A method for detecting integrity of transmission data in a flight process of a UAV

Abstract

The present application relates to the technical field of connector data transmission, and particularly relates to a transmission data integrity detection method in the flight process of a UAV. The method acquires state data of a connector in the flight process of a UAV, and real-time transmission state data of a link layer and an application layer in a data transmission process; based on the state data, determines an environmental influence factor of the connector; analyzes the change of the environmental influence factor to determine a deterioration trend coefficient; combines the real-time transmission state data to determine a real-time data transmission state coefficient; weights the real-time data transmission state coefficient through the deterioration trend coefficient to obtain a data transmission loss degree; and according to the data transmission loss degree and a data cumulative loss amount, obtains a transmission integrity evaluation index of the connector. The present application improves the timeliness of abnormal positioning and repair in the data transmission process, and reduces the transmission loss rate of UAV data.

Description

Technical Field

[0001] This invention relates to the field of connector data transmission technology, and more specifically to a method for detecting the integrity of transmitted data during the flight of a drone. Background Technology

[0002] When drones transmit images and videos during flight, the integrity of the transmission is affected by various factors. For example, vibrations, electromagnetic interference, and other factors can directly impact image transmission quality, leading to blurry images, delays, frame drops, or even complete disconnection, thus reducing data transmission stability and integrity. Furthermore, since connectors are a critical physical interface for data transmission, connecting different subsystems to ensure seamless and reliable data transmission between modules, poor contact in connectors can also cause unstable or lost image, video, or other data transmission.

[0003] Currently, in the process of detecting the integrity of transmitted data based on UAV connectors, the data transmission integrity is generally determined by the data anomaly verification method generated by the data link layer. However, when UAVs fly in certain harsh environments, the contact performance of the physical layer connector and transmission equipment may be abnormal, making it difficult to provide timely feedback. This can lead to errors in the data transmission process, which sometimes cannot be detected by the link layer verification method, resulting in discrepancies between the UAV data transmission integrity assessment results and the actual situation. Summary of the Invention

[0004] To address the technical problem of discrepancies between the obtained data transmission integrity assessment results and the actual data transmission integrity, the present invention aims to provide a method for detecting the transmission integrity of UAV data during flight. The specific technical solution adopted is as follows:

[0005] In a first aspect, embodiments of the present invention provide a method for detecting the integrity of transmitted data during the flight of an unmanned aerial vehicle (UAV), the method comprising:

[0006] The system acquires connector status data during UAV flight and real-time transmission status data of the link layer and application layer during data transmission. The status data includes vibration amplitude, contact resistance, and vibration acceleration. The real-time transmission status data includes data packet timestamps and bit error rate.

[0007] Based on the status data, the environmental impact factors of the connector are determined; the changes in the environmental impact factors are analyzed to determine the degradation trend coefficient; the real-time data transmission status coefficient is determined by combining the real-time transmission status data; and the data transmission loss is obtained by weighting the real-time data transmission status coefficient using the degradation trend coefficient.

[0008] Based on the data transmission loss and the cumulative data loss, the transmission integrity evaluation index of the connector is obtained.

[0009] Further, determining the environmental impact factors of the connector based on the state data includes:

[0010] By comparing the real-time vibration intensity of the connector during UAV flight with the fixed vibration amplitude caused by rotor rotation during stable UAV flight, the vibration anomaly factor of the connector is determined.

[0011] By combining the vibration anomaly factor and the vibration acceleration, the vibration characterization value of the connector is determined;

[0012] Based on the vibration characterization values ​​and the contact resistance, the environmental impact factor of the connector is determined.

[0013] Further, determining the environmental impact factor of the connector based on the vibration characterization value and the contact resistance includes:

[0014] By comparing the real-time resistance of the connector with the rated contact resistance of the connector during the drone's flight, the resistance anomaly factor can be determined.

