CN109060286B - Digital speckle-based unmanned aerial vehicle low-frequency vibration detection device and method - Google Patents
Digital speckle-based unmanned aerial vehicle low-frequency vibration detection device and method Download PDFInfo
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Abstract
The invention discloses a digital speckle-based unmanned aerial vehicle low-frequency vibration detection device and a digital speckle-based unmanned aerial vehicle low-frequency vibration detection method, wherein the device comprises an unmanned aerial vehicle, a driving excitation mechanism and a vibration detection mechanism, wherein random speckles are respectively sprayed on left and right wings of the unmanned aerial vehicle, a plurality of coding mark points are symmetrically stuck on the driving excitation mechanism, the driving excitation mechanism is connected with the left and right wings of the unmanned aerial vehicle and is used for exciting the left and right wings of the unmanned aerial vehicle to vibrate, the vibration detection mechanism comprises two conjugate visual detection groups, two groups of acceleration sensors and processing equipment, the two conjugate visual detection groups are respectively used for detecting the random speckles and the coding mark points on the left and right wings of the unmanned aerial vehicle, and the two groups of acceleration sensors are respectively arranged on the left and right wings of the unmanned aerial vehicle, and the processing equipment is respectively connected with the two conjugate visual detection groups and the two groups of acceleration sensors. The invention can realize comprehensive, rapid and high-precision vibration detection of the wing part structure of the unmanned aerial vehicle which is mainly loaded to generate vibration.
Description
Technical Field
The invention relates to a vibration detection device, in particular to a digital speckle-based unmanned aerial vehicle low-frequency vibration detection device and method, and belongs to the field of vibration detection of large flexible structures.
Background
The large unmanned aerial vehicle can often receive airflow load to produce low-frequency vibration in the flight to the inside and outside load distribution of wing all can change, produces multiple complex mode vibration such as crooked, torsion, and vibration deformation can seriously influence the flight performance to a certain extent, destroys unmanned aerial vehicle structure, produces even and shakes and makes the aircraft unstability lead to destroying. For a large unmanned aerial vehicle with a span of 40-50 m, the wing tip fluctuation can exceed 1m, and for a falcon type fixed wing unmanned aerial vehicle, the overall size is relatively small, but the aspect ratio is large, so that the lift-drag ratio of a wing part is reduced after loaded deformation, the rolling moment and the yaw moment are obviously increased, the flying performance which needs flexible maneuvering is greatly influenced, and the dynamic deformation influence caused by low-frequency large-amplitude vibration is obvious. Therefore, the method has great significance in low-frequency vibration measurement of the wing part of the unmanned aerial vehicle, which is mainly stressed and generates vibration.
The unmanned aerial vehicle wing vibration detection method is various, but traditional measurement methods such as an acceleration sensor, a strain gauge and a laser displacement sensor are difficult to install on the surface of a wing on the premise that the flight of the unmanned aerial vehicle is not affected, and are single-point measurement, so that wing three-dimensional vibration information cannot be obtained, and more problems exist in the installation and measurement of a large-scale curved surface structure.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a digital speckle-based unmanned aerial vehicle low-frequency vibration detection device which can realize comprehensive, rapid and high-precision vibration detection of a wing part structure of an unmanned aerial vehicle which is mainly loaded to generate vibration.
The invention further aims to provide a digital speckle-based unmanned aerial vehicle low-frequency vibration detection method.
The aim of the invention can be achieved by adopting the following technical scheme:
the utility model provides an unmanned aerial vehicle low frequency vibration detection device based on digital speckle, includes unmanned aerial vehicle, drive actuating mechanism and vibration detection mechanism, the spraying has random speckle respectively on unmanned aerial vehicle's the left and right sides wing, and the symmetry paste has a plurality of coding mark points, drive actuating mechanism is connected with unmanned aerial vehicle's the left and right sides wing for the left and right sides wing of excitation unmanned aerial vehicle produces the vibration, vibration detection mechanism includes two conjugate vision detection group, two sets of acceleration sensor and processing equipment, two conjugate vision detection group are used for detecting the random speckle and the coding mark point on the left and right sides wing respectively, two sets of acceleration sensor set up respectively on unmanned aerial vehicle's the left and right sides wing, processing equipment is connected with two conjugate vision detection group, two sets of acceleration sensor respectively.
Further, unmanned aerial vehicle includes fuselage, aircraft nose, left wing, right wing, fin and screw, the fuselage is connected with aircraft nose, left wing, right wing, fin, screw respectively, left wing and right wing horizontal suspension.
Further, the left wing and the right wing both comprise stringers, ribs, wing tips and ailerons, the stringers are respectively connected with the ribs and the wing tips, the wing tips are arranged at one end of the stringers, the outer sides of the ribs and the wing tips are provided with skin layers, and the ailerons are arranged on the skin layers and are close to the wing tips.
Further, the driving excitation mechanism comprises a first vibration exciter, a second vibration exciter and a signal processing module, wherein the signal processing module is connected with the first vibration exciter and the second vibration exciter respectively, the first vibration exciter is connected with the left wing of the unmanned aerial vehicle, and the second vibration exciter is connected with the right wing of the unmanned aerial vehicle.
