Fiber loop temperature point prediction method and device based on temperature field fitting model

Abstract

The invention discloses an optical fiber ring temperature point prediction method and device based on a temperature field fitting model, and relates to the technical field of inertial navigation optical fiber gyroscopes. According to the method, a thermal diffusion delay response temperature model is combined with a temperature model of multiple point positions in an optical fiber ring, and temperature data of a certain point in the optical fiber ring is predicted through external temperature; and further predicting the temperature data of other points in the optical fiber ring through the predicted temperature data of the point. According to the method, the temperature data of different point positions on the optical fiber ring can be accurately obtained only through external temperature data, so that the distribution of the temperature field in the optical fiber ring is reflected more clearly, a large amount of temperature data is provided for subsequent temperature compensation of the optical fiber gyroscope, and the compensation precision can be better improved; the problems of the positions and the number of the temperature sensors arranged on hardware are solved.

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 gyroscope is a high-precision angular velocity sensor. Based on its solid-state structure, digital output, fast response speed and many other advantages, it has been widely used in the fields of navigation, aviation, aerospace, etc. As the application of fiber optic gyroscopes becomes more and more extensive and the working environment becomes more and more diverse, the requirements for the adaptability and output accuracy of fiber optic gyroscopes are also getting higher and higher.

[0003] The main source of error in the fiber optic gyroscope is the change in temperature on the fiber optic ring. When the temperature of the working environment of the fiber optic gyroscope changes, the temperature changes at various points inside the fiber optic ring are different, and the temperature gradients at various points are no longer consistent. The temperature data of traditional temperature compensation mostly comes from the single-point temperature of the temperature sensor inside the fiber optic gyroscope, and the temperature of one point is used to represent the temperature of the entire fiber optic ring and perform compensation. This will cause compensation deviations in the existing temperature gradient-based compensation algorithm, limiting the further improvement of the full-temperature stability of the high-precision fiber optic gyroscope. If a temperature sensor is added to the fiber optic ring, it will not only increase the cost and hardware complexity, but the heat generated by the temperature sensor itself will also affect the temperature field of the fiber optic ring. Therefore, how to obtain temperature data at various points inside the fiber optic ring becomes a difficult problem. Summary of the invention

[0004] The purpose of the present 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 temperature points 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] According to the ambient temperature, a thermal diffusion delayed 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 delayed response temperature model is a relationship model between the ambient temperature and the temperature of the target point inside the optical fiber ring;

[0009] According to the predicted temperature of the target point on the inner side of the optical fiber loop, apply the multi-point temperature prediction model in the optical fiber loop to determine the predicted temperatures of multiple non-target points on the inner side of the optical fiber loop; the non-target points and the target point are distributed along the axial direction of the optical fiber loop; the multi-point temperature prediction model in the optical fiber loop 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 delay response temperature model and the multi-point temperature prediction model in the optical fiber loop.

[0010] In a second aspect, the present application provides an optical fiber loop temperature point prediction device based on a temperature field fitting model, including:

[0011] An ambient temperature acquisition module, configured to acquire the ambient temperature of the environment where the optical fiber gyroscope is located;

[0012] A target point temperature prediction module, configured to determine the predicted temperature of a target point on the inner side of the optical fiber loop of the optical fiber gyroscope according to the ambient temperature by applying the thermal diffusion delay response temperature model; the thermal diffusion delay response temperature model is a relationship model between the ambient temperature and the temperature of the target point on the inner side of the optical fiber loop;

[0013] A non-target point temperature prediction module, configured to determine the predicted temperatures of multiple non-target points on the inner side of the optical fiber loop according to the predicted temperature of the target point on the inner side of the optical fiber loop by applying the multi-point temperature prediction model in the optical fiber loop; the non-target points and the target point are distributed along the axial direction of the optical fiber loop; the multi-point temperature prediction model in the optical fiber loop 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 delay response temperature model and the multi-point temperature prediction model in the optical fiber loop.

[0014] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the above-mentioned optical fiber loop temperature point prediction method based on a temperature field fitting model.

[0015] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the above-mentioned optical fiber loop temperature point prediction method based on a temperature field fitting model.

