A fiber ring temperature point prediction method and device based on a temperature field fitting model

Abstract

The application discloses a kind of temperature point prediction method and device of optical fiber ring based on temperature field fitting model, it is related to inertial navigation optical fiber gyroscope technical field, the method combines heat diffusion delay response temperature model with the temperature model of the inside multiple point position of optical fiber ring, the temperature data of the inside certain point of optical fiber ring is predicted using external temperature, and the temperature data of each point in the inside of optical fiber ring is further predicted by the point prediction temperature data.The application in this application can accurately obtain the temperature data of different point positions on the optical fiber ring only with external temperature data, so that the temperature field distribution in the inside of optical fiber ring is more clearly reflected, a large amount of temperature data is provided for subsequent optical fiber gyroscope temperature compensation, so as to better improve compensation accuracy, solve the problem of the number of temperature sensor positions and quantity arranged on hardware.

Description

Technical Field

[0001] The present application relates to the technical field of inertial navigation fiber optic gyroscopes, and in particular to a method and device for predicting the temperature points of an optical fiber ring based on a temperature field fitting model. Background Art

[0002] Fiber-optic gyroscopes (FOGs) are high-precision angular velocity sensors. Due to their solid-state structure, digital output, and fast response speed, they are widely used in fields such as navigation, aviation, and aerospace. As FOG applications expand and operating environments become more diverse, the requirements for their adaptability and output accuracy are also increasing.

[0003] The primary source of error in a fiber optic gyroscope (FOG) is temperature fluctuations within the fiber optic ring. When the ambient temperature of the FOG's operating environment changes, the temperature changes vary at various points within the ring, and the temperature gradients at each point become inconsistent. Traditional temperature compensation typically uses temperature data from a single-point temperature sensor within the FOG, using that single point temperature to represent the temperature of the entire fiber optic ring for compensation. This results in compensation bias in existing temperature gradient-based compensation algorithms, limiting further improvements in the full-temperature stability of high-precision FOGs. Adding a temperature sensor to the fiber optic ring not only increases cost and hardware complexity, but also the heat generated by the temperature sensor itself affects the temperature field within the ring. Therefore, obtaining temperature data at each point within the ring becomes a challenge. Summary of the Invention

[0004] The purpose of this application is to provide a method and device for predicting the temperature points of an optical fiber ring based on a temperature field fitting model, which only requires external temperature data to accurately obtain the temperature data of different points on the optical fiber ring.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a method for predicting the temperature point of an optical fiber ring based on a temperature field fitting model, comprising:

[0007] Obtain the ambient temperature of the environment where the fiber optic gyroscope is located;

[0008] Determining the predicted temperature of a target point inside the fiber optic ring of the fiber optic gyroscope by applying a thermal diffusion delay response temperature model based on the ambient temperature; the thermal diffusion delay response temperature model is a relationship model between the ambient temperature and the temperature of the target point inside the fiber optic ring;

[0009] According to the predicted temperature of the target point inside the optical fiber ring, a multi-point temperature prediction model inside the optical fiber ring is applied to determine the predicted temperatures of multiple non-target points inside the optical fiber ring; the non-target points and the target points are distributed along the axial direction of the optical fiber ring; the multi-point temperature prediction model inside the optical fiber ring is a relationship model between the temperature of the target point and the temperatures of each non-target point; the temperature field fitting model includes the thermal diffusion delayed response temperature model and the multi-point temperature prediction model inside the optical fiber ring.

[0010] In a second aspect, the present application provides a device for predicting optical fiber ring temperature points based on a temperature field fitting model, comprising:

[0011] An ambient temperature acquisition module is used to obtain the ambient temperature of the environment in which the fiber optic gyroscope is located;

[0012] a target point temperature prediction module, configured to determine a predicted temperature of a target point inside the optical fiber ring of the optical fiber gyroscope based on the ambient temperature and applying a thermal diffusion delayed response temperature model; the thermal diffusion delayed response temperature model is a relationship model between the ambient temperature and the temperature of the target point inside the optical fiber ring;

[0013] The non-target point temperature prediction module is used to determine the predicted temperatures of multiple non-target points inside the optical fiber ring based on the predicted temperature of the target point inside the optical fiber ring and applying the multi-point temperature prediction model inside the optical fiber ring; the non-target points and the target points are distributed along the axial direction of the optical fiber ring; the multi-point temperature prediction model inside the optical fiber ring is a relationship model between the temperature of the target point and the temperatures of each non-target point; and the temperature field fitting model includes the thermal diffusion delayed response temperature model and the multi-point temperature prediction model inside the optical fiber ring.