Further, the signal processing module comprises a signal generator and a power amplifier, wherein the signal generator is connected with the power amplifier, and the power amplifier is respectively connected with the first vibration exciter and the second vibration exciter.
Further, each conjugate vision detection group comprises two high-speed cameras, two hydraulic holders and two sliding blocks, the two high-speed cameras, the two hydraulic holders and the two sliding blocks are in one-to-one correspondence, each high-speed camera is arranged on the corresponding hydraulic holder, each hydraulic holder is fixed on the corresponding sliding block, and the sliding blocks of the two conjugate vision detection groups are arranged on a sliding rail in a sliding way;
the two conjugate visual detection groups are a first conjugate visual detection group and a second conjugate visual detection group respectively, the two high-speed camera lenses of the first conjugate visual detection group are aligned with random speckles and coding mark points on the left wing of the unmanned aerial vehicle, and the two high-speed camera lenses of the second conjugate visual detection group are aligned with random speckles and coding mark points on the right wing of the unmanned aerial vehicle.
Further, the processing equipment comprises a computer, an A/D acquisition card, a charge amplifier and a synchronous trigger, wherein the computer is connected with two conjugate visual detection groups through the synchronous trigger and is connected with two groups of acceleration sensors through the A/D acquisition card and the charge amplifier in sequence.
Further, the device also comprises a supporting platform, and the unmanned aerial vehicle is fixed on the supporting platform.
Further, the device also comprises a working platform, and the two conjugated vision detection groups are arranged on the working platform.
The other object of the invention can be achieved by adopting the following technical scheme:
the method for detecting the low-frequency vibration of the unmanned aerial vehicle based on the digital speckle comprises the following steps:
adjusting the two high-speed cameras of the first conjugate visual detection group to enable the lenses of the two high-speed cameras to be aligned with random speckle and coding mark points on the left wing of the unmanned aerial vehicle, and adjusting the two high-speed cameras of the second conjugate visual detection group to enable the lenses of the two high-speed cameras to be aligned with random speckle and coding mark points on the right wing of the unmanned aerial vehicle;
calibrating the two high-speed cameras of the first conjugate visual inspection group to obtain internal parameters and a first pose relationship of the two high-speed cameras of the first conjugate visual inspection group; calibrating the two high-speed cameras of the second conjugate vision detection group to obtain internal parameters and a second pose relationship of the two high-speed cameras of the second conjugate vision detection group; calibrating one camera of the first conjugate visual detection group and one camera adjacent to the second conjugate visual detection group to obtain a third pose relationship of the two cameras;
in the driving excitation mechanism, a signal generator sends out an excitation signal, and after the signal is amplified by a power amplifier, a first vibration exciter and a second vibration exciter are driven to excite low-frequency vibration of left and right wings of the unmanned aerial vehicle;
the method comprises the steps that two high-speed cameras of a first conjugate vision detection group collect random speckle sequence images on a left wing of an unmanned aerial vehicle, image coordinates of coding mark points on the left wing are utilized to provide matching initial values, diffusion correlation matching is conducted on speckle areas around the coding mark points, and real-time three-dimensional point cloud of the left wing is rebuilt according to homonymous points of vibration dynamic deformation continuity matching sequence images and combination of internal references and first pose relations of the two high-speed cameras of the conjugate vision detection group;
two high-speed cameras of the second conjugate vision detection group collect random speckle sequence images on the right wing of the unmanned aerial vehicle, provide a matching initial value by utilizing image coordinates of coding mark points on the right wing, carry out diffusion correlation matching on speckle areas around the coding mark points, and reconstruct real-time three-dimensional point cloud of the right wing according to homonymous points of the vibration dynamic deformation continuity matching sequence images and combining internal references and second pose relations of the two high-speed cameras of the conjugate vision detection group;
according to the first pose relation and the third pose relation, converting the real-time three-dimensional point cloud of the right wing into a coordinate system of a high-speed camera of the first conjugate vision detection group to obtain the whole three-dimensional point cloud of the left wing and the right wing under the coordinate system of the high-speed camera, and calculating vibration quantity;
and selecting the vibration quantity of the corresponding point and the vibration quantity detected by the acceleration sensor for comparison verification, modifying the excitation parameters, and carrying out multiple experiments.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the invention, the digital speckle correlation method is utilized to detect the wing part of the unmanned aerial vehicle, random speckle is easy to manufacture, an auxiliary optical structure is not needed, the cost is reduced, the non-contact measurement is realized by adopting two conjugate vision detection groups, the precision is high, the full-field measurement can be realized, circuit noise is not needed to be introduced, and the problem of inconvenient installation of the curved surface detection sensor is avoided; in addition, two groups of acceleration sensors are also arranged and are respectively used for detecting the vibration quantity of the left wing and the right wing of the unmanned aerial vehicle, the detection result is compared with the speckle related detection result for verification, and the reliability of the measurement result is improved.
