WO2021217437A1 - 振动模态优化方法、振动模态优化装置和无人机 - Google Patents

振动模态优化方法、振动模态优化装置和无人机 Download PDF

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Publication number
WO2021217437A1
WO2021217437A1 PCT/CN2020/087559 CN2020087559W WO2021217437A1 WO 2021217437 A1 WO2021217437 A1 WO 2021217437A1 CN 2020087559 W CN2020087559 W CN 2020087559W WO 2021217437 A1 WO2021217437 A1 WO 2021217437A1
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Prior art keywords
arm
frequency
torsion
vibration mode
machine
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PCT/CN2020/087559
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English (en)
French (fr)
Inventor
赵鹏飞
刘祥
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深圳市大疆创新科技有限公司
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Application filed by 深圳市大疆创新科技有限公司 filed Critical 深圳市大疆创新科技有限公司
Priority to PCT/CN2020/087559 priority Critical patent/WO2021217437A1/zh
Priority to CN202080005354.9A priority patent/CN112867671A/zh
Publication of WO2021217437A1 publication Critical patent/WO2021217437A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64C—AEROPLANES; HELICOPTERS
    • B64C27/00—Rotorcraft; Rotors peculiar thereto
    • B64C27/51—Damping of blade movements
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64C—AEROPLANES; HELICOPTERS
    • B64C27/00—Rotorcraft; Rotors peculiar thereto
    • B64C27/04—Helicopters
    • B64C27/08—Helicopters with two or more rotors
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64C—AEROPLANES; HELICOPTERS
    • B64C27/00—Rotorcraft; Rotors peculiar thereto
    • B64C27/32—Rotors
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64C—AEROPLANES; HELICOPTERS
    • B64C27/00—Rotorcraft; Rotors peculiar thereto
    • B64C27/54—Mechanisms for controlling blade adjustment or movement relative to rotor head, e.g. lag-lead movement
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U10/00—Type of UAV
    • B64U10/10—Rotorcrafts

Definitions

  • This application relates to the technical field of drones, and in particular to a vibration mode optimization method, a vibration mode optimization device, and a drone.
  • UAVs mostly use folding blades.
  • the drone arm is relatively long, and the motor at the end has a larger mass.
  • the motor at the end has a larger mass.
  • the embodiments of the present application provide a vibration mode optimization method, a vibration mode optimization device, and an unmanned aerial vehicle.
  • the vibration mode optimization method of the embodiment of the present application is applied to an unmanned aerial vehicle.
  • the unmanned aerial vehicle includes a fuselage and an arm assembly, the arm assembly includes an arm and a motor, and one end of the arm is rotatably Connected to the fuselage, the motor is connected to the top of the other end of the arm, a tripod is connected to the bottom of the other end of the arm, and a paddle is connected to the output shaft of the motor;
  • the vibration mode optimization method includes:
  • the critical unstable propeller frequency of the blade adjust the torsion frequency of the arm, the distance from the blade plane of the blade to the torsion axis of the arm, and the distance of the arm assembly with respect to the torsion axis of the arm. At least one of the moments of inertia.
  • the vibration mode optimization device of the embodiment of the present application is used in an unmanned aerial vehicle.
  • the unmanned aerial vehicle includes a fuselage and an arm assembly, the arm assembly includes an arm and a motor, and one end of the arm is rotatably
  • the fuselage is connected, the motor is connected to the top of the other end of the arm, a tripod is connected to the bottom of the other end of the arm, the output shaft of the motor is connected to a blade, and the vibration mode is optimized
  • the device includes a processor for obtaining the critical instability frequency of the blade; and for adjusting the torsion frequency of the arm and the blade according to the critical instability frequency of the blade. At least one of the distance from the plane of the blade to the torsion axis of the arm and the moment of inertia of the arm assembly with respect to the torsion axis of the arm.
  • the unmanned aerial vehicle of the embodiment of the present application is optimized by the above-mentioned vibration mode optimization method.
  • the vibration mode optimization method, the vibration mode optimization device and the unmanned aerial vehicle of the embodiments of the present application adjust the torsion frequency of the arm, the plane of the blade to the torsion axis of the arm by referring to the critical instability propeller frequency of the blade At least one of the distance between and the moment of inertia of the arm assembly with respect to the torsion axis of the arm, so that the actual blade frequency is lower than the critical instability blade frequency requirement of the blade. In this way, when the blade rotates at a high speed, the vibration of the arm assembly can be minimized, and the flight safety and normal operation of the UAV can be ensured.
  • FIG. 1 is a schematic flowchart of a vibration mode optimization method according to an embodiment of the present application
  • FIG. 2 is a schematic diagram of the structure of the unmanned aerial vehicle according to the embodiment of the present application.
  • FIG. 3 is another schematic diagram of the structure of the unmanned aerial vehicle according to the embodiment of the present application.
  • FIG. 4 is a schematic diagram of a module of a vibration mode optimization device according to an embodiment of the present application.
  • FIG. 5 is a schematic flowchart of a vibration mode optimization method according to another embodiment of the present application.
  • FIG. 6 is a schematic flowchart of a vibration mode optimization method according to another embodiment of the present application.
  • FIG. 7 is a schematic flowchart of a vibration mode optimization method according to still another embodiment of the present application.
  • FIG. 8 is a schematic flowchart of a vibration mode optimization method according to another embodiment of the present application.
  • FIG. 9 is a schematic diagram of the structure of the arm of the unmanned aerial vehicle according to the embodiment of the present application.
  • FIG. 10 is a schematic diagram of the structure of the tripod of the unmanned aerial vehicle according to the embodiment of the present application.
  • FIG. 11 is another schematic diagram of the structure of the tripod of the unmanned aerial vehicle according to the embodiment of the present application.
  • Fig. 12 is another schematic diagram of the structure of the arm assembly of the unmanned aerial vehicle according to the embodiment of the present application.
  • first and second are only used for description purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with “first” and “second” may explicitly or implicitly include one or more of the features. In the description of the present application, “multiple” means two or more than two, unless otherwise specifically defined.
  • connection should be understood in a broad sense, unless otherwise clearly specified and limited.
  • it can be a fixed connection or a detachable connection.
  • Connected or integrally connected it can be mechanically connected, or electrically connected or can communicate with each other; it can be directly connected, or indirectly connected through an intermediate medium, it can be the internal communication of two components or the interaction of two components relation.
  • connection should be understood according to specific circumstances.
  • the drone 100 includes a fuselage 20 and an arm assembly 30, and the arm assembly 30 includes The arm 32 and the motor 34.
  • One end of the arm 32 is rotatably connected to the fuselage 20, the top of the other end of the arm 32 is connected with a motor 34, and the bottom of the other end of the arm 32 is connected with a tripod 40, the output shaft of the motor 34 Connected with paddle 50;
  • Vibration mode optimization methods include:
  • Step S11 Obtain the critical unstable propeller frequency ⁇ of the blade 50;
  • Step S12 Adjust the torsion frequency ⁇ x of the arm 32, the distance h from the blade plane of the blade 50 to the torsion axis of the arm, and the distance h of the arm assembly 30 with respect to the torsion axis of the arm according to the critical instability propeller frequency ⁇ of the blade 50 At least one of the moments of inertia Mx.
  • the distance h from the blade plane of the blade 50 to the torsion axis of the arm is the vertical distance from the center of gravity of the blade 50 to the torsion axis of the arm; the moment of inertia Mx of the arm assembly 30 with respect to the torsion axis of the arm refers to the arm 32.
  • the moment of inertia of the structure such as the motor 34 and the tripod 40 relative to the torsion axis of the arm.
  • the vibration mode optimization device 200 of the embodiment of the present application is used for the drone 100.
  • the drone 100 includes a fuselage 20 and an arm assembly 30.
  • the arm assembly 30 includes an arm 32 and a motor 34.
  • One end of the arm 32 is rotatably connected to the fuselage 20, a motor 34 is connected to the top of the other end of the arm 32, a foot stand 40 is connected to the bottom of the other end of the arm 32, and a paddle 50 is connected to the output shaft of the motor 34.
  • the vibration mode optimization device 200 includes a processor 201 for obtaining the critical instability propeller frequency ⁇ of the blade 50; and for adjusting the torsion frequency of the arm 32 according to the critical instability propeller frequency ⁇ of the blade 50 ⁇ x, at least one of the distance h from the blade plane of the blade 50 to the torsion axis of the arm, and the moment of inertia Mx of the arm assembly 30 with respect to the torsion axis of the arm.
  • the unmanned aerial vehicle 100 of the embodiment of the present application is optimized by the above-mentioned vibration mode optimization method.
  • the vibration mode optimization method, the vibration mode optimization device 200 and the unmanned aerial vehicle 100 of the embodiments of the present application adjust the torsional frequency ⁇ x and the blade At least one of the distance h from the plane to the torsion axis of the arm and the moment of inertia Mx of the arm assembly 30 with respect to the torsion axis of the arm, so that the actual propeller frequency of the blade 50 is lower than the requirement of the critical unstable propeller frequency ⁇ of the blade 50 In this way, when the blade 50 rotates at a high speed, the vibration of the arm assembly 30 can be minimized, and the flight safety and normal operation of the UAV 100 can be ensured.
  • the unmanned aerial vehicle 100 may include a pan/tilt mounted on the fuselage 20, and the pan/tilt mounted with a photographing device.
  • the drone 100 can have a shooting function, and the pan/tilt can stabilize the shooting device and adjust the posture, so that the shooting effect is better and more needs can be met.
  • drones often use folding blades for folding portability.
  • the drone arm is relatively long, and the motor at the end has a larger mass.
  • Instability occurs when the man-machine is maneuvering and the blades are at high speed, and the arm's violent vibration affects flight safety and normal imaging.
  • the mechanical properties of the material are reduced, and the arm vibration is more likely to occur, which poses a greater risk to the safe operation of the UAV.
  • the arm material with a high modulus will generally have a higher density.
  • Using a material with a higher modulus for the arm structure will increase the cost or weight.
  • the use of non-folding paddles will increase the folding volume of the drone, resulting in reduced portability.
  • the use of non-folding blades will also cause the vibration of the arm to be amplified.
  • the vibration mode optimization method, the vibration mode optimization device 200, and the drone 100 of the embodiments of the present application adjust at least one of the aforementioned parameters by using the critical instability propeller frequency ⁇ of the blade 50 as a reference. While solving the above problems, the actual blade frequency of the blades of the blade 50 can be lower than the requirement of the critical instability blade frequency ⁇ of the blade 50, so that the vibration of the arm assembly 30 is minimized when the blade 50 rotates at a high speed. It is beneficial to ensure the flight safety and normal operation of the UAV 100.
  • step S11 input information may be obtained, and the critical instability propeller frequency ⁇ may be determined according to the input information.
  • the user can input the input information into the vibration mode optimization device 200, so that the processor 201 can obtain the critical instability propeller frequency ⁇ , which is convenient for the user to customize settings and debugging.
  • the input information may include the critical unstable propeller frequency ⁇ , and the processor 201 may recognize the input information to obtain the critical unstable propeller frequency ⁇ .
  • the input information may also include data for calculating the critical instability propeller frequency ⁇ , and the processor 201 may calculate the critical instability propeller frequency ⁇ according to the input information.
  • the vibration mode optimization device 200 may be connected to an input device, which includes but is not limited to a touch screen, keys (including a mouse and a keyboard), a gesture recognition camera, and a microphone.
  • the input information includes, but is not limited to, information input by the touch screen, key information, gesture information, and voice information. The specific form of the input information is not limited here.
