Fault monitoring method, system, medium and equipment based on PTZ

Abstract

The embodiment of the present invention discloses a gimbal-based fault monitoring method, system, medium and device. The system obtains first data when the gimbal is calibrated before takeoff and second data of the gimbal during the ascent. The system compares the first data with the second data. If the first data is different from the second data, it indicates that there is a flight fault, and a flight fault signal is generated. Then the system obtains the axial error data of the gyroscope on the drone, obtains the data information of the gyroscope, generates adjustment data based on the axial error data of the drone, generates an adjustment command based on the adjustment data, and sends it to the drone. The drone executes the adjustment command and configures adjustment parameters for each blade drive motor to adjust the output power of each blade drive motor to control the balance of the drone. Through real-time monitoring and fault detection, the stability of the gimbal and the drone is ensured, and loss of control or image jitter caused by faults during flight is avoided.

Description

Technical Field

[0001] The present invention relates to the field of pan / tilt technology, and in particular to a pan / tilt-based fault monitoring method, system, medium and equipment. Background Art

[0002] A gimbal is a crucial component of drone systems, used to stabilize cameras or sensors, allowing them to maintain a steady image and adjust shooting angles during flight. Whether it's professional aerial photography, terrain mapping, or industrial applications, the gimbal plays a key role.

[0003] Initial gimbal control methods were very simple, achieving basic motion solely through current-driven motors. The motor's angle adjustment relied entirely on the magnitude and timing of the input current, with no feedback mechanism. This is known as open-loop control. However, this method lacks precise control over the motor's actual position or speed. External interference (such as wind and load variations) or hardware errors can easily cause motor output to deviate from expectations. This results in poor stability and makes it difficult to meet the demands of complex applications.

[0004] With the introduction of stepper motors, which gradually rotate the rotor through the stator coils, each step has a fixed angular increment. The gimbal control system calculates the angular position of the motor by counting the steps, thus achieving a preliminary improvement in accuracy.

[0005] However, stepper motors are not sensitive to external interference. If steps are lost or slips occur, the control system cannot correct the deviation.

[0006] Then, by introducing a position encoder, the encoder can provide real-time feedback on the actual position of the motor. The control system adjusts the current to correct the deviation by comparing the target position with the actual position.

[0007] A speed encoder is introduced to achieve speed closed-loop control. The speed encoder can measure the speed of the motor and help the system adjust the current in real time to maintain a steady movement speed.

[0008] During the use of drones, although the gimbal's control over itself has become very sophisticated, its own status is limited to the encoder or gyroscope.

[0009] For example, when using a drone, some users will add some external module structures at different positions of the drone to change some of the requirements during use of the drone (adding cameras, searchlights, power modules, etc. with different functions). At this time, the peripheral modules are directly fixed on the drone's body, and there is no data interaction or electrical connection with the drone system. The drone cannot determine whether there are external modules on the body. When these modules are installed on the drone, weight imbalance problems will occur, causing the motor to over-run during calibration to compensate for the center of gravity problem. This imbalance will cause the motor to work continuously, causing the motor to heat up and run under load, causing the gimbal to shake or shake, unable to transmit the picture, and affecting the image imaging.

[0010] Secondly, because the gimbal's motor over-runs to compensate during calibration, it is very easy for the gimbal's motor to be judged as faulty during the calibration process, which in turn renders the drone's gimbal unusable. Summary of the Invention

[0011] Based on this, it is necessary to propose a fault monitoring method, system, medium and equipment based on a pan-tilt system to address the above problems.

[0012] The present invention proposes a fault monitoring method based on a pan-tilt platform, the method comprising:

[0013] Get the first data of gimbal calibration before takeoff;

[0014] Obtain the second data of the gimbal during the flight;

[0015] comparing the first data with the second data;

[0016] If the first data is different from the second data, it is determined to be a flight failure, and the data information of the drone's gyroscope is obtained;

[0017] generating adjustment data according to the data information of the drone gyroscope, and generating an adjustment command according to the adjustment data;

[0018] The adjustment command is executed to enable each blade drive motor of the drone to adjust the output power according to the adjustment data to control the balance of the drone.

[0019] In at least one embodiment of the present application, the method further includes:

[0020] Acquire third data of the pan / tilt platform after the adjustment command is executed;

[0021] comparing the third data with the first data;

[0022] If the third data is different from the first data, it is determined that the drone is abnormal, and a hovering instruction is generated and executed to control the drone to hover.

