High-density and miniaturized connector

Abstract

The invention relates to the field of connectors, and discloses a high-density and miniaturized connector. Comprising a shell module, and a first connecting area is formed on one side of the shell module; an insertion core module, wherein the insertion core module is packaged in the shell module; and the tail sleeve comprises a tail sleeve body and an extension assembly, the extension assembly is fixedly connected with the first connection area of the shell module, an optical fiber connection area is arranged in the tail sleeve body, and a preset optical fiber connection line is connected with the insertion core module in the shell module through the optical fiber connection area. The centralized optical fiber connection area is arranged in the tail sleeve body, and the connection area of the optical fiber connection line and the insertion core module is integrated in the tail sleeve, so that the occupation of external wiring space is reduced, and high-density arrangement of multi-core optical fibers can be realized in a limited volume.

Description

Technical Field

[0001] This application relates to the field of connector technology, and more particularly to a high-density and miniaturized connector. Background Technology

[0002] In the field of fiber optic communication, high-density, miniaturized connectors are key components for realizing the integration of optical devices. Traditional fiber optic connectors typically adopt a split tail sleeve structure, and the tail sleeve is usually fixed to the outer shell module by a single snap or thread connection. This results in uneven stress distribution after assembly, which can easily lead to loosening or poor contact. In addition, the fiber connection area is scattered and occupies a large space, making it difficult to meet the needs of high-density cabling. Summary of the Invention

[0003] This application provides a high-density and miniaturized connector, which aims to solve the problems of traditional fiber optic connectors that usually adopt a split tail sleeve structure, and the tail sleeve is usually fixed to the outer shell module by a single snap or thread connection, resulting in uneven stress distribution after assembly, easy loosening or poor contact, and the fiber optic connection area is scattered, occupying a large space, making it difficult to meet the needs of high-density cabling.

[0004] In a first aspect, embodiments of this application provide a high-density and miniaturized connector, comprising: A housing module, wherein a first connection area is formed on one side of the housing module; A ferrule module, wherein the ferrule module is encapsulated inside the outer casing module; The tail sleeve includes a tail sleeve body and an extension component. The extension component is fixedly connected to the first connection area of ​​the outer shell module. The tail sleeve body is provided with an optical fiber connection area, and a preset optical fiber connection line is connected to the ferrule module in the outer shell module through the optical fiber connection area.

[0005] In some embodiments, the device further includes a crimped aluminum ring disposed between the tail sleeve body and the outer casing module.

[0006] In some embodiments, the ferrule module includes a ferrule, a metal guide pin holder, a ferrule sleeve, and a spring.

[0007] In some embodiments, the assembly position optimization of the first connection area and the mating part is achieved by establishing a three-dimensional assembly model of the first connection area of ​​the outer shell module, inputting material properties and assembly tolerance ranges; using machine learning algorithms to train historical assembly data to establish a prediction model of the assembly position; and outputting the optimal assembly coordinate range that satisfies the signal transmission loss threshold of the ferrule module through the prediction model.

[0008] In some embodiments, the machine learning algorithm employs a convolutional neural network model. The input layer of the model includes the surface roughness of the first connection region, the geometric tolerance of the mating part, and the assembly environment temperature parameters. The output layer is the coordinate offset of the assembly position. The convolutional neural network model is trained through supervised learning using historical assembly good product data.

[0009] In some embodiments, the tail sleeve includes a plurality of hollowed-out sections.

[0010] In some embodiments, the size and position optimization of the hollow section are achieved by using 3D scanning to obtain the structural parameters of the tail sleeve body and constructing a lightweight finite element model; setting volume constraints and structural strength thresholds for the hollow section; using a genetic algorithm to iteratively optimize the geometric parameters of the hollow section; and outputting a hollow layout scheme that meets the heat dissipation requirements of the optical fiber connection area and the mechanical strength requirements of the tail sleeve.

[0011] In some embodiments, the fitness function of the genetic algorithm includes the heat dissipation efficiency index of the hollowed-out part and the modal frequency index of the tail sleeve body. The position coordinates, radius and depth parameters of the hollowed-out part are globally searched through crossover and mutation operations to generate an optimization iteration sequence of no less than three generations.

[0012] In some embodiments, the optical power, transmission distance, and spatial limitation parameters of the target optical fiber communication scenario are collected; a multi-objective optimization model is established based on the optical power, transmission distance, and spatial limitation parameters, with the optimization objectives being to minimize the total volume of the tail sleeve and maximize the bending radius of the optical fiber; the multi-objective optimization model is solved by a simulated annealing algorithm, and the optimal combination parameters corresponding to the length of the ferrule module, the outer shell module, and the tail sleeve, the number of tail sleeves, and the inner diameter of the tail sleeve are output.

[0013] In some embodiments, the multi-objective optimization model integrates a real-time feedback mechanism. When the optical fiber communication requirement parameters change, it triggers the dynamic restart procedure of the simulated annealing algorithm to recalculate the optimal solution for the number of tail sleeves and component dimensions based on the updated parameter set.

