CN113443167B

CN113443167B - Unmanned aerial vehicle state evaluation method, unmanned aerial vehicle state evaluation device, server and storage medium

Info

Publication number: CN113443167B
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: 2023-08-04
Anticipated expiration: 2040-03-24
Also published as: CN113443167A

Abstract

The embodiment of the application discloses an unmanned aerial vehicle state evaluation method, a device, a server and a storage medium, wherein the unmanned aerial vehicle state evaluation method comprises the following steps: acquiring unmanned aerial vehicle state parameters acquired at target time by an unmanned aerial vehicle parameter acquisition device; calculating unmanned aerial vehicle performance parameters according to unmanned aerial vehicle state parameters; acquiring a weight ratio coefficient corresponding to each performance parameter in the performance parameters of the unmanned aerial vehicle; 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 coefficients. According to the unmanned aerial vehicle performance state evaluation method and device, maintenance and use of the unmanned aerial vehicle can be guided, operation abnormality and faults caused by the state of the unmanned aerial vehicle are reduced, unmanned aerial vehicle potential can be fully exerted, the possibility and time of occurrence of faults of the unmanned aerial vehicle are predicted, the unmanned aerial vehicle performance state evaluation method and device serve as the basis for maintenance and overhaul, and in addition, the estimated unmanned aerial vehicle performance state can also serve as the guiding basis for selecting unmanned aerial vehicle operation tasks.

Description

Unmanned aerial vehicle state evaluation method, unmanned aerial vehicle state evaluation 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 is operated safely, the national policy temporary management method and the national policy temporary management standard are correspondingly implemented in the ground, and particularly the unmanned aerial vehicle is operated in the city and is still in a carefully fuelled stage. For unmanned aerial vehicles in different scenes, if large-scale normalized operation is required, the operation safety of the unmanned aerial vehicle is ensured under the condition of fully playing and utilizing the operation capability of the unmanned aerial vehicle besides the qualified authentication of a third party authentication mechanism.

Similar to the automobile industry, the dealer stores corresponding to the maintenance of the automobile can conduct regular mileage-fixing maintenance on the automobile, if the customer does not conduct maintenance under the requirement, the corresponding results are self-born by the customer, risks are all transferred to the customer, the daily maintenance and inspection costs are also self-born by the customer, and all the maintenance, repair and risks of non-quality problems are self-born after the customer purchases the automobile. The performance state of the automobile is fed back by the vehicle-mounted sensor to various parameters, and the parameters are comprehensively evaluated by the driving computer and displayed in a fault code and information mode.

For civil unmanned aerial vehicle, because the limitation of cost and operation scene is limited, the unmanned aerial vehicle performance status is not fully known, and the unmanned aerial vehicle can be maintained only by adopting a method of regular maintenance, or can be maintained under the condition that the unmanned aerial vehicle is abnormal or has a fault, so that the cost and the risk are greatly increased.

Disclosure of Invention

The embodiment of the invention provides an unmanned aerial vehicle state evaluation method, device, server and storage medium, which can guide maintenance, maintenance and use of an unmanned aerial vehicle, reduce operation abnormality and faults caused by the state of the unmanned aerial vehicle, fully exert the potential of the unmanned aerial vehicle, predict the possibility and time of occurrence of the faults of the unmanned aerial vehicle, and serve as the basis for maintenance and overhaul.

In one aspect, the present application 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, and 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 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 aerial vehicle performance parameters according to the unmanned aerial vehicle state parameters;

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

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

In some embodiments of the present application, the calculating, according to the unmanned aerial vehicle state parameter, a unmanned aerial vehicle performance parameter includes:

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

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

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

In some embodiments of the present application, the battery state parameter includes a plurality of parameters among a voltage parameter, a current parameter, a capacity parameter, an internal resistance parameter, a charge-discharge number, a temperature parameter, and a usage status parameter;

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

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

and calculating the battery performance parameters of the unmanned aerial vehicle according to the weight duty ratio 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 unmanned aerial vehicle;

The determining the power system performance parameter of the unmanned aerial vehicle according to the power system state parameter comprises the following steps:

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

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

calculating motor rotation speed weight according to the motor rotation speed and a preset motor rotation 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, according to the performance parameter of the unmanned aerial vehicle and the weight ratio coefficient, a performance state of the unmanned aerial vehicle at the target time includes:

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

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 each performance parameter and the attenuation coefficient corresponding to the performance parameter 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 effective performance parameters of each performance parameter according to the comprehensive performance parameters 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 the 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 in target time;

forming each performance curve corresponding to the performance parameters of the unmanned aerial vehicle based on the test data;

and determining attenuation coefficients corresponding to each performance parameter in the performance parameters of the unmanned aerial vehicle according to the performance curves.