  • the vibration mode optimization device 200 includes, but is not limited to, personal computers, mobile phones, tablet computers, notebook computers, and wearable devices. The specific form of the vibration mode optimization device 200 is not limited here.
  • the vibration mode optimization device 200 may include a memory 202, the memory 202 may store the critical unstable propeller frequency ⁇ , and the processor 201 may read the critical unstable propeller frequency ⁇ from the memory 202. In this way, no user input is required, and the acquisition speed is faster, which is beneficial to shorten the execution time of the vibration mode optimization method.
  • the value of the critical instability propeller frequency ⁇ may be equal to the highest value of the speed of the blade 50. In this case, since the speed of the blade 50 cannot exceed the highest value of the speed of the blade 50 Therefore, the rotation speed of the blade 50 cannot exceed the critical instability propeller frequency ⁇ . In this way, it is possible to prevent the rotation speed of the blade 50 from being higher than the critical instability propeller frequency ⁇ , thereby avoiding the instability of the blade 50 and causing the arm 32 to vibrate while ensuring the maneuverability of the UAV 100.
  • step S12 the torsion frequency ⁇ x of the arm 32, the distance h from the blade plane of the blade 50 to the torsion axis of the arm, and the distance h of the arm assembly 30 relative to the arm One, two or all of the moments of inertia Mx of the torsion axis.
  • the torsion frequency ⁇ x of the arm 32 can be adjusted according to the critical instability propeller frequency ⁇ of the blade 50.
  • the distance h from the blade plane of the blade 50 to the torsion axis of the arm can be adjusted according to the critical instability propeller frequency ⁇ of the blade 50.
  • the moment of inertia Mx of the arm assembly 30 with respect to the torsion axis of the arm can be adjusted according to the critical instability propeller frequency ⁇ of the blade 50.
  • the torsion frequency ⁇ x of the arm 32 and the distance h from the blade plane of the blade 50 to the torsion axis of the arm can be adjusted according to the critical instability propeller frequency ⁇ of the blade 50.
  • the torsion frequency ⁇ x of the arm 32 and the moment of inertia Mx of the arm assembly 30 with respect to the torsion axis of the arm can be adjusted according to the critical instability propeller frequency ⁇ of the blade 50.
  • the distance h from the blade plane of the blade 50 to the torsion axis of the arm and the moment of inertia Mx of the arm assembly 30 with respect to the torsion axis of the arm can be adjusted according to the critical instability propeller frequency ⁇ of the blade 50.
  • the torsion frequency ⁇ x of the arm 32, the distance h from the blade plane of the blade 50 to the torsion axis of the arm and the distance h of the arm assembly 30 relative to the machine arm can be adjusted according to the critical instability propeller frequency ⁇ of the blade 50.
  • the critical instability propeller frequency ⁇ is positively correlated with the torsion frequency ⁇ x of the arm 32; the critical instability propeller frequency ⁇ is negatively correlated with the square h 2 of the distance h from the blade plane to the torsion axis of the arm; critical The unstable propeller frequency ⁇ is negatively related to the moment of inertia Mx of the arm assembly 30 with respect to the torsion axis of the arm.
  • the correlation between the critical unstable propeller frequency ⁇ and the above parameters can be expressed by the following formula:
  • ⁇ is the critical instability propeller frequency
  • ⁇ x is the torsion frequency of the arm 32
  • K is the influence factor
  • h is the distance from the blade plane to the torsion axis of the arm
  • Mx is the distance of the arm assembly 30 with respect to the torsion axis of the arm.
  • the critical instability propeller frequency ⁇ is negatively correlated with the influence factor K, and the influence factor K is positively correlated with the square of the distance h from the blade plane to the torsion axis of the arm, and is related to the moment of inertia of the arm assembly 30 with respect to the torsion axis of the arm Mx is positively correlated, therefore, the critical instability propeller frequency ⁇ is negatively correlated with the square of the distance h of the arm torsion axis, and is negatively correlated with the moment of inertia Mx of the arm assembly 30 with respect to the arm torsion axis.
  • the distance h from the plane of the blade to the torsion axis of the arm can be reduced to make The value of is increased to the value of the obtained critical instability propeller frequency ⁇ ; it can also be reduced by reducing the moment of inertia Mx of the torsion axis of the arm to make The value of is increased to the value of the obtained critical instability propeller frequency ⁇ ; the torsional frequency ⁇ x of the arm 32 can also be increased to make The value of is increased to the value of the acquired critical instability propeller frequency ⁇ .
  • the rotation frequency of the blade 50 installed on the arm 32 will not exceed the critical instability propeller frequency ⁇ , therefore, there is nothing in the embodiment of the present application.
  • the human-machine design can meet the requirements of the critical instability propeller frequency ⁇ , so that when the blade 50 rotates at a high speed, the vibration of the arm assembly 30 is minimized, thereby ensuring the flight safety and normal operation of the UAV 100.
  • a set distance range can be obtained, and the distance h from the blade plane to the torsion axis of the arm can be adjusted within the distance range. In this way, it is possible to prevent the distance h from the blade plane to the torsion axis of the arm from exceeding the set distance range and causing the arm 32 to buckle and vibrate.
  • the set distance range can be 1-5cm. For example, it is 1cm, 2cm, 2.5cm, 3cm, 4cm, 5cm. The specific value of the set distance range is not limited here.
  • the vibration mode optimization method includes:
  • the processor 201 is used to adjust the radius r of the arm 32, the wall thickness t of the arm 32, the length L of the arm 32, the shear modulus G of the arm 32, and the torque of the arm 32. At least one of the moments of inertia I is used to adjust the torsion frequency ⁇ x of the arm 32.
  • step S12 includes the torsion frequency ⁇ x of the arm 32
  • the adjustment of the torsion frequency ⁇ x of the arm 32 can be achieved by the above-mentioned method.
  • the above parameters can be adjusted to adjust the radius r of the arm 32, the wall thickness t of the arm 32, the length L of the arm 32, the shear modulus G of the arm 32, and the moment of inertia I of the arm 32 torsion.
  • One, two, three, four or all are used to adjust the torsion frequency ⁇ x of the arm 32.
  • the number of adjusted parameters is not limited here.
  • the radius r of the arm 32 may be adjusted preferentially. It can be understood that among the above parameters, the radius r of the arm 32 has a greater influence on the torsion frequency ⁇ x. In other words, adjusting the radius r of the arm 32 is more effective for adjusting the torsion frequency ⁇ x. Therefore, the radius r of the arm 32 can be adjusted preferentially, thereby improving the adjustment efficiency. It can be understood that in other embodiments, multiple parameters can be adjusted in a different order according to specific actual conditions, and it is not limited to adjusting the radius of the arm 32 first.
  • a set radius range can be obtained, and the radius r of the arm 32 can be adjusted within the set radius range. In this way, it can be avoided that the radius r of the arm 32 is too low or too high, which may cause the arm 32 to interfere with other structures of the drone 100, or break the constraints of the appearance of the drone 100.
  • a set wall thickness range can be obtained, and the wall thickness t of the arm 32 can be adjusted within the set wall thickness range. In this way, it is possible to prevent the wall thickness t of the arm 32 from being too low, resulting in lower reliability of the arm 32, and to avoid the wall thickness t of the arm 32 from being too high, resulting in excessive weight and resistance of the drone 100. Too high.
  • a set length range can be obtained, and the length L of the arm 32 can be adjusted within the set length range. In this way, it can be avoided that the length L of the arm 32 is too low or too high, which may cause the arm 32 to interfere with other structures of the drone 100, or cause the performance of the drone 100 to be poor.
  • the shear modulus G of the arm 32 is related to the material of the arm 32. In this way, the shear modulus G of the arm 32 can be adjusted by selecting different materials.
  • the material of the arm 32 may include polyamide (PA), or a mixed material of PA and glass fiber.
  • PA polyamide
  • the shear modulus G of the arm 32 can be made high.
  • the performance of such a material has little change with temperature and little change with humidity, so that the weight of the arm 32 can be reduced.
  • PA612 and glass fiber 55 can be selected as the material of the arm 32. In this way, the moisture absorption performance of the arm 32 can be improved, and performance degradation caused by excessive moisture absorption can be avoided.
  • PA612 and glass fiber 55 are plastic materials, and the material properties can be changed by changing the fiber content.
  • the torsional moment of inertia I of the arm 32 increases proportionally. Therefore, the torsional moment of inertia I of the arm 32 can be adjusted by adjusting the density of the material of the arm 32.
  • the torsion frequency ⁇ x of the arm 32 is positively correlated with the radius r of the arm 32; the torsion frequency ⁇ x of the arm 32 is positively correlated with the wall thickness t of the arm 32; the torsion frequency ⁇ x of the arm 32 is positively correlated with The length L of the arm 32 is negatively correlated; the torsional frequency ⁇ x of the arm 32 is positively correlated with the shear modulus G of the arm 32; the torsional frequency ⁇ x of the arm 32 is negatively correlated with the torsional moment of inertia I of the arm 32.
  • the correlation between the torsion frequency ⁇ x of the arm 32 and the above-mentioned parameters can be expressed by the following formula:
  • ⁇ x is the torsion frequency of the arm 32
  • G is the shear modulus of the arm 32
  • J is the arm factor
  • L is the length of the arm 32
  • I is the torsional moment of inertia of the arm 32.
  • the arm factor J is proportional to r 3 t. r is the radius of the arm 32 and t is the wall thickness of the arm 32.
  • the torsion frequency ⁇ x is positively correlated with the arm factor J
  • the arm factor J is positively correlated with the radius r of the arm 32, and is positively correlated with the wall thickness t of the arm 32. Therefore, the torsion frequency ⁇ x is positively correlated with the radius of the arm 32.
  • r is positively correlated and positively correlated with the wall thickness t of the arm 32.
  • the torsion frequency ⁇ x can be increased by increasing the radius r of the arm 32, so that The value of is increased to the value of the obtained critical instability propeller frequency ⁇ ; the torsion frequency ⁇ x can be increased by increasing the wall thickness t of the arm 32, thereby making The value of is increased to the value of the acquired critical instability propeller frequency ⁇ .
  • the actual propeller frequency of the blade 50 can be lower than the requirement of the critical instability propeller frequency ⁇ , thereby minimizing the vibration of the arm assembly 30 when the blade 50 rotates at a high speed, thereby ensuring the flight safety of the UAV 100 Sex and normal work.
  • the vibration mode optimization method includes:
  • Step S1311 Determine the arm 32 according to the critical instability frequency ⁇ of the blade 50, the distance h from the blade plane of the blade 50 to the torsion axis of the arm, and the moment of inertia Mx of the arm assembly 30 with respect to the torsion axis of the arm.
  • Step S1312 Determine according to the critical instability torsion frequency ⁇ x1 of the machine arm 32, the wall thickness t of the machine arm 32, the length L of the machine arm 32, the shear modulus G of the machine arm 32, and the torsional moment of inertia I of the machine arm 32 The critical instability radius r1 of the arm 32;
  • Step S1313 According to the critical instability radius r1 of the arm 32, determine the wall thickness t corresponding to the arm 32, the length L of the arm 32, the shear modulus G of the arm 32, and the torsional moment of inertia I of the arm 32 The range of the radius r of the arm 32.
  • the processor 201 is used to determine the critical instability frequency ⁇ of the blade 50, the distance h from the blade plane of the blade 50 to the torsion axis of the arm, and the arm assembly 30 about the torsion axis of the arm.