[0014] This invention integrates the connection area between the optical fiber connector and the ferrule module inside the tail sleeve body by incorporating a centralized optical fiber connection area, thereby reducing the space occupied by external wiring and enabling high-density arrangement of multi-core optical fibers within a limited volume.

[0015] The structure of fixing the outer shell module by using the tail sleeve body and extension components replaces the traditional complex multi-part assembly method, simplifies the overall structure, reduces the size of the connector, and is suitable for compact optical communication equipment.

[0016] The co-fixing structure between the tail sleeve and the outer casing module enhances the mechanical connection strength and reduces displacement caused by vibration or insertion / removal operations. At the same time, the enclosed design of the fiber optic connection area reduces interference from dust and external forces on the fiber optic connection point, improving signal transmission stability.

[0017] The modular design of the tail sleeve facilitates quick insertion, removal, and replacement of optical fibers. Combined with the open layout of the optical fiber connection area, it can significantly reduce on-site installation and maintenance costs.

[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the structure of a high-density and miniaturized connector provided in one embodiment of this application; Figure 2 This is an exploded view of a high-density and miniaturized connector provided in an embodiment of this application.

[0021] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Detailed Implementation

[0022] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0024] It should be understood that, in order to clearly describe the technical solutions of the embodiments of the present invention, the terms "first" and "second" are used in the embodiments of the present invention to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0025] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0026] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0027] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0028] In the field of fiber optic communication, high-density, miniaturized connectors are key components for achieving the integration of optical devices. Traditional fiber optic connectors typically employ a split tail sleeve structure, with the tail sleeve and outer shell module often secured by a single snap-fit ​​or threaded connection. This results in uneven stress distribution after assembly, making loosening or poor contact likely. Furthermore, the dispersed fiber connection area layout occupies a significant amount of space, making it difficult to meet the demands of high-density cabling. Current connector tail sleeve designs often focus on a single function (such as simply securing the fiber), lacking optimization of the structural synergy between the outer shell module, ferrule module, and tail sleeve. In particular, they do not address lightweight fixation through the mating structure of the tail sleeve body and extension components, or improving space utilization through integrated fiber connection areas. Therefore, current technologies lack the inspiration to design a tail sleeve that "fixes the outer shell module with the tail sleeve body and extension components, and incorporates a centralized fiber connection area within the tail sleeve body." Achieving high-density integration and miniaturization of connectors through structural innovation remains a pressing technical challenge.

[0029] To solve the above problem, please refer to Figure 1 and Figure 2This application provides a high-density and miniaturized connector, including a housing module 10, on one side of which a first connection area 11 is formed; a ferrule module 20, which is encapsulated inside the housing module; and a tail sleeve 30, which includes a tail sleeve body 31 and an extension component 32, the extension component being fixedly connected to the first connection area of ​​the housing module, and the tail sleeve body having an optical fiber connection area, through which a preset optical fiber connection line is connected to the ferrule module inside the housing module.

[0030] Specifically, the connector provided in this application solves the problems of uneven stress distribution and large space occupation of traditional connectors through the innovative structural design of the tail sleeve and the integrated layout of the centralized optical fiber connection area, achieving high-density integration and miniaturization. A first connection area is set on one side of the shell module for fixed connection with external equipment or structures, providing basic support.

[0031] The ferrule module is encapsulated inside the outer casing module and is responsible for the precise alignment and optical connection of the optical fiber.

[0032] The tail sleeve body has a centralized fiber optic connection area inside, which is used to store fiber optic cables and connect them to the ferrule module; the outside has a structure (such as a buckle, a sliding groove, etc.) that cooperates with the extension components.

[0033] The extension component is linked with the tail sleeve body, and locks with the first connection area of ​​the outer shell module through a push-pull action, so as to achieve lightweight and uniform stress fixation between the tail sleeve and the outer shell module.

[0034] The centralized fiber optic connection area integrates multiple fiber optic interfaces within the tail sleeve body, reducing the space occupied by the fiber optic connection area through a compact layout and supporting high-density cabling.

[0035] The main body of the outer shell module is a columnar or square structure, with a first connection area (such as a boss, threaded hole, or snap-fit ​​groove) formed on one side for fixing to external structures such as the frame and panel. The internal hollow area encapsulates the ferrule module, with its front end (optical connection end) exposed at the front of the outer shell module for mating with the opposite connector. The outer shell module can be made of metal (such as stainless steel) or high-strength engineering plastics (such as POM or PEI), balancing strength and lightweight design.

[0036] The ferrule module has internal fiber optic through-holes for securing the fiber end face and achieving optical alignment. The ferrule module is fixed to the outer casing module via injection molding or mechanical crimping, ensuring that the optical axis aligns with the outer casing module's axis.

[0037] The tail sleeve body is cylindrical and is fitted onto the tail of the outer shell module, with its inner wall slidingly engaging with the outer wall of the outer shell module.