2. The method adopts a mode of pasting the coding mark points to provide accurate initial values for speckle matching, and uses the coding mark points as centers to diffuse relevant matching, so that the matching efficiency and accuracy are improved; the global unification of the cloud coordinates of the left wing point and the right wing point is realized through the grouping of cameras for multiple three-dimensional calibration.
3. According to the invention, each conjugate vision detection group is provided with two high-speed cameras, the horizontal positions of the two high-speed cameras can be adjusted by moving the two sliding blocks on the sliding rail, so that the position relation between the two high-speed cameras is changed, random speckles and coding mark points of the left wing and the right wing of the unmanned aerial vehicle are ensured to be in the visual detection field range of the two high-speed cameras, the pitching angle and the horizontal angle of the two high-speed cameras can be adjusted by the pitching damping knob and the panoramic rotation knob of the two hydraulic cloud platforms, and the comprehensive, rapid and high-precision vibration detection of the wing part structure mainly loaded by the unmanned aerial vehicle to generate vibration can be realized.
4. According to the invention, more information can be obtained, and the influence of different load conditions on the unmanned plane structure can be studied by changing excitation parameters, fitting a vibration curved surface, calculating the vibration rate, searching the vibration maximum position and the like.
Drawings
Fig. 1 is a schematic diagram of the overall structure of a digital speckle-based low-frequency vibration detection device for an unmanned aerial vehicle according to embodiment 1 of the present invention.
Fig. 2 is a front view of a digital speckle-based low-frequency vibration detection device of an unmanned aerial vehicle according to embodiment 1 of the present invention.
Fig. 3 is a top view of a digital speckle-based low-frequency vibration detection device for a drone according to embodiment 1 of the present invention.
Fig. 4 is a right wing section view of the unmanned aerial vehicle of embodiment 1 of the present invention.
Fig. 5 is a schematic diagram of two conjugate vision inspection groups according to embodiment 1 of the present invention.
Fig. 6 is a general flow chart of a digital speckle-based method for detecting low-frequency vibration of a unmanned aerial vehicle according to embodiment 1 of the present invention.
Fig. 7 is a schematic diagram of matching of the digital speckle-based unmanned aerial vehicle low-frequency vibration detection method according to embodiment 1 of the present invention.
Wherein 1-unmanned plane, 101-fuselage, 102-aircraft nose, 103-left wing, 104-right wing, 1041-stringer, 1042-rib, 1043-wing tip, 1044-aileron, 1045-skin, 105-tail, 106-propeller, 107-first base, 2-random speckle, 3-coded mark point, 4-supporting platform, 401-first vertical support bar, 402-first transverse support bar, 403-base plate, 5-first vibration exciter, 501-first ejector pin, 502-second base, 6-second vibration exciter, 601-second ejector pin, 602-third base, 7-signal generator, 8-power amplifier, 9-first high speed camera, 10-a second high-speed camera, 11-a first hydraulic cradle head, 12-a second hydraulic cradle head, 13-a first slide block, 14-a second slide block, 15-a third high-speed camera, 16-a fourth high-speed camera, 17-a third hydraulic cradle head, 18-a fourth hydraulic cradle head, 19-a third slide block, 20-a fourth slide block, 21-a slide rail, 22-a fourth base, 23-a first acceleration sensor, 24-a second acceleration sensor, 25-a computer, 26-A/D acquisition card, 27-charge amplifier, 28-synchronous trigger, 29-working platform, 2901-second vertical support bar, 2902-first laminate, 2903-second laminate.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but embodiments of the present invention are not limited thereto.
Example 1:
the three-dimensional speckle vision measurement method based on Digital Image Correlation (DIC) technology developed in recent years has been applied to many industrial detection fields by virtue of the advantages of high measurement speed, high precision, strong real-time performance, small influence by light path environment and non-contact full-field measurement, and the method is also very suitable for full-field vibration measurement of unmanned aerial vehicle wings.
The Digital Speckle Correlation Method (DSCM) based on DIC technology is an optical measurement vibration method, images of objects to be measured sprayed with random speckle are collected through a binocular vision system, vibration dynamic deformation continuity is utilized to match corresponding homonymous points of front and rear images according to gray scale correlation coefficients, and three-dimensional point cloud coordinates are reconstructed in real time in combination with a vision three-dimensional calibration result, so that a full-field three-dimensional vibration quantity array is obtained. However, because the randomness of the matching search is low, the matching efficiency and accuracy are generally low, the embodiment adopts the method of pasting special coding mark points, and provides accurate initial values for matching of the adjacent speckle areas by searching the coding mark points in advance, so that diffusion correlation matching is performed, and the detection efficiency and accuracy are improved.
As shown in fig. 1 to 3, the present embodiment provides a digital speckle-based low-frequency vibration detection device for an unmanned aerial vehicle, which includes an unmanned aerial vehicle 1, a driving excitation mechanism and a vibration detection mechanism, wherein the vibration detection mechanism includes two conjugate vision detection groups, two acceleration sensors and a processing device, a dotted line in fig. 1 indicates a connection relationship between the respective devices, a directional arrow indicates a transmission direction of a detection signal flow, and a dotted line in fig. 3 indicates a direction of a high-speed camera lens.
