Bionic unmanned aerial vehicle three-dimensional dynamic integrated sensing method

Abstract

The invention belongs to the field of aircraft design and intelligent sensing, particularly provides a three-dimensional dynamic integrated sensing method for a bionic unmanned aerial vehicle, relates to wing three-dimensional flexible dynamic real-time reconstruction and airfoil velocity field real-time reconstruction for bionic flapping-wing aircrafts, and aims to meet the sensing design requirements for the bionic flapping-wing aircrafts. According to the method, an open-circuit output voltage signal model V (t) and a short-circuit output current signal model I (t) of the integrated wing are creatively provided and used for representing the mapping relation between the signal amplitude and the integrated wing motion parameters such as the flapping wing frequency f, the flapping wing angle theta (t) and the rigid infinitesimal pitch angle gamma i (t), and according to the actually-measured signal amplitude and mapping analysis, the motion parameters of the integrated wing can be obtained. Real-time wing surface flexible parameters are analyzed, dynamic sensing of targets such as the flapping wing frequency, the flapping wing angle and wing surface deformation parameters of flapping wing motion is achieved, and three-dimensional reconstruction of wing three-dimensional flexible dynamic and wing surface speed fields of the bionic flapping wing aircraft is achieved.

Description

Technical Field

[0001] The present invention belongs to the field of aircraft design and intelligent sensing, and particularly provides a three-dimensional dynamic integrated sensing method for a bionic unmanned aircraft, which involves the three-dimensional flexible dynamic real-time reconstruction of the wing of a bionic flapping-wing aircraft and the real-time reconstruction of the wing surface velocity field. Background Art

[0002] As one of the common bionic unmanned aircraft, the bionic flapping-wing aircraft has a wide range of applications in many fields. During the flapping flight of the bionic flapping-wing aircraft, the perception ability of the wing motion form will provide important control inputs for the flight control system, optimize the flight controllability and stability of the bionic flapping-wing aircraft, and is an important construction link for intelligent autonomous flight applications. Secondly, the flexible motion recognition of the wing has a positive impact on understanding the aerodynamic generation mechanism and optimizing the energy efficiency. At present, methods such as Hall sensors or optoelectronic sensors are commonly used to monitor the flapping flexible motion, but this type of non-contact sensing method has obvious defects for bionic flapping-wing aircraft. First, the common measurement system is large in volume and heavy in mass, which will increase huge flight costs for bionic flapping-wing aircraft with weak load capacity. Second, the conventional sensing system is an active system, which consumes a large amount of on-board energy during operation and has a negative impact on the endurance of the bionic flapping-wing aircraft. Third, the current on-board sensing only measures a single index of the flapping wing, especially the measurement of the flexibility of the flexible wing surface is missing, and the integration level of the wing motion sensing system is not high, greatly weakening the functionality applied to the flexible monitoring of the bionic flapping-wing aircraft wing.

[0003] In view of the important role of wing motion state recognition in the intelligent perception and aerodynamic optimization design of bionic flapping-wing aircraft, it is urgent to implement a new method to realize the multi-modal perception of the motion state and flexible deformation of the flexible wing under the limitation of weak aerodynamic load of the bionic flapping wing without affecting the aerodynamic performance and flight ability of the flexible wing itself, especially to realize the fusion sensing of the real-time three-dimensional reconstruction of the flexible wing shape and the reconstruction of the wing surface velocity field under on-board application. Summary of the Invention

[0004] The purpose of the present invention is to propose a three-dimensional dynamic integrated sensing method for a bionic unmanned aircraft, which realizes on-board sensing for the three-dimensional flexible dynamics of a bionic wing and the reconstruction of the wing surface velocity field, and realizes the high-integration real-time three-dimensional reconstruction of the three-dimensional flexibility dynamics of the wing and the reconstruction of the wing surface velocity field based on the principle of an electrostatic nanogenerator, meeting the sensing design requirements for bionic flapping-wing aircraft.

[0005] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0006] A three-dimensional dynamic integrated sensing method for a bionic unmanned aircraft, characterized by comprising the following steps:

[0007] Map and characterize the flapping motion of the integrated wing as an open - circuit output voltage signal model and a short - circuit output current signal model;

[0008] Collect the voltage signal amplitude and current signal amplitude output by the integrated wing in real - time, introduce them into the open - circuit output voltage signal model and the short - circuit output current signal model, and obtain the maximum flapping angle within the flapping period and the maximum pitching angle of the rigid micro - element;

[0009] Introduce the maximum flapping angle within the flapping period and the maximum pitching angle of the rigid micro - element into the wing surface flexible motion empirical model to obtain the wing surface flexible motion law, and complete the airborne sensing for the three - dimensional flexible dynamics of the bionic wing and the reconstruction of the wing surface velocity field.