[0016] In a fifth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the above-mentioned optical fiber loop temperature point prediction method based on a temperature field fitting model.

[0017] According to the specific embodiments provided by the present application, the following technical effects are disclosed in the present application:

[0018] The present application provides a method and device for predicting the temperature points of an optical fiber ring based on a temperature field fitting model, which combines a thermal diffusion delayed response temperature model with a temperature model of multiple points inside an optical fiber ring (a temperature prediction model of multiple points inside an optical fiber ring), and uses the external temperature to predict the temperature data of a certain point inside the optical fiber ring, and then further predicts the temperature data of other points inside the optical fiber ring through the temperature data predicted at the point. In the present application, only the external temperature data is needed to accurately obtain the temperature data of different points on the optical fiber ring, thereby more clearly reflecting the temperature field distribution inside the optical fiber ring, providing a large amount of temperature data for subsequent optical fiber gyroscope temperature compensation, so as to better improve the compensation accuracy, and solve the problem of the location and number of temperature sensors arranged in hardware. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 This is an application environment diagram of a method for predicting temperature points of an optical fiber ring based on a temperature field fitting model in one embodiment of the present application;

[0021] Figure 2 A schematic flow chart of a method for predicting temperature points of an optical fiber ring based on a temperature field fitting model provided in one embodiment of the present application;

[0022] Figure 3 A diagram showing the modeling of a fiber optic gyroscope according to an embodiment of the present application;

[0023] Figure 4 A temperature curve diagram at a temperature change rate of 0.5°C / min provided in an embodiment of the present application;

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

[0025] Figure 6 A temperature curve diagram of each point at a temperature change rate of 0.5°C / min provided in an embodiment of the present application;

[0026] Figure 7 A comparison chart of the initial model temperature prediction and the actual simulation temperature at a temperature change rate of 0.5°C / min provided in an embodiment of the present application;

[0027] Figure 8 A comparison chart of the initial model temperature prediction and the actual simulation temperature at a temperature change rate of 1°C / min provided in an embodiment of the present application;

[0028] Fig. 9 A comparison chart of the improved model temperature prediction and the actual simulation temperature at a temperature change rate of 0.5°C / min provided in an embodiment of the present application;

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

[0030] Fig.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] Fig.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 the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

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

[0034] The optical 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 1In the application environment shown. Among them, the terminal communicates with the server through the network. The data storage system can store the data that the server needs to process. The data storage system can be set up separately, integrated on the server, or placed on the cloud or other servers. The terminal can send a fiber ring temperature point prediction request to the server. After the server receives the fiber ring temperature point prediction request, the server obtains the ambient temperature of the environment in which the fiber optic gyroscope is located; according to the ambient temperature, the thermal diffusion delayed response temperature model is applied to determine the predicted temperature of a target point inside the fiber ring of the fiber optic gyroscope; the thermal diffusion delayed response temperature model is a relationship model between the ambient temperature and the temperature of the target point inside the fiber ring; according to the predicted temperature of the target point inside the fiber ring, the multi-point temperature prediction model inside the fiber ring is applied to determine the predicted temperature of multiple non-target points inside the fiber ring; the non-target points and the target points are distributed along the axial direction of the fiber ring; the multi-point temperature prediction model inside the fiber ring is a relationship model between the temperature of the target point and the temperature 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 fiber ring. The server can feed back the predicted temperature of each point inside the fiber ring to the terminal. In addition, in some embodiments, the fiber optic ring temperature point prediction method based on the temperature field fitting model can also be implemented independently by a server or a terminal. For example, the terminal can directly perform a fiber optic ring temperature point prediction based on the temperature field fitting model in response to a fiber optic ring temperature point prediction request, or the server can obtain the ambient temperature of the environment in which the fiber optic gyroscope is located from a data storage system, and perform a fiber optic ring temperature point prediction based on the temperature field fitting model in response to the ambient temperature of the environment in which the fiber optic gyroscope is located based on the fiber optic ring temperature point prediction request.

[0035] The terminal may be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, IoT devices, and portable wearable devices. The server may be implemented as an independent server or a server cluster consisting of multiple servers, or may be a cloud server.

