A data analysis-based comprehensive detection system for unmanned aerial vehicle performance

Abstract

The application discloses a kind of based on data analysis's unmanned aerial vehicle operating performance comprehensive detection system, it is related to unmanned aerial vehicle performance detection technical field, solve the existing technology, power test cannot be combined with endurance analysis to build corresponding curve, cannot be carried out multi-type performance detection by curve The technical problem is, specifically virtual simulation module and physical measurement module, virtual simulation module and physical measurement module are used for the data detection analysis of the body performance of unmanned aerial vehicle, whether the inference unmanned aircraft associated components linkage is normal, determine that after cooperation linkage is qualified, physical measurement module carries out work should be measured operation to associated components;Power test analysis module and endurance synchronous analysis module, power test analysis module and endurance synchronous analysis module are compared and analyzed when data intercommunication is interchanged synchronously, whether the dynamic performance of current unmanned aerial vehicle meets actual demand by power test inference.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) performance testing technology, specifically to a comprehensive UAV operational performance testing system based on data analysis. Background Technology

[0002] The UAV Operation Performance Comprehensive Testing System is an intelligent system that integrates multi-dimensional technologies to comprehensively evaluate core indicators of UAVs such as flight stability, power system, navigation accuracy, and environmental adaptability.

[0003] However, in existing technologies, it is impossible to combine virtual simulation technology with physical measurement technology during drone operation. It is also impossible to infer the linkage efficiency of various components within the drone based on data analysis, which leads to a decrease in the accuracy of subsequent power tests. In addition, it is impossible to combine endurance analysis to construct corresponding curves during power tests, and it is impossible to perform multi-type performance tests through curves, which reduces the comprehensiveness of operational performance testing.

[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to solve the problems mentioned above by proposing a comprehensive detection system for the operational performance of unmanned aerial vehicles based on data analysis.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A comprehensive performance testing system for unmanned aerial vehicles (UAVs) based on data analysis includes a comprehensive testing platform. The comprehensive testing platform is communicatively connected to a data aggregation center, which includes:

[0008] The virtual simulation module and the physical measurement module are used to perform data detection and analysis on the airframe performance of the UAV, infer whether the linkage of the UAV's related components is normal, and after confirming that the linkage is qualified, the physical measurement module supplies the related components for actual test operation.

[0009] The power test analysis module and the endurance synchronization analysis module run synchronously to exchange and compare data, and infer whether the dynamic performance of the current drone meets the actual requirements through power test.

[0010] In a preferred embodiment of the present invention, the virtual simulation module operates as follows:

[0011] Based on real-time monitoring of the UAV assembly, the UAV is divided into several individual components, such as power supply, frame, propeller, etc. The correlation of each individual component is analyzed according to the operation process of each component of the UAV, and the components are divided into correlated components and non-correlated components. A virtual simulation environment is constructed, in which each individual component of the UAV is run individually. When a correlated component is running, after the individual component runs, the corresponding correlated component receives the output of the corresponding component and runs synchronously.

[0012] In a preferred embodiment of the present invention, when a single component of the UAV executes within a virtual simulation environment, the current time is marked as the start time. If the operating parameters of related components fluctuate at the start time, while the operating parameters of unrelated components do not fluctuate, it is inferred that the coordinated linkage of related components of the UAV is normal, and there is no interference in the coordinated linkage of unrelated components. The coordinated linkage of the UAV in the virtual simulation environment meets the actual requirements. If the operating parameters of related components do not fluctuate at the start time, or if the operating parameters of unrelated components fluctuate, it is inferred that the coordinated linkage of related components of the UAV is abnormal, or there is interference in the coordinated linkage of unrelated components. The coordinated linkage of the UAV in the virtual simulation environment does not meet the actual requirements, and adjustments are made based on the connection relationships of the various components of the UAV.

