Regulation System and Method for Mounting Bracket of Multi-Beam Detection Device

Abstract

The present disclosure provides a regulation system and method for a mounting bracket of a multi-beam detection device, relating to the technical field of data processing. The system includes: a closed-loop calibration module, configured to obtain real-time attitude parameters of the bracket based on real-time attitude monitoring data of the mounting bracket of the multi-beam detection device, compare the real-time attitude parameters with preset target attitude data, and generate a calibration instruction; a dynamic compensation module, configured to determine a bracket attitude deviation and perform a compensation calculation according to the calibration instruction output by the closed-loop calibration module in combination with the monitoring data of a vibration sensor, and generate a correction instruction; an adaptive optimization module, configured to adaptively adjust control parameters of the bracket through gradient descent according to the correction instruction output by the dynamic compensation module in combination with task parameters in a task parameter library, so as to optimize the attitude of the bracket. The technical solution in the present disclosure can improve the accuracy and stability of the multi-beam detection device in various environments.

Description

Background Art

[0002] In the application of multi-beam detection devices, the bracket, as a crucial support structure, directly affects the detection accuracy and system stability. With the continuous evolution of technology, the detection environment has become increasingly complex and variable, and traditional bracket designs are no longer able to meet the high requirements for accuracy and dynamic response in modern detection tasks.

[0003] In the prior art, mounting brackets for multi-beam detection devices usually adopt mechanical fixed structures or simple manual adjustment systems. Although such structures can meet basic installation requirements, they expose many deficiencies when facing complex detection environments. Especially in application scenarios that require dynamic adjustment, the bracket is difficult to effectively cope with the variability and uncertainty of the external environment. For example, vibrations, tilts, or other environmental interferences may cause the bracket attitude to deviate, further affecting the detection accuracy of the detection device. In addition, the prior art also has problems with insufficient dynamic response capabilities. In actual use, the impact of changes in the external environment usually occurs in real time, and traditional brackets cannot complete corresponding adjustments and compensations in a short time, often resulting in the continuous accumulation of attitude deviations of the detection device and even the risk of mission interruption. This problem is particularly prominent in scenarios involving high dynamics or high-precision requirements (such as shipborne detection or mobile platform operations).

[0004] To address the above deficiencies, there is an urgent need for a technical solution that can achieve efficient perception and dynamic adjustment of the bracket attitude, and at the same time has a fast response ability to ensure the accuracy and stability of multi-beam detection devices in various complex environments, so as to better meet the needs of practical applications. Summary of the Invention

[0005] The purpose of the embodiments of the present disclosure is to provide a control system and method for a mounting bracket of a multi-beam detection device, thereby at least to some extent improving the accuracy and stability of the multi-beam detection device in various environments.

[0006] Other features and advantages of the present disclosure will become apparent through the following detailed description, or be learned in part through the practice of the present disclosure.

[0007] According to the first aspect of the embodiments of the present disclosure, a regulation system for a mounting bracket of a multi-beam detection device is provided. The system includes: a closed-loop calibration module, configured to obtain real-time attitude parameters of the bracket based on real-time attitude monitoring data of the mounting bracket of the multi-beam detection device, compare the real-time attitude parameters with preset target attitude data, and generate a calibration instruction; a dynamic compensation module, configured to determine an attitude deviation of the bracket and perform a compensation calculation based on the calibration instruction output by the closed-loop calibration module and in combination with monitoring data of a vibration sensor, and generate a correction instruction; an adaptive optimization module, configured to adaptively adjust control parameters of the bracket by gradient descent based on the correction instruction output by the dynamic compensation module and in combination with task parameters in a task parameter library, so as to optimize the attitude of the bracket.

[0008] According to the second aspect of the embodiments of the present disclosure, a regulation method for a mounting bracket of a multi-beam detection device is provided. The method includes: obtaining real-time attitude parameters of the bracket based on real-time attitude monitoring data of the mounting bracket of the multi-beam detection device, comparing the real-time attitude parameters with preset target attitude data, and generating a calibration instruction; determining an attitude deviation of the bracket and performing a compensation calculation based on the calibration instruction and in combination with monitoring data of a vibration sensor and a displacement sensor, and generating a correction instruction; optimizing control parameters of the bracket by an adaptive adjustment algorithm based on the correction instruction and in combination with task parameters in a task parameter library.

[0009] According to the third aspect of the embodiments of the present disclosure, an electronic device is provided, including: a processor; and a memory, on which computer-readable instructions are stored, and when the computer-readable instructions are executed by the processor, the regulation method for the mounting bracket of the multi-beam detection device as described above is implemented.

[0010] According to the fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the regulation method for the mounting bracket of the multi-beam detection device as described above is implemented.

[0011] The technical solutions provided by the embodiments of the present disclosure may include the following beneficial effects:

[0012] The regulation system for the mounting bracket of the multi-beam detection device in the exemplary embodiments of the present disclosure includes a closed-loop calibration module, a dynamic compensation module, and an adaptive optimization module.

[0013] Through the closed-loop calibration module, the attitude parameters of the mounting bracket of the multi-beam detection device can be obtained in real time and compared with the preset target attitude data. This step can promptly detect the deviation of the bracket attitude and generate a calibration instruction to ensure that the bracket attitude is consistent with the predetermined target. Thus, the system can achieve precise monitoring of the real-time attitude of the bracket and quickly correct it when the attitude deviates from the target, thereby improving the stability and accuracy of the system. Further, through the dynamic compensation module combined with the monitoring data of the vibration sensor, the attitude deviation of the bracket is compensated according to the calibration instruction. This process can effectively eliminate the attitude error caused by vibration or external disturbances, thereby reducing the attitude drift caused by external factors and improving the detection accuracy of the multi-beam detection device. The correction instruction generated by the compensation calculation can further reduce the bracket deviation and optimize the motion state of the bracket, providing guarantee for the precise operation of the device. Finally, with the help of the adaptive optimization module, combining the task parameters in the task parameter library and the correction instruction output by the dynamic compensation module, the system automatically adjusts the control parameters of the bracket through the gradient descent method. This optimization step can dynamically adapt to different task requirements and environmental changes, effectively improving the flexibility and accuracy of the bracket attitude regulation. Through adaptive adjustment, the system can accurately optimize the motion state of the bracket according to the actual task load and the real-time data of the bracket motion, ensuring the best performance of the multi-beam detection device under various working conditions.