[0023] In at least one embodiment of the present application, the method further includes:

[0024] If the third data is the same as the first data, it is determined that the drone has gained weight, drone operation modification data is generated according to the adjustment data, and the drone is controlled to fly according to the drone operation modification data.

[0025] In at least one embodiment of the present application, the method further includes:

[0026] The first data includes angle data during gimbal calibration, center of gravity data during calibration, and sensor data;

[0027] The second data is the angle data, center of gravity data and sensor data of the gimbal during the vertical ascent of the UAV.

[0028] In at least one embodiment of the present application, the method further includes:

[0029] Get the fourth data of the gimbal of the drone in hovering state;

[0030] The fourth data is compared with the third data, and if the fourth data is different from the third data, a pan / tilt abnormality signal is generated.

[0031] In at least one embodiment of the present application, the method further includes:

[0032] Secondary calibration data is generated according to the fourth data and the first data, and the secondary calibration data is sent to the pitch axis motor, the roll axis motor, and the yaw axis motor of the gimbal to calibrate the angle of the gimbal.

[0033] In at least one embodiment of the present application, the method further includes:

[0034] If the fourth data is the same as the third data, it is determined that the drone is operating normally.

[0035] A PTZ-based fault monitoring system, applied to any of the above-mentioned PTZ-based fault monitoring methods, comprises:

[0036] A gimbal parameter acquisition module, configured to acquire first data during gimbal calibration before takeoff and second data during the gimbal's flight;

[0037] a comparison module, comparing the first data with the second data;

[0038] Gyroscope parameter acquisition module, used to obtain gyroscope data information;

[0039] An adjustment command generation module generates an adjustment command based on the data information of the gyroscope;

[0040] An execution module, used to execute adjustment commands to control the drone;

[0041] The system performs the following steps:

[0042] Get the first data of gimbal calibration before takeoff;

[0043] Obtain the second data of the gimbal during the flight;

[0044] comparing the first data with the second data;

[0045] If the first data is different from the second data, it is determined to be a flight failure, and the data information of the drone's gyroscope is obtained;

[0046] generating adjustment data according to the data information of the drone gyroscope, and generating an adjustment command according to the adjustment data;

[0047] The adjustment command is executed to enable each blade drive motor of the drone to adjust the output power according to the adjustment data to control the balance of the drone.

[0048] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the following steps:

[0049] Get the first data of gimbal calibration before takeoff;

[0050] Obtain the second data of the gimbal during the flight;

[0051] comparing the first data with the second data;

[0052] If the first data is different from the second data, it is determined to be a flight failure, and the data information of the drone's gyroscope is obtained;

[0053] generating adjustment data according to the data information of the drone gyroscope, and generating an adjustment command according to the adjustment data;

[0054] The adjustment command is executed to enable each blade drive motor of the drone to adjust the output power according to the adjustment data to control the balance of the drone.

[0055] A computer-readable storage medium stores a computer program, which, when executed by a processor, causes the processor to perform the following steps:

[0056] Get the first data of gimbal calibration before takeoff;

[0057] Obtain the second data of the gimbal during the flight;

[0058] comparing the first data with the second data;

[0059] If the first data is different from the second data, it is determined to be a flight failure, and the data information of the drone's gyroscope is obtained;

[0060] generating adjustment data according to the data information of the drone gyroscope, and generating an adjustment command according to the adjustment data;

[0061] The adjustment command is executed to enable each blade drive motor of the drone to adjust the output power according to the adjustment data to control the balance of the drone.

[0062] The implementation of the PTZ-based fault monitoring method, system, medium, and device of the present invention will have at least the following beneficial effects:

[0063] The present invention provides a gimbal-based fault monitoring method, system, medium and equipment. The system obtains first data during gimbal calibration before takeoff and second data during the launch process. The system compares the first data with the second data. If the first data is different from the second data, it indicates that there is a flight fault, and a flight fault signal is generated.

[0064] The system then obtains the axial error data of the gyroscope on the drone, obtains the data information of the gyroscope, generates adjustment data based on the axial error data of the drone, generates adjustment commands based on the adjustment data, and sends them to the drone.

[0065] The drone executes the adjustment command and configures adjustment parameters for each blade drive motor to adjust the output power of each blade drive motor to control the balance of the drone.

