CN108303278B - Method and device for detecting takeoff state of paddle type aircraft - Google Patents
Method and device for detecting takeoff state of paddle type aircraft Download PDFInfo
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Abstract
The invention provides a method and a device for detecting the takeoff state of a paddle type aircraft, which relate to the technical field of unmanned aerial vehicle monitoring, and the method comprises the following steps: obtaining the natural vibration frequency spectrum of the first takeoff machine body of the aircraft through the motion sensor; obtaining a highest energy packet according to the natural vibration frequency spectrum; obtaining a confidence interval according to the highest energy packet; obtaining a first vibration frequency spectrum of the aircraft body through the motion sensor; and comparing the first vibration frequency spectrum with the confidence interval to determine the flight state of the aircraft. The technical problem that the flight state of the unmanned aerial vehicle cannot be accurately recorded and evaluated due to the fact that no standard third party flight state detection authentication exists in the prior art is solved. The technical effects of accurately identifying the takeoff characteristic of the unmanned aerial vehicle, effectively monitoring the flight state of the unmanned aerial vehicle and providing effective flight data of a flyer are achieved.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle monitoring, in particular to a method and a device for detecting the takeoff state of a paddle type aircraft.
Background
Along with the more and more extensive use of unmanned aerial vehicles, the emerging industry of unmanned aerial vehicle flyers is also rising. Because the unmanned aerial vehicle flight degree of difficulty is higher, unmanned aerial vehicle flight hand needs special training to similar with the pilot.
The flight experience of the unmanned aerial vehicle flyer is crucial, and the unmanned aerial vehicle supervision and the flying experience value are recorded.
The technical problem that the flight state of the unmanned aerial vehicle cannot be accurately recorded and evaluated exists in the prior art because no standard third-party flight state detection authentication exists.
Disclosure of Invention
The embodiment of the invention provides a method and a device for detecting the takeoff state of a paddle type aircraft, which solve the technical problem that the flight state of an unmanned aerial vehicle cannot be accurately recorded and evaluated because no standard third party flight state detection authentication exists in the prior art.
In view of the above problems, the embodiments of the present application are proposed to provide a method and a device for detecting the takeoff state of a paddle type aircraft.
In a first aspect, the present invention provides a method for detecting a takeoff state of a paddle type aircraft, which is applied to the paddle type aircraft, wherein the paddle type aircraft is provided with a motion sensor, and the method comprises the following steps: obtaining the natural vibration frequency spectrum of the first takeoff machine body of the aircraft through the motion sensor; obtaining a highest energy packet according to the natural vibration frequency spectrum; obtaining a confidence interval according to the highest energy packet; obtaining a first vibration frequency spectrum of the aircraft body through the motion sensor; and comparing the first vibration frequency spectrum with the confidence interval to determine the flight state of the aircraft.
Preferably, the obtaining the highest energy packet according to the natural vibration spectrum specifically includes: obtaining an empirical formula; determining the position of the vibration fundamental frequency according to the empirical formula; and obtaining the highest energy packet according to the vibration fundamental frequency position.
Preferably, the empirical formula is:
R＝V×KV
F＝μf
wherein R represents the rotating speed and the unit is R/min; f represents the rotation frequency in Hz; f represents the vibration frequency in Hz; μ denotes a scale factor.
Preferably, the comparing the first vibration spectrum with the confidence interval to determine the flight state of the aircraft specifically includes: extracting a judgment threshold value of the confidence interval according to the confidence interval; and comparing the first vibration frequency spectrum with a judgment threshold value of the confidence interval to determine the flight state of the aircraft.
Preferably, the confidence interval is a dynamic interval.
Preferably, the first vibration frequency spectrum is compared with a judgment threshold value of the confidence interval to determine the flight state of the aircraft, and the determination is specifically realized by the following formula:
wherein X is a frequency data vector of the confidence interval;
y is a frequency data vector of the first vibration frequency spectrum;
n is X vector coefficient;
m is a Y vector coefficient;
n is X, Y vector capacity.
In a second aspect, the invention provides a takeoff state detection device for a paddle type aircraft, comprising:
the first obtaining unit is used for obtaining the natural vibration frequency spectrum of the aircraft first takeoff machine body through the motion sensor;
a second obtaining unit, configured to obtain a highest energy packet according to the natural vibration spectrum;
a third obtaining unit, configured to obtain a confidence interval according to the highest energy packet;
a fourth obtaining unit, configured to obtain, by the motion sensor, a first vibration spectrum of the aircraft body;
a first determination unit configured to compare the first vibration spectrum with the confidence interval and determine a flight status of the aircraft.