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

And scheduling 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, the scheduling a flight mission for the unmanned aerial vehicle based on a performance status level of the unmanned aerial vehicle at a target time includes:

acquiring an unmanned aerial vehicle flight task set;

acquiring a corresponding relation between a preset unmanned aerial vehicle performance state level and a route distance;

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

and arranging the first target flight task for the unmanned aerial vehicle.

In some embodiments of the present application, after the scheduling of the flight mission for the drone based on the performance status level of the drone at the target time, the method further includes:

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

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

and if the first target parameter value in the first environment 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 the current safe-use limit parameter of the unmanned aerial vehicle for performing the current flight task includes:

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

acquiring 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 for executing the current flight task 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 environmental parameter of the unmanned aerial vehicle in the process of executing the flight task;

if the second target parameter value in the second environment parameter reaches the second target parameter value in the current safe use limit parameter, initiating early warning to a preset manager 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 instruction or a landing instruction to the unmanned aerial vehicle.

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

acquiring a second target flight task;

acquiring a plurality of unmanned aerial vehicle information of a predetermined performance state level;

determining a target unmanned aerial vehicle matched with the second target flight task in the plurality of unmanned aerial vehicles based on the corresponding relation;

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

On the other hand, the 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 still includes the unmanned aerial vehicle parameter acquisition device of setting 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 target time;

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

the second acquisition unit is used for acquiring weight ratio coefficients corresponding to each performance parameter in the performance parameters of the unmanned aerial vehicle;

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

In some embodiments of the present application, the unmanned aerial vehicle state parameters include a battery state parameter, a power system state parameter, and a target core component state parameter;

The computing unit is specifically configured to:

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 coefficients, a flight task is arranged 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 an unmanned aerial vehicle flight task set;

and arranging the first target flight task for the unmanned aerial vehicle.

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

After the unmanned aerial vehicle is scheduled to fly based on the performance state level of the unmanned aerial vehicle at the target time, determining a current safe use limit parameter of the unmanned aerial vehicle for executing the current fly task;

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 assessment method.

In another aspect, the present application also provides a computer readable storage medium having stored thereon a computer program to be loaded by a processor for performing the steps of the unmanned aerial vehicle state assessment method.

According to the embodiment of the application, the unmanned aerial vehicle state parameters acquired at the target time by the unmanned aerial vehicle parameter acquisition device are acquired; calculating unmanned aerial vehicle performance parameters according to the unmanned aerial vehicle state parameters; acquiring a weight ratio coefficient corresponding to each performance parameter in the performance parameters of the unmanned aerial vehicle; and determining the performance state of the unmanned aerial vehicle at the target time according to the unmanned aerial vehicle performance parameter and the weight ratio coefficient. According to the unmanned aerial vehicle performance state monitoring system, on the basis that the unmanned aerial vehicle performance state is not fully known in the using process of the unmanned aerial vehicle in the prior art, the unmanned aerial vehicle state parameters are collected through the unmanned aerial vehicle parameter collecting device, the performance state of the unmanned aerial vehicle is determined according to the unmanned aerial vehicle state parameters, maintenance and use of the unmanned aerial vehicle are guided, meanwhile, operation abnormality and faults caused by the state of the unmanned aerial vehicle are reduced, unmanned aerial vehicle potential can be fully exerted, the possibility and time of occurrence of faults of the unmanned aerial vehicle are predicted, the unmanned aerial vehicle performance state monitoring system is used as the basis for maintenance and overhaul, and in addition, the estimated unmanned aerial vehicle performance state can also be used as the guiding basis for selecting unmanned aerial vehicle operation tasks.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic view of a scenario of an unmanned aerial vehicle state evaluation system provided by an embodiment of the present invention;

fig. 2 is a flowchart of an embodiment of a method for evaluating a status of a drone according to an embodiment of the present invention;

FIG. 3 is a flow chart of one embodiment of step 202 provided in an embodiment of the present invention;

FIG. 4 is a flow chart of one embodiment of step 204 provided in an embodiment of the present invention;

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

fig. 6 is a schematic structural diagram of an embodiment of a server according to the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.

In the description of the present invention, it should 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 the drawings are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the apparatus or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.

In this application, the term "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 purposes 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 have not been described in detail so as not to obscure 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 an unmanned aerial vehicle state evaluation method, an unmanned aerial vehicle state evaluation device, a server and a storage medium, and the unmanned aerial vehicle state evaluation method, the unmanned aerial vehicle state evaluation device, the server and the storage medium are respectively described in detail below.

Referring to fig. 1, fig. 1 is a schematic view of a scenario of an unmanned aerial vehicle state evaluation system provided by an embodiment of the present invention, where the unmanned aerial vehicle state evaluation system 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, 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.