[0014] Integrating the collaborative work of the above-mentioned modules, the present disclosure realizes high-precision regulation of the bracket attitude, has robustness and adaptability in complex environments, and greatly improves the measurement accuracy and working stability of the multi-beam detection device.

[0015] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0017] Figure 1 Schematically shows a schematic diagram of the composition of a regulation system for a mounting bracket of a multi-beam detection device according to some embodiments of the present disclosure.

[0018] Figure 2 Schematically shows a schematic diagram of the composition of another regulation system for a mounting bracket of a multi-beam detection device according to some embodiments of the present disclosure.

[0019] Figure 3Schematically shows a schematic diagram of the working process of a closed-loop calibration module according to some embodiments of the present disclosure.

[0020] Figure 4 Schematically shows a schematic diagram of the working process of a dynamic compensation module according to some embodiments of the present disclosure.

[0021] Figure 5 Schematically shows a schematic diagram of the working process of an adaptive optimization module according to some embodiments of the present disclosure.

[0022] Figure 6 Schematically shows a schematic diagram of a flow of a method for regulating an installation bracket of a multi-beam detection device according to some embodiments of the present disclosure.

[0023] Figure 7 Schematically shows a schematic diagram of the structure of a computer system of an electronic device according to some embodiments of the present disclosure.

[0024] Figure 8 Schematically shows a schematic diagram of a computer-readable storage medium according to some embodiments of the present disclosure.

[0025] In the drawings, the same or corresponding reference numerals denote the same or corresponding parts. Detailed Description of the Embodiments

[0026] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this specification. On the contrary, they are merely examples of devices and methods consistent with some aspects of this specification as detailed in the appended claims.

[0027] The terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit this specification. The singular forms "a", "the", and "said" used in this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0028] It should be understood that although the terms first, second, third, etc. may be used in this specification to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this specification, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "while" or "in response to determining".

[0029] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be more complete and comprehensive, and will fully convey the concept of the example embodiments to those skilled in the art.

[0030] In addition, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of the embodiments of the present disclosure. However, those skilled in the art will realize that the technical solutions of the present disclosure can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be used. In other cases, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the present disclosure.

[0031] In addition, the drawings are only schematic diagrams and are not necessarily drawn to scale. The block diagrams shown in the drawings are only functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0032] In the application of a multi-beam detection device, the bracket, as a key support structure, directly affects the detection accuracy and system stability. However, in related technologies, the mounting brackets of multi-beam detection devices usually adopt mechanical fixing structures or manual adjustment systems, and these brackets have significant deficiencies in complex environments. First, external vibrations, tilts, and other interferences may cause the bracket attitude to shift, affecting the detection accuracy. Second, the existing brackets lack the ability to adjust in real time dynamically and cannot quickly respond and compensate when the environment changes, resulting in the accumulation of attitude deviations and affecting the detection stability. Especially in scenarios with high dynamic or high-precision requirements, traditional brackets cannot meet the needs of real-time adjustment and compensation.

[0033] To solve some or all of the above technical problems, the present disclosure provides a control system for a mounting bracket of a multi-beam detection device. Figure 1Schematically shows a composition diagram of a regulation system for a mounting bracket of a multi-beam detection device according to some embodiments of the present disclosure. Refer to Figure 1 As shown, the regulation system for the mounting bracket of the multi-beam detection device may include the following modules:

[0034] A closed-loop calibration module 1, configured to obtain real-time attitude parameters of the bracket based on real-time attitude monitoring data of the mounting bracket of the multi-beam detection device, compare the real-time attitude parameters with preset target attitude data, and generate a calibration instruction;

[0035] A dynamic compensation module 2, configured to determine the attitude deviation of the bracket and perform compensation calculation based on the calibration instruction output by the closed-loop calibration module and in combination with the monitoring data of the vibration sensor, and generate a correction instruction;

[0036] An adaptive optimization module 3, configured to adaptively adjust the control parameters of the bracket through gradient descent based on the correction instruction output by the dynamic compensation module and in combination with the task parameters in the task parameter library, so as to optimize the attitude of the bracket.

[0037] Specifically, the above-mentioned regulation system for the mounting bracket of the multi-beam detection device includes multiple modules, and each module works in cooperation to achieve precise adjustment of the bracket attitude.

[0038] First, the closed-loop calibration module 1 obtains the current attitude parameters of the bracket through real-time attitude monitoring data. By comparing with the preset target attitude data, this module determines whether there is a deviation in the attitude of the bracket and generates corresponding calibration instructions accordingly. The main function of the closed-loop calibration module 1 is to achieve real-time monitoring of the bracket attitude, ensure that the bracket can maintain a position close to the target attitude at any time, and thus provide an accurate data basis for subsequent compensation and optimization work.

[0039] Next, the dynamic compensation module 2 further analyzes the deviation of the bracket attitude according to the calibration instruction output by the closed-loop calibration module 1 and in combination with the vibration sensor monitoring data. By monitoring vibrations or other external disturbances, this module can calculate and generate correction instructions in real time to dynamically compensate the bracket attitude. This compensation process can effectively eliminate the attitude errors caused by external vibrations, impacts or other environmental changes, ensure that the bracket always maintains a stable working attitude, and avoid adverse effects of attitude deviation on the detection accuracy.

