Regulation and control system and method for mounting bracket of multi-beam detection device

Abstract

The invention provides a regulation and control system and method for a multi-beam detection device mounting bracket, and relates to the technical field of data processing. The system comprises a closed-loop calibration module used for acquiring real-time attitude parameters of a bracket based on real-time attitude monitoring data of a multi-beam detection device mounting bracket, and comparing the real-time attitude parameters with preset target attitude data to generate a calibration instruction; the dynamic compensation module is used for determining the attitude deviation of the bracket and performing compensation calculation according to the calibration instruction output by the closed-loop calibration module and the monitoring data of the vibration sensor to generate a correction instruction; and the adaptive optimization module is used for adaptively adjusting the control parameters of the bracket through gradient descent according to the correction instruction output by the dynamic compensation module in combination with the task parameters in the task parameter library so as to optimize the attitude of the bracket. According to the technical scheme provided by the invention, the detection accuracy and stability of the multi-beam detection device in various environments can be improved.

Description

Background Art

[0002] In the application of multi-beam detection devices, the bracket, as a key supporting structure, directly affects the detection accuracy and system stability. With the continuous change of technology, the detection environment has become more complex and changeable. The traditional bracket design can no longer meet the high requirements of modern detection tasks for accuracy and dynamic response.

[0003] In the prior art, the mounting bracket for the multi-beam detection device usually adopts a mechanical fixing structure or a simple manual adjustment system. Although such a structure can meet the basic installation requirements, it exposes many shortcomings when facing a complex detection environment. Especially in application scenarios that require dynamic adjustment, it is difficult for the bracket to effectively cope with the variability and uncertainty of the external environment. For example, vibration, tilt or other environmental interference may cause the bracket to shift in posture, further affecting the detection accuracy of the detection device. In addition, the prior art also has the problem of insufficient dynamic response capability. In actual use, the impact of changes in the external environment usually occurs in real time, and traditional brackets cannot complete the corresponding adjustments and compensation in a short time, which often leads to the continuous accumulation of posture deviations of the detection device, and even the risk of mission interruption. This problem is particularly prominent in scenarios involving high dynamic or high precision requirements (such as shipborne detection or mobile platform operations).

[0004] In view of the above defects, there is an urgent need for a technical solution that can achieve efficient perception and dynamic adjustment of the bracket posture, while having rapid response capabilities, to ensure the accuracy and stability of the multi-beam detection device 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 improving the accuracy and stability of the multi-beam detection device in various environments at least to a certain extent.

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

[0007] According to a first aspect of an embodiment of the present disclosure, a control system for a mounting bracket of a multi-beam detection device is provided, the system comprising: a closed-loop calibration module, for acquiring real-time attitude parameters of the mounting bracket of the multi-beam detection device based on real-time attitude monitoring data of the mounting bracket of the multi-beam detection device, and comparing the real-time attitude parameters with preset target attitude data to generate calibration instructions; a dynamic compensation module, for determining the attitude deviation of the bracket and performing compensation calculations to generate correction instructions based on the calibration instructions output by the closed-loop calibration module in combination with monitoring data of a vibration sensor; and an adaptive optimization module, for adaptively adjusting the control parameters of the bracket through gradient descent in combination with task parameters in a task parameter library based on the correction instructions output by the dynamic compensation module to optimize the attitude of the bracket.

[0008] According to a second aspect of an embodiment of the present disclosure, a control method for a mounting bracket of a multi-beam detection device is provided, the method comprising: based on real-time attitude monitoring data of the mounting bracket of the multi-beam detection device, acquiring real-time attitude parameters of the bracket, and comparing the real-time attitude parameters with preset target attitude data to generate calibration instructions; according to the calibration instructions, in combination with the monitoring data of a vibration sensor and a displacement sensor, determining the attitude deviation of the bracket and performing compensation calculations to generate correction instructions; according to the correction instructions, in combination with the task parameters in a task parameter library, optimizing the control parameters of the bracket through an adaptive adjustment algorithm.

[0009] According to a third aspect of an embodiment of the present disclosure, there is provided an electronic device, comprising: a processor; and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the above-mentioned control method for mounting a bracket for a multi-beam detection device is implemented.

[0010] According to a fourth aspect of an embodiment of the present disclosure, there is provided a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the control method for mounting a bracket for a multi-beam detection device is implemented according to the above-mentioned method.

[0011] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects: The control system for a multi-beam detection device mounting bracket in the exemplary embodiment of the present disclosure includes a closed-loop calibration module, a dynamic compensation module, and an adaptive optimization module.