The server 200 in the embodiment of the invention 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 aerial vehicle performance parameters according to the unmanned aerial vehicle state parameters; acquiring a weight ratio coefficient corresponding to each performance parameter in the performance parameters of the unmanned aerial vehicle; and determining the performance state of the unmanned aerial vehicle at the target time according to the unmanned aerial vehicle performance parameter and the weight ratio coefficient.

In the embodiment of the present invention, the server 200 may be an independent server, or may be a server network or a server cluster formed by servers, for example, the server 200 described in the 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 formed by a plurality of servers. Wherein the Cloud server is composed of a large number of computers or web servers based on Cloud Computing (Cloud Computing). In embodiments of the present invention, communication between the server and the user terminal may be achieved by any communication means, including, but not limited to, mobile communication based on the third generation partnership project (3rd Generation Partnership Project,3GPP), long term evolution (Long Term Evolution, LTE), worldwide interoperability for microwave access (Worldwide Interoperability for Microwave Access, wiMAX), or computer network communication based on the TCP/IP protocol family (TCP/IP Protocol Suite, TCP/IP), user datagram protocol (User Datagram Protocol, UDP), etc.

It will be understood by those skilled in the art that the application environment shown in fig. 1 is merely an application scenario of the present application, and is not limited to the application scenario of the present application, and other application environments may also include more or fewer unmanned aerial vehicles than those shown in fig. 1, or a server network connection relationship, for example, only 1 server and 2 unmanned aerial vehicles are shown in fig. 1, and it is understood that the unmanned aerial vehicle state evaluation system may also include one or more other unmanned aerial vehicles connected to a server network, which 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 states of the unmanned aerial vehicle, and the like, collected by the unmanned aerial vehicle parameter collecting device.

It should be noted that, the schematic view of the scenario 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 scenario described in the embodiments of the present invention are for more clearly describing the technical solution of the embodiments of the present invention, and do not constitute a limitation on the technical solution provided by the embodiments of the present invention, and as a person of ordinary skill in the art can know that, along with the evolution of the unmanned aerial vehicle state evaluation system and the appearance of a new service scenario, the technical solution provided by the embodiments of the present invention is equally applicable to similar technical problems.

Firstly, 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, and 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 target time; calculating unmanned aerial vehicle performance parameters according to the unmanned aerial vehicle state parameters; acquiring a weight ratio coefficient corresponding to each performance parameter in the performance parameters of the unmanned aerial vehicle; and determining the performance state of the unmanned aerial vehicle at the target time according to the unmanned aerial vehicle performance parameter and the weight ratio coefficient.

Fig. 2 is a schematic flow chart of an embodiment of a method for evaluating the status of an unmanned aerial vehicle according to an embodiment of the present invention, where the method for evaluating the status of the 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 the 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 quantity and the type of this at least one sensor can set up as required unmanned aerial vehicle state parameter that gathers, for example, if include driving system state parameter in the unmanned aerial vehicle state parameter, then at least one sensor can include vibration sensor and the noise sensor that set up to driving system, if include the pneumatic system parameter in the unmanned aerial vehicle state parameter, then at least one sensor can include the stress strain sensor that sets up to unmanned aerial vehicle pneumatic system.

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

It is theoretically most appropriate to collect various information by sensors as much as possible without considering costs, i.e. the more and more detailed the unmanned aerial vehicle state parameters are collected, the best is the evaluation of the unmanned aerial vehicle state. However, when the cost is too high, and the development of the civil unmanned aerial vehicle is imperfect, the development experience of the medical science and the automobile industry is not available, how to distribute and assign the maintenance of the size, how many items belong to the conventional detection, how many items belong to the depth detection, and no applicable standard is available, but for enterprises or individuals who own the unmanned aerial vehicle, consumers bear the later use cost of the unmanned aerial vehicle, parts are replaced, damaged and maintained, and the like, and the production enterprises do not take the cost of the later maintenance as the primary consideration (similar to automobiles, low-cost sales and high-cost maintenance). The enterprise with the unmanned aerial vehicle generally operates autonomously and autonomously bears later maintenance, so that the old unmanned aerial vehicle can be fully utilized as much as possible, the use and maintenance cost is reduced, and the operation risk is controlled.

Therefore, in order to reduce the cost, the method and the device can integrate various indexes of the state information of the associated unmanned aerial vehicle, extract the key index of the most core (autonomously determined according to operation experience), and achieve the multi-sensor acquisition effect by using a small number of sensors, namely, the state parameters of the unmanned aerial vehicle are state parameters corresponding to the preset core performance parameters.

