Fault detection system based on unmanned aerial vehicle WPT power transmission

Abstract

The invention belongs to the technical field of power fault detection, and particularly relates to an unmanned aerial vehicle WPT power transmission-based fault detection system, which comprises a power transmission module, a charging dynamic adjustment module, a charging power control and evaluation module, an energy transmission efficiency monitoring and evaluation module and a charging base station supervision center, the charging base station supervision center controls the power transmission module to which the target WPT base station belongs to start wireless charging of the unmanned aerial vehicle, the charging dynamic adjustment module monitors the charging power of the unmanned aerial vehicle in real time and adaptively adjusts the charging power of the unmanned aerial vehicle, and the charging power control and evaluation module evaluates the power control condition in the wireless charging process of the unmanned aerial vehicle. And when the power control evaluation qualified signal is generated, energy transmission efficiency abnormity capture analysis is performed, so that a supervisor can take corresponding regulation and control improvement measures in time, the electric energy loss in the wireless charging process is reduced, the charging efficiency is ensured, and the supervision and control difficulty in the unmanned aerial vehicle WPT power transmission process is remarkably reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power fault detection, and in particular to a fault detection system based on UAV WPT power transmission. Background Art

[0002] Traditional power equipment inspection relies on manual inspections or fixed sensor networks, which suffer from low efficiency, high costs, and numerous blind spots. In recent years, drone inspection technology has been gradually adopted, but its battery life is limited, requiring frequent return flights for battery replacement, making it difficult to support long-term continuous operation. Among existing technologies, wireless power transmission (WPT) has been used to charge drones.

[0003] A Chinese invention patent with publication number CN110254258A discloses a wireless charging system and method for drones. This invention uses GPS positioning information to calculate the relative position of the drone and the charging station. The drone ground station sends position adjustment and landing control signals to the drone. An ultrasonic ranging module detects the relative height of the drone and the charging station. After landing, the charging station and the drone communicate wirelessly via Bluetooth. This allows the inspection drone to autonomously navigate to a nearby charging station for wireless charging when the battery is low, improving the inspection range and efficiency of the inspection drone.

[0004] However, in actual application, the above-mentioned technical solution is difficult to effectively monitor the UAV wireless power transmission process and accurately judge the charging power control performance and energy transmission efficiency. It is also difficult to reasonably analyze and comprehensively evaluate the power transmission risks and issue timely warnings. Supervisors cannot take corresponding regulatory and improvement measures in a timely manner, which is not conducive to reducing the power loss of the wireless charging process and ensuring charging efficiency and charging safety. The supervision and control of the UAV WPT power transmission process is difficult.

[0005] In view of the above technical defects, a solution is now proposed. Summary of the Invention

[0006] The purpose of the present invention is to provide a fault detection system based on UAV WPT power transmission, which solves the problem that the existing technology is difficult to effectively monitor the UAV wireless power transmission process and accurately judge the charging power control performance and energy transmission efficiency, as well as the inability to reasonably analyze and comprehensively evaluate the power transmission risk and timely warn, which is not conducive to reducing the power loss in the wireless charging process and ensuring charging efficiency and charging safety, and the difficulty of supervising and controlling UAV WPT power transmission.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A fault detection system based on wireless power transmission (WPT) for drones includes a power transmission module, a dynamic charging adjustment module, a charging power control and evaluation module, an energy transmission efficiency monitoring and evaluation module, and a charging base station monitoring center. When a drone arrives at a target WPT base station, the charging base station monitoring center controls the power transmission module of the target WPT base station to initiate wireless charging for the drone.

[0009] The charging dynamic adjustment module monitors the charging power of the drone in real time and adaptively adjusts it, and sends the adjustment information to the charging base station supervision center. The charging power control evaluation module evaluates the power control status of the drone's wireless charging process, and generates a power control evaluation qualified signal or a power control evaluation abnormality signal based on the evaluation, and sends the power control evaluation qualified signal to the energy transmission efficiency monitoring and evaluation module, and also sends the power control evaluation qualified signal to the charging base station supervision center.

