A method for risk assessment and quality monitoring of unmanned aerial vehicle flight

Abstract

The present invention provides a method for risk assessment and quality monitoring of unmanned aerial vehicle flight, and relates to the technical field of unmanned aerial vehicle flight. The method comprises: acquiring flight data of unmanned aerial vehicle flight, and performing risk assessment on the unmanned aerial vehicle flight; acquiring and processing current flight monitoring data of the unmanned aerial vehicle flight, and establishing an unmanned aerial vehicle flight simulation model according to historical flight monitoring data and a preset simulation model to determine the flight quality of the unmanned aerial vehicle flight; constructing an unmanned aerial vehicle flight comprehensive assessment model, and performing mutual comprehensive calibration on the risk assessment result of the unmanned aerial vehicle flight and the flight quality of the unmanned aerial vehicle flight, and determining the comprehensive risk assessment result and the comprehensive flight quality of the unmanned aerial vehicle flight; constructing a flight sequence of the unmanned aerial vehicle, and performing comparative analysis on the comprehensive risk assessment result and the comprehensive flight quality, and optimizing the flight control strategy of the unmanned aerial vehicle, so as to effectively realize the risk assessment and quality monitoring of the unmanned aerial vehicle flight.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicle flight technology, and in particular to a method for unmanned aerial vehicle flight risk assessment and quality monitoring. Background Art

[0002] With the continuous development of drone technology, the number of drone flights is increasing, but there are many risk factors in the drone flight process, which seriously affect the safety of drone flight; in addition, in order to ensure the safety of drone flight, the flight ability requirements of drone pilots are increasing, and improving flight ability requires real-time monitoring and evaluation of drone flight quality; the existing quality monitoring and evaluation mainly relies on manual evaluation, and the evaluation quality is low.

[0003] Therefore, the present invention provides a method for risk assessment and quality monitoring of UAV flight. Summary of the invention

[0004] The present invention provides a method for risk assessment and quality monitoring of unmanned aerial vehicle flight. The method comprises the following steps: performing risk assessment on unmanned aerial vehicle flight by acquiring flight data of unmanned aerial vehicle flight; acquiring and processing current flight monitoring data of unmanned aerial vehicle flight, establishing an unmanned aerial vehicle flight simulation model according to historical flight monitoring data and a preset simulation model to determine the flight quality of unmanned aerial vehicle flight; constructing an unmanned aerial vehicle flight comprehensive assessment model, performing mutual comprehensive calibration on the risk assessment result of unmanned aerial vehicle flight and the flight quality of unmanned aerial vehicle flight, and determining the comprehensive risk assessment result and comprehensive flight quality of unmanned aerial vehicle flight; constructing a flight sequence of unmanned aerial vehicle, performing comparative analysis on the comprehensive risk assessment result and comprehensive flight quality, optimizing the flight control strategy of unmanned aerial vehicle, and effectively realizing risk assessment and quality monitoring of unmanned aerial vehicle flight.

[0005] The present invention provides a method for unmanned aerial vehicle flight risk assessment and quality monitoring, comprising:

[0006] Step 1: Obtain the flight environment data, flight mission data and flight status data of the UAV flight, and conduct a risk assessment on the UAV flight;

[0007] Step 2: Obtain and process the current flight monitoring data of the UAV flight, establish a UAV flight simulation model based on the historical flight monitoring data and the preset simulation model, input the current flight monitoring data of the UAV, and determine the flight quality of the UAV flight;

[0008] Step 3: Construct a comprehensive assessment model for UAV flight, conduct mutual comprehensive calibration of the risk assessment results of UAV flight and the flight quality of UAV flight, and determine the comprehensive risk assessment results and comprehensive flight quality of UAV flight;

[0009] Step 4: Construct a flight sequence for the UAV, compare and analyze the comprehensive risk assessment results and the comprehensive flight quality, and optimize the flight control strategy of the UAV.

[0010] According to a UAV flight risk assessment and quality monitoring method provided by the present invention, the flight environment data, flight mission data and flight status data of the UAV flight are obtained, and the risk assessment of the UAV flight is performed, including:

[0011] Obtain the current flight environment data, current flight mission data and current flight status data of the UAV flight and perform data preprocessing;

[0012] Perform data integration processing on the current flight environment data, current flight mission data and current flight status data of the UAV flight that have completed data preprocessing to construct a flight data set;

[0013] The flight risk impact data of UAV flight is determined based on the historical flight data of UAV flight, a UAV flight risk assessment model is constructed, and the current flight risk impact data of the flight data set is input to conduct a risk assessment on UAV flight.