  • the moment of inertia Mx of the machine arm 32 determines the critical instability torsion frequency ⁇ x1 of the machine arm 32; and is used to determine the critical instability torsion frequency ⁇ x1 of the machine arm 32 according to the
  • the shear modulus G and the torsional moment of inertia I of the arm 32 are used to determine the critical instability radius r1 of the arm 32; and used to determine the wall thickness corresponding to the arm 32 according to the critical instability radius r1 of the arm 32 t, the value range of the length L of the arm 32, the shear modulus G of the arm 32, and the radius r of the arm 32 of the torsional moment of inertia I of the arm 32.
  • the critical instability radius r1 of the arm 32 can be determined, and then the value range of the radius r of the arm 32 can be determined. Adjusting the radius r of the arm 32 to adjust the torsion frequency ⁇ x within the value range of is beneficial to improve the adjustment efficiency.
  • the critical instability torsion frequency ⁇ x1 of the arm 32 can be determined by formula (1), and then the critical instability radius r1 of the arm 32 can be determined according to formula (2), so as to determine the value range of the radius r of the arm 32 .
  • the value range of the radius r may be stored in the memory 202 and used as the radius range set in the above embodiment.
  • the radius range set in the preceding paragraph is preset by the user, and the value range of the radius r And the radius range set in the previous section can be taken as an intersection to update the value range of the radius r.
  • the vibration mode optimization method includes:
  • Step S1321 Determine the arm 32 according to the critical instability frequency ⁇ of the blade 50, the distance h from the blade plane of the blade 50 to the torsion axis of the arm, and the moment of inertia Mx of the arm assembly 30 with respect to the torsion axis of the arm.
  • Step S1322 Determine the machine arm 32 based on the critical instability torsion frequency ⁇ x1, the radius r of the machine arm 32, the length L of the machine arm 32, the shear modulus G of the machine arm 32, and the torsional moment of inertia I of the machine arm 32 The critical instability wall thickness t1 of the arm 32;
  • Step S1323 According to the critical instability wall thickness t1 of the arm 32, determine the radius r corresponding to the arm 32, the length L of the arm 32, the shear modulus G of the arm 32, and the torsional moment of inertia I of the arm 32 The range of the wall thickness t of the arm 32.
  • the processor 201 is used to determine the critical instability frequency ⁇ of the blade 50, the distance h from the blade plane of the blade 50 to the torsion axis of the arm, and the arm assembly 30 about the torsion axis of the arm.
  • the moment of inertia Mx of the machine arm 32 is used to determine the critical instability torsion frequency ⁇ x1 of the machine arm 32;
  • the shear modulus G and the torsional moment of inertia I of the arm 32 determine the critical instability wall thickness t1 of the arm 32; and are used to determine the radius corresponding to the arm 32 according to the critical instability wall thickness t1 of the arm 32 r, the length L of the arm 32, the shear modulus G of the arm 32, and the wall thickness t of the arm 32 for the torsional moment of inertia I of the arm 32.
  • step S1311, step S1312 and step S1313. You can refer to the explanation and description of step S1311, step S1312 and step S1313. To avoid redundancy, it will not be repeated here.
  • the vibration mode optimization method includes:
  • Step S1331 Determine the arm 32 according to the critical instability propeller frequency ⁇ of the blade 50, the distance h from the blade plane of the blade 50 to the torsion axis of the arm, and the moment of inertia Mx of the arm assembly 30 with respect to the torsion axis of the arm.
  • Step S1332 Determine according to the critical instability torsion frequency ⁇ x1 of the machine arm 32, the wall thickness t of the machine arm 32, the radius r of the machine arm 32, the shear modulus G of the machine arm 32, and the torsional moment of inertia I of the machine arm 32 The critical instability length L1 of the arm 32;
  • Step S1333 According to the critical instability length L1 of the machine arm 32, determine the radius r corresponding to the machine arm 32, the length L of the machine arm 32, the shear modulus G of the machine arm 32, and the torsional moment of inertia I of the machine arm 32 The value range of the length L of the arm 32.
  • the processor 201 is used to determine the critical instability frequency ⁇ of the blade 50, the distance h from the blade plane of the blade 50 to the torsion axis of the arm, and the arm assembly 30 about the torsion axis of the arm.
  • the moment of inertia Mx of the machine arm 32 is used to determine the critical instability torsion frequency ⁇ x1 of the machine arm 32;
  • the shear modulus G of the machine arm 32 and the torsional moment of inertia I of the machine arm 32 determine the critical buckling length L1 of the machine arm 32; and used to determine the radius r corresponding to the machine arm 32 according to the critical buckling length L1 of the machine arm 32 ,
  • the range of the length L of the arm 32, the shear modulus G of the arm 32, and the length L of the arm 32 of the torsional moment of inertia I of the arm 32 are examples of the length L of the arm 32, the shear modulus G of the arm 32, and the length L of the arm 32 of the torsional moment of inertia I of the arm 32.
  • step S1311, step S1312 and step S1313. You can refer to the explanation and description of step S1311, step S1312 and step S1313. To avoid redundancy, it will not be repeated here.
  • the vibration mode optimization method includes:
  • Step S151 divide the machine arm 32 into a plurality of machine arm parts along the length direction of the machine arm 32;
  • Step S152 Perform sensitivity analysis on multiple arm positions to obtain the influence intensity of each arm position on the torsion frequency ⁇ x of the arm 32;
  • Step S153 optimizing the structure of multiple arm parts according to the influence intensity from large to small.
  • the processor 201 is used to divide the arm 32 into a plurality of arm parts along the length direction of the arm 32; and used to perform sensitivity analysis on the multiple arm parts to obtain each arm The influence intensity of the part on the torsion frequency ⁇ x of the arm 32; and used to optimize the structure of multiple arm parts according to the influence intensity from large to small.
  • the machine arm 32 can be made uniform and smooth in the length direction of the machine arm 32, and the outer diameter of the machine arm 32 can be prevented from drastically changing locally, such as changes in opening, sharp contraction, etc., especially at both ends of the machine arm 32.
  • the sharp change of the outer diameter at the position ensures a smooth transition of the lines of the arm 32, thereby adjusting the torsion frequency ⁇ x.
  • the arm 32 has a curved surface, and the violent contraction means that the curved surface turns more violently, or in other words, the curvature is larger and the radius of curvature is smaller.
  • the uniformity of the arm 32 is weaker in the severely contracted part.
  • the arm 32 can be divided into 7 arm parts along the length direction of the arm 32.
  • the direction from the body 20 to the motor 34 is 7
  • the arm parts are respectively the arm part P1, the arm part P2, the arm part P3, the arm part P4, the arm part P5, the arm part P6, and the arm part P7.
  • it can be judged by the structure and parameter thresholds that from the arm part P5 to the arm part P7, the arm part P6 is severely contracted.
  • the number of divided arm parts may also be 2, 3, 4, 5, 6, 8, or other numbers. There is no limitation here.
  • Sensitivity analysis is a method to study and analyze the sensitivity of the state or output changes of a system (or model) to changes in system parameters or surrounding conditions. Specifically, in step S152, sensitivity analysis is used to determine the strength of the influence of each arm position on the torsion frequency ⁇ x of the arm 32. Specifically, the stiffness, material parameters, size parameters and other parameters of each arm part can be adjusted separately, and the degree of change of the torsion frequency ⁇ x can be measured, so as to determine the strength of the influence of each arm part on the torsion frequency ⁇ x of the arm 32.
  • step S153 the multiple arm parts are optimized according to the influence intensity from large to small, that is, the arm parts with greater influence are optimized first, and then the arm parts with less influence are optimized. In this way, the optimization efficiency can be improved and the optimization time can be shortened.
  • the optimized part of the arm has already met the requirement of the torsion frequency ⁇ x, that is, the requirement of the critical instability propeller frequency ⁇ is met, the remaining part of the arm may not be optimized.
  • the arm position that has the highest influence on the torsion frequency ⁇ x of the arm 32 is arm position P6, followed by arm position P7, and arm position P3.
  • the arm part P5 is the next
  • the arm part P4 is the next
  • the arm part P2 is the second
  • the arm part P1 is the lowest.
  • the arm part P6 can be adjusted first, and then the arm part P7, the arm part P3, the arm part P5, the arm part P4, the arm part P2, and the arm part P1 can be adjusted.
  • step S153 includes:
  • the processor 201 is used to increase the radius of the arm part; and/or the processor 201 is used to increase the rib position in the arm part.
  • the radius is enlarged; in another example, for the curved surface with an opening at the lower part of the arm, move the opening down so that the lower surface is the lowest of the arm.
  • the bottom surface is basically flush.
  • ribs are added to the arm part to strengthen the arm part and prevent the arm part from deforming. In another example, increase the radius of the arm part, and increase the rib position in the arm part.
  • the vibration mode optimization method includes at least one of the following:
  • the mass of the lower end of the foot frame 40 is adjusted to adjust the torsion frequency ⁇ x of the arm 32.
  • the processor 201 is configured to perform at least one of the following methods: adjust the stiffness of the structure at the connection between the foot stand 40 and the arm 32 to adjust the torsion frequency ⁇ x of the arm 32; adjust the length of the foot stand 40 to Adjust the torsion frequency ⁇ x of the arm 32; adjust the mass of the lower end of the tripod 40 to adjust the torsion frequency ⁇ x of the arm 32.
  • the torsion frequency ⁇ x of the arm 32 is adjusted by adjusting the foot frame 40 to meet the requirement of the critical instability propeller frequency ⁇ of the blade 50.
  • the torsion frequency ⁇ x of the arm 32 is positively correlated with the stiffness of the structure at the junction of the tripod 40 and the arm 32; the torsion frequency ⁇ x of the arm 32 is negatively related to the length of the tripod 40; the torsion frequency ⁇ x of the arm 32 It is negatively related to the mass of the lower end of the tripod 40.
  • the above-mentioned parameters can be adjusted more accurately and quickly, which is beneficial to shorten the adjustment time and improve the efficiency of the adjustment.
  • the rigidity of the structure of the connection between the foot frame 40 and the machine arm 32 can be adjusted by stiffening the foot frame 40, adding thickness to the foot frame 40, and adding the connecting piece between the foot frame 40 and the machine arm 32, so that the foot frame 40 There is no shaking between the arm 32 and the arm 32, or the shaking range is within a desired range.
  • the stand 40 includes a connecting portion 401 and a supporting portion 402, and the connecting portion 401 connects the supporting portion 402 and the arm 32.
  • the connecting portion 401 is formed with a connecting hole 4011, and the tripod 40 and the arm 32 can be connected with three screws passing through the connecting hole 4011 first.
  • the fourth screw is used to connect the tripod 40 and the arm 32 on the fixing plane of the first three screws, that is, in the vertical direction of the plane where the connecting portion 401 is located. In this way, it can be ensured that there is no gap between the tripod 40 and the arm 32 and no shaking.
  • the length of the tripod 40 can be reduced to reduce the moment of inertia I brought about by the tripod 40, thereby increasing the torsion frequency ⁇ x.
  • the length of the foot stand 40 can be adjusted within the preset length of the foot stand, so as to avoid the function of the foot stand 40 being affected by adjusting the length of the foot stand 40.
  • the length range of the tripod can be determined based on the accommodating and performance of the antenna in the tripod 40, or it can be determined based on factors such as the UAV 100's requirements for the height from the ground, that is, the tripod 40 must be guaranteed to meet additional functional requirements In this case, adjust the length of the tripod 40.
  • the mass of the lower end of the tripod 40 can be reduced to increase the torsion frequency ⁇ x.
  • lighter materials may be used to reduce the mass of the lower end of the tripod 40.
  • the material of the tripod 40 is related to the torsional frequency ⁇ x of the arm 32.
