CN113443167A

CN113443167A - Unmanned aerial vehicle state evaluation method and device, server and storage medium

Info

Publication number: CN113443167A
Application number: CN202010212812.8A
Authority: CN
Inventors: 马凡
Original assignee: Fengyi Technology Shenzhen Co ltd
Current assignee: Fengyi Technology Shenzhen Co ltd
Priority date: 2020-03-24
Filing date: 2020-03-24
Publication date: 2021-09-28
Anticipated expiration: 2040-03-24
Also published as: CN113443167B

Abstract

The embodiment of the application discloses a method and a device for evaluating the state of an unmanned aerial vehicle, a server and a storage medium, wherein the method for evaluating the state of the unmanned aerial vehicle comprises the following steps: acquiring unmanned aerial vehicle state parameters acquired by an unmanned aerial vehicle parameter acquisition device at a target time; calculating unmanned plane performance parameters according to the unmanned plane state parameters; obtaining a weight ratio coefficient corresponding to each performance parameter in the unmanned aerial vehicle performance parameters; and determining the performance state of the unmanned aerial vehicle at the target time according to the unmanned aerial vehicle performance parameters and the weight ratio coefficient. In this application embodiment can instruct to maintain unmanned aerial vehicle, maintain and use, reduce simultaneously because the operation that unmanned aerial vehicle self state leads to is unusual and the trouble, can full play unmanned aerial vehicle latent energy, possibility and time that the prediction unmanned aerial vehicle trouble appears are as the foundation of maintaining and overhauing, and in addition, the unmanned aerial vehicle performance state of aassessment still can be for selecting unmanned aerial vehicle operation task to do the guidance foundation.

Description

Unmanned aerial vehicle state evaluation method and device, server and storage medium

Technical Field

The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle state evaluation method, an unmanned aerial vehicle state evaluation device, a server and a storage medium.

Background

At present, the unmanned aerial vehicle safely operates the block, the corresponding landing implementation of the national policy temporary management method and the standard, in particular to the operation of the unmanned aerial vehicle in the city, and the unmanned aerial vehicle is still in a cautious exploration stage. For unmanned aerial vehicles in different scenes, if large-scale normalized operation is required, the operation safety of the unmanned aerial vehicles is ensured under the condition of fully exerting and utilizing the operation capacity of the unmanned aerial vehicles except the qualified certification of a third-party certification authority.

Similar to the automobile industry, a dealer store with corresponding automobile maintenance can perform routine maintenance with fixed mileage on an automobile, if a customer does not perform maintenance on the automobile on demand, corresponding consequences are born by the customer, risks are all transferred to the customer, the cost of daily maintenance and inspection is born by the customer, and in the first place, after the customer purchases the automobile, all maintenance, repair and risks which are not quality problems need to be born by the customer. The performance state of the automobile is comprehensively evaluated by a traveling computer through various parameters fed back by the vehicle-mounted sensor and displayed in a fault code and information mode.

For civil unmanned aerial vehicles, due to the limitation of cost and operation scenes, the performance condition of the unmanned aerial vehicles is not fully known, the unmanned aerial vehicles can only be maintained by adopting a regular maintenance method, or the unmanned aerial vehicles are maintained under the condition of abnormity or faults, and the cost and the risk are greatly increased.

Disclosure of Invention

The embodiment of the invention provides an unmanned aerial vehicle state evaluation method, an unmanned aerial vehicle state evaluation device, a server and a storage medium, which can guide maintenance, maintenance and use of an unmanned aerial vehicle, reduce abnormal operation and faults caused by the self state of the unmanned aerial vehicle, give full play to the potential of the unmanned aerial vehicle, predict the possibility and time of the fault of the unmanned aerial vehicle and serve as the basis for maintenance and overhaul, and besides, the evaluated performance state of the unmanned aerial vehicle can also serve as the guidance basis for selecting the operation task of the unmanned aerial vehicle.

In one aspect, the present application provides an unmanned aerial vehicle state evaluation method, which is applied to a server, the server is located in an unmanned aerial vehicle state evaluation system, the unmanned aerial vehicle state evaluation system further includes an unmanned aerial vehicle parameter acquisition device arranged on an unmanned aerial vehicle, and the method includes:

acquiring unmanned aerial vehicle state parameters acquired by the unmanned aerial vehicle parameter acquisition device at a target time, wherein the unmanned aerial vehicle state parameters comprise battery state parameters, power system state parameters and target core component state parameters;

calculating unmanned plane performance parameters according to the unmanned plane state parameters;

obtaining a weight ratio coefficient corresponding to each performance parameter in the unmanned aerial vehicle performance parameters;

and determining the performance state of the unmanned aerial vehicle at the target time according to the unmanned aerial vehicle performance parameters and the weight ratio coefficient.

In some embodiments of the present application, calculating the performance parameter of the drone according to the state parameter of the drone includes:

determining battery performance parameters of the unmanned aerial vehicle according to the battery state parameters;

determining power system performance parameters of the unmanned aerial vehicle according to the power system state parameters;

and determining the target core component performance parameters of the unmanned aerial vehicle according to the target core component state parameters.

In some embodiments of the present application, the battery state parameter includes a plurality of parameters selected from a voltage parameter, a current parameter, a capacity parameter, an internal resistance parameter, a number of charging and discharging times, a temperature parameter, and a usage condition parameter;

the determining the battery performance parameters of the unmanned aerial vehicle according to the battery state parameters comprises:

according to the parameters, respectively calculating the weight ratio of the parameters;

and calculating the battery performance parameters of the unmanned aerial vehicle according to the weight proportion of the parameters.

In some embodiments of the present application, the power system state parameters include motor operating current, motor temperature, and motor speed in the drone;

according to the power system state parameter, determining the power system performance parameter of the unmanned aerial vehicle, including:

calculating the weight of the motor working current according to the motor working current and a preset motor working current interval;

calculating the weight of the motor temperature according to the motor temperature and a preset motor temperature interval;

calculating the weight of the motor rotating speed according to the motor rotating speed and a preset motor rotating speed interval;

and determining the power system performance parameters of the unmanned aerial vehicle according to the motor working current weight, the motor temperature weight and the motor temperature weight.