[0010] When generating a power control evaluation qualified signal, the energy transmission efficiency monitoring and evaluation module is used to capture and analyze energy transmission efficiency anomalies, and a transmission efficiency qualified signal or a transmission efficiency abnormality signal is generated accordingly, and the transmission efficiency qualified signal or the transmission efficiency abnormality signal is sent to the charging base station supervision center; when the charging base station supervision center receives the power control evaluation abnormality signal or the transmission efficiency abnormality signal, it will issue a corresponding warning.

[0011] Furthermore, before wirelessly charging the drone, when the drone battery power drops to the lower power threshold, the onboard controller on the drone sends a charging request to the charging base station supervision center via 5G or Beidou. After receiving the charging request, the charging base station supervision center plans the optimal charging station based on the drone location and WPT base station status and feeds back to the drone. The drone receives the feedback information and flies to the target WPT base station.

[0012] Furthermore, the specific analysis process of the charging power control and evaluation module is as follows:

[0013] Obtain the real-time charging power of the wireless charging process, calculate the difference between the real-time supply power and the set target power, and take the absolute value to obtain the charging power deviation value. If the charging power deviation value exceeds the preset charging power deviation threshold, it is determined that the current power is in a poor state;

[0014] The total duration of the wireless charging process in the poor power state per unit time is obtained and marked as the power control anomaly value. The power control anomaly value is compared with the preset power control anomaly threshold. If the power control anomaly value exceeds the preset power control anomaly threshold, a power control evaluation abnormality signal is generated.

[0015] Furthermore, if the power control asynchrony value does not exceed the preset power control asynchrony threshold, the number of occurrences in which the wireless charging process is in a poor power state per unit time exceeds the corresponding preset single duration threshold is marked as a power adjustment frequency asynchrony value, and the maximum single duration in which the wireless charging process is in a poor power state per unit time is marked as a power adjustment amplitude asynchrony value;

[0016] The power control evaluation coefficient is obtained by weighted summing the power control timing value, the power adjustment frequency value and the power adjustment amplitude value, and the power control evaluation coefficient is numerically compared with the preset power control evaluation coefficient threshold. If the power control evaluation coefficient exceeds the preset power control evaluation coefficient threshold, a power control evaluation abnormal signal is generated; if the power control evaluation coefficient does not exceed the preset power control evaluation coefficient threshold, a power control evaluation qualified signal is generated.

[0017] Furthermore, the specific analysis process of the energy transmission efficiency monitoring and evaluation module is as follows:

[0018] A number of monitoring periods are set within a unit time, and the actual energy transmission efficiency of the corresponding monitoring period is collected. The actual energy transmission efficiency is numerically compared with the corresponding preset energy transmission efficiency threshold. If the actual energy transmission efficiency does not exceed the preset energy transmission efficiency threshold, the corresponding monitoring period is marked as an energy transmission inefficiency period. The number of energy transmission inefficiency periods within a unit time is obtained and the ratio is calculated with the total number of monitoring periods to obtain an energy transmission inefficiency value. The energy transmission inefficiency value is numerically compared with the preset energy transmission inefficiency threshold. If the energy transmission inefficiency value exceeds the preset energy transmission inefficiency threshold, an energy transmission abnormality signal is generated.

[0019] If the energy transmission inefficiency value does not exceed the preset energy transmission inefficiency threshold, the actual energy transmission efficiency is compared with the corresponding preset energy transmission efficiency threshold to obtain the energy transmission performance value, the energy transmission performance values of all monitoring periods within the unit time are averaged to obtain the energy transmission characteristic value, and the energy transmission characteristic value is numerically compared with the preset energy transmission characteristic threshold. If the energy transmission characteristic value exceeds the preset energy transmission characteristic threshold, a transmission efficiency qualified signal is generated; if the energy transmission characteristic value does not exceed the preset energy transmission characteristic threshold, an transmission efficiency abnormal signal is generated.

[0020] Furthermore, the energy transmission efficiency monitoring and evaluation module is communicatively connected to the transmission risk identification module. The energy transmission efficiency monitoring and evaluation module sends a transmission efficiency qualified signal to the transmission risk identification module. When the transmission risk identification module receives the transmission efficiency qualified signal, it evaluates the energy transmission risk status during the wireless charging process, and generates a high-risk transmission signal or a low-risk transmission signal accordingly, and sends the high-risk transmission signal or the low-risk transmission signal to the charging base station supervision center. When the charging base station supervision center receives the high-risk transmission signal, it issues a corresponding warning.