[0013] In a preferred embodiment of the present invention, the process of the physical measurement module is as follows:

[0014] Set the real-time operating parameters of a single component to simulate the input value range, and ensure that the simulated input value range is within the rated operating parameter range of the corresponding single component. Based on the input value of the single component, the output value is obtained, such as the power supply generating electricity. After the associated component receives the output value, the non-intersecting span between the actual output range and the rated operating range of the corresponding associated component is obtained.

[0015] If the non-intersection span exceeds the maximum value of the set non-intersection span threshold range, and the actual output range is much lower than the rated operating range, it is inferred that the operating efficiency does not meet the rated operating performance.

[0016] If the non-intersecting span of the range does not exceed the minimum value of the set non-intersecting span threshold range, and the actual output range is much higher than the rated operating range, then it is inferred that the operating load does not meet the rated operating performance.

[0017] If the non-intersecting span of the range is within the set non-intersecting span threshold range, then it is inferred that the operation is satisfied.

[0018] As a preferred embodiment of the present invention, the data interoperability comparison and analysis process is as follows:

[0019] The system sets up an operating space for the drone, and conducts operational tests within this space. The power test analysis module records the power parameters of the drone during its operation, using the drone's actual flight speed as the power performance parameter. The endurance synchronization analysis module records the endurance parameters of the drone during its operation, using the internal power level of the power supply as the endurance performance parameter. The power supply's output power is set as the horizontal axis, and the power performance parameter and endurance performance parameter are set as the left and right vertical axes, respectively. Parameters are collected during the drone's operational test, and these parameters are used to construct power performance curves and endurance performance curves in the coordinate system. Based on the wind speed values ​​at each recorded moment, the system categorizes the operation into two types: obstructed operation and assisted operation.

[0020] In a preferred embodiment of the present invention, when the power performance curve is in both the hindered operation and the assisted operation stages, the vertical fluctuation span of the power performance curve and the corresponding lateral offset span of the power performance curve within the corresponding stage are collected. It should be explained that the vertical fluctuation span and the corresponding lateral offset span of the power performance curve can be obtained by using the vertical and horizontal coordinates of the coordinate system corresponding to the curve, respectively. If either the vertical fluctuation span of the power performance curve or the corresponding lateral offset span of the power performance curve within the corresponding stage exceeds the corresponding set span threshold, it is inferred that the power test of the UAV is abnormal, and the operation of the related components involving the power supply within the UAV is monitored, and the power of the UAV is adjusted.

[0021] If neither the vertical fluctuation range of the power performance curve nor the horizontal offset range of the power performance curve within the corresponding stage exceeds the corresponding set threshold, then it is inferred that the power test of the UAV is normal.

[0022] In a preferred embodiment of the present invention, when the endurance curve is in both the hindered operation and the assisted operation stages, the deviation of the battery depletion rate corresponding to the adjacent stages is collected. At the same time, as the increase span of the corresponding battery depletion rate deviation is continuously and alternately collected for adjacent stages, if the corresponding battery depletion rate deviation of the adjacent stages exceeds the depletion rate deviation threshold, or the increase span of the battery depletion rate deviation exceeds the deviation increase span threshold, it is inferred that the endurance analysis of the drone is abnormal, and the internal power loss of the power supply and the operating consumption of related components are monitored and the power consumption is adjusted; if the corresponding battery depletion rate deviation of the adjacent stages does not exceed the depletion rate deviation threshold, and the increase span of the battery depletion rate deviation does not exceed the deviation increase span threshold, it is inferred that the endurance analysis of the drone is normal.

[0023] Compared with the prior art, the beneficial effects of the present invention are:

[0024] 1. In this invention, virtual simulation technology reduces the site and space requirements for UAV operation experiments, and can also detect the operating performance of various UAV components. At the same time, it can be compared synchronously with physical measurements to infer whether the current overall operating performance of the UAV meets the requirements, improve the efficiency of UAV testing, and ensure that the UAV operating performance test is not affected by the failure of its own components, which would reduce the accuracy of the test and affect the efficiency of UAV use.