[0012] 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 timely detect the deviation of the bracket attitude and generate calibration instructions to ensure that the bracket attitude is consistent with the predetermined target. As a result, the system can accurately monitor 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, the dynamic compensation module is combined with the vibration sensor monitoring data to compensate for the deviation of the bracket attitude according to the calibration instructions. This process can effectively eliminate the attitude error caused by vibration or external disturbance, thereby reducing the attitude drift caused by external factors and improving the detection accuracy of the multi-beam detection device. The correction instructions generated by the compensation calculation can further reduce the bracket deviation, optimize the motion state of the bracket, and provide guarantee for the precise operation of the equipment. Finally, with the help of the adaptive optimization module, combined with the task parameters in the task parameter library and the correction instructions 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, and effectively improve the flexibility and accuracy of the bracket attitude control. Through adaptive adjustment, the system can accurately optimize the motion state of the bracket according to the actual mission load and real-time data of the bracket movement, ensuring the best performance of the multi-beam detection device under various working conditions.

[0013] By integrating the collaborative work of the above modules, the present invention realizes high-precision control of the bracket posture, has robustness and adaptability in complex environments, and greatly improves the measurement accuracy and working stability of the multi-beam detection device.

[0014] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0016] Figure 1 The present invention schematically shows a composition diagram of a control system for a mounting bracket of a multi-beam detection device according to some embodiments of the present disclosure.

[0017] Figure 2 A schematic diagram of the composition of another control system for a mounting bracket of a multi-beam detection device according to some embodiments of the present disclosure is schematically shown.

[0018] Figure 3The following schematically shows a workflow diagram of a closed-loop calibration module according to some embodiments of the present disclosure.

[0019] Figure 4 The following schematically shows a working flow diagram of a dynamic compensation module according to some embodiments of the present disclosure.

[0020] Figure 5 A schematic diagram of the workflow of an adaptive optimization module according to some embodiments of the present disclosure is schematically shown.

[0021] Figure 6 A flow chart of a method for controlling a mounting bracket of a multi-beam detection device according to some embodiments of the present disclosure is schematically shown.

[0022] Figure 7 A schematic diagram of the structure of a computer system of an electronic device according to some embodiments of the present disclosure is schematically shown.

[0023] Figure 8 A schematic diagram of a computer-readable storage medium according to some embodiments of the present disclosure is schematically shown.

[0024] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0025] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying 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 implementations described in the following exemplary embodiments do not represent all implementations consistent with this specification. Instead, they are merely examples of devices and methods consistent with some aspects of this specification as detailed in the appended claims.

[0026] The terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit this specification. The singular forms "a", "the" and "the" used in this specification and the appended claims are also intended to include 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 associated listed items.

[0027] It should be understood that although the terms first, second, third, etc. may be used in this specification to describe various information, this information should not be limited to these terms. These terms are only used to distinguish the same type of information 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 "at the time of" or "when" or "in response to determining".

[0028] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of 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 comprehensive and complete and will fully convey the concept of the example embodiments to those skilled in the art.

[0029] In addition, the described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring the various aspects of the present disclosure.

[0030] Furthermore, the drawings are only schematic illustrations 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 separate entities. That is, these functional entities may 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.

[0031] In the application of multi-beam detection devices, the bracket, as a key supporting structure, directly affects the detection accuracy and system stability. However, in the related art, the mounting bracket of the multi-beam detection device usually adopts a mechanical fixing structure or a manual adjustment system, and these brackets have significant deficiencies in complex environments. First, external interference such as vibration and tilt may cause the bracket to shift in posture, affecting the detection accuracy. Secondly, the existing bracket lacks real-time dynamic adjustment capabilities and cannot respond and compensate quickly when the environment changes, resulting in the accumulation of posture deviations and affecting the detection stability. Especially in scenarios with high dynamics or high precision requirements, traditional brackets cannot meet the needs of real-time adjustment and compensation.

[0032] In order 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 1The schematic diagram of the components of the control system for mounting a bracket of a multi-beam detection device according to some embodiments of the present disclosure is shown schematically. Figure 1 As shown, the control system for the multi-beam detection device mounting bracket may include the following modules: The closed-loop calibration module 1 is used to obtain the real-time attitude parameters of the bracket based on the real-time attitude monitoring data of the bracket installed by the multi-beam detection device, and compare the real-time attitude parameters with the preset target attitude data to generate a calibration instruction; The dynamic compensation module 2 is used to determine the posture deviation of the bracket and perform compensation calculation according to the calibration instruction output by the closed-loop calibration module and the monitoring data of the vibration sensor to generate a correction instruction; The adaptive optimization module 3 is used to adaptively adjust the control parameters of the bracket through gradient descent according to the correction instructions output by the dynamic compensation module and the task parameters in the task parameter library, so as to optimize the posture of the bracket.

[0033] Specifically, the control system for the mounting bracket of the multi-beam detection device includes a plurality of modules, and each module works together to achieve precise adjustment of the posture of the bracket.