Preferably, the apparatus further comprises:
a fifth obtaining unit, configured to obtain an empirical formula;
a second determination unit for determining a vibration fundamental frequency position according to the empirical formula;
a sixth obtaining unit configured to obtain the highest energy packet according to the vibration fundamental frequency position.
Preferably, the empirical formula is:
R＝V×KV
F＝μf
wherein R represents the rotating speed and the unit is R/min; f represents the rotation frequency in Hz; f represents the vibration frequency in Hz; μ denotes a scale factor.
Preferably, the apparatus further comprises:
a first extraction unit, configured to extract a determination threshold of the confidence interval according to the confidence interval;
a third determining unit, configured to compare the first vibration spectrum with a judgment threshold value of the confidence interval, and determine a flight state of the aircraft.
Preferably, the apparatus further comprises: the confidence interval is a dynamic interval.
Preferably, the apparatus further comprises: the first vibration frequency spectrum is compared with a judgment threshold value of the confidence interval to determine the flight state of the aircraft, and the determination is specifically realized by the following formula:
wherein X is a frequency data vector of the confidence interval;
y is a frequency data vector of the first vibration frequency spectrum;
n is X vector coefficient;
m is a Y vector coefficient;
n is X, Y vector capacity.
In a third aspect, the present invention provides a takeoff state detection device for a paddle type aircraft, including a memory, a processor and a computer program stored in the memory and operable on the processor, wherein the processor implements the following steps when executing the program: obtaining the natural vibration frequency spectrum of the first takeoff machine body of the aircraft through the motion sensor; obtaining a highest energy packet according to the natural vibration frequency spectrum; obtaining a confidence interval according to the highest energy packet; obtaining a first vibration frequency spectrum of the aircraft body through the motion sensor; and comparing the first vibration frequency spectrum with the confidence interval to determine the flight state of the aircraft.
One or more technical solutions in the embodiments of the present application have at least one or more of the following technical effects:
1. according to the method and the device for detecting the takeoff state of the paddle type aircraft, the natural vibration frequency spectrum of the first takeoff machine body of the aircraft is obtained through the motion sensor; obtaining a highest energy packet according to the natural vibration frequency spectrum; obtaining a confidence interval according to the highest energy packet; obtaining a first vibration frequency spectrum of the aircraft body through the motion sensor; and comparing the first vibration frequency spectrum with the confidence interval to determine the flight state of the aircraft. The technical problem that the flight state of the unmanned aerial vehicle cannot be accurately recorded and evaluated due to the fact that no standard third party flight state detection authentication exists in the prior art is solved. The technical effects of accurately identifying the takeoff characteristic of the unmanned aerial vehicle, effectively monitoring the flight state of the unmanned aerial vehicle and providing effective flight data of a flyer are achieved.
2. According to the method and the device, the technical problem that the flight state of the unmanned aerial vehicle cannot be accurately recorded and evaluated due to the fact that no standard third party flight state detection authentication exists in the prior art is solved through dynamically adjusting the confidence interval. The technical effect of continuously updating and perfecting the confidence interval to ensure the accuracy of the next detection is further achieved.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
FIG. 1 is a schematic flow chart of a method for detecting a takeoff state of a paddle type aircraft according to an embodiment of the invention;
FIG. 2 is a schematic structural diagram of a takeoff state detection device of a paddle type aircraft according to an embodiment of the invention;
FIG. 3 is a schematic structural diagram of another takeoff state detection device of a paddle type aircraft according to an embodiment of the invention;
FIG. 4 is a waveform diagram of the fundamental frequency position of vibration of a paddle type aircraft according to an embodiment of the invention;
fig. 5 is a waveform of a confidence interval for a paddle aircraft in an embodiment of the invention.
