Deflection angle identification method and system, holder and storage medium

Abstract

The invention discloses a deflection angle identification method and system, a cradle head and a storage medium, and relates to the technical field of deflection angle identification, and the method comprises the steps: calculating an electromagnetic interference coefficient of a target cradle head through obtaining electromagnetic signals around the target cradle head; obtaining vibration data of the target holder and calculating a vibration interference coefficient of the target holder; acquiring temperature data of the target holder and calculating a temperature fluctuation coefficient of the target holder; the interference coefficient is obtained according to the electromagnetic interference coefficient, the vibration interference coefficient and the temperature fluctuation coefficient, the interference degree of the target holder is judged by combining a preset interference coefficient threshold value, the deflection angle of the target holder is optimized and recognized, the recognition result of the deflection angle of the holder can be judged, the deflection angle of the target holder is optimized and recognized, and the recognition accuracy of the target holder is improved. And accurate identification of the deflection angle of the target holder is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of deflection angle recognition, and in particular to a deflection angle recognition method, system, pan / tilt platform and storage medium. Background Art

[0002] The deflection angle recognition method of the gimbal is usually achieved through built-in sensors such as gyroscopes and accelerometers. These sensors can monitor the movement of the gimbal in real time and measure its angle changes in each axis. By combining with the feedback from the gimbal control system, the precise deflection angle can be calculated. At the same time, some high-precision gimbals also use optical encoders or magnetometers to assist in detection to improve the accuracy and stability of angle measurement. These data are fed back to the control system through the transmission system to achieve precise control and angle correction of the gimbal.

[0003] In some special industrial environments or outdoor applications, the gimbal may face interference from various factors, which will affect the normal operation of the sensor, especially in sensitive applications such as Hall effect sensors and accelerometers, which may cause inaccurate recognition of the gimbal's deflection angle. Summary of the invention

[0004] The purpose of the present invention is to solve the above-mentioned problems and provide a deflection angle recognition method, system, pan / tilt head and storage medium.

[0005] In a first aspect of the present invention, a deflection angle identification method is first proposed, the method comprising:

[0006] Acquire electromagnetic signals around the target gimbal, and calculate the electromagnetic interference coefficient of the target gimbal according to the electromagnetic signals;

[0007] Acquire the vibration data of the target gimbal, and calculate the vibration interference coefficient of the target gimbal according to the vibration data;

[0008] Acquire the temperature data of the target gimbal, and calculate the temperature fluctuation coefficient of the target gimbal according to the temperature data;

[0009] The interference coefficient is obtained according to the electromagnetic interference coefficient, the vibration interference coefficient and the temperature fluctuation coefficient, and the interference degree of the target gimbal is judged in combination with the preset interference coefficient threshold, and the deflection angle of the target gimbal is optimized and identified.

[0010] Optionally, calculating the electromagnetic interference coefficient of the target gimbal according to the electromagnetic signal includes:

[0011] The electromagnetic signals around the target gimbal at multiple consecutive moments are marked as B(t), where t = 1, 2, 3, 4, ..., Z, where Z is a positive integer and Z represents the number of electromagnetic signals;

[0012] Morlet wavelet is used to perform continuous wavelet transform on the electromagnetic interference signal B(t) at each moment. Through continuous wavelet transform, the electromagnetic interference signal is decomposed into several scales, and the result calculated by wavelet transform at each scale is called wavelet coefficient;

[0013] According to the calculated wavelet coefficients, the energy of the wavelet coefficients at each scale is calculated, and the energy of different scales is weighted summed to obtain the comprehensive energy feature F total ;

[0014] Calculate the electromagnetic interference index at each moment, the calculation expression is: BK(t) = F total Where, BK(t) is the electromagnetic interference index;

[0015] Add the electromagnetic interference index BK(t) at different times to get the electromagnetic interference coefficient. The calculation formula is: Where JM is the electromagnetic interference coefficient.

