All-fiber random Raman laser based on Sagnac ring

Abstract

The invention relates to an all-fiber random Raman laser based on a Sagnac ring, and the laser comprises a pumping source module which dynamically adjusts the power and wavelength of pumping light through simulated annealing, so as to generate the pumping light; the optical fiber coupler module is used for optimizing an optical fiber coupler through a genetic algorithm and coupling the pump light into an optical fiber transmission path according to the optimized optical fiber coupler; and the gain optical fiber section module is used for receiving the pump light, optimizing parameters of a gain optical fiber section through a particle swarm optimization algorithm and generating a Raman scattering effect. According to the all-fiber random Raman laser based on the Sagnac ring, comprehensive performance improvement and innovative design are carried out on the all-fiber random Raman laser based on the Sagnac ring by fusing multiple intelligent optimization technologies, and the overall performance of the laser is improved.

Description

Technical Field

[0001] This invention relates to the field of lasers, and more specifically, to an all-fiber random Raman laser based on a Sagnac ring. Background Technology

[0002] In the field of modern technology, lasers, with their unique ability to generate high-intensity, highly monochromatic beams, have become indispensable tools in scientific research, industry, and daily life. They are widely used in various fields, including but not limited to communications, medical diagnosis and treatment, materials processing, and environmental monitoring.

[0003] However, rapid technological advancements and increasing industry demands for high-precision, high-efficiency tools have rendered traditional lasers increasingly inadequate to meet the ever-growing performance requirements. Particularly in specific applications such as long-distance fiber optic communication, delicate medical surgery, and high-precision material processing, unprecedentedly high standards have been set for laser performance indicators such as efficiency, stability, output power, and wavelength range.

[0004] In the field of communications, with the explosive growth of data volume, traditional optical communication technology is gradually reaching its bottleneck in terms of transmission rate and distance. Summary of the Invention

[0005] The technical problem to be solved by this invention is to overcome the shortcomings of the prior art and provide an all-fiber random Raman laser based on a Sagnac ring. By integrating a variety of intelligent optimization techniques, the performance of the all-fiber random Raman laser based on the Sagnac ring is comprehensively improved and innovatively designed, thereby enhancing the overall performance of the laser.

[0006] To solve the above-mentioned technical problems, the basic concept of the technical solution adopted by the present invention is as follows: An all-fiber random Raman laser based on a Sagnac ring, comprising: The pump source module dynamically adjusts the power and wavelength of the pump light through simulated annealing to generate pump light; The fiber optic coupler module optimizes the fiber optic coupler using a genetic algorithm and couples the pump light into the fiber optic transmission path based on the optimized fiber optic coupler. The gain fiber segment module is used to receive pump light. The parameters of the gain fiber segment are optimized by the particle swarm optimization algorithm, and Raman scattering effect is generated. The Sagnac ring module is used to optimize the parameters of the Sagnac ring structure based on the Raman scattering effect using a differential evolution algorithm, and to adjust the cyclic transmission and polarization state of the optical signal to generate random Raman scattering. The output module is used to receive random Raman scattering and optimize the design of the output device using an ant colony optimization algorithm to achieve the extraction and output of random Raman laser.

[0007] Preferably, pump light is generated by dynamically adjusting the power and wavelength of the pump light through simulated annealing, including: Determine the basic parameters of the simulated annealing algorithm, including the initial temperature, cooling rate, termination temperature, and number of iterations at each temperature. Set the initial power and wavelength of the pump light as the starting search point of the algorithm. Based on the current pump light power and wavelength, new power and wavelength values ​​are generated through random perturbation to obtain a new solution; Define the objective function, calculate the objective function value of the new solution, and calculate the difference between the objective function values ​​of the current solution and the new solution; Based on the difference in the objective function value, the new solution is accepted or rejected, and the cooling process is updated according to the set cooling rate to obtain the final solution; Based on the final solution, adjust the power and wavelength of the pump light to generate the pump light.

[0008] Preferably, the objective function is: ; in, It is the output power of the pump light. It is the weighting coefficient for output power. It is the ratio of the target's input power to its output power. It is the weighting coefficient for pump efficiency deviation. It is the target wavelength. It is the weighting coefficient for wavelength deviation. It's the wavelength. It is the objective function.

[0009] Preferably, the fiber optic coupler is optimized using a genetic algorithm, and the pump light is coupled into the fiber optic transmission path based on the optimized fiber optic coupler, including: Determine the optimization objectives and performance parameters of the fiber optic coupler. The optimization objectives include improving coupling efficiency and reducing insertion loss, while the performance parameters include the coupler's structural dimensions and material properties. Initialize the genetic algorithm parameters, encode the optimization parameters of the fiber coupler to form individuals in the genetic algorithm, and calculate the fitness value of each individual; Based on the fitness value of an individual, select the best individuals, generate new individuals through crossover, and introduce new gene combinations through mutation until the predetermined number of iterations is reached and the solution converges to the final solution. Based on the final solution, extract the fiber coupler parameter combination, adjust the incident angle, polarization state and other parameters of the pump light, and couple the pump light into the fiber transmission path.