In some embodiments of the present application, the determining the performance state of the drone at the target time according to the drone performance parameter and the weight ratio coefficient includes:

determining comprehensive performance parameters corresponding to each performance parameter in the unmanned aerial vehicle performance parameters according to the unmanned aerial vehicle performance parameters and the weight ratio coefficient;

obtaining attenuation coefficients corresponding to the performance parameters of the unmanned aerial vehicle;

and determining the performance state grade of the unmanned aerial vehicle according to the comprehensive performance parameters corresponding to the performance parameters and the attenuation coefficients corresponding to the performance parameters of the unmanned aerial vehicle.

In some embodiments of the present application, the determining the performance state level of the unmanned aerial vehicle according to the comprehensive performance parameter corresponding to each performance parameter and the attenuation coefficient corresponding to the performance parameter of the unmanned aerial vehicle includes:

calculating the effective performance parameter of each performance parameter according to the comprehensive performance parameter corresponding to each performance parameter and the attenuation coefficient corresponding to each performance parameter;

calculating the sum of the effective performance parameters of each performance parameter;

and determining the performance state grade of the unmanned aerial vehicle according to the sum value.

In some embodiments of the present application, the obtaining an attenuation coefficient corresponding to the performance parameter of the unmanned aerial vehicle includes:

acquiring test data of unmanned aerial vehicle performance parameters of a test unmanned aerial vehicle within target time;

forming various performance curves corresponding to the performance parameters of the unmanned aerial vehicle based on the test data;

and determining the attenuation coefficient corresponding to each performance parameter in the unmanned aerial vehicle performance parameters according to each performance curve.

In some embodiments of the present application, after determining the performance state of the drone at the target time according to the drone performance parameters and the weighting ratio coefficients, the method further comprises:

and arranging a flight task for the unmanned aerial vehicle based on the performance state grade of the unmanned aerial vehicle at the target time.

In some embodiments of the present application, said scheduling a flight mission for the drone based on the performance state level of the drone at the target time comprises:

acquiring a flight task set of the unmanned aerial vehicle;

acquiring a corresponding relation between a preset performance state grade of the unmanned aerial vehicle and a route distance;

determining a first target flight task matched with the performance state grade of the unmanned aerial vehicle in the flight task set based on the corresponding relation;

arranging the first target flight mission for the drone.

In some embodiments of the present application, after said scheduling a mission for the drone based on the performance state level of the drone at the target time, the method further comprises:

determining a current safe use limit parameter of the unmanned aerial vehicle for executing a current flight task;

acquiring a first environment parameter of the unmanned aerial vehicle before executing a scheduled flight mission, wherein the parameter type included in the first environment parameter is the same as the parameter type included in the current safe use limit parameter;

and if the first target parameter value in the first environmental parameter reaches the first target parameter value in the current safe use limit parameter, prohibiting the unmanned aerial vehicle from taking off and executing a flight task.

In some embodiments of the present application, the determining a current safe use limit parameter for the drone to perform the current flight mission includes:

acquiring a safe use limit parameter of the unmanned aerial vehicle;

obtaining an attenuation coefficient of the current performance state of the unmanned aerial vehicle;

and calculating the current safe use limit parameter of the unmanned aerial vehicle executing the current flight mission based on the safe use limit parameter and the attenuation parameter.

In some embodiments of the present application, the method further comprises:

acquiring a second environment parameter of the unmanned aerial vehicle in the process of executing a flight task;

if a second target parameter value in the second environment parameter reaches a second target parameter value in the current safe use limit parameter, initiating an early warning to a preset administrator terminal;

and if the third target parameter value in the second environment parameter reaches the third target parameter value in the current safe use limit parameter, sending a return command or a landing command to the unmanned aerial vehicle.

In some embodiments of the present application, the method further comprises:

acquiring a second target flight task;

acquiring information of a plurality of unmanned aerial vehicles with predetermined performance state levels;

determining a target drone that matches the second target mission based on the corresponding relationship among the plurality of drones;

and arranging the second target flight mission to the target unmanned aerial vehicle.

On the other hand, this application provides an unmanned aerial vehicle state evaluation device, is applied to the server, the server is located unmanned aerial vehicle state evaluation system, unmanned aerial vehicle state evaluation system is still including setting up the unmanned aerial vehicle parameter acquisition device on unmanned aerial vehicle, the device includes:

the first acquisition unit is used for acquiring unmanned aerial vehicle state parameters acquired by the unmanned aerial vehicle parameter acquisition device at a target time;

the calculating unit is used for calculating the performance parameters of the unmanned aerial vehicle according to the state parameters of the unmanned aerial vehicle;

the second obtaining unit is used for obtaining a weight ratio coefficient corresponding to each performance parameter in the unmanned aerial vehicle performance parameters;

and the determining unit is used for determining the performance state of the unmanned aerial vehicle at the target time according to the unmanned aerial vehicle performance parameters and the weight ratio coefficient.

In some embodiments of the present application, the drone status parameters include a battery status parameter, a power system status parameter, and a target core component status parameter;

the computing unit is specifically configured to:

In some embodiments of the present application, the determining unit is specifically configured to:

In some embodiments of the present application, the apparatus further includes a task allocation unit, where the task allocation unit is specifically configured to:

after the performance state of the unmanned aerial vehicle at the target time is determined according to the unmanned aerial vehicle performance parameters and the weight ratio coefficient, arranging a flight mission for the unmanned aerial vehicle based on the performance state grade of the unmanned aerial vehicle at the target time.

In some embodiments of the present application, the task allocation unit is specifically configured to:

acquiring a flight task set of the unmanned aerial vehicle;

arranging the first target flight mission for the drone.

In some embodiments of the present application, the task allocation unit is further specifically configured to:

determining a current safe use limit parameter for the drone to execute a current flight mission after the scheduling of a flight mission for the drone based on the performance state level of the drone at a target time;

acquiring a safe use limit parameter of the unmanned aerial vehicle;

In some embodiments of the present application, the apparatus further includes an early warning unit, where the early warning unit is specifically configured to:

acquiring a second target flight task;

In another aspect, the present application further provides a server, including:

one or more processors;

a memory; and

one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the drone state evaluation method.

In another aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is loaded by a processor to execute the steps in the method for estimating the state of a drone.