[0038] The fiber optic connection area is located at the rear of the tailpiece body and is equipped with multiple fiber optic mounting slots or adapter interfaces (such as miniaturized interfaces like LC and MU) to support the centralized access of multiple fibers (such as ribbon fibers or single-core fibers). The fiber optic connection cable is introduced through the inlet hole at the rear of the tailpiece body and is connected to the fiber optic pigtail of the ferrule module within the fiber optic connection area via heat fusion, cold splicing, or adapters.

[0039] The outer side is provided with a first mating part, such as an annular protrusion, a snap-fit ​​protrusion, or a groove, for linkage with the extension component.

[0040] The extension component is in the form of a ring or sleeve, and is fitted on the outside of the tail sleeve body, and can slide along the axial direction of the tail sleeve body.

[0041] The inner side is provided with a second mating part, corresponding to the first mating part of the tail sleeve body, such as a groove, a snap-fit ​​groove, or a rack. A push-pull handle or anti-slip texture can be provided on the rear edge for easy manual operation. The front end of the extension component is provided with a locking structure, such as a spring snap, a thread, or a wedge block, corresponding to the locking mating part (such as a slot or threaded hole) of the first connection area of ​​the outer shell module.

[0042] The push-pull locking process includes: Initial state: The extension component is located at the rear end of the tail sleeve body, and the locking structure is separated from the first connection area of ​​the outer shell module. Push-in action: Push the extension component forward, and the second mating part of the extension component engages with the first mating part of the tail sleeve body (like a buckle snapping into a groove). At the same time, the locking structure at the front end of the extension component inserts into the locking mating part of the first connection area of ​​the outer shell module, forming a double fixation (the tail sleeve body and the extension component work together to lock the outer shell module). Locked state: The tail sleeve body and the extension component form a whole through structural engagement, evenly compressing the first connection area of ​​the outer shell module. The stress is distributed on the annular contact surface, avoiding the local stress concentration problem of traditional single buckles. Disassembly action: Pull the extension component backward to release the engagement and lock, thus separating the tail sleeve from the outer shell module.

[0043] The tail sleeve body employs an array-style layout, with multiple fiber optic interfaces arranged compactly along the circumference or axial direction. For example: circumferential arrangement: multiple fiber optic interfaces are distributed in a ring within the cross-section of the tail sleeve body, reducing axial space occupation. Axial stacking: fiber optic interfaces are arranged in layers, with each layer corresponding to a set of fiber optic connections, and interference is avoided through partitions or guiding structures.

[0044] Fiber optic connections utilize pre-terminated fiber optic assemblies, such as fiber optic adapters with pigtails, which are directly inserted into the fiber connection area of ​​the pigtail body and secured by mechanical clips or elastic elements. For field termination scenarios, the pigtail body can be equipped with fiber fusion splice chambers or cold splice mounting positions, allowing for field termination of fibers and centralized storage.

[0045] Traditional split-type connectors require separate space for each fiber optic interface, resulting in a scattered layout. This design integrates the fiber optic connection area, compressing multiple channels into the same space, which can reduce the lateral size of the connector by more than 30%, meeting the needs of high-density cabling (such as data center optical backplanes, chip-level optical interconnects, etc.).

[0046] The tailpiece body and extension components are made of lightweight materials (such as carbon fiber reinforced plastic) and are molded using injection molding to ensure fitting precision and structural strength.

[0047] The mating surfaces of the extension assembly and the tail sleeve body feature a rounded transition to avoid stress concentration. The locking structure uses an elastic material (such as silicone or spring steel) to allow for minor deformation to compensate for assembly errors and improve connection stability.

[0048] This connector is suitable for scenarios with high requirements for space density and reliability, including: Data center optical modules: high-density optical interconnect backplanes, reducing rack space occupation. Internal cabling of communication equipment: such as optical interface modules for routers and switches, supporting miniaturized design. Aerospace and military industries: the need for lightweight, high-reliability fiber optic connectors. Optoelectronic integrated devices: such as the coupling connection between silicon photonics chips and optical fibers, realizing chip-level optical interconnects.

[0049] Through the aforementioned structural innovations, the connector provided in this application breaks through the technical bottlenecks of traditional connectors by combining the tail sleeve with a centralized fiber connection area design, providing an effective solution for the high-density integration and miniaturization of optical devices.

[0050] In some embodiments, such as Figure 2 The document also includes a press-fit aluminum ring 40, which is disposed between the tail sleeve body and the outer shell module.

[0051] By adding a pressure-fitting aluminum ring, located between the tail sleeve body and the outer shell module, the connection strength is enhanced, stress distribution is optimized, or heat dissipation is assisted.

[0052] The crimped aluminum ring is a circular metal component with an inner diameter that is interference-fitted with the outer diameter of the outer casing module, and an outer diameter that is clearance-fitted with the inner wall of the tail sleeve body. The aluminum ring is embedded between the tail sleeve body and the outer casing module through an axial crimping process, forming a metal-to-metal contact surface and improving connection rigidity. This further disperses the assembly stress between the tail sleeve and the outer casing module, preventing deformation of the plastic components due to localized compression. The high thermal conductivity of the aluminum ring helps conduct heat in the fiber optic connection area, making it suitable for high-power optical transmission scenarios.