[0025] 2. In this invention, data exchange and comparison analysis are performed during synchronous operation. Through power testing, it can be inferred whether the dynamic performance of the current UAV meets the actual requirements. It can also be combined with the actual flight endurance synchronous analysis to infer whether there are fluctuations in the real-time operating performance of the UAV under different flight states. This is to improve the overall detection efficiency of the UAV, detect the operating performance of the UAV more comprehensively, and carry out targeted rectification and maintenance for operating performance defects or abnormal fluctuations in real time. Attached Figure Description

[0026] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0027] Figure 1 This is a principle block diagram of Embodiment 1 of the present invention;

[0028] Figure 2 This is a principle block diagram of Embodiment 2 of the present invention. Detailed Implementation

[0029] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments. Example 1

[0031] Please see Figure 1As shown, a data analysis-based comprehensive testing system for the operational performance of unmanned aerial vehicles (UAVs) includes a comprehensive testing platform, which is communicatively connected to a data aggregation center and performs UAV performance testing based on data collected by the data aggregation center.

[0032] The data aggregation center includes a virtual simulation module and a physical measurement module. These modules are used to perform data detection and analysis on the airframe performance of the UAV. Virtual simulation technology reduces the site and space requirements for UAV operation experiments and can also detect the operating performance of various UAV components. At the same time, combined with physical measurement, it can be compared synchronously to infer whether the overall operating performance of the UAV meets the requirements, improve the efficiency of UAV testing, and ensure that the UAV's operating performance test is not affected by the failure of its own components, which would reduce the accuracy of the test and affect the efficiency of the UAV's use.

[0033] Based on real-time monitoring of the UAV assembly, the UAV is divided into several individual components, such as power supply, frame, propeller, etc. Correlation analysis is performed on each individual component according to the operation process of each component. That is, when the current individual component is running, if the real-time operating parameters increase, the real-time operating parameters of another individual component will also increase. The current individual component is marked as a correlated component, and vice versa. The correlated components are represented by the power supply and the propeller. The power supply provides energy, and when the real-time energy supply increases, the rotation speed of the propeller is generated and continues to increase.

[0034] A virtual simulation environment is constructed, in which each individual component of the UAV is operated individually. When related components are running, after an individual component runs, the corresponding related component receives the output of the corresponding component and runs synchronously; however, the components of the UAV do not cooperate with each other, that is, no flight test is performed.

[0035] When a single component of a UAV executes within a virtual simulation environment, and the current time is marked as the start time, if the operating parameters of related components fluctuate at the start time while the operating parameters of unrelated components do not fluctuate, it can be inferred that the related components of the UAV are cooperating normally, and the unrelated components are not interfering with each other. Therefore, the UAV's coordination and linkage in the virtual simulation environment meets the actual requirements.

[0036] If the operating parameters of the associated components do not fluctuate at the start of operation, or the operating parameters of the unassociated components fluctuate, it is inferred that the coordination and linkage of the associated components of the UAV is abnormal, or there is interference in the coordination and linkage of the unassociated components. The coordination and linkage of the UAV in the virtual simulation environment does not meet the actual requirements, and the detection and adjustment are carried out according to the connection relationship of each component of the UAV.

[0037] After confirming that the coordination and linkage are qualified, the physical measurement module performs supply test operation on the related components. At this time, the virtual simulation environment is deactivated, and the various components of the UAV operate in conjunction with each other.

[0038] The system sets the real-time operating parameters of a single component to a simulated input range, ensuring that the simulated input range is within the rated operating parameter range of the corresponding single component. Based on the input value of the single component, the output value is derived, such as the power supply generating electricity. After the associated component receives the output value, the system obtains the non-intersecting span between the actual output range and the rated operating range of the associated component. If the non-intersecting span exceeds the maximum value of the set non-intersecting span threshold range, and the actual output range is significantly lower than the rated operating range, it is inferred that the operating efficiency of the associated component driven by the single component does not meet the rated operating performance. If the non-intersecting span does not exceed the minimum value of the set non-intersecting span threshold range, and the actual output range is significantly higher than the rated operating range, it is inferred that the operating load of the associated component driven by the single component does not meet the rated operating performance.

