CN118090765A - Unmanned aerial vehicle-mounted detection equipment and method and unmanned aerial vehicle - Google Patents
Unmanned aerial vehicle-mounted detection equipment and method and unmanned aerial vehicle Download PDFInfo
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Abstract
The invention provides unmanned aerial vehicle-mounted detection equipment, method and unmanned aerial vehicle for detecting component abnormality of a target structure, wherein the unmanned aerial vehicle-mounted detection equipment comprises the following components: an image acquisition device for acquiring an image of a target structure; a laser detection mechanism, comprising: a light source; an optical transceiver having a first port and a second port; a first optical path in which a first filtering convergence component for acquiring raman scattered light and a spectroscopic device for acquiring raman scattered spectrum signals reflecting target structure information are provided; photoelectric conversion means for converting an optical signal into an electrical signal; a second optical path in which a second filtering convergence assembly is disposed; a control device configured to determine whether there is a compositional abnormality based on the received image of the target structure and further configured to determine an abnormal compositional parameter based on the received electrical signal.
Description
Technical Field
The present invention relates to an unmanned aerial vehicle-mounted detection device for detecting component anomalies of a target structure, a method executable by the device, and an unmanned aerial vehicle.
Background
In large structures made of, for example, steel materials, material composition changes, such as rust-out of the steel materials, are a safety hazard for the structure. In this regard, component anomaly detection needs to be performed periodically on such large structures in order to discover anomalies in time, track anomalies, evaluate anomalies, and take countermeasures in time.
Currently, in steel structures, rust detection methods mainly include manual visual methods, manual knocking methods, ultrasonic detection methods, electrochemical detection methods, magnetic detection methods and the like. These methods may also suffer from certain drawbacks in terms of detection accuracy or feasibility.
Instead, in recent years, a machine vision-based inspection method has been proposed in which the presence or absence of rust on the surface of a steel structure is determined by means of an image processing algorithm. The rust product of the steel structure is not a single type and the respective types of rust products show similar forms in the image, so that there is a case of erroneous judgment in the machine vision-based detection method. Furthermore, it is also difficult to learn the specific type of rust product using machine vision algorithms, which is detrimental to the subsequent implementation of safety measures.
It should be noted that what is described herein merely provides background information related to the present disclosure and is not necessarily prior art.
Disclosure of Invention
According to various aspects, it is an object of the present invention to provide an improved unmanned aerial vehicle-mounted detection device, a method executable by such a device, and an unmanned aerial vehicle comprising such a device.
In addition, the invention aims to solve or alleviate other technical problems in the prior art.
According to a first aspect of the present invention, the above-mentioned problems are solved by providing an unmanned on-board detection device for detecting component anomalies of a target structure, in particular comprising:
an image acquisition device for acquiring an image of a target structure;
a laser detection mechanism, comprising:
A light source for emitting laser light;
an optical transceiver having a first port and a second port;
A first optical path, in which a first filtering convergence component for acquiring raman scattered light and a spectroscopic device for acquiring raman scattered spectrum signals reflecting target structure information are arranged, the spectroscopic device is located behind the first filtering convergence component along the optical path direction, wherein laser light is emitted to a target structure through the first port, and laser light from the target structure is retroreflected through the first port;
photoelectric conversion means for converting an optical signal into an electrical signal;
a second optical path in which a second filtering convergence assembly is provided, via which laser light is directed to a target structure through the second port and laser light retroreflected from the target structure through the second port is emitted to a photoelectric conversion device;
a control device configured to determine whether there is a compositional abnormality based on the received image of the target structure and further configured to determine an abnormal compositional parameter based on the received electrical signal.
Optionally, in the unmanned aerial vehicle-mounted detection apparatus according to the present invention, the light transceiver and the image acquisition device are arranged to overlap in a vertical direction.
Optionally, in the unmanned aerial vehicle-mounted detection apparatus according to the present invention, the light receiving and transmitting device and the image capturing device are rotatably fixed in a vertical plane to act on the upper, lower and lateral target structures.