[0034] First, the closed-loop calibration module 1 obtains the current posture parameters of the bracket through real-time posture monitoring data. The module compares the posture with the preset target posture data to determine whether there is a deviation in the posture of the bracket, and generates corresponding calibration instructions accordingly. The main function of the closed-loop calibration module 1 is to realize real-time monitoring of the posture of the bracket, ensuring that the bracket can maintain a position close to the target posture at any time, thereby providing an accurate data basis for subsequent compensation and optimization work.

[0035] Next, the dynamic compensation module 2 further analyzes the deviation of the bracket posture according to the calibration instructions output by the closed-loop calibration module 1 and the monitoring data of the vibration sensor. By monitoring vibration or other external disturbances, the module can calculate and generate correction instructions in real time to dynamically compensate for the bracket posture. This compensation process can effectively eliminate the posture error caused by external vibration, impact or other environmental changes, ensure that the bracket always maintains a stable working posture, and avoid the adverse effects of posture deviation on detection accuracy.

[0036] 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 through the gradient descent method. Through this process, the system can automatically optimize the posture 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 continue to maintain the optimal posture configuration under various dynamic changes.

[0037] 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 that can monitor, compensate and optimize the support attitude in real time. Through the synergy of these modules, the system can accurately control the support 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 dynamic or high precision requirements.

[0038] Next, in other embodiments of the present disclosure, the control system for the mounting bracket of the multi-beam detection device is further described.

[0039] refer to 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 workflow of the adaptive optimization module can be as follows: Figure 3 As shown, the functional principles of each unit in the closed-loop calibration module are introduced in detail below.

[0040] The data acquisition unit 11 can be used to collect the real-time attitude monitoring data of the mounting bracket of the multi-beam detection device in real time through the 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 sensor combination for measuring acceleration, angular velocity and direction change, which can include accelerometers, gyroscopes and magnetometers. The multi-beam detection device can represent a device that can perform high-precision detection in a wide area by simultaneously transmitting and receiving signals through multiple detection beams, which can be used for measurement tasks in underwater or marine environments. The mounting bracket of the device is used to support and fix the detection device to ensure that it maintains the required attitude stability during operation. The attitude monitoring data can represent the real-time data about the current attitude of the bracket provided by the inertial measurement component, which is used to describe the spatial position and direction change of the bracket. The attitude parameters can represent the specific parameters about the attitude of the bracket 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.

[0041] In some embodiments, the real-time attitude monitoring data includes acceleration data and angular velocity data, and the real-time attitude monitoring data is converted into the real-time attitude parameters of the bracket, specifically including the following technical steps: The first step is to 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 posture data at the initial moment. In this embodiment, the quaternion is updated by the angular velocity data obtained by the inertial measurement component, thereby realizing dynamic posture tracking. The angular velocity data can represent the real-time data on the rotation rate of the bracket collected by the inertial measurement component.

[0042] Specifically, the quaternion can be updated through the following process: First, set the initial time The quaternion ,in, represents the scalar part of the quaternion, , , Represents the vector part of the quaternion. By initializing the quaternion, the posture of the bracket at the starting time is clarified, providing a reference point for subsequent dynamic updates.

[0043] Then, according to: Determining the derivative of a quaternion ,in, Indicates time t The quaternion of represents quaternion multiplication operation, Indicates that the angular velocity data Expanded to quaternion form, t Represents time. The change rate of the support attitude is obtained by the mutual operation of the current quaternion and the angular velocity data. This derivative term reflects the trend of the support attitude changing over time and provides accurate dynamic information for the quaternion update at the next moment.

[0044] Finally, according to Iteratively update the quaternion, where represents the sampling time interval, Indicates at time The corresponding updated quaternion. The prediction and calculation of the posture at the next moment are completed by adding the product of the derivative term and the time step to the quaternion at the current moment.

[0045] The second step is to use the acceleration data to assist in correcting the updated quaternion. The acceleration data can represent the real-time data about the acceleration of the bracket collected by the inertial measurement unit, which can be provided by the accelerometer. Using the acceleration data, the updated quaternion can be assisted in correcting the accumulated error caused by the angular velocity data. By combining the acceleration data with the quaternion, the accuracy of the attitude estimation can be improved, especially the error compensation effect at small angle changes.

[0046] Specifically, the process of auxiliary correction of the updated quaternion is as follows: First, determine the actual direction vector corresponding to the acceleration data , and according to the quaternion Calculate the theoretical gravity direction vector ,in, Represents acceleration data. The actual direction vector refers to the unit vector calculated based on the acceleration data collected by the inertial measurement component, which represents the normalized direction of the acceleration data at the current moment. Theoretical gravity direction vector The quaternion at the current moment can be Initial gravity direction vector The calculation formula is: in, Represents the standard gravity direction unit vector in the inertial coordinate system, and its value is , and Respectively represent the current quaternion and its conjugate inverse operation, Represents quaternion multiplication.