  • high modulus, low density, and low moisture absorption materials can be used.
  • the PC modulus is lower, usually only 2.2, the PA modulus is 4.6, and the hygroscopicity is also higher. In this way, the torsional frequency ⁇ x of the arm 32 can be increased, the risk of arm vibration can be reduced, and the environmental adaptability can be improved.
  • a spacer 42 is provided on the lower end surface of the tripod 40, and the material and mass of the spacer 42 are related to the torsion frequency ⁇ x of the arm 32.
  • the tripod 40 can be made more wear-resistant when the drone 100 is landed.
  • the gasket 42 can be designed to reduce weight, for example, the thickness of the gasket 42 is limited to a preset thickness range. In this way, the spacer 42 is made thinner and lighter in weight, which is beneficial to increase the torsion frequency ⁇ x.
  • the material of the gasket 42 includes a thermoplastic polyurethane elastomer (TPU) material.
  • TPU thermoplastic polyurethane elastomer
  • the TPU material is light in weight and has good glue adhesion.
  • the use of the gasket 42 of the TPU material can reduce the quality of the gasket 42 and make the connection between the gasket 42 and the tripod 40 more stable.
  • the arm 32 is rotated and connected to the fuselage 20 through a shaft 3201, and the vibration mode optimization method includes:
  • the structural rigidity at the rotating shaft 3201 is adjusted to adjust the torsion frequency ⁇ x of the arm 32.
  • the arm 32 is connected to the fuselage 20 through a rotating shaft 3201, and the processor 201 is used to adjust the structural rigidity at the rotating shaft 3201 to adjust the torsional frequency ⁇ x of the arm 32.
  • the torsion frequency ⁇ x of the arm 32 can be adjusted by adjusting the structure at the rotating shaft 3201. It can be understood that the virtual position and shaking of the structure at the rotating shaft 3201 will seriously reduce the torsional frequency ⁇ x, so that the actual blade frequency of the blade cannot be lower than the requirement of the critical unstable blade frequency ⁇ , and the vibration will be amplified. Adjusting the structural rigidity of the rotating shaft 3201 can eliminate the virtual gap at the rotating shaft 3201, thereby eliminating shaking in all directions.
  • the torsional frequency ⁇ x of the arm 32 is positively correlated with the structural rigidity at the rotating shaft 3201. Therefore, the structural rigidity at the shaft 3201 can be increased to increase the torsional frequency ⁇ x, so that the actual blade frequency is lower than the requirement of the critical instability blade frequency ⁇ .
  • an interference amount can be set at the rotating shaft 3201 so that the arm 32 rotates through the rotating shaft 3201 to be in an interference fit with the fuselage 20.
  • the opening angle at the rotating shaft 3201 can be avoided, thereby ensuring no shaking and avoiding a virtual position, so that the arm 32 rotates through the rotating shaft 3201 to closely fit with the body 20.
  • the torsion axis of the arm is shown by the dashed line 3202.
  • the apparent reason for the vibration of the arm 32 is that the speed of the blade 50 is higher than the critical speed, that is, higher than the critical instability propeller frequency ⁇ , which causes the blade 50 to be unstable and the arm 32 vibrates.
  • the internal reason for the vibration of the arm 32 is that the length of the arm 32 is large, and the mass and inertia introduced by the motor 34 and the tripod 40 are large, resulting in a low torsional frequency ⁇ x of the arm 32.
  • the critical speed of the instability of the blade 50 is reduced, and the arm vibration is prone to occur when the drone 100 is performing high-speed maneuvers.
  • the vibration mode optimization method, the vibration mode optimization device 200, and the drone 100 of the embodiment of the present application have been optimized for the structure of the arm 32, the tripod 40, the motor 34 and the blade 50, the rotation axis 3201 of the arm 32, etc.
  • the torsional frequency ⁇ x of the arm 32 can be increased with the least cost, so that the actual blade frequency is lower than the critical buckling frequency ⁇ of the blade 50, and the risk of arm vibration is eliminated.
  • the maneuverability and working range of the drone 100 can be improved, the structural reliability of the drone 100 can be improved, and the explosion caused by vibration can be avoided.
  • a "computer-readable medium” can be any device that can contain, store, communicate, propagate, or transmit a program for use by an instruction execution system, device, or device or in combination with these instruction execution systems, devices, or devices.
  • computer readable media include the following: electrical connections (electronic devices) with one or more wiring, portable computer disk cases (magnetic devices), random access memory (RAM), Read only memory (ROM), erasable and editable read only memory (EPROM or flash memory), fiber optic devices, and portable compact disk read only memory (CDROM).
  • the computer-readable medium may even be paper or other suitable medium on which the program can be printed, because it can be used, for example, by optically scanning the paper or other medium, followed by editing, interpretation, or other suitable media if necessary. The program is processed in a manner to obtain the program electronically, and then stored in the computer memory.