The unmanned aerial vehicle described in the embodiment of the invention can be an electrically-driven light and small civil unmanned aerial vehicle, and in this case, the unmanned aerial vehicle comprises a battery. For all industrial unmanned aerial vehicles driven by electricity, it is desirable to have as long a voyage and range as possible, i.e., longer flight times and longer flight distances, while maintaining reasonable cruising speeds. The most important components of the unmanned aerial vehicle system that determine this factor are the battery and the power system.

The unmanned aerial vehicle parameter acquisition device can also comprise a processor of the unmanned aerial vehicle, and can acquire some parameters of a battery of the unmanned aerial vehicle through the processor, such as voltage, current, capacity, internal resistance, charge and discharge times and the like of the battery, and of course, the battery temperature can be acquired through a temperature sensor. That is, the unmanned plane state parameters include battery state parameters, which may include a plurality of parameters of voltage parameters, current parameters, capacity parameters, internal resistance parameters, charge and discharge times, temperature parameters, and usage status parameters, it is to be understood that, in other embodiments of the present invention, the battery state parameters may include other battery state parameters besides those listed above, such as remaining service life of the battery, manufacturer information of the battery, and the like, which are not limited herein.

Besides the battery state parameters recorded by the unmanned aerial vehicle, the battery state parameters need to be uploaded to a server, and the server can conduct unmanned aerial vehicle state analysis 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.

The unmanned aerial vehicle generally comprises a power system (such as a motor), and for the power system, the main factors are that the motor has the information mainly including indexes such as motor service time, motor voltage, motor current, motor rotating speed, motor vibration, motor noise and the like. The motor bears axial load and radial load simultaneously for a long time, weight reduction is considered in structural design, performance and cost are considered, the motor bearing is more easily worn relative to the motor bearing of ground equipment, a wear gap and a virtual position are easily generated, and therefore unmanned aerial vehicle is abnormal or fails.

Thus, in some embodiments of the present invention, the unmanned aerial vehicle state parameters may include a power system state parameter, where the power system state parameter may include a motor operating current, a motor temperature, and a motor rotational speed in the unmanned aerial vehicle, and it may be understood that in other embodiments of the present invention, the power system state parameter may also include other motor parameters, for example, similar to an automobile, the longer the unmanned aerial vehicle is used, the greater the abnormal noise and wind noise may increase, and in particular, the rotating structural member may be worn, loosened, and the fastening structural member may have a lock loose or failure condition, where a motor vibration parameter (collected by a vibration sensor), a noise parameter (collected by a noise sensor), and so on may be collected, and in particular, the present invention is not limited.

In addition, in some embodiments of the present invention, the unmanned aerial vehicle state parameter may further include a target core component state parameter, where the target core component is a core component other than a battery and a power system, for example, an unmanned aerial vehicle avionics system or an unmanned aerial vehicle aerodynamic system, and may specifically be selected according to an actual scenario.

If the target core component includes an avionics system, the electronic component may be aged during use of the avionics system, and the internal resistance may be increased, so the state parameter of the target core component may include the internal resistance of the avionics system, the current used by the avionics system, and the power consumption of the avionics system device, which is not limited herein specifically.

If the target core component includes a pneumatic system, for an unmanned aerial vehicle pneumatic system, the main parameters relate to a pneumatic profile, a propeller airfoil, a fixed wing airfoil, a tail wing airfoil, and the like, so that the state parameters of the target core component may include parameters such as the pneumatic profile, the propeller airfoil, the fixed wing airfoil, the tail wing airfoil, and the like, and may be specifically acquired by using a stress-strain sensor.

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

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

In some embodiments of the invention, the unmanned aerial vehicle state parameters include a battery state parameter, a powertrain state parameter, and a target core component state parameter, as described in step 201; at this time, as shown in fig. 3, the calculating, according to the unmanned aerial vehicle state parameter, the unmanned aerial vehicle performance parameter 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 charge/discharge number, a temperature parameter, and a use condition parameter; at this time, the determining, according to the battery state parameter, the battery performance parameter of the unmanned aerial vehicle includes: respectively calculating the weight duty ratio of the parameters according to the parameters; and calculating the battery performance parameters of the unmanned aerial vehicle according to the weight duty ratio 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 state parameters of the power system may include a motor working current, a motor temperature and a motor rotation speed in the unmanned aerial vehicle; the determining the power system performance parameter of the unmanned aerial vehicle according to the power system state parameter comprises the following steps: calculating the weight of the motor working current according to the motor working current and a preset motor working current interval; calculating motor temperature weight according to the motor temperature and a preset motor temperature interval; calculating motor rotation speed weight according to the motor rotation speed and a preset motor rotation 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 a specific embodiment, the unmanned aerial vehicle motor current working range is 5 A+/-2A, namely 3A-7A, the motor current index weight is 0.4, the motor rotating speed range is 2000 rad/s+/-200 rad/s, namely 1800-2200rad/s, the motor rotating 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 rotation speed is 2100rad/s, and the motor temperature is 55 ℃, the calculation mode is as follows:

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

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

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

The performance parameters of the power system of the unmanned aerial vehicle, namely the comprehensive weight ratio, wherein the comprehensive weight ratio S=0.5×0.3+0.75×0.4+0.75×0.3=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 performance parameters of the target core component of the unmanned aerial vehicle according to the state parameters of the target core component.