[0014] According to a UAV flight risk assessment and quality monitoring method provided by the present invention, the flight risk impact data of the UAV flight is determined based on the historical flight data of the UAV flight, and a UAV flight risk assessment model is constructed, including:

[0015] Obtain historical flight data of UAV flights, conduct risk assessments based on flight data types, and determine flight risk impact data, where the flight data types include: flight environment data types, flight mission data types, and flight status data types;

[0016] Based on the historical flight data of UAV flights and the flight risk impact data, comprehensive learning is carried out to determine the impact weight of the flight risk impact data on the risk assessment results, and a UAV flight risk assessment model is constructed.

[0017] According to a UAV flight risk assessment and quality monitoring method provided by the present invention, current flight monitoring data of the UAV flight is obtained and processed, including:

[0018] Obtain the current flight monitoring data of the UAV flight, perform data noise reduction processing, and upload it to the flight monitoring platform in real time, where the current flight monitoring data includes: current flight environment monitoring data, current flight mission monitoring data, and current flight status monitoring data;

[0019] Conduct data consistency checks on the current flight monitoring data uploaded in real time and perform data conversion processing according to the preset data format of the flight monitoring platform;

[0020] When the data conversion process is completed, the flight monitoring platform receives the current flight monitoring data of the UAV flight.

[0021] According to a UAV flight risk assessment and quality monitoring method provided by the present invention, a UAV flight simulation model is established based on historical flight monitoring data and a preset simulation model, and the current flight monitoring data of the UAV is input to determine the flight quality of the UAV flight, including:

[0022] Obtain historical flight monitoring data of the UAV and establish a UAV flight simulation model based on the preset simulation model;

[0023] Calibrate the model parameters of the UAV flight simulation model according to the historical flight monitoring data of the UAV;

[0024] Compare the current flight monitoring data of the UAV with the historical flight monitoring data of the UAV. If the current flight monitoring data contains data variables of data types inconsistent with the historical flight monitoring data, extract the data variables and perform a secondary model parameter calibration on the UAV flight simulation model that has completed the primary model parameter calibration process.

[0025] The preset flight quality evaluation index of the UAV flight is obtained, and the current flight monitoring data of the UAV is input into the UAV flight simulation model after the model parameter calibration process is completed to determine the flight quality of the UAV.

[0026] According to a UAV flight risk assessment and quality monitoring method provided by the present invention, a UAV flight comprehensive assessment model is constructed, the risk assessment result of the UAV flight and the flight quality of the UAV flight are calibrated against each other, and the comprehensive risk assessment result and the comprehensive flight quality of the UAV flight are determined, including:

[0027] Construct a comprehensive assessment model for UAV flight, conduct mutual comprehensive calibration of the risk assessment results and the flight quality of UAV flight, and determine the mutual influence weights between the risk assessment results and the flight quality;

[0028] The minimum risk impact weight of the flight impact data in the comprehensive assessment model of the UAV flight is set. When the risk impact weight of the current flight risk impact data of the monitored UAV flight on the current flight monitoring data is not higher than the minimum risk impact weight, the current flight risk impact data is removed;

[0029] Perform comprehensive quality screening on the current flight risk impact data that has been eliminated based on the quality impact weight of flight quality on risk assessment results;

[0030] When the quality-weighted risk impact weight of the current flight risk impact data after the data elimination process is weighted by the quality impact weight is not higher than the minimum risk impact weight, a secondary data elimination process is performed to determine the comprehensive risk impact data after the comprehensive calibration process, and a comprehensive risk assessment is performed;

[0031] Fix the comprehensive risk impact data completed by the comprehensive calibration process, construct secondary indicators for the flight quality evaluation index of the flight quality based on the risk impact weight of the flight quality in combination with the risk assessment result, determine the comprehensive flight quality evaluation index completed by the comprehensive verification process, and conduct a comprehensive flight quality evaluation;

[0032] The comprehensive quantitative value of UAV flight is calculated based on the comprehensive risk assessment results and the comprehensive flight quality assessment results;