The unmanned aerial vehicle 1 comprises a machine body 101, a nose 102, a left wing 103, a right wing 104, a tail wing 105 and a propeller 106, wherein the machine body 101 is respectively connected with the nose 102, the left wing 103, the right wing 104, the tail wing 105 and the propeller 106, and the left wing 103 and the right wing 104 are horizontally suspended.
The left wing 103 and the right wing 104 are respectively sprayed with random speckles 2, a plurality of coding mark points 3 are symmetrically stuck, non-contact measurement is carried out by utilizing a digital image correlation technique, no load effect is caused, no circuit noise is introduced, the random speckles 2 are adopted as identification matching characteristics, full-field measurement can be realized, meanwhile, the coding mark points 3 are adopted to provide a matching initial value, and searching matching is carried out near a corresponding reference subarea in a target image by utilizing vibration dynamic deformation continuity, so that the efficiency and the precision can be improved; the left wing 103 and the right wing 104 have the same structure, taking the right wing 104 as an example, as shown in fig. 4, the wing comprises a stringer 1041, a wing rib 1042, a wing tip 1043 and an aileron 1044, the stringer 1041 is respectively connected with the wing rib 1042 and the wing tip 1043, the wing tip 1043 is arranged at one suspended end of the stringer 1041, the stringer 1041 bears a main bending moment, the wing rib 1042 provides a transverse support, a skin layer 1045 is arranged outside the wing rib 1042 and the wing tip 1043, the skin is made of a composite material, the aileron 1044 is arranged on the skin layer 1045 and is close to the wing tip 1043, and the aileron 1044 can be used for adjusting the steering of the unmanned aerial vehicle 1.
Preferably, in order to stably support the unmanned aerial vehicle 1, the low-frequency vibration detection device of the unmanned aerial vehicle further comprises a support platform 4, the overall height of the support platform 4 is low, the surfaces of the left wing 103 and the right wing 104 can be ensured to be in the view field range of two conjugate visual detection groups of the vibration detection mechanism, the device comprises four first vertical support rods 401, eight first transverse support rods 402 and a base plate 403, the upper ends of the four first vertical support rods 401 are respectively fixedly connected with the base plate 403 through four first transverse support rods 402, and the middle parts of the four first vertical support rods 401 are respectively connected with the four first transverse support rods 402; the body 101 is fixed on the upper surface of the base plate 403, specifically, the body 101 is disposed above the first base 107, and is fixed on the upper surface of the base plate 403 by the first base 107, both sides of the first base 107 have reinforcing ribs and a baffle plate for fixing the body 101, and the body 101 can be regarded as a rigid fixing portion when vibrating.
In the embodiment, the unmanned aerial vehicle 1 adopts a scaling model, the stringers 1041 and ribs 1042 of the left wing 103 and the right wing 104 are of steel frame structure, the skin layer 1045 adopts high-density EPO material, the wingspan is 1.97m, and the body length is 1.28m; the supporting platform 4 is composed of twelve sections (corresponding to four first vertical supporting rods 401 and eight first transverse supporting rods 402) and is used for supporting a 1500mm multiplied by 1200mm stainless steel plate (corresponding to a base plate 403), and is connected with screws through angle irons.
The driving excitation mechanism is used for exciting the left wing 103 and the right wing 104 of the unmanned aerial vehicle 1 to generate vibration and comprises a first vibration exciter 5, a second vibration exciter 6 and a signal processing module, wherein the signal processing module comprises a signal generator 7 and a power amplifier 8, a first channel of the signal generator 7 is connected with a first channel of the power amplifier 8, a second channel of the signal generator 7 is connected with a second channel of the power amplifier 8, the first channel and the second channel of the power amplifier 8 are respectively connected with the first vibration exciter 5 and the second vibration exciter 6, the first vibration exciter 5 is connected with the left wing 103 through a first ejector rod 501, and the second vibration exciter 6 is connected with the right wing 104 through a second ejector rod 601; the first channel of the signal generator 7 generates an excitation signal, the excitation signal is amplified by the first channel of the power amplifier 8 and then transmitted to the first vibration exciter 5, the second channel of the signal generator 7 generates an excitation signal, the excitation signal is amplified by the second channel of the power amplifier 8 and then transmitted to the second vibration exciter 6, the first ejector rod 501 of the first vibration exciter 5 drives the left wing 103 to vibrate, the second ejector rod 601 of the second vibration exciter 6 drives the right wing 104 to vibrate, when the excitation signal of the first vibration exciter 5 is identical to the excitation signal of the second vibration exciter 6, the left wing 103 and the right wing 104 generate bending vibration, when the phases are opposite, the left wing 103 and the right wing 104 generate torsional vibration, the excitation amplitude or frequency is changed, and the maximum vibration curve of the left wing 103 and the right wing 104 under different excitation conditions can be obtained through the detection result of the random speckle 2, so that the excitation signal generator can be used for unmanned aerial vehicle wing performance research and fatigue failure test.
Specifically, the first exciter 5 is held by the second base 502 and fixed to the substrate 403 through the second base 502, and the second exciter 6 is held by the third base 602 and fixed to the substrate 403 through the third base 602. It will be appreciated that the first exciter 5 may also be fixed to the ground by the second base 502, and the second exciter 6 may also be fixed to the ground by the third base 602.