[0010] Preferred fitness values ​​for each individual: ; in, It's about coupling efficiency. It is insertion loss. It is the input optical power. It is the optical power coupled into the optical fiber. The optical power loss is due to polarization mismatch. It is the reflected light power. It's bandwidth. , , , and These are weighting coefficients. It is the fitness value of an individual.

[0011] Preferably, the parameters of the gain fiber segment are optimized using a particle swarm optimization algorithm to generate a Raman scattering effect, including: The optimization objectives and constraints are determined. The optimization objectives include maximizing Raman gain and optimizing gain flatness. The constraints include the wavelength range of the pump light, the fiber length, and the allowable loss. Initialize the particle swarm by randomly generating a group of particles in the search space. Each particle represents a possible combination of parameters and has a position and a velocity. Set the parameters for the particle swarm optimization algorithm, including the total number of particles, the maximum number of iterations, the inertia weight, and the learning factor; Calculate the performance evaluation value for each particle and compare its current fitness value with the historical performance evaluation value to update the individual extreme value and the global extreme value. The performance evaluation value is the weighted value of Raman gain minus the weighted penalty value of gain flatness deviation. Adjust the particle's velocity and position based on its current velocity, individual extreme value, and global extreme value; Based on the particle's velocity and position, the maximum number of iterations is reached to optimize the parameters of the gain fiber segment; Raman scattering effect is generated based on the optimized gain fiber segment.

[0012] Preferably, based on the Raman scattering effect, the parameters of the Sagnac ring structure are optimized using a differential evolution algorithm, and the cyclic propagation and polarization state of the optical signal are adjusted to generate random Raman scattering, including: Define the optimization objective and constraints; A set of individuals is randomly generated in the search space, and each individual represents a Sagnac ring structure parameter setting; Set the parameters for the differential evolution algorithm, including population size, differential weight factor, and crossover probability; For each individual, based on the evaluation value under the current parameter combination, mutation and crossover operations are performed on individuals in the population to generate new candidate individuals. The evaluation values ​​of the candidate individuals are compared with those of the original individuals, and individuals with higher fitness values ​​are selected to enter the next generation of the population. When the maximum number of iterations is reached, the iteration is terminated, and the final solution is obtained. Based on the final solution, the parameters of the optimized Sagnac ring structure are obtained, and the cyclic transmission and polarization state of the optical signal are adjusted according to the parameters to generate random Raman scattering.

[0013] Preferably, the formula for calculating the evaluation value is: ; in, , and These are weighting coefficients. It refers to the efficiency of optical signal transmission. It is the rate of change of the polarization angle. It is the integrated Raman scattering spectrum intensity. , , It is the exponential coefficient. It is a tiny positive number. It is an evaluation value.

[0014] Preferably, random Raman scattering is received, and the design of the output device is optimized using an ant colony optimization algorithm to achieve the extraction and output of random Raman laser light, including: Determine the specific objectives for optimizing the output device design; Receive random Raman scattering signals and preprocess the scattering signals; A set of design parameters for the output device is randomly generated as the starting point for the ant colony search. Ant colony search and pheromone updates are performed to output the final solution. Based on the final solution, the design parameters of the output device are set to achieve the extraction and output of random Raman laser.

[0015] By adopting the above technical solution, the present invention has the following beneficial effects compared with the prior art: By dynamically adjusting the power and wavelength of the pump light through simulated annealing, it is possible to ensure that the pump light enters the gain fiber in an optimal state, thereby improving the overall efficiency and stability of the laser. Optimizing the fiber coupler using a genetic algorithm can significantly improve the coupling efficiency between the pump light and the fiber, reduce optical loss, and thus increase the laser's output power. Optimizing the parameters of the gain fiber segment using a particle swarm optimization algorithm can maximize Raman gain and optimize gain flatness, thereby generating a stronger Raman scattering effect and improving laser performance. Optimizing the parameters of the Sagnac ring structure using a differential evolution algorithm can effectively regulate the cyclic transmission and polarization state of the optical signal, further improving the transmission quality of the optical signal and generating more stable random Raman scattering. The application of an ant colony optimization algorithm optimizes the design of the output device, enabling more efficient extraction and output of random Raman laser light, improving the laser's practicality and reliability. The laser design targets a wavelength range with wide applications in communications, medicine, materials processing, and other fields. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the all-fiber random Raman laser based on the Sagnac ring of this invention. Detailed Implementation

[0017] like Figure 1 As shown, this invention provides an all-fiber random Raman laser based on a Sagnac ring, comprising: Pump source module 11 dynamically adjusts the power and wavelength of the pump light through simulated annealing to generate pump light; The fiber optic coupler module 12 optimizes the fiber optic coupler using a genetic algorithm and couples the pump light into the fiber optic transmission path based on the optimized fiber optic coupler. Gain fiber segment module 13 is used to receive pump light, optimize the parameters of the gain fiber segment through particle swarm optimization algorithm, and generate Raman scattering effect. Sagnac ring module 14 is used to optimize the parameters of the Sagnac ring structure based on the Raman scattering effect using a differential evolution algorithm, and to adjust the cyclic transmission and polarization state of the optical signal to generate random Raman scattering. The output module 15 is used to receive random Raman scattering and optimize the design of the output device through an ant colony optimization algorithm to achieve the extraction and output of random Raman laser.