[0010] Furthermore, the open - circuit output voltage signal model of the integrated wing is expressed as V(t), specifically:

[0011]

[0012] Ω' T =[x'y'01]

[0013] Among them, σ T is the bound charge density of the friction medium layer, ε(r) is the dielectric constant of the observation space, a is the length of the nano - generator sensitive unit, b is the width of the nano - generator sensitive unit, and Δc is the distance from the upper edge of the nano - generator sensitive unit to the leading edge of the wing; Φ ub is the transformation matrix from the rigid micro - element coordinate system of the upper wing surface to the body coordinate system, Φ lb is the transformation matrix from the rigid micro - element coordinate system of the lower wing surface to the body coordinate system, Ω' T is the coordinate of the friction medium layer region of the integrated wing in the rigid micro - element coordinate system, and Ω is the coordinate of the center point of the conductive layer on the upper wing surface.

[0014] Furthermore, the short - circuit output current signal model of the integrated wing is expressed as I(t), specifically:

[0015]

[0016] Ω' T =[x'y'01]

[0017] Among them, σ T is the bound charge density of the friction medium layer, σ u (t) is the free charge density of the conductive layer, s is the integration region for calculating the current on the conductive layer; ε(r) is the dielectric constant of the observation space, a is the length of the nano - generator sensitive unit, b is the width of the nano - generator sensitive unit, and Δc is the distance from the upper edge of the nano - generator sensitive unit to the leading edge of the wing, Φ ubis the transformation matrix from the rigid body micro-element coordinate system of the upper wing surface to the body coordinate system, Φ lb is the transformation matrix from the rigid body micro-element coordinate system of the lower wing surface to the body coordinate system, Ω' T is the coordinate of the integrated fin wing friction medium layer region in the rigid body micro-element coordinate system, and Ω is the coordinate of the center point of the upper wing surface conductive layer.

[0018] Furthermore, in the open-circuit output voltage signal model and the short-circuit output current signal model, the transformation matrix Φ from the rigid body micro-element coordinate system of the upper wing surface to the body coordinate system ub Specifically:

[0019]

[0020] T iu =[0 Δw 0]

[0021]

[0022] where I is the identity matrix, γ i is the pitch angle of the wing surface rigid micro-element, Δw is the distance between the central axis of the rigid micro-element and the wing root of the fin wing, θ0 is the initial phase angle of the flapping wing, and θ is the flapping angle of the fin wing.

[0023] Furthermore, in the open-circuit output voltage signal model and the short-circuit output current signal model, the transformation matrix Φ from the rigid body micro-element coordinate system of the lower wing surface to the body coordinate system lb Specifically:

[0024]

[0025] T il =[0 Δw 0]

[0026]

[0027] where I is the identity matrix, γ i is the pitch angle of the wing surface rigid micro-element, Δw is the distance between the central axis of the rigid micro-element and the wing root of the fin wing, θ0 is the initial phase angle of the flapping wing, and θ is the flapping angle of the fin wing.

[0028] Furthermore, in the open-circuit output voltage signal model and the short-circuit output current signal model, the coordinate of the conductive layer region in the rigid body micro-element coordinate system is specifically: Ω' u =[x' y' -(d + Δd) 1], where d is the thickness of the upper fin wing friction medium layer, and Δd is the model accuracy correction parameter;

[0029] Furthermore, in the open-circuit output voltage signal model and the short-circuit output current signal model, the coordinate of the center point of the upper wing surface conductive layer Ω is specifically:

[0030] Furthermore, the wing surface flexible motion experience model is expressed as:

[0031]

[0032] where θ is the flapping angle of the wing, and γ i is the pitching angle of the rigid microelement of the wing surface; θ max is the maximum flapping angle within the flapping period, and γ max is the maximum pitching angle of the rigid microelement within the flapping period, f is the flapping frequency, and w is the wingspan length of the wing.

[0033] Based on the above technical solutions, the beneficial effects of the present invention are as follows:

[0034] The present invention provides a three-dimensional dynamic integrated sensing method for a bionic unmanned aerial vehicle, which is used to realize the three-dimensional flexible dynamic reconstruction of the wing and the reconstruction of the wing surface velocity field during the flapping flight of the bionic flapping-wing aircraft; the present invention creatively proposes an open-circuit output voltage signal model V(t) and a short-circuit output current signal model I(t) of the integrated wing, which are used to characterize the mapping relationship between the signal amplitude and the integrated wing motion parameters such as the flapping frequency f, the flapping angle θ(t), and the pitching angle γ i (t) of the rigid microelement. According to the actually measured signal amplitude and mapping analysis, the real-time wing surface flexible parameters are analyzed to achieve the dynamic sensing of the flapping frequency, flapping angle, wing surface deformation parameters, etc. of the flapping motion, and the three-dimensional reconstruction of the wing surface shape and motion velocity field is realized; moreover, the three-dimensional dynamic integrated sensing process relies on the integration of micro-nano energy, continuously forms energy output during the flapping process, the signal output process of the wing surface flexible reconstruction sensing no longer consumes on-board energy, and the integrated wing is used as a self-powered sensing functional device. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic structural diagram of the integrated wing device in the present invention.