[0047] Then, determine the error between the actual direction vector and the theoretical gravity direction vector , and according to Derivatives with respect to quaternions Perform auxiliary correction and use the derivative after auxiliary correction Recalculate ,in, Represents the correction coefficient. Specifically, the theoretical gravity direction vector refers to the current quaternion The calculated unit vector of gravity direction corresponding to the theoretical posture of the bracket reflects the theoretical gravity direction of the bracket posture in the inertial coordinate system. Corrected quaternion By recalculating , and correct the attitude deviation. This process can significantly reduce the attitude deviation caused by cumulative error or transient error, thereby improving the accuracy and stability of the bracket attitude control.

[0048] The third step is to normalize the corrected quaternion and convert it into Euler angles, which are used as the real-time attitude parameters of the bracket. The corrected quaternion is normalized to ensure that its value conforms to the unit length constraint of the quaternion. Euler angles can represent a commonly used three-dimensional rotation angle representation method, which is usually composed of three angle parameters, such as pitch angle, yaw angle and roll angle.

[0049] Specifically, the corrected quaternion is normalized to ensure that its physical meaning conforms to the characteristics of the unit quaternion, thereby avoiding errors introduced during the rotation calculation due to the modulus not being 1. The normalized formula is: in, represents the normalized quaternion, Represents the corrected quaternion; Represents the modulus of the quaternion, and its calculation formula is: in, They are The scalar part and three vector components of the quaternion can represent the rotation amplitude and rotation axis direction of the quaternion. After normalization, the normalized quaternion satisfies the unit length property, that is, .

[0050] Then, the normalized quaternion Convert to Euler angles , respectively represent the roll angle, pitch angle and yaw angle of the bracket, and the calculation formula is as follows: Roll The calculation formula is: Pitch The calculation formula is: Yaw The calculation formula is: in, is the scalar part of the quaternion, indicating the rotation amplitude; The vector component of the quaternion represents the component in the direction of the rotation axis. The Euler angle calculated by the above formula The three-dimensional rotation state of the bracket in the inertial coordinate system is accurately described. As the real-time attitude parameter of the bracket, the Euler angle can intuitively reflect the attitude of the bracket in the roll, pitch and yaw directions, providing reliable support for the attitude control of the multi-beam detection device.

[0051] The deviation calculation unit 12 can be used to compare the real-time attitude parameters with the preset target attitude data, determine the difference between the real-time attitude parameters and the target attitude data in pitch, roll and yaw angles, and thus determine the attitude deviation. The attitude deviation can represent the difference between the real-time attitude parameters and the preset target attitude data, specifically including the deviation amount in three dimensions of pitch angle, roll angle and yaw angle, and the attitude deviation can be used to quantify the degree of deviation between the current support attitude and the target attitude.

[0052] The instruction generation unit 13 can be used to generate a calibration instruction for adjusting the posture of the multi-beam detection device mounting bracket by performing calculation processing using a PID controller according to the posture deviation.

[0053] Specifically, the instruction generation unit 13 generates an instruction based on the posture deviation. The calculation logic of the PID controller generates calibration instructions for adjusting the posture of the mounting bracket of the multi-beam detection device. They represent roll angle deviation, pitch angle deviation and yaw angle deviation respectively. The operation process of PID controller comprehensively considers the three controls of proportion (P), integration (I) and differentiation (D) to ensure the precise adjustment and dynamic response of calibration instructions to attitude deviation. The basic operation formula of PID controller can be expressed as: in, Indicates the calibration instruction generated at the current moment; They represent the proportional, integral and differential control coefficients respectively, and are used to adjust the weights of the controller for different control items; Indicates the error amount at the current moment, corresponding to the target component of the attitude deviation (such as pitch angle deviation ); Indicates that from the initial moment To the current time The error integral is used to compensate for the accumulated error; It indicates the rate of change of the current error based on time, that is, the differential of the error, reflecting the trend of error change.

[0054] For this example, the calibration instruction The pitch, roll and yaw angles of the bracket are calculated separately. The specific calculation formulas are as follows: in, 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; Represents the attitude deviations of roll, pitch and yaw angles respectively; are the integral terms corresponding to the angle deviation respectively; are the differential terms corresponding to the angular deviations.

[0055] Based on the above process, the PID controller processes each posture deviation component in real time to generate the calibration instruction Directly reflects the amount of adjustment required to correct the bracket's posture. These calibration instructions are transmitted to the actuator to adjust the bracket's actual posture so that it gradually approaches the target posture. Through the comprehensive effects of the PID controller's proportion, integration, and differentiation, the system can achieve rapid response to posture deviations, correction of accumulated errors, and smooth adjustment of dynamic changes, ensuring accurate control and stable adjustment of the bracket's posture.

