Fbg sensor package housing manufacturing method and related apparatus

Abstract

The embodiment of the application provides a FBG sensor packaging shell manufacturing method and related equipment, and belongs to the technical field of automatic manufacturing. The method comprises the following steps: scanning the surface structure of a measured target to obtain first three-dimensional data, and acquiring second three-dimensional data of the surface of a target FBG sensor; determining a shell three-dimensional model of a packaging shell according to the first three-dimensional data and the second three-dimensional data; and printing the shell three-dimensional model by using an additive manufacturing technology to obtain the packaging shell of the target FBG sensor. The scheme can reduce the influence of the packaging shell on the measurement accuracy of the FBG sensor, and improve the measurement accuracy of the packaged FBG sensor.

Description

Technical Field

[0001] This application relates to the field of automated manufacturing technology, and in particular to a method and related equipment for manufacturing an FBG sensor package housing. Background Technology

[0002] In recent years, fiber Bragg grating (FBG) sensors have demonstrated significant application potential in slope disaster monitoring due to their small size, high measurement accuracy, and excellent electromagnetic interference resistance, becoming an important technical means for geological disaster early warning. Generally, FBG sensors are encapsulated in rectangular housings made of various materials, which are then adhered to the surface of the object being measured, such as rock, for strain measurement. However, in real-world environments, the complex geological characteristics of slope soil and rock, including heterogeneity and anisotropy, coupled with the harsh effects of rainwater erosion and freeze-thaw cycles, present multiple technical bottlenecks in FBG sensor encapsulation. Traditional encapsulation processes lack adaptability to irregular slope surfaces and struggle to meet the deformation transfer requirements of discontinuous geological interfaces. This leads to a prominent contradiction between mechanical protection and sensing accuracy for FBG sensors, resulting in measurement accuracy issues caused by signal distortion in actual monitoring. Summary of the Invention

[0003] The main objective of this application is to provide a method and related equipment for manufacturing an FBG sensor package housing, which aims to reduce the impact of the package housing on the measurement accuracy of the FBG sensor and improve the measurement accuracy of the packaged FBG sensor.

[0004] To achieve the above objectives, one aspect of this application proposes a method for manufacturing an FBG sensor packaging housing, comprising the following steps: The surface structure of the target under test is scanned to obtain the first three-dimensional data, and the second three-dimensional data of the target FBG sensor surface is acquired. Based on the first three-dimensional data and the second three-dimensional data, determine the three-dimensional model of the packaging shell; The three-dimensional model of the housing is printed using additive manufacturing technology to obtain the encapsulation housing of the target FBG sensor.

[0005] In some embodiments, determining the three-dimensional model of the packaging housing based on the first three-dimensional data and the second three-dimensional data includes the following steps: The first three-dimensional data is reverse-processed to obtain the third three-dimensional data; and the second three-dimensional data is reverse-processed to obtain the fourth three-dimensional data. In response to the first selection command, select the target base model from the base model library; The third three-dimensional data is written into the outer surface mounting area of ​​the target base model, and the fourth three-dimensional data is written into the inner surface mounting area of ​​the target base model to obtain the shell three-dimensional model.

[0006] In some embodiments, determining the three-dimensional model of the packaging housing based on the first three-dimensional data and the second three-dimensional data further includes the following steps: In response to the second selection command, select the three-dimensional data of the target microstructure from the surface microstructure library; The outer surface of the shell 3D model is optimized based on the target microstructure 3D data to obtain the optimized shell 3D model.

[0007] In some embodiments, determining the three-dimensional model of the packaging housing based on the first three-dimensional data and the second three-dimensional data further includes the following steps: In response to the operation command on the inner surface of the three-dimensional model of the housing, the mounting area of ​​the temperature sensor is determined; The printing material properties of the three-dimensional data of the corresponding installation area in the three-dimensional model of the shell are determined to be a preset heat-conducting material.

[0008] In some embodiments, determining the three-dimensional model of the packaging housing based on the first three-dimensional data and the second three-dimensional data further includes the following steps: In response to the guide channel configuration command, a guide channel model is constructed; the guide channel configuration command includes the guide channel height and the guide channel width. The orientation of the guide channel model is adjusted according to the desired installation direction, and the three-dimensional model of the shell is adjusted according to the guide channel model after the orientation adjustment.

[0009] In some embodiments, printing the three-dimensional model of the housing using additive manufacturing technology to obtain the packaging housing of the target FBG sensor includes the following steps: A geometric analysis is performed on the three-dimensional model of the shell to determine its geometric complexity. Select the target process program from the process program library based on the geometric complexity; The 3D printer is controlled according to the target process procedure to print the three-dimensional model of the shell, thereby obtaining the encapsulated shell.