Detailed Description
The embodiment of the invention provides a method and a device for detecting the takeoff state of a paddle type aircraft, which are used for solving the technical problem that the flight state of an unmanned aerial vehicle cannot be accurately recorded and evaluated because no standard third party flight state detection authentication exists in the prior art. The technical scheme provided by the invention has the following general idea:
in the technical scheme of the embodiment of the invention, the natural vibration frequency spectrum of the first takeoff machine body of the aircraft is obtained through the motion sensor; obtaining a highest energy packet according to the natural vibration frequency spectrum; obtaining a confidence interval according to the highest energy packet; obtaining a first vibration frequency spectrum of the aircraft body through the motion sensor; and comparing the first vibration frequency spectrum with the confidence interval to determine the flight state of the aircraft. The technical effects of accurately identifying the takeoff characteristic of the unmanned aerial vehicle, effectively monitoring the flight state of the unmanned aerial vehicle and providing effective flight data of a flyer are achieved.
The technical solutions of the present invention are described in detail below with reference to the drawings and specific embodiments, and it should be understood that the specific features in the embodiments and examples of the present invention are described in detail in the technical solutions of the present application, and are not limited to the technical solutions of the present application, and the technical features in the embodiments and examples of the present application may be combined with each other without conflict.
The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
Example one
The embodiment of the application provides a method for detecting the takeoff state of a paddle type aircraft, and fig. 1 is a schematic flow chart of the method for detecting the takeoff state of the paddle type aircraft in the embodiment of the invention. As shown in fig. 1, the method includes:
step 110: obtaining the natural vibration frequency spectrum of the first takeoff machine body of the aircraft through the motion sensor;
specifically, the first flight is the start-up calibration flight when the adaptive machine needs to be adapted, the best identification effect can be realized by the part of operations, and the operation flow is as follows: the Agent positioning equipment is fixed on the surface of a machine → the equipment is started, the machine runs → the mobile phone APP end is bound with the equipment, the equipment is clicked to take off and then normally fly, the equipment is clicked to land after the flight is finished, the machine calibration is finished, and then the equipment automatically detects whether the airplane is started to fly or not without any operation during the flight. The motion sensor is arranged on the paddle type aircraft, and the motion sensor converts motion signals received by the paddle type aircraft into electric signals so as to send the electric signals to a control system wirelessly connected with the paddle type aircraft, wherein the control system can be electronic equipment such as a mobile phone, a tablet personal computer and an intelligent watch. Therefore, the natural vibration frequency spectrum of the aircraft first takeoff body can be sent to the control system. The collective natural vibration frequency spectrum is the vibration frequency spectrum of the aircraft in the normal takeoff state.
Step 120: obtaining a highest energy packet according to the natural vibration frequency spectrum; further, the obtaining the highest energy packet according to the natural vibration spectrum specifically includes: obtaining an empirical formula; determining the position of the vibration fundamental frequency according to the empirical formula; and obtaining the highest energy packet according to the vibration fundamental frequency position. The empirical formula is:
R＝V×KV
F＝μf
wherein R represents the rotating speed and the unit is R/min; f represents the rotation frequency in Hz; f represents the vibration frequency in Hz; μ denotes a scale factor.
Particularly, the unmanned aerial vehicle motor adopts brushless motor mostly. Multiple test experiments show that the natural vibration frequency (non-fault oscillation) of the body is in a direct proportion relation with the motor rotation frequency, and the input of the voltage of the brushless motor of the unmanned aerial vehicle and the idle rotation speed of the motor follow a strict linear proportion relation, so that a formula of the rotation speed and the vibration frequency of the unmanned aerial vehicle is deduced, and the formula is as follows:
R＝V×KV
F＝μf
the data operation range can be simplified according to the confidence interval determined by the empirical formula, so that the operation quantity of the acquisition operation of the confidence interval and the real-time dynamic data matching in the later period is greatly simplified, and the real-time dynamic data processing matching can be realized by the Cortex M4 inner core mobile processor.
In practical application, the rotating speed of the motor is generally not controlled by directly regulating and controlling the voltage, but the rotating speed of the motor is controlled by controlling the electric regulation module through the PWM duty ratio, namely the rotating speed is regulated by regulating the voltage received by the motor according to the PWM duty ratio: when the PWM duty ratio is completely zero, the motor is connected with 0V voltage; when the PWM duty ratio is 100%, the whole voltage of the battery is fed into the motor; when the unmanned aerial vehicle flies normally, the PWM duty ratio range is 30% -100%, and the main energy is concentrated in the range of 0.3F-F.