In the embodiment of the application, the unmanned aerial vehicle state parameters acquired by the unmanned aerial vehicle parameter acquisition device at the target time are acquired; calculating unmanned plane performance parameters according to the unmanned plane state parameters; obtaining a weight ratio coefficient corresponding to each performance parameter in the unmanned aerial vehicle performance parameters; and determining the performance state of the unmanned aerial vehicle at the target time according to the unmanned aerial vehicle performance parameters and the weight ratio coefficient. In the embodiment of the application, on the basis of insufficient understanding of unmanned aerial vehicle performance in prior art unmanned aerial vehicle use, through unmanned aerial vehicle parameter acquisition device, gather unmanned aerial vehicle state parameter, confirm unmanned aerial vehicle's performance state according to unmanned aerial vehicle state parameter, maintain unmanned aerial vehicle in order to guide, maintenance and use, reduce simultaneously because unusual and the trouble of operation that unmanned aerial vehicle self state leads to, can full play unmanned aerial vehicle latent energy, predict possibility and time that unmanned aerial vehicle trouble appears, as the foundation of maintaining and overhauing, in addition, the unmanned aerial vehicle performance state of aassessment still can be for selecting unmanned aerial vehicle operation task to do the guidance foundation.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a schematic view of a scene of a state evaluation system of an unmanned aerial vehicle according to an embodiment of the present invention;

fig. 2 is a schematic flow chart of an embodiment of a method for evaluating a state of an unmanned aerial vehicle according to an embodiment of the present invention;

FIG. 3 is a flowchart of one embodiment of step 202 provided in embodiments of the present invention;

FIG. 4 is a flowchart of one embodiment of step 204 provided in embodiments of the present invention;

fig. 5 is a schematic structural diagram of an embodiment of the unmanned aerial vehicle state evaluation apparatus provided in the embodiment of the present invention;

fig. 6 is a schematic structural diagram of an embodiment of the server provided in the embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention. Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.

In this application, the word "exemplary" is used to mean "serving as an example, instance, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is presented to enable any person skilled in the art to make and use the invention. In the following description, details are set forth for the purpose of explanation. It will be apparent to one of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known structures and processes are not shown in detail to avoid obscuring the description of the invention with unnecessary detail. Thus, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

The embodiment of the invention provides a method and a device for evaluating the state of an unmanned aerial vehicle, a server and a storage medium, which are respectively described in detail below.

Referring to fig. 1, fig. 1 is a schematic view of a scene of a state evaluation system of an unmanned aerial vehicle according to an embodiment of the present invention, where the state evaluation system of the unmanned aerial vehicle may include an unmanned aerial vehicle 100 and a server 200, the unmanned aerial vehicle 100 is connected to the server 20 through a network, an unmanned aerial vehicle parameter acquisition device is disposed in the unmanned aerial vehicle 100, and an unmanned aerial vehicle state evaluation device is integrated in the server 200, such as the server in fig. 1, and the unmanned aerial vehicle 100 may perform data interaction with the server 200.

In the embodiment of the invention, the server 200 is mainly used for acquiring the unmanned aerial vehicle state parameters acquired by the unmanned aerial vehicle parameter acquisition device at the target time; calculating unmanned plane performance parameters according to the unmanned plane state parameters; obtaining a weight ratio coefficient corresponding to each performance parameter in the unmanned aerial vehicle performance parameters; and determining the performance state of the unmanned aerial vehicle at the target time according to the unmanned aerial vehicle performance parameters and the weight ratio coefficient.

In this embodiment of the present invention, the server 200 may be an independent server, or may be a server network or a server cluster composed of servers, for example, the server 200 described in this embodiment of the present invention includes, but is not limited to, a computer, a network host, a single network server, a plurality of network server sets, or a cloud server composed of a plurality of servers. Among them, the Cloud server is constituted by a large number of computers or web servers based on Cloud Computing (Cloud Computing). In the embodiment of the present invention, the server and the User terminal may implement communication through any communication manner, including but not limited to mobile communication based on the third Generation Partnership Project (3 GPP), Long Term Evolution (LTE), Worldwide Interoperability for Microwave Access (WiMAX), or computer network communication based on the TCP/IP Protocol Suite (TCP/IP), User Datagram Protocol (UDP) Protocol, and the like.

Those skilled in the art will understand that the application environment shown in fig. 1 is only one application scenario related to the present application, and does not constitute a limitation on the application scenario of the present application, and that other application environments may further include more or fewer drones than those shown in fig. 1, or a server network connection relationship, for example, only 1 server and 2 drones are shown in fig. 1, and it is understood that the drone status evaluation system may further include one or more other drones connected to the server network, and is not limited herein.

In addition, as shown in fig. 1, the unmanned aerial vehicle state evaluation system may further include a memory 300 for storing unmanned aerial vehicle data, such as unmanned aerial vehicle state parameters, weather data, latest performance state of the unmanned aerial vehicle, and the like, collected by the unmanned aerial vehicle parameter collection device.

It should be noted that the scene schematic diagram of the unmanned aerial vehicle state evaluation system shown in fig. 1 is only an example, and the unmanned aerial vehicle state evaluation system and the scene described in the embodiment of the present invention are for more clearly illustrating the technical solution of the embodiment of the present invention, and do not form a limitation on the technical solution provided in the embodiment of the present invention.

First, an embodiment of the present invention provides an unmanned aerial vehicle state evaluation method, which is applied to a server, where the server is located in an unmanned aerial vehicle state evaluation system, the unmanned aerial vehicle state evaluation system further includes an unmanned aerial vehicle parameter acquisition device disposed on an unmanned aerial vehicle, and the method includes: acquiring unmanned aerial vehicle state parameters acquired by the unmanned aerial vehicle parameter acquisition device at a target time; calculating unmanned plane performance parameters according to the unmanned plane state parameters; obtaining a weight ratio coefficient corresponding to each performance parameter in the unmanned aerial vehicle performance parameters; and determining the performance state of the unmanned aerial vehicle at the target time according to the unmanned aerial vehicle performance parameters and the weight ratio coefficient.

As shown in fig. 2, which is a schematic flow chart of an embodiment of a method for estimating a state of an unmanned aerial vehicle according to an embodiment of the present invention, the method for estimating a state of an unmanned aerial vehicle includes:

201. and acquiring unmanned aerial vehicle state parameters acquired by the unmanned aerial vehicle parameter acquisition device at target time.

The target time may be a current time when the unmanned aerial vehicle is evaluated, or may be a time before the current time, which is not limited herein.