[0036] Figure 2 It is a schematic cross-sectional structural diagram of the integrated wing device in the present invention.

[0037] Figure 3 It is a schematic front structural diagram of the integrated wing device in the present invention.

[0038] Figure 4 It is a schematic diagram of the definition of the wing flexible motion coordinate system and the pitching angle of the wing surface rigid microelement in the present invention.

[0039] Figure 5 It is a schematic diagram of the structural parameters of the integrated wing device in the present invention.

[0040] Figure 6This is a waveform comparison diagram of the measured signal and the mapped simulation signal in an embodiment of the three-dimensional flexible dynamic and wing surface velocity field reconstruction sensing of the wing of the present invention. Among them, (a) is the waveform comparison of the voltage signal; (b) is the waveform comparison of the current signal.

[0041] Figure 7 This is a three-dimensional projection plane of the mapping relationship between the wing motion parameters and the signal amplitude in an embodiment of the three-dimensional flexible dynamic and wing surface velocity field reconstruction sensing of the wing of the present invention. Among them, (a) is the projection plane describing the mapping relationship between the voltage amplitude and the maximum flapping angle; (b) is the projection plane describing the mapping relationship between the current amplitude and the maximum pitching angle of the rigid microelement.

[0042] Figure 8 This is a comparison diagram of the three-dimensional flexible dynamic reconstruction result of the wing and the binocular stereo vision verification result in an embodiment of the three-dimensional flexible dynamic and wing surface velocity field reconstruction sensing of the wing of the present invention. Among them, (a) is the comparison of the three-dimensional reconstruction result of the wing flexible morphology at 0.2T; (b) is the comparison of the three-dimensional reconstruction result of the wing flexible morphology at 0.4T; (c) is the comparison of the three-dimensional reconstruction result of the wing flexible morphology at 0.6T; (d) is the comparison of the three-dimensional reconstruction result of the wing flexible morphology at 0.8T.

[0043] Figure 9 This is a comparison diagram of the wing surface motion velocity field reconstruction result and the binocular stereo vision verification result in an embodiment of the three-dimensional flexible dynamic and wing surface velocity field reconstruction sensing of the wing of the present invention. Among them, (a) is the wing surface motion velocity field reconstruction result; (b) is the binocular stereo vision verification result. Detailed implementation mode

[0044] To make the purpose, technical solution and beneficial effects of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the drawings and embodiments.

[0045] The present invention provides a three-dimensional dynamic integrated sensing method for a bionic unmanned aerial vehicle, which is used to complete the three-dimensional flexible dynamic reconstruction of the wing of a bionic flapping-wing aircraft and the reconstruction of the wing surface velocity field. By adopting a local electrostatic nanogenerator and the flexible integration method and manufacturing technology of the wing surface, the flexible structure of the nanogenerator is integrated on the wing surface to improve the miniaturization and lightweight degree of the wing with a highly integrated system structure.

[0046] The integrated wing device structure is as Figure 1 shown, and it consists of two wing surfaces, including: the upper wing (1) and the lower wing (2); among them, the lower wing (2) is a common wing surface, and the material can be a thin film structural material such as paper or polymer; the upper wing (1) is a wing surface with a local nanogenerator integrated structure.

[0047] The local nano - generator integrated structure of the upper wing (1) is a laminated design structure, which is a sensitive unit. The structural cross - section is as Figure 2 shown, specifically including: a local conductive layer (101), an integrated wing base surface (102), and a local dielectric friction layer (103); optimally, the material of the integrated wing base surface (102) is the same as that of the lower wing (2).

[0048] In the structure of the upper wing (1), the local conductive layer (101) and the local dielectric friction layer (103) are respectively distributed on the upper and lower surfaces of the integrated wing base surface (102). The number of areas where the local dielectric friction layer (103) is arranged is equal to that of the local conductive layer (101). The position where the local conductive layer (101) is arranged is vertically aligned with the local dielectric friction layer within the reference plane of the wing surface of the upper wing (1).

[0049] The front view of the upper wing (1) is as Figure 3 shown. The peripheral circuit (104) is distributed on the surface where the local conductive layer (101) is located and is closely adhered to the integrated wing base surface (102). The peripheral circuit (104) is connected to the local conductive layer to transmit electrical signals and energy outward.