In the embodiment, the first vibration exciter 5 and the second vibration exciter 6 are JZ-50 magneto-electric vibration exciters of Jia Union measurement and control company, the working frequency is 5-3000 Hz, the amplitude is +/-5 mm, and the rated output is 500N; the signal generator 7 is a multi-function signal generator with model number UTG9002C produced by Ulide UNI-T company, can generate sine waves with frequency error less than or equal to 1% and maximum amplitude of 20V, and can generate sine waves with frequency error of 0.2 Hz-2 MHz; the power amplifier 8 is a 50WD1000 power amplifier manufactured by AR company in America, and has an operating frequency of DC to 1000MHz.
As shown in fig. 1 to 3 and 5, in the vibration detection mechanism, two conjugate visual detection groups are a first conjugate visual detection group and a second conjugate visual detection group, wherein the first conjugate visual detection group is used for detecting random speckles 2 and coding mark points 3 on a left wing 103, and comprises a first high-speed camera 9, a second high-speed camera 10, a first hydraulic tripod head 11, a second hydraulic tripod head 12, a first sliding block 13 and a second sliding block 14, the first high-speed camera 9 is arranged on the first hydraulic tripod head 11, the second high-speed camera 10 is arranged on the second hydraulic tripod head 12, the first hydraulic tripod head 11 is fixed on the first sliding block 13, the second hydraulic tripod head 12 is fixed on the second sliding block 14, and the pitching angle and the horizontal rotation angle of the first high-speed camera 9 and the second high-speed camera 10 can be adjusted through the first hydraulic tripod head 11 and the second hydraulic tripod head 12; the second conjugate vision detection group is used for detecting random speckles 2 and coding mark points 3 on the right wing 104, and comprises a third high-speed camera 15, a fourth high-speed camera 16, a third hydraulic tripod head 17, a fourth hydraulic tripod head 18, a third sliding block 19 and a fourth sliding block 20, wherein the third high-speed camera 15 is arranged on the third hydraulic tripod head 17, the fourth high-speed camera 16 is arranged on the fourth hydraulic tripod head 18, the third hydraulic tripod head 17 is fixed on the third sliding block 19, the fourth hydraulic tripod head 18 is fixed on the fourth sliding block 20, and the pitching angle and the horizontal rotation angle of the third high-speed camera 15 and the fourth high-speed camera 16 can be adjusted through the third hydraulic tripod head 17 and the fourth hydraulic tripod head 18; the first slide block 13, the second slide block 14, the third slide block 19 and the fourth slide block 20 are slidably arranged on a slide rail 21, that is, the first slide block 13, the second slide block 14, the third slide block 19 and the fourth slide block 20 can move on the slide rail 21, the slide rail 21 is fixed on the fourth base 22, and by moving the first slide block 13, the second slide block 14, the third slide block 19 and the fourth slide block 20, the horizontal positions of the first high-speed camera 9, the second high-speed camera 10, the third high-speed camera 15 and the fourth high-speed camera 16 can be adjusted, so that the relative position relationship among the first high-speed camera 9, the second high-speed camera 10, the third high-speed camera 15 and the fourth high-speed camera 16 is changed, in combination with the pitch angle and horizontal rotation angle adjustment of the first high-speed camera 9, the second high-speed camera 10, the third high-speed camera 15 and the fourth high-speed camera 16, the lenses of the first high-speed camera 9 and the second high-speed camera 10 can be aligned with random speckles and coding mark points on the left wing 103, the lenses of the third high-speed camera 15 and the fourth high-speed camera 16 can be aligned with random speckles and coding mark points on the right wing 104, the fields of view of the first high-speed camera 9 and the second high-speed camera 10 can completely comprise the left wing 103, the fields of view of the third high-speed camera 15 and the fourth high-speed camera 16 can completely comprise the right wing 104, and a certain common field of view exists between the second high-speed camera 10 and the third high-speed camera 15; the first conjugate vision detection group detects vibration information of the left wing 103, the second conjugate vision detection group detects vibration information of the right wing 104, and then the point cloud coordinates are unified through pose relations among the high-speed cameras, so that the splicing of the vibration dynamic deformation information of the whole wing is realized.
The two sets of acceleration sensors are a first set of acceleration sensors and a second set of acceleration sensors respectively, the first set of acceleration sensors is provided with two first acceleration sensors 23, the two first acceleration sensors 23 are arranged on the lower surface of the left wing 103 and are close to the wing tip and used for detecting the vibration quantity of the wing tip position of the left wing 103, the second set of acceleration sensors is provided with two second acceleration sensors 24, and the two second acceleration sensors 24 are arranged on the lower surface of the right wing 104 and are close to the wing tip and used for detecting the vibration quantity of the wing tip position of the right wing 104.