If the target core component comprises an avionics system, the target core component state parameter may include internal resistance in the avionics system, avionics system power consumption, and avionics system device power consumption. 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 avionics system according to the internal resistance in the avionics system and the initial internal resistance in the avionics system; calculating the weight of the avionics system power consumption current according to the avionics system power consumption current and a preset avionics system power consumption current interval; calculating the weight of the power consumption of the avionics system equipment according to the power consumption of the avionics system equipment and a preset power consumption interval of the avionics 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 avionics system, the weight of the power consumption current of the avionics system and the weight of the power consumption of the avionics system equipment.

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

The unmanned aerial vehicle has the advantages that the performance of the unmanned aerial vehicle is reduced along with the lengthening of the service time, the unmanned aerial vehicle is similar to an automobile, the longer the service time is, the higher the oil consumption is, the more serious the abrasion of a tire and a brake pad is, the longer the braking distance is, the poorer the charging and discharging performance of a storage battery is, and the like. For unmanned aerial vehicles, various performance indexes are attenuated. The specific and most obvious index is the battery capacity, the actual capacity is phi' assuming that the battery capacity is phi, the service time (the number of charge and discharge cycles of the battery) is t, and the attenuation coefficient is lambda ₁ (as the service time is prolonged, the less the energy storage of the battery is, the larger the internal resistance is, the less the discharge capacity is), the temperature (environment) correction parameter is mu (different environment temperatures, different battery charging and discharging effects are achieved), and the historical state correction parameter is epsilon ₁ (whether the battery is charged or discharged without the specified operation, the history of the battery is abnormal or faulty, and the battery is overcharged or overdischarged) with an estimated formula of Φ' =Φμε ₁ (100％-λ ₁ t-2)。

Wherein the temperature (environment) correction parameter is related to the current unmanned aerial vehicle operation environment temperature, and the historical state correction parameter is related toThe historical battery usage correlates with the decay factor associated with each different brand of battery performance. Similarly, the longer the motor is used, the more serious the bearing wear, 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 lambda ₂ (normal decay according to actual test), the state correction parameter is ε ₂ (history state is abnormal or fault, whether maintenance record exists) according to motors in different positions, a position correction coefficient p (the parameter is related to the structural form of the unmanned aerial vehicle) is also required to be added, for example, when the unmanned aerial vehicle is a four-rotor unmanned aerial vehicle, when the unmanned aerial vehicle flies forward at a certain attitude angle, the power output of the four motors is different, the power output of the six-rotor motor and the eight-rotor motor is also different, the motors are similar to front wheels and rear wheels of a front-drive automobile, and the front wheels bear load, turn and travel, and are more worn than the rear wheels.

Therefore, the actual output power estimation formula of the unmanned aerial vehicle may be Q' =qλ ₂ ε ₂ +p, wherein Q is the normal rated output power, Q' is the actual output power, lambda ₂ For the attenuation coefficient (normal attenuation from actual test), ε ₂ Parameters (historical status anomalies or faults, whether maintenance records are present) are corrected for status.

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

In some embodiments of the present invention, as shown in fig. 4, the determining, according to the performance parameter of the unmanned aerial vehicle and the weight ratio coefficient, the performance state of the unmanned aerial vehicle at the target time 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 coefficients.

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

Normally, all coefficients are dynamically changing, e.g. attenuation coefficients, the longer the service time, the more severe the ageing and the more severe the attenuation. In the test stage, a curve of each performance index changing along with time can be formed in advance, and a function can be fitted, so that attenuation coefficients, state correction coefficients and position correction coefficients of each stage are obtained. Specifically, the obtaining 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 in target time; forming each performance curve corresponding to the performance parameters of the unmanned aerial vehicle based on the test data; and determining attenuation coefficients corresponding to each performance parameter in the performance parameters of the unmanned aerial vehicle according to the performance curves.

403. And 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 performance parameter of the unmanned aerial vehicle.

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 unmanned aerial vehicle performance parameter includes: calculating effective performance parameters of each performance parameter according to the comprehensive performance parameters 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 the following table 1, assuming that O is a performance level parameter of another unmanned aerial vehicle, the battery weight ratio coefficient is T1, the motor weight ratio coefficient is T2, the weight ratio coefficients of the other performance level parameters are T3, T1, T2 and T3 are obtained in advance according to the unmanned aerial vehicle test, the coefficients are different from each other, T1, T2 and T3 are 1, the comprehensive weight ratio in the current state is S, and the unmanned aerial vehicle performance level l1= (Φ 't1+q' t2+ot3) S, specifically, L1 may be classified into one stage, two stage, three stage, four stage and five stage according to the result.