Wherein, unmanned aerial vehicle parameter acquisition device can include at least one sensor, and the unmanned aerial vehicle state parameter that this at least one sensor was gathered can set up as required, for example, if including driving system state parameter in the unmanned aerial vehicle state parameter, then at least one sensor can include vibration sensor and noise sensor to the driving system setting, if including the pneumatic system parameter in the unmanned aerial vehicle state parameter, then at least one sensor can include the stress strain sensor to the setting of unmanned aerial vehicle pneumatic system.

The state parameter of the unmanned aerial vehicle is a parameter reflecting the current state of the unmanned aerial vehicle, and specifically, may include a parameter of a preset component of the unmanned aerial vehicle, such as a battery state parameter, a power system state parameter, a target core component state parameter, and the like, which is described in detail below.

It is theoretically most appropriate to collect various information by as many sensors as possible, without considering the cost, i.e. the more and more detailed the collection of the state parameters of the drone, the better the evaluation of the state of the drone. However, when the cost is too high, the civil unmanned aerial vehicle is not developed completely, no medical and automobile industry development experience exists, how to distribute and assign maintenance in a specified size, how many items are detected to be conventional detection, how many items are detected to be deep detection, and no applicable standard exists, but for enterprises or individuals with unmanned aerial vehicles, consumers bear the later-stage use cost of the unmanned aerial vehicles, parts are replaced, damage and maintenance are carried out, and production enterprises do not take the later-stage maintenance cost as the primary consideration (similar to automobiles, low-cost sale and high-cost maintenance). The enterprise that possess unmanned aerial vehicle generally independently operates, independently undertakes later stage maintenance, so can make full use of as far as possible unmanned aerial vehicle of old and of a specified duration, reduces and uses the maintenance cost, controls the operation risk.

Therefore, in order to reduce the cost, the embodiment of the invention can integrate multiple indexes related to the state information of the unmanned aerial vehicle, extract the most core key index (determined autonomously according to the operation experience), and achieve the multi-sensor acquisition effect by using a small number of sensors, namely, the state parameter of the unmanned aerial vehicle is the state parameter corresponding to the preset core performance parameter.

The unmanned aerial vehicle described in the embodiment of the present invention may be an electrically driven light small civil unmanned aerial vehicle, and at this time, the unmanned aerial vehicle includes a battery. For all industrial unmanned planes driven by electricity, it is desirable to have the longest possible flight time and flight distance, i.e. longer flight time and longer flight distance, while keeping reasonable cruising speed. And the most important components of the drone system that determine this factor are the battery and power system.

Wherein, unmanned aerial vehicle parameter acquisition device can also include unmanned aerial vehicle self treater, can gather some parameters of unmanned aerial vehicle's battery through the treater, for example, the voltage, electric current, capacity, internal resistance, the number of times of charging and discharging of battery etc. battery temperature can gather through temperature sensor certainly. That is, the state parameter of the unmanned aerial vehicle includes a battery state parameter, and the battery state parameter may include a plurality of parameters of a voltage parameter, a current parameter, a capacity parameter, an internal resistance parameter, a number of charging and discharging times, a temperature parameter, and a usage condition parameter.

Besides recording battery state parameters, the unmanned aerial vehicle also needs to upload the battery state parameters to the server, and the server can analyze the state of the unmanned aerial vehicle based on the battery state parameters, for example, when a large amount of battery state parameter information is accumulated to a certain degree, a battery performance state attenuation curve can be formed.

Generally include driving system (like the motor) among the unmanned aerial vehicle, to driving system, the leading factor lies in the motor, and its information mainly is indexes such as motor live time, motor voltage, motor current, motor speed, motor vibration, motor noise. The motor bears axial load and radial load simultaneously for a long time, has not only considered to subtract heavy in structural design, but also has taken into account performance and cost for the motor bearing is more easy wearing and tearing for ground equipment motor bearing, produces wearing and tearing clearance and virtual position easily, and then leads to unmanned aerial vehicle unusual or trouble.

Therefore, in some embodiments of the present invention, the state parameters of the drone may include a state parameter of a power system, and the state parameter of the power system may include an operating current of a motor in the drone, a temperature of the motor, and a rotation speed of the motor, and it is understood that in some other embodiments of the present invention, the state parameter of the power system may further include other parameters of the motor, for example, similar to an automobile, the longer the drone is used, the greater noise and wind noise may be increased, especially, the rotating structural member is worn and loosened, and the fastening structural member may have a situation of being locked or failed, and at this time, a vibration parameter of the motor (collected by a vibration sensor), a noise parameter (collected by a noise sensor), and the like, which are not limited herein.

In addition, in some embodiments of the present invention, the state parameters of the drone may further include state parameters of a target core component, where the target core component is a core component other than a battery and a power system, for example, an avionic system or a pneumatic system of the drone, and may be specifically selected according to an actual scene.

If the target core component includes an avionics system, the state parameters of the target core component may include internal resistance in the avionics system, power consumption current of the avionics system, and power consumption of equipment of the avionics system, because the avionics system is aged and increases internal resistance in the use process of electronic components, and the specific details are not limited herein.

If the target core component comprises a pneumatic system, aiming at the pneumatic system of the unmanned aerial vehicle, main parameters relate to aerodynamic shape, propeller wing profile, fixed wing profile, empennage wing profile and the like, so that the state parameters of the target core component can comprise parameters of aerodynamic shape, propeller wing profile, fixed wing profile, empennage wing profile and the like, and can be specifically acquired by using a stress-strain sensor.

202. And calculating the performance parameters of the unmanned aerial vehicle according to the state parameters of the unmanned aerial vehicle.

The unmanned aerial vehicle performance parameters are obtained after the unmanned aerial vehicle state parameters are subjected to weight calculation, the unmanned aerial vehicle performance parameters correspond to the unmanned aerial vehicle state parameters, and the unmanned aerial vehicle performance parameters comprise battery performance parameters, power system performance parameters and target core component performance parameters; if the unmanned aerial vehicle state parameters include target core component state parameters, the unmanned aerial vehicle performance parameters include target core component performance parameters, specifically, the pneumatic system performance parameters.

As described in step 201, in some embodiments of the present invention, the drone status parameters include a battery status parameter, a power system status parameter, and a target core component status parameter; at this time, as shown in fig. 3, the calculating the performance parameter of the drone according to the state parameter of the drone includes:

301. and determining the battery performance parameters of the unmanned aerial vehicle according to the battery state parameters.

