Temperature monitoring method and device for umbilical cable stacked on winch, medium and product

Abstract

The invention discloses a temperature monitoring method and device for an umbilical cable stacked on a winch, a medium and a product, and relates to the field of umbilical cable temperature monitoring, and the method comprises the steps: constructing a finite element model of multilayer stacking of the umbilical cable to be detected according to the structure, material thermal parameters and boundary conditions of the umbilical cable to be detected; stacking the to-be-tested umbilical cable on a winch drum, placing the to-be-tested umbilical cable in an environment simulation cabin, carrying out a temperature rise test, and obtaining the operation temperature of the to-be-tested umbilical cable by using a distributed optical fiber temperature measurement system connected with an outer port of the to-be-tested umbilical cable; and constructing a time sequence data set according to the operation temperature, the operation time, the environment temperature, the stacking layer number and the current-carrying capacity of the to-be-tested umbilical cable, training a neural network according to the time sequence data set, and predicting the temperature rise of the to-be-tested umbilical cable by using the trained neural network. According to the invention, the operation temperature of the umbilical cable can be monitored on line, and the temperature rise of the umbilical cable can be predicted.

Description

Technical Field

[0001] The present application relates to the field of umbilical cable temperature monitoring, and in particular to a method, device, medium and product for monitoring the temperature of an umbilical cable stacked on a winch. Background Art

[0002] As scientific research vessels move to the deep sea, the marine umbilical cable is an important device that connects the winch of the scientific research vessel with the deep-sea ROV. The marine umbilical cable transmits electrical energy to the ROV and is an important device for deep-sea operations. Due to the different sizes of the winch drum and the different operating depths of the ROV, the umbilical cable needs to be stacked on the winch when working. The umbilical cables stacked on the winch have different temperature rises due to different operating environments, different stacking layers, and different current carrying capacities, which affects the current carrying capacity and the deep-sea operations of the ROV. How to monitor the working temperature of the umbilical cable online and how to predict the temperature rise of the umbilical cable are issues that need to be solved urgently. Summary of the invention

[0003] The purpose of the present application is to provide a method, device, medium and product for monitoring the temperature of an umbilical cable stacked on a winch, which can realize online monitoring of the operating temperature of the umbilical cable and prediction of the temperature rise of the umbilical cable.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] In a first aspect, the present application provides a method for monitoring the temperature of an umbilical cable stacked on a winch, the method for monitoring the temperature of an umbilical cable stacked on a winch comprising:

[0006] Obtain the structure, material thermal parameters and boundary conditions of the umbilical cable to be tested;

[0007] Constructing a finite element model of a multi-layer stack of the umbilical cable to be tested according to the structure, material thermal parameters and boundary conditions of the umbilical cable to be tested; the finite element model is used to determine the stacking temperature of the umbilical cable to be tested;

[0008] The umbilical cable to be tested is stacked on a winch drum and placed in an environmental simulation chamber for a temperature rise test, and the operating temperature of the umbilical cable to be tested is obtained using a distributed optical fiber temperature measurement system connected to the external port of the umbilical cable to be tested; a pulse laser in the distributed optical fiber temperature measurement system emits laser pulses, which are injected into the built-in multimode optical fiber of the umbilical cable, and the Raman scattered light signal carrying the temperature information is reflected in the multimode optical fiber and returned along the multimode optical fiber;

[0009] A time series data set is constructed based on the operating temperature, operating time, ambient temperature, number of stacked layers, and current carrying capacity of the umbilical cable to be tested. A neural network is trained based on the time series data set, and the temperature rise of the umbilical cable to be tested is predicted using the trained neural network.

[0010] Optionally, the structure of the umbilical cable to be tested includes: a conductor, an insulating layer, a multimode optical fiber, an optical fiber steel tube, an inner sheath, an aramid armor and an outer sheath.

[0011] Optionally, the material thermal parameters include: thermal conductivity of the conductor, thermal conductivity of the insulation layer, thermal conductivity of the inner sheath, thermal conductivity of the aramid, thermal conductivity of the outer sheath, thermal resistance coefficient of the external environment of the umbilical cable to be tested, temperature of the external environment of the umbilical cable to be tested, and convection heat transfer coefficient.