[0010] In some embodiments, the method for manufacturing the FBG sensor package housing further includes the following steps: Take images of the surface of the packaging shell; The packaging shell is subjected to defect detection based on the surface image to obtain the detection result of the packaging shell.

[0011] To achieve the above objectives, another aspect of this application provides an FBG sensor packaging housing manufacturing system, comprising: The scanning module is used to scan the surface structure of the target to obtain first three-dimensional data, and to acquire second three-dimensional data of the target FBG sensor surface; The model building module is used to determine the three-dimensional model of the encapsulation shell based on the first three-dimensional data and the second three-dimensional data; The printing module is used to print the three-dimensional model of the housing using additive manufacturing technology to obtain the encapsulation housing of the target FBG sensor.

[0012] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0013] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0014] The embodiments of this application include at least the following beneficial effects: This application provides a method, system, electronic device, and program product for manufacturing an FBG sensor encapsulation housing. This solution obtains first three-dimensional data by scanning the surface structure of the target object and acquires second three-dimensional data of the target FBG sensor surface. Then, a three-dimensional model of the encapsulation housing is constructed based on the first and second three-dimensional data. Additive manufacturing technology is then used to print the three-dimensional model of the housing to obtain the encapsulation housing of the target FBG sensor. This solution, by scanning the surface structure of the target object and constructing a three-dimensional housing model based on the scanned structure, ensures that the printed encapsulation housing can match the deformation transfer requirements of the target object's surface. Simultaneously, by constructing a three-dimensional housing model based on the surface structure of the FBG sensor, the FBG sensor can be stably and securely mounted within the encapsulation housing, reducing the impact of the encapsulation housing on the FBG sensor's measurement accuracy. Attached Figure Description

[0015] Figure 1 This is a flowchart of the FBG sensor packaging housing manufacturing method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the FBG sensor packaging housing manufacturing system provided in an embodiment of this application; Figure 3 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0017] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0018] Before providing a detailed description of the embodiments of this application, some of the nouns and terms involved in the embodiments of this application will be explained first. The nouns and terms involved in the embodiments of this application are subject to the following interpretations.

[0019] 1) FBG sensor (Fiber Bragg Grating Sensor) is an advanced sensing device that uses fiber optic grating structure to achieve high-precision measurement of external physical quantities (such as strain, temperature, pressure, etc.).

[0020] 2) Additive manufacturing technology (also known as 3D printing technology) is a manufacturing method based on the layer-by-layer deposition of material from a digital model. Its core principle contrasts sharply with traditional subtractive manufacturing (machining) and equal-material manufacturing (casting and forging). This technology uses computer-aided design (CAD) to break down a 3D model into thin layers of data, which are then formed layer by layer through methods such as laser sintering, photopolymerization, and fused deposition modeling, ultimately enabling the direct manufacturing of complex structural parts.

[0021] In related technologies, there are four main packaging methods for FBG sensors: (1) Epoxy resin bonding and encapsulation: Fiber Bragg gratings (FBGs) are directly bonded to the surface of the structure under test using adhesives such as epoxy resin, or encapsulated in a prefabricated protective shell. This method is simple to operate and has a low cost, and was common in early FBG applications.

[0022] (2) Metal sleeve encapsulation: The FBG is placed inside a metal sleeve (such as a stainless steel tube or copper tube), and both ends are fixed with epoxy resin or other sealing materials to form an independent sensing unit. The metal sleeve can provide a certain mechanical protection for the FBG and is suitable for scenarios with high protection requirements.

[0023] (3) Polymer-based encapsulation: Polymer materials such as polyvinyl chloride (PVC) and polytetrafluoroethylene (PTFE) are used to encapsulate FBG through injection molding, compression molding, etc. Polymer materials have certain flexibility and corrosion resistance, and can adapt to some complex environments.

[0024] (4) Clamp-type packaging: The FBG is fixed to the structure under test using mechanical clamps (such as metal clips and bolts). The prestress of the FBG is applied and the installation is stabilized by adjusting the tightness of the clamps. This method is convenient for installation and disassembly and can be reused.

[0025] The aforementioned method of directly bonding the FBG sensor to the surface of the measured structure using adhesives such as epoxy resin is prone to causing poor long-term stability of the FBG sensor. It is susceptible to aging due to changes in temperature and humidity, leading to decreased adhesion and slippage between the sensor and the measured structure, thus affecting the accuracy of the monitoring data. Furthermore, the internal stress generated during the adhesive curing process may alter the initial center wavelength of the FBG sensor, causing measurement errors. While metal sleeve encapsulation, polymer-based encapsulation, or clamp-type encapsulation can mitigate the influence of the external environment on the FBG sensor to some extent, currently manufactured encapsulation shells lack adaptability to irregular slopes and struggle to meet the deformation transmission requirements of discontinuous geological interfaces. This results in a significant contradiction between mechanical protection and sensing accuracy for the FBG sensor, leading to signal distortion and measurement accuracy issues in actual monitoring.