Specifically, the battery state parameters may include a plurality of parameters among a voltage parameter, a current parameter, a capacity parameter, an internal resistance parameter, a number of charge and discharge times, a temperature parameter, and a usage condition parameter; at this time, determining the battery performance parameters of the unmanned aerial vehicle according to the battery state parameters includes: according to the parameters, respectively calculating the weight ratio of the parameters; and calculating the battery performance parameters of the unmanned aerial vehicle according to the weight proportion of the parameters.

302. And determining the power system performance parameters of the unmanned aerial vehicle according to the power system state parameters.

Specifically, the power system state parameters may include a motor working current, a motor temperature, and a motor rotation speed in the unmanned aerial vehicle; according to the power system state parameter, determining the power system performance parameter of the unmanned aerial vehicle, including: calculating the weight of the motor working current according to the motor working current and a preset motor working current interval; calculating the weight of the motor temperature according to the motor temperature and a preset motor temperature interval; calculating the weight of the motor rotating speed according to the motor rotating speed and a preset motor rotating speed interval; and determining the power system performance parameters of the unmanned aerial vehicle according to the motor working current weight, the motor temperature weight and the motor temperature weight.

In one embodiment, assume that the unmanned aerial vehicle motor current working range is 5A + -2A, i.e. 3A-7A, the motor current index weight is 0.4, the motor rotation speed range is 2000rad/s + -200 rad/s, i.e. 1800 plus 2200rad/s, the motor rotation speed index weight is 0.3, the motor temperature range is 50-60 ℃, and the motor temperature index weight is 0.3. Assuming that the current motor current is 6A, the motor rotating speed is 2100rad/s, the motor temperature is 55 ℃, and the calculation mode is as follows:

motor temperature weight: tem (55-50)/(60-50) 0.5

Motor current weight: a ═ 0.75 (6-3)/(7-3)

Motor speed weight: v ═ 0.75 (2100 + 1800)/(2200 + 1800) -

The performance parameters of the power system of the unmanned aerial vehicle are comprehensive weight ratio, wherein the comprehensive weight ratio S is 0.5 x 0.3+0.75 x 0.4+0.75 x 0.3 is 0.675, specifically, 0.5 is the optimal state of the power system, 0-0.5 data is smaller, the whole is located in a lower deviation interval, 0.5-1 data is larger, the whole is located in an upper deviation interval, and the power system is not in the optimal state.

303. And determining the target core component performance parameters of the unmanned aerial vehicle according to the target core component state parameters.

If the target core component comprises an avionics system, the state parameters of the target core component can comprise internal resistance in the avionics system, power current used by the avionics system and power consumption of equipment of the avionics system. At this time, determining the target core component performance parameter of the unmanned aerial vehicle according to the target core component state parameter may include:

calculating the weight of the internal resistance in the avionic system according to the internal resistance in the avionic system and the initial internal resistance in the avionic system; calculating the weight of the avionic system power utilization current according to the avionic system power utilization current and a preset avionic system power utilization current interval; calculating the weight of the power consumption of the avionic system equipment according to the power consumption of the avionic system equipment and a preset power consumption interval of the avionic system equipment; and determining the performance parameters of the target core component of the unmanned aerial vehicle according to the weight of the internal resistance in the avionic system, the weight of the power consumption current of the avionic system and the weight of the power consumption of the avionic system equipment.

203. And acquiring a weight ratio coefficient corresponding to each performance parameter in the unmanned aerial vehicle performance parameters.

The unmanned aerial vehicle performance can be reduced along with the lengthening of the service time, and the likeLike an automobile, the longer the service life is, the higher the oil consumption is, the more serious the abrasion of tires and brake pads is, the longer the brake distance is, the worse the charge and discharge performance of a battery is, and the like. For unmanned aerial vehicles, each performance index can be attenuated to some extent. The most obvious index is battery capacity, assuming battery capacity as phi, actual capacity as phi', service time (number of battery charge-discharge cycles) as t, attenuation coefficient as lambda₁(along with the lengthening of the service time, the less the energy storage of the battery, the larger the internal resistance and the less the discharge capacity), the temperature (environment) correction parameter is mu (different environment temperatures and different battery charging and discharging effects), and the historical state correction parameter is epsilon₁(whether the battery is not charged or discharged according to the specified operation, the battery history is abnormal or fails, and the battery is overcharged or overdischarged), and the estimation formula is phi' ═ phi mu epsilon₁(100％-λ₁t-2)。

Wherein the temperature (environment) correction parameters are related to the current operating environment temperature of the unmanned aerial vehicle, the historical state correction parameters are related to the historical service condition of the battery, and the attenuation coefficient is related to the battery performance of each different brand. Similarly, the longer the motor is used, the more serious the bearing wear is, and under the same working condition, the state performance is reduced, the output power is reduced, and the efficiency is reduced. Assuming that the normal rated output power is Q, the actual output power is Q', and the attenuation coefficient is lambda₂(based on actual test, the resulting normal decay), the condition correction parameter is ε₂(historical state is unusual or trouble, whether have maintenance record), according to the motor of different positions, still need increase position correction coefficient p (this parameter is relevant with unmanned aerial vehicle structural style), for example for four rotor unmanned aerial vehicles, when flying forward with certain attitude angle, the power output of four motors is different, and the same reason six rotors, eight rotor motor power output are also different, similar car front and back wheel, and forerunner's car front wheel bearing, turn to, travel, wear and tear more seriously than the back wheel.

Therefore, the actual output power estimation formula of the unmanned aerial vehicle can be Q' ═ Q lambda₂ε₂+ p, where Q is the normal rated output power, Q' is the actual output power, λ₂Is the attenuation coefficient (normal attenuation obtained from practical test), epsilon₂For repairing statePositive parameters (historical status exception or fault, whether there is a service record).

204. And determining the performance state of the unmanned aerial vehicle at the target time according to the unmanned aerial vehicle performance parameters and the weight ratio coefficient.

In some embodiments of the present invention, as shown in fig. 4, the determining the performance state of the drone at the target time according to the drone performance parameter and the weight ratio coefficient may include:

401. and determining the comprehensive performance parameters corresponding to each performance parameter in the unmanned aerial vehicle performance parameters according to the unmanned aerial vehicle performance parameters and the weight ratio coefficient.