[0036] In an exemplary embodiment, Figure 2 As shown, a method for predicting the temperature point of an optical fiber ring based on a temperature field fitting model is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The server in the example is used to illustrate, including the following steps 101 to 103. Among them:

[0037] Step 101, obtaining the ambient temperature of the environment in which the fiber optic gyroscope is located.

[0038] Step 102, 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; 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.

[0039] Step 103, according to the predicted temperature of the target point inside the optical fiber ring, the 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.

[0040] By implementing the above-mentioned steps 101 to 103, by combining the thermal diffusion delayed response temperature model with the temperature models of multiple points inside the optical fiber ring, the temperature data of one point inside the optical fiber ring is predicted by the external temperature, and then the temperature data of multiple points inside the optical fiber ring are predicted by the data, so as to more clearly reflect the temperature field distribution inside the optical fiber ring, and provide a large amount of temperature data for the subsequent optical fiber 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, and 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 frame, Y waveguide and coupler. Figure 3 (b) is the upper part of the fiber optic gyroscope, which includes components such as circuit boards and light sources. 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 conducive 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. When performing 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, and the natural convection heat transfer coefficient and heating power are set before simulation.

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

[0043]

[0044] The accurate delayed response time τ is obtained through experimental data of different temperature change rates t And model parameters (a, b, c, d, e, f). In order to ensure the accuracy of the model parameters, new experimental data can be used to verify the accuracy of the model parameters. is the ambient temperature T o The first derivative of .

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

[0046]

[0047] Where, T s is the predicted temperature of the target point inside the fiber ring; T o is the ambient temperature; is the ambient temperature T o The first derivative of t is the delayed response time; a, b, c, d, e, and f are model parameters.

[0048] Based on the above content, in step 102, according to the ambient temperature, a thermal diffusion delayed response temperature model is applied to determine the predicted temperature of a target point inside the optical fiber ring of the optical fiber gyroscope, specifically including:

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

[0050] (a2) 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 along the axial distribution on the inner side of the optical fiber ring in the three-dimensional simulation model when applying the heat load with 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.

[0051] (a3) fitting data based on the simulated temperature of the environment at different temperature change rates and the simulated temperature of the target point inside the optical fiber ring to obtain a thermal diffusion delay response temperature model; the target point refers to any point among the multiple points distributed along the axial direction inside the optical fiber ring.

[0052] (a4) 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.

[0053] In order to obtain more temperature data on the fiber ring, a temperature model of multiple points inside the fiber ring is established (multi-point temperature prediction model inside the fiber ring). The selection of internal points needs to be determined according to the temperature gradient on the fiber 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 ring mainly comes from the contact heat conduction between the fiber ring and the bottom of the fiber optic gyroscope. Since the air temperature around the fiber ring is basically the same, the fiber temperature at the inner wall and the outer wall of the fiber 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 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 the temperature change rate of 0.5℃ / 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 optical 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. The initial model is used to obtain the predicted temperature of point 2 under the 0.5℃ / min temperature change rate simulation experiment. Figure 7 As shown in Figure 2, 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 change rate of 1°C / min, there is a large deviation between the predicted temperature and the simulated temperature at point 2. In order to obtain a universal temperature point prediction model, the single polynomial fitting model (the initial model mentioned above) is improved by adding the error between the predicted result of the initial model and the actual simulation value:

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

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

[0059] When the model order is higher, the fitting effect on a 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 coupling term of the two and the error e ic are added to obtain an improved temperature point prediction model (multi-point temperature prediction model in the fiber optic loop):

[0060]

[0061] Among them, T ic is the predicted temperature at non-target point i in the fiber optic loop; T s is the predicted temperature of the target point on the inner side of the fiber optic loop; is the first derivative of T s ; e ic is the temperature error term at non-target point i in the fiber optic loop; a ic , b ic , c ic , d ic are model parameters.

[0062] Similarly, in the simulation experiment with a temperature change rate of 0.5 °C / min, 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 fiber optic loop. As Fig. 9 shown, for point 2, the prediction effect of this model is almost the same as that of the initial model. Based on the model training parameters of this time (a ic , b ic , c ic , d ic ), using the simulated temperature data of point 1 in the simulation experiment with a temperature change rate of 1 °C / min, the temperature of point 2 is predicted. As Fig.10 shown, the predicted temperature of point 2 can better approximate the actual simulated temperature of point 2 compared to Figure 8 .