The processing device comprises a computer 25, an A/D acquisition card 26, a charge amplifier 27 and a synchronous trigger 28, wherein the computer 25 is connected with a first high-speed camera 9, a second high-speed camera 10, a third high-speed camera 15 and a fourth high-speed camera 16 through the synchronous trigger 28, specifically, the first high-speed camera 9, the second high-speed camera 10, the third high-speed camera 15 and the fourth high-speed camera 16 adopt external triggering to ensure synchronization, the first high-speed camera 9, the second high-speed camera 10, the third high-speed camera 15 and the fourth high-speed camera 16 are respectively connected with four channels of the synchronous trigger 28, the computer 25 outputs a pulse rising edge or a pulse falling edge to trigger synchronous acquisition of the first high-speed camera 9, the second high-speed camera 10, the third high-speed camera 15 and the fourth high-speed camera 16, the acquired images are transmitted into the computer 25 through USB interfaces and stored, the computer 25 analyzes images of random speckles 2, a corresponding image processing program is operated, a matching value is provided by using image coordinates of a coding mark point 3, a corresponding image coordinate of the random speckle 2 is obtained by using a matching value, a three-dimensional coordinate system of a three-dimensional cloud system is obtained by matching the three-dimensional system, and the three-dimensional cloud system is obtained by matching the three-dimensional system; in addition, the computer 25 is connected with the first acceleration sensor 23 and the second acceleration sensor 24 sequentially through the A/D acquisition card 26 and the charge amplifier 27, the first acceleration sensor 23 detects the vibration quantity of the wing tip position of the left wing 103, the second acceleration sensor 24 detects the vibration quantity of the wing tip position of the right wing 104, the vibration quantity is amplified by the charge amplifier 27 and then acquired by the A/D acquisition card 26 and transmitted to the computer 25, and the vibration quantity is compared with the vibration quantity detected by the three-dimensional random speckle 2 for verification.
Preferably, the low-frequency vibration detection device of the unmanned aerial vehicle of the embodiment further comprises a working platform 29, the working platform 29 comprises four second vertical support rods 2901 and two laminates, the two laminates are a first laminate 2902 and a second laminate 2903 from top to bottom respectively, the upper ends of the four second vertical support rods 2901 are fixedly connected with four corners of the first laminate 2902 respectively, the middle lower parts of the four second vertical support rods 2901 are fixedly connected with four corners of the second laminate 2903 respectively, and the fourth base 22 is fixed on the upper surface of the first laminate 2902 through bolts.
In this embodiment, the first high-speed camera 9, the second high-speed camera 10, the third high-speed camera 15 and the fourth high-speed camera 16 are selected from NAC high-speed cameras, NAC Memrecam HX-7S, CMOS sensors are used, the resolution is 2560×1920 pixels, the speed can reach 1000fps, a 32G memory is built in, the download transmission speed is 500M/S, the acquisition and storage of continuous images in the vibration process can be completely realized, the gigabit network and the USB3.0 real-time image output are adopted, the size is 100w×100h×205D (mm), and the weight is 2.9kg; the first hydraulic cradle head 11, the second hydraulic cradle head 12, the third hydraulic cradle head 17 and the fourth hydraulic cradle head 18 are all made of aluminum alloy materials, hydraulic damping is arranged in the hydraulic cradle head, and the pitching angles and the horizontal rotation angles of the first high-speed camera 9, the second high-speed camera 10, the third high-speed camera 15 and the fourth high-speed camera 16 can be adjusted; the slide rail 21 is a Famous F8 carbon fiber slide rail, and the total length is 120cm; the A/D acquisition card 26 selects a Guanghua PCL-813B12-bit 32-channel acquisition card, and the sampling rate is 25kS/s; the charge amplifier 27 is a unidirectional charge sensor with a model number of 8203A, which is manufactured by the company of kittler, and has a nominal measurement range of +/-1000 mv/g and a measurement frequency range of 5 Hz-4 KHz; the synchronous trigger 28 is FPKEN-triggerresynch produced by Fuguangjingji corporation, and can be triggered by pulse rising edge or falling edge, and the radio frequency sensitivity is 100MHz.
As shown in fig. 1 to 6, the present embodiment further provides a method for detecting low-frequency vibration of an unmanned aerial vehicle based on digital speckle, where the method is implemented based on the above device, and includes the following steps:
step one, the first high-speed camera 9 and the second high-speed camera 10 are adjusted, so that lenses of the first high-speed camera 9 and the second high-speed camera 10 are aligned with the random speckle 2 and the code mark point 3 on the left wing 103, and the third high-speed camera 15 and the fourth high-speed camera 16 are adjusted, so that lenses of the third high-speed camera 15 and the fourth high-speed camera 16 are aligned with the random speckle 2 and the code mark point 3 on the right wing 104.
Calibrating the first high-speed camera 9 and the second high-speed camera 10 by using a checkerboard calibration plate to obtain internal references of the first high-speed camera 9 and the second high-speed camera 10 and a first pose relation H 21 The method comprises the steps of carrying out a first treatment on the surface of the Calibrating the third high-speed camera 15 and the fourth high-speed camera 16 by using a checkerboard calibration plate to obtain internal parameters and a second pose relationship H of the third high-speed camera 15 and the fourth high-speed camera 16 43 The method comprises the steps of carrying out a first treatment on the surface of the Second high-speed camera 10 and third high-speed camera 15 are calibrated by checkerboard calibrationCalibrating to obtain a third pose relationship H of the second high-speed camera 10 and the third high-speed camera 15 32 。
Step three, the signal generator 7 sends out excitation signals, and after the signals are amplified by the power amplifier 8, the first vibration exciter 5 and the second vibration exciter 6 are driven to excite the low-frequency vibration of the left wing 103 and the right wing 104.