[0014] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned method for predicting the temperature point of an optical fiber ring based on a temperature field fitting model.

[0015] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for predicting the temperature point of an optical fiber ring based on a temperature field fitting model.

[0016] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above-mentioned method for predicting the temperature point of an optical fiber ring based on a temperature field fitting model.

[0017] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0018] The application provides a fiber ring temperature point prediction method and device based on a temperature field fitting model, which combines a thermal diffusion delay response temperature model and a temperature model of multiple points in a fiber ring (a fiber ring internal multiple point temperature prediction model), predicts temperature data of a certain point in the fiber ring by using external temperature, and further predicts temperature data of other points in the fiber ring by using the predicted temperature data of the point. In the application, only external temperature data is needed to accurately obtain temperature data of different points on the fiber ring, so that the temperature field distribution in the fiber ring is more clearly reflected, a large amount of temperature data is provided for subsequent fiber gyroscope temperature compensation, so that the compensation accuracy can be better improved, and the problem of arranging the position and number of temperature sensors on hardware is solved. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments will be briefly introduced. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of these drawings.

[0020] Figure 1 An application environment diagram of a fiber ring temperature point prediction method based on a temperature field fitting model according to an embodiment of the present application;

[0021] Figure 2 A flowchart of a fiber ring temperature point prediction method based on a temperature field fitting model according to an embodiment of the present application;

[0022] Figure 3 A fiber gyroscope whole machine modeling diagram provided by an embodiment of the present application;

[0023] Figure 4 A temperature curve diagram under a 0.5℃ / min temperature change rate provided by an embodiment of the present application;

[0024] Figure 5 A temperature distribution diagram at a certain moment provided by an embodiment of the present application;

[0025] Figure 6 A temperature curve diagram of each point under a 0.5℃ / min temperature change rate provided by an embodiment of the present application;

[0026] Figure 7 A comparison diagram of initial model temperature prediction and actual simulation temperature under a 0.5℃ / min temperature change rate provided by an embodiment of the present application;

[0027] Figure 8 A comparison diagram of initial model temperature prediction and actual simulation temperature under a 1℃ / min temperature change rate provided by an embodiment of the present application;

[0028] Figure 9 A comparison chart of the improved model temperature prediction and the actual simulated temperature at a temperature ramp rate of 0.5°C / min provided in one embodiment of the present application;

[0029] Figure 10 A comparison chart of the improved model temperature prediction and the actual simulated temperature at a temperature change rate of 1°C / min provided in one embodiment of the present application;

[0030] Figure 11 A schematic diagram of the functional modules of a fiber ring temperature point prediction device based on a temperature field fitting model provided in one embodiment of the present application.