Optionally, in the unmanned aerial vehicle detection apparatus according to the present invention, the optical transceiver and the image capturing device are arranged such that the center of the light spot emitted by the first port and the second port is located at the center of the image captured by the image capturing device.
Optionally, in the unmanned aerial vehicle-mounted detection device according to the present invention, the light receiving and transmitting device and the image acquisition device are respectively or jointly assigned with an angle sensor, by means of which the light emitting angle and the light receiving angle of the image acquisition device and the light receiving and transmitting device are measured.
Alternatively, in the unmanned aerial vehicle-mounted detection apparatus according to the present invention, the control device is configured to calculate a vertical distance between the light transceiving device and the target structure based on an electric signal regarding the laser light retroreflected via the second optical path, the light exit angle, and the received light angle, and calculate an actual area corresponding to an image area where a component abnormality exists as a part of the abnormal component parameter based on the vertical distance and the image, in a case where it is determined that the component abnormality exists.
Optionally, in the unmanned aerial vehicle detection apparatus according to the present invention, the control device is further configured to calculate a corresponding raman peak parameter based on an electrical signal characterizing the raman scattering spectrum signal and compare it with a pre-stored fingerprint peak to determine an outlier component type as part of the outlier component parameter.
Optionally, in the unmanned aerial vehicle on-board detection device according to the present invention, the first filtering convergence assembly includes a dichroic mirror, wherein the laser light from the light source is incident at the target structure after transmitting the dichroic mirror, and the scattered light retroreflected from the target structure is incident into the spectroscopic apparatus after being reflected by the dichroic mirror.
Optionally, in the unmanned aerial vehicle-mounted detection device provided by the invention, the light splitting device sequentially comprises a collimating mirror, a diffraction grating and a converging mirror along the light path direction, wherein the laser converged by the converging mirror is emitted to the photoelectric conversion device.
According to a second aspect of the present invention, there is also presented a method for detecting a compositional abnormality of a target structure, comprising the steps executable by such an unmanned aerial vehicle detection device of:
acquiring an image of a target structure, and judging whether the target structure has abnormal components based on the image;
Generating a trigger signal in response to determining that a component abnormality exists, the trigger signal being used to activate the laser detection mechanism;
an electrical signal reflecting information of the target structure is acquired, and an abnormal component parameter of the target structure is determined based on the electrical signal and the image.
Finally, according to a third aspect of the invention, there is also proposed an unmanned aerial vehicle on which the device for detecting a constituent anomaly of a target structure set forth above is arranged.
Optionally, in the unmanned aerial vehicle according to the present invention, the optical transceiver and the image acquisition device are rotatably fixed in a vertical plane at a central hollow structure of a skeleton of the unmanned aerial vehicle by means of a pan-tilt, so as to act on the upper, lower and lateral target structures through the central hollow structure.
Alternatively, in the unmanned aerial vehicle according to the invention, the fuselage comprises two opposing arc-shaped structures at the upper part, the radially inner edges of which form a free space which has a horn-shaped cross section and widens gradually in the direction towards the outside, wherein in the free space the light transceiver and the image acquisition device rotate in a vertical plane without blocking the view angle range thereof.
According to the present disclosure, detection and identification of component anomalies of a target structure can be achieved more accurately by combining "screening for anomalies using machine vision" with "screening results using raman scattering and determining specific anomaly parameters".
Drawings
The above and other features of the present invention will become apparent with reference to the accompanying drawings, in which,
Fig. 1 shows from the front a form of embodiment of a drone according to the invention, on which a detection device for component anomalies of a target structure is provided;
Fig. 2 shows the drone according to fig. 1 from the back side;
fig. 3 shows another embodiment of a drone according to the invention from above;
fig. 4 schematically shows an arrangement of a laser detection mechanism of a detection device according to the invention with respect to an image acquisition means;
Fig. 5 schematically shows an application scenario of a drone according to the invention;
fig. 6 schematically shows another application scenario of the drone according to the invention;
fig. 7 schematically shows a schematic diagram of calculating a vertical distance in a method according to the invention;
fig. 8 shows an optical path configuration of the laser detection mechanism according to the present invention;
FIG. 9 shows a plot of the horizontal axis plotted with Raman peak shift and the vertical axis plotted with Raman scattered photon count for determining anomalous constituent parameters;
Fig. 10 schematically shows an embodiment of the method according to the invention.