[0050] The signal output principle of the integrated wing device is as follows: An integrated wing sensor device is made by the integrated upper wing (1) and the un - integrated lower wing (2). The local friction dielectric layer (103) of the upper wing (1) and the wing surface material of the lower wing (2) form a single - electrode electrostatic nano - generator integrated structure. The periodic opening and closing movements of the wings cause the periodic contact between the wing surface friction dielectric layers and carry equal amounts of opposite charges. During the movement of the upper and lower wings, the distance between the friction dielectric layers continuously changes. The periodically changing spatial electric field enables the local conductive layer (101) of the upper wing to output or capture free electrons to the peripheral circuit (104), and an alternating electric signal and electric energy are formed in the external circuit. Analyze the wing movement information contained in the signal to achieve three - dimensional reconstruction sensing of the self - powered flexible movement of the wings.

[0051] The behavior of the integrated wing device to output an alternating current signal to the external circuit is caused by the periodic movement of the wings. The signal quantity output in the external circuit will be closely related to the movement parameters of the flexible wing device. The present invention mainly protects a flapping - wing motion mapping decoupling method based on modeling analysis that can realize three - dimensional flexible dynamics of the wings and reconstruction of the wing surface velocity field, so as to achieve airborne sensing.

[0052] Analyze the morphological laws of bionic flexible wing flapping, mainly by superimposing two motion forms: First, the active rotation of the wing surface around the fuselage axis; second, the passive torsion of the wing surface around the leading edge of the wing; The morphological laws of bionic flexible wing flapping are through the body coordinate system ox b y b z bQuantitatively expressed in terms of the wing coordinate systems of the upper and lower wings (the upper wing coordinate system ox u y u z u , and the lower wing coordinate system ox l y l z l ), as described in Figure 4 ; the body coordinate system ox b y b z b is a Cartesian coordinate system with the origin o at the intersection of the leading edges of the four wings, and the ox b axis is established in the forward direction along the fuselage, the oy b axis is established as the lateral axis perpendicular to the vertical symmetry plane of the fuselage, and the oz b axis is established in the downward direction along the vertical symmetry plane of the fuselage; the wing coordinate system is divided into the upper wing coordinate system ox u y u z u and the lower wing coordinate system ox l y l z l , and the upper and lower wing coordinate systems share the x-axis and the coordinate origin with the body coordinate system ox b y b z b ; the y-axis is established along the leading edge spanwise of the upper and lower wing surfaces, that is, the oy u axis of the upper wing and the oy l axis of the lower wing, and both the upper and lower wing coordinate systems rotate relative to the body coordinate system about the fuselage ox b axis.

[0053] During the flapping process of the wings, the flapping angle is described as Figure 1 shown. At the initial position of a flapping cycle, the upper and lower wing surfaces coincide, and at this time, the coincident surface forms an initial plane in space, which is defined as the average position of the wing flapping; the upper and lower wing surfaces move symmetrically about the plane of the average position, and the angle between the average position and the horizontal plane, that is, ∠y b oy u , is used as the initial phase angle θ0 of the wing flapping, and the angle formed by the leading edge of the wing and the average position of the wing is the flapping angle θ of the wing.

[0054] During the passive torsion process of the wing surface, taking the upper wing (1) as an example, a strip-shaped unit with a distance of Δw along the wingspan and a width of Δr is intercepted and defined as a rigid microelement, and the wing surface is composed of countless approximate rigid microelements; in order to express the torsion of the wing surface, a microelement coordinate system o i x i y i z i is defined in the intercepted rigid microelement, and the origin o of the microelement coordinate iDefined at the central axis of the rigid microelement, y i axis coincides with the y u axis of the upper wing coordinate system, and the x i axis is parallel to the microelement surface with the forward direction as positive; the microelement coordinate x i axis and the straight line parallel to the x u axis of the wing coordinate system form an included angle defined as the pitch angle γ i of the microelement; the wing surface of the lower wing (2) describes the passive torsion of the wing surface using the above method.