[0018] In this embodiment of the invention, simulated annealing and dynamic adjustment enable more precise control of the pump light power and wavelength, thereby improving the efficiency and stability of laser generation. Optimized pump light parameters help reduce energy consumption and extend the lifespan of the pump source. The application of genetic algorithms makes the optimization of fiber couplers more efficient and accurate, improving the efficiency of pump light coupling into the fiber transmission path. The optimized fiber coupler can reduce optical signal attenuation and distortion, improving signal transmission quality. Particle swarm optimization algorithm optimizes the parameters of the gain fiber segment, enhancing the Raman scattering effect, thereby improving the laser gain and output power. The optimized gain fiber segment helps reduce nonlinear effects and noise, improving the quality of the laser beam. The application of differential evolution algorithm makes the parameter optimization of the Sagnac ring structure more precise, effectively regulating the cyclic transmission and polarization state of the optical signal. The optimized Sagnac ring can generate more stable and controllable random Raman scattering, providing a strong guarantee for the performance of the laser system. Ant colony optimization algorithm optimizes the output device design, improving the extraction efficiency and output stability of random Raman laser. The optimized output device can reduce optical signal loss and scattering, ensuring the purity and consistency of laser output.

[0019] In the all-fiber random Raman laser based on the Sagnac ring described in this embodiment of the invention, the pump source module 11 includes: Determine the basic parameters of the simulated annealing algorithm, including the initial temperature, cooling rate, termination temperature, and number of iterations at each temperature. Set the initial power and wavelength of the pump light as the starting search point of the algorithm. Based on the current pump light power and wavelength, new power and wavelength values ​​are generated through random perturbation to obtain a new solution; Define the objective function, calculate the objective function value of the new solution, and calculate the difference between the objective function values ​​of the current solution and the new solution; Based on the difference in the objective function value, the new solution is accepted or rejected, and the cooling process is updated according to the set cooling rate to obtain the final solution; Based on the final solution, adjust the power and wavelength of the pump light to generate the pump light.

[0020] In this embodiment of the invention, by reasonably setting parameters such as initial temperature and cooling rate, the simulated annealing algorithm can perform efficient global searches, avoiding getting trapped in local optima, and thus is more likely to find the globally optimal pump light power and wavelength configuration. The algorithm generates new power and wavelength values ​​through random perturbation; this flexibility allows the search process to escape local minima and explore a wider solution space. Simultaneously, accepting or rejecting new solutions based on the difference in objective function values ​​allows the algorithm to adaptively adjust its search direction. By precisely adjusting the pump light power and wavelength, the energy consumption of the laser system can be optimized, avoiding unnecessary energy waste. Furthermore, suitable pump light parameters can improve the efficiency of laser generation, making the laser system more efficient and stable. Automatic adjustment of pump light parameters by the algorithm reduces the need for manual intervention, simplifies the operation and maintenance process of the laser system, reduces operational difficulty, and improves the system's usability.

[0021] In the specific implementation of this invention, the specific steps include: The parameters of the simulated annealing algorithm are determined as follows: initial temperature (the temperature at which the simulated annealing algorithm begins); cooling rate (the cooling rate determines how quickly the temperature decreases); termination temperature (the algorithm stops when the temperature drops to the termination temperature, which is usually set to a value close to 0, indicating that the algorithm has cooled sufficiently); and number of iterations at each temperature (the algorithm will attempt to find a better solution multiple times at each temperature; the more iterations, the more thoroughly the algorithm explores each temperature).

[0022] Set the initial pump light parameters: initial power (set an initial power value according to the specifications of the pump light source); initial wavelength (set an initial wavelength value according to the application requirements).

[0023] Set the current temperature as the initial temperature, and set the current pump light power and wavelength as initial values. Based on the current pump light power and wavelength, generate new power and wavelength values ​​through random perturbation, where the perturbation randomly adds or subtracts a small value.

[0024] The objective function value is calculated according to the formula to evaluate the performance of a given pump power and wavelength. The objective function values ​​of the new solution and the current solution are calculated, and the difference between the objective function values ​​is calculated. If the difference is less than 0, meaning the new solution is better, it is accepted unconditionally; if the difference is greater than 0, meaning the new solution is worse, it is accepted. If the new solution is accepted, the current pump power and wavelength are updated, and the above steps are repeated until the number of iterations at the current temperature is reached. Then, the current temperature is updated according to the cooling rate. When the temperature drops to the termination temperature, the iteration stops, and the current pump power and wavelength are output as the final solution.

[0025] Based on the final pump light power and wavelength output by the simulated annealing algorithm, the globally optimal or near-optimal pump light power and wavelength settings are found, and the actual power and wavelength settings of the pump source module are adjusted to generate the required pump light.

[0026] In the all-fiber random Raman laser based on the Sagnac ring described in this embodiment of the invention, the objective function of the pump source module 11 is: ; in, It is the output power of the pump light. It is the weighting coefficient for output power. It is the ratio of the target's input power to its output power. It is the weighting coefficient for pump efficiency deviation. It is the target wavelength. It is the weighting coefficient for wavelength deviation. It's the wavelength. It is the objective function.