[0016] Optionally, calculating the vibration interference coefficient of the target gimbal according to the vibration data includes:

[0017] The vibration amplitude of the target gimbal at multiple consecutive moments, and the vibration amplitude at each moment is marked as R e , where e = 1, 2, 3, 4, ..., d, d is a positive integer, and d represents the total number of vibration amplitudes;

[0018] Calculate the average vibration amplitude of the target gimbal using the following formula: Where Qs is the mean value of the vibration amplitude of the target gimbal;

[0019] Calculate the vibration interference coefficient, the calculation formula is: ED = m1·Qs+m2·max(R1, R2, R3....R e ), where ED is the vibration interference coefficient, and m1 and m2 are the preset weight coefficients.

[0020] Optionally, calculating the temperature fluctuation coefficient of the target gimbal according to the temperature data includes:

[0021] The temperature value of the target gimbal at multiple consecutive moments, and mark the temperature value at each moment as E u , u represents the order number of the temperature value, u = 1, 2, 3, 4, ..., p, p is the total number of the above temperature values, and p is a positive integer;

[0022] Calculate the mean of the temperature values ​​using the formula:

[0023] Calculate the temperature fluctuation coefficient using the following formula:

[0024]

[0025] Where YK is the temperature fluctuation coefficient.

[0026] Optionally, the interference coefficient obtained according to the electromagnetic interference coefficient, the vibration interference coefficient and the temperature fluctuation coefficient includes:

[0027] DCG=f1×JM+1+f2×ED+f3×YK

[0028] Wherein, DCG is the interference coefficient, JM, ED, and YK are the electromagnetic interference coefficient, vibration interference coefficient, and temperature fluctuation coefficient, respectively; f1, f2, and f3 are the preset proportional coefficients of JM, ED, and YK, respectively, and f1, f2, and f3 are all greater than 0.

[0029] Optionally, judging the interference degree of the target gimbal in combination with a preset interference coefficient threshold includes:

[0030] The interference coefficient is compared with a preset interference coefficient threshold. If the interference coefficient is less than the preset interference coefficient threshold, it means that the interference degree of the target gimbal is relatively light, and the deflection angle of the target gimbal identified by the Hall effect sensor and accelerometer inside the target gimbal is accurate;

[0031] If the interference coefficient is not less than the preset interference coefficient threshold, it means that the target gimbal is severely interfered with. The target gimbal deflection angle identified by the Hall effect sensor and accelerometer inside the target gimbal is inaccurate. The real-time data of the Hall effect sensor and accelerometer are processed through the Kalman filtering algorithm, and the target gimbal deflection angle is identified based on the processed data.

[0032] In a second aspect of the present invention, a deflection angle identification system is provided, comprising: the device comprising:

[0033] The system comprises:

[0034] Electromagnetic interference module: obtains electromagnetic signals around the target gimbal and calculates the electromagnetic interference coefficient of the target gimbal based on the electromagnetic signals;

[0035] Vibration interference module: obtains the vibration data of the target gimbal and calculates the vibration interference coefficient of the target gimbal based on the vibration data;

[0036] Temperature fluctuation module: obtains the temperature data of the target gimbal and calculates the temperature fluctuation coefficient of the target gimbal based on the temperature data;

[0037] Deflection angle identification module: The interference coefficient is obtained according to the electromagnetic interference coefficient, vibration interference coefficient and temperature fluctuation coefficient, and the interference degree of the target gimbal is judged in combination with the preset interference coefficient threshold, and the deflection angle of the target gimbal is optimized and identified.

[0038] In a third aspect of the implementation of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, any of the above-mentioned methods is implemented.

[0039] Beneficial effects of the present invention:

[0040] The present invention proposes a deflection angle recognition method, system, pan / tilt and storage medium, which obtain electromagnetic signals around a target pan / tilt to calculate the electromagnetic interference coefficient of the target pan / tilt; obtain vibration data of the target pan / tilt to calculate the vibration interference coefficient of the target pan / tilt; obtain temperature data of the target pan / tilt to calculate the temperature fluctuation coefficient of the target pan / tilt; obtain an interference coefficient based on the electromagnetic interference coefficient, the vibration interference coefficient and the temperature fluctuation coefficient, and judge the interference degree of the target pan / tilt in combination with a preset interference coefficient threshold, and optimize and identify the deflection angle of the target pan / tilt, which can judge the result of pan / tilt deflection angle recognition, optimize and identify the deflection angle of the target pan / tilt, and ensure accurate recognition of the deflection angle of the target pan / tilt. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The present invention will be further described below in conjunction with the accompanying drawings.