Detailed Description
It is to be understood that, according to the technical solution of the present invention, those skilled in the art may propose various alternative structural modes and implementation modes without changing the true spirit of the present invention. Accordingly, the following detailed description and drawings are merely illustrative of the invention and are not intended to be exhaustive or to limit the invention to the precise form disclosed.
Terms of orientation such as up, down, left, right, front, rear, front, back, top, bottom, etc. mentioned or possible to be mentioned in the present specification are defined with respect to the configurations shown in the drawings, which are relative concepts, and thus may be changed according to different positions and different use states thereof. These and other directional terms should not be construed as limiting terms. Furthermore, the terms "first," "second," "third," and the like are used for descriptive and distinguishing purposes only and are not to be construed as indicating or implying a relative importance of the corresponding components.
It should be noted that the unmanned aerial vehicle detection device proposed here is used for detecting component anomalies of a target structure, which can be referred to not only for the steel structures mentioned above (for example the building exterior wall shown in fig. 5 or the bridge shown in fig. 6), but also for other structures of materials, in particular large structures, which over time can develop component anomalies and thus pose a threat to the safety of use. Further, the component abnormality relates to abnormality of chemical components, and is not limited to the steel rust product mentioned above.
Referring to fig. 1, 2, 3 and 8, a drone 100 according to the present invention is illustrated that generally includes a power system 110, a fuselage 120, a battery 130, a central controller 140, and corresponding power and signal connection cables. The power system 110 is for effecting climbing motion in a vertical direction and traversing motion in a horizontal plane and includes a rotor, a motor for the rotor, and a horn for securing the rotor to the fuselage 120. The body 120 includes or is formed of a skeleton 121, and a plurality of support feet 122 are further provided at a lower portion of the body, wherein the body or the skeleton may be made of a lightweight carbon fiber material. The central controller 140 communicates with the user and is used for start-stop and course control of the unmanned aerial vehicle's flight power system. Further, according to the present invention, in order to realize detection of component abnormality of a target structure, particularly a large-sized target structure, a detection device including an image acquisition device 210, a laser detection mechanism 220, and a control device as a whole is mounted on the unmanned aerial vehicle 100.
The control device of the detection device may be integrated in the central controller 140 of the unmanned aerial vehicle, that is to say the central controller may assume both unmanned aerial vehicle flight control tasks and component anomaly detection calculation tasks. For example, unmanned aerial vehicle flight control tasks may be performed at the cloud or remote end, while the control means for the component anomaly detection device may be in the form of an edge calculator that may be arranged directly adjacent to the head for processing at the data source and thereby improving computational efficiency and data transmission accuracy.
The image capturing device 210 is used to capture an image of a target structure, which can be a camera for capturing video or a camera for capturing photographs. The image acquisition device 210 is fastened to the main body 120, in particular to the frame 121, by means of a cradle head 230, wherein the image acquisition device can be moved in space by means of the cradle head. The acquired images or videos are input into a control device of the detection device, wherein whether a component abnormality exists is identified by means of a built-in deep learning algorithm. For example, it is determined whether or not there is a component abnormality by means of a classifier of a built-in neural network model of the control device (which is trained in advance based on a sample set). In other words, here, screening for the presence or absence of component abnormalities is achieved using machine vision.
