle group being put into the 4th step is concentrated, and the particle of deduplication, to the obtain second outside collection, obtaining the second outside concentrated non-dominant collection by the method for the 3rd step, is the 3rd outside collection with this non-dominant collection;

11 step, upgrade the individual extreme value of each particle: each particle in population has oneself an individual extreme value, to the kth particle repeatedly upgraded, the each multiple goal fitness upgraded of record, obtain multiple multiple goal fitness, aerodynamic arrangement's parameter of getting a kth particle corresponding to wherein minimum multiple goal fitness is updated to individual extreme value X _{k, Pbest};

12 step, upgrades global optimum particle: calculate the 3rd outside concentrated each interparticle distance that the tenth step obtains, concentrate the particle that non-dominant distribution of particles is the most sparse to be updated to new global optimum particle X around the 3rd outside _gbest;

13 step, upgrades the flying speed of each particle in population and pneumatic layout parameter by following method, gets back to the 8th step;

In population, aerodynamic arrangement's parameter that a kth particle upgraded in last time is with flying speed be this flying speed upgraded of a kth particle is designated as aerodynamic arrangement's parameter is designated as this flying speed upgraded of a kth particle with pneumatic layout parameter for:

$V_k^r=w{V}_k^{r-1}+c_1(X_{k,\mathrm{Pbest}}-{X_k}^{r-1})+c_2(X_{\mathrm{Gbest}}-{X_k}^{r-1})$

$X_k^r=X_k^{r-1}+V_k^r$

Wherein w is inertia weight coefficient, generally gets 0.8; c ₁and c ₂being Studying factors, is the random number between 0 to 1;

If beyond the design bound parameter area of new design helicopter, then aerodynamic arrangement's parameter of this particle of stochastic generation again in the design bound parameter area of new design helicopter and ${V_k}^r=\left[\begin{array}{ccc}0& ...& 0\end{array}\right];$

14 step, according to the 8th step to the method for the 13 step, carries out R time to population and upgrades, and the last the arrive the 3rd outside collection is exported the aerodynamic arrangement's parameter feasible zone border for new design helicopter;

15 step, in any Ge Quyizu aerodynamic arrangement of feasible zone boundaries on either side parameter, is designated as X respectively ₁and X ₂, corresponding flying quality is f (X ₁) and f (X ₂), if right 1≤j≤M, meets f _j(X ₁) > g _j, then X ₁side is feasible zone, X ₂side is infeasible territory, otherwise X ₂side is feasible zone, X ₁side is infeasible territory.