[0033] ;in, Indicates the comprehensive quantitative value of drone flight; Indicates the influence weight of comprehensive risk impact data of UAV flight environment on comprehensive risk assessment results; Indicates the weight of the comprehensive risk impact data of the UAV flight mission on the comprehensive risk assessment results; Indicates the influence weight of the comprehensive risk impact data of the UAV flight status on the comprehensive risk assessment results; Indicates that there is no drone flight The probability that a comprehensive risk affects the data; Indicates the first Comprehensive risk impact data; Indicates the first The comprehensive value of the comprehensive flight quality evaluation indicators; Indicates the first The preset values ​​of the preset flight quality evaluation indicators; Indicates the quality impact weight of flight quality on risk assessment results; Indicates the risk impact weight of risk assessment results on flight quality; Indicates the number of comprehensive risk impact data; Represents the number of comprehensive flight quality evaluation indicators.

[0034] A method for evaluating and monitoring the flight risk of a drone provided by the present invention further includes:

[0035] Generate UAV flight report data or UAV flight alarm data according to the comprehensive quantitative value of the UAV flight;

[0036] The adjustment period of the UAV's flight control strategy is set. When the UAV flight report data or the UAV flight alarm data is monitored, if no manual adjustment of the flight control strategy occurs within the corresponding adjustment period, the flight control strategy is automatically adjusted.

[0037] According to a UAV flight risk assessment and quality monitoring method provided by the present invention, a flight sequence of the UAV is constructed, the comprehensive risk assessment results and the comprehensive flight quality are compared and analyzed, and the flight control strategy of the UAV is optimized, including:

[0038] Construct the flight sequence of the UAV and divide the flight path of the UAV into sequences, wherein the flight sequence of the UAV includes: flight time sequence and flight space sequence;

[0039] According to the sequence division results, the comprehensive risk assessment results and the comprehensive flight quality are compared horizontally and vertically;

[0040] Determine the flight optimization target of the UAV flight according to the comparison results of the current flight sequence, and optimize the flight control strategy of the UAV;

[0041] The flight control strategy optimized by the strategy is applied in the next flight sequence, and the flight control strategy optimized by the strategy is optimized and verified according to the comparison result of the next flight sequence. If the optimization verification fails, a secondary strategy optimization and secondary optimization verification are performed.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] Acquire the flight data of UAV flight and conduct risk assessment on UAV flight; acquire and process the current flight monitoring data of UAV flight, establish a UAV flight simulation model based on historical flight monitoring data and preset simulation models to determine the flight quality of UAV flight; construct a comprehensive assessment model for UAV flight, conduct mutual comprehensive calibration of the risk assessment results of UAV flight and the flight quality of UAV flight, and determine the comprehensive risk assessment results and comprehensive flight quality of UAV flight; construct the flight sequence of UAV, conduct comparative analysis on the comprehensive risk assessment results and comprehensive flight quality, optimize the flight control strategy of UAV, and effectively realize the risk assessment and quality monitoring of UAV flight.

[0044] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0045] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0047] Figure 1 It is a flow chart of a method for risk assessment and quality monitoring of unmanned aerial vehicle flight provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0049] Embodiment 1:

[0050] The present invention provides a method for risk assessment and quality monitoring of unmanned aerial vehicle flight. Figure 1 As shown, including:

[0051] Step 1: Obtain the flight environment data, flight mission data and flight status data of the UAV flight, and conduct a risk assessment on the UAV flight;

[0052] Step 2: Obtain and process the current flight monitoring data of the UAV flight, establish a UAV flight simulation model based on the historical flight monitoring data and the preset simulation model, input the current flight monitoring data of the UAV, and determine the flight quality of the UAV flight;

[0053] Step 3: Construct a comprehensive assessment model for UAV flight, conduct mutual comprehensive calibration of the risk assessment results of UAV flight and the flight quality of UAV flight, and determine the comprehensive risk assessment results and comprehensive flight quality of UAV flight;

[0054] Step 4: Construct a flight sequence for the UAV, compare and analyze the comprehensive risk assessment results and the comprehensive flight quality, and optimize the flight control strategy of the UAV.

[0055] In this embodiment, the current flight monitoring data of the UAV flight refers to the current flight environment monitoring data, the current flight mission monitoring data and the current flight status monitoring data of the UAV flight.

[0056] In this embodiment, the UAV flight simulation model is used to simulate the flight of the UAV, and then determine the flight quality of the UAV flight.

[0057] In this embodiment, the UAV flight comprehensive assessment model is used to comprehensively calibrate the risk assessment results and flight quality of the UAV flight.