402. And obtaining the attenuation coefficient corresponding to the unmanned aerial vehicle performance parameter.

Normally, all coefficients are dynamically changing, such as attenuation coefficient, the longer the usage time, the more aging and the more attenuation. During the testing stage, curves of various performance indexes changing along with time can be formed in advance, and a function can be fitted, so that the attenuation coefficient, the state correction coefficient and the position correction coefficient of each stage are obtained. Specifically, the obtaining of the weight ratio coefficient corresponding to each performance parameter in the performance parameters of the unmanned aerial vehicle includes: acquiring test data of unmanned aerial vehicle performance parameters of a test unmanned aerial vehicle within target time; forming various performance curves corresponding to the performance parameters of the unmanned aerial vehicle based on the test data; and determining the attenuation coefficient corresponding to each performance parameter in the unmanned aerial vehicle performance parameters according to each performance curve.

403. And determining the performance state grade of the unmanned aerial vehicle according to the comprehensive performance parameters corresponding to the performance parameters and the attenuation coefficients corresponding to the performance parameters of the unmanned aerial vehicle.

Wherein, the determining the performance state grade of the unmanned aerial vehicle according to the comprehensive performance parameters corresponding to each performance parameter and the attenuation coefficient corresponding to the unmanned aerial vehicle performance parameter comprises: calculating the effective performance parameter of each performance parameter according to the comprehensive performance parameter corresponding to each performance parameter and the attenuation coefficient corresponding to each performance parameter; calculating the sum of the effective performance parameters of each performance parameter; and determining the performance state grade of the unmanned aerial vehicle according to the sum value.

In a specific embodiment, as shown in table 1 below, assuming that O is another drone performance level parameter, the battery weight ratio coefficient is T1, the motor weight ratio coefficient is T2, the weight ratio coefficient of the other drone performance level parameter is T3, T1, T2, and T3 are obtained in advance according to drone tests, the coefficients are different for different models, the sum of T1, T2, and T3 is 1, the comprehensive weight ratio in the current state is S, the drone performance level L1 is (Φ 'T1 + Q' T2+ OT3) S, and specifically, L1 may be divided into one stage, two stages, three stages, four stages, and five stages according to the result.

TABLE 1

In the above embodiments, the determined performance status of the drone (e.g., performance level L1) may prompt the operator whether the drone needs to be overhauled and maintained, or may evaluate whether the current drone can complete the current flight mission. For example, in one specific embodiment, after determining the performance state of the drone at the target time according to the drone performance parameters and the weighting ratio coefficients, the method further comprises: and arranging a flight task for the unmanned aerial vehicle based on the performance state grade of the unmanned aerial vehicle at the target time.

Wherein the scheduling a flight mission for the drone based on the performance state level of the drone at the target time may further include: acquiring a flight task set of the unmanned aerial vehicle; acquiring a corresponding relation between a preset performance state grade of the unmanned aerial vehicle and a route distance; determining a first target flight task matched with the performance state grade of the unmanned aerial vehicle in the flight task set based on the corresponding relation; arranging the first target flight mission for the drone.

Before the unmanned aerial vehicle arranges the flight task, the unmanned aerial vehicle flight task can constantly exist in the system, and the set that the unmanned aerial vehicle flight task is formed is the unmanned aerial vehicle flight task set. At this moment, if the performance state of the unmanned aerial vehicle is in the first level, if the preset corresponding relation between the performance state level of the unmanned aerial vehicle and the air route distance corresponds to the first level of the unmanned aerial vehicle with the performance state of 20KM, at this moment, the flight tasks of the air routes which are lower than 20KM in the flight task set of the unmanned aerial vehicle can be matched with the performance state of the unmanned aerial vehicle, namely, the first target flight task needs to be determined and arranged in the flight task of the air routes which are lower than 20 KM.

After performance state evaluation is carried out on the unmanned aerial vehicle, the unmanned aerial vehicle can be subjected to full-life state monitoring, abnormity or fault prediction, flight task risk prediction and the like, real-time monitoring and early warning can be carried out in the flight task execution process, namely, the prediction and early warning before taking off is carried out, whether the task can be executed or not is judged, real-time monitoring and early warning after taking off is carried out, and the unmanned aerial vehicle fault or accident caused by sudden change of external conditions is prevented.

In some embodiments of the present invention, after the scheduling a flight mission for the drone based on the performance state level of the drone at the target time, the method in embodiments of the present invention further comprises: determining a current safe use limit parameter of the unmanned aerial vehicle for executing a current flight task; acquiring a first environment parameter of the unmanned aerial vehicle before executing a scheduled flight mission, wherein the parameter type included in the first environment parameter is the same as the parameter type included in the current safe use limit parameter; and if the first target parameter value in the first environmental parameter reaches the first target parameter value in the current safe use limit parameter, prohibiting the unmanned aerial vehicle from taking off and executing a flight task.

Wherein, the determining the current safe use limit parameter of the unmanned aerial vehicle executing the current flight mission comprises: acquiring a safe use limit parameter of the unmanned aerial vehicle; obtaining an attenuation coefficient of the current performance state of the unmanned aerial vehicle; and calculating the current safe use limit parameter of the unmanned aerial vehicle executing the current flight mission based on the safe use limit parameter and the attenuation parameter.

When the unmanned aerial vehicle is in the optimal state (the optimal state of a bathtub curve, no maintenance and replacement record and no fault record exist, and a power system, particularly a battery and a motor are in the optimal state), according to the test data and the designed performance indexes of the unmanned aerial vehicle, a safe operation use limit exists, such as the wind speed of 20m/s, the takeoff is forbidden when the load is more than 15kg, and other indexes include weather data such as rainfall, visibility, temperature and the like, and once the weather data exceeds the other indexes, the takeoff is forbidden. The unmanned aerial vehicle has the range capacity of 20km, the air route exceeds 20km, and the takeoff is forbidden. And weather data exceed the standard in the flight process of the unmanned aerial vehicle, and the unmanned aerial vehicle also returns to the air or lands nearby.

The unmanned aerial vehicle can enter a performance attenuation state along with use, the performance of the unmanned aerial vehicle descends to some extent in the attenuation state, the use limit indexes are changed according to the test data and the performance attenuation curve of the unmanned aerial vehicle, for example, the unmanned aerial vehicle is forbidden to take off at the wind speed of 18m/s, the load is more than 13kg, the unmanned aerial vehicle is forbidden to take off, the meteorological data exceed the standard in the flight process in the same way, and the unmanned aerial vehicle returns to the air immediately or is forced to land nearby.