TABLE 1

In the above embodiment, the determined performance status (e.g., the performance level L1) of the unmanned aerial vehicle may prompt the operator whether the unmanned aerial vehicle needs to be overhauled and maintained, or may evaluate whether the current unmanned aerial vehicle may 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 parameter and the weight ratio coefficient, the method further includes: and scheduling a flight task for the unmanned aerial vehicle based on the performance state grade of the unmanned aerial vehicle at the target time.

Wherein, based on the performance state level of the unmanned aerial vehicle at the target time, the unmanned aerial vehicle is scheduled to fly, may further comprise: acquiring an unmanned aerial vehicle flight task set; acquiring a corresponding relation between a preset unmanned aerial vehicle performance state level and a route distance; determining a first target flight task matched with the performance state level of the unmanned aerial vehicle in the flight task set based on the corresponding relation; and arranging the first target flight task for the unmanned aerial vehicle.

Before unmanned aerial vehicle arranges the flight mission, can constantly have unmanned aerial vehicle flight mission in the system, unmanned aerial vehicle flight mission constitutes the collection that is unmanned aerial vehicle flight mission set. At this time, if the performance state of the unmanned aerial vehicle is at "one level", if the corresponding relationship between the preset performance state level of the unmanned aerial vehicle and the route distance is that the performance state of the unmanned aerial vehicle corresponds to 20KM, at this time, the performance state of the unmanned aerial vehicle can be matched with the performance state of the unmanned aerial vehicle only when the performance state of the unmanned aerial vehicle is concentrated to the flight task of the route lower than 20KM, that is, the first target flight task needs to be determined and arranged in the flight task of the route lower than 20 KM.

After performance state evaluation is carried out on the unmanned aerial vehicle, full life state monitoring, abnormal prediction or fault prediction, flight task risk prediction and the like can be carried out on the unmanned aerial vehicle, real-time monitoring and early warning can be carried out in the execution process of the flight task, namely, the pre-take-off prediction early warning is carried out, whether the task can be executed or not is judged, the real-time monitoring and early warning is carried out after the take-off, and unmanned aerial vehicle faults or accidents caused by external condition mutation are prevented.

In some embodiments of the present invention, after the unmanned aerial vehicle is scheduled to fly based on the performance status level of the unmanned aerial vehicle at the target time, the method in the embodiment of the present invention further includes: determining a current safe use limit parameter of the unmanned aerial vehicle for executing a current flight task; acquiring a first environmental parameter of the unmanned aerial vehicle before executing a scheduled flight task, wherein the type of the parameter included in the first environmental parameter is the same as the type of the parameter included in the current safe use limit parameter; and if the first target parameter value in the first environment 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 for executing the current flight task comprises: acquiring a safe use limit parameter of the unmanned aerial vehicle; acquiring 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 for executing the current flight task based on the safe use limit parameter and the attenuation parameter.

When the unmanned aerial vehicle is in an optimal state (the optimal state of a bathtub curve, no maintenance and replacement record exists, fault records exist, a power system, particularly a battery and a motor are in an optimal state), according to the test data of the unmanned aerial vehicle and the designed performance indexes, the unmanned aerial vehicle has a safe operation use limit, such as 20m/s of wind speed, forbidden take-off, more than 15kg of load, and meteorological data, such as rainfall, visibility, temperature and the like, and once the meteorological data exceeds, the unmanned aerial vehicle is forbidden to take-off. The unmanned aerial vehicle has the range capacity of 20km, the route exceeds 20km, and take-off is forbidden. Meteorological data exceeds standard in the unmanned aerial vehicle flight process, also return to the voyage immediately or fall nearby.

The unmanned aerial vehicle can get into performance decay state along with using, and under the decay state, unmanned aerial vehicle performance descends to some extent, according to unmanned aerial vehicle test data and performance decay curve, uses limit index to change, for example wind speed 18m/s forbids taking off, and load 13kg is more, forbids taking off, and meteorological data exceeds standard in the same process of flying, and unmanned aerial vehicle returns to the journey immediately or just about forced landing.