[0058] In this embodiment, a flight sequence of the UAV is constructed, wherein the flight sequence of the UAV includes: a flight time sequence and a flight space sequence.

[0059] In this embodiment, constructing the flight sequence of the UAV and performing comparative analysis on the comprehensive risk assessment results and the comprehensive flight quality refers to performing horizontal comparative analysis on the flight sequence and vertical comparative analysis on the flight sequence on the comprehensive risk assessment results and the comprehensive flight quality, respectively.

[0060] The working principle and beneficial effects of the above technical solution are: obtaining the flight data of the UAV flight and conducting a risk assessment on the UAV flight; obtaining and processing the current flight monitoring data of the UAV flight, establishing a UAV flight simulation model based on the historical flight monitoring data and a preset simulation model to determine the flight quality of the UAV flight; constructing a comprehensive evaluation model for UAV flight, calibrating the risk assessment results of the UAV flight and the flight quality of the UAV flight, and determining the comprehensive risk assessment results and comprehensive flight quality of the UAV flight; constructing a flight sequence for the UAV, comparing and analyzing the comprehensive risk assessment results and the comprehensive flight quality, optimizing the flight control strategy of the UAV, and effectively realizing the risk assessment and quality monitoring of the UAV flight.

[0061] Embodiment 2:

[0062] The embodiment of the present invention provides a method for risk assessment and quality monitoring of UAV flight, which obtains flight environment data, flight mission data, and flight status data of the UAV flight, and performs risk assessment on the UAV flight, including:

[0063] Obtain the current flight environment data, current flight mission data and current flight status data of the UAV flight and perform data preprocessing;

[0064] Perform data integration processing on the current flight environment data, current flight mission data and current flight status data of the UAV flight that have completed data preprocessing to construct a flight data set;

[0065] The flight risk impact data of UAV flight is determined based on the historical flight data of UAV flight, a UAV flight risk assessment model is constructed, and the current flight risk impact data of the flight data set is input to conduct a risk assessment on UAV flight.

[0066] In this embodiment, the flight environment data of the UAV flight is obtained, wherein the flight environment data includes: flight meteorological environment data, flight geographical environment data and flight control environment data.

[0067] In this embodiment, flight mission data of the UAV flight is obtained, wherein the flight mission data includes: flight mission type data, flight mission path data, and flight mission load data.

[0068] In this embodiment, the flight status data of the UAV is obtained, wherein the flight status data includes: flight software status data and flight hardware status data.

[0069] In this embodiment, the flight data set refers to a collection of current data of the UAV flight.

[0070] The working principle and beneficial effect of the above technical solution are: by obtaining the flight environment data, flight mission data and flight status data of the UAV flight, the risk assessment of the UAV flight is carried out, which is conducive to ensuring the flight safety of the UAV.

[0071] Embodiment 3:

[0072] The embodiment of the present invention provides a method for evaluating and monitoring the flight risk of a drone, which determines the flight risk impact data of the drone flight according to the historical flight data of the drone flight, and constructs a drone flight risk evaluation model, including:

[0073] Obtain historical flight data of UAV flights, conduct risk assessments based on flight data types, and determine flight risk impact data, where the flight data types include: flight environment data types, flight mission data types, and flight status data types;

[0074] Based on the historical flight data of UAV flights and the flight risk impact data, comprehensive learning is carried out to determine the impact weight of the flight risk impact data on the risk assessment results, and a UAV flight risk assessment model is constructed.

[0075] In this embodiment, the flight risk impact data refers to data that affects the flight of the UAV, such as flight environment risk impact data and flight mission risk impact data.

[0076] In this embodiment, the UAV flight risk assessment model is used to perform comprehensive quantitative weighting on various flight risk impact data, determine the risk assessment value of the UAV, and implement risk assessment of UAV flight.

[0077] The working principle and beneficial effects of the above technical solution are: determining the flight risk impact data of UAV flight based on the historical flight data of UAV flight, and constructing a UAV flight risk assessment model, which is conducive to realizing the risk assessment of UAV flight.