[0040] Finally, the adaptive optimization module 3 receives the correction instructions from the dynamic compensation module 2 and combines the task parameters in the task parameter library to adaptively adjust the control parameters of the bracket by means of the gradient descent method. Through this process, the system can automatically optimize the attitude and control accuracy of the bracket under different working environments and task requirements. The role of the adaptive optimization module 3 is to dynamically adjust the motion parameters of the bracket according to real-time data and task requirements to ensure that the bracket can continuously maintain the best attitude configuration under various dynamic changes.

[0041] In summary, the closed-loop calibration module 1, the dynamic compensation module 2, and the adaptive optimization module 3 together constitute a complete attitude control system, which can monitor, compensate, and optimize the bracket attitude in real time. Through the coordinated action of these modules, the system can accurately control the bracket attitude under complex and changing environmental conditions, significantly improve the measurement accuracy and stability of the multi-beam detection device, and ensure continuous and stable operation in scenarios with high dynamics or high-precision requirements.

[0042] Next, in other embodiments of the present disclosure, the above-mentioned control system for the installation bracket of the multi-beam detection device will be further described.

[0043] Reference Figure 2 As shown, in some embodiments, the closed-loop calibration module 1 includes a data acquisition unit 11, a deviation calculation unit 12, and an instruction generation unit 13. The working process of the adaptive optimization module can be as Figure 3 shown. Next, the functional principles of each unit in the closed-loop calibration module will be introduced in detail.

[0044] The data acquisition unit 11 can be used to collect the real-time attitude monitoring data of the installation bracket of the multi-beam detection device in real time through an inertial measurement component and convert the real-time attitude monitoring data into the real-time attitude parameters of the bracket. Among them, the inertial measurement component can represent a combination of sensors for measuring acceleration, angular velocity, and direction changes, which can include an accelerometer, a gyroscope, a magnetometer, etc. The multi-beam detection device can represent a device that can simultaneously transmit and receive signals through multiple detection beams and can perform high-precision detection in a wide area, which can be used for measurement tasks in underwater or marine environments. The installation bracket of this device is used to support and fix the detection device to ensure its required attitude stability during operation. The attitude monitoring data can represent the real-time data provided by the inertial measurement component about the current attitude of the bracket, which is used to describe the spatial position and direction changes of the bracket. The attitude parameters can represent the specific parameters about the bracket attitude obtained by processing and converting the attitude monitoring data, including the actual pitch angle, yaw angle, and roll angle of the bracket, etc., which are used to quantify the spatial attitude of the bracket and provide basic data for subsequent calibration and compensation operations.

[0045] In some embodiments, the real-time attitude monitoring data includes acceleration data and angular velocity data. Converting the real-time attitude monitoring data into the real-time attitude parameters of the bracket specifically includes the following technical steps:

[0046] First, determine the quaternion corresponding to the bracket at the initial moment and update the quaternion according to the angular velocity data. Among them, the quaternion can represent a mathematical tool for representing the three-dimensional rotation of an object, usually composed of four real numbers. The quaternion is determined by the attitude data at the initial moment. In this embodiment, the angular velocity data obtained by the inertial measurement component is used to update the quaternion, so as to achieve the tracking of the dynamic attitude. The angular velocity data can represent the real-time data of the rotation rate of the bracket collected by the inertial measurement component.

[0047] Specifically, the quaternion can be updated through the following process:

[0048] First, set the initial moment of the quaternion , where represents the scalar part of the quaternion, , , represent the vector part of the quaternion. By initializing the quaternion, the attitude of the bracket at the starting moment is clarified, providing a reference point for subsequent dynamic updates.

[0049] Then, according to:

[0050]

[0051] determine the derivative of the quaternion, where represents the quaternion at time t , represents the quaternion multiplication operation, represents expanding the angular velocity data into quaternion form, t represents time. Through the mutual operation of the current quaternion and the angular velocity data, the change rate of the bracket attitude is obtained. This derivative term reflects the trend of the bracket attitude changing with time, providing accurate dynamic information for the update of the quaternion at the next moment.

[0052] Finally, according to iterate and update the quaternion, where represents the sampling time interval, represents the updated quaternion corresponding to time . By adding the product of the derivative term and the time step to the quaternion at the current moment, the prediction and calculation of the attitude at the next moment are completed.

[0053] In the second step, the updated quaternion is assisted and corrected using acceleration data. The acceleration data can represent real-time data on the acceleration of the bracket collected by the inertial measurement unit and can be provided by the accelerometer. By using the acceleration data, the updated quaternion can be assisted and corrected to correct the cumulative error caused by the angular velocity data. By combining the acceleration data with the quaternion, the accuracy of attitude estimation can be improved, especially the error compensation effect during small-angle changes.

[0054] Specifically, the process of assisting and correcting the updated quaternion is as follows:

[0055] First, determine the actual direction vector corresponding to the acceleration data , and calculate the theoretical gravity direction vector according to the quaternion , where represents the acceleration data. The actual direction vector refers to the unit vector calculated based on the acceleration data collected by the inertial measurement unit and represents the normalized direction of the acceleration data at the current moment. The theoretical gravity direction vector can be obtained by rotating the initial gravity direction vector through the quaternion at the current moment, and its calculation formula is:

[0056]

[0057] where represents the standard gravity direction unit vector in the inertial coordinate system, with a value of , and respectively represent the current quaternion and its conjugate inverse operation, represents quaternion multiplication.