Referring to fig. 8, a configuration of a laser detection mechanism 220 according to the present invention is shown in schematic form, wherein the optical path is made clearer by the dashed lines. The laser detection mechanism 220 can be activated when it is determined that there is a component abnormality based on the image or activated only when it is determined that there is a component abnormality based on the image to qualitatively analyze the abnormal component by means of laser light. Here, by conditionally triggering the laser detection mechanism 220, the computational load of the control device can be reduced. The laser detection mechanism 220 includes a light source 221, an optical transceiver 222, a beam splitter 223, and a photoelectric conversion device 224, wherein two paths of light paths are formed, namely: a first optical path for determining the type of abnormal component based on raman scattering, and a second optical path for determining a vertical distance based on laser reflection, and then based on the vertical distance, the actual area of the component abnormality can be calculated.
Here, the light source 221 is used to provide laser light for abnormality detection, for example, laser light having a fixed wavelength (which may be denoted as λ 0), which is transmitted into the optical transceiver 222 via a cable and then emitted to the target structure through a corresponding port. According to the present invention, in order to qualitatively analyze abnormal components, a first filtering convergence unit for acquiring raman scattered light in the retro-reflected laser light and a spectroscopic device 223 for separating the raman scattered light to obtain a raman scattered spectrum signal reflecting target structural information are provided in the first optical path. The raman scattered spectrum signal is then transmitted to the photoelectric conversion device 224 where the number of photons of different wavelengths in the optical path is detected and an electrical signal is generated accordingly. The electrical signal is transmitted to a control device, in which the corresponding abnormal component parameters, for example the abnormal component type, are detected by means of a built-in spectral analysis method. The photoelectric conversion device 224 may be implemented as a photosensor, for example.
In summary, the detection apparatus according to the present invention is configured to screen whether or not there is a component abnormality based on the received image of the target structure, on the one hand, and to screen the screening result based on the received electric signal and specifically determine the abnormal component parameter, on the other hand. Taking steel rust detection as an example, wherein rust products can comprise alpha-FeOOH, gamma-FeOOH and alpha-Fe 2O3、Fe3O4, the performances of the rust products in terms of laser Raman scattering are different from each other, by means of the fusion detection method, the detection efficiency is improved by visual large-scale rapid intelligent identification, and the specific rust products are determined by laser Raman scattering, which is clearly advantageous in practical application.
In some embodiments, the first filter convergence assembly of the first optical path comprises a first convex lens 2221, a first filter 2222 (especially a bandpass filter), a dichroic mirror 2225, a second convex lens located at the first port (which is relatively to the right in the drawing and which is not provided with a reference numeral in the drawing for clarity), a mirror 2226, a second filter 2227 (especially a lowpass filter), and a third convex lens 2228. On the incident light path of the first light path, the laser light from the light source 221 split into the first light path is first converged and filtered by the first convex lens 2221 and the first filter 2222, and then transmitted through the dichroic mirror 2225 arranged at an angle of 45 ° to the light, and then, after being converged again by the second convex lens, is emitted from the first port of the optical transceiver 222 onto the target structure. For the retro-reflective optical path of the first optical path, after converging the laser light emitted from the target structure through the second convex lens at the first port, the non-scattered light portion thereof transmits the dichroic mirror 2225, and the scattered light portion thereof is reflected by the dichroic mirror 2225. The scattered light portion is reflected by the mirror 2226 and filtered by the second filter 2227, and the filtered scattered light portion is focused and coupled into the transmission fiber by the third convex lens 2228 and reaches the spectroscopic device 223.
In other embodiments, the beam splitting device 223 includes a collimator lens 2231, a diffraction grating 2232 and a converging lens 2233 sequentially along the optical path direction, wherein the collimator lens 2231 is used to collimate the raman scattered light into parallel light and reflect the parallel light onto the diffraction grating 2232, the raman scattered light with different frequencies are separated by the diffraction grating 2232 and arranged according to wavelengths, and then the raman scattered light with different wavelengths are converged by the converging lens 2233, and finally reflected to the photoelectric conversion device 224, especially the photosensitive element, to be converted into an electrical signal usable by the control device.