Step four, the first high-speed camera 9 and the second high-speed camera 10 collect random speckle 2 sequence images on the left wing 103, provide a matching initial value by using the image coordinates of the coding mark point 3 on the left wing 103, perform diffusion correlation matching on the random speckle 2 area around the coding mark point 3, as shown in fig. 7, perform correlation matching in the m×n area with the image coordinates of the corresponding coding point distance (dx, dy) as the center of the next frame, namely select the center of the sub-area with the largest correlation coefficient (DCC) as the matching point, and calculate the correlation coefficient (DCC) as follows:
wherein f=f (x i ，y i ) Representing a reference subregion (x i ，y i ) The gray value at the point is a function of the gray value at the point,represents the average gray value of the reference subregion, g=g (x' i ，y’ i ) Representing the target subregion (x' i ，y’ i ) Gray value at point +.>Representing the average gray value of the target subregion.
And reconstructing the real-time three-dimensional point cloud of the left wing 103 according to the homonymous points of the vibration dynamic deformation continuity matching sequence images and combining the internal parameters and the first pose relationship of the first high-speed camera 9 and the second high-speed camera 10.
Step five, similar to step four, the third high-speed camera 15 and the fourth high-speed camera 16 collect random speckle sequence images on the right wing 104, provide a matching initial value by using image coordinates of the coding mark points 3 on the right wing 104, perform diffusion-related matching on random speckle 2 areas around the coding mark points 3, and reconstruct real-time three-dimensional point cloud of the right wing according to homonymous points of the vibration dynamic deformation continuity matching sequence images and combining internal parameters and second pose relations of the third high-speed camera 15 and the fourth high-speed camera 16.
Step six, according to the first pose relation and the third pose relation, unifying the real-time three-dimensional point cloud conversion of the right wing to the coordinate system of the first high-speed camera 9, obtaining the whole three-dimensional point cloud of the left wing and the right wing in the coordinate system of the first high-speed camera 9, and calculating the vibration quantity, wherein the vibration quantity is as follows:
wherein,representing the three-dimensional coordinates of the speckle in the first high-speed camera 9 coordinate system,/for>Representing three-dimensional coordinates of the speckle in the third high-speed camera 15 coordinate system; h 31 The pose relationship between the first high-speed camera 9 and the third high-speed camera 15 can be obtained through a three-dimensional calibration result as follows:
and seventh, selecting vibration quantity of the corresponding point, comparing and verifying the vibration quantity with the vibration quantity detected by the first acceleration sensor 23 and the second acceleration sensor 24, modifying the excitation parameters, and performing multiple experiments.
In summary, the method utilizes the digital speckle correlation method to detect the wing part of the unmanned aerial vehicle, random speckle is easy to manufacture, no auxiliary optical structure is needed, the cost is reduced, the non-contact measurement is realized by adopting two conjugate vision detection groups, the precision is high, the full-field measurement can be realized, circuit noise is not needed to be introduced, and the problem of inconvenient installation of the curved surface detection sensor is avoided; in addition, two groups of acceleration sensors are also arranged and are respectively used for detecting the vibration quantity of the left wing and the right wing of the unmanned aerial vehicle, the detection result is compared with the speckle related detection result for verification, and the reliability of the measurement result is improved.
The above-mentioned embodiments are only preferred embodiments of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art can make equivalent substitutions or modifications according to the technical solution and the inventive concept of the present invention within the scope of the present invention disclosed in the present invention patent, and all those skilled in the art belong to the protection scope of the present invention.