[0021] Furthermore, the transmission risk identification module is communicatively connected to the hovering and docking stability judgment module and the transmission environment detection and evaluation module. The hovering and docking stability judgment module analyzes and judges the hovering and docking stability of the UAV and the target WPT base station, assigns a first impact characteristic symbol ZP-1 or ZP-2 based on the analysis, and sends the first impact characteristic symbol ZP-1 or ZP-2 to the transmission risk identification module.

[0022] The transmission environment detection and assessment module detects and assesses the wireless charging environment, assigns a second impact characteristic symbol QP-1 or QP-2 accordingly, and sends the second impact characteristic symbol QP-1 or QP-2 to the transmission risk identification module; the transmission risk identification module generates a low transmission risk signal when receiving ZP-2∩QP-2, and generates a high transmission risk signal in other cases.

[0023] Furthermore, the specific analysis process of the hover docking stability judgment module is as follows:

[0024] The distance between the drone and the target WPT base station is collected and the deviation from the set standard distance is marked as the wireless transmission distance deviation. The angle between the normal direction of the transmitting coil and the receiving coil is collected and marked as the coil inclination value. The horizontal distance between the geometric center points of the transmitting coil and the receiving coil is collected and marked as the coil center deviation value.

[0025] The hovering docking detection value is calculated by weighted summing the wireless transmission distance deviation, coil tilt angle, and coil center deviation. The hovering docking detection value is then compared with a preset hovering docking detection threshold. If the hovering docking detection value exceeds the preset hovering docking detection threshold, it is determined that the current hovering docking state is non-optimal.

[0026] All hovering docking detection values within the unit time are obtained and their average is calculated to obtain the hovering docking evaluation value, and the total time in the hovering docking non-optimal state within the unit time is marked as the hovering docking asynchronous value, and the hovering docking evaluation value and the hovering docking asynchronous value are numerically compared with the preset hovering docking evaluation threshold and the preset hovering docking asynchronous threshold respectively. If the hovering docking evaluation value or the hovering docking asynchronous value exceeds the corresponding preset threshold, the first influencing characteristic symbol ZP-1 is assigned; if both the hovering docking evaluation value and the hovering docking asynchronous value do not exceed the corresponding preset threshold, the first influencing characteristic symbol ZP-2 is assigned.

[0027] Furthermore, the specific analysis process of the transmission environment detection and evaluation module is as follows:

[0028] Obtain the temperature and humidity of the wireless charging environment, calculate the difference between the temperature and the median of a preset suitable wireless charging environment temperature range, and take the absolute value to obtain a charging environment temperature analysis value; calculate the difference between the humidity and the median of a preset suitable wireless charging environment humidity range, and take the absolute value to obtain a charging environment humidity analysis value; and obtain the wind speed of the wireless charging environment and mark it as the charging environment wind analysis value;

[0029] The transmission environment detection value is calculated by weighted summing the charging ring temperature analysis value, the charging ring humidity analysis value, and the charging ring wind analysis value. The transmission environment detection value is numerically compared with the preset transmission environment detection threshold. If the transmission environment detection value exceeds the preset transmission environment detection threshold, it is determined that the transmission environment is in a non-optimal state;

[0030] The total duration of the wireless charging environment in a non-optimal transmission environment state within a unit time is obtained and marked as the wireless transmission loop resistance value, and the average of all transmission environment detection values within the unit time is calculated to obtain the transmission environment evaluation value. The wireless transmission loop resistance value and the transmission environment evaluation value are numerically compared with the preset wireless transmission loop resistance threshold and the preset transmission environment evaluation threshold respectively. If the wireless transmission loop resistance value or the transmission environment evaluation value exceeds the corresponding preset threshold, a second impact characteristic symbol QP-1 is assigned; if neither the wireless transmission loop resistance value nor the transmission environment evaluation value exceeds the corresponding preset threshold, a second impact characteristic symbol QP-2 is assigned.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] 1. In the present invention, the power transmission module of the target WPT base station is controlled by the charging base station supervision center to start wireless charging of the drone. The charging dynamic adjustment module monitors the charging power of the drone in real time and adaptively adjusts it. The charging power control and evaluation module evaluates the power control status of the drone's wireless charging process and analyzes energy transmission efficiency anomalies when generating a power control and evaluation qualified signal. This helps supervisors take timely corresponding regulatory and improvement measures, reduces energy loss during the wireless charging process, ensures charging efficiency, and significantly reduces the difficulty of supervising and controlling the drone's WPT power transmission process.