[0078] Embodiment 4:

[0079] The embodiment of the present invention provides a method for risk assessment and quality monitoring of UAV flight, which acquires and processes current flight monitoring data of UAV flight, including:

[0080] Obtain the current flight monitoring data of the UAV flight, perform data noise reduction processing, and upload it to the flight monitoring platform in real time, where the current flight monitoring data includes: current flight environment monitoring data, current flight mission monitoring data, and current flight status monitoring data;

[0081] Conduct data consistency checks on the current flight monitoring data uploaded in real time and perform data conversion processing according to the preset data format of the flight monitoring platform;

[0082] When the data conversion process is completed, the flight monitoring platform receives the current flight monitoring data of the UAV flight.

[0083] In this embodiment, data consistency determination is performed on the current flight monitoring data uploaded in real time to ensure that the data is continuous, complete and valid.

[0084] The working principle and beneficial effect of the above technical solution are: by acquiring and processing the current flight monitoring data of the UAV flight, a data foundation is laid for the subsequent quality monitoring of the UAV flight.

[0085] Embodiment 5:

[0086] The embodiment of the present invention provides a method for risk assessment and quality monitoring of unmanned aerial vehicle flight, which establishes an unmanned aerial vehicle flight simulation model according to historical flight monitoring data and a preset simulation model, inputs the current flight monitoring data of the unmanned aerial vehicle, and determines the flight quality of the unmanned aerial vehicle flight, including:

[0087] Obtain historical flight monitoring data of the UAV and establish a UAV flight simulation model based on the preset simulation model;

[0088] Calibrate the model parameters of the UAV flight simulation model according to the historical flight monitoring data of the UAV;

[0089] Compare the current flight monitoring data of the UAV with the historical flight monitoring data of the UAV. If the current flight monitoring data contains data variables of data types inconsistent with the historical flight monitoring data, extract the data variables and perform a secondary model parameter calibration on the UAV flight simulation model that has completed the primary model parameter calibration process.

[0090] The preset flight quality evaluation index of the UAV flight is obtained, and the current flight monitoring data of the UAV is input into the UAV flight simulation model after the model parameter calibration process is completed to determine the flight quality of the UAV.

[0091] In this embodiment, calibrating the model parameters of the UAV flight simulation model according to the historical flight monitoring data of the UAV refers to calibrating the parameters of the UAV flight simulation model according to the historical flight monitoring data, so as to ensure the simulation accuracy of the UAV flight simulation model.

[0092] In this embodiment, the current flight monitoring data contains data variables of data types inconsistent with those of the historical flight monitoring data, that is, such data does not exist in the historical flight monitoring data.

[0093] In this embodiment, the data variables are extracted and a secondary model parameter calibration is performed on the UAV flight simulation model that has completed the primary model parameter calibration process, so as to ensure that the UAV flight simulation model accurately simulates and analyzes the current flight monitoring data.

[0094] In this embodiment, preset flight quality evaluation indicators of the UAV flight are obtained, such as a flight quality stability evaluation indicator, a flight quality efficiency evaluation indicator, and a flight quality task completion evaluation indicator.

[0095] The working principle and beneficial effects of the above technical solution are: establishing a UAV flight simulation model based on historical flight monitoring data and a preset simulation model, inputting the current flight monitoring data of the UAV, determining the flight quality of the UAV flight, and effectively realizing the quality monitoring of the UAV flight.

[0096] Embodiment 6:

[0097] The embodiment of the present invention provides a method for risk assessment and quality monitoring of UAV flight, constructs a comprehensive assessment model for UAV flight, performs mutual comprehensive calibration on the risk assessment result of UAV flight and the flight quality of UAV flight, and determines the comprehensive risk assessment result and comprehensive flight quality of UAV flight, including:

[0098] Construct a comprehensive assessment model for UAV flight, conduct mutual comprehensive calibration of the risk assessment results and the flight quality of UAV flight, and determine the mutual influence weights between the risk assessment results and the flight quality;

[0099] The minimum risk impact weight of the flight impact data in the comprehensive assessment model of the UAV flight is set. When the risk impact weight of the current flight risk impact data of the monitored UAV flight on the current flight monitoring data is not higher than the minimum risk impact weight, the current flight risk impact data is removed;

[0100] Perform comprehensive quality screening on the current flight risk impact data that has been eliminated based on the quality impact weight of flight quality on risk assessment results;

[0101] When the quality-weighted risk impact weight of the current flight risk impact data after the data elimination process is weighted by the quality impact weight is not higher than the minimum risk impact weight, a secondary data elimination process is performed to determine the comprehensive risk impact data after the comprehensive calibration process, and a comprehensive risk assessment is performed;