[0015] By combining the vibration characterization values ​​and the resistance anomaly factor, the environmental impact factor of the connector is determined.

[0016] Further, determining the vibration characterization value of the connector by combining the vibration anomaly factor and the vibration acceleration includes:

[0017] Calculate the product of the vibration anomaly factor and the vibration acceleration as the vibration characterization value of the connector.

[0018] Furthermore, the analysis of changes in the environmental impact factors to determine the degradation trend coefficient includes:

[0019] For all sampling times, the mean change of environmental impact factors at each two adjacent sampling times is calculated as the degradation trend coefficient.

[0020] Furthermore, determining the real-time data transmission status coefficient by combining the real-time transmission status data includes:

[0021] Compare the timestamp difference between the currently received data packet and the previous data packet with the preset timestamp difference to determine the time state coefficient;

[0022] By combining the time state coefficient and the bit error rate during transmission, the real-time data transmission state coefficient is obtained.

[0023] Further, the step of comparing the timestamp difference between the currently received data packet and the previous data packet with a preset timestamp difference to determine the time state coefficient includes:

[0024] Calculate the ratio of the difference between the timestamp of the data packet received at the current moment and the timestamp of the previous data packet to the preset timestamp difference, and use the difference between the ratio and the preset constant as the time state coefficient.

[0025] Furthermore, the step of weighting the real-time data transmission state coefficients using a degradation trend coefficient to obtain the data transmission loss includes:

[0026] The adjustment state coefficient is obtained by weighting the real-time data transmission state coefficient with the degradation trend coefficient as the weight.

[0027] The sum of the adjustment state coefficient and the real-time data transmission state coefficient is used as the data transmission loss.

[0028] Furthermore, the step of obtaining the transmission integrity evaluation index based on the data transmission loss and the cumulative data loss includes:

[0029] For the current transmission cycle, calculate the difference in data transmission loss between adjacent sampling times within the transmission cycle, and use it as the transmission loss at a single moment.

[0030] The sum of the single-time transmission losses at all adjacent sampling times within the transmission period is multiplied by the cumulative data loss, and this product is used as the transmission integrity evaluation index.

[0031] Furthermore, the cumulative data loss is the difference in the total number of bytes of data before transmission and after reception corresponding to the transmission cycle.

[0032] Secondly, a data integrity detection system for unmanned aerial vehicles (UAVs) during flight is provided, the system comprising the following modules:

[0033] The data acquisition module is used to acquire the connector status data during UAV flight and the real-time transmission status data of the link layer and application layer during data transmission; wherein, the status data includes: vibration amplitude, contact resistance, and vibration acceleration; the real-time transmission status data includes: data packet timestamp and bit error rate;

[0034] The data transmission analysis module is used to determine the environmental impact factors of the connector based on the status data; analyze the changes in the environmental impact factors to determine the degradation trend coefficient; combine the real-time transmission status data to determine the real-time data transmission status coefficient; and weight the real-time data transmission status coefficient using the degradation trend coefficient to obtain the data transmission loss degree.

[0035] The transmission evaluation module is used to obtain a transmission integrity evaluation index based on the data transmission loss and the cumulative data loss.

[0036] Thirdly, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores executable code, and when the processor executes the executable code, it implements the various possible implementations of the first aspect.

[0037] Fourthly, embodiments of the present invention provide a computer program product comprising: computer program code, which, when executed on a computer, causes the computer to perform the method described in the first aspect or any possible implementation thereof.

[0038] Fifthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the various possible implementations of the first aspect.