In other embodiments, the second light path is a distance measuring light path, i.e. the positional relationship of the drone, in particular the transmitting port of the light transceiver 222, to the structural target is determined based on the principle of laser reflection, which can then be used to determine the actual area of the compositional anomaly. This actual area can be used in practice to evaluate the degree of component abnormality. A second filter assembly is disposed in the second optical path, wherein the laser light split into the second optical path from the light source 221 is emitted onto the target structure via the second filter assembly, and the laser light retroreflected by the target structure is also emitted to the photoelectric conversion device 224 via the second filter assembly. Specifically, as shown in fig. 8, the second filtering convergence assembly includes a fourth convex lens 2223, a third filter 2224 (particularly a bandpass filter), and a fifth convex lens located at the second port (which is relatively located to the right in the drawing and which is not provided with a reference numeral in the drawing for clarity), wherein the filtered and converged laser light is irradiated in parallel onto the target structure. On the retro-reflected light path of the second light path, the laser light from the target structure is filtered by the third filter 2224 after converging by the fifth convex lens, and finally is focus-coupled into a transmission fiber via the fourth convex lens 2223, the output end of the transmission fiber being connected to the photoelectric conversion device 224.
For the second light path for distance measurement, the photoelectric conversion means 224 sends the first reflected signal to the control means, where the light path length is first calculated by the speed of light, the emission time, the reflection time, and then the absolute distance of the light transceiving means (in particular the emission port of the light transceiving means) to the surface of the target structure is obtained after deducting the known transmission distance within the device, which is marked L in fig. 7.
In embodiments where the two optical paths are provided, the optical transceiver 222 has a first port for the first optical path through which laser light is emitted to the target structure, and through which laser light retroreflected from the target structure propagates into the retroreflected optical path. The optical transceiver 222 also has a second port for a second optical path, and likewise, laser light is emitted through the second port to the target structure and retroreflected through the second port. The first port and the second port may also be referred to herein as transceiving ports. The light receiving and transmitting device 222 and the image capturing device 210 are disposed to overlap in the vertical direction, and further preferably, both are in the vertical perpendicular direction.
The spatial position of the light transceiver 222 and the image acquisition device 210 can be measured by an angle sensor (not shown), which can be assigned to both the light transceiver and the image acquisition device or to both of them. The angle sensor is used to measure the light exit angle (which may be referred to as the light exit angle) and the light receiving angle (which may be referred to as the light receiving angle) of the light transceiver 222 and the image pickup device 210, which involves an azimuth angle in the horizontal plane and an inclination angle in the vertical plane, based on which the centers of the light exit and light receiving ports of both are maintained in a vertical line position.
In some embodiments, the light transceiving device 222 and the image capture device 210 are arranged in a vertical direction such that the spot centers of the laser light emitted from the first port and the second port of the light transceiving device are at the center of the image captured by the image capture device, or as much as possible. Taking a steel structure as an example, the plane shape formed by rust development may be irregular, so that the light spot center is positioned at the image center, and misjudgment caused by that a laser spot is not actually hit in a rust area due to a special rust shape can be avoided. As shown in fig. 4, the spot center (which is represented by a black dot) is located at the center of the acquired image (which is represented by a box), wherein the component anomaly region is outlined by a curve.
In other embodiments, the light transceiver 222 and the image capture device 210 are fixed by means of a cradle head such that they are rotatable in a vertical plane to achieve unobstructed extension of the viewing angle range of the light transceiver and the image capture device to an upper target structure (e.g., the lower surface of the bridge in fig. 6), a lower target structure (e.g., the upper surface of the bridge in fig. 6), and a lateral target structure (e.g., the outer wall of the building in fig. 5). The expression "rotatable in the vertical plane" can be understood in connection with fig. 3, wherein the image acquisition means 210 and the light transceiving means 222 are rotated in a plane perpendicular to the plane of the drawing, i.e. both are rotatable about a horizontal own central axis. The image acquisition device 210 and the light transceiver 222 are rotatable 360 ° in particular in a vertical plane. The rotatability mentioned here can be achieved by means of the movement of the holder 230.