[0026] In view of this, this application provides a method and related equipment for manufacturing an FBG sensor encapsulation housing. This method scans the surface structure of the target being measured and constructs a three-dimensional model of the housing based on the scanned structure. The encapsulation housing printed based on additive manufacturing technology can match the deformation transfer requirements of the target surface. At the same time, a three-dimensional model of the housing is constructed based on the surface structure of the FBG sensor, so that the FBG sensor can be stably attached and installed in the encapsulation housing, reducing the impact of the encapsulation housing on the measurement accuracy of the FBG sensor.

[0027] The FBG sensor packaging shell manufacturing method provided in this application relates to the field of automated manufacturing technology. This method can be applied to terminals, servers, or software running on either a terminal or server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the FBG sensor packaging shell manufacturing method, but is not limited to the above forms.

[0028] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0029] Exemplarily, embodiments of this application can be applied to a human-computer interaction terminal, which connects a 3D printer and a 3D scanner. The 3D scanner is used to measure the set of three-dimensional coordinate points on the surface of a physical object; the resulting set of numerous coordinate points is called a point cloud. A 3D printer, also known as a three-dimensional printer (3DP), is a type of cumulative manufacturing technology, or rapid prototyping technology. It uses a digital model file as a basis and selectable adhesive materials such as special waxes, powdered metals, or plastics to print layers of adhesive material to create three-dimensional objects. The principle of a 3D printer is that data and raw materials are put into the printer, and the machine will build the product layer by layer according to the program. The human-computer interaction terminal uses a 3D scanner to collect first three-dimensional data of the surface structure of the target object, such as a rock, and second three-dimensional data of the surface structure from an FBG sensor. Based on the first and second three-dimensional data, the human-computer interaction terminal can automatically construct a three-dimensional model of the shell. The terminal can also interact with the user, receiving relevant user input commands to adaptively adjust the shell's three-dimensional model. After completing the construction of the shell's three-dimensional model, the human-computer interaction terminal sends the shell's three-dimensional model to the 3D printer for encapsulation shell manufacturing.

[0030] Figure 1 This is an optional flowchart of the FBG sensor package housing manufacturing method provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S103.

[0031] Step S101: Scan the surface structure of the target to obtain the first three-dimensional data, and acquire the second three-dimensional data of the target FBG sensor surface; Step S102: Determine the three-dimensional model of the encapsulation shell based on the first three-dimensional data and the second three-dimensional data; Step S103: The three-dimensional model of the housing is printed using additive manufacturing technology to obtain the encapsulation housing of the target FBG sensor.

[0032] Steps S101 to S103 of this embodiment involve obtaining first three-dimensional data and second three-dimensional data of the target FBG sensor surface by scanning the surface structure of the target. Then, a three-dimensional model of the encapsulation housing is constructed based on the first and second three-dimensional data. Additive manufacturing technology is then used to print the three-dimensional model of the housing to obtain the encapsulation housing of the target FBG sensor. This embodiment, by scanning the surface structure of the target and constructing a three-dimensional housing model based on the scanned structure, ensures that the printed encapsulation housing matches the deformation transfer requirements of the target surface. Simultaneously, by constructing a three-dimensional housing model based on the surface structure of the FBG sensor, the FBG sensor can be stably mounted within the encapsulation housing, reducing the impact of the encapsulation housing on the measurement accuracy of the FBG sensor.

[0033] In step S101 of some embodiments, the first three-dimensional data is a set of point cloud data characterizing the surface spatial structure of the bonding area of ​​the target being measured. The target being measured can be a rock surface, and the bonding area may have structural features such as rock cracks. A 3D scanner can represent structural features such as cracks as three-dimensional data in a computer virtual space. The target FBG sensor refers to the sensor model used to measure the target being measured. Sensor selection can be based on the needs of slope displacement monitoring, accurately matching the optimal FBG sensor type to improve monitoring accuracy. The second three-dimensional data of the target FBG sensor surface can be obtained by scanning the target FBG sensor with a 3D scanner, or the surface three-dimensional data corresponding to various FBG sensor models can be stored in a human-computer interaction terminal. The user can select the sensor model on the human-computer interaction terminal to determine the second three-dimensional data of the target FBG sensor surface.