[0058] Then, determine the error between the actual direction vector and the theoretical gravity direction vector, and assist and correct the derivative of the quaternion according to . Use the assisted and corrected derivative to recalculate , where represents the correction coefficient. Specifically, the theoretical gravity direction vector refers to the gravity direction unit vector corresponding to the theoretical attitude of the bracket calculated using the current quaternion and reflects the theoretical gravity direction of the bracket attitude in the inertial coordinate system. The corrected quaternion corrects the attitude deviation by recalculating . This process can significantly reduce the attitude offset caused by cumulative error or transient error, thereby improving the accuracy and stability of the bracket attitude control.

[0059] In the third step, normalize the corrected quaternion and convert the normalized quaternion into Euler angles, and use the Euler angles as the real-time attitude parameters of the bracket. Among them, normalize the corrected quaternion to ensure that its value conforms to the unit length constraint of the quaternion. Euler angles can represent a common way of representing three-dimensional rotation angles, usually composed of three angle parameters, such as pitch angle, yaw angle, and roll angle.

[0060] Specifically, normalize the corrected quaternion to ensure that its physical meaning conforms to the characteristics of the unit quaternion, thereby avoiding errors introduced due to the modulus length not being 1 during the rotation calculation process. The corrected quaternion The normalization formula is:

[0061]

[0062] Among them, represents the normalized quaternion, represents the corrected quaternion; represents the modulus length of the quaternion, and its calculation formula is:

[0063]

[0064] Among them, are respectively The scalar part and the three vector components of can represent the rotation amplitude and the rotation axis direction of the quaternion. After normalization, the normalized quaternion satisfies the unit length property, that is .

[0065] Subsequently, convert the normalized quaternion into Euler angles , which respectively represent the roll angle, pitch angle, and yaw angle of the bracket, and their calculation formulas are as follows:

[0066] Roll angle The calculation formula of is:

[0067]

[0068] Pitch angle The calculation formula of is:

[0069]

[0070] Yaw angle The calculation formula of is:

[0071]

[0072] Among them, is the scalar part of the quaternion, representing the rotation amplitude; represents the vector component of the quaternion, which is the component representing the direction of the rotation axis. The Euler angles calculated through the above formula accurately describe the three-dimensional rotation state of the bracket in the inertial coordinate system. As the real-time attitude parameter of the bracket, the Euler angles can intuitively reflect the attitude of the bracket in the roll, pitch, and yaw directions, providing reliable support for the attitude adjustment of the multi-beam detection device.

[0073] The deviation calculation unit 12 can be used to compare the real-time attitude parameter with the preset target attitude data, determine the differences in the pitch, roll, and yaw angles between the real-time attitude parameter and the target attitude data, so as to determine the attitude deviation. Among them, the attitude deviation can represent the difference between the real-time attitude parameter and the preset target attitude data, specifically including the deviation amounts in the three dimensions of the pitch angle, roll angle, and yaw angle. The attitude deviation can be used to quantify the deviation degree of the current bracket attitude from the target attitude.

[0074] The instruction generation unit 13 can be used to perform arithmetic processing using a PID controller according to the attitude deviation, and generate a calibration instruction for adjusting the attitude of the mounting bracket of the multi-beam detection device.

[0075] Specifically, the instruction generation unit 13 generates a calibration instruction for adjusting the attitude of the mounting bracket of the multi-beam detection device based on the attitude deviation and the arithmetic logic of the PID controller. respectively represent the roll angle deviation, pitch angle deviation, and yaw angle deviation. The arithmetic process of the PID controller comprehensively considers the three control terms of proportional (P), integral (I), and derivative (D) to ensure the precise adjustment and dynamic response of the calibration instruction to the attitude deviation. The basic arithmetic formula of the PID controller can be expressed as:

[0076]

[0077] Among them, represents the calibration instruction generated at the current moment; respectively represent the proportional, integral, and derivative control coefficients, which are used to adjust the weights of the controller for different control terms; represents the error amount at the current moment, corresponding to the target component of the attitude deviation (such as the pitch angle deviation ); represents the integral of the error from the initial moment to the current moment for the compensation of the accumulated error; represents the rate of change of the current error with respect to time, that is, the derivative of the error, reflecting the trend of the error change.

[0078] For this embodiment, the calibration instruction Calculate the pitch, roll, and yaw angles of the bracket respectively, and the specific calculation formulas are as follows:

[0079]

[0080]

[0081]

[0082] Among them, respectively represent the calibration instructions for roll, pitch, and yaw angles; are the proportional, integral, and differential control coefficients of the roll angle respectively; are the proportional, integral, and differential control coefficients of the pitch angle respectively; are the proportional, integral, and differential control coefficients of the yaw angle respectively; respectively represent the attitude deviations of roll, pitch, and yaw angles; are the integral terms of the corresponding angle deviations respectively; are the differential terms of the corresponding angle deviations respectively.

[0083] Combining the above processes, the PID controller processes each attitude deviation component in real time, and the generated calibration instruction directly reflects the adjustment amount required to correct the bracket attitude. These calibration instructions are transmitted to the actuator to adjust the actual attitude of the bracket, making it gradually tend to the target attitude. Through the combined action of the proportional, integral, and differential of the PID controller, the system can achieve a rapid response to attitude deviations, correction of cumulative errors, and smooth adjustment of dynamic changes, ensuring precise control and stable adjustment of the bracket attitude.

[0084] Next, referring to Figure 2 , in some embodiments, the dynamic compensation module 2 may include a preprocessing unit 21, a disturbance analysis unit 22, and a correction instruction unit 23. The working process of the dynamic compensation module can be as shown in Figure 4 , and the functional principles of each unit in the dynamic compensation module will be introduced in detail below.