[0031] Figure 12 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0033] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0034] The fiber ring temperature point prediction method based on the temperature field fitting model provided in the embodiment of the present application can be applied to Figure 1The application environment is shown. Among them, the terminal communicates with the server through the network. The data storage system can store the data required by the server to process. The data storage system can be separately arranged, integrated on the server, or placed on the cloud or other servers. The terminal can send an optical fiber ring temperature point prediction request to the server. After the server receives the optical fiber ring temperature point prediction request, the server obtains the environment temperature of the environment where the optical fiber gyroscope is located; according to the environment temperature, a thermal diffusion delay response temperature model is applied to determine the predicted temperature of a target point inside the optical fiber ring of the optical fiber gyroscope; the thermal diffusion delay response temperature model is a relationship model between the environment temperature and the temperature of the target point inside the optical fiber ring; according to the predicted temperature of the target point inside the optical fiber ring, a multi-point temperature prediction model of the optical fiber ring is applied to determine the predicted temperature of multiple non-target points inside the optical fiber ring; the non-target points and the target points are distributed along the axial direction of the optical fiber ring; the multi-point temperature prediction model of the optical fiber ring is a relationship model between the temperature of the target point and the temperature of each non-target point; and the temperature field fitting model includes the thermal diffusion delay response temperature model and the multi-point temperature prediction model of the optical fiber ring. The server can feed back the predicted temperature of each point inside the optical fiber ring to the terminal. In addition, in some embodiments, the optical fiber ring temperature point prediction method based on the temperature field fitting model can also be implemented by the server or the terminal alone, such as the terminal directly performing optical fiber ring temperature point prediction based on the temperature field fitting model for the optical fiber ring temperature point prediction request, or the server obtaining the environment temperature of the environment where the optical fiber gyroscope is located from the data storage system, and performing optical fiber ring temperature point prediction based on the temperature field fitting model for the environment temperature of the environment where the optical fiber gyroscope is located based on the optical fiber ring temperature point prediction request.

[0035] Among them, the terminal can be but not limited to various desktop computers, notebook computers, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The server can be implemented by an independent server or a server cluster composed of multiple servers, and can also be a cloud server.

[0036] In an exemplary embodiment, as Figure 2 shown, a temperature field fitting model-based optical fiber ring temperature point prediction method is provided, which is executed by a computer device, specifically by a terminal or a server, or by a terminal and a server together. In the embodiments of the present application, the method is applied to the server in Figure 1 the application environment, which includes the following steps 101 to 103. Among them:

[0037] Step 101, obtaining the environment temperature of the environment where the optical fiber gyroscope is located.

[0038] Step 102: Determine the predicted temperature of a target point inside the fiber ring of the fiber optic gyroscope by applying a thermal diffusion delay response temperature model based on the ambient temperature; the thermal diffusion delay response temperature model is a relationship model between the ambient temperature and the temperature of the target point inside the fiber ring.

[0039] Step 103: Based on the predicted temperature of the target point inside the optical fiber ring, a multi-point temperature prediction model inside the optical fiber ring is applied to determine the predicted temperatures of multiple non-target points inside the optical fiber ring; the non-target points and the target point are distributed along the axial direction of the optical fiber ring; the multi-point temperature prediction model inside the optical fiber ring is a relationship model between the temperature of the target point and the temperatures of each non-target point; and the temperature field fitting model includes the thermal diffusion delayed response temperature model and the multi-point temperature prediction model inside the optical fiber ring.

[0040] By implementing the above steps 101 to 103, by combining the thermal diffusion delay response temperature model with the temperature models of multiple points inside the fiber ring, the temperature data of one point inside the fiber ring is predicted by the external temperature, and the temperature data of multiple points inside the fiber ring are then predicted by using this data. This more clearly reflects the temperature field distribution inside the fiber ring, providing a large amount of temperature data for subsequent fiber optic gyroscope temperature compensation, so as to better improve the compensation accuracy.

[0041] In another exemplary embodiment of the present application, in step 102, the fiber optic gyroscope is first modeled as a whole. After measuring the actual size data of the fiber optic gyroscope, the fiber optic gyroscope is 3D modeled as a whole using SolidWorks, and then the temperature field data is obtained by ANSYS finite element simulation. Since the present application is only concerned with the temperature field distribution of the fiber ring, the modeling of the internal heat source only needs to be replaced by a uniform heating material with the same geometric size. Figure 3 As shown, Figure 3 (a) is the bottom of the fiber optic gyroscope, which includes the fiber ring, fiber ring skeleton, Y waveguide and coupler. Figure 3 (b) is the upper part of the fiber optic gyroscope, which includes components such as a circuit board and a light source. When performing finite element analysis, the complexity of the fiber optic gyroscope simulation model determines the speed of the solution. Since the simulation purpose is mainly to observe the temperature field on the fiber ring, in order to save computing resources, reasonable simplification of the fiber optic gyroscope as a whole is beneficial to improving the efficiency of the calculation. Unnecessary chamfers, grooves, holes, etc. inside the fiber optic gyroscope are simplified, and some components such as the internal Y-waveguide and coupler are ignored. Only the fiber optic gyroscope shell, fiber ring, circuit board, and light source are retained. During the finite element simulation, the boundary condition temperature load is applied to the top, bottom, and outside of the fiber optic gyroscope at the same time. The natural convection heat transfer coefficient and heating power are set before the simulation is performed.