[0066] Through real-time monitoring and fault detection, the stability of the gimbal and drone is ensured to avoid loss of control or image jitter caused by faults during flight.

[0067] By automatically adjusting the balance and posture control, the operator's complex operations are reduced and the ease of use is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0069] in:

[0070] Figure 1 is a flow chart of a PTZ-based fault monitoring method according to one embodiment;

[0071] Figure 2 is a flow chart of a PTZ-based fault monitoring method according to another embodiment;

[0072] Figure 3 is a structural block diagram of a PTZ-based fault monitoring system in one embodiment;

[0073] Figure 4 FIG. 1 is a structural block diagram of a computer device in one embodiment.

[0074] in:

[0075] 100. PTZ-based fault monitoring system; 110. PTZ parameter acquisition module; 120. Comparison module; 130. Adjustment command generation module; 140. Gyroscope parameter acquisition module; 150. Execution module. DETAILED DESCRIPTION

[0076] 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. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0077] The present invention proposes a fault monitoring method based on a pan-tilt platform, the method comprising:

[0078] S101, obtaining first data during gimbal calibration before takeoff;

[0079] S102, obtaining second data of the gimbal during the flight;

[0080] S103, comparing the first data with the second data;

[0081] S104: If the first data and the second data are different, it is determined to be a flight failure, and data information of the drone's gyroscope is obtained;

[0082] S105, generating adjustment data based on the data information of the drone gyroscope, and generating an adjustment command based on the adjustment data;

[0083] S106: Execute the adjustment command to enable each blade drive motor of the drone to adjust the output power according to the adjustment data to control the balance of the drone.

[0084] Please refer to Figures 1 to 2 In this embodiment, the system obtains the first data when the gimbal is calibrated before takeoff and the second data of the gimbal during the ascent. The system compares the first data with the second data. If the first data is different from the second data, it indicates that there is a flight fault, and a flight fault signal is generated. The flight fault signal at this time may be that the drone has added external equipment or the drone is affected by airflow during the ascent.

[0085] The system then obtains the axial error data of the gyroscope on the drone, obtains the data information of the gyroscope, generates adjustment data based on the axial error data of the drone, generates adjustment commands based on the adjustment data, and sends them to the drone.

[0086] The drone executes the adjustment command and configures adjustment parameters for each blade drive motor to adjust the output power of each blade drive motor to control the drone to be in a balanced state (level).

[0087] Through real-time monitoring and fault detection, the stability of the gimbal and drone is ensured to avoid loss of control or image jitter caused by faults during flight.

[0088] By automatically adjusting the balance and posture control, the operator's complex operations are reduced and the ease of use is improved.

[0089] It should be noted that the data information of the gyroscope is the alignment error data of each axis of the gyroscope.

[0090] The first data is the parameter data after the gimbal is calibrated before the drone takes off, including angle data, center of gravity data, pitch axis motor data, roll axis motor data, yaw axis motor data, etc.

[0091] The second data is the parameter data of the gimbal during the vertical takeoff of the drone, including the angle data, center of gravity data, pitch axis motor, roll axis motor, yaw axis motor data, etc. during the vertical takeoff process.

[0092] It should be further explained that real-time flight data is obtained. Flight data includes gyroscope data (including the angular velocity of the drone's pitch, roll, and yaw axes, as well as the angle change relative to the ground), gimbal data (real-time angle data (such as pitch, roll, and yaw angles) and status (such as the output power of the gimbal motor)).

[0093] Compare the first data before flight (first data, such as angle and center of gravity data during calibration) with the second data during real-time flight (second data, such as angle and center of gravity data during calibration).

[0094] By comparing the difference between the two, we can identify the attitude deviation during flight. For example:

[0095] If the pitch angle deviates from the preset value, the motor power of the pitch axis needs to be adjusted.

[0096] If the roll angle deviates from the normal range, the motor power of the roll axis needs to be adjusted.

[0097] If the yaw angle is outside the predetermined range, the power to the yaw axis motor may need to be adjusted.

[0098] Based on the attitude deviation and flight requirements, calculate the amount of adjustment required for the motor output power of each axis.

[0099] For example, adjustment parameters are generated based on PID control.

[0100] If the first and second data are consistent, the gimbal maintained the expected stability and attitude during flight after pre-takeoff calibration. There were no significant disturbances during flight, and the gimbal was not affected by external factors. The system can continue the mission and the gimbal is operating normally.

