Radio frequency signal debugging method and device based on meta-heuristic algorithm, medium and product

Abstract

The invention discloses a radio frequency signal debugging method and device based on a meta-heuristic algorithm, a medium and a product, and relates to the field of multi-coupler particle accelerator debugging, and the method comprises the steps: obtaining the current phase of a radio frequency signal outputted by a low-level control system and the current gain of each channel of the low-level control system; a meta-heuristic algorithm is adopted to optimize the current phase and the current gain, and the optimal phase and the optimal gain are determined; and debugging the radio frequency signal based on the optimal phase and the optimal gain. According to the invention, the consistency of the output power of each coupler can be realized, the reflection power is reduced to the greatest extent, and the accurate debugging of radio frequency signals and the overall stability of the system are ensured.

Description

Technical Field

[0001] The present application relates to the field of multi-coupler particle accelerator debugging, and in particular to a radio frequency signal debugging method, device, medium and product based on a meta-heuristic algorithm. Background Art

[0002] In the AB-BNCT (accelerator-based boron neutron capture therapy) device, the phase and gain debugging of the low-level control system (LLRF) of the multi-coupler accelerator is a complex process, especially in medical devices, which require extremely high stability and precision of the equipment. The traditional manual debugging method is time-consuming and difficult to ensure the best output effect. It is difficult to adapt to the mutual influence between the multi-couplers, and it is easy to cause excessive reflected power, affecting the stability of the system. Summary of the invention

[0003] The purpose of this application is to provide a method, device, medium and product for debugging a radio frequency signal based on a meta-heuristic algorithm. By introducing a meta-heuristic algorithm, more efficient and stable radio frequency signal debugging can be achieved.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] In a first aspect, the present application provides a radio frequency signal debugging method based on a meta-heuristic algorithm, comprising:

[0006] Acquire the current phase of the radio frequency signal output by the low-level control system and the current gain of each channel of the low-level control system;

[0007] The meta-heuristic algorithm is used to optimize the current phase and current gain to determine the optimal phase and optimal gain;

[0008] The radio frequency signal is debugged based on the optimal phase and the optimal gain.

[0009] In a second aspect, the present application provides a radio frequency signal debugging device based on a meta-heuristic algorithm, comprising:

[0010] An acquisition module, used to acquire the current phase of the radio frequency signal output by the low-level control system and the current gain of each channel of the low-level control system;

[0011] An optimization module is used to optimize the current phase and the current gain by using a meta-heuristic algorithm to determine the optimal phase and the optimal gain;

[0012] A debugging module is used to debug the radio frequency signal based on the optimal phase and the optimal gain.

[0013] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned radio frequency signal debugging method based on a meta-heuristic algorithm.

[0014] In a fourth aspect, the present application provides a computer program product, including a computer program, which implements the above-mentioned radio frequency signal debugging method based on the meta-heuristic algorithm when executed by a processor.

[0015] According to the specific embodiments provided in this application, this application has the following technical effects:

[0016] The present application provides a method, device, medium and product for debugging radio frequency signals based on a meta-heuristic algorithm, which utilizes a meta-heuristic algorithm to automatically adjust the phase of the radio frequency signal output by the low-level control system and the gain of each channel of the low-level control system to achieve consistency in the output power on each coupler and minimize reflected power, thereby ensuring accurate debugging of the radio frequency signal and overall stability of the system, and is particularly suitable for medical equipment with extremely high requirements for stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a schematic diagram of the structure of the low-level system of the AB-BNCT cavity;

[0019] Figure 2 A schematic diagram of a flow chart of a radio frequency signal debugging method based on a meta-heuristic algorithm provided in an embodiment of the present application;

[0020] Figure 3 A schematic diagram of the workflow of a radio frequency signal debugging method based on a meta-heuristic algorithm provided in one embodiment of the present application. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0022] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0023] The RF signal debugging method based on the meta-heuristic algorithm provided in this application is applied to the AB-BNCT cavity low-level system, such as Figure 1 As shown, the AB-BNCT cavity low-level system includes a signal generator, a low-level control system, a solid-state power source, a multi-coupler and a resonant cavity connected in sequence.

[0024] The signal generator first generates a stable RF signal and inputs it into a low-level control system for use as a clock and RF signal reference. The low-level control system accurately controls and adjusts the amplitude and phase of the RF signal it outputs to generate an RF signal that meets the requirements of the resonant cavity. The modulated signal is amplified by a solid-state power source to reach the required power level. The amplified signal is transmitted to the resonant cavity through a multi-coupler, which simultaneously collects the incident power and reflected power signals, and feeds these signals back to the low-level control system to achieve real-time monitoring and ensure stable operation of the system. After receiving power, the resonant cavity generates an accelerating electric field in the cavity for particle acceleration; the signal in the cavity (cavity signal) reflects the actual working state of the accelerating electric field, and is also fed back to the low-level control system. According to the debugging method provided in this application, the amplitude and phase adjustment of the RF signal are completed to achieve precise closed-loop control.