[0042] To find the delayed response time τ in the thermal diffusion delayed response temperature modelt and model parameters, respectively, the thermal load with different temperature change rates is applied to the outer surface of the fiber optic gyroscope, and the data of the center node of the gyroscope shell is recorded as the environmental temperature T o , and the data of a node (target point) inside the fiber coil is recorded as the temperature data T s detected by the temperature sensor. The temperature curves of the two at a temperature change rate of 0.5 ℃ / min are shown in Figure 4 . After adding the delay response time τ t , the thermal diffusion delay response temperature model is established by T o and . The thermal diffusion delay response temperature model is established as follows:

[0043]

[0044] The accurate delay response time τ t and model parameters (a, b, c, d, e, f) are obtained through experimental data of different temperature change rates. In order to ensure the accuracy of the model parameters, the accuracy of the model parameters can be verified again by using new experimental data. is the first derivative of the environmental temperature T o .

[0045] Based on the above, the expression of the thermal diffusion delay response temperature model is as follows:

[0046]

[0047] In the formula, T s is the predicted temperature of the target point inside the fiber coil; T o is the environmental temperature; is the first derivative of the environmental temperature T o ; τ t is the delay response time; a, b, c, d, e, and f are model parameters.

[0048] Based on the above, in step 102, according to the environmental temperature, the thermal diffusion delay response temperature model is applied to determine the predicted temperature of a target point inside the fiber coil of the fiber optic gyroscope, specifically including:

[0049] (a1) establishing a three-dimensional simulation model of the fiber optic gyroscope.

[0050] (a2) applying thermal loads with different temperature change rates to the three-dimensional simulation model for temperature field simulation, recording the simulation temperatures of the center node temperature of the gyroscope shell and the multiple points along the axial distribution inside the fiber coil of the three-dimensional simulation model when applying thermal loads with each temperature change rate; the center node temperature of the gyroscope shell in the three-dimensional simulation model is regarded as the environmental simulation temperature.

[0051] (a3) fitting data based on the simulated ambient temperature at different temperature change rates and the simulated temperature of a target point inside the fiber ring to derive a thermal diffusion delay response temperature model; the target point is any one of a plurality of points distributed along the axial direction inside the fiber ring.

[0052] (a4) Determining a predicted temperature of a target point inside the optical fiber ring of the optical fiber gyroscope by applying a thermal diffusion delayed response temperature model according to the ambient temperature.

[0053] In order to obtain more temperature data on the fiber optic ring, a temperature model of multiple points inside the fiber optic ring (multi-point temperature prediction model inside the fiber optic ring) is established. The selection of internal points needs to be determined according to the temperature gradient on the fiber optic ring. The temperature distribution at a certain moment in the temperature change process is selected. Figure 5 As shown. During the heat transfer process, the temperature change on the fiber optic ring mainly comes from the contact heat conduction between the fiber optic ring and the bottom of the fiber optic gyroscope. Since the air temperature around the fiber optic ring is basically the same, the fiber temperature at the inner wall and the outer wall of the fiber optic ring relative to the position is also basically the same, that is, the circumferential temperature distribution is relatively uniform, so the temperature field on the fiber optic ring is mainly distributed along the axial direction. In order to better reflect the temperature change, the selected points are all on the same axis. At the temperature change rate of 0.5℃ / min, the temperature data of four points are selected as follows Figure 6 shown.

