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

Abstract

The embodiment of the invention discloses a fault monitoring method and system based on a cradle head, a medium and equipment, the system obtains first data during cradle head calibration before take-off and second data of the cradle head in the lift-off process, the system compares the first data with the second data, and if the first data and the second data are different, the cradle head is monitored. If yes, the flight has a fault, and a flight fault signal is generated. And then the system obtains axial error data of the gyroscope on the unmanned aerial vehicle, obtains data information of the gyroscope, generates adjustment data according to the axial error data of the unmanned aerial vehicle, generates an adjustment command according to the adjustment data, and sends the adjustment command to the unmanned aerial vehicle. And the unmanned aerial vehicle executes the adjustment command and configures adjustment parameters for each blade driving motor to adjust the output power of each blade driving motor so as to control the balance of the unmanned aerial vehicle. Through real-time monitoring and fault detection, the stability of the holder and the unmanned aerial vehicle is ensured, and out-of-control or picture jitter caused by faults in the flight process 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 device. Background Art

[0002] The gimbal is one of the important components of the drone system. It is mainly used to stabilize the camera or sensor so that it can keep the picture stable and adjust the shooting angle during flight. Whether it is professional aerial photography, terrain mapping, or industrial applications, the gimbal plays a key role.

[0003] The original PTZ control method was very simple, and only used current to drive the motor to achieve basic movement. The angle adjustment of the motor depends entirely on the input current and time, without a feedback mechanism, which is the so-called open-loop control. The disadvantage of this method is that it cannot accurately control the actual position or speed of the motor. Due to external interference (such as wind force, load changes) or hardware errors, the motor output is easy to deviate from expectations. The stability is poor and it is difficult to meet the needs of complex applications.

[0004] With the introduction of stepper motors, the stepper motor drives the rotor to rotate step by step through the stator coil, with a fixed angle increment for each step. The gimbal control determines 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 disturbances. 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] The speed encoder is introduced to realize 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 has very sophisticated control over itself, its own status is limited to the encoder or gyroscope.

[0009] For example, during the use of a drone, some users will add some external module structures at different positions of the drone to change some requirements of the drone during use (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 exchange and 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 sway, making it impossible to transmit the picture, affecting the imaging of the picture.

[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 diagnosis process, which in turn renders the drone's gimbal unusable. Summary of the invention

[0011] Based on this, it is necessary to propose a pan-tilt-based fault monitoring method, system, medium and equipment 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] Acquire 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 gyroscope is obtained;

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

[0018] The adjustment command is executed so that each blade driving motor of the drone adjusts 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 gimbal 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 parameters during calibration, and sensor parameters;

[0027] The second data is the angle data, center of gravity parameters and sensor parameters of the gimbal during the vertical launch 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 is applied to any of the PTZ-based fault monitoring methods described above, the system comprising:

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

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

[0038] A gyroscope parameter acquisition module is used to obtain gyroscope data information;

[0039] An adjustment command generation module generates an adjustment command according to 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] Acquire 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 gyroscope is obtained;

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

[0047] The adjustment command is executed so that each blade driving motor of the drone adjusts 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] Acquire 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 gyroscope is obtained;

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

[0054] The adjustment command is executed so that each blade driving motor of the drone adjusts 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] Acquire 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 gyroscope is obtained;

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

[0061] The adjustment command is executed so that each blade driving motor of the drone adjusts 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 when the gimbal is calibrated before takeoff and second data of the gimbal 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] Then the system obtains the axial error data of the gyroscope on the drone, obtains the data information of the gyroscope, generates adjustment data according to the axial error data of the drone, generates adjustment commands according to 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 drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 creative work.

[0069] in:

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

[0071] Figure 2 is a flow chart of a fault monitoring method based on a pan / tilt platform in another embodiment;

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

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

[0074] in:

[0075] 100. A fault monitoring system based on a pan-tilt system; 110. A pan-tilt system parameter acquisition module; 120. A comparison module; 130. An adjustment command generation module; 140. A gyroscope parameter acquisition module; 150. An execution module. DETAILED DESCRIPTION

[0076] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are 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 of 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 is different from the second data, it is determined to be a flight failure, and data information of the drone gyroscope is obtained;

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

[0083] S106, executing the adjustment command so that each blade driving motor of the drone adjusts the output power according to the adjustment data to control the balance of the drone.

[0084] Please refer to Figure 1 to Figure 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 means 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] Then the system obtains the axial error data of the gyroscope on the drone, obtains the data information of the gyroscope, generates adjustment data according to the axial error data of the drone, generates adjustment commands according to 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 (horizontal).

[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, roll axis motor, yaw axis motor data, etc.

[0091] The second data is the parameter data of the gimbal during the vertical take-off 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 take-off.

[0092] It should be further explained that real-time flight data is obtained, which 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, yaw angle) and status (such as the output power of the gimbal motor)).