In order to keep the viewing angle range of the light transceiver 222 and the image capture device 210 unobstructed in a plurality of orientations or in each case, the unmanned aerial vehicle according to the invention can be designed in such a way that both are fastened to the central hollow 1211 of the unmanned aerial vehicle frame by means of the tripod head 230, the light rays emitted by both pass through the central channel of the central hollow 1211 to the target structure and the retroreflected light rays pass through the central channel back into both. As illustrated in fig. 3, the central hollow 1211 is a circular ring structure on which the light transceiver 222 and the image capture device 210 are centrally supported by the holder 230.
It should be noted that, the viewing angle ranges of the light transceiver 222 and the image capturing device 210 are at least unobstructed when the light outlet and the light receiving outlet of both are located on a horizontal line or on a vertical line.
It is of course possible that the viewing angle range of the light transceiver 222 and the image capture device 210 is not blocked when they are rotated in a vertical plane, in particular 360 ° rotation, which can be achieved by a rational design of the skeleton and the fuselage. In the alternative embodiment shown in fig. 3, the fuselage comprises two opposing arc structures 123 in the upper part, the distance between the radially inner edges of which forms a free space. The free space has a horn-shaped cross section and gradually widens in a direction toward the outside, in which the light transceiving means 222 and the image pickup means 210 are not shielded in their viewing angle ranges when rotated in a vertical plane and can efficiently pick up images or receive and dispatch laser light. The arc-shaped structures 123 are connected by circular connection parts made of carbon fibers, for example.
In the embodiment shown in fig. 3, the overall spatial arrangement of the drone can be understood in analogy to fig. 1. Specifically, in the accommodation space surrounded by the arc structure 123 and the lower skeleton 121, the battery 130 for supplying power to the entire apparatus may be fixed in an annular space surrounding the center hollow structure, and the spectroscopic device 223, the control device or the center controller 140 of the laser detection mechanism, and the corresponding signal power and signal connection cable may be fixed below the cradle head 230, specifically, may be fixed on the skeleton of the unmanned aerial vehicle through a bracket.
In an alternative embodiment, the detection device for component anomalies is configured to acquire an electrical signal of the second light path for distance measurement, a sensor signal of the angle sensor and image data and to calculate the actual area in which the component anomalies occur as part of the anomalous component parameters on the basis of this if a component anomaly is found to exist when the preliminary screening is carried out on the basis of the images. Specifically, first, a vertical distance d between the optical transceiver and the target structure is calculated based on the electric signal and the sensor signal (i.e., the sensor signals on the light emitting angle and the light receiving angle described above) and the viewing angle range of the image pickup device is acquired based thereon. Next, the number of pixels of the image area where the composition abnormality exists is acquired and the corresponding actual area is calculated by pixel conversion. Here, the horizontal azimuth angle and the vertical inclination angle measured by the angle sensor are denoted by α 1 and α 2, respectively, and d=l×cos α 1*cosα2.
In still other embodiments, the control device is further configured to calculate a corresponding raman peak parameter from the electrical signal in the first optical path that characterizes the raman scattering spectrum signal and compare it to a pre-stored fingerprint peak to determine an anomalous component type as part of the anomalous component parameter. Specifically, first, an electrical signal characterizing a raman scattering spectrum signal is acquired and a corresponding raman peak offset is calculated; secondly, calculating a Raman peak parameter based on the calculated Raman peak offset; subsequently, the calculated raman peak parameter is compared with a pre-stored fingerprint peak and the abnormal component type is determined based on the comparison result.