[0042] Figure 1 is a flow chart of the deflection angle identification method;

[0043] Figure 2 It is the framework diagram of the deflection angle recognition system;

[0044] Figure 3 A diagram of the framework for identifying the gimbal's deflection angle. DETAILED DESCRIPTION

[0045] 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.

[0046] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0047] The embodiment of the present invention provides a method for identifying a deflection angle. Figure 1 , Figure 1 A flow chart of a deflection angle identification method provided by an embodiment of the present invention. The method comprises the following steps:

[0048] Acquire electromagnetic signals around the target gimbal, and calculate the electromagnetic interference coefficient of the target gimbal according to the electromagnetic signals;

[0049] Obtaining vibration data of the target gimbal, and calculating the vibration interference coefficient of the target gimbal according to the vibration data;

[0050] Acquire the temperature data of the target gimbal, and calculate the temperature fluctuation coefficient of the target gimbal according to the temperature data;

[0051] The interference coefficient is obtained according to the electromagnetic interference coefficient, the vibration interference coefficient and the temperature fluctuation coefficient, and the interference degree of the target gimbal is judged in combination with the preset interference coefficient threshold, and the deflection angle of the target gimbal is optimized and identified.

[0052] Based on the deflection angle recognition method provided by the embodiment of the present invention, the above steps can be used to judge the result of the gimbal deflection angle recognition, and optimize the recognition of the deflection angle of the target gimbal, thereby ensuring accurate recognition of the deflection angle of the target gimbal.

[0053] In one embodiment, acquiring electromagnetic signals around a target gimbal and calculating an electromagnetic interference coefficient of the target gimbal according to the electromagnetic signals includes:

[0054] The electromagnetic signals around the target gimbal at multiple consecutive moments are marked as B(t), where t = 1, 2, 3, 4, ..., Z, where Z is a positive integer and Z represents the number of electromagnetic signals;

[0055] Morlet wavelet is used to perform continuous wavelet transform on the electromagnetic interference signal B(t) at each moment. Through continuous wavelet transform (CWT), the electromagnetic interference signal is decomposed into several scales, and the result calculated by wavelet transform at each scale is called wavelet coefficient; among them, continuous wavelet transform is realized by convolution, and its calculation formula is as follows: Where x(t) is the input signal, ψ(t) is the selected wavelet basis function, a is the scale parameter used to adjust the scale of the wavelet basis function; b is the translation parameter used to adjust the position of the wavelet basis function; t represents the time coordinate of the signal, that is, the position on the time axis;

[0056] The result calculated by wavelet transform at each scale is called wavelet coefficient;

[0057] According to the calculated wavelet coefficients, the energy of the wavelet coefficients at each scale is calculated, and the energy of different scales is weighted summed to obtain the comprehensive energy feature F total ; The calculation formula is as follows: Where F(a) is the energy at scale a, CWT(a,b) is the wavelet coefficient; F total =∑ a wa ·F(a), where w a is the weight of scale a; weight a is used to reflect the importance of different scales to the comprehensive energy characteristics. If some scales are more critical to the representation of the signal, they may be given larger weights. The choice of weight usually depends on the nature of the signal and the purpose of the analysis;

[0058] Calculate the electromagnetic interference index at each moment, the calculation expression is: BK(t) = F total Where, BK(t) is the electromagnetic interference index;

[0059] Add the electromagnetic interference index BK(t) at different times to get the electromagnetic interference coefficient. The calculation formula is: Where JM is the electromagnetic interference coefficient.

[0060] Calculate the electromagnetic interference index at each moment, the calculation expression is: BK(t) = F total Where, BK(t) is the electromagnetic interference index;

[0061] Add the electromagnetic interference index BK(t) at different times to get the electromagnetic interference coefficient. The calculation formula is: Where JM is the electromagnetic interference coefficient.

[0062] It should be noted that the electromagnetic signals around the target gimbal can be obtained through the electromagnetic sensor built into the target gimbal. The electromagnetic sensor can sense the changes in electromagnetic signals within different frequency bands and provide accurate signal data for subsequent interference coefficient calculation and analysis.