[0033] 2. In the present invention, the hovering and docking stability judgment module analyzes and judges the hovering and docking stability of the UAV and the target WPT base station, the transmission environment detection and evaluation module detects and evaluates the wireless charging environment, and the transmission risk identification module comprehensively evaluates the energy transmission risk status during the wireless charging process based on the hovering and docking stability judgment result and the transmission environment analysis result when receiving the transmission qualified signal. When a high-risk transmission signal is generated, the wireless charging process of the UAV is suspended or reasonable improvement measures are taken, which is conducive to reducing the risk of UAV WPT power transmission and reducing transmission loss, and further reducing the difficulty of supervising the wireless charging process. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0035] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0036] Figure 2 This is a system block diagram of Embodiment 2, Embodiment 3 and Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0038] Example 1: Figure 1 As shown in the figure, the present invention proposes a fault detection system based on UAV WPT power transmission, including a power transmission module, a charging dynamic adjustment module, a charging power control and evaluation module, an energy transmission efficiency monitoring and evaluation module, and a charging base station supervision center;

[0039] When the drone's battery power drops to the lower limit, the drone's onboard controller sends a charging request to the charging base station monitoring center via 5G or Beidou. After receiving the charging request, the charging base station monitoring center plans the optimal charging station based on the drone's location and the status of the WPT base station and feedbacks it to the drone. The drone receives the feedback information and flies to the target WPT base station. When the drone arrives at the target WPT base station, the charging base station monitoring center controls the power transmission module of the target WPT base station to start wireless charging for the drone.

[0040] The charging dynamic adjustment module monitors the UAV's charging power in real time and adaptively adjusts it, sending the adjustment information to the charging base station supervision center and the charging power control and evaluation module. The charging power control and evaluation module evaluates the power control status of the UAV's wireless charging process and generates a power control evaluation pass signal or a power control evaluation abnormality signal accordingly.

[0041] The power control evaluation qualified signal is sent to the charging base station supervision center. When the charging base station supervision center receives the abnormal power control evaluation signal, it issues a corresponding warning to remind the supervisor to investigate and analyze the cause and take corresponding improvement measures, thereby ensuring the control accuracy of wireless charging power, improving charging efficiency and charging safety while reducing charging losses. The specific analysis process of the charging power control evaluation module is as follows:

[0042] Obtain the real-time charging power of the wireless charging process, calculate the difference between the real-time supply power and the set target power, and take the absolute value to obtain the charging power deviation value. If the charging power deviation value exceeds the preset charging power deviation threshold, it is determined that the current power is in a poor state;

[0043] The total duration of the wireless charging process in a poor power state per unit time is obtained and marked as the power control anomaly value. The power control anomaly value is compared with the preset power control anomaly threshold. If the power control anomaly value exceeds the preset power control anomaly threshold, it indicates that the charging power control performance of the drone charging process is poor, and a power control evaluation abnormality signal is generated.

[0044] Furthermore, if the power control asynchrony value does not exceed the preset power control asynchrony threshold, the number of occurrences in which the wireless charging process is in a poor power state per unit time exceeds the corresponding preset single duration threshold is marked as the power adjustment asynchrony value, and the maximum single duration in which the wireless charging process is in a poor power state per unit time is marked as the power adjustment asynchrony value;

[0045] The power control evaluation coefficient is calculated by weighted summing the power control time difference value, the power adjustment frequency difference value, and the power adjustment amplitude difference value. That is, the power control time difference value, the power adjustment frequency difference value, and the power adjustment amplitude difference value are assigned corresponding preset weight coefficients, and the power control time difference value, the power adjustment frequency difference value, and the power adjustment amplitude difference value are multiplied by the corresponding preset weight coefficients, and the sum of the three sets of product results is marked as the power control evaluation coefficient. Moreover, the larger the value of the power control evaluation coefficient, the worse the overall charging power control performance of the UAV charging process.