[0039] The embodiments of the present invention have at least the following beneficial effects:

[0040] This invention optimizes the problem of delayed abnormal connector detection due to the lack of real-time diagnostic feedback mechanisms in connectors. It determines the real-time environmental impact factor of the connector based on the real-time vibration impact and electrical characteristics during data transmission. Then, it determines the data transmission loss degree based on the relationship between the connector's real-time degradation state and the data integrity of different data transmission layers. Finally, it performs data transmission integrity detection by combining the data transmission loss degree and the cumulative data volume. This improves the timeliness of anomaly location and repair during data transmission and reduces the data transmission loss rate of UAVs. Attached Figure Description

[0041] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 A flowchart illustrating a method for detecting the integrity of transmitted data during the flight of an unmanned aerial vehicle (UAV) according to an embodiment of the present invention;

[0043] Figure 2 A system block diagram of a data integrity detection system for unmanned aerial vehicle (UAV) transmission during flight, provided as an embodiment of the present invention;

[0044] Figure 3 This is a schematic diagram of the structure of a computer device provided in one embodiment of the present invention. Detailed Implementation

[0045] To further illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the following detailed description, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a method for detecting the integrity of transmitted data during the flight of an unmanned aerial vehicle (UAV) according to the present invention.

[0046] In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments may be combined in any suitable form.

[0047] In the description of the embodiments of the present invention, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of the present invention, "multiple" means two or more.

[0048] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0050] The embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art will recognize that, with technological advancements and the emergence of new scenarios, the technical solutions provided by the embodiments of the present invention are equally applicable to similar technical problems.

[0051] The following description, in conjunction with the accompanying drawings, details a specific scheme for a method for detecting the integrity of transmitted data during the flight of an unmanned aerial vehicle (UAV).

[0052] Please see Figure 1 The diagram illustrates a flowchart of a method for detecting the integrity of transmitted data during the flight of a drone, according to an embodiment of the present invention. The method includes the following steps:

[0053] Step S100: Acquire the connector status data during UAV flight and the real-time transmission status data of the link layer and application layer during data transmission; wherein, the status data includes: vibration amplitude, contact resistance and vibration acceleration; the real-time transmission status data includes: data packet timestamp and bit error rate.

[0054] Drones transmit various signals, including control signals, sensor data, and video signals, via connectors. The quality of these connectors directly affects the stability and reliability of these signal transmissions. For example, the connector between the controller and sensors is responsible for transmitting commands and data. If the connector has poor contact or is worn out, it may lead to signal loss or data transmission errors, thus affecting the drone's mission execution and data transmission.

[0055] Because connectors lack a real-time diagnostic feedback mechanism and cannot proactively report connection status or transmission anomalies, the system's response and recovery to abnormal transmissions are delayed. Therefore, this invention addresses this by installing an integrated sensor at the connector connection point responsible for data transmission and introducing a bypass test channel, independent of the main data transmission channel. This method allows for real-time acquisition and transmission of the connector's operating status and electrical characteristic data (contact resistance, voltage, vibration amplitude, etc., with a sampling interval of 0.1ms), thereby helping to monitor whether the connector is functioning correctly and whether any abnormalities occur during data transmission, avoiding delayed anomaly feedback.

[0056] The vibration amplitude, contact resistance, and vibration acceleration of the connector during the drone's flight are collectively referred to as state data.

[0057] Meanwhile, since data transmission requires the coordination of multiple layers, any abnormality at any layer will lead to a reduction in data transmission integrity. However, the connector only represents the transmission status of the physical layer. Therefore, in order to more accurately detect abnormal states of the connector during transmission, this embodiment of the invention also needs to obtain real-time transmission status data (data packet timestamp, bit error rate, hash value, etc.) at the link layer and application layer through the system's data detection module. This allows for the detection and early warning of the transmission status of multiple connectors by combining the real-time correlation between the physical layer and other layers of data transmission.

[0058] Data packet timestamps and bit error rates are collectively referred to as time-transmission status data.

[0059] Step S200: Based on the status data, determine the environmental impact factor of the connector; analyze the changes in the environmental impact factor to determine the degradation trend coefficient; combine the real-time transmission status data to determine the real-time data transmission status coefficient; and use the degradation trend coefficient to weight the real-time data transmission status coefficient to obtain the data transmission loss.