  • each part of this application can be executed by hardware, software, firmware, or a combination thereof.
  • multiple steps or methods can be executed by software or firmware stored in a memory and executed by a suitable instruction execution system.
  • a logic gate circuit for performing logic functions on data signals
  • Discrete logic circuits Discrete logic circuits
  • application specific integrated circuits with suitable combinational logic gates
  • PGA programmable gate array
  • FPGA field programmable gate array
  • a person of ordinary skill in the art can understand that all or part of the steps carried in the above implementation method can be executed by a program instructing relevant hardware to complete.
  • the program can be stored in a computer-readable storage medium, and the program can be executed when the program is executed. When it includes one of the steps of the method embodiment or a combination thereof.
  • the functional units in the various embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units may be integrated into one module.
  • the above-mentioned integrated modules can be executed in the form of hardware or software function modules. If the integrated module is executed in the form of a software function module and sold or used as an independent product, it may also be stored in a computer readable storage medium.
  • the aforementioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.

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  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Aviation & Aerospace Engineering (AREA)
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  • Apparatuses For Generation Of Mechanical Vibrations (AREA)
  • Vibration Prevention Devices (AREA)

Abstract

一种振动模态优化方法，用于无人机(100)，无人机(100)包括机身(20)和机臂组件(30)，机臂组件(30)包括机臂(32)和电机(34)，机臂(32)的一端可转动地连接机身(20)，机臂(32)另一端的顶部连接有电机(34)，机臂(32)另一端的底部连接有脚架(40)，电机(34)的输出轴连接有桨叶(50)；振动模态优化方法包括：获取桨叶(50)的临界失稳桨频(ω)；根据桨叶(50)的临界失稳桨频(ω)，调节机臂(32)的扭转频率(ωx)、桨叶(50)的桨叶平面到机臂(32)扭转轴的距离(h)和机臂组件(30)关于机臂(32)扭转轴的惯性矩(Mx)中的至少一个。本申请还公开了一种振动模态优化装置(200)和无人机(100)。

Description

振动模态优化方法、振动模态优化装置和无人机 技术领域
本申请涉及无人机技术领域，特别涉及一种振动模态优化方法、振动模态优化装置和无人机。
背景技术
目前无人机为了折叠的便携性，多采用折叠桨叶。无人机机臂相对较长，端部的电机质量较大，脚架除起到支撑作用之外，还有其它附加功能，这使得对机臂部分引入更多的质量和惯量，容易在无人机大机动、桨叶高转速时发生失稳，机臂的剧烈振动，影响飞行安全性和正常成像。
发明内容
本申请的实施方式提供一种振动模态优化方法、振动模态优化装置和无人机。
本申请实施方式的振动模态优化方法，用于无人机，所述无人机包括机身和机臂组件，所述机臂组件包括机臂和电机，所述机臂的一端可转动地连接所述机身，所述机臂另一端的顶部连接有所述电机，所述机臂另一端的底部连接有脚架，所述电机的输出轴连接有桨叶；
所述振动模态优化方法包括：
获取所述桨叶的临界失稳桨频；
根据所述桨叶的临界失稳桨频，调节所述机臂的扭转频率、所述桨叶的桨叶平面到机臂扭转轴的距离和所述机臂组件关于所述机臂扭转轴的惯性矩中的至少一个。
本申请实施方式的振动模态优化装置，用于无人机，所述无人机包括机身和机臂组件，所述机臂组件包括机臂和电机，所述机臂的一端可转动地连接所述机身，所述机臂另一端的顶部连接有所述电机，所述机臂另一端的底部连接有脚架，所述电机的输出轴连接有桨叶，所述振动模态优化装置包括处理器，所述处理器用于获取所述桨叶的临界失稳桨频；以及用于根据所述桨叶的临界失稳桨频，调节所述机臂的扭转频率、所述桨叶的桨叶平面到机臂扭转轴的距离和所述机臂组件关于所述机臂扭转轴的惯性矩中的至少一个。
本申请实施方式的无人机，由上述的振动模态优化方法优化得到。
本申请实施方式的振动模态优化方法、振动模态优化装置和无人机，通过以桨叶的临界失稳桨频为参照，来调节机臂的扭转频率、桨叶平面到机臂扭转轴的距离和机臂组件关于机臂扭转轴的惯性矩的至少一个，来使得桨叶的实际桨频低于桨叶的临界失稳桨频的要 求。这样在桨叶高速转动时，能够使机臂组件的振动最小化，保证了无人机的飞行安全性和正常工作。
本申请的实施方式的附加方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本申请的实施方式的实践了解到。
附图说明
本申请的上述和/或附加的方面和优点从结合下面附图对实施方式的描述中将变得明显和容易理解，其中：
图1是本申请实施方式的振动模态优化方法的流程示意图；
图2是本申请实施方式的无人机的结构示意图；
图3是本申请实施方式的无人机的另一结构示意图；
图4是本申请实施方式的振动模态优化装置的模块示意图；
图5是本申请另一实施方式的振动模态优化方法的流程示意图；
图6是本申请又一实施方式的振动模态优化方法的流程示意图；
图7是本申请再一实施方式的振动模态优化方法的流程示意图；
图8是本申请另一实施方式的振动模态优化方法的流程示意图；
图9是本申请实施方式的无人机的机臂的结构示意图；
图10是本申请实施方式的无人机的脚架的结构示意图；
图11是本申请实施方式的无人机的脚架的另一结构示意图；
图12是本申请实施方式的无人机的机臂组件的另一结构示意图。
具体实施方式
下面详细描述本申请的实施方式，所述实施方式的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施方式是示例性的，仅用于解释本申请，而不能理解为对本申请的限制。
在本申请的描述中，需要理解的是，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多个所述特征。在本申请的描述中，“多个”的含义是两个或两个以上，除非另有明确具体的限定。
在本申请的描述中，需要说明的是，除非另有明确的规定和限定，术语“安装”、“相连”、“连接”应做广义理解，例如，可以是固定连接，也可以是可拆卸连接，或一体地连接；可以是机械连接，也可以是电连接或可以相互通信；可以是直接相连，也可以通过 中间媒介间接相连，可以是两个元件内部的连通或两个元件的相互作用关系。对于本领域的普通技术人员而言，可以根据具体情况理解上述术语在本申请中的具体含义。
下文的公开提供了许多不同的实施方式或例子用来实现本申请的不同结构。为了简化本申请的公开，下文中对特定例子的部件和设置进行描述。当然，它们仅仅为示例，并且目的不在于限制本申请。此外，本申请可以在不同例子中重复参考数字和/或参考字母，这种重复是为了简化和清楚的目的，其本身不指示所讨论各种实施方式和/或设置之间的关系。此外，本申请提供了的各种特定的工艺和材料的例子，但是本领域普通技术人员可以意识到其他工艺的应用和/或其他材料的使用。
下面详细描述本申请的实施方式，所述实施方式的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施方式是示例性的，仅用于解释本申请，而不能理解为对本申请的限制。
请参阅图1、图2和图3，本申请实施方式的一种振动模态优化方法，用于无人机100，无人机100包括机身20和机臂组件30，机臂组件30包括机臂32和电机34，机臂32的一端可转动地连接机身20，机臂32另一端的顶部连接有电机34，机臂32另一端的底部连接有脚架40，电机34的输出轴连接有桨叶50；
振动模态优化方法包括：
步骤S11：获取桨叶50的临界失稳桨频ω；
步骤S12：根据桨叶50的临界失稳桨频ω，调节机臂32的扭转频率ωx、桨叶50的桨叶平面到机臂扭转轴的距离h和机臂组件30关于机臂扭转轴的惯性矩Mx中的至少一个。
其中，桨叶50的桨叶平面到机臂扭转轴的距离h为桨叶50的重心到机臂扭转轴的垂向距离；机臂组件30关于机臂扭转轴的惯性矩Mx是指机臂32、电机34、脚架40等结构相对于机臂扭转轴的惯性矩。
请参阅图4，本申请实施方式的振动模态优化装置200，用于无人机100，无人机100包括机身20和机臂组件30，机臂组件30包括机臂32和电机34，机臂32的一端可转动地连接机身20，机臂32另一端的顶部连接有电机34，机臂32另一端的底部连接有脚架40，电机34的输出轴连接有桨叶50。振动模态优化装置200包括处理器201，处理器201用于获取桨叶50的临界失稳桨频ω；以及用于根据桨叶50的临界失稳桨频ω，调节机臂32的扭转频率ωx、桨叶50的桨叶平面到机臂扭转轴的距离h和机臂组件30关于机臂扭转轴的惯性矩Mx中的至少一个。
本申请实施方式的无人机100，由上述的振动模态优化方法优化得到。
本申请实施方式的振动模态优化方法、振动模态优化装置200和无人机100，通过以桨叶50的临界失稳桨频ω为参照，来调节机臂32的扭转频率ωx、桨叶平面到机臂扭转轴 的距离h和机臂组件30关于机臂扭转轴的惯性矩Mx的至少一个，来使得桨叶50的实际桨频低于桨叶50的临界失稳桨频ω的要求，这样在桨叶50高速转动时，能够使机臂组件30的振动最小化，保证了无人机100的飞行安全性和正常工作。
具体地，无人机100可包括云台，云台安装在机身20，云台上设置有拍摄装置。如此，可以无人机100可具备拍摄功能，而云台可为拍摄装置增稳及姿态调整，使得拍摄效果更好和能够满足更多需求。
可以理解，在相关技术中，无人机为了折叠的便携性，多采用折叠桨叶。无人机机臂相对较长，端部的电机质量较大，脚架除起到支撑作用之外，还有其它附加功能，这使得对机臂部分引入更多的质量和惯量，容易在无人机大机动、桨叶高转速时发生失稳，机臂的剧烈振动，影响飞行安全性和正常成像。而且，在高温高湿环境下，材料力学性能下降，更容易发生机臂振动，对无人机安全工作形成更大的风险。
相关技术通常通过以下三种方式减弱机臂的振动：限制无人机的桨叶转速以在变动空间较小的情况下避免发生振动、对机臂结构使用模量更高的材料以提升机臂的扭转频率从而提高桨叶的临界转速、使用非折叠桨。
然而，限制无人机的桨叶转速会限制无人机的拉力和机动性。模量高的机臂材料相应的密度一般也会更大，对机臂结构使用模量更高的材料，会增加成本或重量。使用非折叠桨，会增加无人机的折叠体积，导致便携性降低。而且，使用非折叠桨叶，也会出现机臂振动放大的现象。