The KV value distribution of the brushless motor of the unmanned aerial vehicle is about 700 or less, so that the maximum rotation speed can be calculated to be about 48 × 700 — 33600r/min, and it can be presumed that the vibration fundamental frequency position is: 33600/60 Hz 560Hz, when the drone is turned on, there will be a low frequency high energy vibration, i.e. the highest energy packet, which can be detected and recorded by the motion sensor, and this data is used in this system to detect the turning-on state of the drone.
In the embodiment, taking the data collected by the flying hurricane 3510360 KV motor as an example,
according to the formula R24X 360X 8640R/min
F＝8640/60＝144r/s
The natural frequency of the machine body is centered at 0.3F-0.9F → 43-144, as shown in FIG. 4.
It can be seen that the position of the fundamental frequency of vibration is within 100HZ, and the energy packet near 117HZ is the natural frequency of vibration of the body. The back energy package is frequency multiplication and other interference vibration. As shown in FIG. 5, the energy is concentrated at 110-130, the calculated value is basically consistent with the actual measured value, the positive scale factor in the formula is close to 1, the vibration fundamental frequency position can be accurately pre-judged through the pre-estimation calculation of the vibration fundamental frequency position by the empirical formula, the calculated amount is greatly reduced, and the technical effect of improving the detection efficiency is achieved.
Step 130: obtaining a confidence interval according to the highest energy packet;
specifically, the highest vibration frequency energy packet except the fundamental frequency is searched according to the detected vibration frequency, and the confidence interval of the vibration inherent frequency of the motor is judged, for example, the confidence interval of fig. 5 can be extracted according to the data in the test case.
Step 140: obtaining a first vibration frequency spectrum of the aircraft body through the motion sensor;
specifically, when the aircraft is ready to take off, a vibration spectrum of the aircraft is obtained through a motion sensor, wherein the aircraft to take off is ready to receive a detected aircraft, the obtained vibration spectrum is a vibration spectrum generated when the aircraft takes off, various unknown conditions may exist in the vibration spectrum, that is, a certain fault may exist, and the vibration spectrum is the first vibration spectrum.
Step 150: and comparing the first vibration frequency spectrum with the confidence interval to determine the flight state of the aircraft.
Further, the comparing the first vibration spectrum with the confidence interval to determine the flight state of the aircraft specifically includes: extracting a judgment threshold value of the confidence interval according to the confidence interval; and comparing the first vibration frequency spectrum with a judgment threshold value of the confidence interval to determine the flight state of the aircraft. Wherein the confidence interval is a dynamic interval. The first vibration frequency spectrum is compared with a judgment threshold value of the confidence interval to determine the flight state of the aircraft, and the determination is specifically realized by the following formula:
wherein X is a frequency data vector of the confidence interval;
y is a frequency data vector of the first vibration frequency spectrum;
n is X vector coefficient;
m is a Y vector coefficient;
n is X, Y vector capacity.
Specifically, after the confidence interval is correctly obtained, a judgment threshold value is extracted, and the extraction of the threshold value is synchronously performed in the first flight verification process. The extracted threshold value exists in the form of a threshold value domain to judge normal flight of the aircraft under flight modes of different intensities.
After the detection is finished, a vibration confidence interval and a threshold value domain extracted in the follow-up verification flight process are compared with the first vibration frequency spectrum of the aircraft to be detected, if the first vibration frequency spectrum of the lawsuit lake aircraft falls into the confidence interval, the flight state of the aircraft to be detected is normal, and if the first vibration frequency spectrum does not fall into the confidence interval, the aircraft to be detected is in an abnormal flight state, the operation needs to be stopped immediately, and the aircraft to be detected is overhauled. The confidence interval and the confidence domain are continuously updated and perfected in each flight process so as to ensure the accuracy of the next detection.
Further, the process of detecting the flight state of the aircraft to be detected by comparing the confidence interval with the first frequency spectrum is specifically calculated by the following formula, so as to obtain a detection result:
according to the embodiment of the application, the flight fault can be detected when the aircraft is started and does not fly, whether the aircraft to be detected and the aircraft to be detected are the same frame or not can be analyzed according to the frequency spectrum characteristics, and the technical effect of aircraft discrimination is achieved.