[0060] Since abnormal contact performance between the physical layer connectors and transmission devices is difficult to report in a timely manner, this study first analyzes the environmental impact on the connectors based on real-time status data during data transmission to determine their degradation state and obtain a degradation trend coefficient. Then, by analyzing the relationship between the real-time degradation trend coefficient of the connectors and the data integrity of different data transmission layers, data transmission integrity is detected. Finally, a data transmission load coordination mechanism is established based on the real-time degradation status of multiple connectors.

[0061] Drone connectors play a crucial bridging and safeguarding role in data transmission. Data can be seamlessly transmitted between various modules via connectors. However, drones may encounter various harsh environments during flight, including diverse interferences and vibrations. Over time, the contact performance of the connectors may deteriorate, affecting the integrity of data transmission. To improve the timeliness of anomaly detection, this step analyzes the real-time environmental parameters of the drone connectors.

[0062] During missions, drones may operate in harsh weather conditions. In such conditions, the contact springs in the connectors may experience fatigue cracking or reduced elasticity due to sudden increases in vibration, leading to poor contact. Therefore, the real-time vibration characteristics during flight can affect the contact performance of the connectors, thereby reducing data transmission integrity.

[0063] Therefore, in this embodiment of the invention, the real-time vibration intensity of the connector during the flight of the UAV is first compared with the fixed vibration amplitude caused by the rotation of the rotor when the UAV is flying smoothly, so as to determine the vibration anomaly factor of the connector; and the vibration characterization value of the connector is determined by combining the vibration anomaly factor and the vibration acceleration.

[0064] In some embodiments, the vibration anomaly factor is obtained by calculating the ratio of the real-time vibration intensity to the fixed vibration amplitude caused by the rotor rotation during the smooth flight of the UAV, and using this ratio as the vibration anomaly factor of the connector.

[0065] In some embodiments, the vibration characterization value of the connector is obtained by calculating the product of the vibration anomaly factor and the vibration acceleration as the vibration characterization value of the connector.

[0066] Taking the i-th sampling time as an example, the vibration characterization value corresponding to the i-th sampling time The calculation formula is: Among them, for The real-time vibration amplitude at the connector position at the i-th sampling time; The fixed amplitude generated by the rotor rotation during drone flight; Let be the vibration acceleration at the connector at the i-th sampling moment; Let be the vibration anomaly factor at the i-th sampling time.

[0067] in, The value of represents the real-time amplitude rise; the larger the value, the more intense the real-time vibration of the drone connector. The rate of change of vibration velocity reflects the frequency of vibration. Therefore, the greater the intensity and frequency of real-time vibration, the greater the corresponding real-time vibration strength.

[0068] Vibration can damage the contact surfaces of connectors (such as the contact points of pins and sockets), especially under high-frequency or high-intensity vibration. Damaged contact surfaces can increase contact resistance, leading to signal attenuation and impaired current flow. Therefore, when determining the real-time flight environment of a drone connector, it is necessary to combine the changes in the real-time electrical characteristics of the connector caused by vibration for accurate evaluation.

[0069] Therefore, for any sampling moment during data transmission, the environmental impact factor of the connector can be determined based on the vibration characterization value and the contact resistance. Specifically, the real-time resistance of the connector during UAV flight is compared with the rated contact resistance of the connector to determine the resistance anomaly factor; and the environmental impact factor of the connector is determined by combining the vibration characterization value and the resistance anomaly factor.

[0070] In some embodiments, the environmental impact factor at the i-th sampling time The calculation formula is: ;in, Let be the average contact resistance of all pins of the connector at the i-th sampling time. This is the rated contact resistance of the connector; Let be the real-time vibration intensity of the connector at the i-th sampling time.