[0053] In some embodiments, such as Figure 2 As shown, the ferrule module includes a ferrule 21, a metal guide pin holder 23, a ferrule sleeve 22, and a spring 24.

[0054] The ferrule is made of ceramic or glass, with a central through-hole precision down to the micrometer level, used to fix the fiber end face and achieve optical alignment.

[0055] A metal guide pin holder surrounds the outside of the ferrule, providing mechanical support. The positioning holes on the guide pin holder mate with the internal bosses of the housing module to ensure that the ferrule axis is coaxial with the housing module axis.

[0056] The insert sleeve is made of elastic polymer material (such as silicone) to wrap the gap between the insert and the guide pin frame, buffering vibration and sealing against dust.

[0057] A spring is fitted at the tail of the ferrule, with one end abutting against the guide pin holder and the other end abutting against the inner wall of the housing module, providing axial elastic force to ensure tight contact between the ferrule and the optical end face of the opposite connector.

[0058] The assembly process involves inserting an optical fiber into the ferrule through-hole and fixing the end face with UV-cured adhesive; pressing the ferrule into a metal guide pin holder to form the core of the ferrule module; covering the ferrule module with a ferrule sleeve and inserting it into the outer shell module; and locking it after the spring is compressed to a preset length.

[0059] For example, such as Figure 2 As shown, the ferrule module may also include a heat-fusion tube 26, a stop 25, a stop cover 27, and a female head positioning seat 28.

[0060] In some embodiments, the assembly position optimization of the first connection area and the mating part is achieved by establishing a three-dimensional assembly model of the first connection area of ​​the outer shell module, inputting material properties and assembly tolerance ranges; using machine learning algorithms to train historical assembly data to establish a prediction model of the assembly position; and outputting the optimal assembly coordinate range that satisfies the signal transmission loss threshold of the ferrule module through the prediction model.

[0061] Signal loss is reduced by optimizing the assembly position of the first connection area and mating part of the shell module based on machine learning algorithms.

[0062] Establish a three-dimensional assembly model of the first connection area of ​​the outer shell module. The parameters include: geometric features: dimensions of the first connection area (such as boss height and snap-fit ​​groove depth), surface roughness (Ra value); material properties: elastic modulus and Poisson's ratio of the outer shell module and the tail sleeve; assembly tolerances: clearance range of mating parts (such as ±0.05mm) and angular deviation (such as ±0.1°).

[0063] Input parameter set: {Surface roughness, geometric tolerance, material elastic modulus, assembly force}.

[0064] Collect historical assembly data, including assembly position coordinates (such as axial displacement and circumferential rotation angle) and corresponding optical transmission loss values.

[0065] Supervised learning algorithms (such as random forests and neural networks) are used to establish a mapping relationship: assembly position coordinates → loss prediction value; training objective: minimize the mean square error (MSE) between the predicted value and the measured value, and set a loss threshold (such as ≤0.3dB).

[0066] The model outputs the optimal assembly coordinate range (e.g., axial position 2.5±0.1mm, circumferential angle 0°±2°) that meets the loss threshold, guiding the precise positioning of automated assembly equipment.

[0067] It can be used in mass production to dynamically adjust the coordinate parameters of assembly robots, reducing manual debugging time.

[0068] In some embodiments, the machine learning algorithm employs a convolutional neural network model. The input layer of the model includes the surface roughness of the first connection region, the geometric tolerance of the mating part, and the assembly environment temperature parameters. The output layer is the coordinate offset of the assembly position. The convolutional neural network model is trained through supervised learning using historical assembly good product data.

[0069] A convolutional neural network (CNN) model is used to optimize the assembly position, with inputs including spatial geometry and environmental parameters.

[0070] The model architecture design includes: Input layer: Surface roughness of the first connection region (numerical, such as Ra 0.8μm); Geometric tolerances of the mating parts (e.g., ferrule eccentricity ≤ 0.002 mm, tail sleeve inner diameter tolerance ± 0.01 mm); assembly environment temperature (e.g., 25 ± 2℃, affecting the material's thermal expansion coefficient). Input format: Geometric parameters are encoded as a two-dimensional matrix (e.g., simulated surface topography image) to facilitate spatial feature extraction by CNN. Convolutional layer: 3×3 convolutional kernels are used to extract spatial features such as surface texture and tolerance distribution, and dimensionality is reduced through pooling layers. Fully connected layer: Outputs the coordinate offset (Δx, Δy, Δθ) of the assembly position, i.e., the adjustment amount relative to the theoretical position.

[0071] The dataset includes: 3D scan data of historically assembled good products (e.g., CT scans to obtain the contact area of ​​mating surfaces) and corresponding loss values. Labels: Optimal assembly coordinates (determined through high-precision instrument measurements). Loss function: Mean Squared Error (MSE) + regularization term to prevent overfitting.