[0055] On this basis, the three-dimensional dynamic integrated sensing method of the bionic unmanned aerial vehicle specifically includes the following steps:

[0056] Map and characterize the flapping motion of the integrated wing as a voltage signal model V(t) with open-circuit output and a current signal model I(t) with short-circuit output;

[0057] The open-circuit output voltage signal model V(t) of the integrated wing is:

[0058]

[0059] The short-circuit output current signal model I(t) of the integrated wing is:

[0060]

[0061] In equations (1)-(3), σ T is the bound charge density of the friction medium layer, σu(t) is the free charge density of the conductive layer, and t is the time variable; ε(r) is the dielectric constant of the observation space, r is the space vector, a is the length of the nanogenerator sensitive unit, b is the width of the nanogenerator sensitive unit, Δc is the distance from the upper edge of the nanogenerator sensitive unit to the leading edge of the wing, and s is the integration region for calculating the current on the conductive layer;

[0062] In equations (1)-(3), Φ ub is the transformation matrix from the rigid microelement coordinate system of the upper wing surface to the body coordinate system:

[0063]

[0064] T iu =[0 Δw 0] (6)

[0065]

[0066] In equations (1)-(3), Φ lb is the transformation matrix from the rigid microelement coordinate system of the lower wing surface to the body coordinate system:

[0067]

[0068] T il = [0 Δw 0] (10)

[0069]

[0070] In formulas (1)-(3), Ω' T is the coordinate expression of the integrated fin friction medium layer region in the rigid body micro-element coordinate system, and Ω' T = [x'y'01];

[0071] In formulas (1)-(3), Ω' u is the coordinate expression of the conductive layer region in the rigid body micro-element coordinate system, and Ω' u = [x'y'-(d + Δd)1], where d is the thickness of the upper fin friction medium layer and Δd is the model accuracy correction parameter;

[0072] In formulas (1)-(3), Ω is the coordinate of the center point of the conductive layer on the upper wing surface:

[0073]

[0074] In formulas (5)-(12), γ i is the pitch angle of the wing surface rigid micro-element, θ is the flapping angle of the fin; Δw is the distance between the central axis of the rigid micro-element and the fin root, and θ0 is the initial phase angle of flapping;

[0075] The flapping angle θ of the fin and the pitch angle γ of the wing surface rigid micro-element i are used to describe the flexible motion law of flapping. The empirical law fitted by the flapping angle θ and the pitch angle γ of the wing surface rigid micro-element i is:

[0076]

[0077] In formulas (13)-(15), θ max is the maximum flapping angle within the flapping period, γ max is the maximum pitch angle of the rigid micro-element within the flapping period, f is the flapping frequency, and w is the wingspan length of the fin;

[0078] The open-circuit output voltage signal model V(t) and short-circuit output current signal model I(t) of the above integrated fin characterize the mapping relationship between the signal amplitude and parameters such as the flapping frequency f, flapping angle θ(t), and pitch angle γ i (t); during the airborne sensing process of the three-dimensional flexible dynamics of the fin and the reconstruction of the wing surface velocity field, the amplitudes of the output voltage signal and current signal are collected and analyzed using formulas (1)-(3) to obtain the decoupled maximum flapping angle θ max within the flapping period and the maximum pitch angle γ of the rigid micro-element max; Then, according to the flexible motion law of the wing surface described by equations (13) - (15), the real-time three-dimensional reconstruction of the flexible motion of the wing surface during the flapping cycle can be carried out; for the reconstruction of the wing surface motion velocity field, based on the real-time results of the three-dimensional reconstruction of the flexible motion of the flapping wing, calculate the real-time spatial position coordinates of the characteristic points, calculate the differential of the spatial position coordinates of the characteristic points at the calculation moment, obtain the motion velocity vectors of the wing surface characteristic points, and realize the real-time reconstruction of the flexible motion velocity field of the wing surface according to the velocity vectors of each characteristic point on the wing surface.

[0079] In terms of the working principle:

[0080] The flapping of the wing is described by a quasi-sinusoidal periodic motion. The flapping angle of the wing is approximately described as a motion pattern with a sine characteristic. The motion description function of the flapping angle θ is shown in equation (13); for the wing surface torsion motion, to retain the flexible characteristics of the wing, there is a certain distribution characteristic of the pitch angles of the rigid micro-elements that make up the wing surface. The pitch angle γ i is approximately arctangent distributed along the wingspan direction. The pitch angle γ of the micro-element of the torsion motion i description function is shown in equations (14) and (15);

[0081] The motion of the local nanogenerator area of the wing is the superposition of the wing flapping and the pitch motion of the rigid micro-element where the symmetry center of the nanogenerator area is located. In the unilateral wing surface nanogenerator area, the potential φ(x, y, z) of the local electrode layer (101) area of the upper wing (1) is expressed as the comprehensive contribution of the field quantities of the surface friction-bound charges and free charges of each material. The potential φ(x, y, z) is:

[0082]

[0083] In equation (16), a is the length of the nanogenerator sensitive unit, b is the width of the nanogenerator sensitive unit, Δc is the distance from the upper edge of the nanogenerator sensitive unit to the leading edge of the wing, as Figure 5 described; σ T is the charge density of the friction medium layer, σ u is the charge density of the conductive layer, Ω' T is the coordinate expression of the nanogenerator friction medium layer area in the rigid micro-element coordinate system, Ω' u is the coordinate expression of the nanogenerator conductive layer area in the rigid micro-element coordinate system, Ω is the coordinate of the center point of the conductive layer of the upper wing (1); d is the thickness of the upper wing (1), and Δd is introduced as a model accuracy correction parameter;