[0034] In step S102 of some embodiments, the human-machine interface terminal constructs the outer surface features of the shell's three-dimensional model based on the first three-dimensional data. This allows the subsequently printed encapsulated shell to match the deformation transfer requirements of the target surface, improving the adaptability of the encapsulated FBG sensor to different measured objects and increasing measurement accuracy. The human-machine interface terminal constructs the inner surface features of the shell's three-dimensional model based on the second three-dimensional data. This allows the subsequently printed encapsulated shell to couple with the shape of the target FBG sensor, improving the stability of the target FBG sensor within the encapsulated shell and thus enhancing measurement reliability.

[0035] In step S103 of some embodiments, the three-dimensional model of the shell represents the encapsulated shell structure through a series of point clouds in a computer virtual space. Each point cloud includes the coordinate information of structural points and printing material. After the human-computer interaction terminal completes the construction of the three-dimensional model of the shell, it sends the three-dimensional model of the shell to the 3D printer for encapsulation shell manufacturing. Additive manufacturing technology (i.e., 3D printer) can feed printing consumables such as polylactic acid (PLA), acrylonitrile-butadiene-styrene (ABS), and nylon into the heating module, transforming them from a solid state to a molten state, and then precisely extruding them into shape according to the three-dimensional model of the shell through the printing nozzle. Compared with traditional subtractive manufacturing methods, additive manufacturing technology effectively overcomes the inherent drawbacks of traditional monitoring instruments, such as long processing cycles, limited structural design, and weak environmental adaptability, due to its low cost, high speed, high precision, and highly flexible customization capabilities. This innovative model of "directly driving physical manufacturing from digital models" not only provides a new technical path for the innovative research and development of high-performance sensing elements, but also becomes a key technical support for solving the encapsulation problem of FBG sensors for slope monitoring due to its excellent customization capabilities under complex working conditions.

[0036] According to some embodiments of this application, step S102 may include, but is not limited to, the following steps: Step S201: Reverse process the first three-dimensional data to obtain the third three-dimensional data; and reverse process the second three-dimensional data to obtain the fourth three-dimensional data; Step S202: In response to the first selection instruction, select the target base model from the base model library; Step S203: Write the third three-dimensional data into the outer surface mounting area of ​​the target base model, and write the fourth three-dimensional data into the inner surface mounting area of ​​the target base model to obtain the shell three-dimensional model.

[0037] In step S201 of some embodiments, the first three-dimensional data represents the surface structure of the target being measured. The outer surface of the encapsulation shell needs to be coupled with the surface structure of the target being measured; therefore, reverse engineering is required to process the first three-dimensional data to obtain the third three-dimensional data. Specifically, the surface geometric features of the object being measured can be extracted from the first three-dimensional data, and then a surface can be generated based on the surface geometric features using parametric modeling techniques based on B-spline surfaces, NURBS surface modeling techniques, least squares methods, or deep learning networks, thereby obtaining the third three-dimensional data. The process of reverse processing the second three-dimensional data to obtain the fourth three-dimensional data is similar and will not be described further here.

[0038] In step S202 of some embodiments, the basic model library stores multiple basic models. A basic model is a three-dimensional model representing the basic spatial structure of the encapsulation shell. For example, a basic model can be a hollow square, rectangle, or cone with a certain thickness. The human-computer interaction terminal can access the basic model library and display the basic models therein. Based on the basic models displayed on the human-computer interaction terminal, the user inputs a first selection command for one of the basic models, thereby determining the target basic model.

[0039] In step S203 of some embodiments, the human-computer interaction terminal displays a target base model. The user can select a housing mounting area (i.e., the outer surface mounting area) on the outer surface of the target base model and a sensor pasting area (i.e., the inner surface mounting area) on the inner surface of the target base model. Then, the target base model is scaled according to the proportional relationship between the third 3D data and the outer surface mounting area, or according to the proportional relationship between the fourth 3D data and the inner surface mounting area, so that the target base model is suitable for the actual installation environment. The third 3D data is written into the outer surface mounting area of ​​the target base model, and the fourth 3D data is written into the inner surface mounting area of ​​the target base model to obtain the housing 3D model. Specifically, the lowest point of the third 3D data can be aligned with the outer surface of the target base model, and then point cloud filling is performed on the outer surface of the target base model according to the third 3D data. Similarly, the lowest point of the fourth 3D data can be aligned with the inner surface of the target base model, and then point cloud filling is performed on the outer surface of the target base model according to the fourth 3D data to realize the construction of the housing 3D model. The user can adjust the minimum distance between the inner and outer surfaces of the housing 3D model by adjusting the thickness of the target base model.