[0072] During assembly, sensors collect real-time data on the surface roughness of the first connection area (such as a laser micrometer) and ambient temperature, inputting this data into a CNN model to predict the offset and guide the robotic arm to dynamically adjust the assembly position.

[0073] In some embodiments, the tail sleeve includes a plurality of hollowed-out sections.

[0074] By incorporating multiple hollowed-out sections within the tail sleeve, lightweight design and optimized heat dissipation are achieved.

[0075] Hollowed-out section morphology: Shape: circular, elliptical or racetrack-shaped through holes, distributed in the non-load-bearing area of ​​the tail sleeve body (such as both sides of the fiber optic connection area, the outside of the sliding path of the extension component); Function: reduce material usage and weight; form an air convection channel to improve heat dissipation efficiency.

[0076] Layout principles: Avoid fiber optic connection areas and locking structures to ensure mechanical strength; symmetrical distribution to avoid stress concentration, such as evenly setting 4 to 6 hollow sections along the circumference of the tail sleeve.

[0077] In some embodiments, the size and position optimization of the hollow section are achieved by using 3D scanning to obtain the structural parameters of the tail sleeve body and constructing a lightweight finite element model; setting volume constraints and structural strength thresholds for the hollow section; using a genetic algorithm to iteratively optimize the geometric parameters of the hollow section; and outputting a hollow layout scheme that meets the heat dissipation requirements of the optical fiber connection area and the mechanical strength requirements of the tail sleeve.

[0078] The size and location of the hollow section are optimized using 3D scanning and genetic algorithms to balance lightweight, strength and heat dissipation.

[0079] 3D scanning uses industrial CT or laser scanners to obtain a precise geometric model of the tail sleeve body and extract parameters such as wall thickness and stress concentration points.

[0080] Finite element modeling: Material properties: elastic modulus, Poisson's ratio, thermal conductivity; Boundary conditions: Apply assembly stress (e.g., axial tensile force of 5N) and thermal load (e.g., heat generated in the fiber optic connection area of ​​0.5W).

[0081] Parameter encoding encodes the location coordinates (x, y), radius r, and depth h of the excavated part into a gene sequence (such as a floating-point vector).

[0082] Fitness function: F=αQ / Qmax+βf* / fmin; where: Q: heat dissipation efficiency (heat flux density calculated by finite element method); f: minimum modal frequency of the tail sleeve body (vibration resistance index); α, β: weighting coefficients (e.g., α=0.6, β=0.4).

[0083] Iterative operation: Randomly generate an initial population (e.g., 50 hollow layout schemes); calculate the fitness of each individual and retain the top 20% as the parent generation; the parent generation generates offspring through crossover (e.g., single-point crossover) and mutation (e.g., randomly adjusting r ± 10%); repeat for 3 generations or more until the fitness converges.

[0084] The optimized cutout layout (such as three circular holes with a radius of 2mm, distributed at 120° intervals around the rear section of the tail sleeve body) reduces weight by 15%, improves heat dissipation efficiency by 20%, and achieves a modal frequency ≥500Hz (meeting vibration resistance requirements).

[0085] In some embodiments, the fitness function of the genetic algorithm includes the heat dissipation efficiency index of the hollowed-out part and the modal frequency index of the tail sleeve body. The position coordinates, radius and depth parameters of the hollowed-out part are globally searched through crossover and mutation operations to generate an optimization iteration sequence of no less than three generations.

[0086] The fitness function of the genetic algorithm is refined into heat dissipation and modal frequency indices, and the global optimum is achieved through multiple generations of iteration.

[0087] The fitness function is used to design the heat dissipation efficiency index: the temperature gradient around the hollow part is calculated, and the goal is to make the maximum temperature of the fiber connection area ≤60℃; heat flow path optimization is introduced, and a "heat dissipation channel" is formed through the hollow part to shorten the heat conduction distance.

[0088] Modal frequency indicators: Avoid the hollowed-out part being close to the locking structure to prevent the natural frequency from resonating with the external vibration frequency (such as the equipment operating frequency of 100Hz); the target minimum modal frequency is ≥2 times the operating frequency (i.e. ≥200Hz).

[0089] Parameter search space: Number of cutouts: 2~6; Location coordinates: limited to the rear 1 / 3 area of ​​the tail sleeve body (away from the insert module); Radius: 1~3mm; Depth: through-hole or non-through-hole (blind hole, depth ≤ 80% of the tail sleeve wall thickness).

[0090] Algorithm optimization includes: crossover probability: 0.8 (high crossover rate promotes gene recombination); mutation probability: 0.05 (low mutation rate maintains population stability); termination condition: optimal fitness increase <1% for 3 consecutive generations.