[0101] The first and second data are inconsistent, indicating the gimbal failed to maintain its intended stability during flight. This could be due to external interference (such as wind or uneven load) or gimbal adjustment failure (such as a motor or sensor issue). The system has determined this to be a flight malfunction and requires further investigation, possibly requiring gimbal adjustment or hardware inspection.

[0102] It should be further explained that if the gimbal angle needs to be adjusted during the flight, the gimbal data during the launch process is obtained, and the adjustment angle parameters of the gimbal control are obtained. The difference between the adjustment angle parameters and the gimbal data is calculated to obtain the second data.

[0103] In at least one embodiment of the present application, the method further includes:

[0104] S201, obtaining third data of the PTZ after the adjustment command is executed;

[0105] S202, comparing the third data with the first data;

[0106] S203: If the third data is different from the first data, it is determined that the drone is abnormal, and a hovering instruction is generated and executed to control the drone to hover.

[0107] S204: If the third data is the same as the first data, it is determined that the drone has gained weight, drone operation modification data is generated according to the adjustment data, and the drone is controlled to fly according to the drone operation modification data.

[0108] In at least one embodiment of the present application, the method further includes:

[0109] S205, obtaining fourth data of the gimbal of the drone in a hovering state;

[0110] S206: If the fourth data is the same as the third data, it is determined that the drone is operating normally.

[0111] In at least one embodiment of the present application, the method further includes:

[0112] S207, comparing the fourth data with the third data;

[0113] S208. If the fourth data is different from the third data, a pan / tilt abnormality signal is generated.

[0114] In at least one embodiment of the present application, the method further includes:

[0115] S209 , generating secondary calibration data according to the fourth data and the first data, and sending the secondary calibration data to the pitch axis motor, the roll axis motor, and the yaw axis motor of the gimbal to calibrate the angle of the gimbal.

[0116] Please refer to Figures 1 to 2 In this embodiment, when the drone adjustment is completed, that is, the drone is in a horizontal state, the system obtains the third data of the gimbal at this time, and the third data includes the adjusted angle data and the status data of the gimbal motor.

[0117] The third data is compared with the first data. If the third data is the same as the first data, it means that the drone has added peripherals, that is, the drone has an increased load.

[0118] At this point, the adjusted gimbal status is consistent with the pre-takeoff gimbal calibration state, and there are no gimbal adjustment issues. This indicates that the gimbal itself is functioning properly and is accurately adjusted. This means that the drone has gained weight. During flight, additional payloads (such as additional equipment, sensors, and cameras) have increased the total weight of the drone, requiring the gimbal to make additional adjustments and compensation.

[0119] It should be noted that the adjustment command is an instruction to control the drone to achieve a balanced flight state. That is, according to the gyroscope data information, the adjustment command adjusts the gyroscope to a horizontal state. This avoids the problem of judgment error caused by the tilt of the drone body.

[0120] When the system determines that the drone has gained weight, the flight control system needs to generate modification data based on the flight conditions after the weight gain. Since the weight gain will increase the total load of the drone, the flight control system needs to adjust the power output of the blade drive motor to ensure flight stability and sufficient thrust.

[0121] Adding weight may cause the drone's center of gravity to change, so the flight attitude may need to be adjusted to ensure the drone remains level or flies at a predetermined angle.

[0122] Flying with increased weight may affect flight speed, range, energy consumption, etc., and the control system may need to adjust the flight plan accordingly.

[0123] If the third data is the same as the first data, it means that the gimbal adjustment is successful and stable, but since there is no gimbal abnormality, the system will infer that the drone has gained weight.

[0124] By monitoring the gimbal adjustment and flight status, the flight control system can be adjusted in time when weight increases or other unexpected load changes occur, ensuring that the drone can continue to fly stably.

[0125] If the third data at this time is different from the first data, it means that the gimbal of the drone is in an abnormal state or is affected by airflow and cannot be stabilized, and the drone is judged to be abnormal.

[0126] At this time, the system generates a hovering instruction, controls the drone to perform a hovering operation, and obtains the fourth data of the drone's gimbal in the hovering state (angle and center of gravity data in the hovering state).

[0127] The third data is compared with the fourth data, and if the fourth data is different from the third data, a pan / tilt abnormality signal is generated.