而本申请实施方式的振动模态优化方法、振动模态优化装置200和无人机100，通过以桨叶50的临界失稳桨频ω为参照，来调节前述参数中的至少一个，在避免了上述问题的同时，可以使得桨50叶的实际桨频低于桨叶50的临界失稳桨频ω的要求，从而在桨叶50高速转动时，使得机臂组件30的振动最小化，有利于保证无人机100的飞行安全性和正常工作。
具体地，在步骤S11中，可以获取输入信息，并根据输入信息确定临界失稳桨频ω。如此，用户可以通过将输入信息输入至振动模态优化装置200，从而使得处理器201获取临界失稳桨频ω，便于用户的自定义设置和调试。具体地，输入信息可以包括临界失稳桨频ω，处理器201可识别输入信息以得到临界失稳桨频ω。输入信息也可包括用于计算临界失稳桨频ω的数据，处理器201可根据输入信息计算临界失稳桨频ω。具体地，振动模态优化装置200可连接有输入装置，输入装置包括但不限于触摸屏、按键(包括鼠标和键盘)、手势识别摄像头及麦克风。输入信息包括但不限于由触摸屏输入的信息、按键信息、手势信息、语音信息。在此不对输入信息的具体形式进行限定。
振动模态优化装置200包括但不限于个人计算机、手机、平板电脑、笔记本电脑、可 穿戴设备。在此不对振动模态优化装置200的具体形式进行限定。振动模态优化装置200可包括存储器202，存储器202可存储有临界失稳桨频ω，处理器201可从存储器202读取临界失稳桨频ω。如此，无需用户输入，获取速度较快，有利于缩短振动模态优化方法的执行时间。
可以理解，若桨叶50的转速高于临界失稳桨频ω，容易导致桨叶50失稳，从而引发机臂32振动。在步骤S12中，在一个实施方式中，临界失稳桨频ω的值可以等于桨叶50转速的最高值，在这种情况下，由于桨叶50的转速不可能超过桨叶50转速的最高值，因此，桨叶50的转速也就不可能超过临界失稳桨频ω。这样，就可以避免桨叶50的转速高于临界失稳桨频ω，从而在保证无人机100机动性的情况下，可避免桨叶50失稳而引发机臂32振动。
在步骤S12中，可根据桨叶50的临界失稳桨频ω，调节机臂32的扭转频率ωx、桨叶50的桨叶平面到机臂扭转轴的距离h和机臂组件30关于机臂扭转轴的惯性矩Mx中的一个、两个或全部。
在一个例子中，可根据桨叶50的临界失稳桨频ω，调节机臂32的扭转频率ωx。在另一个例子中，可根据桨叶50的临界失稳桨频ω，调节桨叶50的桨叶平面到机臂扭转轴的距离h。在又一个例子中，可根据桨叶50的临界失稳桨频ω，调节机臂组件30关于机臂扭转轴的惯性矩Mx。
在再一个例子中，可根据桨叶50的临界失稳桨频ω，调节机臂32的扭转频率ωx和桨叶50的桨叶平面到机臂扭转轴的距离h。在另一个例子中，可根据桨叶50的临界失稳桨频ω，调节机臂32的扭转频率ωx和机臂组件30关于机臂扭转轴的惯性矩Mx。在又一个例子中，可根据桨叶50的临界失稳桨频ω，调节桨叶50的桨叶平面到机臂扭转轴的距离h和机臂组件30关于机臂扭转轴的惯性矩Mx。
在再一个例子中，可根据桨叶50的临界失稳桨频ω，调节机臂32的扭转频率ωx、桨叶50的桨叶平面到机臂扭转轴的距离h和机臂组件30关于机臂扭转轴的惯性矩Mx。
请注意，以上仅为示例，在此不对调节参数的具体内容和具体数量进行限定。
在某些实施方式中，临界失稳桨频ω与机臂32的扭转频率ωx正相关；临界失稳桨频ω与桨叶平面到机臂扭转轴的距离h的平方h 2负相关；临界失稳桨频ω与机臂组件30关于机臂扭转轴的惯性矩Mx负相关。
如此，通过临界失稳桨频ω与上述参数的相关性，可更加准确快速地调节上述参数，有利于缩短调节的时间和提高调节的效率。在本实施方式中，临界失稳桨频ω与上述参数的相关性可用如下公式表达：
Figure PCTCN2020087559-appb-000001
其中，ω为临界失稳桨频，ω x为机臂32的扭转频率，K为影响因子，h为桨叶平面到机臂扭转轴的距离，Mx为机臂组件30关于机臂扭转轴的惯性矩。
可以理解，临界失稳桨频ω与影响因子K负相关，而影响因子K与桨叶平面到机臂扭转轴的距离h的平方正相关，与机臂组件30关于机臂扭转轴的惯性矩Mx正相关，所以，临界失稳桨频ω与机臂扭转轴的距离h的平方负相关，与机臂组件30关于机臂扭转轴的惯性矩Mx负相关。
因此，可通过降低桨叶平面到机臂扭转轴的距离h，使得
Figure PCTCN2020087559-appb-000002
的值提高至获取到的临界失稳桨频ω的值；也可通过降低机臂扭转轴的惯性矩Mx，使得
Figure PCTCN2020087559-appb-000003
的值提高至获取到的临界失稳桨频ω的值；还可通过提高机臂32的扭转频率ωx，使得
Figure PCTCN2020087559-appb-000004
的值提高至获取到的临界失稳桨频ω的值。这样，由于实际操作中，通过本申请实施方式得到的无人机100中，机臂32上安装的桨叶50的转动频率不会超过临界失稳桨频ω，因此，本申请实施方式的无人机设计可以满足临界失稳桨频ω的要求，从而在桨叶50高速转动时，使机臂组件30的振动最小化，从而保证无人机100的飞行安全性和正常工作。
进一步地，可获取设定的距离范围，并在距离范围内调节桨叶平面到机臂扭转轴的距离h。如此，可以避免桨叶平面到机臂扭转轴的距离h超出设定的距离范围而导致机臂32发生失稳振动。设定的距离范围可为1-5cm。例如为1cm、2cm、2.5cm、3cm、4cm、5cm。在此不对设定的距离范围的具体数值进行限定。
在某些实施方式中，振动模态优化方法包括：
调节机臂32的半径r、机臂32的壁厚t、机臂32的长度L、机臂32的剪切模量G、机臂32扭转的转动惯量I中的至少一个来调节机臂32的扭转频率ωx。
在某些实施方式中，处理器201用于调节机臂32的半径r、机臂32的壁厚t、机臂32的长度L、机臂32的剪切模量G、机臂32扭转的转动惯量I中的至少一个来调节机臂32的扭转频率ωx。
如此，在步骤S12中要调节的参数包括机臂32的扭转频率ωx的情况下，可以通过上述方法实现对机臂32的扭转频率ωx的调节。
具体地，可调节上述参数调节机臂32的半径r、机臂32的壁厚t、机臂32的长度L、机臂32的剪切模量G、机臂32扭转的转动惯量I中的一个、两个、三个、四个或全部，来调节机臂32的扭转频率ωx。在此不对调节的参数的数量进行限定。
进一步地，在调节多个参数的情况下，可优先调节机臂32的半径r。可以理解，在上 述参数中，机臂32的半径r对于扭转频率ωx的影响较大，换言之，调节机臂32的半径r对于调节扭转频率ωx较有效。因此，可优先调节机臂32的半径r，从而提高调节效率。可以理解，在其它实施方式中，可根据具体的实际情况可对多个参数按不同的顺序进行调整，而不限于先调整机臂32的半径。
进一步地，可获取设定的半径范围，并在设定的半径范围内调节机臂32的半径r。如此，可以避免机臂32的半径r过低或过高，而导致机臂32与无人机100的其他结构干涉，或突破了无人机100外观造型的约束。
进一步地，可获取设定的壁厚范围，并在设定的壁厚范围内调节机臂32的壁厚t。如此，可以避免机臂32的壁厚t过低，而导致机臂32的可靠性较低，并可避免机臂32的壁厚t过高，而导致无人机100的重量过大、阻力过高。
进一步地，可获取设定的长度范围，并在设定的长度范围内调节机臂32的长度L。如此，可以避免机臂32的长度L过低或过高，而导致机臂32与无人机100的其他结构干涉，或导致无人机100的性能较差。
进一步地，机臂32的剪切模量G与机臂32的材料相关。如此，可通过选用不同的材料来调节机臂32的剪切模量G。
更进一步地，机臂32的材料可包括聚酰胺(Polyamide，PA)，或PA与玻璃纤维的混合材料。如此，可以使得机臂32的剪切模量G较高。而且，这样的材料的性能随温度变化少、随湿度变化少，可以降低机臂32的重量。
在本实施方式的一个例子中，可选用PA612和玻璃纤维55作为机臂32的材料。如此，可改善机臂32的吸湿性能，避免由于吸湿过多而导致的性能下降。另外，PA612和玻璃纤维55是塑胶材料，可以通过改变含纤量，来改变材料性能。
另外，机臂32的材料的密度增加，机臂32扭转转动惯量I会等比例增加。所以，可通过调节机臂32的材料的密度，以调节机臂32扭转转动惯量I。
在某些实施方式中，机臂32的扭转频率ωx与机臂32的半径r正相关；机臂32的扭转频率ωx与机臂32的壁厚t正相关；机臂32的扭转频率ωx与机臂32的长度L负相关；机臂32的扭转频率ωx与机臂32的剪切模量G正相关；机臂32的扭转频率ωx与机臂32扭转转动惯量I负相关。
如此，通过机臂32的扭转频率ωx与上述参数的相关性，可更加快速准确地调节上述参数，有利于缩短调节的时间和提高调节的效率。在本实施方式中，机臂32的扭转频率ωx与上述参数的相关性可用如下公式表达：
Figure PCTCN2020087559-appb-000005
其中，ωx为机臂32的扭转频率，G为机臂32的剪切模量，J为机臂因子，L为机臂 32的长度，I为机臂32扭转转动惯量。机臂因子J与r 3t成正比。r为机臂32的半径，t为机臂32的壁厚。
可以理解，扭转频率ωx与机臂因子J正相关，机臂因子J与机臂32的半径r正相关，与机臂32的壁厚t正相关，所以，扭转频率ωx与机臂32的半径r正相关，与机臂32的壁厚t正相关。
因此，可通过增大机臂32的半径r，使得扭转频率ωx增大，从而使得
Figure PCTCN2020087559-appb-000006
的值提高至获取到的临界失稳桨频ω的值；可通过增大机臂32的壁厚t，使得扭转频率ωx增大，从而使得
Figure PCTCN2020087559-appb-000007
的值提高至获取到的临界失稳桨频ω的值。这样，可以使得桨叶50的实际桨频低于临界失稳桨频ω的要求，从而在桨叶50高速转动时，使机臂组件30的振动最小化，从而保证无人机100的飞行安全性和正常工作。
请参阅图5，在某些实施方式中，振动模态优化方法包括：
步骤S1311：根据桨叶50的临界失稳桨频ω、桨叶50的桨叶平面到机臂扭转轴的距离h、和机臂组件30关于机臂扭转轴的惯性矩Mx，确定机臂32的临界失稳扭转频率ωx1；
步骤S1312：根据机臂32的临界失稳扭转频率ωx1、机臂32的壁厚t、机臂32的长度L、机臂32的剪切模量G、和机臂32扭转转动惯量I，确定机臂32的临界失稳半径r1；
步骤S1313：根据机臂32的临界失稳半径r1，确定对应于机臂32的壁厚t、机臂32的长度L、机臂32的剪切模量G、和机臂32扭转转动惯量I的机臂32的半径r的取值范围。
在某些实施方式中，处理器201用于根据桨叶50的临界失稳桨频ω、桨叶50的桨叶平面到机臂扭转轴的距离h、和机臂组件30关于机臂扭转轴的惯性矩Mx，确定机臂32的临界失稳扭转频率ωx1；及用于根据机臂32的临界失稳扭转频率ωx1、机臂32的壁厚t、机臂32的长度L、机臂32的剪切模量G、和机臂32扭转转动惯量I，确定机臂32的临界失稳半径r1；以及用于根据机臂32的临界失稳半径r1，确定对应于机臂32的壁厚t、机臂32的长度L、机臂32的剪切模量G、和机臂32扭转转动惯量I的机臂32的半径r的取值范围。
如此，可以在确定机臂32的临界失稳扭转频率ωx1的情况下，确定机臂32的临界失稳半径r1，进而确定确定机臂32的半径r的取值范围，这样，可在半径r的取值范围内对机臂32的半径r进行调节以调节扭转频率ωx，有利于提高调节效率。
具体地，可通过公式(1)确定机臂32的临界失稳扭转频率ωx1，再根据公式(2)确定机臂32的临界失稳半径r1，从而确定机臂32的半径r的取值范围。在一个实施方式中，半径r的取值范围可存储于存储器202并作为上述实施方式设定的半径范围。在另一个实 施方式中，在上述实施方式设定的半径范围的来源与半径r的取值范围无关的情况下，例如前文中设定的半径范围由用户预先设定，半径r的取值范围和前文中设定的半径范围可取交集以更新半径r的取值范围。
请参阅图6，在某些实施方式中，振动模态优化方法包括：
步骤S1321：根据桨叶50的临界失稳桨频ω、桨叶50的桨叶平面到机臂扭转轴的距离h、和机臂组件30关于机臂扭转轴的惯性矩Mx，确定机臂32的临界失稳扭转频率ωx1；
步骤S1322：根据机臂32的临界失稳扭转频率ωx1、机臂32的半径r、机臂32的长度L、机臂32的剪切模量G、和机臂32扭转转动惯量I，确定机臂32的临界失稳壁厚t1；
步骤S1323：根据机臂32的临界失稳壁厚t1，确定对应于机臂32的半径r、机臂32的长度L、机臂32的剪切模量G、和机臂32扭转转动惯量I的机臂32的壁厚t的取值范围。
在某些实施方式中，处理器201用于根据桨叶50的临界失稳桨频ω、桨叶50的桨叶平面到机臂扭转轴的距离h、和机臂组件30关于机臂扭转轴的惯性矩Mx，确定机臂32的临界失稳扭转频率ωx1；及用于根据机臂32的临界失稳扭转频率ωx1、机臂32的半径r、机臂32的长度L、机臂32的剪切模量G、和机臂32扭转转动惯量I，确定机臂32的临界失稳壁厚t1；以及用于根据机臂32的临界失稳壁厚t1，确定对应于机臂32的半径r、机臂32的长度L、机臂32的剪切模量G、和机臂32扭转转动惯量I的机臂32的壁厚t的取值范围。