[0071] in, This characterizes the instability of the connector's contact resistance. The larger the value, the greater the deviation of the contact resistance from the rated value, indicating a worse contact performance of the connector. Simultaneously, combining the instability of the contact resistance and the real-time vibration intensity, an environmental impact factor was obtained. A larger environmental impact factor indicates a greater degree of environmental influence on the connector's contact performance at that moment, resulting in poorer real-time contact performance.

[0072] The above method is used to evaluate the real-time contact performance of the connector and obtain the environmental impact factor of the connector. Subsequently, the contact performance is detected and early warning is given based on the relationship between the real-time degradation state of the connector and the data integrity of different data transmission layers.

[0073] Since data transmission requires coordination across multiple transport layers, and connectors only represent the data transmission status of the physical layer, any abnormalities in other layers can also affect the integrity of data transmission. Therefore, to more accurately detect the data transmission integrity of connectors, this step analyzes the real-time degradation trend of the connector and its relationship with the data integrity of different data transmission layers for a fusion assessment.

[0074] The harsh flight environment of drones can lead to degradation of the contact performance of their connectors, and contact performance determines the integrity of data transmission at the physical layer. Therefore, it is necessary to determine the real-time degradation trend of the connectors based on real-time environmental impact factors. As data is transmitted through the connectors, the real-time environmental impact factor sequence is obtained through the above steps. , The time is the current sampling time. The environmental impact factor at the first sampling time; The environmental impact factors at the second sampling time; Let be the environmental impact factor at the i-th sampling time. If the real-time environmental impact factor of the sequence shows an increasing trend in historical time points, it indicates a more significant decline in the contact performance of the connector. Therefore, for any sampling time, the changes in the environmental impact factor can be analyzed to determine the degradation trend coefficient.

[0075] Taking the i-th sampling time as an example, the degradation trend coefficient at the i-th sampling time The calculation formula is:

[0076] ;

[0077] in, Representing the The degradation trend coefficient of the connector at each sampling time; For the first Environmental impact factors of the connector at each sampling time; For the first Environmental impact factors of the connector at each sampling time.

[0078] So This average difference represents the difference in environmental parameters between any two adjacent times. The larger the value, the more pronounced the upward trend, indicating a harsher environment for the drone, a more significant impact on its contact performance, and a greater degree of degradation. Then, the real-time degradation trend coefficient is obtained and normalized to the range [0,1]. The normalized degradation trend coefficient is then updated to a new degradation trend coefficient.

[0079] This confirms the degradation of the physical layer connector itself during data transmission. However, data transmission requires coordination among the physical layer, link layer, and application layer to ensure complete transmission. The physical layer focuses on the state of the transmission medium and the physical connection, the link layer focuses on whether the data frames of the communication protocol are damaged or lost during transmission on the link, and the application layer focuses on whether the data frames are complete and ordered after being received. Any abnormal state in any layer will affect the integrity of data transmission.

[0080] In general, the link layer and application layer of data transmission are different from the physical layer and are the upper layer of transmission. Abnormal network conditions during transmission will directly affect the integrity of data transmission. Therefore, it is necessary to determine the real-time abnormal status of the upper layer of UAV transmission.

[0081] Generally, the application layer primarily performs content and sequence checks on the data received from the link layer. If the upper-layer state is abnormal during transmission, the corresponding check results will be biased. That is, if the timestamp of the data frame received at the sampling time exceeds a preset range, and the real-time bit error rate of the link layer is higher, it indicates that the upper-layer transmission network is unstable at that time, and the corresponding real-time data transmission status is worse. In this embodiment of the invention, transmission delay is ignored. Therefore, for data packets received at any sampling time of the application layer, a real-time data transmission status coefficient can be determined by combining it with real-time transmission status data.

[0082] First, compare the difference between the timestamp of the data packet received at the current moment and the timestamp of the previous data packet with the preset timestamp difference to determine the time state coefficient. Specifically, calculate the ratio of the difference between the timestamp of the data packet received at the current moment and the timestamp of the previous data packet to the preset timestamp difference, and use the difference between the ratio and the preset constant as the time state coefficient.