[0063] It should be noted that when the electromagnetic signal around the target gimbal is larger, that is, the electromagnetic interference coefficient is larger, it will affect the applications such as the Hall effect sensor and accelerometer inside the target gimbal, which may cause inaccurate identification of the gimbal's deflection angle. The reason is that the Hall effect sensor is used to detect changes in the magnetic field to infer the angle, while the accelerometer determines the tilt angle by sensing changes in acceleration. The working principle of these sensors depends on the accurate perception and conversion of external signals. However, strong electromagnetic interference will generate noise signals, affect the output of the sensor, and cause measurement errors. Specifically, electromagnetic interference may cause deviation or failure of the sensor by changing the current flow inside the sensor or disturbing the magnetic field and acceleration signals it senses. For example, the Hall effect sensor may not be able to correctly identify changes in the magnetic field strength, and the accelerometer may misread the external electromagnetic interference signal as an acceleration change, which ultimately makes the gimbal's deflection angle identification inaccurate. Therefore, electromagnetic interference will have a significant impact on the stability and accuracy of the sensor, and thus affect the accuracy of the gimbal angle measurement.

[0064] In one implementation, the benefit of analyzing the electromagnetic interference coefficient for determining the accuracy of the target gimbal deflection angle recognition is that by calculating and evaluating the electromagnetic interference coefficient, the electromagnetic interference intensity in the surrounding environment can be quantified, thereby providing a reference for the accuracy of angle recognition. When the electromagnetic interference coefficient is large, it means that the noise of the electromagnetic signal may affect the normal operation of the sensors inside the gimbal (such as Hall effect sensors and accelerometers), resulting in errors in the deflection angle. Therefore, monitoring the electromagnetic interference coefficient can timely detect potential sources of interference and provide a basis for subsequent optimization and compensation. By setting a preset threshold and comparing it with the interference coefficient, it is possible to determine whether the current angle recognition is reliable, and then take corresponding corrective measures, such as dynamically adjusting sensor parameters or applying filtering algorithms to reduce interference effects. This analysis method helps improve the robustness and accuracy of gimbal angle recognition, especially in complex or harsh electromagnetic environments, and can ensure the stability and accuracy of the gimbal system.

[0065] In one embodiment, obtaining vibration data of a target gimbal and calculating a vibration interference coefficient of the target gimbal according to the vibration data includes:

[0066] The vibration amplitude of the target gimbal at multiple consecutive moments, and the vibration amplitude at each moment is marked as R e , where e = 1, 2, 3, 4, ..., d, d is a positive integer, and d represents the total number of vibration amplitudes;

[0067] Calculate the average vibration amplitude of the target gimbal using the following formula: Where Qs is the mean value of the vibration amplitude of the target gimbal;

[0068] Calculate the vibration interference coefficient, the calculation formula is: ED = m1·Qs+m2·max(R1, R2, R3....R e ), where ED is the vibration interference coefficient, m1 and m2 are preset weight coefficients, which are used to indicate the influence of the average amplitude and the maximum vibration amplitude on the final interference coefficient.

[0069] It should be noted that the vibration amplitude of the target gimbal can be obtained through the vibration sensor built into the target gimbal, which can detect the vibration of the gimbal in all directions in real time. The sensor will record the vibration intensity at different time points and convert it into a vibration amplitude value.

[0070] It should be noted that when the vibration interference coefficient of the target gimbal is larger, it will affect the applications such as the Hall effect sensor and accelerometer inside the target gimbal, which may cause inaccurate identification of the gimbal's deflection angle. The reason is that when the vibration interference coefficient of the target gimbal is larger, it means that the vibration and vibration intensity of the gimbal increase, which will directly affect the measurement accuracy of the Hall effect sensor and accelerometer inside the gimbal. The Hall effect sensor relies on the change of the magnetic field to infer the angle, while the accelerometer determines the tilt angle of the gimbal by sensing the change of acceleration. When the vibration interference coefficient is large, the vibration will cause instantaneous disturbance inside the sensor, causing the output signal of the sensor to produce noise or offset, thereby misleading the angle measurement. Specifically, the vibration may cause false acceleration or magnetic field changes in the sensor. In particular, for the accelerometer, the instantaneous acceleration change caused by the vibration may be mistaken for the actual movement of the gimbal, thereby affecting the accuracy of the angle calculation. For the Hall effect sensor, strong vibration may disturb its magnetic field sensing element, resulting in signal distortion or sampling error. Therefore, a large vibration interference coefficient will cause inaccurate identification of the gimbal's deflection angle, affecting the stability and reliability of the system.