[0027] In this embodiment of the invention, by minimizing the ratio of input power to output power, i.e., improving pump efficiency, energy consumption can be reduced, achieving greener laser operation. Optimized pump efficiency means less energy waste, helping to reduce operating costs and improve the overall energy efficiency of the system. Considering the output power of the pump light in the objective function helps to precisely control the output energy of the laser. Stable output power is crucial for many laser applications, such as materials processing and medical treatment, ensuring process consistency and reliability. By minimizing the deviation between the wavelength and the target wavelength, the wavelength accuracy of the laser output can be ensured. Wavelength accuracy directly affects the interaction between the laser and matter; therefore, precise control of it can improve the effect and quality of laser applications. By adjusting the weighting coefficients in the objective function, the optimization objective can be flexibly adjusted. Optimizing the objective function can reduce system instability factors and performance fluctuations, thereby improving the stability and lifespan of the laser.

[0028] In the all-fiber random Raman laser based on the Sagnac ring described in this embodiment of the invention, the fiber coupler module 12 includes: Determine the optimization objectives and performance parameters of the fiber optic coupler. The optimization objectives include improving coupling efficiency and reducing insertion loss, while the performance parameters include the coupler's structural dimensions and material properties. Initialize the genetic algorithm parameters, encode the optimization parameters of the fiber coupler to form individuals in the genetic algorithm, and calculate the fitness value of each individual; Based on the fitness value of an individual, select the best individuals, generate new individuals through crossover, and introduce new gene combinations through mutation until the predetermined number of iterations is reached and the solution converges to the final solution. Based on the final solution, extract the fiber coupler parameter combination, adjust the incident angle, polarization state and other parameters of the pump light, and couple the pump light into the fiber transmission path.

[0029] In this embodiment of the invention, by optimizing the structural dimensions and material properties of the fiber coupler, the coupling efficiency between the pump light and the optical fiber can be significantly improved. More pump light can be effectively guided into the optical fiber transmission path, thereby improving the overall efficiency of the laser system. The optimization process of the genetic algorithm aims to reduce the insertion loss introduced by the fiber coupler. Reducing loss means reducing energy attenuation during optical signal transmission, which helps maintain the strength and quality of the optical signal. By improving coupling efficiency and reducing loss, the system can utilize pump light resources more effectively, reduce unnecessary energy waste, contribute to energy conservation and emission reduction, and also reduce operating costs. The optimized fiber coupler has more stable performance, reducing fluctuations and interference in the optical signal during transmission, which helps improve the stability and reliability of the entire laser system. The genetic algorithm can efficiently search for optimized parameter combinations, thereby shortening the design and experimental cycle of the fiber coupler, helping to accelerate product development and improve market competitiveness. The fiber coupler parameter combinations obtained through genetic algorithm optimization can significantly improve product performance. The optimized fiber coupler may have a simpler structure and easier-to-adjust parameters, thereby simplifying the operation and maintenance process.

[0030] In the specific implementation of this invention, the specific steps include: The optimization objectives include improving coupling efficiency to ensure that as much pump light as possible is coupled into the fiber, reducing optical energy loss; and reducing insertion loss to reduce light attenuation as it passes through the coupler, thereby improving overall optical path efficiency.

[0031] Define performance parameters, including structural dimensions, such as the length, width, and height of the coupler; and material properties, including the refractive index, light transmittance, and scattering loss characteristics of the material.

[0032] Initialize the genetic algorithm parameters, including setting the population size, i.e. the number of individuals, which determines the breadth of the search space and the convergence speed of the algorithm; determine the crossover rate, mutation rate and selection strategy to control the evolution process of the algorithm; set the maximum number of iterations or convergence conditions as the basis for terminating the algorithm.

[0033] The performance parameters of the fiber optic coupler, such as structural dimensions and material properties, are numerically represented using binary, real numbers, or other suitable encoding methods. These parameters are encoded as "genes" in a genetic algorithm. Each "gene" combination forms an "individual," representing a possible fiber optic coupler design. For each individual, i.e., each coupler design, its coupling efficiency and insertion loss are measured through simulation or experiment. Based on the formula, the fitness value of each individual is obtained.

[0034] Methods such as roulette wheel selection and tournament selection are used to select superior individuals for the next generation based on their fitness values. Individuals with high fitness have a greater chance of being selected, thus ensuring the transmission of superior genes. Selected individuals are randomly paired and gene crossover is performed at a random position to randomly change certain gene values ​​of some individuals at a certain mutation rate.

[0035] The fitness evaluation, selection, crossover, and mutation operations are repeated until the predetermined number of iterations is reached or the convergence condition is met. During the iteration process, the individuals in the population will gradually tend towards a better solution. When the algorithm meets the termination condition, the algorithm stops iterating. At this time, the optimal individual in the population is the combination of fiber coupler parameters obtained by the genetic algorithm optimization.

[0036] The specific parameter combination of the fiber coupler is decoded from the optimal individual, such as the optimal structural size and material properties. Based on the optimized fiber coupler characteristics, parameters such as the incident angle and polarization state of the pump light are adjusted to ensure that the pump light can be coupled into the fiber transmission path with the highest efficiency. The adjusted pump light is then coupled into the fiber transmission path using the optimized fiber coupler.