[0091] In some embodiments, the optical power, transmission distance, and spatial limitation parameters of the target optical fiber communication scenario are collected; a multi-objective optimization model is established based on the optical power, transmission distance, and spatial limitation parameters, with the optimization objectives being to minimize the total volume of the tail sleeve and maximize the bending radius of the optical fiber; the multi-objective optimization model is solved by a simulated annealing algorithm, and the optimal combination parameters corresponding to the length of the ferrule module, the outer shell module, and the tail sleeve, the number of tail sleeves, and the inner diameter of the tail sleeve are output.

[0092] By employing multi-objective optimization based on simulated annealing algorithm, the goal is to balance minimizing the tail sleeve volume with maximizing the fiber bending radius.

[0093] Parameter input and modeling scenario parameters: optical power (e.g., 10mW~100mW), transmission distance (e.g., 100m~10km), space constraints (e.g., installation space diameter ≤10mm); fiber type: single-mode / multimode, lower limit of bending radius (e.g., single-mode fiber ≥30mm). Optimization variables: total tail sleeve length L, inner diameter D; number of tail sleeves N (e.g., 1~3, multiple tail sleeves can be cascaded to expand the fiber channel); ferrule module length l (affects the fiber bending start point). Multi-objective functions include: Objective 1: Minimize the total tail sleeve volume V=N*π*(D / 2) 2 *L.

[0094] Objective 2: Maximize the bending radius of the optical fiber: R = min( 0.5L 0.5L, 0.5D (r fiber); (assuming the fiber is U-shaped bent inside the tail sleeve, r ( optical fiber ) (This refers to the outer diameter of the optical fiber).

[0095] Simulated annealing algorithm flow: Initial solution: Randomly generate a set of parameters (e.g., N=2, L=20mm, D=6mm); Neighborhood search: Perturb parameters (e.g., ΔL=±1mm, ΔD=±0.5mm), calculate the objective function value of the new solution; Acceptance criteria: If the new solution is better (smaller V and larger R), accept it directly. Termination criteria: The temperature drops below the threshold (e.g., T=0.01), or there is no improvement after 100 consecutive iterations.

[0096] In some embodiments, the multi-objective optimization model integrates a real-time feedback mechanism. When the optical fiber communication requirement parameters change, it triggers the dynamic restart procedure of the simulated annealing algorithm to recalculate the optimal solution for the number of tail sleeves and component dimensions based on the updated parameter set.

[0097] The multi-objective optimization model integrates a real-time feedback mechanism to dynamically adjust parameters to cope with changes in demand.

[0098] Sensor monitoring: real-time optical power (e.g., via photodiodes), transmission bit error rate; environmental parameters: temperature, vibration frequency (affecting fiber optic bending loss). Triggering conditions for requirement changes: optical power fluctuations exceeding ±20%; new space constraints (e.g., reduced installation size after equipment upgrades); temporary adjustments to transmission distance (e.g., network topology changes).

[0099] When demand parameters change, the system automatically: pauses the current assembly / operation process; refreshes the input parameters of the multi-objective optimization model (e.g., updating the space constraint to a diameter ≤ 8mm); restarts the simulated annealing algorithm and calculates the optimal solution based on the new parameter set; and outputs the adjusted component dimensions (e.g., reducing the inner diameter of the tail sleeve from 6mm to 5mm and increasing the number of tail sleeves to 3 to maintain the number of fiber optic channels). During dynamic reconfiguration of data center optical networks, the connector structure can be quickly adjusted according to real-time service requirements, avoiding the time-consuming costs of hardware redesign.

[0100] In some embodiments, to address the problem of stress concentration and uneven distribution after assembly caused by a single snap-fit ​​design in traditional snap-fit ​​connections, this embodiment uses reinforcement learning (RL) to simulate the assembly interaction process between the snap-fit ​​and the first connection area of ​​the housing module. By intelligently optimizing the geometric parameters (angle, thickness, position) of the snap-fit, a uniform distribution of stress is achieved at the connection interface, while ensuring a balance between connection strength and assembly convenience.

[0101] The model is constructed by establishing a three-dimensional assembly finite element model of the first connection area (such as the boss) of the outer shell module and the tail sleeve extension component (such as the buckle). The key parameter space of the buckle is defined as follows: buckle tilt angle θ: 30°~60° (affecting the insertion force and stress transmission during assembly); buckle thickness t: 1~3mm (affecting mechanical strength); buckle position offset Δx relative to the center of the outer shell module: -2~2mm (adjusting the symmetry of stress distribution).

[0102] The reinforcement learning environment design includes: State: After assembly, the stress distribution characteristics obtained through finite element analysis (such as the maximum stress value σ_max, stress standard deviation σ_std, reflecting stress concentration and uniformity); Action: The agent selects a set of latching parameters (θ, t, Δx) from the parameter space. Reward function: Design a comprehensive reward to balance stress performance and connection strength: R = α*σmax β*σstd+γ*F hold; where α, β, and γ are weighting coefficients (e.g., α=0.5, β=0.3, γ=0.2); Fhold is the connection holding force of the buckle (calculated through simulation, it needs to be ≥50N to meet the loosening requirement).