[0102] Fix the comprehensive risk impact data completed by the comprehensive calibration process, construct secondary indicators for the flight quality evaluation index of the flight quality based on the risk impact weight of the flight quality in combination with the risk assessment result, determine the comprehensive flight quality evaluation index completed by the comprehensive verification process, and conduct a comprehensive flight quality evaluation;

[0103] The comprehensive quantitative value of UAV flight is calculated based on the comprehensive risk assessment results and the comprehensive flight quality assessment results;

[0104] ;in, Indicates the comprehensive quantitative value of drone flight; Indicates the influence weight of comprehensive risk impact data of UAV flight environment on comprehensive risk assessment results; Indicates the weight of the comprehensive risk impact data of the UAV flight mission on the comprehensive risk assessment results; Indicates the influence weight of the comprehensive risk impact data of the UAV flight status on the comprehensive risk assessment results; Indicates that there is no drone flight The probability that a comprehensive risk will affect the data; Indicates the first Comprehensive risk impact data; Indicates the first The comprehensive value of the comprehensive flight quality evaluation indicators; Indicates the first The preset values ​​of the preset flight quality evaluation indicators; Indicates the quality impact weight of flight quality on risk assessment results; Indicates the risk impact weight of risk assessment results on flight quality; Indicates the number of comprehensive risk impact data; Represents the number of comprehensive flight quality evaluation indicators.

[0105] In this embodiment, when the risk impact weight of the current flight risk impact data of the monitored drone flight on the current flight monitoring data is not higher than the minimum risk impact weight, the current flight risk impact data does not affect the drone flight.

[0106] In this embodiment, performing comprehensive quality screening on the current flight risk impact data after data elimination according to the quality impact weight of the flight quality on the risk assessment result refers to screening performed under consideration of the impact of the flight quality on the risk assessment result.

[0107] In this embodiment, when the quality-weighted risk impact weight of the current flight risk impact data after the data elimination processing is weighted by the quality impact weight is not higher than the minimum risk impact weight, the current flight risk impact data under the influence of flight quality does not affect the flight of the drone.

[0108] In this embodiment, the mutual influence weights of the risk assessment result and the flight quality are determined. For example, the risk influence weight c1 of the risk assessment result a1 on the flight quality b1, that is, the comprehensive flight quality is c1b1.

[0109] In this embodiment, the comprehensive quantitative value of the UAV flight is used to represent the comprehensive risk assessment result and the comprehensive flight quality assessment result of the UAV flight. The smaller the comprehensive quantitative value, the lower the corresponding comprehensive risk assessment and the higher the comprehensive flight quality.

[0110] The working principle and beneficial effects of the above technical solution are: by constructing a comprehensive assessment model for UAV flight, the risk assessment results of UAV flight and the flight quality of UAV flight are calibrated against each other, the comprehensive risk assessment results and comprehensive flight quality of UAV flight are determined, and the risk assessment and quality monitoring of UAV flight are effectively realized.

[0111] Embodiment 7:

[0112] The embodiment of the present invention provides a method for evaluating and monitoring the flight risk of a drone, further comprising:

[0113] Generate UAV flight report data or UAV flight alarm data according to the comprehensive quantitative value of the UAV flight;

[0114] The adjustment period of the UAV's flight control strategy is set. When the UAV flight report data or the UAV flight alarm data is monitored, if no manual adjustment of the flight control strategy occurs within the corresponding adjustment period, the flight control strategy is automatically adjusted.

[0115] In this embodiment, drone flight report data is generated when the drone flight risk assessment and quality monitoring are normal.

[0116] In this embodiment, drone flight alarm data is generated when drone flight risk assessment or quality monitoring is abnormal.

[0117] The working principle and beneficial effects of the above technical solution are: by generating UAV flight report data or UAV flight alarm data, executing manual or automatic adjustment of flight control strategy, the safety of UAV flight is effectively ensured.

[0118] Embodiment 8:

[0119] The embodiment of the present invention provides a method for evaluating the flight risk and monitoring the quality of a UAV, constructing a flight sequence of a UAV, performing comparative analysis on the comprehensive risk evaluation results and the comprehensive flight quality, and optimizing the flight control strategy of the UAV, including:

[0120] Construct the flight sequence of the UAV and divide the flight path of the UAV into sequences, wherein the flight sequence of the UAV includes: flight time sequence and flight space sequence;

[0121] According to the sequence division results, the comprehensive risk assessment results and the comprehensive flight quality are compared horizontally and vertically;

[0122] Determine the flight optimization target of the UAV flight according to the comparison results of the current flight sequence, and optimize the flight control strategy of the UAV;

[0123] The flight control strategy optimized by the strategy is applied in the next flight sequence, and the flight control strategy optimized by the strategy is optimized and verified according to the comparison result of the next flight sequence. If the optimization verification fails, a secondary strategy optimization and secondary optimization verification are performed.