Claims (7)
1. The unmanned aerial vehicle low-frequency vibration detection method based on the digital speckle is realized by adopting an unmanned aerial vehicle low-frequency vibration detection device based on the digital speckle, and is characterized in that: the device comprises an unmanned aerial vehicle, a driving excitation mechanism, a vibration detection mechanism and a working platform, wherein random speckles are respectively sprayed on the left wing and the right wing of the unmanned aerial vehicle, a plurality of coding mark points are symmetrically stuck on the left wing and the right wing of the unmanned aerial vehicle, the random speckles cover all parts of the left wing and the right wing of the unmanned aerial vehicle, the driving excitation mechanism is connected with the left wing and the right wing of the unmanned aerial vehicle and is used for exciting the left wing and the right wing of the unmanned aerial vehicle to generate vibration, the vibration detection mechanism comprises two conjugate vision detection groups, two groups of acceleration sensors and processing equipment, the two conjugate vision detection groups are respectively used for detecting the random speckles and the coding mark points on the left wing and the right wing of the unmanned aerial vehicle, the two groups of acceleration sensors are respectively connected with the two conjugate vision detection groups, the two conjugate vision detection groups are arranged on the upper surface of the working platform, and the working platform is positioned right in front of the unmanned aerial vehicle; each conjugate vision detection group comprises two high-speed cameras, two hydraulic holders and two sliding blocks, the two high-speed cameras, the two hydraulic holders and the two sliding blocks are in one-to-one correspondence, each high-speed camera is arranged on the corresponding hydraulic holder, each hydraulic holder is fixed on the corresponding sliding block, and the sliding blocks of the two conjugate vision detection groups are arranged on a sliding rail in a sliding way;
the method comprises the following steps:
adjusting the two high-speed cameras of the first conjugate visual detection group to enable the lenses of the two high-speed cameras to be aligned with random speckle and coding mark points on the left wing of the unmanned aerial vehicle, and adjusting the two high-speed cameras of the second conjugate visual detection group to enable the lenses of the two high-speed cameras to be aligned with random speckle and coding mark points on the right wing of the unmanned aerial vehicle;
calibrating the two high-speed cameras of the first conjugate visual inspection group to obtain internal parameters and a first pose relationship of the two high-speed cameras of the first conjugate visual inspection group; calibrating the two high-speed cameras of the second conjugate vision detection group to obtain internal parameters and a second pose relationship of the two high-speed cameras of the second conjugate vision detection group; calibrating one camera of the first conjugate visual detection group and one camera adjacent to the second conjugate visual detection group to obtain a third pose relationship of the two cameras;
in the driving excitation mechanism, a signal generator sends out an excitation signal, and after the signal is amplified by a power amplifier, a first vibration exciter and a second vibration exciter are driven to excite low-frequency vibration of left and right wings of the unmanned aerial vehicle;
the method comprises the steps that two high-speed cameras of a first conjugate vision detection group collect random speckle sequence images on a left wing of an unmanned aerial vehicle, image coordinates of coding mark points on the left wing are utilized to provide matching initial values, diffusion correlation matching is conducted on speckle areas around the coding mark points, and real-time three-dimensional point cloud of the left wing is rebuilt according to homonymous points of vibration dynamic deformation continuity matching sequence images and combination of internal references and first pose relations of the two high-speed cameras of the conjugate vision detection group;
two high-speed cameras of the second conjugate vision detection group collect random speckle sequence images on the right wing of the unmanned aerial vehicle, provide a matching initial value by utilizing image coordinates of coding mark points on the right wing, carry out diffusion correlation matching on speckle areas around the coding mark points, and reconstruct real-time three-dimensional point cloud of the right wing according to homonymous points of the vibration dynamic deformation continuity matching sequence images and combining internal references and second pose relations of the two high-speed cameras of the conjugate vision detection group;
according to the first pose relation and the third pose relation, converting the real-time three-dimensional point cloud of the right wing into a coordinate system of a high-speed camera of the first conjugate vision detection group to obtain the whole three-dimensional point cloud of the left wing and the right wing under the coordinate system of the high-speed camera, and calculating vibration quantity;
and selecting the vibration quantity of the corresponding point and the vibration quantity detected by the acceleration sensor for comparison verification, modifying the excitation parameters, and carrying out multiple experiments.
2. The digital speckle-based unmanned aerial vehicle low-frequency vibration detection method of claim 1, wherein: the unmanned aerial vehicle comprises a machine body, a machine head, a left wing, a right wing, a tail wing and a propeller, wherein the machine body is respectively connected with the machine head, the left wing, the right wing, the tail wing and the propeller, and the left wing and the right wing are horizontally suspended.
3. The digital speckle-based drone low frequency vibration detection method of claim 2, wherein: the left wing and the right wing comprise stringers, ribs, wing tips and ailerons, the stringers are respectively connected with the ribs and the wing tips, the wing tips are arranged at one end of the stringers, the outer sides of the ribs and the wing tips are provided with skin layers, and the ailerons are arranged on the skin layers and are close to the wing tips.
4. The digital speckle-based unmanned aerial vehicle low-frequency vibration detection method of claim 1, wherein: the driving excitation mechanism comprises a first vibration exciter, a second vibration exciter and a signal processing module, wherein the signal processing module is connected with the first vibration exciter and the second vibration exciter respectively, the first vibration exciter is connected with the left wing of the unmanned aerial vehicle, and the second vibration exciter is connected with the right wing of the unmanned aerial vehicle.
5. The digital speckle-based drone low frequency vibration detection method of claim 4, wherein: the signal processing module comprises a signal generator and a power amplifier, wherein the signal generator is connected with the power amplifier, and the power amplifier is respectively connected with the first vibration exciter and the second vibration exciter.
6. The digital speckle-based drone low frequency vibration detection method of any one of claims 1-5, wherein: the processing equipment comprises a computer, an A/D acquisition card, a charge amplifier and a synchronous trigger, wherein the computer is connected with two conjugated vision detection groups through the synchronous trigger and is connected with two groups of acceleration sensors through the A/D acquisition card and the charge amplifier in sequence.
7. The digital speckle-based drone low frequency vibration detection method of any one of claims 1-5, wherein: the device also comprises a supporting platform, and the unmanned aerial vehicle is fixed on the supporting platform.
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