[0128] Since the third data is the gimbal data obtained after the drone adjusts the propeller motor output power, and the fourth data is the gimbal data obtained while the drone is in a hovering state, by comparing the third and fourth data, it can be determined that the gimbal has not returned to its normal position. This is because the launch process may be affected by airflow, while the hovering process is affected by lateral airflow, making the judgment more accurate.

[0129] Because the parameters of the gimbal in the hovering state should be the same as the data after adjusting the drone, and the third data is different from the fourth data, it can be directly judged that the drone's gimbal is faulty, thus eliminating the influence of lateral airflow.

[0130] The third data point is the gimbal status recorded after the adjustment command is executed, while the fourth data point is the gimbal status recorded during hovering. During flight, external factors such as strong winds, aerodynamic disturbances, or an unbalanced drone load (e.g., additional equipment, cameras, etc.) may cause the gimbal to fail to maintain stability.

[0131] For example, when the drone carries additional payload, the gimbal may require additional adjustments to maintain stability. Even after executing the adjustment command, the gimbal may still deviate due to uneven payload or airflow changes during flight, resulting in inconsistencies between the third and fourth data.

[0132] Secondary calibration data is generated according to the fourth data and the first data, and the secondary calibration data is sent to the pitch axis motor, the roll axis motor, and the yaw axis motor of the gimbal to calibrate the angle of the gimbal.

[0133] Comparing the fourth data with the first data is to detect any significant changes to the gimbal during flight. If the fourth data is inconsistent with the first, it may indicate deviations or anomalies in the gimbal's angle, center of gravity, or sensor data during flight, potentially leading to unstable flight.

[0134] If the fourth data differs from the first data, the system needs to generate secondary calibration data. This indicates that some changes occurred during flight, causing the gimbal to deviate from its initial calibration state. To restore normal flight, the system compares the data, analyzes the differences, and generates new calibration data to ensure the gimbal angle and flight control system are stabilized.

[0135] The secondary calibration data is obtained by performing difference calculation on the parameters of the same type in the fourth data and the first data, and then generating secondary calibration data according to the difference result, and calibrating the gimbal according to the secondary correction data.

[0136] For example, the pitch tilt angle in the first data is 15°, the roll tilt angle is 5°, and the yaw axis tilt angle is 8°.

[0137] The fourth data has a pitch tilt angle of 10°, a roll tilt angle of 6°, and a yaw axis tilt angle of 4°.

[0138] The data parameters of the difference results are: the difference angle of pitch tilt is 5°, the difference angle of roll tilt is -1°, and the difference angle of yaw axis tilt is 4°.

[0139] Secondary calibration data is then generated based on the difference results.

[0140] The system calculates the difference between the fourth data (the actual state of the gimbal during flight) and the first data (the standard state of the gimbal before takeoff).

[0141] Based on these differences, the adjusted gimbal angle and center of gravity data are generated as the basis for calibration correction.

[0142] If the feedback data from the sensor also deviates, the system will make corrections based on the sensor data of the fourth data to ensure that the sensor provides accurate flight data.

[0143] When the secondary calibration data is generated, the system sends these calibration data to the corresponding motors of the gimbal to correct the angle.

[0144] By adjusting the motor control of the pitch, roll, and yaw axes, the angle of the gimbal will gradually adjust to a position consistent with the secondary calibration data.

[0145] Through secondary calibration, the angle of the gimbal is corrected to ensure that the gimbal can continue to remain stable and avoid image jitter or instability caused by angle deviation.

[0146] After adjusting the gimbal angle, the stability of the drone will be restored, and the flight control system can better control the flight attitude and ensure balance during flight.

[0147] Correct gimbal angle calibration ensures that the camera or sensor can maintain stable shooting, reducing image blur or shaking caused by abnormal flight conditions.

[0148] If the third and fourth data are the same, it means the fault has been repaired, there is no problem with the drone, and the gimbal is not faulty.

[0149] The third data represents the state of the gimbal after the adjustment command is executed. At this time, the gimbal will make certain attitude adjustments (such as pitch, roll, yaw, etc.) to restore to the flight target position.

[0150] The fourth data is the gimbal status data when the drone enters the hovering state. When hovering, the gimbal should remain stable and the posture will not change drastically.