[0093] The first data before the flight (the first data, such as the angle and the center of gravity parameters during calibration) and the second data in the real-time flight (the second data, such as the angle and the center of gravity parameters during calibration) are compared.

[0094] By comparing the difference between the two, the attitude deviation generated during the flight can be identified. 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 attitude deviation and flight requirements, calculate the adjustments needed to the motor output power for each axis.

[0099] For example, the adjustment parameters are generated according to PID control.

[0100] When the first data is consistent with the second data, the gimbal has maintained the expected stability and attitude during flight after the pre-takeoff calibration. There is no significant interference during flight, and the gimbal is not affected by external factors. At this point, the system can continue to perform the mission and the gimbal is working normally.

[0101] The first data is inconsistent with the second data. The gimbal failed to maintain the original stable state during flight. There may be external interference (such as wind force, load imbalance, etc.) or gimbal adjustment failure (such as motor or sensor problem). The system determines that it is a flight failure and requires further investigation. It may be necessary to adjust the gimbal or perform 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, and the difference calculation is performed based on the adjustment angle parameters and the gimbal data 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 gimbal 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 Figure 1 to Figure 2 In this embodiment, when the adjustment of the drone 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 state 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 gimbal status after adjustment is consistent with the gimbal calibration status before takeoff, and there is no gimbal adjustment problem. This means that the gimbal itself is working properly and the adjustment is accurate. This means that the drone has gained weight, that is, during the flight, some additional loads (such as additional equipment, sensors, cameras, etc.) have increased the total weight of the drone, causing the gimbal to need more adjustments and compensation.

[0119] It should be noted that the adjustment command is an instruction to control the drone to achieve balance in flight, that is, according to the data information of the gyroscope, the gyroscope is adjusted to a horizontal state after the adjustment command is adjusted, so as to avoid 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 center of gravity of the drone to change, so the flight attitude may need to be adjusted to ensure that the drone remains level or flies at a predetermined angle.

[0122] Flying after gaining weight may affect flight speed, range, energy consumption, etc. The control system may need to adjust the flight plan accordingly.

[0123] When 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 there is weight gain or other unexpected load changes to ensure 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 command, controls the drone to perform a hovering operation, and obtains the fourth data of the gimbal of the drone in the hovering state (angle and center of gravity parameters 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 output motor power of the propeller blades, and the fourth data is the gimbal data of the drone in the hovering state, by comparing the third data and the fourth data, it can be determined that the gimbal has not returned to the normal position. Because the process of taking off may be affected by airflow, and the process of hovering will be affected by lateral airflow, the judgment result is 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 gimbal of the drone is faulty, so as to eliminate the influence of lateral airflow.

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

[0131] For example, when the drone carries additional load, the gimbal may need additional adjustments to maintain stability. Even if the adjustment command is executed, the gimbal may still deviate due to uneven load or airflow changes during flight, resulting in inconsistency 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] The purpose of comparing the fourth data with the first data is to detect whether the gimbal has undergone significant changes during flight. If the fourth data is inconsistent with the first data, it may indicate that the gimbal's angle, center of gravity or sensor data has deviated or become abnormal during flight, which may lead to unstable flight.

[0134] When the fourth data differs from the first data, the system needs to generate secondary calibration data. This means that something has changed during the flight, causing the gimbal to be inconsistent with the initial calibration state. In order to restore normal flight status, the system generates new calibration data by comparing the data, analyzing the differences, and ensuring that the gimbal angle and flight control system can be stabilized again.

[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 the 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 pitch tilt angle in the fourth data is 10°, the roll tilt angle is 6°, and the yaw axis tilt angle is 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 parameters 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] The correct angle calibration of the gimbal ensures that the camera or sensor can maintain stable shooting and reduce image blur or shaking caused by abnormal flight status.

[0148] If the third data is the same as the fourth data, it means the fault has been fixed, there is no problem with the drone, and the gimbal has no fault.

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

[0152] For example, during the hovering process, the gimbal's angle, center of gravity parameters, etc. should be maintained within a stable value range. If the adjustment command restores the gimbal from an unstable state to a normal flight attitude, and the gimbal state remains consistent during the hovering process, then it means that there is no abnormality during the flight and the gimbal is operating normally.

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

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

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

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

[0157] The third data is consistent with the first data: the gimbal adjustment is successful and has returned to the state consistent with the pre-takeoff calibration. The system's adjustment of the gimbal 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 was inaccurate, and the gimbal failed to return to the predetermined calibration state. There may be a hardware failure, sensor deviation, or adjustment command problem. The system detected an abnormality and further adjustment or inspection of the gimbal is required.

[0159] The third and fourth data:

[0160] The third data is consistent with the fourth data: the gimbal adjustment is successful, and the adjusted attitude is stably maintained in the hovering state. The flight control system works normally, the gimbal attitude is stable and in line with expectations, and the drone can continue to fly normally at this time.