[0040] For example, for drilling installation scenarios, users may consider using a variable-diameter encapsulation structure, where the front section of the housing is designed as a frustum-shaped guide head to facilitate smooth insertion into the borehole. Therefore, users can select a conical base model as the target base model via a human-computer interaction terminal. 3D scanning is used to acquire the surface morphology of a rock structure with cracks. Then, through reverse engineering and in conjunction with the target base model, an encapsulation housing with biomimetic tooth-like protrusions is generated. The shape of the protrusions matches the crack characteristics of the structural surface, and the height of the protrusions is dynamically adjusted according to the crack width. Through mechanical interlocking, the housing forms an integral part with the structural surface, allowing the sensor to deform synchronously with the structural surface. Furthermore, users can also set an annular expansion groove in the middle section of the encapsulation housing in virtual space. The expansion groove is filled with water-swellable rubber material. After the sensor is in place, an expansion agent is injected, causing the rubber to expand and tightly adhere to the borehole wall, achieving zero-gap installation.

[0041] This embodiment improves model building efficiency and meets user needs by providing users with a basic model library for selecting target base models and constructing a shell 3D model based on these target base models. Furthermore, this embodiment can adaptively adjust the size and thickness of the target base model according to the actual dimensions represented by third-party 3D data, further improving the efficiency of shell 3D model construction.

[0042] According to some embodiments of this application, step S102 may also include, but is not limited to, the following steps: Step S301: In response to the second selection instruction, select the three-dimensional data of the target microstructure from the surface microstructure library; Step S302: Optimize the outer surface of the shell 3D model based on the target microstructure 3D data to obtain the optimized shell 3D model.

[0043] In this embodiment, considering the accuracy limitations of the 3D scanner or the influence of the scanning environment, it may be unable to identify the subtle texture of the rock, resulting in poor adhesion between the printed encapsulation shell and the rock. Alternatively, user needs may require optimization of the microstructure of the shell's outer surface to improve the adhesion between the shell and the rock surface. This embodiment provides a surface microstructure library, which stores 3D data of multiple surface microstructures. A human-computer interaction terminal can access the surface microstructure library and display the surface microstructures within it. Based on the surface microstructures displayed on the human-computer interaction terminal, the user inputs a second selection command for one of the surface microstructures, thereby determining the 3D data of the target microstructure. The human-computer interaction terminal optimizes the filling of the outer surface of the shell's 3D model based on the target microstructure 3D data, obtaining an optimized shell 3D model. Fabricating the encapsulation shell based on the optimized shell 3D model improves the adhesion between the shell and the rock surface, thereby improving the measurement reliability of the encapsulated FBG sensor.

[0044] For example, for sloping slopes, users may design a housing with barbed anchors to improve the fit between the housing and the target being measured. The user selects a triangular array of barbed microstructures displayed on the human-machine interface (HMI). The HMI then uses an optimization algorithm to generate the triangular array of barbs on the installation area of ​​the housing's 3D model. The angle of the barbs' inclination is maintained between 15° and 20° with the slope normal. This ensures that the housing, printed from the 3D model, forms a self-locking effect under its own weight and soil pressure, further improving the fit between the sensor housing and the target.

[0045] According to some embodiments of this application, step S102 may also include, but is not limited to, the following steps: Step S401: In response to the operation command on the inner surface of the three-dimensional model of the housing, determine the installation area of ​​the temperature sensor; Step S402: Determine the material configuration of the corresponding installation area in the three-dimensional model of the shell as a preset heat-conducting material.

[0046] In this embodiment, when using an FBG displacement sensor for testing, a temperature sensor can be configured simultaneously. A temperature-wavelength compensation model is used to eliminate the interference of ambient temperature on displacement monitoring. Therefore, in some scenarios, a temperature sensor needs to be encapsulated within the housing. However, the measurement accuracy of the temperature sensor on the target object is also affected by the housing. Based on this, the human-computer interaction terminal in this embodiment displays a three-dimensional model of the housing. The user can select the installation area of ​​the temperature sensor on the inner surface of the three-dimensional model. The human-computer interaction terminal determines the printing material properties of the three-dimensional data (i.e., point cloud data) of the corresponding installation area in the three-dimensional model of the housing as a preset thermally conductive material. For the point cloud data of other areas of the three-dimensional model of the housing, the printing material properties are determined to be materials configured by the user (such as polylactic acid (PLA), acrylonitrile-butadiene-styrene (ABS), nylon, etc.). The preset thermally conductive material refers to the material information with thermal conductivity set by the user. Users select the temperature sensor mounting area on the inner surface of the visualized 3D model of the shell. The human-computer interaction terminal automatically modifies the corresponding point cloud data material properties according to the selected mounting area. During the printing process, the 3D printer can select the corresponding material nozzles for printing according to the material properties of different structural points, so that the produced encapsulation shell has a temperature-sensitive area for placing the temperature sensor. This area should have good thermal conductivity to reduce the influence of the encapsulation shell on the target being measured by the temperature sensor.