[0071] In one implementation, the benefit of analyzing the vibration interference coefficient for determining the accuracy of the target gimbal deflection angle recognition is that the vibration interference coefficient can quantify the intensity and duration of the vibration to which the gimbal is subjected during operation, thereby providing a direct evaluation indicator for the accuracy of angle recognition. By real-time monitoring of the vibration interference coefficient, the system can promptly detect the possible impact of vibration on sensors (such as Hall effect sensors and accelerometers) and take corresponding compensation or optimization measures. If the vibration interference coefficient is high, it means that the sensor may be subject to a large disturbance, resulting in an increase in the angle measurement error. At this time, the robustness of the system can be improved by filtering algorithms, dynamically adjusting sensor parameters, or adding additional redundant sensors. In addition, the vibration interference coefficient can also provide a predictive basis for the performance of the system in complex environments, help identify potential performance bottlenecks or failure risks, and ensure that the gimbal can provide stable and accurate angle recognition under various working conditions. This analysis method can significantly improve the reliability and accuracy of the gimbal system in dynamic and vibration environments.

[0072] In one embodiment, acquiring temperature data of a target gimbal and calculating a temperature fluctuation coefficient of the target gimbal according to the temperature data includes:

[0073] The temperature value of the target gimbal at multiple consecutive moments, and mark the temperature value at each moment as E u , u represents the order number of the temperature value, u = 1, 2, 3, 4, ..., p, p is the total number of the above temperature values, and p is a positive integer;

[0074] Calculate the mean of the temperature values ​​using the formula:

[0075] Calculate the temperature fluctuation coefficient using the following formula:

[0076]

[0077] Where YK is the temperature fluctuation coefficient.

[0078] It should be noted that the temperature value of the target gimbal can be obtained through the temperature sensor built into the target gimbal, which can monitor the working environment and internal temperature changes of the gimbal, usually using thermocouples, RTD (resistance temperature detector) and other technologies for measurement. The temperature values ​​recorded by the temperature sensor at different time points will be used for subsequent analysis, and the average temperature value will be calculated to reflect the overall temperature trend.

[0079] It should be noted that when the temperature fluctuation coefficient of the target gimbal is larger, it will affect the applications such as the Hall effect sensor and accelerometer inside the target gimbal, and may cause inaccurate identification of the gimbal's deflection angle. The reason is that when the temperature fluctuation coefficient of the target gimbal is larger, it means that the working environment temperature of the gimbal fluctuates greatly, which will directly affect the performance of sensors such as the Hall effect sensor and accelerometer inside the gimbal. The Hall effect sensor is highly sensitive to temperature. The temperature fluctuation may cause the resistance of the magnetic field sensing element to change, thereby affecting the output signal of the sensor, and then causing errors in the measurement of the deflection angle. The accelerometer determines the tilt angle of the gimbal by detecting the change in force caused by acceleration, and the temperature fluctuation may cause the physical properties of the sensitive element of the accelerometer (such as piezoelectric material or MEMS structure) to change, thereby affecting the accuracy of its acceleration response. For example, high temperature may cause the material to expand, and low temperature may cause the material to shrink, both of which will cause errors in the accelerometer. These performance deviations caused by temperature will accumulate in the angle recognition, resulting in inaccurate identification of the gimbal's deflection angle. Therefore, the increase in the temperature fluctuation coefficient directly affects the reliability of the sensor, which in turn leads to a decrease in the accuracy of the gimbal's angle recognition.