[0151] If the third and fourth data are the same, it means that the gimbal adjustment goal has been successfully achieved, and the drone is not affected by external interference (such as wind, load changes, etc.) when hovering. The system control accuracy and gimbal stability are in line with expectations.

[0152] For example, during hovering, the gimbal's angle and center of gravity should remain within a stable range. If the adjustment command restores the gimbal from an unstable state to a normal flight attitude, and the gimbal remains consistent during hovering, then there are no abnormalities during flight and the gimbal is operating normally.

[0153] It should be noted that the third data and the first data:

[0154] Comparison of the gimbal state after adjustment and the calibration state before takeoff

[0155] Third data: The state data of the gimbal after executing the adjustment command. After the adjustment command is executed, the gimbal's attitude should return to the predetermined state or target position.

[0156] First data: calibration data before gimbal takes off.

[0157] The third data is consistent with the first data: the gimbal adjustment was successful and restored to the state consistent with the pre-takeoff calibration. The system's gimbal adjustment is accurate and effective, and the flight control system is working normally without any abnormalities.

[0158] The third data is inconsistent with the first data: The gimbal adjustment failed or is inaccurate. The gimbal has not returned to its pre-calibrated state. This may indicate a hardware failure, sensor deviation, or an issue with the adjustment command. The system has detected an anomaly and requires further adjustment or inspection of the gimbal.

[0159] The third and fourth data:

[0160] The third and fourth data points are consistent: the gimbal adjustment was successful, and the adjusted attitude is stable in the hover state. The flight control system is working normally, the gimbal attitude is stable and as expected, and the drone can continue to fly normally.

[0161] The third and fourth data values ​​are inconsistent: The gimbal failed to stabilize in hover after adjustment. This may be due to external factors (such as airflow, uneven load), or gimbal hardware failure. If an anomaly occurs during flight, further inspection of the gimbal or flight control system is required. The system can trigger an anomaly warning and take remedial measures.

[0162]

[0163] In at least one embodiment of the present application, the method further includes:

[0164] The first data includes angle data during gimbal calibration, center of gravity data during calibration, and sensor data;

[0165] The second data is the angle data, center of gravity data and sensor data of the gimbal during the vertical ascent of the UAV.

[0166] In this embodiment, the first data is the status data recorded during the gimbal calibration before the drone takes off, which mainly includes the following three parts:

[0167] Gimbal angle data: This refers to the angles of the gimbal's various axes (such as pitch, roll, and yaw), which determine the gimbal's position and orientation in three-dimensional space. During gimbal calibration, the system records this angle data to determine the gimbal's initial state.

[0168] Center of Gravity (CG) data refers to the overall CG position of the drone, specifically the gimbal's CG during installation. This gimbal's CG data is crucial for flight control and affects the drone's flight stability. If additional equipment is installed or the gimbal's position is changed, this shift in CG will affect flight balance and stability. Therefore, CG data during calibration provides a baseline for subsequent flight.

[0169] Sensor data: This includes status data from sensors such as the gyroscope, accelerometer, and magnetometer. This sensor data helps the system detect the drone's motion and environmental changes. During calibration, the system records the initial sensor states to ensure that in-flight data can be compared with this baseline.

[0170] The second data is the gimbal status data recorded during the vertical ascent of the drone, which mainly includes the following parts:

[0171] Gimbal Angle Data: This is the same as the gimbal angle data in the first data set, but the angle data in the second data set is measured in real time during flight. Since the drone may be affected by external factors during flight (such as wind, uneven thrust, and load changes), the gimbal angle data may vary. By recording this data, you can determine whether the gimbal remains stable during flight.

[0172] Center of Gravity Data: The second data point reflects the center of gravity changes during the flight. Although the center of gravity does not change drastically during flight, it may change slightly due to the addition of loads or payloads (such as additional equipment, sensors, etc.), helping to identify any imbalance or loading issues during flight.

[0173] Sensor data: During flight, the drone's sensors monitor and provide real-time feedback on its motion, flight attitude, and changes in the external environment (such as airflow and air pressure). The sensor data in the secondary data typically includes the real-time status of sensors such as gyroscopes, accelerometers, and magnetometers.