[0083] By combining the time state coefficient and the bit error rate during transmission, the real-time data transmission state coefficient is obtained. ;

[0084] in, Let be the real-time data transmission state coefficient at the i-th sampling time. For the first The difference in timestamp between the data packet received at each sampling moment and the previous data packet. This is to account for the difference in preset timestamps. This represents the real-time bit error rate during transmission.

[0085] The bit error rate represents the accuracy of the data packet content at a given moment. The higher the value, the greater the difference between the data content and the original data, and the worse the data integrity. This represents the sequential consistency of data transmission. A larger value indicates that the timestamp difference of the data frames at that moment exceeds expectations, suggesting packet loss and poorer data transmission stability. In this embodiment of the invention, the preset timestamp difference is set based on the average timestamp difference between adjacent data packets received during normal data transmission.

[0086] Regarding data transmission, environmental factors can lead to contact degradation at the physical layer, further impacting data transmission integrity. Even if the upper layer transmission is normal, incomplete data may still be received. Therefore, to more accurately evaluate data transmission integrity, a weighted comprehensive assessment is performed using the connector degradation trend coefficient as the weight, combined with the real-time data transmission status coefficient, to obtain the data transmission loss.

[0087] Specifically: The real-time data transmission state coefficient is weighted using the degradation trend coefficient as the weight to obtain the adjustment state coefficient; the sum of the adjustment state coefficient and the real-time data transmission state coefficient is used as the data transmission loss.

[0088] Taking the i-th sampling time as an example, the data transmission loss at the i-th sampling time The calculation formula is: ;

[0089] in, Let be the data transmission loss at the i-th sampling time. Let be the degradation trend coefficient of the connector at the i-th sampling time. Let be the real-time data transmission status coefficient at the i-th sampling time. Then, the larger the real-time degradation trend coefficient of the connector, the greater the decrease in data transmission integrity. Combined with the real-time data transmission status coefficient... In other words, the greater the decline in data transmission integrity and the worse the transmission status, the greater the loss of data during transmission.

[0090] Step S300: Based on the data transmission loss and the cumulative data loss, obtain the transmission integrity evaluation index.

[0091] Within any transmission cycle of the drone connector, since the drone's data transmission is in units of data frames, the transmission process involves the passage of massive amounts of data frames. Therefore, if the real-time data loss fluctuation of the periodically transmitted data frames is greater and the cumulative loss is greater, it indicates that the data transmission integrity of this connector is worse.

[0092] Therefore, the transmission integrity of the connector can be evaluated by combining the data transmission loss and the cumulative data loss, so as to obtain the transmission integrity evaluation index of the connector.

[0093] For the current transmission cycle, calculate the difference in data transmission loss between adjacent sampling times within the transmission cycle, and use it as the transmission loss at a single moment.

[0094] The sum of the single-time transmission losses at all adjacent sampling moments within the transmission period is multiplied by the cumulative data loss, and this product is used as the transmission integrity evaluation index. The cumulative data loss is the difference in the total number of bytes of data before transmission and after reception within the corresponding transmission period.

[0095] In some embodiments, for a connector, the formula for calculating the transmission integrity evaluation index G of its data frames is: ; ;

[0096] in, and These represent the total number of bytes of data before transmission and after reception, respectively, corresponding to the transmission cycle. This represents the cumulative amount of data loss. The transmission loss of the data frame corresponding to the (i+1)th sampling time during transmission; Let $\frac{i}{i}$ be the transmission loss of the data frame corresponding to the $i$-th sampling time during transmission. This represents the number of data frames in the current transmission cycle, which is also the number of sampling moments in the current transmission cycle.

[0097] So This represents the fluctuation of real-time data loss during transmission. Generally, the real-time loss is minimal and stable when data is transmitted completely. Therefore, a larger value indicates a more unstable transmission process. This is also considered in conjunction with the cumulative data loss. ,Right now The larger the connector, the greater its impact on data transmission integrity, and the greater the degree of data integrity degradation.