[0046] The power control evaluation coefficient is numerically compared with the preset power control evaluation coefficient threshold. If the power control evaluation coefficient exceeds the preset power control evaluation coefficient threshold, it indicates that the charging power control performance of the drone charging process is generally poor, and a power control evaluation abnormality signal is generated; if the power control evaluation coefficient does not exceed the preset power control evaluation coefficient threshold, it indicates that the charging power control performance of the drone charging process is generally good, and a power control evaluation qualified signal is generated.

[0047] When generating a power control evaluation qualified signal, the energy transmission efficiency monitoring and evaluation module is used to capture and analyze energy transmission efficiency anomalies, and accordingly generates a transmission efficiency qualified signal or a transmission efficiency abnormality signal, and sends the transmission efficiency qualified signal or the transmission efficiency abnormality signal to the charging base station supervision center. When the charging base station supervision center receives the transmission efficiency abnormality signal, it issues a corresponding warning to remind the supervisor to conduct a cause investigation and analysis and take corresponding control measures in a timely manner, thereby further reducing the power loss in the wireless charging process and ensuring charging efficiency. The specific analysis process of the energy transmission efficiency monitoring and evaluation module is as follows:

[0048] A number of monitoring periods are set within a unit of time, and the actual energy transmission efficiency of the corresponding monitoring period is collected. The actual energy transmission efficiency is numerically compared with the corresponding preset energy transmission efficiency threshold. If the actual energy transmission efficiency does not exceed the preset energy transmission efficiency threshold, it indicates that the energy transmission loss of the corresponding monitoring period is large, and the corresponding monitoring period is marked as an energy transmission inefficient period;

[0049] The number of energy transmission inefficiency periods per unit time is obtained and the ratio thereof is calculated with the total number of monitoring periods to obtain an energy transmission inefficiency value, and the energy transmission inefficiency value is numerically compared with a preset energy transmission inefficiency threshold. If the energy transmission inefficiency value exceeds the preset energy transmission inefficiency threshold, indicating that the energy transmission efficiency per unit time is poor, an energy transmission abnormality signal is generated;

[0050] If the energy transmission inefficiency value does not exceed the preset energy transmission inefficiency threshold, the actual energy transmission efficiency is compared with the corresponding preset energy transmission efficiency threshold to obtain an energy transmission performance value, the energy transmission performance values of all monitoring periods in the unit time are averaged to obtain an energy transmission characteristic value, and the energy transmission characteristic value is numerically compared with the preset energy transmission characteristic threshold;

[0051] If the energy transfer characteristic value exceeds the preset energy transfer characteristic threshold, indicating that the energy transfer efficiency performance per unit time is generally good, a transmission efficiency qualified signal is generated; if the energy transfer characteristic value does not exceed the preset energy transfer characteristic threshold, indicating that the energy transfer efficiency performance per unit time is generally poor, an transmission efficiency abnormality signal is generated.

[0052] Example 2: Figure 2 As shown, the difference between this embodiment and the first embodiment is that the energy transmission efficiency monitoring and evaluation module is communicatively connected to the transmission risk identification module. The energy transmission efficiency monitoring and evaluation module sends a transmission efficiency qualified signal to the transmission risk identification module. When the transmission risk identification module receives the transmission efficiency qualified signal, it evaluates the energy transmission risk status during the wireless charging process.

[0053] Based on this, a high-risk transmission signal or a low-risk transmission signal is generated and sent to the charging base station supervision center. When the charging base station supervision center receives the high-risk transmission signal, it issues a corresponding warning to remind the back-end supervision personnel to suspend the wireless charging process of the drone in time or take reasonable improvement measures. This is conducive to reducing the risk of drone WPT power transmission and transmission loss, and further reducing the difficulty of supervising the wireless charging process. The specific process is as follows:

[0054] The first influencing characteristic symbol ZP-1 or ZP-2 and the second influencing characteristic symbol QP-1 or QP-2 are obtained. If ZP-2∩QP-2 is received, a low-risk transmission signal is generated. In other cases (ZP-1∩QP-2, ZP-2∩QP-1 or ZP-1∩QP-1), a high-risk transmission signal is generated.