[0085] The preprocessing unit 21 can be used to collect the vibration signals of the vibration sensor and perform Fourier transform on the vibration signals to obtain frequency-domain data. Among them, the vibration signal can represent a signal that changes with time collected by the vibration sensor, and this signal reflects the vibration characteristics of the bracket in the working environment. The Fourier transform can represent a method of performing a mathematical transform on the vibration signal, which converts the vibration signal from the time domain to the frequency domain, enabling the amplitude and phase information of different frequency components to be clearly separated, thus facilitating the analysis of disturbances in a specific frequency band. The frequency-domain data can represent the representation of the vibration signal in the frequency domain obtained through Fourier transform, and this data is composed of the amplitudes and phases of multiple frequency components and can reflect the energy distribution of the vibration signal at different frequencies.

[0086] Specifically, the vibration signal can be represented by a continuous-time signal where represents the vibration amplitude that changes with time, which is the time-domain data collected by the vibration sensor in real time, represents the time variable. To analyze the frequency-domain characteristics of the signal, Fourier transform is used to perform frequency-domain conversion on , and its transformation formula is:

[0087]

[0088] where represents the frequency-domain signal, that is, the spectrum after Fourier transform; represents the frequency variable, reflecting the frequency components of the signal; is the complex exponential kernel function, representing the transformation basis for mapping the signal from the time domain to the frequency domain.

[0089] In the actual processing process, since the collected vibration signal is discrete, it is necessary to perform discrete Fourier transform (DFT) on it. The formula for discrete Fourier transform is:

[0090]

[0091] where represents the th frequency component of the frequency-domain data; represents the th sampling point of the discrete vibration signal; represents the total number of sampling points of the discrete signal; represents the frequency index of the frequency-domain data; represents the basis function of the discrete Fourier transform.

[0092] The perturbation analysis unit 22 can be used to extract the perturbation signals in a specific frequency band from the frequency-domain data, and determine the perturbation state corresponding to the perturbation signals by using the state equation and the measurement equation. Among them, the perturbation signals can represent the signals in a specific frequency band selected in the frequency-domain data, and these signals correspond to the dynamic perturbation factors that may affect the stability of the support. The state equation can represent the mathematical model used to describe the change of the perturbation signals over time. This equation uses the dynamic characteristics of the system to quantitatively represent the relationship between the perturbation state and the input signals, so as to provide a mathematical description of the perturbation behavior. The measurement equation can represent the mathematical equation used to correlate the actually measured vibration signal data with the theoretical state model. The perturbation state can represent the characteristic parameters of the perturbation signals estimated by the state equation and the measurement equation.

[0093] Specifically, the process of extracting the perturbation signals in a specific frequency band from the frequency-domain data includes the following steps:

[0094] First, determine the target frequency band range , where represents the lowest frequency of the target frequency band; represents the highest frequency of the target frequency band.

[0095] Through the frequency resolution formula , convert the frequency range into the frequency-domain index range , and its calculation formula is:

[0096]

[0097] Among them, and are respectively the start and end indexes of the frequency band; represents the sampling frequency of the vibration signal; represents the total number of sampling points of the discrete Fourier transform, k represents the corresponding frequency index in the frequency domain, represents the k th frequency value corresponding to the

[0098] Extract the signal in the specific frequency band in the frequency-domain data according to the following formula:

[0099]

[0100] Among them, represents the th frequency component of the frequency-domain signal obtained by the discrete Fourier transform; represents the extracted signal in the specific frequency band.

[0101] For the extracted frequency-domain data Perform inverse discrete Fourier transform to reconstruct the time domain representation of the target frequency band signal :

[0102]

[0103] in, Represents the time domain representation of the disturbance signal in a specific frequency band, Represents the basis functions for the inverse discrete Fourier transform.

[0104] In some embodiments, the disturbance state corresponding to the disturbance signal is determined using the state equation and the measurement equation, specifically including the following technical steps:

[0105] Constructing the equation of state and the measurement equation ,in, represents the state transfer matrix, represents the input matrix, represents the observation matrix, represents the disturbance signal state vector, represents the process noise vector, represents the observation noise vector, Represents the input vector.

[0106] according to Sure Predicted state at the moment ,in, Indicates at time The corresponding disturbance signal state vector, Indicates at time The predicted state vector at time .

[0107] according to Time observation vector Determine the observed residuals ,in, , and according to the Kalman gain matrix , observation residuals and moments The predicted state vector is determined when The estimated value of the disturbance state corresponding to the disturbance signal at the moment Specifically, according to the measurement equation, the observation residual is calculated :

[0108]

[0109] in, express The observation residual at time express The observation vector at the moment is collected by the sensor; represents the observation matrix, which maps the state vector to the observation space.

[0110] Calculate the Kalman gain matrix The calculation process is as follows:

[0111]

[0112] where represents the Kalman gain matrix at time represents the observation noise covariance matrix, represents the state estimation error covariance matrix at time represents the transpose of the observation matrix.

[0113] Combine the predicted state and the observation residual to update the state estimate at time :

[0114]

[0115] Update the covariance matrix according to the following formula:

[0116]

[0117] where represents the identity matrix, which is used to keep the matrix dimensions consistent.

[0118] Finally, obtain the disturbance state estimate corresponding to the disturbance signal at time , and the updated covariance matrix . These results can be used for further analysis of the dynamic characteristics of the disturbance signal and its impact on the system.

[0119] The correction instruction unit 23 can be used to determine the compensation amount according to the disturbance state based on the linear control law, and generate a correction instruction for adjusting the support attitude in combination with the calibration instruction. Among them, the linear control law can represent the control strategy for calculating the compensation amount according to the disturbance state. This control law adopts a linear operation method to generate the corresponding compensation instruction according to the disturbance state variables to reduce or offset the impact of the disturbance on the support attitude. The compensation amount can represent the adjustment value calculated according to the linear control law to offset the disturbance impact.

[0120] Specifically, the generation of the correction instruction can be carried out through the following steps:

[0121] First, based on the known disturbance state estimate , calculate the compensation amount using the linear control law, and generate a correction instruction in combination with the calibration instruction. Specifically, set Represents The dynamic characteristic parameters of the moment disturbance signal, including position, velocity, acceleration, etc. It can be defined as:

[0122]

[0123] Wherein, Represents the th component of the disturbance state, specifically the estimated value of the current state of the system.