[0047] According to some embodiments of this application, step S102 may also include, but is not limited to, the following steps: Step S501: In response to the guide channel configuration command, construct the guide channel model; the guide channel configuration command includes the guide channel height and the guide channel width; Step S502: Adjust the orientation of the guide channel model according to the desired installation direction, and adjust the three-dimensional model of the shell according to the guide channel model after the orientation adjustment.

[0048] In this embodiment, the user can input a flow channel configuration command into the human-machine interface terminal. The flow channel configuration command includes the flow channel height and the flow channel width. The human-machine interface terminal constructs a flow channel model based on the flow channel configuration command, and then adjusts the direction of the flow channel model according to the desired installation direction (such as along the direction of gravity when the housing is installed) to ensure that the flow direction of the flow channel model is consistent with the desired installation direction. Then, the flow channel structure is created on the three-dimensional model of the housing based on the adjusted flow channel model, resulting in the three-dimensional model of the housing. The encapsulation shell made based on this three-dimensional model of the housing can guide the slope runoff and prevent water erosion that could cause the sensor to loosen after encapsulation.

[0049] According to some embodiments of this application, step S103 may include, but is not limited to, the following steps: Step S601: Perform geometric analysis on the three-dimensional model of the shell to determine the geometric complexity of the three-dimensional model of the shell. Step S602: Select the target process program from the process program library based on the geometric complexity; Step S603: Control the 3D printer to print the three-dimensional model of the shell according to the target process program to obtain the encapsulated shell.

[0050] In this embodiment, the geometric analysis of the shell's 3D model refers to analyzing the surface curvature and volume of the shell's 3D model to obtain the overall curvature. The overall curvature and volume are used to characterize the geometric complexity of the shell's 3D model; that is, the greater the overall curvature, the greater the geometric complexity, and the smaller the volume, the greater the geometric complexity. Based on the geometric complexity, a target process program is selected from the process program library. The terminal is configured with corresponding process programs for different geometric complexity ranges. The target process program can be determined based on the range in which the shell's 3D model's geometric complexity falls. Then, the 3D printer is controlled to print the shell's 3D model according to the target process program to obtain the encapsulated shell. This embodiment can further combine material property information to select the target process program. This embodiment automatically analyzes the geometric complexity of the shell's 3D model to characterize the printing difficulty, and then adaptively selects a process program for printing, improving the printing effect of the encapsulated shell.

[0051] For example, a suitable additive manufacturing process is determined based on the sensor packaging structure design and material selection. For packaging structures made of thermoplastics such as PLA and ABS, the FDM process can be used. FDM equipment is relatively inexpensive and easy to operate, making it suitable for manufacturing sensor packaging shells with less complex structures and larger dimensions (i.e., lower geometric complexity). For sensor packaging structures with high precision and complex internal structures (i.e., higher geometric complexity), the SLA process can be used. The SLA process utilizes photosensitive resin cured under ultraviolet light, achieving high precision and surface finish. For example, the spot diameter of an SLA printer can reach tens of micrometers, enabling the printing of very fine structures. During the printing process, printing parameters are strictly controlled, and quality checks are performed. When generating the printing path file using 3D model slicing software, parameters such as the filling method and support structure are set appropriately.

[0052] According to some embodiments of this application, the method for manufacturing the FBG sensor package housing of this application may also include, but is not limited to, the following steps: Step S701: Acquire a surface image of the package housing; Step S702: Perform defect detection on the package shell based on the surface image to obtain the detection result of the package shell.

[0053] In this embodiment, after printing, a surface image of the encapsulation shell is captured by a camera. This image is then input into a defect detection model for defect detection, yielding a result indicating whether the encapsulation shell has defects. The defect detection model can be trained using a convolutional neural network model. Its principle is to extract and classify features from the image to determine whether a defect exists. Furthermore, this embodiment can also use tools such as a 3D scanner to measure whether the encapsulation shell meets the design dimensional requirements, improving the quality of the manufactured sensor encapsulation structure.

[0054] According to some embodiments of this application, the overall process of FBG sensor packaging is as follows: the selected FBG sensor is installed and fixed within the additively manufactured packaging housing according to design requirements. For strain sensors, a special adhesive (such as epoxy resin, which has good bonding and aging resistance) is used to bond the FBG sensor to the strain-sensitive part inside the packaging structure, ensuring tight coupling between the sensor and the structure, and enabling accurate sensing of strain changes in the structure. During bonding, the amount of adhesive is controlled to avoid excessive adhesive affecting sensor performance, while ensuring accurate bonding position. For temperature sensors, the temperature sensor is placed in a specially designed temperature-sensitive area within the packaging housing. This area should have good thermal conductivity and be unaffected by other factors.