[0063] The above content takes point 2 as an example to illustrate the determination process of the point temperature prediction model in the fiber optic loop corresponding to point 2. For other points, only the data of point 2 need to be replaced with the data of the corresponding points (such as point 3, point 4, etc.). Finally, the temperature prediction models of each non-target point in the fiber optic loop can be obtained, that is, through the temperature of a known target point (such as point 1) on a fiber optic loop, the temperature data of multiple other points can be obtained.

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

[0065]

[0066] Where, 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 is the model parameter.

[0067] Based on the above, in step 103, according to the predicted temperature of the target point inside the optical fiber ring, the predicted temperature of multiple non-target points inside the optical fiber ring is determined by applying the multi-point temperature prediction model inside the optical fiber ring, specifically including:

[0068] (b1) Data fitting is performed based on the simulated temperatures recorded at each non-target point and the target point on the inner side of the optical fiber ring under the application of thermal loads at different temperature change rates, to obtain an initial model for predicting the temperature of the points inside the optical fiber ring corresponding to each non-target point; the initial model for predicting the temperature of the points inside the optical fiber ring 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 at each non-target point inside the optical fiber ring under the application of a thermal load at any temperature change rate is brought into the corresponding initial model for predicting the temperature of the points inside the optical fiber ring to obtain the initial model predicted temperature of each non-target point.

[0070] (b3) Calculate the error value between the initial model predicted temperature and the recorded simulated temperature for each non-target point.

[0071] (b4) performing data fitting based on the simulated temperatures and error values ​​recorded at each non-target point and the target point on the inner side of the optical fiber ring under the application of thermal loads at different temperature change rates, and 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 point temperature prediction model inside the optical fiber ring corresponding to each non-target point.

[0072] (b5) Substituting the predicted temperature of the target point inside the optical fiber ring 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.

[0073] In this embodiment, considering the process of heat transfer in the fiber optic gyroscope, there is a time delay in the response of the temperature change on the fiber optic loop compared to the external temperature change. A thermal diffusion delay response temperature model is established by adding a delay response time according to the external temperature and the temperature change rate. The temperature data of a point inside the fiber optic loop can be obtained through the external temperature data. A temperature model for multiple points inside the fiber optic loop is established based on the temperature data of a point inside the fiber optic loop. Different points have different model parameters, that is, different temperature prediction models for points inside the fiber optic loop. After adding an error term, even if the temperature change rate is changed, the temperature of different points can be accurately predicted through the temperature data of a point inside. By combining the thermal diffusion delay response temperature model and the temperature prediction model for multiple points inside the fiber optic loop, the temperature data of different points on the fiber optic loop can be obtained only through the external temperature data, providing a large amount of data for the temperature compensation of the fiber optic gyroscope and solving the problem of the position and number of temperature sensors arranged on the hardware.

[0074] The present application also provides an application scenario, which applies the above-mentioned fiber optic loop temperature point prediction method based on the temperature field fitting model. Specifically: The fiber optic loop temperature point prediction method based on the temperature field fitting model provided in this embodiment can be applied to the temperature compensation scenario of the fiber optic gyroscope. This scenario includes a temperature field fitting link and a temperature compensation link; the temperature field fitting link is used to deduce the temperature data of the position of the temperature sensor inside the fiber optic gyroscope by using the external ambient temperature, adding a delay response time, and using the temperature and the temperature change rate, and then use the deduced temperature data of the position of the temperature sensor to obtain the temperature data of multiple other points inside the fiber optic gyroscope for subsequent temperature compensation work; the temperature compensation link is used to perform temperature compensation according to the fitted temperature field inside the fiber optic loop. The fiber optic loop temperature point prediction method based on the temperature field fitting model provided in this embodiment belongs to the temperature field fitting link.