[0124] Then, according to the linear control law, the compensation amount Is determined by the product of the disturbance state and the feedback gain matrix:

[0125]

[0126] Wherein, Represents The compensation amount vector at the moment; Represents the control gain matrix, which is used to adjust the system feedback intensity, Represents The estimated value of the disturbance state at the moment.

[0127] Calibration instruction Is generated according to the closed-loop calibration module and is used to correct the initial attitude deviation of the bracket. It is defined as follows:

[0128]

[0129] Wherein, Represents the calibration instruction; Represents the calibration gain matrix; Represents the calibration error, which can be defined as the difference between the current attitude and the target attitude.

[0130] Final correction instruction Is generated by combining the compensation amount and the calibration instruction, and the formula is as follows:

[0131]

[0132] Wherein, Represents The correction instruction at the moment.

[0133] Input the generated correction instruction Into the bracket control system to adjust the attitude of the bracket, so as to achieve the effect of suppressing disturbance and restoring balance. The correction instruction converts the signal into a specific action through the actuator to adjust the attitude parameters (such as pitch angle, yaw angle, roll angle) of the bracket in real time.

[0134] Then refer to Figure 2, in some embodiments, the adaptive optimization module 3 includes a task parameter unit 31, a parameter initial setting unit 32, a gradient optimization unit 33, and a verification and adjustment unit 34. The working process of the adaptive optimization module can be as Figure 5 shown. The functional principles of each unit in the adaptive optimization module will be introduced in detail below.

[0135] The task parameter unit 31 can be used to extract the required parameters of the current task from the task parameter library stored in matrix form according to the correction instruction. Among them, the task parameter library can represent a parameter set stored in matrix form, and this parameter library contains historical optimization parameters in different task scenarios, which are used to provide reference values for different task requirements. The required parameters can represent the control parameters related to the current task extracted from the task parameter library, and this parameter can affect the attitude optimization process of the bracket to meet the requirements of specific application scenarios.

[0136] The parameter initial setting unit 32 can be used to determine the initial value of the bracket control parameter by combining the correction instruction and the extracted task parameters. Specifically, the process of determining the initial value of the bracket control parameter can be expressed as:

[0137]

[0138] where, represents the task parameters extracted from the task parameter library, represents the initial vector of the control parameter; represents the weight factor, which determines the influence ratio of the task parameters and the correction instruction; represents the current moment of the correction instruction. The purpose of the parameter initial setting unit is to provide an optimized initial reference value, ensure a reasonable starting point for the optimization algorithm, and reduce the convergence time.

[0139] The gradient optimization unit 33 can be used to iteratively adjust the initial value of the control parameter according to gradient descent. Specifically, it can be based on:

[0140]

[0141] to iteratively update the initial value of the control parameter, where, represents the parameter vector of the th iteration, represents the learning rate, represents the gradient of the performance error function.

[0142] The verification and adjustment unit 34 can be used to compare the actual attitude of the optimized bracket with the target attitude, and update the control parameter according to the comparison result. The update rule can be expressed as:

[0143]

[0144] Among them, represents the optimized parameters after the final adjustment; represents the optimized parameters obtained by the gradient optimization unit; represents the adjustment factor, which is used to balance the correction amplitude; and respectively represent the target attitude and the actual attitude of the bracket. Through the verification and adjustment unit, the control parameters can be further optimized, enabling the bracket to be accurately adjusted to the required attitude, and improving the control stability and adaptability.

[0145] In the control system for the installation bracket of the multi-beam detection device in the above embodiments, the system combines a closed-loop calibration module, a dynamic compensation module, and an adaptive optimization module to achieve high-precision dynamic adjustment of the bracket attitude, improving the stability and detection accuracy of the detection device in complex environments. Compared with traditional technologies, the present disclosure can adaptively adjust the control parameters according to external disturbances and task requirements, enabling the bracket to respond in real time and maintain the target attitude in complex environments.

[0146] First of all, the closed-loop calibration module can real-time obtain the attitude monitoring data of the bracket, and convert it into the attitude parameters of the bracket through a high-precision calculation method, ensuring the stability and accuracy of data calculation. Based on this parameter, the system can calculate the attitude deviation and generate a calibration instruction through a control algorithm, enabling the bracket to actively adjust to the target attitude, avoiding the decline in measurement accuracy caused by the accumulation of attitude errors in traditional methods.

[0147] Secondly, the dynamic compensation module can perform real-time monitoring and compensation for the attitude deviation caused by environmental vibration or other external disturbances. By analyzing the vibration signal and extracting specific frequency bands, the present disclosure can accurately identify the disturbance components affecting the bracket attitude, and combine an intelligent filtering algorithm to perform real-time estimation of the disturbance state. Through the calculation of the control compensation amount and real-time calibration, it is ensured that the compensation result can adapt to different working environments and effectively improve the dynamic stability of the bracket.

[0148] In addition, the adaptive optimization module enables the bracket to be precisely controlled according to task requirements through an intelligent parameter regulation mechanism. The system extracts relevant parameters from the historical data in the task parameter library and combines the real-time attitude adjustment data to calculate the initial value of the bracket control parameters. Different from the traditional fixed-parameter control method, the present disclosure uses an adaptive optimization algorithm to continuously optimize the control parameters, enabling the control system to quickly adjust to the optimal state under different task conditions, reducing the impact of parameter setting on the system performance. Through the intelligent learning mechanism, this module can dynamically adjust the optimization strategy, enabling the bracket to maintain high-precision regulation during long-term operation and having a high degree of task adaptability.