[0054] Taking a temperature change rate of 0.5°C / min as an example, the simulated temperature data of point 1 (target point) and point 2 (which can be regarded as non-target point i) are extracted to train the initial model for temperature prediction of points in the fiber ring:

[0055]

[0056] Get a ia 、b ia 、c ia d ia 、e ia 、f ia Model parameters. T ia is the temperature at the non-target point i. Using this initial model, the predicted temperature of point 2 is obtained under the 0.5℃ / min temperature change rate simulation experiment. Figure 7 As shown in , the initial predicted temperature of point 2 is close to the actual simulated temperature of point 2. Under the initial model parameters, the simulated temperature data of point 1 under the 1℃ / min temperature change rate simulation experiment is used to predict the temperature data of point 2. Figure 8 As shown in the figure, at a temperature ramp rate of 1°C / min, a large deviation occurs between the predicted and simulated temperatures at point 2. To obtain a universal temperature point prediction model, the single polynomial fitting model (the initial model mentioned above) is improved by taking into account the error between the initial model's prediction results and the actual simulated values:

[0057] e ic =T i -T ia ;

[0058] Among them, T i is the predicted temperature of the non-target point i based on the above initial model.

[0059] When the model order is higher, the fitting effect of single data is better. However, in order to obtain a more general model, the first-order temperature and temperature change rate are selected, and then the two and the error e are added. ic The improved temperature point prediction model (multi-point temperature prediction model in the optical fiber ring) is obtained by coupling the terms of

[0060]

[0061] Among them, T ic is the predicted temperature at the non-target point i in the fiber ring; T s is the predicted temperature of the target point inside the fiber ring; T s The first derivative of ic is the temperature error term at the non-target point i in the fiber ring; a ic 、b ic 、c ic d ic are model parameters.

[0062] Similarly, in the 0.5℃ / min temperature change rate simulation experiment, the temperature data of point 1 (target point) and point 2 (which can be regarded as non-target point i) are used to train the multi-point temperature prediction model in the optical fiber ring, as shown in Figure 2. Figure 9 As shown, for point 2, the prediction effect of this model is almost the same as that of the initial model. Based on the training parameters (a ic 、b ic 、c ic d ic ), using the simulated temperature data of point 1 under the 1℃ / min temperature change rate simulation experiment, the temperature of point 2 is predicted, such as Figure 10 As shown, the predicted temperature at point 2 is Figure 8 It can better match the actual simulation temperature of point 2.

[0063] The above description uses point 2 as an example to illustrate the process of determining the temperature prediction model for the point within the fiber loop corresponding to point 2. For other points, simply replace the data for point 2 with the data for the corresponding points (e.g., points 3, 4, etc.). Ultimately, a temperature prediction model for each non-target point within the fiber loop can be obtained. In other words, using the temperature of a known target point (e.g., point 1) on the fiber loop, the temperature data for multiple other points can be derived.

[0064] Based on the above, the expression of the multi-point temperature prediction model in the fiber ring is:

[0065]

[0066] In the formula, T ic is the predicted temperature of the non-target point i in the fiber ring; T s is the predicted temperature of the target point on the inner side of the fiber ring; is the first derivative of T s ; e ic is the temperature error term of the non-target point i in the fiber ring; a ic , b ic , c ic , and d ic are model parameters.

[0067] Based on the above, in step 103, according to the predicted temperature of the target point on the inner side of the fiber ring, the multi-point temperature prediction model in the fiber ring is applied to determine the predicted temperature of the multiple non-target points on the inner side of the fiber ring, specifically including:

[0068] (b1) According to the simulated temperatures recorded under the thermal load of different temperature change rates of each non-target point and the target point on the inner side of the fiber ring, data fitting is performed to obtain the respective corresponding fiber ring point temperature prediction initial model of each non-target point; the fiber ring point temperature prediction initial model is an initial relationship model between the temperature of the target point and the temperature of any non-target point.

[0069] (b2) The simulated temperature recorded under the thermal load of any temperature change rate of each non-target point on the inner side of the fiber ring is brought into the corresponding fiber ring point temperature prediction initial model to obtain the initial model predicted temperature of each non-target point.