[0174] A PTZ-based fault monitoring system 100 is applied to any of the above-mentioned PTZ-based fault monitoring methods, and the system includes:

[0175] The gimbal parameter acquisition module 110 is used to acquire first data during gimbal calibration before takeoff and second data during the gimbal flight;

[0176] a comparison module 120 , comparing the first data with the second data;

[0177] A gyroscope parameter acquisition module 140 is used to obtain gyroscope data information;

[0178] An adjustment command generating module 130 generates an adjustment command based on the data information of the gyroscope;

[0179] an execution module 150 for executing adjustment commands to control the UAV;

[0180] The system performs the following steps:

[0181] Get the first data of gimbal calibration before takeoff;

[0182] Obtain the second data of the gimbal during the flight;

[0183] comparing the first data with the second data;

[0184] If the first data is different from the second data, it is determined to be a flight failure, and the data information of the drone's gyroscope is obtained;

[0185] generating adjustment data according to the data information of the drone gyroscope, and generating an adjustment command according to the adjustment data;

[0186] The adjustment command is executed to enable each blade drive motor of the drone to adjust the output power according to the adjustment data to control the balance of the drone.

[0187] Please refer to Figure 3 In this embodiment, the system 100 obtains the first data of the gimbal calibration before takeoff and the second data of the gimbal during the ascent through the gimbal parameter acquisition module 110. The system 100 compares the first data with the second data through the comparison module 120. If the first data is different from the second data, it indicates that there is a flight fault, and a flight fault signal is generated.

[0188] The system then obtains the axial error data of the gyroscope on the drone through the gyroscope parameter acquisition module 140 to obtain the data information of the gyroscope. The system parses the axial error data in the gyroscope data information based on the adjustment command generation module 130 to generate adjustment data, generates an adjustment command based on the adjustment data, and sends it to the drone.

[0189] The system executes the adjustment command through the execution module 150 and configures adjustment parameters for each blade drive motor to adjust the output power of each blade drive motor to control the balance of the drone.

[0190] Through real-time monitoring and fault detection, the stability of the gimbal and drone is ensured to avoid loss of control or image jitter caused by faults during flight.

[0191] By automatically adjusting the balance and posture control, the operator's complex operations are reduced and the ease of use is improved.

[0192] It should be noted that the PTZ parameter acquisition module 110 is used to acquire first data, second data, third data and fourth data.

[0193] The comparison module 120 is used to compare the first data with the second data, the first data with the third data, and the third data with the fourth data.

[0194] In one embodiment, a computer device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the following steps:

[0195] The system performs the following steps:

[0196] Get the first data of gimbal calibration before takeoff;

[0197] Obtain the second data of the gimbal during the flight;

[0198] comparing the first data with the second data;

[0199] If the first data is different from the second data, it is determined to be a flight failure, and the data information of the drone's gyroscope is obtained;

[0200] generating adjustment data according to the data information of the drone gyroscope, and generating an adjustment command according to the adjustment data;

[0201] The adjustment command is executed to enable each blade drive motor of the drone to adjust the output power according to the adjustment data to control the balance of the drone.

[0202] In this embodiment, the system obtains the first data when the gimbal is calibrated before takeoff and the second data of the gimbal during the ascent. The system compares the first data with the second data. If the first data is different from the second data, it indicates that there is a flight fault, and a flight fault signal is generated. The flight fault signal at this time may be that the drone has added external equipment or the drone is affected by airflow during the ascent.

[0203] The system then obtains the axial error data of the gyroscope on the drone, obtains the data information of the gyroscope, generates adjustment data based on the axial error data of the drone, generates adjustment commands based on the adjustment data, and sends them to the drone.

[0204] The drone executes the adjustment command and configures adjustment parameters for each blade drive motor to adjust the output power of each blade drive motor to control the drone to be in a balanced state (level).

[0205] Through real-time monitoring and fault detection, the stability of the gimbal and drone is ensured to avoid loss of control or image jitter caused by faults during flight.

[0206] By automatically adjusting the balance and posture control, the operator's complex operations are reduced and the ease of use is improved.

[0207] Figure 4 FIG1 shows an internal structure diagram of a computer device in an embodiment. The computer device can be a terminal or a server. Figure 4 As shown, the computer device includes a processor, a memory, and a network interface connected via a system bus. The memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program. When the computer program is executed by the processor, the processor can implement a fault monitoring method based on a pan-tilt platform. The internal memory may also store a computer program. When the computer program is executed by the processor, the processor can implement a fault monitoring method based on a pan-tilt platform. Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0208] In one embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the processor performs the following steps:

[0209] Get the first data of gimbal calibration before takeoff;

[0210] Obtain the second data of the gimbal during the flight;

[0211] comparing the first data with the second data;

[0212] If the first data is different from the second data, it is determined to be a flight failure, and the data information of the drone's gyroscope is obtained;

[0213] generating adjustment data according to the data information of the drone gyroscope, and generating an adjustment command according to the adjustment data;

[0214] The adjustment command is executed to enable each blade drive motor of the drone to adjust the output power according to the adjustment data to control the balance of the drone.