[0080] In one implementation, the benefit of analyzing the temperature fluctuation coefficient for determining the accuracy of the target gimbal deflection angle recognition is that the temperature fluctuation coefficient can provide a key indicator of the temperature stability of the gimbal working environment, helping the system predict and evaluate the potential impact of temperature changes on sensor performance. When the temperature fluctuation coefficient is large, the system can promptly identify the error source that may be caused by temperature changes, and then take measures to correct or optimize it. For example, by dynamically compensating the Hall effect sensor and accelerometer in the case of large temperature fluctuations, or adjusting the operating parameters of the sensor to adapt to the current temperature conditions. This analysis method not only helps to improve the accuracy of angle recognition, but also increases the stability and reliability of the gimbal in complex and extreme temperature environments. By monitoring the temperature fluctuation coefficient in real time, the system can dynamically adapt to environmental changes, reduce measurement errors caused by temperature fluctuations, and ensure the accuracy and stability of the gimbal in various working environments.

[0081] In one embodiment, the interference coefficient obtained according to the electromagnetic interference coefficient, the vibration interference coefficient and the temperature fluctuation coefficient includes:

[0082] DCG=f1×JM+1+f2×ED+f3×YK

[0083] Wherein, DCG is the interference coefficient, JM, ED, and YK are the electromagnetic interference coefficient, vibration interference coefficient, and temperature fluctuation coefficient respectively; f1, f2, and f3 are the preset proportional coefficients of JM, ED, and YK respectively, and f1, f2, and f3 are all greater than 0;

[0084] It should be noted that f1, f2, and f3 are set by professionals according to actual conditions. Generally, the sum of f1, f2, and f3 is 1. For example, f1, f2, and f3 can be 0.27, 0.41, and 0.32, respectively, or other numbers without specific limitation. In addition, commonly used normalization processing methods include Min-Max normalization, Z-Score standardization, etc. The specific method is selected by professionals according to actual conditions, and no specific limitation or elaboration is made.

[0085] In one embodiment, judging the interference degree of the target gimbal in combination with a preset interference coefficient threshold includes:

[0086] The interference coefficient is compared with a preset interference coefficient threshold. If the interference coefficient is less than the preset interference coefficient threshold, it means that the interference degree of the target gimbal is relatively light, and the deflection angle of the target gimbal identified by the Hall effect sensor and accelerometer inside the target gimbal is accurate;

[0087] If the interference coefficient is not less than the preset interference coefficient threshold, it means that the target gimbal is severely interfered with. The target gimbal deflection angle identified by the Hall effect sensor and accelerometer inside the target gimbal is inaccurate. The real-time data of the Hall effect sensor and accelerometer are processed through the Kalman filtering algorithm, and the target gimbal deflection angle is identified based on the processed data.

[0088] It should be noted that the preset interference coefficient threshold is set by professionals according to actual conditions, and no specific limitation or elaboration is made thereon;

[0089] It should be noted that when the interference coefficient is not less than the preset threshold, it means that the target gimbal is subject to strong interference, which may be the combined influence of electromagnetic interference, vibration or temperature fluctuation, resulting in the data of the Hall effect sensor and the accelerometer being affected by large noise, so that the real deflection angle of the gimbal cannot be accurately reflected. At this time, the error in the original data may be amplified, resulting in an increase in the deviation of the angle measurement, affecting the reliability and stability of the system; in order to solve this problem, it is necessary to optimize the real-time data of the Hall effect sensor and the accelerometer, and use the Kalman filter algorithm. The Kalman filter algorithm can combine the data of multiple sensors, and perform noise suppression and data fusion based on the physical model and measurement model of the system. Through Kalman filtering, interference noise can be effectively filtered out to provide more accurate angle estimation. Specifically, the Kalman filter algorithm adjusts the sensor's measurement value in real time through a cycle of prediction and correction, so that in the presence of interference, the accurate target gimbal deflection angle can still be obtained; in the process of applying the Kalman filter, the system will dynamically adjust the filter parameters according to the sensor's measurement error to optimize the data processing process. For example, when the environmental interference is large, the Kalman filter can enhance the control of uncertainty, thereby reducing the error caused by interference. Ultimately, the filtered data will be more stable and accurate, ensuring the accuracy of the PTZ deflection angle recognition and the normal operation of the system in harsh environments. This optimization method can significantly improve the robustness and adaptability of the PTZ, especially under complex and dynamic working conditions.