[0070] (b3) The error value between the initial model predicted temperature of each non-target point and the recorded simulated temperature is calculated.

[0071] (b4) According to the simulated temperatures recorded under the thermal load of different temperature change rates of each non-target point and the target point on the inner side of the fiber ring and the error value, data fitting is performed to obtain the multi-point temperature prediction model in the fiber ring; the multi-point temperature prediction model in the fiber ring includes the fiber ring point temperature prediction model corresponding to each non-target point.

[0072] (b5) The predicted temperature of the target point on the inner side of the fiber ring is respectively substituted into the fiber ring point temperature prediction model corresponding to each non-target point to obtain the predicted temperature of each non-target point in the fiber ring.

[0073] In this embodiment, the temperature change on the fiber ring is considered to have a delay time in response to the change of the outside temperature in the process of heat transfer of the fiber optic gyroscope. A heat diffusion delay response temperature model is established by adding the delay response time according to the outside temperature and the temperature change rate, and the temperature data of a point inside the fiber ring can be obtained through the outside temperature data. A multi-point temperature model inside the fiber ring is established through the temperature data of a point inside the fiber ring, and different point positions have different model parameters, that is, different fiber ring point temperature prediction models. After adding the error term, even if the temperature change rate is changed, the temperature of different point positions can be accurately predicted through the temperature data of a point inside. The heat diffusion delay response temperature model and the multi-point temperature prediction model inside the fiber ring are combined, and the temperature data of different point positions on the fiber ring can be obtained only by using the outside temperature data, which provides a large amount of data for temperature compensation of the fiber optic gyroscope and solves the problem of the number and position of temperature sensors arranged on the hardware.

[0074] The application also provides an application scenario of the above-mentioned fiber ring temperature point prediction method based on a temperature field fitting model. Specifically, the fiber ring temperature point prediction method based on a temperature field fitting model provided in this embodiment can be applied in a fiber optic gyroscope temperature compensation scenario. The scenario includes a temperature field fitting link and a temperature compensation link. The temperature field fitting link is used to derive the temperature data of the temperature sensor position inside the fiber optic gyroscope by using the outside environment temperature and the temperature and temperature change rate after adding the delay response time, and then obtain the temperature data of other multiple point positions inside the fiber optic gyroscope by using the temperature data of the temperature sensor position, so as to facilitate subsequent temperature compensation work. The temperature compensation link is used to perform temperature compensation according to the fitted temperature field inside the fiber ring. The fiber ring temperature point prediction method based on a temperature field fitting model provided in this embodiment belongs to the temperature field fitting link.

[0075] Based on the same inventive concept, the application embodiment also provides a fiber ring temperature point prediction device based on a temperature field fitting model for implementing the above-mentioned fiber ring temperature point prediction method based on a temperature field fitting model. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above-mentioned method, and therefore the specific limitations in one or more fiber ring temperature point prediction device embodiments based on a temperature field fitting model provided below can be referred to the limitations of the fiber ring temperature point prediction method based on a temperature field fitting model in the above text, which will not be described here again.

[0076] In one exemplary embodiment, as shown in Figure 11 a fiber ring temperature point prediction device based on a temperature field fitting model is provided, which includes:

[0077] An environment temperature acquisition module M1 is configured to acquire an environment temperature of an environment in which the fiber optic gyroscope is located.

[0078] The target point temperature prediction module M2 is used to determine the predicted temperature of a target point inside the optical fiber ring of the optical fiber gyroscope based on the ambient temperature and applying a thermal diffusion delayed response temperature model; the thermal diffusion delayed response temperature model is a relationship model between the ambient temperature and the temperature of the target point inside the optical fiber ring.

[0079] The non-target point temperature prediction module M3 is used to determine the predicted temperatures of multiple non-target points inside the optical fiber ring based on the predicted temperature of the target point inside the optical fiber ring and applying the multi-point temperature prediction model inside the optical fiber ring; the non-target points and the target points are distributed along the axial direction of the optical fiber ring; the multi-point temperature prediction model inside the optical fiber ring is a relationship model between the temperature of the target point and the temperatures of each non-target point; the temperature field fitting model includes the thermal diffusion delayed response temperature model and the multi-point temperature prediction model inside the optical fiber ring.