[0037] In the all-fiber random Raman laser based on the Sagnac ring described in this embodiment of the invention, the fitness value of each individual fiber coupler module 12 is as follows: ; in, It's about coupling efficiency. It is insertion loss. It is the input optical power. It is the optical power coupled into the optical fiber. The optical power loss is due to polarization mismatch. It is the reflected light power. It's bandwidth. , , , and These are weighting coefficients. It is the fitness value of an individual.

[0038] In this embodiment of the invention, by comprehensively considering multiple performance indicators, the fitness function ensures the overall performance of the fiber optic coupler is optimized. This is not limited to improving a single indicator, but achieves a balance between multiple key performance aspects, resulting in a more comprehensive and superior fiber optic coupler design. The fitness function considers optical power loss caused by polarization mismatch; optimization can reduce this loss, improve optical energy utilization efficiency, and contribute to improving the overall efficiency and stability of the laser system. The optimization process considers reflected light power; reducing reflected light can reduce the impact on the light source and system, improving system stability and reliability. Simultaneously, reducing reflection also means that more optical energy is effectively utilized. Bandwidth, as part of the fitness function, helps improve the performance consistency of the fiber optic coupler at different frequencies. By using a genetic algorithm and this comprehensive fitness function, designers can more efficiently find the optimal design parameters for the fiber optic coupler, shortening the design cycle and improving design efficiency. The introduction of weighting coefficients allows designers to adjust the priority of various indicators according to specific application scenarios, thereby customizing a fiber optic coupler that better meets specific needs.

[0039] In the all-fiber random Raman laser based on the Sagnac ring described in this embodiment of the invention, the gain fiber segment module 13 includes: The optimization objectives and constraints are determined. The optimization objectives include maximizing Raman gain and optimizing gain flatness. The constraints include the wavelength range of the pump light, the fiber length, and the allowable loss. Initialize the particle swarm by randomly generating a group of particles in the search space. Each particle represents a possible combination of parameters and has a position and a velocity. Set the parameters for the particle swarm optimization algorithm, including the total number of particles, the maximum number of iterations, the inertia weight, and the learning factor; Calculate the performance evaluation value for each particle and compare its current fitness value with the historical performance evaluation value to update the individual extreme value and the global extreme value. The performance evaluation value is the weighted value of Raman gain minus the weighted penalty value of gain flatness deviation. Adjust the particle's velocity and position based on its current velocity, individual extreme value, and global extreme value; Based on the particle's velocity and position, the maximum number of iterations is reached to optimize the parameters of the gain fiber segment; Raman scattering effect is generated based on the optimized gain fiber segment.

[0040] In this embodiment of the invention, by maximizing Raman gain as one of the optimization objectives, the Raman gain of the laser system can be significantly improved, thereby enhancing the output power and efficiency of the laser. Optimizing gain flatness means that the gain obtained at different wavelengths is more uniform. By setting constraints, such as the wavelength range of the pump light, fiber length, and allowable loss, the optimization process can be ensured to be carried out within the range that meets actual needs and physical limitations. The particle swarm optimization algorithm has a powerful global search capability, which can quickly find near-optimal solutions in complex parameter spaces, improving optimization efficiency. Through continuous updates of individual extrema and global extrema, the particle swarm optimization algorithm can adaptively adjust the search direction and speed, thereby better approximating the optimal solution.

[0041] In the specific implementation of this invention, the specific steps include: Define optimization objectives, including maximizing Raman gain to ensure the highest possible Raman gain within the specified wavelength range; and optimizing gain flatness to distribute the gain as evenly as possible within the target wavelength range, reducing gain fluctuations.

[0042] Set constraints, including the wavelength range of the pump light, limiting the operating wavelength of the pump light to between; fiber length, setting upper and lower limits for the fiber length according to actual application requirements; and allowable loss, defining the maximum acceptable optical loss value for the system.

[0043] A certain number of particles are randomly generated in the parameter space. Each particle represents a set of possible combinations of gain fiber segment parameters, such as fiber length and doping concentration. Each particle has two attributes: position and velocity. Position indicates the current parameter combination, and velocity is used to guide the direction of particle movement in the search space.

[0044] Configure algorithm parameters, including total number of particles, which sets the number of particles in the particle swarm, affecting the breadth of the search and computational complexity; maximum number of iterations, which defines the maximum number of iterations of the algorithm as one of the stopping conditions; inertia weight, which controls the degree to which the particle's current velocity affects the next velocity update; and learning factors, including individual learning factors and global learning factors, which affect the particle's ability to learn towards the individual optimal and global optimal positions, respectively.

[0045] For each particle representing a combination of parameters, its Raman gain and gain flatness are measured through simulation or experiment. Based on the optimization objective, a performance evaluation value is designed. The performance evaluation value is the weighted value of the Raman gain minus the weighted penalty value of the gain flatness deviation. The current performance evaluation value of each particle is compared with its historical best performance evaluation value. If the current value is better, the individual extreme value of the particle is updated. Among all particles, the particle with the best performance evaluation value is found. If its performance is better than the current global extreme value, the global extreme value is updated.

[0046] Based on the particle's current velocity, its distance from the individual extremum, and its distance from the global extremum, through Update the particle velocity, where, It is a particle exist The speed of time, It is a particle exist The speed of time, It is inertial weight. and It is the learning factor coefficient. and It is a random number in the range [0,1]. It is a particle The optimal position of an individual It is the globally optimal position for the entire particle swarm. It is a particle exist The position at any given moment; calculate the particle's next position based on the updated velocity and current position.