[0098] Thus, the real-time data transmission integrity evaluation of the connector has been obtained through steps S100 to S300. If this indicator of the data frame fluctuates during transmission, it indicates increased data transmission jitter, which corresponds to an increase in the contact resistance of the connector and a deterioration in the contact performance of the connector.

[0099] Since drone data transmission involves multiple connectors of different types, the above method is used to check the data transmission integrity of all connectors. If a transmission anomaly occurs, the transmission load coordination mechanism can be activated to ensure data transmission during the fault. Relevant personnel can promptly locate the fault source and repair it based on the early warning results. At the same time, connector manufacturers can optimize their designs based on the statistical results of connectors with abnormal contact performance (gold-plated contacts, dual-path connections, rubber pads, plug locking, etc.) to ensure complete and stable data transmission.

[0100] Please see Figure 2 , Figure 2 This invention provides a system module diagram of a data integrity detection system for unmanned aerial vehicles (UAVs) during flight. The system includes:

[0101] The data acquisition module is used to acquire the connector status data during UAV flight and the real-time transmission status data of the link layer and application layer during data transmission; wherein, the status data includes: vibration amplitude, contact resistance, and vibration acceleration; the real-time transmission status data includes: data packet timestamp and bit error rate;

[0102] The data transmission analysis module is used to determine the environmental impact factors of the connector based on the status data; analyze the changes in the environmental impact factors to determine the degradation trend coefficient; combine the real-time transmission status data to determine the real-time data transmission status coefficient; and weight the real-time data transmission status coefficient using the degradation trend coefficient to obtain the data transmission loss degree.

[0103] The transmission evaluation module is used to obtain a transmission integrity evaluation index based on the data transmission loss and the cumulative data loss.

[0104] Alternatively, the transmission medium may be a wired link, such as, but not limited to, coaxial cable, fiber optic cable and digital subscriber line, or a wireless link, such as, but not limited to, wireless Fidelity (WIFI), Bluetooth and mobile device networks.

[0105] It should be noted that the device provided in the above embodiments is only an example of the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device can be divided into different functional modules to complete all or part of the functions described above.

[0106] Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. For example, as shown... Figure 3 As shown, the computer device 400 includes: a memory 410, a processor 420, and a computer program 430 stored in the memory 410 and running on the processor 420. When the processor 420 executes the computer program 430, the computer device can execute any of the aforementioned methods for detecting the integrity of transmitted data during UAV flight.

[0107] Furthermore, embodiments of the present invention also protect an apparatus that may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to perform a method for detecting the integrity of transmitted data during the flight of a UAV provided in embodiments of the present invention.

[0108] In this embodiment of the invention, the device can be divided into functional modules according to the above method example. For example, each module can correspond to a separate function, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and is only a logical functional division. In actual implementation, there may be other division methods.

[0109] When each module is divided according to its function, the device may also include a signal uploading module, a determination module, and an adjustment module. It should be noted that all relevant content of each step involved in the above method embodiments can be referenced from the functional descriptions of the corresponding functional modules, and will not be repeated here.

[0110] It should be understood that the apparatus provided in this embodiment of the invention is used to perform the above-described method for detecting the integrity of transmitted data during the flight of a UAV, and therefore can achieve the same effect as the above-described implementation method.

[0111] When using integrated units, the device may include a processing module and a storage module. When applied to a device, the processing module can be used to control and manage the device's operations. The storage module can be used to support the device in executing program code, etc. The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits as described in this disclosure. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of Digital Signal Processing (DSP) and a microprocessor, etc., and the storage module may be a memory.

[0112] In addition, the device provided in the embodiments of the present invention may specifically be a chip, component or module. The chip may include a connected processor and a memory. The memory is used to store instructions. When the processor calls and executes the instructions, the chip can execute the data integrity detection method for transmission during the flight of a UAV provided in the above embodiments.