关于该部分的解释和说明，与步骤S1311、步骤S1312和步骤S1313的解释和说明类似，可参照步骤S1311、步骤S1312和步骤S1313的解释和说明，为避免冗余，在此不再赘述。
请参阅图7，在某些实施方式中，振动模态优化方法包括：
步骤S1331：根据桨叶50的临界失稳桨频ω、桨叶50的桨叶平面到机臂扭转轴的距离h、和机臂组件30关于机臂扭转轴的惯性矩Mx，确定机臂32的临界失稳扭转频率ωx1；
步骤S1332：根据机臂32的临界失稳扭转频率ωx1、机臂32的壁厚t、机臂32的半径r、机臂32的剪切模量G、和机臂32扭转转动惯量I，确定机臂32的临界失稳长度L1；
步骤S1333：根据机臂32的临界失稳长度L1，确定对应于机臂32的半径r、机臂32的长度L、机臂32的剪切模量G、和机臂32扭转转动惯量I的机臂32的长度L的取值范围。
在某些实施方式中，处理器201用于根据桨叶50的临界失稳桨频ω、桨叶50的桨叶平面到机臂扭转轴的距离h、和机臂组件30关于机臂扭转轴的惯性矩Mx，确定机臂32的临界失稳扭转频率ωx1；及用于根据机臂32的临界失稳扭转频率ωx1、机臂32的壁厚t、 机臂32的半径r、机臂32的剪切模量G、和机臂32扭转转动惯量I，确定机臂32的临界失稳长度L1；以及用于根据机臂32的临界失稳长度L1，确定对应于机臂32的半径r、机臂32的长度L、机臂32的剪切模量G、和机臂32扭转转动惯量I的机臂32的长度L的取值范围。
关于该部分的解释和说明，与步骤S1311、步骤S1312和步骤S1313的解释和说明类似，可参照步骤S1311、步骤S1312和步骤S1313的解释和说明，为避免冗余，在此不再赘述。
请参阅图8和图9，在某些实施方式中，振动模态优化方法包括：
步骤S151：沿机臂32的长度方向将机臂32划分为多个机臂部位；
步骤S152：对多个机臂部位分别进行灵敏度分析以获得每个机臂部位对机臂32的扭转频率ωx的影响强度；
步骤S153：按影响强度从大到小对多个机臂部位进行结构优化。
在某些实施方式中，处理器201用于沿机臂32的长度方向将机臂32划分为多个机臂部位；及用于对多个机臂部位分别进行灵敏度分析以获得每个机臂部位对机臂32的扭转频率ωx的影响强度；以及用于按影响强度从大到小对多个机臂部位进行结构优化。
如此，可使得机臂32在机臂32的长度方向上均匀、平滑，避免机臂32的外径在局部发生剧烈变化，例如开口、剧烈收缩等变化，尤其可以避免在机臂32的两端处的外径的剧烈变化，从而保证机臂32线条的平滑过渡，从而调节扭转频率ωx。具体地，机臂32呈曲面，剧烈收缩是指曲面的转折较为剧烈，或者说，曲率较大，曲率半径较小。机臂32的均匀性在剧烈收缩的部位就比较薄弱。
在步骤S151中，在一个例子中，可沿机臂32的长度方向将机臂32划分为7个机臂部位，如图2和图9所示，从机身20至电机34的方向，7个机臂部位分别为机臂部位P1、机臂部位P2、机臂部位P3、机臂部位P4、机臂部位P5、机臂部位P6、机臂部位P7。其中，通过结构和参数阈值可判断，从机臂部位P5至机臂部位P7，在机臂部位P6剧烈收缩。
在其他的示例中，划分的机臂部位的数量也可为2个、3个、4个、5个、6个、8个或其他数量。在此不进行限定。
灵敏度分析是研究与分析一个系统(或模型)的状态或输出变化对系统参数或周围条件变化的敏感程度的方法。具体在步骤S152中，则是通过灵敏度分析，确定每个机臂部位对机臂32的扭转频率ωx的影响强度。具体地，可分别调节每个机臂部位的刚度、材料参数、尺寸参数等参数，并测量扭转频率ωx的变化程度，从而确定每个机臂部位对机臂32的扭转频率ωx的影响强度。
在步骤S153中，按影响强度从大到小对多个机臂部位进行结构优化，也即是说，先优 化影响强度较大的机臂部位，再优化影响强度较小的机臂部位。如此，可以提高优化的效率，缩短优化的时间。另外，在优化了部分机臂部位已经满足扭转频率ωx的要求，即满足临界失稳桨频ω的要求的情况下，可以不优化剩余部分的机臂部位。
对于图9中的机臂32，经过灵敏度分析，可确定对机臂32的扭转频率ωx的影响强度最高的机臂部位为机臂部位P6，机臂部位P7次之，机臂部位P3次之，机臂部位P5次之，机臂部位P4次之，机臂部位P2次之，机臂部位P1最低。基于此，可先调节机臂部位P6，再调节机臂部位P7、机臂部位P3、机臂部位P5、机臂部位P4、机臂部位P2、机臂部位P1。
在某些实施方式中，步骤S153包括：
增加机臂部位的半径，和/或，在机臂部位增加筋位。
在某些实施方式中，处理器201用于增加机臂部位的半径；和/或，处理器201用于在机臂部位增加筋位。
如此，实现按影响强度从大到小对多个机臂部位进行结构优化。在一个例子中，对机臂部位的剧烈收缩的曲面，扩大半径；在另一个例子中，对机臂部位的下部有开口的曲面，将开口下移，以使下表面与机臂的最低的下表面基本齐平。在又一个例子中，在机臂部位增加筋位，以对机臂部位进行加强，防止机臂部位变形。在再一个例子中，增加机臂部位的半径，并且，在机臂部位增加筋位。在此不进行限定。
在某些实施方式中，振动模态优化方法包括以下至少一种：
调节脚架40和机臂32的连接处结构的刚度以调节机臂32的扭转频率ωx；
调节脚架40的长度以调节机臂32的扭转频率ωx；
调节脚架40下端部的质量以调节机臂32的扭转频率ωx。
在某些实施方式中，处理器201用于执行以下至少一种方法：调节脚架40和机臂32的连接处结构的刚度以调节机臂32的扭转频率ωx；调节脚架40的长度以调节机臂32的扭转频率ωx；调节脚架40下端部的质量以调节机臂32的扭转频率ωx。
如此，通过调节脚架40调节机臂32的扭转频率ωx，来满足桨叶50的临界失稳桨频ω的要求。
具体地，机臂32的扭转频率ωx与脚架40和机臂32的连接处结构的刚度正相关；机臂32的扭转频率ωx与脚架40的长度负相关；机臂32的扭转频率ωx与脚架40下端部的质量负相关。如此，通过机臂32的扭转频率ωx与上述参数的相关性，可更加准确快速地调节上述参数，有利于缩短调节的时间和提高调节的效率。
可通过对脚架40加筋位、对脚架40加厚度，增加脚架40和机臂32的连接件，来调节脚架40和机臂32的连接处结构的刚度，使得脚架40和机臂32之间不晃动，或晃 动范围在期望的范围。
请参阅图10和图11，在一个例子中，脚架40包括连接部401和支撑部402，连接部401连接支撑部402和机臂32。连接部401形成有连接孔4011，可先通过三个穿设于连接孔4011的螺钉连接脚架40和机臂32。再通过第四个螺钉，在前三个螺钉的固定平面，即连接部401所在平面的垂直方向上，连接脚架40和机臂32。这样，可以保证脚架40和机臂32之间无缝隙，不晃动。可以理解，脚架40和机臂32的连接偏弱时，容易出现脚架40发生局部振动，从而降低机臂32的扭转频率ωx，使得机臂32的振动更剧烈。这样，可以加强图11中的待加强区域403。请注意，图11中，待加强区域403的不同的灰度，表示不同的待加强程度。
可通过降低脚架40的长度以降低脚架40带来的转动惯量I，从而提高扭转频率ωx。具体地，可在预设的脚架长度范围内，调节脚架40的长度，以避免调节脚架40的长度导致脚架40的功能受到影响。脚架长度范围可基于容置与脚架40内的天线的性能确定，也可基于无人机100对距离地面的高度的要求而确定等因素决定，即要保证脚架40满足附加功能性的情况下，来调整脚架40的长度。
可通过降低脚架40下端部的质量，以提高扭转频率ωx。例如，可采用更轻的材料以降低脚架40下端部的质量。
在某些实施方式中，脚架40的材料与机臂32的扭转频率ωx相关。具体地，可采用高模量、低密度和低吸湿材料。例如，将聚碳酸酯(Polycarbonate，PC)材料改为PA材料，PC模量较低，通常只有2.2，PA模量有4.6，吸湿性也较高。如此，能够提高机臂32的扭转频率ωx、降低机臂振动风险、提高环境适应性。
请参阅图12，在某些实施方式中，脚架40的下端面设有垫片42，垫片42的材料和质量与机臂32的扭转频率ωx相关。
如此，通过设置在脚架40的下端面的垫片42，可以使得无人机100在落地时脚架40更加耐磨。可对垫片42做减重设计，例如将垫片42的厚度限制在预设厚度范围。如此，使得垫片42较薄，重量较轻，有利于提高扭转频率ωx。
在某些实施方式中，垫片42的材料包括热塑性聚氨酯弹性体橡胶(Thermoplastic polyurethanes,TPU)材料。TPU材料质量轻并且胶水粘结性好，采用TPU材料的垫片42，可以降低垫片42的质量，并使得垫片42与脚架40的连接更加稳定。
请参阅图12，在某些实施方式中，机臂32通过转轴3201转动连接机身20，振动模态优化方法包括：
调节转轴3201处的结构刚度以调节机臂32的扭转频率ωx。
在某些实施方式中，机臂32通过转轴3201转动连接机身20，处理器201用于调节 转轴3201处的结构刚度以调节机臂32的扭转频率ωx。
如此，可实现通过调节转轴3201处的结构调节机臂32的扭转频率ωx。可以理解，转轴3201处结构上的虚位和晃动会严重降低扭转频率ωx，从而无法使得桨叶的实际桨频低于临界失稳桨频ω的要求，使振动放大。而调节转轴3201处的结构刚度，可在转轴3201处消除虚位间隙，从而消除各个方向的晃动。
具体地，机臂32的扭转频率ωx与转轴3201处的结构刚度正相关。因此，可增加转轴3201处的结构刚度，以提高扭转频率ωx，从而使得桨叶的实际桨频低于临界失稳桨频ω的要求。
例如，可在转轴3201处设置过盈量，使得机臂32通过转轴3201转动与机身20过盈配合。
又如，可避免转轴3201处的开口角度，从而保证不晃动，避免虚位，使得机臂32通过转轴3201转动与机身20配合紧密。
在图10的示例中，机臂扭转轴如虚线3202所示。
综合以上，机臂32振动的表面原因是桨叶50的转速高于临界转速，即高于临界失稳桨频ω，从而导致桨叶50失稳，机臂32振动。机臂32振动的内部原因是机臂32的长度大、电机34和脚架40引入的质量和惯量大，导致机臂32的扭转频率ωx低。降低了桨叶50失稳的临界转速，在无人机100进行转速高的机动动作时容易发生机臂振动。
本申请实施方式的振动模态优化方法、振动模态优化装置200和无人机100，经过优化机臂32、脚架40、电机34和桨叶50、机臂32的转轴3201处等结构，能够以最少的成本，提高机臂32的扭转频率ωx、使得桨叶的实际桨频低于桨叶50的临界失稳桨频ω的要求，消除机臂振动的风险。这样，能够提升无人机100的机动性能和工作范围，可以提升无人机100的结构可靠性、避免振动导致的炸机。而且，对复杂环境下无人机100的使用可靠性有很大的帮助。
在本说明书的描述中，参考术语“一个实施方式”、“一些实施方式”、“示意性实施方式”、“示例”、“具体示例”、或“一些示例”等的描述意指结合所述实施方式或示例描述的具体特征、结构、材料或者特点包含于本申请的至少一个实施方式或示例中。在本说明书中，对上述术语的示意性表述不一定指的是相同的实施方式或示例。而且，描述的具体特征、结构、材料或者特点可以在任何的一个或多个实施方式或示例中以合适的方式结合。
流程图中或在此以其他方式描述的任何过程或方法描述可以被理解为，表示包括一个或更多个用于执行特定逻辑功能或过程的步骤的可执行指令的代码的模块、片段或部分，并且本申请的优选实施方式的范围包括另外的执行，其中可以不按所示出或讨论的顺序， 包括根据所涉及的功能按基本同时的方式或按相反的顺序，来执行功能，这应被本申请的实施方式所属技术领域的技术人员所理解。
在流程图中表示或在此以其他方式描述的逻辑和/或步骤，例如，可以被认为是用于执行逻辑功能的可执行指令的定序列表，可以具体执行在任何计算机可读介质中，以供指令执行系统、装置或设备(如基于计算机的系统、包括处理器的系统或其他可以从指令执行系统、装置或设备取指令并执行指令的系统)使用，或结合这些指令执行系统、装置或设备而使用。就本说明书而言，"计算机可读介质"可以是任何可以包含、存储、通信、传播或传输程序以供指令执行系统、装置或设备或结合这些指令执行系统、装置或设备而使用的装置。计算机可读介质的更具体的示例(非穷尽性列表)包括以下：具有一个或多个布线的电连接部(电子装置)，便携式计算机盘盒(磁装置)，随机存取存储器(RAM)，只读存储器(ROM)，可擦除可编辑只读存储器(EPROM或闪速存储器)，光纤装置，以及便携式光盘只读存储器(CDROM)。另外，计算机可读介质甚至可以是可在其上打印所述程序的纸或其他合适的介质，因为可以例如通过对纸或其他介质进行光学扫描，接着进行编辑、解译或必要时以其他合适方式进行处理来以电子方式获得所述程序，然后将其存储在计算机存储器中。