[0103] The algorithm training employs Proximal Policy Optimization (PPO) to train the agent and iteratively updates the policy network: Initializing the policy network (e.g., a 3-layer fully connected neural network, with state features as input and action probability distribution as output); In each training round, the agent selects actions (parameter combinations) based on the current policy and calculates the state and reward using a finite element model; Collecting trajectory data from multiple rounds, calculating the advantage function, and updating the policy network to maximize the expected reward; Repeating training until the reward function converges (e.g., reward fluctuation ≤ 5% for 10 consecutive rounds).

[0104] Output the optimal snap-fit ​​parameters (e.g., θ=45°, t=2mm, Δx=0mm), manufacture a prototype, and verify through stress testing (strain gauges) and tensile testing: stress concentration factor (σ_max / material yield strength) ≤0.8 (avoid plastic deformation); stress standard deviation σ_std ≤10MPa (ensure uniform stress distribution); connection holding force F_hold ≥60N (meet the anti-loosening requirements under vibration environment).

[0105] In some embodiments, to address the problem that "different optical fiber communication scenarios (such as data centers and 5G base stations) have large differences in space constraints and transmission performance requirements, and traditional layouts need to be redesigned, resulting in low efficiency," this embodiment uses transfer learning to transfer the optimized layout knowledge of the source scenario (such as data centers) to the target scenario (such as 5G base stations), quickly generating a centralized optical fiber connection area layout adapted to the target scenario, thereby improving space utilization and scenario adaptability.

[0106] Source scenario optimization selects a data center as the source scenario (sufficient space, high fiber density) and uses a genetic algorithm to optimize the fiber connection area layout: optimization objectives: maximize fiber bending radius (≥30mm, reduce loss), minimize the number of fusion splices (≤4 / tail sleeve), and minimize space occupancy (≤20%); output the optimal layout dataset of the source scenario (including fiber arrangement, fusion splice location, bending radius distribution and other features).

[0107] Feature extraction and pre-training are achieved by constructing a convolutional neural network (CNN) as a feature extractor. The input is 3D point cloud data of the source scene layout (reflecting the spatial relationship between the optical fiber and the tail sleeve), and the output is a layout feature vector (such as optical fiber density distribution, bending radius histogram, and space occupancy rate). The CNN is pre-trained with the source scene dataset to master the general features of "high-performance layout" (such as "uniform distribution of bending radius" and "fusion splice points far from heat dissipation blind areas").

[0108] The target scenario migration selects 5G base stations as the target scenario (limited space and short transmission distance), and collects a small amount of target scenario data (such as the maximum outer diameter of the tail sleeve ≤ 20mm and the number of optical fibers ≤ 8 / tail sleeve). Freeze the pre-trained CNN feature extractor (fixed parameters), add an adaptive fine-tuning layer (such as 2 fully connected layers), take the constraint parameters of the target scene (spatial constraints, number of optical fibers) and the feature vector of the source scene as input, and take the layout parameters of the target scene (such as optical fiber spacing and splice offset) as output. Fine-tune the adaptive layer using a small amount of labeled data from the target scene (such as 10 sets of manually designed feasible layouts) to adapt the model to the constraints of the target scene.

[0109] The layout generation and verification process takes the constraint parameters of the target scene as input (e.g., 12mm inner diameter of the tail sleeve and 6 optical fibers) and outputs a centralized optical fiber connection area layout (e.g., the optical fibers are arranged in a hexagonal shape, and the fusion splice is located 10mm on both sides of the central axis of the tail sleeve). The layout is verified through optical transmission simulation (e.g., OptiSystem): insertion loss ≤ 0.3dB (meets the transmission requirements of 5G base stations); space occupancy ≤ 15% (30% lower than the traditional distributed layout); and optical fiber bending radius ≥ 25mm.

[0110] This invention integrates the connection area between the optical fiber connector and the ferrule module inside the tail sleeve body by incorporating a centralized optical fiber connection area, thereby reducing the space occupied by external wiring and enabling high-density arrangement of multi-core optical fibers within a limited volume.

[0111] The structure of fixing the outer shell module by using the tail sleeve body and extension components replaces the traditional complex multi-part assembly method, simplifies the overall structure, reduces the size of the connector, and is suitable for compact optical communication equipment.

[0112] The co-fixing structure between the tail sleeve and the outer casing module enhances the mechanical connection strength and reduces displacement caused by vibration or insertion / removal operations. At the same time, the enclosed design of the fiber optic connection area reduces interference from dust and external forces on the fiber optic connection point, improving signal transmission stability.

[0113] The modular design of the tail sleeve facilitates quick insertion, removal, and replacement of optical fibers. Combined with the open layout of the optical fiber connection area, it can significantly reduce on-site installation and maintenance costs.