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

Under real-time conditions, when meteorological data does not exceed the use limit index (whether in an optimal state or in an attenuation state) of the unmanned aerial vehicle, but the trend of exceeding is provided, 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. In another case, the wind speed is not out of standard, the test data of the unmanned aerial vehicle is assumed to be 20km of the range when the unmanned aerial vehicle is windless, the actual range is L, the unmanned aerial vehicle is influenced by the wind speed V, ζ is a wind speed modification system, and L=20-V ζ is the larger the wind speed, the closer the range is, when L=0, the unmanned aerial vehicle is marked to be only wind-resistant at the moment and can not fly, and when the unmanned aerial vehicle is negative, the unmanned aerial vehicle can not keep the state of the unmanned aerial vehicle at the moment and possibly can be blown over. (actually, the unmanned aerial vehicle state needs to be considered, such as a motor and a battery formula are added.) assuming that the wind speed is 17m/s, the voyage is 10km, the unmanned aerial vehicle flight mission needs to fly 15km and is between 10km and 20km, if no wind exists at all, the mission can be completed, if the wind speed does not exceed the use limit, but the wind speed is 17m/s, only 10km can be flown, the condition needs to monitor the wind speed in real time, and once the L calculation result is close to zero, early warning is needed, for example, a return voyage instruction or a landing instruction is sent to the unmanned aerial vehicle.

For some enterprises, there may be a large number of unmanned aerial vehicles, such as logistics enterprises, at which time the flight tasks may be back-pushed according to the performance state of the unmanned aerial vehicle, i.e. allocated according to the performance state of the unmanned aerial vehicle. In some embodiments of the invention, the method further comprises: acquiring a second target flight task; acquiring a plurality of unmanned aerial vehicle information of a predetermined performance state level; acquiring a corresponding relation between a preset unmanned aerial vehicle performance state level and a route distance; determining a target unmanned aerial vehicle matched with the second target flight task in the plurality of unmanned aerial vehicles based on the corresponding relation; and arranging the second target flight mission to the target unmanned aerial vehicle.

Also taking the example of a drone in real time, it is assumed that the safest voyage is 10km, but in most practical cases between 10-20 km. In order to fully play the role of the unmanned aerial vehicle, reduce the flight risk of the unmanned aerial vehicle, the unmanned aerial vehicle with extremely serious performance attenuation flies the safe route, the aircraft of the best state flies the long distance route, select unmanned aerial vehicle of different performance states to carry out the flight mission according to the flight mission.

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, the embodiment of the present invention further provides an unmanned aerial vehicle state evaluation device, which is applied to a server, where the server is located in an unmanned aerial vehicle state evaluation system, and the unmanned aerial vehicle state evaluation system further includes an unmanned aerial vehicle parameter acquisition device disposed on an unmanned aerial vehicle, as shown in fig. 5, where the unmanned aerial vehicle state evaluation device 500 includes:

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

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

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

And the determining unit 504 is configured to determine a performance state of the unmanned aerial vehicle at the target time according to the performance parameter of the unmanned aerial vehicle and the weight ratio coefficient.

the computing unit 502 is specifically configured to:

The computing unit 502 is specifically configured to:

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

acquiring an unmanned aerial vehicle flight task set;

And arranging the first target flight task for the unmanned aerial vehicle.

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 unmanned aerial vehicle performance parameters according to the unmanned aerial vehicle state parameters; a second obtaining unit 503 obtains a weight ratio coefficient corresponding to each performance parameter in the performance parameters of the unmanned aerial vehicle; the determining unit 504 determines, according to the performance parameter of the unmanned aerial vehicle and the weight ratio coefficient, a performance state of the unmanned aerial vehicle at the target time. According to the unmanned aerial vehicle performance state monitoring system, on the basis that the unmanned aerial vehicle performance state is not fully known in the using process of the unmanned aerial vehicle in the prior art, the unmanned aerial vehicle state parameters are collected through the unmanned aerial vehicle parameter collecting device, the performance state of the unmanned aerial vehicle is determined according to the unmanned aerial vehicle state parameters, maintenance and use of the unmanned aerial vehicle are guided, meanwhile, operation abnormality and faults caused by the state of the unmanned aerial vehicle are reduced, unmanned aerial vehicle potential can be fully exerted, the possibility and time of occurrence of faults of the unmanned aerial vehicle are predicted, the unmanned aerial vehicle performance state monitoring system is used as the basis for maintenance and overhaul, and in addition, the estimated unmanned aerial vehicle performance state can also be used as the guiding basis for selecting unmanned aerial vehicle operation tasks.

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, and the server comprises:

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 perform the steps of the drone state assessment method described in any of the drone state assessment method embodiments described above by the processor.

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, a schematic diagram of a server according to an embodiment of the present invention is shown, specifically:

the server may include one or more processing cores 'processors 601, one or more computer-readable storage media's memory 602, power supply 603, and input unit 604, among other components. Those skilled in the art will appreciate that the server architecture shown in fig. 6 is not limiting of the server and may include more or fewer components than shown, or may combine certain components, 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, the processor 601 may include one or more processing cores; preferably, the processor 601 may integrate an application processor and a modem processor, wherein the application processor primarily handles operating systems, user interfaces, applications, etc., and the modem processor primarily 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 may execute various functional applications and data processing by executing the software programs and modules stored in the memory 602. The memory 602 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data created according to the use of the server, etc. In addition, 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 access to the memory 602 by the processor 601.