[0039] In this application, "far below" is expressed as the current range being 0.7 times lower than another range; "far above" is expressed as the current range being 1.5 times higher than another range.

[0040] If the non-intersecting span of the range is within the set non-intersecting span threshold range, it is inferred that the operation is satisfied when the related component is driven by the operation of a single component; then the operating parameter ranges of each single component are sent together to the data aggregation center for recording and storage, and the operating parameters are compared during continuous operation of the drone, which is used as a standard for detecting fluctuations in the drone's operating performance.

[0041] After confirming that the drone's airframe performance has passed the physical performance test, the drone's dynamic performance test will be conducted.

[0042] like Figure 1 As shown, the data aggregation center also includes a power test analysis module and a flight endurance synchronization analysis module. The power test analysis module and the flight endurance synchronization analysis module are connected to each other, that is, they perform data exchange and comparison analysis when running synchronously. Through power testing, it can infer whether the dynamic performance of the current UAV meets the actual requirements. It can also combine actual flight endurance synchronization analysis to infer whether there are fluctuations in the real-time operating performance of the UAV under different flight states. This is to improve the overall detection efficiency of the UAV, detect the operating performance of the UAV more comprehensively, and carry out targeted rectification and maintenance for operating performance defects or abnormal fluctuations in real time.

[0043] The drone's operating space is set, and the drone conducts operational tests within the current operating space. The power test analysis module records the power parameters of the drone during the operation phase and sets the actual flight speed of the drone as the power performance parameter. The endurance synchronization analysis module records the endurance parameters of the drone during the operation phase and sets the internal power of the power supply as the endurance performance parameter. The power output power of the power supply is set as the horizontal axis, and the power performance parameter and the endurance performance parameter are set as the left and right vertical axes, respectively.

[0044] Parameters were collected during the drone operation test phase, and the parameters were substituted into the coordinate system to construct the power performance curve and the endurance performance curve; and based on the wind force value at each recorded moment, the operation was divided into two types: obstructed operation and assisted operation.

[0045] When the power performance curve is in both the hindered operation and the assisted operation phases, the vertical fluctuation span of the power performance curve and the corresponding horizontal offset span of the power performance curve are collected within the corresponding phase. It should be noted that the vertical fluctuation span and the corresponding horizontal offset span of the power performance curve can be obtained by using the vertical and horizontal coordinates of the coordinate system corresponding to the curve, respectively. If either the vertical fluctuation span of the power performance curve or the corresponding horizontal offset span of the power performance curve exceeds the corresponding set span threshold within the corresponding phase, it is inferred that the power test of the UAV is abnormal, and the operation of the related components involving the power supply within the UAV is monitored, and the power of the UAV is adjusted.

[0046] If neither the vertical fluctuation range of the power performance curve nor the horizontal offset range of the power performance curve within the corresponding stage exceeds the corresponding set threshold, then it is inferred that the power test of the UAV is normal.

[0047] When the endurance curve is in the two stages of hindered operation and assisted operation, the deviation of the battery depletion rate corresponding to the adjacent stage is collected. At the same time, as the battery depletion rate deviation is continuously and alternately collected in the adjacent stages, if the battery depletion rate deviation of the adjacent stages exceeds the depletion rate deviation threshold, or the increase span of the battery depletion rate deviation exceeds the deviation increase span threshold, it is inferred that the drone's endurance analysis is abnormal, and the internal power loss of the power supply and the operation consumption of related components are monitored and the power consumption is adjusted.