[0090] Based on the same inventive concept, the present invention also provides a deflection angle recognition system. Figure 2 , Figure 2 A framework diagram of a deflection angle recognition system provided by an embodiment of the present invention, the system comprising:

[0091] Electromagnetic interference module: obtains the electromagnetic signals around the target gimbal and calculates the electromagnetic interference coefficient of the target gimbal based on the electromagnetic signals;

[0092] Vibration interference module: obtains the vibration data of the target gimbal and calculates the vibration interference coefficient of the target gimbal based on the vibration data;

[0093] Temperature fluctuation module: obtains the temperature data of the target gimbal and calculates the temperature fluctuation coefficient of the target gimbal based on the temperature data;

[0094] Deflection angle identification module: The interference coefficient is obtained according to the electromagnetic interference coefficient, vibration interference coefficient and temperature fluctuation coefficient, and the interference degree of the target gimbal is judged in combination with the preset interference coefficient threshold, and the deflection angle of the target gimbal is optimized and identified.

[0095] Based on the deflection angle recognition system provided by the embodiment of the present invention, the above steps can be used to judge the result of the gimbal deflection angle recognition, and optimize the recognition of the deflection angle of the target gimbal, thereby ensuring accurate recognition of the deflection angle of the target gimbal.

[0096] Based on the same inventive concept, the present invention also provides a pan / tilt platform. Figure 3 , Figure 3 A framework diagram of a pan / tilt provided in an embodiment of the present invention, the pan / tilt comprises:

[0097] Hall effect sensor and accelerometer: used to identify the deflection angle of the target gimbal;

[0098] Electromagnetic sensor: used to obtain the electromagnetic signal of the target gimbal;

[0099] Vibration sensor: used to obtain the vibration amplitude of the target gimbal;

[0100] Temperature sensor: used to obtain the temperature of the target gimbal;

[0101] Processing module: used to process the data recognized by the Hall effect sensor and accelerometer in real time through the stored Kalman filter algorithm.

[0102] In another embodiment of the present invention, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program is executed by a processor, the above-mentioned steps of identifying any deflection angle are implemented.

[0103] In another embodiment provided by the present invention, a computer program product including instructions is also provided, which, when executed on a computer, enables the computer to execute any deflection angle recognition in the above-mentioned embodiments.

[0104] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A deflection angle recognition method, characterized in that: The following steps are involved: Acquire electromagnetic signals around the target gimbal, and calculate the electromagnetic interference coefficient of the target gimbal according to the electromagnetic signals; Acquire the vibration data of the target gimbal, and calculate the vibration interference coefficient of the target gimbal according to the vibration data; Acquire the temperature data of the target gimbal, and calculate the temperature fluctuation coefficient of the target gimbal according to the temperature data; The interference coefficient is obtained according to the electromagnetic interference coefficient, the vibration interference coefficient and the temperature fluctuation coefficient, and the interference degree of the target gimbal is judged in combination with the preset interference coefficient threshold, and the deflection angle of the target gimbal is optimized and identified.

2. The deflection angle recognition method according to claim 1, characterized in that: The electromagnetic interference coefficient of the target gimbal is calculated based on the electromagnetic signal, including: Electromagnetic signals around the target gimbal at multiple times, marked as B ( t ) , where t = 1, 2, 3, 4, ..., Z, Z is a positive integer, and Z represents the number of electromagnetic signals; Use Morlet wavelet to analyze the electromagnetic interference signal B at each moment ( t ) Perform continuous wavelet transform, decompose the electromagnetic interference signal into several scales through continuous wavelet transform, and the result calculated by wavelet transform at each scale is called wavelet coefficient; According to the calculated wavelet coefficients, the energy of the wavelet coefficients at each scale is calculated, and the energy of different scales is weighted summed to obtain the comprehensive energy feature F total ; Calculate the electromagnetic interference index at each moment, the calculation expression is: BK ( t ) =F total Where BK ( t ) is the electromagnetic interference index; The electromagnetic interference index BK at different times ( t ) Add them together to get the electromagnetic interference coefficient, and the calculation formula is: Where JM is the electromagnetic interference coefficient.