[0047] Repeat the steps of performance evaluation, updating the extreme value, and adjusting the particle velocity and position until the maximum number of iterations is reached or other termination conditions are met. When the maximum number of iterations is reached or other termination conditions are met, the algorithm stops iterating and outputs the parameter combination corresponding to the global extreme value as the optimized gain fiber segment parameters.

[0048] Based on the optimized gain fiber segment parameters, such as fiber length and doping concentration, the gain fiber is actually configured or fabricated. When the pump light passes through the optimized gain fiber segment, Raman scattering will occur due to the nonlinear effect in the fiber. The Raman scattering effect causes the energy of the pump light to be transferred to a new wavelength, thereby amplifying the optical signal and broadening the spectrum.

[0049] In the all-fiber random Raman laser based on the Sagnac ring described in this embodiment of the invention, the Sagnac ring module 14 includes: Define the optimization objective and constraints; A set of individuals is randomly generated in the search space, and each individual represents a Sagnac ring structure parameter setting; Set the parameters for the differential evolution algorithm, including population size, differential weight factor, and crossover probability; For each individual, based on the evaluation value under the current parameter combination, mutation and crossover operations are performed on individuals in the population to generate new candidate individuals. The evaluation values ​​of the candidate individuals are compared with those of the original individuals, and individuals with higher fitness values ​​are selected to enter the next generation of the population. When the maximum number of iterations is reached, the iteration is terminated, and the final solution is obtained. Based on the final solution, the parameters of the optimized Sagnac ring structure are obtained, and the cyclic transmission and polarization state of the optical signal are adjusted according to the parameters to generate random Raman scattering.

[0050] In this embodiment of the invention, the differential evolution algorithm is a highly efficient global optimization algorithm that can quickly search for the optimal solution of the Sagnac ring structure parameters, thereby improving the efficiency of the optimization process. By optimizing the structural parameters of the Sagnac ring, it can be made more stable, reducing fluctuations and distortions in the optical signal during transmission and improving the stability of the system. The optimized Sagnac ring structure parameters help improve the cyclic transmission characteristics of the optical signal, reduce signal loss and noise interference, thereby improving the quality of the optical signal. Based on the optimization results, the polarization state of the optical signal can be flexibly adjusted to meet the polarization characteristics requirements of different application scenarios, increasing the flexibility of the system. The optimized Sagnac ring structure may have lower energy consumption characteristics, and by reducing unnecessary energy loss, it helps to reduce the operating cost of the entire system. The differential evolution algorithm automatically searches for the optimal parameters, simplifying the complexity and workload of manual debugging, making system debugging more convenient and efficient.

[0051] In the specific implementation of this invention, the specific steps include: Define the optimization objectives, including the structural parameters of the Sagnac ring.

[0052] Set constraints, including physical size limitations of the Sagnac ring, such as the ring radius and fiber length; material and performance limitations of the fiber and other components; and the system's tolerance to optical signal loss, polarization state changes, etc.

[0053] In the search space of Sagnac ring parameters, a set of individuals is randomly generated, each representing a possible combination of parameters, such as the ring radius, fiber type, splitting ratio, etc.; the population size is the number of individuals.

[0054] Configure algorithm parameters, including population size, which determines the breadth of the search and the convergence speed of the algorithm; differential weight factor, which controls the scaling ratio of the differential vector and affects the step size of the search; and crossover probability, which determines the probability that a new individual inherits elements from a mutated individual during the crossover process.

[0055] Evaluation values ​​are calculated using a formula. The evaluation function quantifies the merits of each individual (i.e., the parameter combination). For each individual in the population, three different individuals are randomly selected, and mutant individuals are generated according to the mutation strategy of the differential evolution algorithm. The mutation strategy is to add the difference vectors of two randomly selected individuals to the third individual and multiply by the difference weight factor. Through a crossover operation, new candidate individuals are generated by combining the original individuals and the mutant individuals. During the crossover process, the crossover probability determines whether each dimension is inherited from the mutant individuals. The evaluation values ​​of the original individuals and the candidate individuals are compared, and the individual with the better evaluation value is selected to enter the next generation of the population.

[0056] The mutation, crossover, and selection operations are repeated until the termination condition is met. During the iteration process, individuals in the population will gradually tend towards a better combination of parameters, reaching the preset maximum number of iterations. After the algorithm terminates, the individual with the highest fitness is selected from the current population as the final solution. The final solution represents the optimized Sagnac ring structure parameters.

[0057] Adjust the actual parameters of the Sagnac ring based on the final solution, such as the ring radius, splitting ratio, and fiber type, to ensure that the Sagnac ring setup is consistent with the optimization results. Based on the optimized Sagnac ring structure, adjust the input conditions and polarization state of the optical signal, monitor and fine-tune the cyclic transmission of the optical signal, and ensure that a stable random Raman scattering effect is generated in the Sagnac ring.