[0056] Next reference 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 workflow of the dynamic compensation module may be as follows: Figure 4 As shown, the functional principles of each unit in the dynamic compensation module are introduced in detail below.

[0057] The preprocessing unit 21 can be used to collect the vibration signal of the vibration sensor and perform Fourier transform on the vibration signal to obtain frequency domain data. Among them, the vibration signal can represent a time-varying signal collected by the vibration sensor, which reflects the vibration characteristics of the bracket in the working environment. Fourier transform can represent a method of mathematically transforming a vibration signal, which converts the vibration signal from the time domain to the frequency domain, so that the amplitude and phase information of different frequency components can be clearly separated, thereby facilitating the analysis of disturbances in a specific frequency band. Frequency domain data can represent the representation of the vibration signal obtained by Fourier transform in the frequency domain, which is composed of the amplitude and phase of multiple frequency components and can reflect the energy distribution of the vibration signal at different frequencies.

[0058] Specifically, the vibration signal can be expressed as a continuous time signal Indicates that Indicates the vibration amplitude that changes with time. It is the time domain data collected in real time by the vibration sensor. In order to analyze the frequency domain characteristics of the signal, Fourier transform is used to Perform frequency domain conversion, and the transformation formula is: in, Represents the frequency domain signal, that is, the spectrum after Fourier transform; Represents frequency variable, reflecting the frequency component of the signal; is a complex exponential kernel function, which represents the transformation basis for mapping the signal from the time domain to the frequency domain.

[0059] 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: in, Represents the frequency domain data frequency components; The discrete vibration signal sampling points; Represents the total number of sampling points of the discrete signal; Represents the frequency index of frequency domain data; Represents the basis functions of the discrete Fourier transform.

[0060] The disturbance analysis unit 22 can be used to extract the disturbance signal of a specific frequency band from the frequency domain data, and determine the disturbance state corresponding to the disturbance signal using the state equation and the measurement equation. Among them, the disturbance signal can represent a specific frequency band signal selected in the frequency domain data, which corresponds to a dynamic disturbance factor that may affect the stability of the bracket. The state equation can represent a mathematical model for describing the change of the disturbance signal over time. The equation uses the dynamic characteristics of the system to quantify the relationship between the disturbance state and the input signal, thereby providing a mathematical description of the disturbance behavior. The measurement equation can represent a mathematical equation for associating the actual measured vibration signal data with the theoretical state model. The disturbance state can represent the characteristic parameters of the disturbance signal estimated by the state equation and the measurement equation.

[0061] Specifically, the process of extracting a disturbance signal in a specific frequency band from frequency domain data includes the following steps: First, determine the target frequency range ,in, Indicates the lowest frequency of the target frequency band; Indicates the highest frequency in the target frequency band.

[0062] The frequency resolution formula , the frequency range Convert to frequency domain index range , and its calculation formula is: in, and are the start and end indexes of the frequency band respectively; Indicates the sampling frequency of the vibration signal; represents the total number of sampling points of discrete Fourier transform, k represents the corresponding frequency index in the frequency domain, Represents the first k The frequency value corresponding to the frequency component.

[0063] In the frequency domain Extract specific frequency band signals The formula is as follows: in, The discrete Fourier transform of the frequency domain signal frequency components; Indicates the extracted signal in a specific frequency band.

[0064] The extracted frequency domain data Perform inverse discrete Fourier transform to reconstruct the time domain representation of the target frequency band signal : 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.

[0065] 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: 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.

[0066] 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 .

[0067] 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 : 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.

[0068] Calculate the Kalman gain matrix The calculation process is as follows: in, express The Kalman gain matrix at time , represents the observation noise covariance matrix, express The state estimation error covariance matrix at time , Represents the transpose of the observation matrix.

[0069] Combine the predicted state and observed residuals to update The estimated value of the state at time : Update the covariance matrix according to the following formula: in, Represents the identity matrix, which is used to keep the matrix dimensions consistent.

[0070] Finally, we get The estimated value of the disturbance state corresponding to the disturbance signal at the moment , and the updated covariance matrix These results can be used to further analyze the dynamic characteristics of the disturbance signal and its impact on the system.

[0071] The correction instruction unit 23 can be used to determine the compensation amount according to the disturbance state and the linear control law, and generate a correction instruction for adjusting the support posture in combination with the calibration instruction. Among them, the linear control law can represent a control strategy for calculating the compensation amount according to the disturbance state. The control law uses a linear operation method to generate corresponding compensation instructions according to the disturbance state variable to reduce or offset the influence of the disturbance on the support posture. The compensation amount can represent an adjustment value calculated according to the linear control law to offset the influence of the disturbance.