[0055] Furthermore, after the sensor is packaged, a high-precision FBG demodulator can be used to conduct systematic performance testing, and calibration work can be completed simultaneously to ensure that key indicators meet the specifications. Key indicator calibration includes, but is not limited to, a full-range scan of intrinsic parameters such as the sensor's center wavelength, reflectivity, and bandwidth, and comparing data before and after packaging to evaluate the stability of optical performance. By applying standard loads (strain / temperature), metrological indicators such as linearity, hysteresis rate, and repeatability error are calibrated to ensure compliance with national specifications.

[0056] Please refer to Figure 2 This application also proposes an FBG sensor packaging housing manufacturing system, comprising: The scanning module is used to scan the surface structure of the target to obtain first three-dimensional data, and to acquire second three-dimensional data of the target FBG sensor surface; The model building module is used to determine the three-dimensional model of the encapsulation shell based on the first three-dimensional data and the second three-dimensional data. The printing module is used to print the three-dimensional model of the housing using additive manufacturing technology to obtain the encapsulation housing of the target FBG sensor.

[0057] It is understood that the methods described in the above method embodiments are applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0058] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described above. This electronic device can be any smart terminal, including tablet computers and computers.

[0059] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0060] Please see Figure 3 , Figure 3 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 902 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901. The input / output interface 903 is used to implement information input and output; The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 905 transmits information between various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904); The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0061] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0062] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0063] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0064] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0065] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0066] The FBG sensor packaging housing manufacturing method and related equipment provided in this application have at least one of the following beneficial effects: (1) High design flexibility: Additive manufacturing technology can quickly produce sensor components with various complex shapes and structures according to specific needs, and is highly customizable. For example, unique structures can be designed to suit different measurement scenarios and objects, such as a fitted sensor structure for a specific curved surface, or a complex three-dimensional structure with a special optical path arrangement, to achieve more accurate measurement and better performance. FBG sensors themselves also have the characteristics of small size and easy integration. The combination of the two can give full play to their respective advantages in design and create sensor systems that meet diverse needs.

[0067] (2) High sensitivity: Additive manufacturing technology can precisely control the packaging structure and surrounding medium of the FBG sensor, optimize the sensor's response characteristics to the measured physical quantity, and thus improve sensitivity. For example, by designing a specific stress transmission structure, the measured stress can be more effectively transmitted to the FBG, causing a more obvious wavelength change, thereby achieving accurate measurement of minute changes in physical quantities.

[0068] (3) Good compatibility: Additive manufacturing technology can select a variety of materials for manufacturing, and can choose compatible materials according to the working environment and performance requirements of the FBG sensor. For example, for FBG sensors that need to work in high-temperature environments, high-temperature resistant ceramic or metal materials can be selected for additive manufacturing packaging; for sensors that need to be used in corrosive environments, corrosion-resistant polymer materials can be selected. This can ensure that the FBG and the additively manufactured structure maintain stable performance in long-term use, and will not affect the accuracy and lifespan of the sensor due to the interaction between materials.

[0069] (4) Achieving Integration and Miniaturization: Additive manufacturing can integrate FBG sensors with other functional components into a single structure, achieving a high degree of integration. Simultaneously, because additive manufacturing can precisely control the size and shape of the structure, it can produce miniaturized sensor systems, reducing the impact on the measured object. This is particularly suitable for applications with stringent space requirements, such as aerospace and micromechanical fields. For example, multiple FBG sensors can be integrated into a tiny structure to simultaneously measure multiple physical quantities or the same physical quantity at different locations without occupying excessive space.

[0070] (5) Improved production efficiency and reduced costs: Additive manufacturing technology eliminates the need for complex molds and multiple processing steps, enabling the rapid and direct production of the required sensor structure, significantly shortening the production cycle and improving production efficiency. For small-batch, customized FBG sensor products, additive manufacturing can avoid the high costs associated with mold manufacturing and other traditional manufacturing methods, thus reducing production costs. Moreover, additive manufacturing has a high material utilization rate, reducing material waste and further lowering costs.

[0071] (6) Enhanced structural performance: Additive manufacturing technology can reduce the weight of sensors without affecting their performance by optimizing structural design, such as using lightweight structures like honeycomb or truss structures, while simultaneously improving their structural strength and stability. In some sensors that require long-term outdoor use, enhanced structural performance can better withstand the effects of harsh environments and ensure the normal operation of the sensors.