[0215] In this embodiment, the system obtains the first data when the gimbal is calibrated before takeoff and the second data of the gimbal during the ascent. The system compares the first data with the second data. If the first data is different from the second data, it indicates that there is a flight fault, and a flight fault signal is generated. The flight fault signal at this time may be that the drone has added external equipment or the drone is affected by airflow during the ascent.

[0216] The system then obtains the axial error data of the gyroscope on the drone, obtains the data information of the gyroscope, generates adjustment data based on the axial error data of the drone, generates adjustment commands based on the adjustment data, and sends them to the drone.

[0217] The drone executes the adjustment command and configures adjustment parameters for each blade drive motor to adjust the output power of each blade drive motor to control the drone to be in a balanced state (level).

[0218] Through real-time monitoring and fault detection, the stability of the gimbal and drone is ensured to avoid loss of control or image jitter caused by faults during flight.

[0219] By automatically adjusting the balance and posture control, the operator's complex operations are reduced and the ease of use is improved.

[0220] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0221] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0222] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A fault monitoring method based on a pan-tilt system, characterized in that: The method comprises: Acquire first data during gimbal calibration before takeoff, the first data including angle data, center of gravity data, and sensor data during gimbal calibration; Acquire second data of the gimbal during the vertical flight, wherein the second data includes angle data, center of gravity data, and sensor data of the gimbal during the vertical flight of the UAV; comparing the first data with the second data; If the first data is different from the second data, it is determined to be a flight failure, and the data information of the drone's gyroscope is obtained; generating adjustment data according to the data information of the drone gyroscope, and generating an adjustment command according to the adjustment data; The adjustment command is executed to enable each blade drive motor of the drone to adjust the output power according to the adjustment data to control the balance of the drone.

2. The fault monitoring method based on a PTZ according to claim 1, characterized in that: The method further comprises: Acquire third data of the pan / tilt platform after the adjustment command is executed, wherein the third data includes angle data after adjustment and status data of the pan / tilt platform motor; comparing the third data with the first data; If the third data is different from the first data, it is determined that the drone is abnormal, and a hovering instruction is generated and executed to control the drone to hover.

3. The fault monitoring method based on a PTZ according to claim 2, characterized in that: The method further comprises: If the third data is the same as the first data, it is determined that the drone has gained weight, drone operation modification data is generated according to the adjustment data, and the drone is controlled to fly according to the drone operation modification data.

4. The fault monitoring method based on a PTZ according to claim 2, characterized in that: The method further comprises: Acquire fourth data of the gimbal of the drone in a hovering state, wherein the fourth data is angle and center of gravity data of the drone in the hovering state; The fourth data is compared with the third data, and if the fourth data is different from the third data, a pan / tilt abnormality signal is generated.

5. The fault monitoring method based on a PTZ according to claim 4, characterized in that: The method further comprises: Secondary calibration data is generated according to the fourth data and the first data, and the secondary calibration data is sent to the pitch axis motor, the roll axis motor, and the yaw axis motor of the gimbal to calibrate the angle of the gimbal.

6. The fault monitoring method based on a PTZ according to claim 4, characterized in that: The method further comprises: If the fourth data is the same as the third data, it is determined that the drone is operating normally.

7. A PTZ-based fault monitoring system, applied to the PTZ-based fault monitoring method according to any one of claims 1 to 6, characterized in that: The system comprises: A gimbal parameter acquisition module, configured to acquire first data during gimbal calibration before takeoff and second data during the gimbal's flight; a comparison module, comparing the first data with the second data; Gyroscope parameter acquisition module, used to obtain gyroscope data information; An adjustment command generation module generates an adjustment command based on the data information of the gyroscope; The execution module is used to execute adjustment commands to control the drone.

8. A computer-readable storage medium, characterized in that A computer program is stored, and when the computer program is executed by a processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 6.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method according to any one of claims 1 to 6.

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