[0058] In the all-fiber random Raman laser based on the Sagnac ring described in this embodiment of the invention, the evaluation value of the Sagnac ring module 14 is calculated using the following formula: ; in, , and These are weighting coefficients. It refers to the efficiency of optical signal transmission. It is the rate of change of the polarization angle. It is the integrated Raman scattering spectrum intensity. , , It is the exponential coefficient. It is a tiny positive number. It is an evaluation value.

[0059] In this embodiment of the invention, the evaluation value comprehensively considers multiple factors such as optical signal transmission efficiency, the rate of change of polarization state angle, and the intensity of integrated Raman scattering spectrum, thus comprehensively reflecting the performance of the Sagnac ring module. Since the evaluation value considers optical signal transmission efficiency, the optimization process will tend to improve this efficiency, thereby accelerating the transmission speed of the optical signal and improving the overall system performance. The inclusion of the rate of change of polarization state angle in the evaluation value means that the optimization will strive to reduce polarization state fluctuations and enhance the stability of the optical signal. By optimizing the intensity of integrated Raman scattering spectrum, the Raman scattering effect can be improved. The weighting coefficients in the formula allow for flexible adjustment of the relative importance of various performance aspects according to different application requirements, enabling the Sagnac ring module to better adapt to diverse application scenarios.

[0060] In the all-fiber random Raman laser based on the Sagnac ring described in this embodiment of the invention, the output module 15 includes: Determine the specific objectives for optimizing the output device design; Receive random Raman scattering signals and preprocess the scattering signals; A set of design parameters for the output device is randomly generated as the starting point for the ant colony search. Ant colony search and pheromone updates are performed to output the final solution. Based on the final solution, the design parameters of the output device are set to achieve the extraction and output of random Raman laser.

[0061] In this embodiment of the invention, by optimizing the design of the output device, the extraction efficiency of random Raman lasers can be maximized, allowing more laser energy to be effectively collected and output, thereby improving the overall efficiency of the laser system. Using the stability of the output spectrum as one of the optimization objectives ensures more stable wavelength and intensity of the laser output. Optimizing the laser output power for specific wavelengths can meet the wavelength requirements of certain applications. The ant colony algorithm has powerful global search capabilities, intelligently finding the optimal solution in the design parameter space, improving the efficiency and accuracy of the optimization process. Through automated ant colony search algorithms, manual intervention in the design and optimization process can be reduced. The ant colony algorithm can flexibly adjust the search strategy according to different optimization objectives, enabling the design of the output device to adapt to various application requirements.

[0062] In the specific implementation of this invention, the specific steps include: The optimization objectives are defined, including maximizing the extraction efficiency of random Raman laser, the stability of the output spectrum, and the laser output power at a specific wavelength.

[0063] The output module first receives random Raman scattering signals from the Sagnac ring. These signals contain rich spectral information. The received scattering signals are preprocessed by filtering, amplification, etc. The signals are then analyzed in detail by equipment such as a spectral analyzer to extract key spectral features.

[0064] In the search space of design parameters, a set of design parameter combinations for the output device is randomly generated. These parameters include the reflectivity, transmittance, and radius of curvature of the output mirror.

[0065] Key parameters such as the number of ants, the initial concentration of pheromones, and the pheromone evaporation rate are determined. Each ant chooses its next movement direction based on the pheromone concentration at its current location and heuristic information. The ants continuously move within the search space, exploring possible combinations of design parameters. For each ant's chosen parameter combination, its performance is verified through simulation or experimentation, and the merits of each parameter set are evaluated based on its extraction efficiency. Based on the evaluation results, the pheromone concentration along the search path is updated. Optimal parameter combinations attract more ants, thereby accelerating the search process.

[0066] Ant colony search stops when the termination condition is met (such as reaching the maximum number of iterations or finding the optimal solution that meets the requirements).

[0067] Based on the final solution obtained from the ant colony search, the design parameters of the output device are adjusted. These parameters may involve the selection of the output mirror, the design of the optical path, and the coupling method of the optical fiber. Under the optimized output device parameters, the actual laser extraction and output operation is performed.

[0068] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. An all-fiber random Raman laser based on a Sagnac ring, characterized in that: include: A pump source module dynamically adjusts the power and wavelength of the pump light through simulated annealing to generate pump light; A fiber coupler module, which optimizes the fiber coupler by using a genetic algorithm and couples the pump light into the fiber transmission path according to the optimized fiber coupler; The gain fiber segment module is used to receive pump light, optimize the parameters of the gain fiber segment through the particle swarm optimization algorithm, and generate Raman scattering effect; The Sagnac ring module is used to optimize the parameters of the Sagnac ring structure using a differential evolution algorithm based on the Raman scattering effect, and to adjust the cyclic transmission and polarization state of the optical signal to generate random Raman scattering; The output module is used to receive random Raman scattering and optimize the design of the output device through an ant colony optimization algorithm to achieve the extraction and output of random Raman laser.

2. The all-fiber random Raman laser based on a Sagnac ring according to claim 1, characterized in that: The power and wavelength of the pump light are dynamically adjusted by simulated annealing to generate pump light, including: Determine the basic parameters of the simulated annealing algorithm, including the initial temperature, cooling rate, termination temperature, and the number of iterations at each temperature, and set the initial power and wavelength of the pump light as the starting search point of the algorithm; Based on the current pump light power and wavelength, new power values ​​and wavelength values ​​are generated through random perturbations to obtain a new solution; Define the objective function, calculate the objective function value of the new solution, and calculate the difference in the objective function value between the current solution and the new solution; According to the difference in the objective function value, the new solution is accepted or rejected, and the cooling is performed according to the set cooling rate update to obtain the final solution; According to the final solution, the power and wavelength of the pump light are adjusted to generate the pump light.