[0149] It should be noted that although several modules or units of the regulation system for the mounting bracket of the multi-beam detection device are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more of the above-described modules or units can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0150] Secondly, in an exemplary embodiment of the present disclosure, a regulation method for the mounting bracket of a multi-beam detection device is also provided. Referring to Figure 6 as shown, the regulation method for the mounting bracket of the multi-beam detection device may include the following steps:

[0151] Step S610, based on the real-time attitude monitoring data of the mounting bracket of the multi-beam detection device, obtain the real-time attitude parameters of the bracket, and compare the real-time attitude parameters with the preset target attitude data to generate a calibration instruction;

[0152] Step S620, according to the calibration instruction, combine the monitoring data of the vibration sensor and the displacement sensor to determine the attitude deviation of the bracket and perform a compensation calculation to generate a correction instruction;

[0153] Step S630, according to the correction instruction, combine the task parameters in the task parameter library, and optimize the control parameters of the bracket through an adaptive adjustment algorithm.

[0154] It should be noted that although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that these steps must be executed in that specific order, or that all the steps shown must be executed to achieve the desired result. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step for execution, and / or one step may be decomposed into multiple steps for execution, etc.

[0155] In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above-mentioned regulation method for the mounting bracket of the multi-beam detection device is also provided.

[0156] Those skilled in the art to which the present disclosure pertains can understand that various aspects of the present disclosure can be implemented as a system, method, or program product. Therefore, various aspects of the present disclosure can be specifically implemented in the following forms, namely: a complete hardware embodiment, a complete software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects, which can be collectively referred to herein as "circuit", "module", or "system".

[0157] Next, refer to Figure 7 to describe the electronic device 700 according to this embodiment of the present disclosure.Figure 7 The illustrated electronic device 700 is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present disclosure.

[0158] As Figure 7 shown, the electronic device 700 is presented in the form of a general-purpose computing device. The components of the electronic device 700 may include, but are not limited to: at least one of the above-mentioned processing units 710, at least one of the above-mentioned storage units 720, a bus 730 connecting different system components (including the storage unit 720 and the processing unit 710), and a display unit 740.

[0159] Among them, the storage unit stores program code, and the program code can be executed by the processing unit 710, so that the processing unit 710 executes the steps according to various exemplary embodiments of the present disclosure described in the "Exemplary Method" section of this specification. The storage unit 720 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 721 and / or a cache storage unit 722, and may further include a read-only storage unit (ROM) 723.

[0160] The storage unit 720 may further include a program / utility 724 having a set (at least one) of program modules 725. Such program modules 725 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data. The implementation of a network environment may be included in each or some combination of these examples.

[0161] The bus 730 may represent one or more of several types of bus structures, including a storage unit bus or a storage unit controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0162] The electronic device 700 can also communicate with one or more external devices 770 (such as a keyboard, a pointing device, a Bluetooth device, etc.), and can also communicate with one or more devices that enable a user to interact with the electronic device 700, and / or communicate with any device that enables the electronic device 700 to communicate with one or more other computing devices (such as a router, a modem, etc.). Such communication can be carried out through the input / output (I / O) interface 750. Moreover, the electronic device 700 can also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through the network adapter 760. As shown in the figure, the network adapter 760 communicates with other modules of the electronic device 700 through the bus 730. It should be understood that although not shown in the figure, other hardware and / or software modules can be used in combination with the electronic device 700, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0163] Through the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein can be implemented by software, or can be implemented by the way of software combined with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure can be embodied in the form of a software product, and the software product can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0164] In an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium, on which a program product capable of implementing the above method of this specification is stored. In some possible embodiments, various aspects of the present disclosure can also be implemented in the form of a program product, which includes program code. When the program product runs on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary embodiments of the present disclosure described in the above "Exemplary Method" section of this specification.

[0165] Reference Figure 8 As shown, a program product 800 for implementing the above method according to an embodiment of the present disclosure is described. It can adopt a portable compact disc read-only memory (CD-ROM) and include program code, and can run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto. In this document, the readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, device, or device.

[0166] The program product may employ any combination of one or more readable media. The readable media may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the readable storage medium (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0167] The computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which the readable program code is carried. Such a propagated data signal may take many forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the foregoing. The readable signal medium may also be any readable medium other than the readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device.

[0168] The program code contained on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, electromagnetic wave, etc., or any suitable combination of the foregoing.

[0169] The program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., and also including conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's device, executed as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., by connecting through the Internet using an Internet service provider).

[0170] In addition, the above drawings are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present disclosure, and are not for limiting purposes. It is easy to understand that the processes shown in the above drawings do not indicate or limit the chronological order of these processes. Additionally, it is also easy to understand that these processes may be executed, for example, synchronously or asynchronously in multiple modules.

[0171] Through the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein can be implemented by software or by a combination of software and necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (such as a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0172] After considering the specification and practicing the invention disclosed herein, those skilled in the art will readily conceive of other embodiments of the present disclosure. The present disclosure is intended to cover any variations, uses, or adaptations of the present disclosure, which follow the general principles of the present disclosure and include known common knowledge or conventional technical means in the technical field not disclosed by the present disclosure. The specification and the embodiments are only regarded as exemplary, and the true scope and spirit of the present disclosure are pointed out by the claims.

[0173] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present disclosure is only limited by the appended claims.