[0084] Define the voltage signal V(t) of the open-circuit output and the current signal I(t) of the short-circuit output of the integrated wing, as shown in equations (1) - (3); according to the derivation of the physical field quantities of the integrated wing device, the output signal of the integrated wing device can be expressed as the pitch angle γ of the rigid micro-element where the nanogenerator area is located iand the functional expression of the flapping angle θ; with the functional expressions of the voltage signal V(t) and the current signal I(t) as the sensing mapping, it characterizes the relationship between the signal amplitude and the flapping frequency and the maximum flapping angle θ within the flapping period max and the maximum pitching angle γ of the rigid microelement max relationship; characterized by the amplitude of the measured signal, corresponding to the functional relationship between the signal amplitude and the measured target, the sensing of the measured target can be realized; further, in the airborne sensing process of the three-dimensional flexible dynamics of the wing and the reconstruction of the wing surface velocity field, the amplitudes of the output voltage and current signals are collected and analyzed by introducing equations (1) to (3) to obtain the decoupled maximum flapping angle θ within the flapping period max and the maximum pitching angle γ of the rigid microelement max ; According to the wing surface flexible motion law described by equations (13) to (15), the three-dimensional reconstruction of the flexible motion of the wing surface within the flapping period can be carried out in real time.

[0085] The three-dimensional dynamic sensing of the wing and the reconstruction of the wing surface velocity field are airborne implementation processes. The integrated wing outputs voltage signals and current signals from the peripheral circuit interface end during flapping. The airborne flight control module captures the signals and analyzes the voltage amplitude and current amplitude, and then analyzes the dynamic parameters of the wing flapping according to the described mapping relationship, and reconstructs the flexible three-dimensional dynamics of the wing and the wing surface velocity field; the reconstructed three-dimensional dynamic information of the wing or the wing surface velocity field feeds back the operating conditions of the wing power components for the flight control of the flapping-wing aircraft, and the wireless communication module on board the flapping-wing aircraft feeds back the operating information of the wing to the ground control personnel.

[0086] Specifically, the present invention provides a specific embodiment of the three-dimensional flexible dynamics of the wing and the reconstruction of the wing surface velocity field sensing; in the integrated wing of this embodiment, the local area of the upper wing (1) adopts the nanogenerator integration process, uses 0.0125 mm thick polyethylene terephthalate (PET) film as the material of the integrated wing base surface (102), uses silk fibroin film as the material of the local friction medium layer (103), and uses conductive silver spray paint as the material of the local electrode layer (101). The surface process mainly includes the integrated preparation of the local electrode layer area (101) and the integrated preparation of the local friction medium layer (103) area; specifically as follows:

[0087] S1. Preparation of the local electrode layer (101):

[0088] S101. Perform double-sided oxygen plasma treatment on the PET film with a power of 60 W for 90 s. This process will enhance the hydrophilicity of the PET material surface and increase the adhesion of the surface to the material to be prepared;

[0089] S102. Use an acrylic thin plate with a hollow electrode layer and an external circuit morphology as a mask, cover it on the surface of the PET film, and evenly spray conductive silver paint 3 times, with a 2-minute interval between each spraying;

[0090] S103. Let the semi-finished wing after spraying stand at room temperature for 2 hours, and then remove the mask;

[0091] S104. Adhere 0.4 mm carbon fiber wing veins to the side surface of the electrode to strengthen the structure of the wing;

[0092] S2. Preparation of the local friction medium layer (103):

[0093] S201. Prepare the acrylic mask into the shape of the friction medium layer area and cover it on the other surface of the PET film. The covering position of the mask is aligned vertically with the electrode layer area;

[0094] S202. Drop 10 μL of silk fibroin solution into the mask of each area and coat it evenly;

[0095] S203. Place the semi-finished integrated wing in a drying oven at 50 °C to dehydrate the silk fibroin solution for 24 hours; the temperature of the drying oven can be moderately adjusted, preferably 50 °C, but not higher than 60 °C. Too high a temperature will cause thermoplastic deformation of the PET substrate.

[0096] Based on the above, the integrated wing is a sensor device, and three-dimensional reconstruction and velocity field reconstruction sensing of the flexible movement of the wing are carried out at a flapping frequency of 10 Hz; the sensing parameters of the integrated wing device are shown in Table 1 and Table 2. Table 1 is the integrated wing structure and material parameters, and Table 2 is the bound charge density parameter of the friction medium layer. The bound charge density of the friction medium layer is a quantity that changes with the flapping frequency.