[0072] Specifically, the generation of the correction instruction can be performed through the following steps: First, given the known disturbance state estimate Based on , the linear control law is used to calculate the compensation amount, and the correction instruction is generated in combination with the calibration instruction. Specifically, set express The dynamic characteristic parameters of the disturbance signal at each moment include position, velocity, acceleration, etc. It can be defined as: in, The disturbance state components, specifically an estimate of the current state of the system.

[0073] Then, according to the linear control law, the compensation Determined by multiplying the disturbance state by the feedback gain matrix: in, express The compensation vector at the moment; represents the control gain matrix, which is used to adjust the system feedback strength. express The estimated value of the disturbance state at time .

[0074] Calibration instructions It is generated according to the closed-loop calibration module and is used to correct the initial posture deviation of the bracket. It is defined as follows: in, Indicates calibration instructions; represents the calibration gain matrix; represents the calibration error, which can be defined as the difference between the current pose and the target pose.

[0075] Final Amendment Order Combining the compensation amount with the calibration instruction, the formula is as follows: in, express Correction instructions at the time.

[0076] The correction instructions generated Input to the support control system to adjust the support's attitude to achieve the effect of suppressing disturbances and restoring balance. The correction command converts the signal into a specific action through the actuator to adjust the support's attitude parameters (such as pitch angle, yaw angle, and roll angle) in real time.

[0077] Next reference Figure 2 In some embodiments, the adaptive optimization module 3 includes a task parameter unit 31, a parameter initialization unit 32, a gradient optimization unit 33, and a verification adjustment unit 34. The workflow of the adaptive optimization module can be as follows: Figure 5 As shown, the functional principles of each unit in the adaptive optimization module are introduced in detail below.

[0078] The task parameter unit 31 can be used to extract the required parameters of the current task from the task parameter library stored in the form of a matrix according to the correction instruction. The task parameter library can represent a parameter set stored in the form of a matrix, and the parameter library contains historical optimization parameters under 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, which can affect the posture optimization process of the bracket to adapt to the requirements of the specific application scenario.

[0079] The parameter initialization unit 32 can be used to combine the correction instruction with the extracted task parameter to determine the initial value of the support control parameter. Specifically, the process of determining the initial value of the support control parameter can be expressed as: in, represents the task parameters extracted from the task parameter library, represents the initial vector of control parameters; Represents the weight factor, which determines the influence ratio of task parameters and correction instructions; Indicates the current time The purpose of the parameter initialization unit is to provide the initial reference value for optimization, ensure that the starting point of the optimization algorithm is reasonable, and reduce the convergence time.

[0080] The gradient optimization unit 33 may be used to iteratively adjust the initial value of the control parameter according to the gradient descent. Specifically, it may be based on: Iteratively update the initial value of the control parameter, where: Indicates The parameter vector for the iteration, represents the learning rate, represents the gradient of the performance error function.

[0081] The verification and adjustment unit 34 can be used to compare the actual posture of the optimized bracket with the target posture, and update the control parameters according to the comparison result. The update rule can be expressed as: in, Represents the final adjusted optimization parameters; Represents the optimization parameters obtained by the gradient optimization unit; Represents the adjustment factor, used to balance the correction amplitude; and They represent the target posture and actual posture of the bracket respectively. By verifying the adjustment unit, the control parameters can be further optimized so that the bracket can be accurately adjusted to the required posture, improving the control stability and adaptability.

[0082] In the control system for mounting a bracket for a multi-beam detection device in the above-mentioned embodiment, the system realizes high-precision dynamic adjustment of the bracket posture by combining a closed-loop calibration module, a dynamic compensation module and an adaptive optimization module, thereby improving the stability and detection accuracy of the detection device in a complex environment. Compared with traditional technologies, the present disclosure can adaptively adjust control parameters according to external disturbances and task requirements, so that the bracket can respond in real time and maintain the target posture in a complex environment.

[0083] First, the closed-loop calibration module can obtain the posture monitoring data of the bracket in real time and convert it into the posture parameters of the bracket through high-precision calculation methods to ensure the stability and accuracy of data calculation. Based on this parameter, the system can calculate the posture deviation and generate calibration instructions through the control algorithm, so that the bracket can actively adjust to the target posture, avoiding the decrease in measurement accuracy caused by the accumulation of posture errors in traditional methods.

[0084] Secondly, the dynamic compensation module can monitor and compensate for posture deviations caused by environmental vibration or other external interference in real time. By analyzing the vibration signal and extracting specific frequency bands, the present invention can accurately identify the disturbance components that affect the posture of the bracket, and combine the intelligent filtering algorithm to estimate the disturbance state in real time. By controlling the calculation and real-time calibration of the compensation amount, it is ensured that the compensation result can adapt to different working environments and effectively improve the dynamic stability of the bracket.