Example 2
Based on the same inventive concept as the takeoff state detection method of the paddle type aircraft in the previous embodiment, the invention also provides a takeoff state detection device of the paddle type aircraft, as shown in fig. 2, comprising:
a first obtaining unit 11, configured to obtain, by the motion sensor, a natural vibration spectrum of a first takeoff aircraft body of the aircraft;
a second obtaining unit 12, configured to obtain a highest energy packet according to the natural vibration spectrum;
a third obtaining unit 13, configured to obtain a confidence interval according to the highest energy packet;
a fourth obtaining unit 14 for obtaining a first vibration spectrum of the aircraft body by the motion sensor;
a first determination unit 15 for comparing the first vibration spectrum with the confidence interval and determining the flight status of the aircraft.
Preferably, the apparatus further comprises:
a fifth obtaining unit, configured to obtain an empirical formula;
a second determination unit for determining a vibration fundamental frequency position according to the empirical formula;
a sixth obtaining unit configured to obtain the highest energy packet according to the vibration fundamental frequency position.
Preferably, the empirical formula is:
R＝V×KV
F＝μf
wherein R represents the rotating speed and the unit is R/min; f represents the rotation frequency in Hz; f represents the vibration frequency in Hz; μ denotes a scale factor.
Preferably, the apparatus further comprises:
a first extraction unit, configured to extract a determination threshold of the confidence interval according to the confidence interval;
a third determining unit, configured to compare the first vibration spectrum with a judgment threshold value of the confidence interval, and determine a flight state of the aircraft.
Preferably, the apparatus further comprises: the confidence interval is a dynamic interval.
Preferably, the apparatus further comprises: the first vibration frequency spectrum is compared with a judgment threshold value of the confidence interval to determine the flight state of the aircraft, and the determination is specifically realized by the following formula:
wherein X is a frequency data vector of the confidence interval;
y is a frequency data vector of the first vibration frequency spectrum;
n is X vector coefficient;
m is a Y vector coefficient;
n is X, Y vector capacity.
Various changes and specific examples of the takeoff state detection method of the paddle aircraft in embodiment 1 of fig. 1 are also applicable to the takeoff state detection device of the paddle aircraft in this embodiment, and through the foregoing detailed description of the takeoff state detection method of the paddle aircraft, those skilled in the art can clearly know the implementation method of the takeoff state detection device of the paddle aircraft in this embodiment, so for the brevity of the description, detailed description is omitted here.
Example 3
Based on the same inventive concept as the takeoff state detection method of the paddle type aircraft in the previous embodiment, the invention also provides a takeoff state detection device of the paddle type aircraft, wherein a computer program is stored on the takeoff state detection device, and the computer program realizes the steps of any method of the takeoff state detection method of the paddle type aircraft when being executed by a processor.
Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 306 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other apparatus over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
One or more technical solutions in the embodiments of the present application have at least one or more of the following technical effects:
1. according to the method and the device for detecting the takeoff state of the paddle type aircraft, the natural vibration frequency spectrum of the aircraft first takeoff machine body is obtained through the motion sensor; obtaining a highest energy packet according to the natural vibration frequency spectrum; obtaining a confidence interval according to the highest energy packet; obtaining a first vibration frequency spectrum of the aircraft body through the motion sensor; and comparing the first vibration frequency spectrum with the confidence interval to determine the flight state of the aircraft. The technical problem that the flight state of the unmanned aerial vehicle cannot be accurately recorded and evaluated due to the fact that no standard third party flight state detection authentication exists in the prior art is solved. The technical effects of accurately identifying the takeoff characteristic of the unmanned aerial vehicle, effectively monitoring the flight state of the unmanned aerial vehicle and providing effective flight data of a flyer are achieved.
2. According to the method and the device, the technical problem that the flight state of the unmanned aerial vehicle cannot be accurately recorded and evaluated due to the fact that no standard third party flight state detection authentication exists in the prior art is solved through dynamically adjusting the confidence interval. The technical effect of continuously updating and perfecting the confidence interval to ensure the accuracy of the next detection is further achieved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (7)
1. A takeoff state detection method of a paddle type aircraft is applied to the paddle type aircraft, the paddle type aircraft is provided with a motion sensor, and the method is characterized by comprising the following steps:
obtaining the natural vibration frequency spectrum of the first takeoff machine body of the aircraft through the motion sensor;
obtaining a highest energy packet according to the natural vibration frequency spectrum;
obtaining a confidence interval according to the highest energy packet;
obtaining a first vibration frequency spectrum of the aircraft body through the motion sensor;
comparing the first vibration frequency spectrum with the confidence interval to determine the flight state of the aircraft;
comparing the first vibration frequency spectrum with a judgment threshold value of the confidence interval to determine the flight state of the aircraft, and specifically realizing the following formula:
wherein X is a frequency data vector of the confidence interval;
y is a frequency data vector of the first vibration frequency spectrum;
n is an X vector coefficient;
m is a Y vector coefficient;
n is X, Y vector capacity.