[0097] Table 1

[0098] w Δw Δc a b d Δd <![CDATA[ε0]]> ε (mm) (mm) (mm) (mm) (mm) (mm) (mm) (F / m) (F / m) 85 75 13.84 8 8 <![CDATA[3.5×10 -5 > 75.1 <![CDATA[8.85×10 -12 > <![CDATA[21.92ε0]]>

[0099] Table 2

[0100]

[0101] In the airborne sensing embodiment of the three-dimensional flexible dynamics of the wing and the reconstruction of the wing surface velocity field, the comparison between the measured signal waveform and the simulated waveform calculated by the mapping model is as Figure 6 shown, Figure 6 where (a) is the voltage signal waveform of the measurement and simulation, Figure 6 and (b) is the current signal waveform of the measurement and simulation. As can be seen from the figure, the measured signal waveform is basically the same as the simulated signal waveform, indicating the accuracy of the established mapping model.

[0102] In the airborne sensing embodiment of the three-dimensional flexible dynamics of the wing and the reconstruction of the wing surface velocity field, by analyzing the law of the output signal and the flapping wing motion, the amplitudes of the voltage and current signals within a period are mapped to the flapping wing frequency, the maximum flapping angle θ within a period max , and the maximum pitch angle γ of the rigid microelement within a period max ; there is a mapping relationship. From this mapping relationship, the maximum flapping angle and the maximum pitch angle of the rigid microelement can be obtained corresponding to the measured amplitudes of the voltage and current signals. In terms of mathematical function representation, this mapping relationship is a hyperplane in a five-dimensional space. As Figure 7 shown, it is the projection plane of this hyperplane in a three-dimensional space. Figure 7 In (a), it is the projection plane describing the mapping relationship between the voltage amplitude and the maximum flapping angle θ max . Figure 7 In (b), it is the projection plane describing the mapping relationship between the current amplitude and the maximum pitch angle γ of the rigid microelement max .

[0103] In the embodiment of the three-dimensional flexible dynamics reconstruction of the wing, the flexible morphology and characteristics of the upper wing surface (1) are reconstructed at a flapping wing frequency of 10 Hz. The reconstructed morphology of the lower wing (2) at each moment is symmetric to the upper wing surface (1) with the initial plane of the wing surface as the symmetry plane. Taking the three-dimensional flexible morphology reconstruction of the upper wing (1) as an example, the reconstruction result is compared with the stereo vision reconstruction result of the binocular camera. As Figure 8 shown, Figure 8 in (a) is the comparison of the three-dimensional reconstruction results of the flexible morphology of the wing at 0.2T, Figure 8 in (b) is the comparison of the three-dimensional reconstruction results of the flexible morphology of the wing at 0.4T, Figure 8 in (c) is the comparison of the three-dimensional reconstruction results of the flexible morphology of the wing at 0.6T, Figure 8 in (d) is the comparison of the three-dimensional reconstruction results of the flexible morphology of the wing at 0.8T. It can be seen from the figure that the three-dimensional reconstruction method of the bionic flapping wing dynamics proposed by the present invention can reconstruct the flexible morphology and spatial relative position of the wing during flapping, and is consistent with the stereo reconstruction results of the binocular vision method.

[0104] In the embodiment of the reconstruction of the wing surface motion velocity field, according to the implementation result of the three-dimensional flexible dynamics reconstruction of the wing, the coordinate positions of the feature points in the three-dimensional space are calculated; the displacement vector differential of the same feature points in the front and rear moments is calculated, and the selected time interval between the front and rear moments is 0.001 seconds. The velocity vectors of the feature points at each moment are calculated, and further the velocity field of the wing surface motion is reconstructed. As Figure 9 shown, it is the reconstruction of the velocity field of the wing surface motion and the result verification based on binocular vision. It can be seen from the figure that the reconstruction method of the bionic flapping wing surface velocity field proposed by the present invention can calculate the velocity vectors of each point on the wing surface at each moment of the flapping wing motion, can reconstruct the velocity field of the wing surface motion, and is consistent with the reconstruction results of the binocular vision method.

[0105] As described above, it is only the specific implementation manner of the present invention. Any feature disclosed in this specification, unless specifically described, can be replaced by other equivalent or alternative features with similar purposes; all the disclosed features, or all the steps in any method or process, except for mutually exclusive features and / or steps, can be combined in any manner.