[0055] Example 3: Figure 2 As shown, the difference between this embodiment and the first and second embodiments is that the transmission risk identification module is communicatively connected to the hovering and docking stability judgment module. The hovering and docking stability judgment module analyzes and judges the hovering and docking stability of the UAV and the target WPT base station, and assigns the first impact characteristic symbol ZP-1 or ZP-2 accordingly.

[0056] The first impact characteristic symbol ZP-1 or ZP-2 is sent to the transmission risk identification module, which can not only reasonably analyze and accurately judge the hovering and docking performance of the UAV, but also provide information support for the analysis process of the transmission risk identification module to ensure the accuracy of its analysis results. The specific analysis process of the hovering and docking stability judgment module is as follows:

[0057] The distance between the drone and the target WPT base station is collected and the deviation from the set standard distance is marked as the wireless transmission distance deviation. The angle between the normal direction of the transmitting coil and the receiving coil is collected and marked as the coil inclination value. The horizontal distance between the geometric center points of the transmitting coil and the receiving coil is collected and marked as the coil center deviation value.

[0058] The hovering docking detection value is calculated by weighted summing the wireless transmission distance deviation, coil tilt angle, and coil center deviation values through a formula. That is, the wireless transmission distance deviation, coil tilt angle, and coil center deviation values are assigned corresponding preset weight coefficients, and the wireless transmission distance deviation, coil tilt angle, and coil center deviation values are multiplied by the corresponding preset weight coefficients, and the sum of the three sets of product results is marked as the hovering docking detection value. Moreover, the larger the value of the hovering docking detection value, the worse the overall real-time hovering docking status of the drone is.

[0059] Compare the hovering docking detection value with the preset hovering docking detection threshold. If the hovering docking detection value exceeds the preset hovering docking detection threshold, it indicates that the real-time hovering docking status of the drone is generally poor, and the drone is judged to be in a non-optimal hovering docking state.

[0060] All hovering and docking detection values within a unit time are obtained and their average is calculated to obtain a hovering and docking evaluation value, and the total time in the hovering and docking non-optimal state within the unit time is marked as a hovering and docking asynchrony value, and the hovering and docking evaluation value and the hovering and docking asynchrony value are numerically compared with a preset hovering and docking evaluation threshold and a preset hovering and docking asynchrony threshold respectively;

[0061] If the hovering and docking evaluation value or the hovering and docking asynchronous value exceeds the corresponding preset threshold, it indicates that the hovering and docking of the UAV is unstable in unit time, which is likely to hinder the stable, safe and efficient wireless charging process, and the first impact characteristic symbol ZP-1 is assigned; if the hovering and docking evaluation value and the hovering and docking asynchronous value do not exceed the corresponding preset threshold, it indicates that the hovering and docking of the UAV is relatively stable in unit time, which is conducive to ensuring the stable, safe and efficient wireless charging process, and the first impact characteristic symbol ZP-2 is assigned.

[0062] Example 4: Figure 2 As shown, the difference between this embodiment and the first, second and third embodiments is that the transmission risk identification module is communicatively connected to the transmission environment detection and evaluation module, and the transmission environment detection and evaluation module detects and evaluates the wireless charging environment and assigns a second impact characteristic symbol QP-1 or QP-2 accordingly;

[0063] The second influencing characteristic symbol QP-1 or QP-2 is sent to the transmission risk identification module, which not only can reasonably analyze and accurately determine the suitability of the wireless charging environment, but also can provide information support for the analysis process of the transmission risk identification module, further ensuring the accuracy of its analysis results. The specific analysis process of the transmission environment detection and evaluation module is as follows:

[0064] Obtain the temperature and humidity of the wireless charging environment, calculate the difference between the temperature and the median of a preset suitable wireless charging environment temperature range, and take the absolute value to obtain a charging environment temperature analysis value; calculate the difference between the humidity and the median of a preset suitable wireless charging environment humidity range, and take the absolute value to obtain a charging environment humidity analysis value; and obtain the wind speed of the wireless charging environment and mark it as the charging environment wind analysis value;