[0075] Based on the same inventive concept, the embodiment of the present application also provides a fiber optic loop temperature point prediction device based on the temperature field fitting model for implementing the above-mentioned fiber optic loop temperature point prediction method based on the temperature field fitting model. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the fiber optic loop temperature point prediction device based on the temperature field fitting model provided below can refer to the limitations on the fiber optic loop temperature point prediction method based on the temperature field fitting model in the above text, and will not be repeated here.

[0076] In an exemplary embodiment, as Fig.11 shown, a fiber optic loop temperature point prediction device based on the temperature field fitting model is provided, including:

[0077] An ambient temperature acquisition module M1, configured to acquire the ambient temperature of the environment where 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 according to the ambient temperature and applying the 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 according to the predicted temperature of the target point inside the optical fiber ring and 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 temperature 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: Fig.12 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the 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 the 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 Fig.12 The structure shown in the figure is only a block diagram of a part 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. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in 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, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

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

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

[0086] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

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

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

Claims

1. A method for predicting the temperature point of an optical fiber ring 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 where the fiber optic gyroscope is located; According to the ambient temperature, a thermal diffusion delayed 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 delayed response temperature model is a relationship model between the ambient 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, the predicted temperature of multiple non-target points inside the optical fiber ring is determined by 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 temperature 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.

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 delayed response temperature model is: Where, T s is the predicted temperature of the target point inside the fiber ring; T o is the ambient temperature; is the ambient temperature T o The first derivative of t is the delayed response time; a, b, c, d, e, and 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, 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 is the model parameter.

4. The optical fiber ring temperature point prediction method based on the temperature field fitting model according to claim 1 is characterized in that: According to the ambient temperature, applying a thermal diffusion delayed response temperature model, determining a 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 the fiber optic gyroscope; Apply heat loads with different temperature change rates to the three-dimensional simulation model to perform temperature field simulation, and record the simulated temperatures of the center node of the fiber optic gyroscope housing and the multiple points distributed along the axial direction on the inner side of the optical fiber ring in the three-dimensional simulation model when applying the heat load of 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; The thermal diffusion delay response temperature model is obtained by performing data fitting based on the simulated temperature of the environment at different temperature change rates and the simulated temperature of the target point inside the optical fiber ring; the target point refers to any point among the 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 the predicted temperature of a target point inside the optical fiber ring of the optical fiber gyroscope.

5. The optical fiber ring temperature point prediction method based on the temperature field fitting model according to claim 4 is characterized in that: According to the predicted temperature of the target point inside the optical fiber ring, the predicted temperature of multiple non-target points inside the optical fiber ring is determined by applying the multi-point temperature prediction model inside the optical fiber ring, specifically including: According to 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, data fitting is performed to obtain 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 optical 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 optical fiber ring inner point to obtain the initial model predicted temperature of each non-target point; Calculate the error value between the initial model predicted temperature and the recorded simulated temperature at each non-target point; According to the simulated temperatures and error values ​​recorded at each non-target point and the target point on the inner side of the optical fiber ring under the application of thermal loads at different temperature change rates, data fitting is performed to obtain a multi-point temperature prediction model in the optical fiber ring; the multi-point temperature prediction model in the optical fiber ring includes a point temperature prediction model in the optical fiber ring 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.

6. The optical fiber ring temperature point prediction method based on the temperature field fitting model according to claim 5 is characterized in that: The expression of the initial model for predicting the temperature of the optical fiber ring is: Where, T ia is the temperature at non-target point i; T s is the temperature of the target point inside the fiber ring; T s The first derivative of ia , b ia 、c ia ,d ia 、e ia 、f ia is the model parameter.

7. A device for predicting the temperature point of an optical fiber ring 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 comprises: An ambient temperature acquisition module is used to acquire the ambient temperature of the environment in which the fiber optic gyroscope is located; A target point temperature prediction module is used to determine the 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 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; The non-target point temperature prediction module is used to determine the predicted temperatures of multiple non-target points inside the optical fiber ring according to the predicted temperature of the target point inside the optical fiber ring and apply 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.

8. 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 described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the optical fiber ring temperature point prediction method based on the temperature field fitting model described in any one of claims 1 to 6 is implemented.

10. 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 described in any one of claims 1 to 6 is implemented.

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