Taking steel rust products as an example, the determination steps of the specific abnormal component types based on Raman scattering are described with reference to FIG. 9, wherein the horizontal axis represents Raman peak shift [ ]) In cm -1, where/>The vertical axis is the number of raman scattered photons, which is the wavelength of raman scattered light, and the unit is one. It should be noted that fig. 9 is merely exemplary and is intended to present different behavior of different rust products in terms of raman scattering or may be said to be different in fig. 9, wherein the specific values represented per unit length on the horizontal and vertical axes may be set at will. It will also be appreciated that the number of raman scattered photons represented by the vertical axis may also be replaced by other parameters which clearly represent the difference between the number of raman photons. Here, the control device decomposes the kernel function to obtain the main peak position (i.e., the horizontal axis coordinate position corresponding to the occurrence of the amplitude in fig. 9) as the raman peak parameter, and compares it with the fingerprint peaks of the rust products α -FeOOH, γ -FeOOH, α -Fe 2O3、Fe3O4 to determine the specific type of the rust product.
In actual operation, can send prompt signal to the mobile controller of inspector when discerning corrosion, can store the information such as image, the actual area of the corrosion product of this steel structure, unmanned aerial vehicle flight position appearance that corresponds to in memory or the high in the clouds simultaneously. It is also contemplated that the above information may be integrated to facilitate overall assessment of the structure's rust, such as by integrating the overall rust area, the ratio of rust area to total detected surface area, the ratio of area of different rust products, and the rust product profile. And then, the development trend of the rust at the part can be tracked by periodically and fixed-point flying the part, so that the time-varying tracking evaluation of the rust is realized.
Furthermore, according to a further aspect of the invention, a method is proposed which can be carried out by the unmanned aerial vehicle detection device according to the invention or the unmanned aerial vehicle according to the invention for detecting a component anomaly of a target structure. According to fig. 10, the method may comprise the steps of:
acquiring an image of a target structure, and judging whether the target structure has abnormal components based on the image;
generating a trigger signal for activating the laser detection mechanism in response to determining that a component anomaly exists;
An electrical signal reflecting the information of the target structure is acquired, and an abnormal component parameter of the target structure is determined based on the electrical signal and the image.
By combining machine vision based screening for the presence or absence of component anomalies with specific determination of anomalous component parameters by means of a laser, a more accurate and comprehensive detection of component anomalies can be achieved.
Specifically, the determination of the abnormal component parameters of the target structure may also be performed as follows:
First, an electric signal regarding the laser light retroreflected through the second optical path and a sensor signal of an angle sensor (i.e., the above-mentioned sensor signals regarding the light emitting angle and the light receiving angle of the image pickup device and the light transceiving device) are acquired, and a vertical distance between the light transceiving device and the target structure is calculated based on the electric signal and the sensor signal;
next, after determining an image area in which a component abnormality exists in an image, for example, by means of a built-in neural network model, an actual area in which the component abnormality exists is calculated based on the image area and the vertical distance.
Specifically, when determining the abnormal component parameters of the target structure, the following steps can also be performed:
Firstly, acquiring an electric signal representing a Raman scattering spectrum signal and calculating a corresponding Raman peak value offset;
Secondly, calculating a Raman peak parameter based on the calculated Raman peak offset;
The calculated raman peak parameter is then compared with a pre-stored fingerprint peak and the type of abnormal component is determined based on the comparison, as can be explained above with reference to the control means of the unmanned airborne detection device according to the present invention.
The method according to the invention yields, in particular, the advantages and features already described above with respect to the unmanned aerial vehicle detection device and the unmanned aerial vehicle according to the invention, and reference is made accordingly to the description made in respect thereof.
It should be understood that all of the above preferred embodiments are exemplary and not limiting, and that various modifications or variations of the above-described specific embodiments, which are within the spirit of the invention, should be made by those skilled in the art within the legal scope of the invention.