[0072] (7) In-situ manufacturing and real-time monitoring: In the manufacturing or repair of some large structures, additive manufacturing technology can be used to integrate FBG sensors in-situ into the structure to achieve real-time monitoring of the structure during the manufacturing process, such as monitoring stress and strain changes inside the structure. This allows for timely detection of problems that occur during the manufacturing process, enabling corresponding measures to be taken for adjustment and improvement, thereby enhancing the quality and reliability of the structure.

[0073] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0074] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0075] The system embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0076] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0077] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0078] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0079] The modules described above as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0080] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0081] If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0082] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method of manufacturing an FBG sensor package housing, characterized by, Includes the following steps: The surface structure of the target under test is scanned to obtain the first three-dimensional data, and the second three-dimensional data of the target FBG sensor surface is acquired. Based on the first three-dimensional data and the second three-dimensional data, determine the three-dimensional model of the packaging shell; The three-dimensional model of the housing is printed using additive manufacturing technology to obtain the encapsulation housing of the target FBG sensor; The step of determining the three-dimensional model of the packaging shell based on the first three-dimensional data and the second three-dimensional data includes the following steps: The first three-dimensional data is reverse-processed to obtain the third three-dimensional data; and the second three-dimensional data is reverse-processed to obtain the fourth three-dimensional data. In response to the first selection command, select the target base model from the base model library; The third three-dimensional data is written into the outer surface mounting area of ​​the target base model, and the fourth three-dimensional data is written into the inner surface mounting area of ​​the target base model to obtain the shell three-dimensional model; The step of determining the three-dimensional model of the packaging shell based on the first three-dimensional data and the second three-dimensional data further includes the following steps: In response to the second selection command, target microstructure 3D data is selected from the surface microstructure library; the outer surface of the shell 3D model is optimized based on the target microstructure 3D data to obtain the optimized shell 3D model; Alternatively, in response to an operation command on the inner surface of the three-dimensional model of the housing, the installation area of ​​the temperature sensor is determined; and the printing material properties of the three-dimensional data of the corresponding installation area in the three-dimensional model of the housing are determined to be a preset heat-conducting material. Alternatively, in response to a guide channel configuration command, a guide channel model is constructed; the guide channel configuration command includes a guide channel height and a guide channel width; the orientation of the guide channel model is adjusted according to the desired installation direction, and the three-dimensional model of the housing is adjusted according to the guide channel model after the orientation adjustment.

2. The method according to claim 1, characterized in that, The process of printing the three-dimensional model of the housing using additive manufacturing technology to obtain the packaging housing of the target FBG sensor includes the following steps: A geometric analysis is performed on the three-dimensional model of the shell to determine its geometric complexity. Select the target process program from the process program library based on the geometric complexity; The 3D printer is controlled according to the target process procedure to print the three-dimensional model of the shell, thereby obtaining the encapsulated shell.

3. The method according to any one of claims 1 to 2, characterized in that, The FBG sensor packaging housing manufacturing method further includes the following steps: Take images of the surface of the packaging shell; The packaging shell is subjected to defect detection based on the surface image to obtain the detection result of the packaging shell.

4. A manufacturing system for an FBG sensor packaging housing, characterized in that, include: The scanning module is used to scan the surface structure of the target to obtain first three-dimensional data, and to acquire second three-dimensional data of the target FBG sensor surface; The model building module is used to determine the three-dimensional model of the encapsulation shell based on the first three-dimensional data and the second three-dimensional data; The printing module is used to print the three-dimensional model of the housing using additive manufacturing technology to obtain the encapsulation housing of the target FBG sensor; The model building module is specifically used to perform the following steps: The first three-dimensional data is reverse-processed to obtain the third three-dimensional data; and the second three-dimensional data is reverse-processed to obtain the fourth three-dimensional data. In response to the first selection command, select the target base model from the base model library; The third three-dimensional data is written into the outer surface mounting area of ​​the target base model, and the fourth three-dimensional data is written into the inner surface mounting area of ​​the target base model to obtain the shell three-dimensional model. The model building module is also specifically used to perform the following steps: In response to the second selection command, target microstructure 3D data is selected from the surface microstructure library; the outer surface of the shell 3D model is optimized based on the target microstructure 3D data to obtain the optimized shell 3D model; Alternatively, in response to an operation command on the inner surface of the three-dimensional model of the housing, the mounting area of ​​the temperature sensor is determined; The printing material properties of the three-dimensional data of the corresponding installation area in the three-dimensional model of the shell are determined to be a preset heat-conducting material; Alternatively, in response to a guide channel configuration command, a guide channel model is constructed; the guide channel configuration command includes a guide channel height and a guide channel width; the orientation of the guide channel model is adjusted according to the desired installation direction, and the three-dimensional model of the housing is adjusted according to the guide channel model after the orientation adjustment.

5. An electronic device, comprising: The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 3.

6. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 3.

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