[0025] In an exemplary embodiment, Figure 2-Figure 3 As shown, a method for debugging a radio frequency signal based on a meta-heuristic algorithm is provided, which is executed by a computer device, specifically, it can be executed by a computer device such as a terminal or a server alone, or it can be executed by a terminal and a server together. In the embodiment of the present application, the method is applied to a server as an example for explanation, and includes the following steps S1 to S3. Among them:

[0026] S1: Acquire the current phase of the radio frequency signal output by the low-level control system and the current gain of each channel of the low-level control system.

[0027] S2: Use the meta-heuristic algorithm to optimize the current phase and current gain to determine the optimal phase and optimal gain.

[0028] Meta-heuristic algorithms are a type of algorithm that solves complex optimization problems through heuristic and heuristic search strategies. Meta-heuristic algorithms (such as annealing algorithms, genetic algorithms, particle swarm optimization, etc.) are used to simulate evolutionary processes, group behaviors or physical processes in nature, perform global search and local optimization in large-scale search spaces, and find the optimal parameter combination to ensure the best performance of the system under multi-coupler conditions.

[0029] Use meta-heuristic algorithms (such as genetic algorithms) to analyze the phase (φ i ) and gain (G i ) parameters are optimized to maximize output power consistency and minimize reflected power. The specific process is as follows:

[0030] (1) Initial population generation:

[0031] Parameter representation: Each individual (solution) consists of phase and gain, that is, Individual = {φ 1 ,φ 2 ,...,φ n ,G 1 ,G 2 ,...,G n}\text{Individual}=\{\phi 1 ,\phi 2 ,...,\phi n ,G 1 ,G 2 ,...,G n \}Individual={φ 1 ,φ 2 ,...,φ n ,G 1 ,G 2 ,...,G n}, where n is the number of couplers.

[0032] Initial generation: Randomly generate a group of individuals that meet the parameter range to form the initial population. The phase is usually in the range of 0°-360°, and the gain is within the gain range allowed by the solid-state power source.

[0033] (2) Fitness function design:

[0034] Goal Definition:

[0035] Maximize output power consistency: The output power P of each coupler out_i Should be as close to the average output power as possible

[0036] Minimize reflected power: Total reflected power Should be as small as possible.

[0037] Fitness Function:

[0038]

[0039] Among them, F represents the fitness function, P out_i is the output power of the ith coupler, is the average output power, P ref_i is the reflected power of the i-th coupler, n is the number of couplers, α and β are weight coefficients used to balance the influence of output power consistency and reflected power on fitness. The negative sign indicates that the fitness function is a minimization problem (i.e., the smaller the better).

[0040] (3) Fitness evaluation:

[0041] Parameter Application: Apply each individual phase and gain to a low level control system.

[0042] Signal measurement: The following data are collected through the feedback loop:

[0043] Incident power P in_i : Power fed into the coupler;

[0044] Reflected power P ref_i : The power reflected back from the coupler;

[0045] Output power P out_i :P out_i =P in_i -P ref_i .

[0046] Fitness calculation: Use the above fitness function to calculate the fitness value of each individual.

[0047] (4) Genetic manipulation:

[0048] 1) Selection:

[0049] Method: Use roulette wheel selection or tournament selection to select individuals with higher fitness from the current population as parents.

[0050] Purpose: To ensure that individuals with better performance have a higher probability of passing their genes to the next generation.

[0051] 2) Crossover:

[0052] Method: The phase and gain parameters of the parent individuals are crossed to generate offspring individuals.

[0053] Operation: Analog binary crossover (SBX) is available for phase and single or multi-point crossover is available for gain.

[0054] Phase Crossover: λ is a random number ranging from 0 to 1.

[0055] Gain Crossover: μ is a random number, ranging from 0 to 1.

[0056] 3) Mutation:

[0057] Methods: The phase and gain of offspring individuals were randomly mutated with small probability.

[0058] operate:

[0059] Phase variation: δ φ It is a random number that satisfies the normal distribution and represents the phase fine-tuning amount.

[0060] Gain variation: δ G It is a random number that satisfies the normal distribution and represents the gain fine-tuning amount.

[0061] Constraint processing: The parameters after mutation must be within the allowable range. If they exceed the range, they must be corrected.

[0062] (5) Next-generation assessment:

[0063] Repeat fitness evaluation: Repeat the fitness calculation process for the newly generated offspring individuals.