3. The deflection angle identification method according to claim 1, characterized in that: The vibration interference coefficient of the target gimbal is calculated based on the vibration data, including: The vibration amplitude of the target gimbal at multiple consecutive moments, and the vibration amplitude at each moment is marked as R e , where e = 1, 2, 3, 4, ..., d, d is a positive integer, and d represents the total number of vibration amplitudes; Calculate the average vibration amplitude of the target gimbal using the following formula: Where Qs is the mean value of the vibration amplitude of the target gimbal; Calculate the vibration interference coefficient. The calculation formula is: ED = m1·Qs+m2·max ( R1, R2, R3.....R e) , where ED is the vibration interference coefficient, and m1 and m2 are the preset weight coefficients.

4. The deflection angle identification method according to claim 1, characterized in that: Calculating the temperature fluctuation coefficient of the target gimbal based on the temperature data includes: The temperature value of the target gimbal at multiple consecutive moments, and mark the temperature value at each moment as E u , u represents the order number of the temperature value, u = 1, 2, 3, 4, ..., p, p is the total number of the above temperature values, and p is a positive integer; Calculate the mean of the temperature values ​​using the formula: Calculate the temperature fluctuation coefficient using the following formula: Where YK is the temperature fluctuation coefficient.

5. The deflection angle recognition method according to claim 1, characterized in that: The interference coefficients obtained based on the electromagnetic interference coefficient, vibration interference coefficient and temperature fluctuation coefficient include: DCG=f1×JM+1+f2×ED+f3×YK Wherein, DCG is the interference coefficient, JM, ED, and YK are the electromagnetic interference coefficient, vibration interference coefficient, and temperature fluctuation coefficient, respectively; f1, f2, and f3 are the preset proportional coefficients of JM, ED, and YK, respectively, and f1, f2, and f3 are all greater than 0.

6. The deflection angle recognition method according to claim 1, characterized in that: The interference degree of the target gimbal is determined by combining the preset interference coefficient threshold, including: The interference coefficient is compared with a preset interference coefficient threshold. If the interference coefficient is less than the preset interference coefficient threshold, it means that the interference degree of the target gimbal is relatively light, and the deflection angle of the target gimbal identified by the Hall effect sensor and accelerometer inside the target gimbal is accurate; If the interference coefficient is not less than the preset interference coefficient threshold, it means that the target gimbal is severely interfered with. The target gimbal deflection angle identified by the Hall effect sensor and accelerometer inside the target gimbal is inaccurate. The real-time data of the Hall effect sensor and accelerometer are processed through the Kalman filtering algorithm, and the target gimbal deflection angle is identified based on the processed data.

7. A deflection angle recognition system, used to implement the deflection angle recognition method according to any one of claims 1 to 6, characterized in that: The system comprises: Electromagnetic interference module: obtains the electromagnetic signals around the target gimbal and calculates the electromagnetic interference coefficient of the target gimbal based on the electromagnetic signals; Vibration interference module: obtains the vibration data of the target gimbal and calculates the vibration interference coefficient of the target gimbal based on the vibration data; Temperature fluctuation module: obtains the temperature data of the target gimbal and calculates the temperature fluctuation coefficient of the target gimbal based on the temperature data; Deflection angle identification module: The interference coefficient is obtained according to the electromagnetic interference coefficient, vibration interference coefficient and temperature fluctuation coefficient, and the interference degree of the target gimbal is judged in combination with the preset interference coefficient threshold, and the deflection angle of the target gimbal is optimized and identified.

8. A deflection angle recognition pan / tilt, used to implement the deflection angle recognition method according to any one of claims 1 to 6, characterized in that: The pan / tilt platform comprises: Hall effect sensor and accelerometer: used to identify the deflection angle of the target gimbal; Electromagnetic sensor: used to obtain the electromagnetic signal of the target gimbal; Vibration sensor: used to obtain the vibration amplitude of the target gimbal; Temperature sensor: used to obtain the temperature of the target gimbal; Processing module: used to process the data recognized by the Hall effect sensor and accelerometer in real time through the stored Kalman filter algorithm.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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