[0085] In addition, the adaptive optimization module enables the bracket to be precisely controlled according to mission requirements through an intelligent parameter control mechanism. The system extracts relevant parameters based on historical data in the mission parameter library, and calculates the initial values ​​of the bracket control parameters in combination with real-time attitude adjustment data. Unlike traditional fixed parameter control methods, the present disclosure adopts an adaptive optimization algorithm to continuously optimize the control parameters, so that the control system can quickly adjust to the optimal state under different mission conditions, reducing the impact of parameter settings on system performance. Through an intelligent learning mechanism, the module can dynamically adjust the optimization strategy, so that the bracket can maintain high-precision control during long-term operation and have a high degree of mission adaptability.

[0086] It should be noted that, although several modules or units of the control system for the multi-beam detection device mounting bracket are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiment of the present disclosure, the features and functions of two or more modules or units described above can be concretized in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units for concretization.

[0087] Secondly, in an exemplary embodiment of the present disclosure, a method for controlling a mounting bracket of a multi-beam detection device is also provided. Figure 6 As shown, the control method for mounting a bracket of a multi-beam detection device may include the following steps: Step S610, 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 the preset target attitude data to generate a calibration instruction; Step S620, according to the calibration instruction, combined with the monitoring data of the vibration sensor and the displacement sensor, determine the posture deviation of the bracket and perform compensation calculation to generate a correction instruction; Step S630: According to the correction instruction and in combination with the task parameters in the task parameter library, the control parameters of the bracket are optimized by an adaptive adjustment algorithm.

[0088] 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 the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0089] In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above-mentioned control method for a mounting bracket of a multi-beam detection device is also provided.

[0090] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure may be specifically implemented in the following forms, namely: complete hardware embodiments, complete software embodiments (including firmware, microcode, etc.), or embodiments combining hardware and software aspects, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0091] Refer to the following Figure 7 hereinafter describes an electronic device 700 according to such an embodiment of the present disclosure. Figure 7 The electronic device 700 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0092] like Figure 7 As shown, the electronic device 700 is in the form of a general computing device. The components of the electronic device 700 may include but are not limited to: the at least one processing unit 710, the at least one storage unit 720, a bus 730 connecting different system components (including the storage unit 720 and the processing unit 710), and a display unit 740.

[0093] The storage unit stores program codes, which 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 above “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.

[0094] The storage unit 720 may also include a program / utility 724 having a set (at least one) of program modules 725, such program modules 725 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0095] Bus 730 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0096] The electronic device 700 may also communicate with one or more external devices 770 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may 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 (e.g., routers, modems, etc.). This communication may be performed through an input / output (I / O) interface 750. In addition, the electronic device 700 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter 760. As shown, the network adapter 760 communicates with other modules of the electronic device 700 through a bus 730. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction 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.

[0097] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present disclosure can be embodied in the form of a software product, which 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, and includes a number of 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 embodiment of the present disclosure.

[0098] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present 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 a program code. When the program product is run 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 the present specification.

[0099] refer to Figure 8 As shown, a program product 800 for implementing the above method according to an embodiment of the present disclosure is described, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be 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, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus or a device.

[0100] The program product may adopt any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with 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 thereof.

[0101] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0102] The program code contained on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, electromagnetic waves, etc., or any suitable combination of the foregoing.

[0103] 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 conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user 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 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., through the Internet using an Internet service provider).

[0104] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present disclosure, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0105] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present disclosure can be embodied in the form of a software product, which 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, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiment of the present disclosure.

[0106] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

[0107] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A control system for a mounting bracket of a multi-beam detection device, characterized in that: include: A closed-loop calibration module, for obtaining real-time attitude parameters of the bracket based on real-time attitude monitoring data of the bracket mounted by the multi-beam detection device, and comparing the real-time attitude parameters with preset target attitude data to generate a calibration instruction; A dynamic compensation module is used to determine the posture 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; The adaptive optimization module is used to adaptively adjust the control parameters of the bracket through gradient descent according to the correction instructions output by the dynamic compensation module and in combination with the task parameters in the task parameter library, so as to optimize the posture of the bracket.

2. The control system for mounting a bracket for a multi-beam detection device according to claim 1, characterized in that: The closed-loop calibration module comprises: A data acquisition unit, used to acquire real-time attitude monitoring data of the mounting bracket of the multi-beam detection device in real time through an inertial measurement assembly, and convert the real-time attitude monitoring data into real-time attitude parameters of the bracket; a deviation calculation unit, used for comparing the real-time attitude parameter with preset target attitude data, determining the difference between the real-time attitude parameter and the target attitude data in pitch, roll and yaw angles, thereby determining the attitude deviation; The instruction generation unit is used to generate the calibration instruction for adjusting the posture of the multi-beam detection device mounting bracket by performing calculation processing using a PID controller according to the posture deviation.