2. The method according to claim 1, wherein the obtaining the highest energy packet according to the natural vibration spectrum specifically comprises:
obtaining an empirical formula;
determining the position of the vibration fundamental frequency according to the empirical formula;
and obtaining the highest energy packet according to the vibration fundamental frequency position.
3. The method of claim 2, wherein the empirical formula is:
R＝V×KV
F＝μf
wherein R represents the rotating speed and the unit is R/min;
f represents the rotation frequency in Hz;
f represents the vibration frequency in Hz;
μ denotes a scale factor.
4. The method of claim 1, wherein comparing the first vibration spectrum to the confidence interval to determine the flight status of the aircraft comprises:
extracting a judgment threshold value of the confidence interval according to the confidence interval;
and comparing the first vibration frequency spectrum with a judgment threshold value of the confidence interval to determine the flight state of the aircraft.
5. The method of claim 4, in which the confidence interval is a dynamic interval.
6. A takeoff state detection device of a paddle type aircraft is applied to the paddle type aircraft, the paddle type aircraft is provided with a motion sensor, and the takeoff state detection device of the paddle type aircraft is characterized by comprising:
the first obtaining unit is used for obtaining the natural vibration frequency spectrum of the aircraft first takeoff machine body through the motion sensor;
a second obtaining unit, configured to obtain a highest energy packet according to the natural vibration spectrum;
a third obtaining unit, configured to obtain a confidence interval according to the highest energy packet;
a fourth obtaining unit, configured to obtain, by the motion sensor, a first vibration spectrum of the aircraft body;
a first determination unit, configured to compare the first vibration spectrum with the confidence interval, and determine a flight state of the aircraft;
comparing the first vibration frequency spectrum with a judgment threshold value of the confidence interval to determine the flight state of the aircraft, and specifically realizing the following formula:
wherein X is a frequency data vector of the confidence interval;
y is a frequency data vector of the first vibration frequency spectrum;
n is an X vector coefficient;
m is a Y vector coefficient;
n is X, Y vector capacity.
7. A takeoff state detection device of a paddle type aircraft, which is applied to the paddle type aircraft, wherein the paddle type aircraft is provided with a motion sensor, the takeoff state detection device of the paddle type aircraft comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, and the processor is characterized in that when executing the program, the processor realizes the following steps:
obtaining the natural vibration frequency spectrum of the first takeoff machine body of the aircraft through the motion sensor;
obtaining a highest energy packet according to the natural vibration frequency spectrum;
obtaining a confidence interval according to the highest energy packet;
obtaining a first vibration frequency spectrum of the aircraft body through the motion sensor;
comparing the first vibration frequency spectrum with the confidence interval to determine the flight state of the aircraft;
comparing the first vibration frequency spectrum with a judgment threshold value of the confidence interval to determine the flight state of the aircraft, and specifically realizing the following formula:
wherein X is a frequency data vector of the confidence interval;
y is a frequency data vector of the first vibration frequency spectrum;
n is an X vector coefficient;
m is a Y vector coefficient;
n is X, Y vector capacity.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810113627.6A CN108303278B (en) | 2018-02-05 | 2018-02-05 | Method and device for detecting takeoff state of paddle type aircraft |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201810113627.6A CN108303278B (en) | 2018-02-05 | 2018-02-05 | Method and device for detecting takeoff state of paddle type aircraft |
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| CN108303278A CN108303278A (en) | 2018-07-20 |
| CN108303278B true CN108303278B (en) | 2020-05-05 |
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| CN111640504A (en) * | 2020-06-01 | 2020-09-08 | 北京中科心研科技有限公司 | Velocity perception detection method and device |
| CN111776248B (en) * | 2020-08-03 | 2022-02-18 | 广州极飞科技股份有限公司 | Vibration testing method and device and aircraft |
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