Claims (13)
1. An unmanned aerial vehicle-mounted detection device for detecting component anomalies of a target structure, comprising:
an image acquisition device for acquiring an image of a target structure;
a laser detection mechanism, comprising:
A light source for emitting laser light;
an optical transceiver having a first port and a second port;
A first optical path, in which a first filtering convergence component for acquiring raman scattered light and a spectroscopic device for acquiring raman scattered spectrum signals reflecting target structure information are arranged, the spectroscopic device is located behind the first filtering convergence component along the optical path direction, wherein laser light is emitted to a target structure through the first port, and laser light from the target structure is retroreflected through the first port;
photoelectric conversion means for converting an optical signal into an electrical signal;
a second optical path in which a second filtering convergence assembly is provided, via which laser light is directed to a target structure through the second port and laser light retroreflected from the target structure through the second port is emitted to a photoelectric conversion device;
a control device configured to determine whether there is a compositional abnormality based on the received image of the target structure and further configured to determine an abnormal compositional parameter based on the received electrical signal.
2. The unmanned aerial vehicle of claim 1, wherein the light transceiver and the image capture device are arranged vertically one above the other.
3. The unmanned aerial vehicle of claim 2, wherein the light transceiver and the image acquisition device are rotatably fixed in a vertical plane to act on upper, lower, and lateral target structures.
4. An unmanned airborne detection apparatus according to claim 2, wherein the light transceiving means and the image acquisition means are arranged such that the centre of the spot emitted by the first and second ports is located at the centre of the image acquired by the image acquisition means.
5. The unmanned aerial vehicle-mounted detection apparatus according to claim 2, wherein the light receiving and transmitting device and the image pickup device are respectively or jointly assigned with an angle sensor by which the light emitting angle and the light receiving angle of the image pickup device and the light receiving and transmitting device are measured.
6. The unmanned aerial vehicle-mounted detection apparatus according to claim 5, wherein the control device is configured to calculate a vertical distance between the light-transceiving device and the target structure based on an electric signal regarding the laser light retroreflected via the second optical path, the light-emitting angle, the received light angle, and calculate an actual area corresponding to an image area where a component abnormality exists as a part of the abnormal component parameter based on the vertical distance and the image, in a case where it is determined that a component abnormality exists.
7. The unmanned aerial vehicle detection apparatus of claim 1, wherein the control device is further configured to calculate a corresponding raman peak parameter based on the electrical signal representative of the raman scattering spectrum signal and compare it to a pre-stored fingerprint peak to determine an outlier component type as part of the outlier component parameter.
8. The unmanned aerial vehicle detection apparatus of claim 1, wherein the first filtering convergence assembly comprises a dichroic mirror, wherein laser light from the light source strikes a target structure after transmitting the dichroic mirror, and scattered light retroreflected from the target structure strikes the beam splitting device after being reflected by the dichroic mirror.
9. The unmanned aerial vehicle-mounted detection apparatus according to claim 1, wherein the spectroscopic device includes a collimator lens, a diffraction grating, and a converging lens in this order along the optical path direction, wherein the laser light converged by the converging lens is emitted to the photoelectric conversion device.
10. A method for detecting a compositional anomaly of a target structure, comprising the steps executable by an unmanned on-board detection device according to any one of claims 1 to 9 of:
acquiring an image of a target structure, and judging whether the target structure has abnormal components based on the image;
Generating a trigger signal in response to determining that a component abnormality exists, the trigger signal being used to activate the laser detection mechanism;
an electrical signal reflecting information of the target structure is acquired, and an abnormal component parameter of the target structure is determined based on the electrical signal and the image.
11. An unmanned aerial vehicle comprising an unmanned airborne detection apparatus according to any of claims 1 to 9.
12. The unmanned aerial vehicle of claim 11, wherein the light transceiver and the image capture device are rotatably secured in a vertical plane at a central hollowed-out structure of the unmanned aerial vehicle's skeleton by means of a pan-tilt to act on upper, lower and lateral target structures through the central hollowed-out structure.
13. The unmanned aerial vehicle of claim 12, wherein the fuselage comprises two opposing arcuate structures in an upper portion, the radially inner edges of the two opposing arcuate structures forming a free space having a horn-shaped cross section and widening gradually in an outward direction, wherein in the free space the light receiving and transmitting device and the image capturing device rotate in a vertical plane without blocking the range of viewing angles thereof.
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