[0080] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 12 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store temperature prediction data at various points in the optical fiber ring. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for predicting optical fiber ring temperature points based on a temperature field fitting model is implemented.

[0081] Those skilled in the art will understand that Figure 12 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present application and does not constitute a limitation on the computer device to which the solution of the present application is applied. A specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement. In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps of the above-mentioned method embodiments when executing the computer program.

[0082] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0083] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0084] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0085] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0086] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0087] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0088] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for predicting optical fiber ring temperature points based on a temperature field fitting model, characterized in that: The optical fiber ring temperature point prediction method based on the temperature field fitting model includes: Obtaining the ambient temperature of the environment in which the fiber optic gyroscope is located; Determining the predicted temperature of a target point inside the fiber optic ring of the fiber optic gyroscope by applying a thermal diffusion delay response temperature model based on the ambient temperature; the thermal diffusion delay response temperature model is a relationship model between the ambient temperature and the temperature of the target point inside the fiber optic ring; Based on the predicted temperature of the target point inside the optical fiber ring, a multi-point temperature prediction model inside the optical fiber ring is applied to determine the predicted temperatures of multiple non-target points inside the optical fiber ring; the non-target points and the target point are distributed along the axial direction of the optical fiber ring; the multi-point temperature prediction model inside the optical fiber ring is a relationship model between the temperature of the target point and the temperatures of each non-target point; the temperature field fitting model includes the thermal diffusion delayed response temperature model and the multi-point temperature prediction model inside the optical fiber ring; Wherein, according to the ambient temperature, applying a thermal diffusion delayed response temperature model to determine the predicted temperature of a target point inside the optical fiber ring of the optical fiber gyroscope specifically includes: Establish a three-dimensional simulation model of fiber optic gyroscope; Applying heat loads with different temperature change rates to the three-dimensional simulation model to perform temperature field simulation, and recording the simulated temperatures of the center node of the fiber optic gyroscope housing and multiple points distributed axially inside the optical fiber ring in the three-dimensional simulation model when applying the heat load at each temperature change rate; the center node temperature of the fiber optic gyroscope housing in the three-dimensional simulation model is regarded as the ambient simulation temperature; A thermal diffusion delay response temperature model is derived by performing data fitting based on the simulated ambient temperature at different temperature change rates and the simulated temperature of a target point inside the optical fiber ring; the target point is any one of multiple points distributed along the axial direction inside the optical fiber ring; According to the ambient temperature, a thermal diffusion delayed response temperature model is applied to determine a predicted temperature of a target point inside the optical fiber ring of the optical fiber gyroscope.

2. The optical fiber ring temperature point prediction method based on the temperature field fitting model according to claim 1 is characterized in that: The expression of the thermal diffusion delay response temperature model is: ； Where, is the predicted temperature of the target point inside the fiber ring; is the ambient temperature; is the ambient temperature The first derivative of Delayed response time ；a 、 b 、c、 d 、 e 、 f are model parameters.

3. The optical fiber ring temperature point prediction method based on the temperature field fitting model according to claim 1 is characterized in that: The expression of the multi-point temperature prediction model in the optical fiber ring is: ； Where, Non-target point in the fiber ring i The predicted temperature at is the predicted temperature of the target point inside the fiber ring; for The first derivative of Non-target point in the fiber ring i The temperature error term at ; 、 、 、 are model parameters.