The server also includes a power supply 603 for powering the various components, preferably, the power supply 603 can be logically coupled to the processor 601 through a power management system, such that functions of managing charging, discharging, and power consumption are performed by the power management system. The power supply 603 may also include one or more of any components, such as a direct current or alternating current power supply, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and the like.

The server may further comprise an input unit 604, which input unit 604 may be used for receiving input numerical or character information and for generating keyboard, mouse, joystick, optical or trackball signal inputs in connection with user settings and function control.

Although not shown, the server may further include a display unit or the like, which is not described herein. In this embodiment, the processor 601 in the server loads executable files corresponding to the processes of one or more application programs into the memory 602 according to the following instructions, and the processor 601 executes the application programs stored in the memory 602, so as to implement various functions as follows:

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

Those of ordinary skill in the art will appreciate that all or a portion of the steps of the various methods of the above embodiments may be performed by instructions, or by instructions controlling associated hardware, 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, random Access Memory), magnetic or optical disk, and the like. And a computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in any unmanned aerial vehicle state evaluation method provided by the embodiment of the invention. For example, the loading of the computer program by the processor may perform the steps of:

In the foregoing embodiments, the descriptions of the embodiments are focused on, and the portions of one embodiment that are not described in detail in the foregoing embodiments may be referred to in the foregoing detailed description of other embodiments, which are not described herein again.

In the implementation, each unit or structure may be implemented as an independent entity, or may be implemented as the same entity or several entities in any combination, and the implementation of each unit or structure may be referred to the foregoing method embodiments and will not be repeated herein.

The specific implementation of each operation above may be referred to the previous embodiments, and will not be described herein.

The method, the device, the server and the storage medium for evaluating the state of the unmanned aerial vehicle provided by the embodiment of the invention are described in detail, and specific examples are applied to the description of the principle and the implementation mode of the invention, and the description of the above embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in light of the ideas of the present invention, the present description should not be construed as limiting the present invention.

Claims

1. The unmanned aerial vehicle state evaluation method is characterized by being applied to a server, wherein 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;

according to the unmanned aerial vehicle performance parameters and the weight ratio coefficients, determining the performance state of the unmanned aerial vehicle at the target time;

the determining, according to the unmanned aerial vehicle performance parameter and the weight ratio coefficient, the performance state of the unmanned aerial vehicle at the target time includes:

determining the performance state level of the unmanned aerial vehicle according to the comprehensive performance parameters corresponding to each performance parameter and the attenuation coefficient corresponding to the performance parameter of the unmanned aerial vehicle;

the determining the performance state level 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 parameters comprises the following steps:

2. The unmanned aerial vehicle state evaluation method of claim 1, wherein the calculating unmanned aerial vehicle performance parameters from the unmanned aerial vehicle state parameters comprises:

3. The unmanned aerial vehicle state evaluation method of claim 2, wherein the battery state parameters 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 use condition parameter;

calculating battery performance parameters of the unmanned aerial vehicle according to the weight duty ratio of the parameters;

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

4. A method for evaluating the status of a drone according to any one of claims 1 to 3, wherein the obtaining the attenuation coefficient corresponding to the performance parameter of the drone comprises:

5. A drone state assessment method according to any one of claims 1 to 3, wherein after determining the performance state of the drone at the target time from the drone performance parameter and the weight ratio coefficient, the method further comprises:

acquiring an unmanned aerial vehicle flight task set;

and arranging the first target flight task for the unmanned aerial vehicle.

6. The unmanned aerial vehicle state assessment method of claim 5, wherein after the scheduling of flight tasks for the unmanned aerial vehicle, the method further comprises:

if the first target parameter value in the first environment 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 for executing the current flight task comprises:

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

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

7. The unmanned aerial vehicle state assessment method of claim 6, wherein the method further comprises:

8. A method of unmanned aerial vehicle state assessment according to any of claims 1 to 3, wherein the method further comprises:

acquiring a second target flight task;

9. 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 still includes the unmanned aerial vehicle parameter acquisition device of setting 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 target time, wherein the unmanned aerial vehicle state parameters comprise battery state parameters, power system state parameters and target core component state parameters;

The calculation unit is used for 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;

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

the determining unit is specifically configured to:

10. A computer-readable storage medium, characterized in that it has stored thereon a computer program, which is loaded by a processor to perform the steps of the unmanned aerial vehicle state assessment method of any of claims 1 to 8.