3. The all-fiber random Raman laser based on a Sagnac ring according to claim 1, characterized in that: The objective function is: ; in, is the output power of the pump light, is the weight coefficient of the output power, is the ratio of the target input power to the output power, is the weight coefficient of the pump efficiency deviation, is the target wavelength, is the weight coefficient for wavelength deviation, is the wavelength, is the objective function.

4. The all-fiber random Raman laser based on a Sagnac ring according to claim 1, characterized in that: The fiber coupler is optimized by a genetic algorithm, and the pump light is coupled into the fiber transmission path according to the optimized fiber coupler, including: Determine the optimization objectives and performance parameters of the optical fiber coupler. The optimization objectives include improving coupling efficiency and reducing insertion loss. The performance parameters include the structural dimensions and material properties of the coupler. Initialize the genetic algorithm parameters, encode the optimization parameters of the optical fiber coupler, form individuals in the genetic algorithm, and calculate the fitness value of each individual; According to the fitness value of the individual, the excellent individuals are retained through the selection operation, new individuals are generated through the crossover operation, and new gene combinations are introduced through the mutation operation until the predetermined number of iterations is reached and convergence to the final solution; According to the final solution, the fiber coupler parameter combination is extracted, and the incident angle, polarization state and other parameters of the pump light are adjusted to couple the pump light into the fiber transmission path.

5. The all-fiber random Raman laser based on a Sagnac ring according to claim 1, characterized in that: The fitness value of each individual is: ; in, is the coupling efficiency, is the insertion loss, is the input optical power, is the optical power coupled into the fiber, is the optical power loss due to the mismatch of polarization states, is the reflected light power, is the bandwidth, , , , and is the weight coefficient, is the fitness value of an individual.

6. The all-fiber random Raman laser based on a Sagnac ring according to claim 1, characterized in that: The parameters of the gain fiber segment are optimized by particle swarm optimization algorithm, and Raman scattering effect is generated, including: Determine the optimization objectives and constraints. The optimization objectives include maximizing Raman gain and optimizing gain flatness. The constraints include the wavelength range of the pump light, the fiber length, and the allowable loss. Initialize the particle swarm and randomly generate a group of particles in the search space. Each particle represents a possible parameter combination, and each particle has a position and a velocity. Set the parameters of the particle swarm optimization algorithm, including the total number of particles, maximum number of iterations, inertia weight, and learning factor; Calculate the performance evaluation value of each particle, compare its current fitness value with the historical performance evaluation value, so as to update the individual extreme value and the global extreme value, wherein the performance evaluation value is the weighted value of the Raman gain minus the weighted penalty value of the gain flatness deviation; Adjust the speed and position of the particle according to the particle's current speed, individual extreme value and global extreme value; According to the speed and position of the particle, a maximum number of iterations is reached to optimize the parameters of the gain fiber segment; According to the optimized gain fiber segment, a Raman scattering effect is generated.

7. The all-fiber random Raman laser based on a Sagnac ring according to claim 1, characterized in that: According to the Raman scattering effect, the differential evolution algorithm is used to optimize the parameters of the Sagnac ring structure, and the cyclic transmission and polarization state of the optical signal are adjusted to generate random Raman scattering, including: Determine optimization objectives and constraints; A set of individuals is randomly generated in the search space, each of which represents a Sagnac ring structure parameter setting; Set the parameters of the differential evolution algorithm, including population size, differential weight factor, and crossover probability; For each individual, based on the evaluation value under the current parameter combination, perform mutation and crossover operations on the individuals in the population to generate new candidate individuals, compare the evaluation values ​​of the candidate individuals with the original individuals, and select individuals with higher fitness values ​​to enter the next generation population. When the maximum number of iterations is reached, the iteration is terminated to obtain the final solution; According to the final solution, the parameters of the optimized Sagnac ring structure are obtained, and the cyclic transmission and polarization state of the optical signal are adjusted according to the parameters to generate random Raman scattering.

8. The all-fiber random Raman laser based on a Sagnac ring according to claim 1, characterized in that: The calculation formula of the evaluation value is: ; in, , and is the weight coefficient, is the optical signal transmission efficiency, is the rate of change of the polarization state angle, is the integrated Raman scattering spectrum intensity, , , is the exponential coefficient, is a small positive number, It is the evaluation value.

9. The all-fiber random Raman laser based on a Sagnac ring according to claim 1, characterized in that: Receive random Raman scattering and optimize the design of the output device through the ant colony optimization algorithm to achieve the extraction and output of random Raman laser, including: Identify specific goals for optimizing output device design; receiving random Raman scattering signals and preprocessing the scattering signals; A set of design parameter combinations of the output device is randomly generated as the starting point of the ant colony search, and the ant colony search and pheromone update are performed to output the final solution; According to the final solution, the design parameters of the output device are set to achieve the extraction and output of random Raman laser.

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