3. The control system for mounting a bracket for a multi-beam detection device according to claim 2, characterized in that: The real-time attitude monitoring data includes acceleration data and angular velocity data, and the step of converting the real-time attitude monitoring data into the real-time attitude parameters of the bracket includes: Determine the quaternion corresponding to the bracket at an initial moment, and update the quaternion according to the angular velocity data; Using the acceleration data to perform auxiliary correction on the updated quaternion; The corrected quaternion is normalized, and the normalized quaternion is converted into Euler angles, and the Euler angles are used as real-time posture parameters of the bracket.

4. The control system for mounting a bracket for a multi-beam detection device according to claim 3, characterized in that: The determining the quaternion corresponding to the bracket at the initial moment and updating the quaternion according to the angular velocity data includes: Set initial time The quaternion ,in, represents the scalar part of the quaternion, , , represents the vector portion of the quaternion; according to: Determine the derivative of the quaternion ,in, Indicates time t The quaternion of represents quaternion multiplication operation, Indicates that the angular velocity data Expanded to quaternion form, t Indicates time; according to The quaternion is iteratively updated, wherein, represents the sampling time interval, Indicates at time The corresponding updated quaternion.

5. The control system for mounting a bracket for a multi-beam detection device according to claim 4, characterized in that: The using the acceleration data to perform auxiliary correction on the updated quaternion includes: Determine the actual direction vector corresponding to the acceleration data , and according to the quaternion Calculate the theoretical gravity direction vector ,in, represents the acceleration data; Determine the error between the actual direction vector and the theoretical gravity direction vector , and according to Derivatives with respect to quaternions Perform auxiliary correction and use the derivative after auxiliary correction Recalculate ,in, Indicates the correction factor.

6. The control system for mounting a bracket for a multi-beam detection device according to claim 1, characterized in that: The dynamic compensation module comprises: A preprocessing unit, used for collecting a vibration signal from a vibration sensor and performing Fourier transform on the vibration signal to obtain frequency domain data; A disturbance analysis unit, used to extract a disturbance signal of a specific frequency band from the frequency domain data, and determine a disturbance state corresponding to the disturbance signal by using a state equation and a measurement equation; The correction instruction unit is used to determine the compensation amount according to the disturbance state and the linear control law, and generate a correction instruction for adjusting the posture of the bracket in combination with the calibration instruction.

7. The control system for mounting a bracket for a multi-beam detection device according to claim 6, characterized in that: Determining the disturbance state corresponding to the disturbance signal by using the state equation and the measurement equation includes: Constructing the state equation 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; 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 ; according to Time observation vector Determine the observed residuals ,in, , and according to the Kalman gain matrix, the observation residual and the moment The predicted state vector Sure The disturbance state estimation value corresponding to the disturbance signal at time instant.

8. The control system for mounting a bracket for a multi-beam detection device according to claim 1, characterized in that: The adaptive optimization module comprises: A task parameter unit, used to extract the required parameters of the current task from a task parameter library stored in a matrix form according to the correction instruction; The parameter initialization unit is used to determine the initial value of the support control parameter by combining the correction instruction with the extracted task parameter; A gradient optimization unit, used for iteratively adjusting the initial value of the control parameter according to the gradient descent; The verification and adjustment unit is used to compare the actual posture of the optimized bracket with the target posture, and update the control parameters according to the comparison result.

9. The control system for mounting a bracket for a multi-beam detection device according to claim 8, characterized in that: The iterative adjustment of the initial value of the control parameter according to the gradient descent comprises: according to: The initial value of the control parameter is iteratively updated, wherein: Indicates The parameter vector for the iteration, represents the learning rate, represents the gradient of the performance error function.

10. A control method for a mounting bracket of a multi-beam detection device, applied to a control system for a mounting bracket of a multi-beam detection device as described in any one of claims 1 to 9, characterized in that: The method comprises: Based on the real-time attitude monitoring data of the mounting bracket of the multi-beam detection device, the real-time attitude parameters of the bracket are obtained, and the real-time attitude parameters are compared with the preset target attitude data to generate a calibration instruction; According to the calibration instruction, combined with the monitoring data of the vibration sensor and the displacement sensor, the posture deviation of the bracket is determined and compensation calculation is performed to generate a correction instruction; According to the correction instruction and in combination with the task parameters in the task parameter library, the control parameters of the bracket are optimized through an adaptive adjustment algorithm.

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