[0161] The third and fourth data are inconsistent: the gimbal fails to stabilize in the hovering state after adjustment. This may be caused by external factors (such as airflow, uneven load) or gimbal hardware failure. If an abnormality occurs during flight, further inspection of the gimbal or flight control system is required. The system can trigger an abnormality 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 parameters during calibration, and sensor parameters;

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

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

[0167] Gimbal angle data: refers to the angles of the gimbal's axes (such as pitch, roll, and yaw), which determine the gimbal's position and direction in three-dimensional space. During the gimbal calibration process, the system will record these angle data to determine the gimbal's initial state.

[0168] Center of gravity parameters: refers to the center of gravity position of the drone as a whole, especially the center of gravity of the gimbal during installation. The center of gravity parameters of the gimbal are crucial in flight control and affect the flight stability of the drone. If additional equipment is installed or the position of the gimbal is changed, the change in the center of gravity will affect the balance and stability of the flight. Therefore, the center of gravity data during calibration provides a benchmark for subsequent flights.

[0169] Sensor parameters: including status data of gyroscopes, accelerometers, magnetometers, etc. These sensor data help the system perceive the motion state of the drone and changes in the external environment. During calibration, the system records the initial state of the sensor to ensure that the data during flight can be compared with these baseline data.

[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: Same as the gimbal angle data in the first data, but the angle data in the second data is measured in real time during flight. Since the drone may be affected by external factors (such as wind, uneven thrust, load changes, etc.) during flight, the gimbal angle data will change. By recording this data, you can understand whether the gimbal remains stable during flight.

[0172] Center of gravity parameters: The center of gravity parameters in the second data reflect the change of the center of gravity of the drone during the launch process. Although the center of gravity will not change drastically during flight, due to the possible increase of load or payload (such as additional equipment, sensors, etc.), the center of gravity may change slightly to help identify whether there is an imbalance or load problem during flight.

[0173] Sensor parameters: During the flight of the drone, the sensor will monitor and feedback the drone's motion state, flight attitude and changes in the external environment (such as airflow, air pressure, etc.) in real time. The sensor parameters in the second data usually include 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 PTZ-based fault monitoring methods described above, and the system comprises:

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

[0176] A comparison module 120 compares the first data with the second data;

[0177] A gyroscope parameter acquisition module 140 is used to acquire data information of the gyroscope;

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

[0179] An execution module 150, used for executing the adjustment command to control the drone;

[0180] The system performs the following steps:

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

[0182] Acquire 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 gyroscope is obtained;

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

[0186] The adjustment command is executed so that each blade driving motor of the drone adjusts 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 launch process 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 fault in the flight, and a flight fault signal is generated.

[0188] Then the system 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 data information of the gyroscope according to the adjustment command generation module 130 to generate adjustment data, generates an adjustment command according to the adjustment data, and sends it to the drone.

[0189] The system executes the adjustment command through the execution module 150 and configures the 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] Acquire 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 gyroscope is obtained;

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

[0201] The adjustment command is executed so that each blade driving motor of the drone adjusts 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] Then the system obtains the axial error data of the gyroscope on the drone, obtains the data information of the gyroscope, generates adjustment data according to the axial error data of the drone, generates adjustment commands according to 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 (horizontal).

[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 FIG. 1 shows an internal structure diagram of a computer device in an embodiment. The computer device may 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 may 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 may implement a fault monitoring method based on a pan-tilt platform. Those skilled in the art will appreciate 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 those shown in the figure, or combine certain components, or have a different arrangement of components.

[0208] In one embodiment, a computer-readable storage medium is provided, storing a computer program, wherein 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] Acquire 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 gyroscope is obtained;

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

[0214] The adjustment command is executed so that each blade driving motor of the drone adjusts 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] Then the system obtains the axial error data of the gyroscope on the drone, obtains the data information of the gyroscope, generates adjustment data according to the axial error data of the drone, generates adjustment commands according to 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 (horizontal).

[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 can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and 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 may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many 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 may 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-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A fault monitoring method based on a pan-tilt system, characterized in that: The method comprises: Get the first data of gimbal calibration before takeoff; Acquire the second data of the gimbal during the flight; 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 gyroscope is obtained; Generate adjustment data according to the data information of the drone gyroscope, and generate an adjustment command according to the adjustment data; The adjustment command is executed so that each blade driving motor of the drone adjusts 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 gimbal after the adjustment command is executed; 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 1, characterized in that: The method further comprises: The first data includes angle data during gimbal calibration, center of gravity parameters during calibration, and sensor parameters; The second data is the angle data, center of gravity parameters and sensor parameters of the gimbal during the vertical launch of the UAV.

5. The fault monitoring method based on a PTZ according to claim 2, characterized in that: The method further comprises: Get the fourth data of the gimbal of the drone in 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.

6. The fault monitoring method based on a PTZ according to claim 5, 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.

7. The fault monitoring method based on a PTZ according to claim 5, 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.

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

9. 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 7.

10. 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 7.

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