Claims

1. A control system for a mounting bracket of a multi-beam detection device, characterized in that, Including: A closed-loop calibration module, which is used to obtain the real-time attitude parameters of the bracket based on the real-time attitude monitoring data of the installation bracket of the multi-beam detection device, compare the real-time attitude parameters with the preset target attitude data, and generate a calibration instruction; A dynamic compensation module, which is used to determine the attitude deviation of the bracket and perform compensation calculation according to the calibration instruction output by the closed-loop calibration module and in combination with the monitoring data of the vibration sensor, and generate a correction instruction; An adaptive optimization module, which is used to adaptively adjust the control parameters of the bracket by gradient descent according to the correction instruction output by the dynamic compensation module and in combination with the task parameters in the task parameter library, so as to optimize the attitude of the bracket; The closed-loop calibration module includes: A data acquisition unit, which is used to collect the real-time attitude monitoring data of the installation bracket of the multi-beam detection device in real time through an inertial measurement component, and the real-time attitude monitoring data includes acceleration data and angular velocity data, determine the quaternion corresponding to the bracket at the initial moment, and update the quaternion according to the angular velocity data; Determine the actual direction vector corresponding to the acceleration data , and calculate the theoretical gravity direction vector according to the quaternion , where , represents the acceleration data; Determine the error between the actual direction vector and the theoretical gravity direction vector , and based on the derivative of the quaternion perform auxiliary correction, and use the derivative after auxiliary correction to recalculate , where represents the correction coefficient; Perform normalization processing on the corrected quaternion, convert the normalized quaternion into Euler angles, and use the Euler angles as the real-time attitude parameters of the bracket; The dynamic compensation module includes: A preprocessing unit, which is used to collect the vibration signal of the vibration sensor and perform Fourier transform on the vibration signal to obtain frequency domain data; A perturbation analysis unit, which is used to extract the perturbation signal in a specific frequency band from the frequency domain data and determine the perturbation state corresponding to the perturbation signal by using the state equation and the measurement equation; A correction instruction unit, which is used to determine the compensation amount according to the perturbation state according to the linear control law, and in combination with the calibration instruction, generate a correction instruction for adjusting the attitude of the bracket. The generation of the correction instruction is through the following steps: Settings Representation The dynamic characteristic parameters of the moment disturbance signal are defined as: Among them, represents the th component of the disturbance state; According to the linear control law, the compensation amount is determined by the product of the disturbance state and the feedback gain matrix: Among them, represents the compensation amount vector at the moment, represents the control gain matrix, represents the estimated value of the disturbance state at the moment; Calibration instruction Is defined as follows: Among them, represents a calibration instruction, represents a calibration gain matrix, represents a calibration error, defined as the difference between the current pose and the target pose; Correction instruction Generated by combining the compensation amount and the calibration instruction, and the formula is as follows: Among them, represents the correction instruction at the moment.

2. The regulation system for the mounting bracket of the multi-beam detection device according to claim 1, wherein, The closed-loop calibration module includes: A deviation calculation unit, which is used to compare the real-time attitude parameters with the preset target attitude data, determine the differences in the pitch, roll and yaw angles between the real-time attitude parameters and the target attitude data, so as to determine the attitude deviation; An instruction generation unit, which is used to perform arithmetic processing by using a PID controller according to the attitude deviation, and generate the calibration instruction for adjusting the attitude of the installation bracket of the multi-beam detection device.

3. The regulation system for the mounting bracket of the multi-beam detection device according to claim 1, characterized in that, The determination of the quaternion corresponding to the bracket at the initial moment and the update of the quaternion according to the angular velocity data includes: Set the initial time quaternion , where represents the scalar part of the quaternion , , represent the vector part of the quaternion According to: Determine the derivative of the quaternion , where represents the quaternion at time t , represents the quaternion multiplication operation represents expanding the angular velocity data into the quaternion form t represents time; According to iteratively update the quaternion, where represents the sampling time interval represents the updated quaternion corresponding to the time ​ 4. The regulation system for the mounting bracket of the multi-beam detection device according to claim 1, characterized in that, The determination of the perturbation state corresponding to the perturbation signal by using the state equation and the measurement equation includes: Construct the state equation and the measurement equation , where represents the state transition matrix, represents the input matrix, represents the observation matrix, represents the disturbance signal state vector, represents the process noise vector, represents the observation noise vector, represents the input vector; According to determine the predicted state at the moment , where represents the disturbance signal state vector corresponding to the moment , and represents the predicted state vector at the moment ; According to the moment observation vector determine the observation residual , where , and according to the Kalman gain matrix, the observation residual and the moment the predicted state vector at determine the estimated disturbance state corresponding to the disturbance signal at the moment.

5. The regulation system for the mounting bracket of the multi-beam detection device according to claim 1, wherein, The adaptive optimization module includes: A task parameter unit, which is used to extract the required parameters of the current task from the task parameter library stored in matrix form according to the correction instruction; A parameter initial setting unit, which is used to determine the initial value of the bracket control parameter in combination with the correction instruction and the extracted task parameters; A gradient optimization unit, which is used to iteratively adjust the initial value of the control parameter according to gradient descent; A verification and adjustment unit, which is used to compare the actual attitude of the optimized bracket with the target attitude, and update the control parameter according to the comparison result.

6. The regulation system for the mounting bracket of the multi-beam detection device according to claim 5, characterized in that, Iteratively adjusting the initial value of the control parameter according to gradient descent includes: According to: Iteratively update the initial value of the control parameter, where represents the parameter vector at the -th iteration, represents the learning rate, represents the gradient of the performance error function.

7. A regulation method for an installation bracket of a multi-beam detection device, applied to the regulation system for the installation bracket of a multi-beam detection device according to any one of the above-mentioned claims 1-6, characterized in that, The method includes: Based on the real-time attitude monitoring data of the mounting bracket of the multi-beam detection device, obtaining the real-time attitude parameters of the bracket, and comparing the real-time attitude parameters with preset target attitude data to generate a calibration instruction; According to the calibration instruction, combining the monitoring data of the vibration sensor and the displacement sensor, determining the attitude deviation of the bracket and performing compensation calculation to generate a correction instruction; According to the correction instruction, combining the task parameters in the task parameter library, optimizing the control parameters of the bracket through an adaptive adjustment algorithm.

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