应当理解，本申请的各部分可以用硬件、软件、固件或它们的组合来执行。在上述实施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来执行。例如，如果用硬件来执行，和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来执行：具有用于对数据信号执行逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)，现场可编程门阵列(FPGA)等。
本技术领域的普通技术人员可以理解执行上述实施方法携带的全部或部分步骤是可以通过程序来指令相关的硬件完成，所述的程序可以存储于一种计算机可读存储介质中，该程序在执行时，包括方法实施方式的步骤之一或其组合。
此外，在本申请各个实施方式中的各功能单元可以集成在一个处理模块中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个模块中。上述集成的模块既可以采用硬件的形式执行，也可以采用软件功能模块的形式执行。所述集成的模块如果以软件功能模块的形式执行并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。
上述提到的存储介质可以是只读存储器，磁盘或光盘等。尽管上面已经示出和描述了本申请的实施方式，可以理解的是，上述实施方式是示例性的，不能理解为对本申请的限制，本领域的普通技术人员在本申请的范围内可以对上述实施方式进行变化、修改、替换和变型。

Claims (38)

  1. 一种振动模态优化方法，用于无人机，其特征在于，所述无人机包括机身和机臂组件，所述机臂组件包括机臂和电机，所述机臂的一端可转动地连接所述机身，所述机臂另一端的顶部连接有所述电机，所述机臂另一端的底部连接有脚架，所述电机的输出轴连接有桨叶；
    所述振动模态优化方法包括：
    获取所述桨叶的临界失稳桨频；
    根据所述桨叶的临界失稳桨频，调节所述机臂的扭转频率、所述桨叶的桨叶平面到机臂扭转轴的距离和所述机臂组件关于所述机臂扭转轴的惯性矩中的至少一个。
  2. 根据权利要求1所述的振动模态优化方法，其特征在于，
    所述临界失稳桨频与所述机臂的扭转频率正相关；
    所述临界失稳桨频与所述桨叶平面到所述机臂扭转轴的距离的平方负相关；
    所述临界失稳桨频与所述机臂组件关于所述机臂扭转轴的惯性矩负相关。
  3. 根据权利要求1所述的振动模态优化方法，其特征在于，所述振动模态优化方法包括：
    调节所述机臂的半径、所述机臂的壁厚、所述机臂的长度、所述机臂的剪切模量、所述机臂扭转的转动惯量中的至少一个来调节所述机臂的扭转频率。
  4. 根据权利要求3所述的振动模态优化方法，其特征在于，所述机臂的剪切模量与所述机臂的材料相关。
  5. 根据权利要求4所述的振动模态优化方法，其特征在于，所述机臂的材料包括聚酰胺，或聚酰胺与玻璃纤维的混合材料。
  6. 根据权利要求3所述的振动模态优化方法，其特征在于，
    所述机臂的扭转频率与所述机臂的半径正相关；
    所述机臂的扭转频率与所述机臂的壁厚正相关；
    所述机臂的扭转频率与所述机臂的长度负相关；
    所述机臂的扭转频率与所述机臂的剪切模量正相关；
    所述机臂的扭转频率与所述机臂扭转转动惯量负相关。
  7. 根据权利要求3所述的振动模态优化方法，其特征在于，所述振动模态优化方法包括：
    根据所述桨叶的临界失稳桨频、所述桨叶的桨叶平面到机臂扭转轴的距离、和所述机臂组件关于所述机臂扭转轴的惯性矩，确定机臂的临界失稳扭转频率；
    根据机臂的临界失稳扭转频率、所述机臂的壁厚、所述机臂的长度、所述机臂的剪切模量、和所述机臂扭转转动惯量，确定所述机臂的临界失稳半径；
    根据所述机臂的临界失稳半径，确定对应于所述机臂的壁厚、所述机臂的长度、所述机臂的剪切模量、和所述机臂扭转转动惯量的所述机臂的半径的取值范围。
  8. 根据权利要求3所述的振动模态优化方法，其特征在于，所述振动模态优化方法包括：
    根据所述桨叶的临界失稳桨频、所述桨叶的桨叶平面到机臂扭转轴的距离、和所述机臂组件关于所述机臂扭转轴的惯性矩，确定机臂的临界失稳扭转频率；
    根据机臂的临界失稳扭转频率、所述机臂的半径、所述机臂的长度、所述机臂的剪切模量、和所述机臂扭转转动惯量，确定所述机臂的临界失稳壁厚；
    根据所述机臂的临界失稳壁厚，确定对应于所述机臂的半径、所述机臂的长度、所述机臂的剪切模量、和所述机臂扭转转动惯量的所述机臂的壁厚的取值范围。
  9. 根据权利要求3所述的振动模态优化方法，其特征在于，所述振动模态优化方法包括：
    根据所述桨叶的临界失稳桨频、所述桨叶的桨叶平面到机臂扭转轴的距离、和所述机臂组件关于所述机臂扭转轴的惯性矩，确定机臂的临界失稳扭转频率；
    根据机臂的临界失稳扭转频率、所述机臂的壁厚、所述机臂的半径、所述机臂的剪切模量、和所述机臂扭转转动惯量，确定所述机臂的临界失稳长度；
    根据所述机臂的临界失稳长度，确定对应于所述机臂的半径、所述机臂的长度、所述机臂的剪切模量、和所述机臂扭转转动惯量的所述机臂的长度的取值范围。
  10. 根据权利要求1所述的振动模态优化方法，其特征在于，所述振动模态优化方法包括：
    沿所述机臂的长度方向将所述机臂划分为多个机臂部位；
    对所述多个机臂部位分别进行灵敏度分析以获得每个所述机臂部位对所述机臂的扭转 频率的影响强度；
    按所述影响强度从大到小对所述多个机臂部位进行结构优化。
  11. 根据权利要求10所述的振动模态优化方法，其特征在于，按所述影响强度从大到小对所述多个机臂部位进行结构优化，包括：
    增加所述机臂部位的半径，和/或，在所述机臂部位增加筋位。
  12. 根据权利要求1所述的振动模态优化方法，其特征在于，所述振动模态优化方法包括以下至少一种：
    调节所述脚架和所述机臂的连接处结构的刚度以调节所述机臂的扭转频率；
    调节所述脚架的长度以调节所述机臂的扭转频率；
    调节所述脚架下端部的质量以调节所述机臂的扭转频率。
  13. 根据权利要求12所述的振动模态优化方法，其特征在于，所述机臂的扭转频率与所述脚架和所述机臂的连接处结构的刚度正相关；
    所述机臂的扭转频率与所述脚架的长度负相关；
    所述机臂的扭转频率与所述脚架下端部的质量负相关。
  14. 根据权利要求1所述的振动模态优化方法，其特征在于，所述脚架的材料与所述机臂的扭转频率相关。
  15. 根据权利要求1所述的振动模态优化方法，其特征在于，所述脚架的下端面设有垫片，所述垫片的材料和质量与所述机臂的扭转频率相关。
  16. 根据权利要求15所述的振动模态优化方法，其特征在于，所述垫片的材料包括热塑性聚氨酯弹性体橡胶。
  17. 根据权利要求1所述的振动模态优化方法，其特征在于，所述机臂通过转轴转动连接所述机身，所述振动模态优化方法包括：
    调节所述转轴处的结构刚度以调节所述机臂的扭转频率。
  18. 根据权利要求17所述的振动模态优化方法，其特征在于，所述机臂的扭转频率与 所述转轴处的结构刚度正相关。
  19. 一种振动模态优化装置，用于无人机，其特征在于，所述无人机包括机身和机臂组件，所述机臂组件包括机臂和电机，所述机臂的一端可转动地连接所述机身，所述机臂另一端的顶部连接有所述电机，所述机臂另一端的底部连接有脚架，所述电机的输出轴连接有桨叶，所述振动模态优化装置包括处理器，所述处理器用于获取所述桨叶的临界失稳桨频；以及用于根据所述桨叶的临界失稳桨频，调节所述机臂的扭转频率、所述桨叶的桨叶平面到机臂扭转轴的距离和所述机臂组件关于所述机臂扭转轴的惯性矩中的至少一个。
  20. 根据权利要求19所述的振动模态优化装置，其特征在于，
    所述临界失稳桨频与所述机臂的扭转频率正相关；
    所述临界失稳桨频与所述桨叶平面到所述机臂扭转轴的距离的平方负相关；
    所述临界失稳桨频与所述机臂组件关于所述机臂扭转轴的惯性矩负相关。
  21. 根据权利要求19所述的振动模态优化装置，其特征在于，所述处理器用于调节所述机臂的半径、所述机臂的壁厚、所述机臂的长度、所述机臂的剪切模量、所述机臂扭转的转动惯量中的至少一个来调节所述机臂的扭转频率。
  22. 根据权利要求21所述的振动模态优化装置，其特征在于，所述机臂的剪切模量与所述机臂的材料相关。
  23. 根据权利要求22所述的振动模态优化装置，其特征在于，所述机臂的材料包括聚酰胺，或聚酰胺与玻璃纤维的混合材料。
  24. 根据权利要求21所述的振动模态优化装置，其特征在于，
    所述机臂的扭转频率与所述机臂的半径正相关；
    所述机臂的扭转频率与所述机臂的壁厚正相关；
    所述机臂的扭转频率与所述机臂的长度负相关；
    所述机臂的扭转频率与所述机臂的剪切模量正相关；
    所述机臂的扭转频率与所述机臂扭转转动惯量负相关。
  25. 根据权利要求21所述的振动模态优化装置，其特征在于，所述处理器用于根据所 述桨叶的临界失稳桨频、所述桨叶的桨叶平面到机臂扭转轴的距离、和所述机臂组件关于所述机臂扭转轴的惯性矩，确定机臂的临界失稳扭转频率；及用于根据机臂的临界失稳扭转频率、所述机臂的壁厚、所述机臂的长度、所述机臂的剪切模量、和所述机臂扭转转动惯量，确定所述机臂的临界失稳半径；以及用于根据所述机臂的临界失稳半径，确定对应于所述机臂的壁厚、所述机臂的长度、所述机臂的剪切模量、和所述机臂扭转转动惯量的所述机臂的半径的取值范围。
  26. 根据权利要求21所述的振动模态优化装置，其特征在于，所述处理器用于根据所述桨叶的临界失稳桨频、所述桨叶的桨叶平面到机臂扭转轴的距离、和所述机臂组件关于所述机臂扭转轴的惯性矩，确定机臂的临界失稳扭转频率；及用于根据机臂的临界失稳扭转频率、所述机臂的半径、所述机臂的长度、所述机臂的剪切模量、和所述机臂扭转转动惯量，确定所述机臂的临界失稳壁厚；以及用于根据所述机臂的临界失稳壁厚，确定对应于所述机臂的半径、所述机臂的长度、所述机臂的剪切模量、和所述机臂扭转转动惯量的所述机臂的壁厚的取值范围。
  27. 根据权利要求21所述的振动模态优化装置，其特征在于，所述处理器用于根据所述桨叶的临界失稳桨频、所述桨叶的桨叶平面到机臂扭转轴的距离、和所述机臂组件关于所述机臂扭转轴的惯性矩，确定机臂的临界失稳扭转频率；及用于根据机臂的临界失稳扭转频率、所述机臂的壁厚、所述机臂的半径、所述机臂的剪切模量、和所述机臂扭转转动惯量，确定所述机臂的临界失稳长度；以及用于根据所述机臂的临界失稳长度，确定对应于所述机臂的半径、所述机臂的长度、所述机臂的剪切模量、和所述机臂扭转转动惯量的所述机臂的长度的取值范围。
  28. 根据权利要求19所述的振动模态优化装置，其特征在于，所述处理器用于沿所述机臂的长度方向将所述机臂划分为多个机臂部位；及用于对所述多个机臂部位分别进行灵敏度分析以获得每个所述机臂部位对所述机臂的扭转频率的影响强度；以及用于按所述影响强度从大到小对所述多个机臂部位进行结构优化。
  29. 根据权利要求28所述的振动模态优化装置，其特征在于，所述处理器用于增加所述机臂部位的半径；和/或，所述处理器用于在所述机臂部位增加筋位。
  30. 根据权利要求19所述的振动模态优化装置，其特征在于，所述处理器用于执行以 下至少一种方法：
    调节所述脚架和所述机臂的连接处结构的刚度以调节所述机臂的扭转频率；
    调节所述脚架的长度以调节所述机臂的扭转频率；
    调节所述脚架下端部的质量以调节所述机臂的扭转频率。
  31. 根据权利要求30所述的振动模态优化装置，其特征在于，所述机臂的扭转频率与所述脚架和所述机臂的连接处结构的刚度正相关；
    所述机臂的扭转频率与所述脚架的长度负相关；
    所述机臂的扭转频率与所述脚架下端部的质量负相关。
  32. 根据权利要求19所述的振动模态优化装置，其特征在于，所述脚架的材料与所述机臂的扭转频率相关。
  33. 根据权利要求19所述的振动模态优化装置，其特征在于，所述脚架的下端面设有垫片，所述垫片的材料和质量与所述机臂的扭转频率相关。
  34. 根据权利要求30所述的振动模态优化装置，其特征在于，所述垫片的材料包括热塑性聚氨酯弹性体橡胶。
  35. 根据权利要求19所述的振动模态优化装置，其特征在于，所述机臂通过转轴转动连接所述机身，所述处理器用于调节所述转轴处的结构刚度以调节所述机臂的扭转频率。
  36. 根据权利要求35所述的振动模态优化装置，其特征在于，所述机臂的扭转频率与所述转轴处的结构刚度正相关。
  37. 一种无人机，其特征在于，所述无人机由权利要求1-18任一项所述的振动模态优化方法优化得到。
  38. 根据权利要求37所述的无人机，其特征在于，所述无人机包括云台，所述云台安装在所述机身，所述云台上设置有拍摄装置。
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