[0064] (6) Iteration loop:

[0065] Loop execution: Selection, crossover, mutation, and evaluation are performed repeatedly to form multiple generations of iterations.

[0066] Termination conditions:

[0067] 1) Fitness convergence: When the fitness no longer increases significantly over several consecutive generations, the algorithm is considered to have converged.

[0068] 2) Maximum number of iterations: Reach the preset maximum number of generations (such as 100 generations).

[0069] 3) Performance indicators are met: when the output power consistency and reflected power meet the preset requirements.

[0070] (7) Application of optimal parameters:

[0071] Select the best individual: Select the individual with the highest fitness from the final population, and its phase and gain are the optimization results.

[0072] S3: Debugging the radio frequency signal based on the optimal phase and the optimal gain.

[0073] After step S3, the method further includes:

[0074] The output power and reflected power of each coupler are monitored in real time, and genetic optimization is performed repeatedly until the low-level control system reaches the optimal steady state, meeting the high stability and high precision requirements of medical equipment. The collected data is stored on the ARM side of the FPGA for further analysis and adjustment.

[0075] Compared with the prior art, this application has the following significant advantages:

[0076] (1) High stability: In view of the high requirements of medical devices for equipment stability, the meta-inspired algorithm optimization of this application combined with the feedback loop ensures the precise adjustment of the multi-coupler particle accelerator and the overall stability of the system.

[0077] (2) High efficiency: Through the global optimization capability of the meta-heuristic algorithm, the consistency of the coupler output power is achieved, the reflected power is minimized, and the overall efficiency of the system is improved.

[0078] (3) High degree of automation: The system can automatically adapt to different operating conditions, reducing the complexity of manual debugging and ensuring stable performance output.

[0079] (4) Real-time data processing: Using FPGA for high-speed data acquisition and storage ensures the system's real-time response and adjustment capabilities under dynamic conditions.

[0080] Based on the same inventive concept, the embodiment of the present application also provides a device for implementing the above-mentioned radio frequency signal debugging method based on the meta-heuristic algorithm. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in one or more embodiments of the radio frequency signal debugging device based on the meta-heuristic algorithm provided below can refer to the limitations of the radio frequency signal debugging method based on the meta-heuristic algorithm above, and will not be repeated here.

[0081] In an exemplary embodiment, a radio frequency signal debugging device based on a meta-heuristic algorithm is provided, comprising:

[0082] The acquisition module is used for the current phase of the radio frequency signal output by the low-level control system and the current gain of each channel of the low-level control system.

[0083] The optimization module is used to optimize the current phase and the current gain by using a meta-heuristic algorithm to determine the optimal phase and the optimal gain.

[0084] A debugging module is used to debug the radio frequency signal based on the optimal phase and the optimal gain.

[0085] As an optional implementation, the debugging module includes:

[0086] A variable phase shifter is used to adjust the current phase of the radio frequency signal output by the low-level control system.

[0087] The phase of the RF signal is adjusted by controlling the variable phase shifter. The specific operation is as follows:

[0088] (1) Signal reception: Receives phase adjustment instructions from the optimization module, which contain the phase angle that needs to be adjusted.

[0089] (2) Control execution: A digital signal processor (DSP) or field programmable gate array (FPGA) is used to generate precise control signals and send them to the variable phase shifter.

[0090] (3) Phase adjustment: The variable phase shifter changes its phase shift amount according to the control signal, thereby adjusting the phase of the RF signal output by the low-level control system so that the output frequency of the power source is consistent with the resonant frequency of the resonant cavity.

[0091] (4) Feedback verification: The adjusted phase information is monitored through the feedback loop module to ensure that the phase adjustment achieves the expected effect.

[0092] The gain control unit is used to adjust the gain of each channel of the low-level control system and control the output power of each coupler.

[0093] By adjusting the gain of each channel of the low-level control system, the output power of each coupler can be precisely controlled. The specific steps include:

[0094] (1) Gain instruction reception: receiving the gain setting value from the optimization module.

[0095] (2) Gain adjustment: Control the gain of each channel of the low-level control system so that its output power reaches the expected value.

[0096] (3) Real-time monitoring: The output power is monitored in real time through the feedback loop module to ensure the accuracy of gain adjustment.

[0097] The radio frequency signal debugging device also includes:

[0098] The feedback loop module is used to monitor the output power and reflected power of each coupler in real time.

[0099] The feedback loop module is responsible for real-time acquisition of the incident power and reflected power signals of the system, providing accurate data support. Specific operations include:

[0100] (1) Signal acquisition: A high-speed analog-to-digital converter (ADC) is used to collect incident and reflected signals from the power source output.