[0113] This invention also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the aforementioned method steps to implement the data integrity detection method for unmanned aerial vehicle (UAV) transmission during flight provided in the above embodiments.

[0114] This invention also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned steps to implement the data integrity detection method for unmanned aerial vehicle (UAV) transmission during flight provided in the above embodiments.

[0115] In this invention, the apparatus, computer-readable storage medium, computer program product, or chip provided in the embodiments are all used to execute the corresponding methods described above. Therefore, the beneficial effects they achieve can be referred to the beneficial effects in the corresponding methods described above, and will not be repeated here. Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In the embodiments provided by this invention, it should be understood that the disclosed apparatus and method can be implemented in other ways.

[0116] The device embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0117] It should also be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0118] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0119] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0120] The above content is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the protection scope of the present invention.

Claims

1. A method for detecting the integrity of transmitted data during the flight of an unmanned aerial vehicle (UAV), characterized in that, The method includes the following steps: The system acquires connector status data during UAV flight and real-time transmission status data of the link layer and application layer during data transmission. The status data includes vibration amplitude, contact resistance, and vibration acceleration. The real-time transmission status data includes data packet timestamps and bit error rate. Based on the status data, the environmental impact factors of the connector are determined; the changes in the environmental impact factors are analyzed to determine the degradation trend coefficient; the real-time data transmission status coefficient is determined by combining the real-time transmission status data; and the data transmission loss is obtained by weighting the real-time data transmission status coefficient using the degradation trend coefficient. Based on the data transmission loss and the cumulative data loss, the transmission integrity evaluation index of the connector is obtained; The method for obtaining the environmental impact factor is as follows: calculate the ratio of the real-time vibration intensity to the fixed vibration amplitude caused by the rotor rotation during the stable flight of the UAV, and use it as the vibration anomaly factor of the connector; calculate the product of the vibration anomaly factor and the vibration acceleration, and use it as the vibration characterization value of the connector; compare the real-time resistance of the connector with the rated contact resistance of the connector during the flight of the UAV to determine the resistance anomaly factor; combine the vibration characterization value and the resistance anomaly factor to determine the environmental impact factor of the connector. The degradation trend coefficient is obtained by calculating the average change of environmental impact factors between any two adjacent sampling times for all sampling times, and using this as the degradation trend coefficient. The method for obtaining the real-time data transmission status coefficient is as follows: calculate the ratio of the difference between the timestamp of the data packet received at the current moment and the timestamp of the previous data packet to the difference between the preset timestamp, and use the difference between the ratio and the preset constant as the time status coefficient; combine the time status coefficient and the bit error rate in the transmission process to obtain the real-time data transmission status coefficient.

2. The method for detecting the integrity of transmitted data during UAV flight as described in claim 1, characterized in that, The process of weighting the real-time data transmission state coefficients using a degradation trend coefficient to obtain the data transmission loss includes: The adjustment state coefficient is obtained by weighting the real-time data transmission state coefficient with the degradation trend coefficient as the weight. The sum of the adjustment state coefficient and the real-time data transmission state coefficient is used as the data transmission loss.

3. The method for detecting the integrity of transmitted data during UAV flight according to claim 1, characterized in that, The process of obtaining transmission integrity evaluation indicators based on the data transmission loss and cumulative data loss includes: For the current transmission cycle, calculate the difference in data transmission loss between adjacent sampling times within the transmission cycle, and use it as the transmission loss at a single moment. The sum of the single-time transmission losses at all adjacent sampling times within the transmission period is multiplied by the cumulative data loss, and this product is used as the transmission integrity evaluation index.

4. The method for detecting the integrity of transmitted data during UAV flight according to claim 1, characterized in that, The cumulative data loss is the difference in the total number of bytes of data before transmission and after reception corresponding to the transmission cycle.

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