[0048] If the deviation of the battery depletion rate between adjacent stages does not exceed the depletion rate deviation threshold, and the increase span of the battery depletion rate deviation does not exceed the deviation increase span threshold, then it is inferred that the drone's endurance analysis is normal. Example 2

[0049] Based on the previous embodiment, when the power test analysis and endurance synchronization analysis of the UAV are normal, the data collected during the UAV operation test phase are synchronized. The power increase phase of the UAV is collected according to the power performance curve, and the increase span of the battery depletion rate corresponding to the endurance performance curve is obtained based on the power increase phase. Simultaneously, when the power increase phase ends and the power returns to the set level, the corresponding battery depletion rate is obtained from the endurance performance curve at the current stage, showing the numerical deviation between the battery depletion rate and the rate of battery depletion during the power increase phase. If the increase span of the battery depletion rate continues to increase, it is inferred that the current power supply of the UAV is incompatible. The power performance parameters, corresponding power, and battery parameters are sent to the data aggregation center, which then resets the range of the UAV's power performance parameters. If the numerical deviation of the battery depletion rate has not decreased compared to before the power increase phase, it is inferred that the UAV's endurance performance is incompatible. The endurance performance parameters and the corresponding power fluctuation phase are sent to the data aggregation center. After receiving the data, the data aggregation center performs hardware adjustments and replacements on the UAV and debugs its endurance performance. Example 3

[0050] Please see Figure 2 As shown, the data aggregation center also includes a flight process monitoring unit. Flight process monitoring is used to monitor the drone's flight in real time to infer whether there are any operational deviations in the current drone operation process, so as to perform execution detection on the drone's flight trajectory and ensure the efficiency of drone execution detection.

[0051] The drone's flight process is continuously monitored. A starting point is set, and an ending point is set according to the flight path. After determining the starting point and ending point, a preset trajectory for the current flight is set according to the flight path. Points where the preset trajectory deviates from the actual trajectory during the drone's flight are collected and marked as deviation points. The time when the deviation occurs is recorded. External interference factors corresponding to the deviation points are collected, such as airflow fluctuations or obstacles. If external interference factors exist, the distance between the deviation point and the starting point for restoring the preset trajectory is collected. If the corresponding distance exceeds the distance threshold, it is inferred that the drone's flight perception performance does not meet the current flight environment, and the drone's dynamic perception performance is adjusted, such as increasing the number of radars or expanding the radar detection range. If no external interference factors exist, it is inferred that the drone's flight memory performance is abnormal, and the linkage of each individual component of the drone is re-tested and maintained.

[0052] In use, this invention employs a virtual simulation module and a physical measurement module. These modules perform data detection and analysis on the UAV's airframe performance, inferring whether the linkage of related components is normal. Once the linkage is confirmed to be qualified, the physical measurement module conducts stress tests on the related components. Simultaneously, a power test analysis module and a range synchronization analysis module perform data exchange and comparison analysis. Through power testing, the system infers whether the current dynamic performance of the UAV meets actual requirements.

[0053] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A comprehensive performance testing system for unmanned aerial vehicles (UAVs) based on data analysis, characterized in that, This includes a comprehensive testing platform, which is connected to a data aggregation center. The data aggregation center includes: The virtual simulation module and the physical measurement module are used to perform data detection and analysis on the airframe performance of the UAV, infer whether the linkage of the UAV's related components is normal, and after confirming that the linkage is qualified, the physical measurement module supplies the related components for actual test operation. The power test analysis module and the endurance synchronization analysis module run synchronously to exchange and compare data, and infer whether the dynamic performance of the current drone meets the actual requirements through power test. The virtual simulation module process is as follows: Based on real-time monitoring of the UAV assembly, the UAV is divided into several individual components. The correlation of each individual component is analyzed according to the operation process of each component, and the components are divided into correlated components and non-correlated components. A virtual simulation environment is constructed, in which each individual component of the UAV is run individually. When a correlated component is running, after the individual component runs, the corresponding correlated component receives the output of the corresponding component and runs synchronously. When a single component of a UAV executes within a virtual simulation environment, and the current time is marked as the start time, if the operating parameters of related components fluctuate at the start time while the operating parameters of unrelated components remain unchanged, it is inferred that the coordination and linkage of related UAV components are normal, and there is no interference in the coordination and linkage of unrelated components. In this case, the coordination and linkage of the UAV in the virtual simulation environment meets the actual requirements. Conversely, if the operating parameters of related components do not fluctuate at the start time, or if the operating parameters of unrelated components fluctuate, it is inferred that the coordination and linkage of related UAV components is abnormal, or there is interference in the coordination and linkage of unrelated components. In this case, the coordination and linkage of the UAV in the virtual simulation environment does not meet the actual requirements, and adjustments are made based on the connection relationships of the various components of the UAV.