[0065] The transmission environment detection value is calculated by weighted summing the charging ambient temperature analysis value, the charging ambient humidity analysis value, and the charging ambient wind analysis value; that is, the charging ambient temperature analysis value, the charging ambient humidity analysis value, and the charging ambient wind analysis value are respectively assigned corresponding preset weight coefficients, and the charging ambient temperature analysis value, the charging ambient humidity analysis value, and the charging ambient wind analysis value are respectively multiplied by the corresponding preset weight coefficients, and the sum of the three sets of product results is marked as the transmission environment detection value; and, the larger the value of the transmission environment detection value, the worse the overall real-time condition of the wireless charging environment is;

[0066] Compare the transmission environment detection value with a preset transmission environment detection threshold. If the transmission environment detection value exceeds the preset transmission environment detection threshold, it indicates that the real-time condition of the wireless charging environment is generally poor, and the transmission environment is determined to be in a non-optimal state.

[0067] Obtain the total duration of the wireless charging environment in a non-optimal transmission environment state per unit time and mark it as the wireless transmission loop resistance value, and calculate the average of all transmission environment detection values per unit time to obtain a transmission environment evaluation value, and compare the wireless transmission loop resistance value and the transmission environment evaluation value with the preset wireless transmission loop resistance threshold and the preset transmission environment evaluation threshold respectively;

[0068] If the wireless transmission loop resistance value or the transmission environment assessment value exceeds the corresponding preset threshold, it indicates that the wireless charging environment condition per unit time is poor, which is likely to hinder the stable, safe, and efficient wireless charging process, and the second impact characteristic symbol QP-1 is assigned; if neither the wireless transmission loop resistance value nor the transmission environment assessment value exceeds the corresponding preset threshold, it indicates that the wireless charging environment condition per unit time is good, which is conducive to ensuring the stable, safe, and efficient wireless charging process, and the second impact characteristic symbol QP-2 is assigned.

[0069] The working principle of the present invention is as follows: when in use, the power transmission module belonging to the target WPT base station is controlled by the charging base station supervision center to start wireless charging of the UAV, the charging dynamic adjustment module monitors the charging power of the UAV in real time and adaptively adjusts it, and the charging power control evaluation module evaluates the power control status of the UAV wireless charging process. When an abnormal power control evaluation signal is generated, the cause is investigated and analyzed and corresponding improvement measures are taken to ensure the control accuracy of the wireless charging power, improve the charging efficiency and charging safety while reducing the charging loss, and when a qualified power control evaluation signal is generated, the energy transmission efficiency monitoring and evaluation module is used to capture and analyze the energy transmission efficiency anomaly. When an abnormal transmission efficiency signal is generated, the cause is investigated and analyzed and corresponding control measures are taken in time to further reduce the power loss of the wireless charging process and ensure the charging efficiency, significantly reducing the difficulty of supervision and control of the UAV WPT power transmission process.

[0070] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The determination of the threshold in the technical solution is based on the data mean obtained under training of a large number of data dimensions. The preferred embodiment does not describe all the details in detail, nor does it limit the invention to only a specific implementation method. Obviously, many modifications and changes can be made based on the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A fault detection system based on UAV WPT power transmission, characterized in that: It includes a power transmission module, a dynamic charging adjustment module, a charging power control and evaluation module, an energy transmission efficiency monitoring and evaluation module, and a charging base station supervision center. When the drone arrives at the target WPT base station, the charging base station supervision center controls the power transmission module of the target WPT base station to start wireless charging for the drone. The charging dynamic adjustment module monitors the charging power of the drone in real time and adaptively adjusts it. The charging power control and evaluation module evaluates the power control status of the drone's wireless charging process, and generates a power control evaluation qualified signal or a power control evaluation abnormal signal accordingly. When generating the power control evaluation qualified signal, the energy transmission efficiency monitoring and evaluation module captures and analyzes energy transmission efficiency anomalies, and generates a transmission efficiency qualified signal or a transmission efficiency abnormal signal accordingly. When the charging base station supervision center receives the power control evaluation abnormal signal or the transmission efficiency abnormal signal, it issues a corresponding warning.

2. A fault detection system based on UAV WPT power transmission according to claim 1, characterized in that: When the drone's battery power drops to the lower limit threshold, the onboard controller on the drone sends a charging request to the charging base station supervision center via 5G or Beidou. After receiving the charging request, the charging base station supervision center plans the optimal charging station based on the drone's location and the WPT base station status and feeds back to the drone. The drone receives the feedback information and flies to the target WPT base station.