[0124] In this embodiment, the comprehensive risk assessment results and the comprehensive flight quality are compared horizontally and vertically according to the sequence division results. For example, the comprehensive risk assessment results and the comprehensive flight quality of each UAV flight are compared horizontally according to the flight space sequence.

[0125] In this embodiment, the flight optimization target of the UAV flight is determined according to the current flight sequence comparison result, for example, the stability of the UAV flight is optimized.

[0126] In this embodiment, secondary strategy optimization and secondary optimization verification are used to periodically optimize the flight control strategy of the UAV flight to ensure flight quality.

[0127] The working principle and beneficial effects of the above technical solution are: constructing a flight sequence for the UAV, comparing and analyzing the comprehensive risk assessment results and the comprehensive flight quality, optimizing the flight control strategy of the UAV, and facilitating the stable and safe flight of the UAV.

[0128] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for risk assessment and quality monitoring of unmanned aerial vehicle flight, characterized in that: include: Step 1: Obtain the flight environment data, flight mission data and flight status data of the UAV flight, and conduct a risk assessment on the UAV flight; Step 2: Obtain and process the current flight monitoring data of the UAV flight, establish a UAV flight simulation model based on the historical flight monitoring data and the preset simulation model, input the current flight monitoring data of the UAV, and determine the flight quality of the UAV flight; Step 3: Construct a comprehensive assessment model for UAV flight, conduct mutual comprehensive calibration of the risk assessment results of UAV flight and the flight quality of UAV flight, and determine the comprehensive risk assessment results and comprehensive flight quality of UAV flight, including: Construct a comprehensive assessment model for UAV flight, conduct mutual comprehensive calibration of the risk assessment results and the flight quality of UAV flight, and determine the mutual influence weights between the risk assessment results and the flight quality; The minimum risk impact weight of the flight impact data in the comprehensive assessment model of the UAV flight is set. When the risk impact weight of the current flight risk impact data of the monitored UAV flight on the current flight monitoring data is not higher than the minimum risk impact weight, the current flight risk impact data is removed; Perform comprehensive quality screening on the current flight risk impact data that has been eliminated based on the quality impact weight of flight quality on risk assessment results; When the quality-weighted risk impact weight of the current flight risk impact data after the data elimination process is weighted by the quality impact weight is not higher than the minimum risk impact weight, a secondary data elimination process is performed to determine the comprehensive risk impact data after the comprehensive calibration process, and a comprehensive risk assessment is performed; Fix the comprehensive risk impact data completed by the comprehensive calibration process, construct secondary indicators for the flight quality evaluation index of the flight quality based on the risk impact weight of the flight quality in combination with the risk assessment result, determine the comprehensive flight quality evaluation index completed by the comprehensive verification process, and conduct a comprehensive flight quality evaluation; The comprehensive quantitative value of UAV flight is calculated based on the comprehensive risk assessment results and the comprehensive flight quality assessment results; ;in, Indicates the comprehensive quantitative value of drone flight; Indicates the influence weight of comprehensive risk impact data of UAV flight environment on comprehensive risk assessment results; Indicates the weight of the comprehensive risk impact data of the UAV flight mission on the comprehensive risk assessment results; Indicates the influence weight of the comprehensive risk impact data of the UAV flight status on the comprehensive risk assessment results; Indicates that there is no drone flight The probability that a comprehensive risk will affect the data; Indicates the first Comprehensive risk impact data; Indicates the first The comprehensive value of the comprehensive flight quality evaluation indicators; Indicates the first The preset values ​​of the preset flight quality evaluation indicators; Indicates the quality impact weight of flight quality on risk assessment results; Indicates the risk impact weight of risk assessment results on flight quality; Indicates the number of comprehensive risk impact data; Indicates the number of comprehensive flight quality evaluation indicators; Step 4: Construct a flight sequence for the UAV, compare and analyze the comprehensive risk assessment results and the comprehensive flight quality, and optimize the flight control strategy of the UAV.