[0114] It should be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. It should be understood that when an element or layer is referred to as “on,” “adjacent to,” “connected to,” or “coupled to” other elements or layers, it may be directly on, adjacent to, connected to, or coupled to other elements or layers, or there may be intervening elements or layers. Conversely, when an element is referred to as “directly on,” “directly adjacent to,” “directly connected to,” or “directly coupled to” other elements or layers, there are no intervening elements or layers. It should be understood that although the terms first, second, third, etc., may be used to describe various elements, components, areas, layers, and / or portions, these elements, components, areas, layers, and / or portions should not be limited by these terms. These terms are merely used to distinguish one element, component, area, layer, or portion from another element, component, area, layer, or portion. Therefore, without departing from the teachings of this application, the first element, component, area, layer, or portion discussed below may be referred to as a second element, component, area, layer, or portion.

[0115] Spatial relation terms such as “below,” “under,” “below,” “under,” “above,” “above,” etc., are used herein for convenience of description to describe the relationship between one element or feature shown in the figure and other elements or features. It should be understood that, in addition to the orientation shown in the figure, spatial relation terms are intended to also include different orientations of the device in use and operation. For example, if the device in the figure is flipped, then the element or feature described as “below,” “under,” or “below” other elements or features will be oriented “above” other elements or features. Therefore, the exemplary terms “below” and “under” can include both above and below orientations. The device may be otherwise oriented (rotated 90 degrees or otherwise) and the spatial descriptive terms used herein will be interpreted accordingly.

[0116] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. When used herein, the singular forms “a,” “an,” and “the” are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising” and / or “including,” when used in this specification, identify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups. When used herein, the term “and / or” includes any and all combinations of the associated listed items.

[0117] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0118] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A high-density and miniaturized connector, characterized in that, include: A housing module, wherein a first connection area is formed on one side of the housing module; A ferrule module, wherein the ferrule module is encapsulated inside the outer casing module; The tail sleeve includes a tail sleeve body and an extension component. The extension component is fixedly connected to the first connection area of ​​the outer shell module. The tail sleeve body is provided with an optical fiber connection area, and a preset optical fiber connection line is connected to the ferrule module in the outer shell module through the optical fiber connection area.

2. The high-density and miniaturized connector according to claim 1, characterized in that, Also includes: A press-fit aluminum ring is disposed between the tail sleeve body and the outer shell module.

3. The high-density and miniaturized connector according to claim 1, characterized in that, The ferrule module includes a ferrule, a metal guide pin holder, a ferrule sleeve, and a spring.

4. The high-density and miniaturized connector according to claim 1, characterized in that, The assembly position optimization of the first connection area and the mating part is achieved by establishing a three-dimensional assembly model of the first connection area of ​​the outer shell module, inputting material properties and assembly tolerance ranges; using machine learning algorithms to train historical assembly data to establish a prediction model of the assembly position; and outputting the optimal assembly coordinate range that satisfies the signal transmission loss threshold of the ferrule module through the prediction model.

5. The high-density and miniaturized connector according to claim 4, characterized in that, The machine learning algorithm employs a convolutional neural network model. The input layer of the model includes the surface roughness of the first connection region, the geometric tolerance of the mating part, and the assembly environment temperature parameters. The output layer is the coordinate offset of the assembly position. The convolutional neural network model is trained through supervised learning using historical assembly good product data.

6. The high-density and miniaturized connector according to claim 1, characterized in that, The tail sleeve includes multiple hollowed-out sections.

7. The high-density and miniaturized connector according to claim 6, characterized in that, The size and position optimization of the hollow section are achieved by using 3D scanning to obtain the structural parameters of the tail sleeve body and constructing a lightweight finite element model; setting volume constraints and structural strength thresholds for the hollow section; using a genetic algorithm to iteratively optimize the geometric parameters of the hollow section; and outputting a hollow layout scheme that meets the heat dissipation requirements of the optical fiber connection area and the mechanical strength requirements of the tail sleeve.

8. The high-density and miniaturized connector according to claim 7, characterized in that, The fitness function of the genetic algorithm includes the heat dissipation efficiency index of the hollow part and the modal frequency index of the tail sleeve body. The position coordinates, radius and depth parameters of the hollow part are globally searched through crossover and mutation operations to generate an optimization iteration sequence of no less than three generations.

9. The high-density and miniaturized connector according to claim 1, characterized in that, The optical power, transmission distance, and spatial limitation parameters of the target optical fiber communication scenario are collected. A multi-objective optimization model is established based on the optical power, transmission distance, and spatial limitation parameters, with the optimization objectives being to minimize the total volume of the tail sleeve and maximize the bending radius of the optical fiber. The multi-objective optimization model is solved by a simulated annealing algorithm, and the optimal combination parameters corresponding to the length of the ferrule module, the outer shell module, and the tail sleeve, the number of tail sleeves, and the inner diameter of the tail sleeve are output.

10. The high-density and miniaturized connector according to claim 9, characterized in that, The multi-objective optimization model integrates a real-time feedback mechanism. When the optical fiber communication requirement parameters change, it triggers the dynamic restart program of the simulated annealing algorithm to recalculate the optimal solution for the number of tail sleeves and component dimensions based on the updated parameter set.

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