3. A fault detection system based on UAV WPT power transmission according to claim 1, characterized in that: The specific analysis process of the charging power control evaluation module is as follows: if the charging power deviation value exceeds the preset charging power deviation threshold, it is determined that the current state is poor power; the total duration of the wireless charging process in the poor power state per unit time is obtained and marked as the power control anomaly value; if the power control anomaly value exceeds the preset power control anomaly threshold, a power control evaluation abnormal signal is generated.

4. A fault detection system based on UAV WPT power transmission according to claim 3, characterized in that: If the power control timing value does not exceed the preset power control timing threshold, the power control evaluation coefficient is obtained by weighted summing the power control timing value, the power adjustment frequency value and the power adjustment amplitude value. If the power control evaluation coefficient exceeds the preset power control evaluation coefficient threshold, a power control evaluation abnormal signal is generated; if the power control evaluation coefficient does not exceed the preset power control evaluation coefficient threshold, a power control evaluation qualified signal is generated.

5. The fault detection system based on UAV WPT power transmission according to claim 1 is characterized in that: The specific analysis process of the energy transmission efficiency monitoring and evaluation module is as follows: The number of energy transmission inefficiency periods per unit time is obtained and the ratio thereof is calculated with the total number of monitoring periods to obtain an energy transmission inefficiency value. If the energy transmission inefficiency value exceeds a preset energy transmission inefficiency threshold, an energy transmission abnormality signal is generated. If the energy transmission inefficiency value does not exceed the preset energy transmission inefficiency threshold, the energy transmission characteristic value is numerically compared with the preset energy transmission characteristic threshold. If the energy transmission characteristic value exceeds the preset energy transmission characteristic threshold, a transmission efficiency qualified signal is generated. Otherwise, an abnormal transmission signal is generated.

6. A fault detection system based on UAV WPT power transmission according to claim 5, characterized in that: The energy transmission efficiency monitoring and evaluation module is communicatively connected to the transmission risk identification module. When the transmission risk identification module receives the transmission efficiency qualified signal, it evaluates the energy transmission risk status during the wireless charging process, and generates a high-risk transmission signal or a low-risk transmission signal accordingly, and sends the high-risk transmission signal or the low-risk transmission signal to the charging base station supervision center.

7. A fault detection system based on UAV WPT power transmission according to claim 6, characterized in that: The transmission risk identification module is communicatively connected to the hovering and docking stability judgment module and the transmission environment detection and evaluation module. The hovering and docking stability judgment module analyzes and determines the hovering and docking stability of the UAV and the target WPT base station, and sends the first impact characteristic symbol ZP-1 or ZP-2 to the transmission risk identification module. The transmission environment detection and evaluation module detects and evaluates the wireless charging environment and sends the second impact characteristic symbol QP-1 or QP-2 to the transmission risk identification module. The transmission risk identification module generates a low transmission risk signal when receiving ZP-2∩QP-2, and generates a high transmission risk signal in other cases.

8. A fault detection system based on UAV WPT power transmission according to claim 7, characterized in that: The specific analysis process of the hover docking stability judgment module is as follows: All hovering and docking detection values within the unit time are obtained and their average is calculated to obtain the hovering and docking evaluation value, and the total time in the hovering and docking non-optimal state within the unit time is marked as the hovering and docking asynchronous value. If the hovering and docking evaluation value or the hovering and docking asynchronous value exceeds the corresponding preset threshold, the first impact characteristic symbol ZP-1 is assigned; otherwise, the first impact characteristic symbol ZP-2 is assigned.

9. A fault detection system based on UAV WPT power transmission according to claim 7, characterized in that: The specific analysis process of the transmission environment detection and evaluation module is as follows: The total duration of the wireless charging environment in a non-optimal transmission environment state per unit time is obtained and marked as the wireless transmission loop resistance value, and the average of all transmission environment detection values per unit time is calculated to obtain a transmission environment evaluation value. If the wireless transmission loop resistance value or the transmission environment evaluation value exceeds the corresponding preset threshold, a second impact characteristic symbol QP-1 is assigned; otherwise, a second impact characteristic symbol QP-2 is assigned.

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