Claims

1. A three-dimensional dynamic integrated perception method for a bionic unmanned aerial vehicle, characterized in that: The following steps are involved: The flapping motion mapping of the integrated wing is characterized as an open-circuit output voltage signal model and a short-circuit output current signal model; The voltage signal amplitude and current signal amplitude of the integrated wing output are collected in real time, introduced into the open-circuit output voltage signal model and the short-circuit output current signal model, and the maximum flapping angle and the maximum pitch angle of the rigid microelement in the flapping cycle are obtained; The maximum flapping angle during the flapping cycle and the maximum pitch angle of the rigid element are introduced into the empirical model of wing flexible motion to obtain the law of wing flexible motion and complete three-dimensional dynamic integrated perception.

2. The three-dimensional dynamic integrated perception method of a bionic unmanned aerial vehicle according to claim 1 is characterized in that: The open-circuit output voltage signal model of the integrated wing is expressed as V(t), specifically: Oh T =[x'y'01] Among them, σ T is the bound charge density of the friction medium layer, ε(r) is the dielectric constant of the observation space, a is the length of the nanogenerator sensitive unit, b is the width of the nanogenerator sensitive unit, Δc is the distance from the upper edge of the nanogenerator sensitive unit to the leading edge of the wing; Φ ub is the transformation matrix from the upper wing rigid body micro-element coordinate system to the body coordinate system, Φ lb is the transformation matrix from the lower wing rigid body micro-element coordinate system to the body coordinate system, Ω' T is the coordinate of the integrated wing friction medium layer area in the rigid body micro-element coordinate system, and Ω is the coordinate of the center point of the upper wing surface conductive layer.

3. The three-dimensional dynamic integrated perception method of a bionic unmanned aerial vehicle according to claim 1 is characterized in that: The short-circuit output current signal model of the integrated wing is expressed as I(t), specifically: Oh T =[x'y'01] Among them, σ T is the bound charge density of the friction medium layer, σ u (t) is the free charge density of the conductive layer, s represents the integral area for calculating the current on the conductive layer; ε(r) is the dielectric constant of the observation space, a is the length of the sensitive unit of the nanogenerator, b is the width of the sensitive unit of the nanogenerator, Δc is the distance from the upper edge of the sensitive unit of the nanogenerator to the leading edge of the wing, Φ ub is the transformation matrix from the upper wing rigid body micro-element coordinate system to the body coordinate system, Φ lb is the transformation matrix from the lower wing rigid body micro-element coordinate system to the body coordinate system, Ω' T is the coordinate of the integrated wing friction medium layer area in the rigid body micro-element coordinate system, and Ω is the coordinate of the center point of the upper wing surface conductive layer.

4. The three-dimensional dynamic integrated perception method of a bionic unmanned aerial vehicle according to claim 2 or 3, characterized in that: In the open-circuit output voltage signal model and the short-circuit output current signal model, the conversion matrix Φ from the upper wing rigid body micro-element coordinate system to the body coordinate system is ub Specifically: T iu =[0Δw 0] Among them, I is the identity matrix, γ i is the pitch angle of the rigid element of the wing surface, Δw is the distance between the central axis of the rigid element and the wing root, θ0 is the initial phase angle of the flapping wing, and θ is the flapping angle of the wing.

5. The three-dimensional dynamic integrated perception method of a bionic unmanned aerial vehicle according to claim 2 or 3, characterized in that: In the open-circuit output voltage signal model and the short-circuit output current signal model, the conversion matrix Φ from the lower wing rigid body micro-element coordinate system to the body coordinate system is lb Specifically: T il =[0Δw 0] Among them, I is the identity matrix, γ i is the pitch angle of the rigid element of the wing surface, Δw is the distance between the central axis of the rigid element and the wing root, θ0 is the initial phase angle of the flapping wing, and θ is the flapping angle of the wing.

6. The three-dimensional dynamic integrated perception method of a bionic unmanned aerial vehicle according to claim 2 or 3, characterized in that: In the open-circuit output voltage signal model and the short-circuit output current signal model, the coordinates of the conductive layer area in the rigid body micro-element coordinate system are specifically: Ω' u =[x'y'-(d+Δd)1], where d is the thickness of the friction medium layer on the upper wing and Δd is the model accuracy correction parameter.

7. The three-dimensional dynamic integrated perception method of a bionic unmanned aerial vehicle according to claim 2 or 3, characterized in that: In the open-circuit output voltage signal model and the short-circuit output current signal model, the coordinate Ω of the center point of the upper wing surface conductive layer is specifically:

8. The three-dimensional dynamic integrated perception method of a bionic unmanned aerial vehicle according to claim 1 is characterized in that: The empirical model of wing surface flexible motion is expressed as: Where θ is the flapping angle of the wing, γ i is the pitch angle of the wing surface rigid element; θ max is the maximum flapping angle within the flapping cycle, γ max is the maximum pitch angle of the rigid element during the flapping cycle, f is the flapping frequency, and w is the wingspan length of the wing.

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