In the application process of the unmanned aerial vehicle, the state of the unmanned aerial vehicle can be monitored in real time, that is, the monitoring of the unmanned aerial vehicle in the real-time state, in other embodiments of the present invention, the method further includes: acquiring a second environment parameter of the unmanned aerial vehicle in the process of executing a flight task; if a second target parameter value in the second environment parameter reaches a second target parameter value in the current safe use limit parameter, initiating an early warning to a preset administrator terminal; and if the third target parameter value in the second environment parameter reaches the third target parameter value in the current safe use limit parameter, sending a return command or a landing command to the unmanned aerial vehicle.

In real time, when the meteorological data do not exceed the use limit index of the unmanned aerial vehicle (no matter in an optimal state or an attenuation state), but the meteorological data tend to exceed the use limit index, for example, the wind speed is 17m/s in the operation process of the unmanned aerial vehicle, and the system gives an early warning in real time. Another kind of condition, the wind speed does not exceed standard, and the journey 20km when supposing that unmanned aerial vehicle test data is windless, and actual journey is L, receives wind speed V to influence, and ζ is the wind speed system of revising, and L20-V ζ is given, and the wind speed is big more promptly, and the journey is more close, when L is 0, marks that unmanned aerial vehicle can only resist wind at this moment, can not fly, when the negative number, indicates that unmanned aerial vehicle can't keep self state at this moment, may be blown over. (actually, the state of the unmanned aerial vehicle needs to be considered, such as adding a motor formula and a battery formula.) when the wind speed is 17m/s, the flight distance is 10km, the flight mission of the unmanned aerial vehicle needs to fly for 15km, which is between 10km and 20km, if the wind is completely absent, the mission can be completed, if the wind speed does not exceed the use limit, the mission can only fly for 10km, but the wind speed is 17m/s, the wind speed needs to be monitored in real time, and once the L calculation result is close to zero, early warning is needed, for example, a return flight instruction or a landing instruction is sent to the unmanned aerial vehicle.

For some enterprises, there may be a large number of drones, such as logistics enterprises, and at this time, the flight mission may be deduced inversely according to the performance state of the drones, that is, the flight mission may be allocated according to the performance state of the drones. In some embodiments of the invention, the method further comprises: acquiring a second target flight task; acquiring information of a plurality of unmanned aerial vehicles with predetermined performance state levels; acquiring a corresponding relation between a preset performance state grade of the unmanned aerial vehicle and a route distance; determining a target drone that matches the second target mission based on the corresponding relationship among the plurality of drones; and arranging the second target flight mission to the target unmanned aerial vehicle.

Also taking the example of a drone in a real-time situation as an example, assume that the safest voyage is 10km, but in most cases it is between 10-20 km. In order to give full play to the function of the unmanned aerial vehicle, reduce the flight risk of the unmanned aerial vehicle, have extremely serious performance attenuation on the safety air route of the unmanned aerial vehicle, and the airplane in the best state flies the long-distance air route, the unmanned aerial vehicles in different performance states are selected to execute flight tasks according to the flight tasks.

In order to better implement the unmanned aerial vehicle state evaluation method in the embodiment of the present invention, on the basis of the unmanned aerial vehicle state evaluation method, an unmanned aerial vehicle state evaluation device is further provided in the embodiment of the present invention, and is applied to a server, the server is located in an unmanned aerial vehicle state evaluation system, the unmanned aerial vehicle state evaluation system further includes an unmanned aerial vehicle parameter acquisition device provided on an unmanned aerial vehicle, as shown in fig. 5, the unmanned aerial vehicle state evaluation device 500 includes:

a first obtaining unit 501, configured to obtain the unmanned aerial vehicle state parameters collected by the unmanned aerial vehicle parameter collecting device at a target time;

a calculating unit 502, configured to calculate a performance parameter of the unmanned aerial vehicle according to the state parameter of the unmanned aerial vehicle;

a second obtaining unit 503, configured to obtain a weight ratio coefficient corresponding to each of the performance parameters of the unmanned aerial vehicle;

a determining unit 504, configured to determine, according to the performance parameter of the drone and the weight ratio coefficient, a performance state of the drone at the target time.

the calculating unit 502 is specifically configured to:

In some embodiments of the present application, the determining unit 504 is specifically configured to:

acquiring a flight task set of the unmanned aerial vehicle;

arranging the first target flight mission for the drone.

acquiring a safe use limit parameter of the unmanned aerial vehicle;

acquiring a second target flight task;

In the embodiment of the application, the first obtaining unit 501 obtains the unmanned aerial vehicle state parameters collected by the unmanned aerial vehicle parameter collecting device at the target time; the calculating unit 502 calculates the performance parameters of the unmanned aerial vehicle according to the state parameters of the unmanned aerial vehicle; a second obtaining unit 503 obtains a weight ratio coefficient corresponding to each of the performance parameters of the unmanned aerial vehicle; the determining unit 504 determines the performance state of the drone at the target time according to the drone performance parameters and the weight ratio coefficients. In the embodiment of the application, on the basis of insufficient understanding of unmanned aerial vehicle performance in prior art unmanned aerial vehicle use, through unmanned aerial vehicle parameter acquisition device, gather unmanned aerial vehicle state parameter, confirm unmanned aerial vehicle's performance state according to unmanned aerial vehicle state parameter, maintain unmanned aerial vehicle in order to guide, maintenance and use, reduce simultaneously because unusual and the trouble of operation that unmanned aerial vehicle self state leads to, can full play unmanned aerial vehicle latent energy, predict possibility and time that unmanned aerial vehicle trouble appears, as the foundation of maintaining and overhauing, in addition, the unmanned aerial vehicle performance state of aassessment still can be for selecting unmanned aerial vehicle operation task to do the guidance foundation.

The embodiment of the present invention further provides a server, which integrates any one of the unmanned aerial vehicle state evaluation devices provided by the embodiments of the present invention, and the server includes:

one or more processors;

a memory; and

one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor for performing the steps of the drone state evaluation method described in any of the drone state evaluation method embodiments above.