[0101] (2) Data processing: The collected signals are digitally processed by filtering, amplification, IQ modulation and demodulation to extract effective information.

[0102] (3) Data transmission: The processed data is stored in the ARM side of the FPGA and transmitted to the optimization module and the user interface module in real time.

[0103] (4) Abnormality detection: Monitors abnormal conditions of the signal, such as excessive reflected power, and promptly feeds back to the system for adjustment.

[0104] The radio frequency signal debugging device also includes:

[0105] User interface module: provides operators with monitoring and control functions for the system, including setting initial values ​​of optimization parameters, viewing optimization progress and manual intervention, etc.

[0106] Function implementation process: Provide a friendly interactive interface for operators to monitor and control the system. Specific functions include:

[0107] (1) Parameter setting: The operator can input the initial parameters, optimization objectives, etc. of the meta-heuristic algorithm through the interface.

[0108] (2) Real-time monitoring: The interface displays the output power of each coupler, the reflected power of each coupler, the phase of the RF signal, the gain of each channel of the low-level control system, and other status information in real time.

[0109] (3) Manual intervention: When necessary, the operator can manually adjust the phase and gain.

[0110] (4) Log recording: Record key data and events during system operation to facilitate later analysis.

[0111] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0112] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0113] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0114] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0115] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0116] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0117] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A radio frequency signal debugging method based on a meta-heuristic algorithm, the debugging method is applied to an AB-BNCT cavity low-level system, the AB-BNCT cavity low-level system comprises a signal generator, a low-level control system, a solid-state power source, a multi-coupler and a resonant cavity connected in sequence, characterized in that: The modulation method comprises: Acquire the current phase of the radio frequency signal output by the low-level control system and the current gain of each channel of the low-level control system; The meta-heuristic algorithm is used to optimize the current phase and current gain to determine the optimal phase and optimal gain; The radio frequency signal is debugged based on the optimal phase and the optimal gain.

2. The radio frequency signal debugging method based on meta-heuristic algorithm according to claim 1 is characterized in that: The meta-heuristic algorithm is used to optimize the current phase and current gain to determine the optimal phase and optimal gain, including: Generate an initial population; the individuals in the initial population represent the phase of the radio frequency signal and the gain of each channel of the low-level control system; The fitness function is constructed with the goal of maximizing the output power consistency of each coupler and minimizing the reflected power of each coupler; Calculating the fitness value of the individual based on the fitness function; The individual with the highest fitness value is selected as the optimal individual; the optimal individual represents the optimal phase and the optimal gain.

3. The radio frequency signal debugging method based on meta-heuristic algorithm according to claim 2 is characterized in that: The fitness function is: Among them, F represents the fitness function, P out_i is the output power of the ith coupler, is the average output power, P ref_i is the reflected power of the i-th coupler, n is the number of couplers, and α and β are weight coefficients.

4. The radio frequency signal debugging method based on meta-heuristic algorithm according to claim 2 is characterized in that: Before calculating the fitness value of the individual based on the fitness function, the method further includes: Perform selection, crossover and mutation operations on individuals.

5. The radio frequency signal debugging method based on meta-heuristic algorithm according to claim 1, characterized in that: The radio frequency signal debugging method also includes: Monitor the output power and reflected power of each coupler in real time.

6. A radio frequency signal debugging device based on a meta-heuristic algorithm, the debugging device is applied to an AB-BNCT cavity low-level system, the AB-BNCT cavity low-level system comprises a signal generator, a low-level control system, a solid-state power source, a multi-coupler and a resonant cavity connected in sequence, characterized in that: The modulation device comprises: An acquisition module, used to acquire the current phase of the radio frequency signal output by the low-level control system and the current gain of each channel of the low-level control system; An optimization module is used to optimize the current phase and the current gain by using a meta-heuristic algorithm to determine the optimal phase and the optimal gain; A debugging module is used to debug the radio frequency signal based on the optimal phase and the optimal gain.

7. The radio frequency signal debugging device based on meta-heuristic algorithm according to claim 6, characterized in that: The debugging module includes: a variable phase shifter, for adjusting the current phase of the radio frequency signal output by the low-level control system; The gain control unit is used to adjust the gain of each channel of the low-level control system and control the output power of each coupler.

8. The radio frequency signal debugging device based on meta-heuristic algorithm according to claim 6, characterized in that: The radio frequency signal debugging device also includes: The feedback loop module is used to monitor the output power and reflected power of each coupler in real time.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the radio frequency signal debugging method based on the meta-heuristic algorithm described in any one of claims 1 to 5 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the radio frequency signal debugging method based on the meta-heuristic algorithm described in any one of claims 1 to 5 is implemented.

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