2. A method for risk assessment and quality monitoring of unmanned aerial vehicle flight according to claim 1, characterized in that: Obtain the flight environment data, flight mission data and flight status data of the UAV flight, and conduct risk assessment on the UAV flight, including: Obtain the current flight environment data, current flight mission data and current flight status data of the UAV flight and perform data preprocessing; Perform data integration processing on the current flight environment data, current flight mission data and current flight status data of the UAV flight that have completed data preprocessing to construct a flight data set; The flight risk impact data of UAV flight is determined based on the historical flight data of UAV flight, a UAV flight risk assessment model is constructed, and the current flight risk impact data of the flight data set is input to conduct a risk assessment on UAV flight.

3. A method for risk assessment and quality monitoring of unmanned aerial vehicle flight according to claim 2, characterized in that: Based on the historical flight data of drone flights, the flight risk impact data of drone flights is determined, and a drone flight risk assessment model is constructed, including: Obtain historical flight data of UAV flights, conduct risk assessments based on flight data types, and determine flight risk impact data, where the flight data types include: flight environment data types, flight mission data types, and flight status data types; Based on the historical flight data of UAV flights and the flight risk impact data, comprehensive learning is carried out to determine the impact weight of the flight risk impact data on the risk assessment results, and a UAV flight risk assessment model is constructed.

4. The method for risk assessment and quality monitoring of unmanned aerial vehicle flight according to claim 1, characterized in that: Acquire and process current flight monitoring data of UAV flights, including: Obtain the current flight monitoring data of the UAV flight, perform data noise reduction processing, and upload it to the flight monitoring platform in real time, where the current flight monitoring data includes: current flight environment monitoring data, current flight mission monitoring data, and current flight status monitoring data; Conduct data consistency checks on the current flight monitoring data uploaded in real time and perform data conversion processing according to the preset data format of the flight monitoring platform; When the data conversion process is completed, the flight monitoring platform receives the current flight monitoring data of the UAV flight.

5. The method for risk assessment and quality monitoring of unmanned aerial vehicle flight according to claim 1, characterized in that: A UAV flight simulation model is established based on historical flight monitoring data and preset simulation models, and the current flight monitoring data of the UAV is input to determine the flight quality of the UAV flight, including: Obtain historical flight monitoring data of the UAV and establish a UAV flight simulation model based on the preset simulation model; Calibrate the model parameters of the UAV flight simulation model according to the historical flight monitoring data of the UAV; Compare the current flight monitoring data of the UAV with the historical flight monitoring data of the UAV. If the current flight monitoring data contains data variables of data types inconsistent with the historical flight monitoring data, extract the data variables and perform a secondary model parameter calibration on the UAV flight simulation model that has completed the primary model parameter calibration process. The preset flight quality evaluation index of the UAV flight is obtained, and the current flight monitoring data of the UAV is input into the UAV flight simulation model after the model parameter calibration process is completed to determine the flight quality of the UAV.

6. The method for risk assessment and quality monitoring of unmanned aerial vehicle flight according to claim 1, characterized in that: Also includes: Generate UAV flight report data or UAV flight alarm data according to the comprehensive quantitative value of the UAV flight; The adjustment period of the UAV's flight control strategy is set. When the UAV flight report data or the UAV flight alarm data is monitored, if no manual adjustment of the flight control strategy occurs within the corresponding adjustment period, the flight control strategy is automatically adjusted.

7. The method for risk assessment and quality monitoring of unmanned aerial vehicle flight according to claim 1, characterized in that: Construct the flight sequence of the UAV, compare and analyze the comprehensive risk assessment results and the comprehensive flight quality, and optimize the flight control strategy of the UAV, including: Construct the flight sequence of the UAV and divide the flight path of the UAV into sequences, wherein the flight sequence of the UAV includes: flight time sequence and flight space sequence; According to the sequence division results, the comprehensive risk assessment results and the comprehensive flight quality are compared horizontally and vertically in the flight sequence; Determine the flight optimization target of the UAV flight according to the comparison results of the current flight sequence, and optimize the flight control strategy of the UAV; The flight control strategy optimized by the strategy is applied in the next flight sequence, and the flight control strategy optimized by the strategy is optimized and verified according to the comparison result of the next flight sequence. If the optimization verification fails, a secondary strategy optimization and secondary optimization verification are performed.

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