The embodiment of the invention also provides a server, which integrates any unmanned aerial vehicle state evaluation device provided by the embodiment of the invention. As shown in fig. 6, it shows a schematic structural diagram of a server according to an embodiment of the present invention, specifically:

the server may include components such as a processor 601 of one or more processing cores, memory 602 of one or more computer-readable storage media, a power supply 603, and an input unit 604. Those skilled in the art will appreciate that the server architecture shown in FIG. 6 is not meant to be limiting, and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.

Wherein:

the processor 601 is a control center of the server, connects various parts of the entire server using various interfaces and lines, and performs various functions of the server and processes data by running or executing software programs and/or modules stored in the memory 602 and calling data stored in the memory 602, thereby performing overall monitoring of the server. Optionally, processor 601 may include one or more processing cores; preferably, the processor 601 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 601.

The memory 602 may be used to store software programs and modules, and the processor 601 executes various functional applications and data processing by operating the software programs and modules stored in the memory 602. The memory 602 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to the use of the server, and the like. Further, the memory 602 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 602 may also include a memory controller to provide the processor 601 with access to the memory 602.

The server further includes a power supply 603 for supplying power to each component, and preferably, the power supply 603 may be logically connected to the processor 601 through a power management system, so as to implement functions of managing charging, discharging, and power consumption through the power management system. The power supply 603 may also include any component of one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and the like.

The server may also include an input unit 604, which input unit 604 may be used to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

Although not shown, the server may further include a display unit and the like, which will not be described in detail herein. Specifically, in this embodiment, the processor 601 in the server loads the executable file corresponding to the process of one or more application programs into the memory 602 according to the following instructions, and the processor 601 runs the application programs stored in the memory 602, thereby implementing various functions as follows:

acquiring unmanned aerial vehicle state parameters acquired by an unmanned aerial vehicle parameter acquisition device at a target time; calculating unmanned plane performance parameters according to the unmanned plane state parameters; obtaining a weight ratio coefficient corresponding to each performance parameter in the unmanned aerial vehicle performance parameters; and determining the performance state of the unmanned aerial vehicle at the target time according to the unmanned aerial vehicle performance parameters and the weight ratio coefficient.

It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by associated hardware controlled by the instructions, which may be stored in a computer readable storage medium and loaded and executed by a processor.

To this end, an embodiment of the present invention provides a computer-readable storage medium, which may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like. The unmanned aerial vehicle state evaluation method comprises a computer program stored thereon, and the computer program is loaded by a processor to execute the steps of any unmanned aerial vehicle state evaluation method provided by the embodiment of the invention. For example, the computer program may be loaded by a processor to perform the steps of:

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and parts that are not described in detail in a certain embodiment may refer to the above detailed descriptions of other embodiments, and are not described herein again.

In a specific implementation, each unit or structure may be implemented as an independent entity, or may be combined arbitrarily to be implemented as one or several entities, and the specific implementation of each unit or structure may refer to the foregoing method embodiment, which is not described herein again.

The above operations can be implemented in the foregoing embodiments, and are not described in detail herein.

The unmanned aerial vehicle state evaluation method, the unmanned aerial vehicle state evaluation device, the server and the storage medium provided by the embodiment of the invention are described in detail, a specific embodiment is applied in the text to explain the principle and the implementation mode of the invention, and the description of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for those skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims

1. The unmanned aerial vehicle state evaluation method is applied to a server, the server is located in an unmanned aerial vehicle state evaluation system, the unmanned aerial vehicle state evaluation system further comprises an unmanned aerial vehicle parameter acquisition device arranged on an unmanned aerial vehicle, and the method comprises the following steps:

calculating unmanned aerial vehicle performance parameters according to the unmanned aerial vehicle state parameters, wherein the unmanned aerial vehicle performance parameters comprise battery performance parameters, power system performance parameters and target core component performance parameters;

2. The method of claim 1, wherein calculating drone performance parameters based on the drone status parameters comprises:

3. The unmanned aerial vehicle state evaluation method of claim 2, wherein the battery state parameters comprise a plurality of parameters selected from a voltage parameter, a current parameter, a capacity parameter, an internal resistance parameter, a number of charging and discharging times, a temperature parameter, and a usage condition parameter;

calculating battery performance parameters of the unmanned aerial vehicle according to the weight proportion of the plurality of parameters;

or the power system state parameters comprise the working current of a motor in the unmanned aerial vehicle, the temperature of the motor and the rotating speed of the motor; according to the power system state parameter, determining the power system performance parameter of the unmanned aerial vehicle, including:

4. The method of claim 1, wherein determining the performance status of the drone at the target time based on the drone performance parameters and the weighting ratio coefficients comprises:

5. The method for evaluating the state of the unmanned aerial vehicle according to claim 4, wherein the determining the performance state level of the unmanned aerial vehicle according to the comprehensive performance parameter corresponding to each performance parameter and the attenuation coefficient corresponding to the performance parameter of the unmanned aerial vehicle comprises:

6. The unmanned aerial vehicle state evaluation method of any one of claims 1 to 5, wherein the obtaining of the attenuation coefficient corresponding to the unmanned aerial vehicle performance parameter comprises:

7. The drone status evaluation method of any one of claims 1 to 5, wherein after determining the performance status of the drone at the target time according to the drone performance parameters and the weighting ratio coefficients, the method further comprises:

acquiring a flight task set of the unmanned aerial vehicle;

arranging the first target flight mission for the drone.

8. The drone status assessment method according to claim 7, wherein after said scheduling of a flight mission for said drone, said method further comprises:

if the first target parameter value in the first environmental parameter reaches the first target parameter value in the current safe use limit parameter, the unmanned aerial vehicle is prohibited to take off and execute a flight task;

wherein, the determining the current safe use limit parameter of the unmanned aerial vehicle executing the current flight mission comprises:

acquiring a safe use limit parameter of the unmanned aerial vehicle;

9. The drone status assessment method according to claim 8, characterized in that it further comprises:

10. The drone status assessment method according to any one of claims 1 to 5, characterized in that said method further comprises:

acquiring a second target flight task;

11. The utility model provides an unmanned aerial vehicle state evaluation device, its characterized in that is applied to the server, the server is located unmanned aerial vehicle state evaluation system, unmanned aerial vehicle state evaluation system is still including setting up unmanned aerial vehicle parameter acquisition device on unmanned aerial vehicle, the device includes:

12. A computer-readable storage medium, having stored thereon a computer program which is loaded by a processor to perform the steps of the drone status assessment method of any one of claims 1 to 10.