2. The comprehensive testing system for UAV operational performance based on data analysis according to claim 1, characterized in that, The process of the physical measurement module is as follows: Set the real-time operating parameters of a single component to simulate the input value range, and ensure that the simulated input value range is within the rated operating parameter range of the corresponding single component. Based on the input value of the single component, the output value is obtained, such as the power supply generating electricity. After the associated component receives the output value, the non-intersecting span between the actual output range and the rated operating range of the corresponding associated component is obtained. If the non-intersection span exceeds the maximum value of the set non-intersection span threshold range, and the actual output range is much lower than the rated operating range, it is inferred that the operating efficiency does not meet the rated operating performance. If the non-intersecting span of the range does not exceed the minimum value of the set non-intersecting span threshold range, and the actual output range is much higher than the rated operating range, then it is inferred that the operating load does not meet the rated operating performance. If the non-intersecting span of the range is within the set non-intersecting span threshold range, then it is inferred that the operation is satisfied.

3. The comprehensive performance testing system for unmanned aerial vehicles (UAVs) based on data analysis according to claim 1, characterized in that, The data exchange and comparison analysis process is as follows: The drone's operating space is set, and the drone is tested within the current operating space. The power test and analysis module records the power parameters of the drone during the operation phase and sets the actual flight speed of the drone as the power parameter. The endurance synchronization analysis module records the endurance parameters of the drone during its operation, and sets the internal power of the power supply as the endurance parameter; sets the power output power as the horizontal axis, and sets the power parameter and endurance parameter as the left and right vertical axes, respectively; it collects parameters during the drone's operation test phase, and substitutes them into the coordinate system to construct the power curve and endurance curve; and classifies the operation into two types based on the wind force value at each recorded time: obstructed operation and assisted operation.

4. The comprehensive testing system for UAV operational performance based on data analysis according to claim 3, characterized in that, When the power performance curve is in the two stages of hindered operation and assisted operation, the vertical fluctuation range of the power performance curve and the corresponding horizontal offset range of the power performance curve within the corresponding stage are collected; if either the vertical fluctuation range of the power performance curve or the corresponding horizontal offset range of the power performance curve within the corresponding stage exceeds the corresponding set span threshold, it is inferred that the power test of the UAV is abnormal, and the operation of the related components involving power supply in the UAV is monitored, and the power of the UAV is adjusted. If neither the vertical fluctuation range of the power performance curve nor the horizontal offset range of the power performance curve within the corresponding stage exceeds the corresponding set threshold, then it is inferred that the power test of the UAV is normal.

5. The comprehensive testing system for UAV operational performance based on data analysis according to claim 4, characterized in that, When the endurance curve is in both the hindered and assisted operation phases, the deviation of the battery depletion rate corresponding to the adjacent phases is collected. Simultaneously, as the deviation of the battery depletion rate corresponding to the adjacent phases is continuously and alternately collected, if the deviation of the battery depletion rate corresponding to the adjacent phases exceeds the depletion rate deviation threshold, or if the increase in the battery depletion rate deviation exceeds the deviation increase span threshold, then the drone's endurance analysis is considered abnormal. In this case, the internal power loss of the power supply and the operational consumption of related components are monitored, and the power consumption is adjusted. If the deviation of the battery depletion rate corresponding to the adjacent phases does not exceed the depletion rate deviation threshold, and the increase in the battery depletion rate deviation does not exceed the deviation increase span threshold, then the drone's endurance analysis is considered normal.

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