4. The method for predicting optical fiber ring temperature points based on a temperature field fitting model according to claim 1, wherein: According to the predicted temperature of the target point inside the optical fiber ring, a multi-point temperature prediction model inside the optical fiber ring is applied to determine the predicted temperatures of multiple non-target points inside the optical fiber ring, specifically including: Data fitting is performed based on the simulated temperatures recorded at the target point and each non-target point inside the optical fiber ring under the application of thermal loads at different temperature change rates, thereby obtaining an initial model for predicting the temperature of the optical fiber ring corresponding to each non-target point; the initial model for predicting the temperature of the optical fiber ring is an initial relationship model between the temperature of the target point and the temperature of any non-target point; The simulated temperature recorded at each non-target point inside the fiber ring under the application of a heat load at any temperature change rate is brought into the corresponding initial model for predicting the temperature of the fiber ring inner point to obtain the initial model predicted temperature of each non-target point; Calculate the error between the initial model predicted temperature and the recorded simulated temperature at each non-target point; Data fitting is performed based on the simulated temperatures and error values ​​recorded at each non-target point and the target point inside the optical fiber ring under thermal loads at different temperature change rates, thereby obtaining a multi-point temperature prediction model inside the optical fiber ring; the multi-point temperature prediction model inside the optical fiber ring includes a temperature prediction model for the optical fiber ring point corresponding to each non-target point; The predicted temperature of the target point inside the optical fiber ring is substituted into the optical fiber ring inner point temperature prediction model corresponding to each non-target point to obtain the predicted temperature of each non-target point in the optical fiber ring.

5. The optical fiber ring temperature point prediction method based on the temperature field fitting model according to claim 4 is characterized in that: The expression of the initial model for predicting the temperature of the optical fiber ring is: ； Where, Non-target point i The temperature at is the temperature of the target point inside the fiber ring; for The first derivative of 、 、 、 、 、 are model parameters.

6. A device for predicting optical fiber ring temperature points based on a temperature field fitting model, characterized in that: The optical fiber ring temperature point prediction device based on the temperature field fitting model includes: An ambient temperature acquisition module is used to obtain the ambient temperature of the environment in which the fiber optic gyroscope is located; a target point temperature prediction module, configured to determine a predicted temperature of a target point inside the optical fiber ring of the optical fiber gyroscope based on the ambient temperature and applying a thermal diffusion delayed response temperature model; the thermal diffusion delayed response temperature model is a relationship model between the ambient temperature and the temperature of the target point inside the optical fiber ring; Wherein, according to the ambient temperature, applying a thermal diffusion delayed response temperature model to determine the predicted temperature of a target point inside the optical fiber ring of the optical fiber gyroscope specifically includes: Establish a three-dimensional simulation model of fiber optic gyroscope; Applying heat loads with different temperature change rates to the three-dimensional simulation model to perform temperature field simulation, and recording the simulated temperatures of the center node of the fiber optic gyroscope housing and multiple points distributed axially inside the optical fiber ring in the three-dimensional simulation model when applying the heat load at each temperature change rate; the center node temperature of the fiber optic gyroscope housing in the three-dimensional simulation model is regarded as the ambient simulation temperature; A thermal diffusion delay response temperature model is derived by performing data fitting based on the simulated ambient temperature at different temperature change rates and the simulated temperature of a target point inside the optical fiber ring; the target point is any one of multiple points distributed along the axial direction inside the optical fiber ring; Determining a predicted temperature of a target point inside the optical fiber ring of the optical fiber gyroscope by applying a thermal diffusion delayed response temperature model according to the ambient temperature; The non-target point temperature prediction module is used to determine the predicted temperatures of multiple non-target points inside the optical fiber ring based on the predicted temperature of the target point inside the optical fiber ring and applying the multi-point temperature prediction model inside the optical fiber ring; the non-target points and the target points are distributed along the axial direction of the optical fiber ring; the multi-point temperature prediction model inside the optical fiber ring is a relationship model between the temperature of the target point and the temperatures of each non-target point; and the temperature field fitting model includes the thermal diffusion delayed response temperature model and the multi-point temperature prediction model inside the optical fiber ring.

7. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the optical fiber ring temperature point prediction method based on the temperature field fitting model according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the optical fiber ring temperature point prediction method based on the temperature field fitting model according to any one of claims 1 to 5 is implemented.

9. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the optical fiber ring temperature point prediction method based on the temperature field fitting model according to any one of claims 1 to 5 is implemented.

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