[0012] Optionally, the umbilical cable to be tested is stacked on a winch drum and placed in an environmental simulation chamber for a temperature rise test, and the operating temperature of the umbilical cable to be tested is obtained using a distributed optical fiber temperature measurement system connected to an external port of the umbilical cable to be tested, specifically including:

[0013] The umbilical cable to be tested for temperature is stacked on the winch drum through a motor and a cable arranger;

[0014] A distributed optical fiber temperature measurement system and an electric power generator are connected to the outer port of the umbilical cable to be tested, and an adjustable load is connected to the inner port of the umbilical cable to be tested;

[0015] In the environmental simulation chamber, load the ambient temperature;

[0016] Turn on the electric power generator to pass current through the conductor of the umbilical cable to be tested for temperature, causing heat and temperature rise;

[0017] Use the distributed optical fiber temperature measurement system to obtain the operating temperature of the umbilical cable to be tested in real time;

[0018] The number of stacked layers on the winch drum is changed through the motor and the cable arranger, and the ambient temperature and current are changed to regain the operating temperature of the umbilical cable to be tested.

[0019] Optionally, the neural network is trained based on the time series data set, specifically including:

[0020] Preprocess the time series data set; preprocessing includes: data cleaning, filling missing values, checking and correcting outliers in the data, and normalizing the operating temperature of the umbilical cable;

[0021] Set a time window; use the time window to split the operating temperature into fixed-length input sequences; use the operating time, ambient temperature, number of stacked layers, and current carrying capacity data as input to predict the temperature of each layer of the umbilical cable at the next moment;

[0022] Divide the time series data set into training set, validation set and test set; and use the training set to train the neural network;

[0023] The performance of the neural network is evaluated using the validation set, the error between the predicted temperature and the actual temperature is calculated, and the model parameters of the neural network are adjusted according to the performance of the validation set; the model parameters include: learning rate, number of layers, and neurons; and the performance of the validation set is used to determine whether the neural network is overfitting, and the visualization result is determined by comparing the predicted curve with the actual curve;

[0024] The final performance of the neural network is evaluated using the test set to obtain a trained neural network. The temperature rise of the umbilical cable to be tested is predicted using the trained neural network, and the data and model parameters are updated regularly.

[0025] Optionally, the neural network is a transformer neural network.

[0026] In a second aspect, the present application provides an umbilical cable temperature monitoring device for stacking on a winch, the umbilical cable temperature monitoring device for stacking on a winch comprising:

[0027] A data acquisition module, used to obtain the structure, material thermal parameters and boundary conditions of the umbilical cable to be tested;

[0028] A finite element model building module is used to build a finite element model of a multi-layer stack of the umbilical cable to be tested according to the structure, material thermal parameters and boundary conditions of the umbilical cable to be tested; the finite element model is used to determine the stacking temperature of the umbilical cable to be tested;

[0029] An operating temperature acquisition module is used to stack the umbilical cable to be tested on a winch drum and place it in an environmental simulation chamber to perform a temperature rise test, and to obtain the operating temperature of the umbilical cable to be tested by using a distributed optical fiber temperature measurement system connected to the external port of the umbilical cable to be tested; a pulse laser in the distributed optical fiber temperature measurement system emits laser pulses, which are injected into the built-in multimode optical fiber of the umbilical cable, and the Raman scattered light signal carrying the temperature information is reflected in the multimode optical fiber and returned along the multimode optical fiber;

[0030] The prediction module is used to construct a time series data set according to the operating temperature, operating time, ambient temperature, number of stacked layers and current carrying capacity of the umbilical cable to be tested, train a neural network according to the time series data set, and use the trained neural network to predict the temperature rise of the umbilical cable to be tested.

[0031] 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 temperature monitoring method for an umbilical cable stacked on a winch.

[0032] 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 temperature monitoring method for an umbilical cable stacked on a winch.

[0033] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the temperature monitoring method for an umbilical cable stacked on a winch.

[0034] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0035] The present application provides a method, device, medium and product for monitoring the temperature of an umbilical cable stacked on a winch. A finite element model of a multi-layer stack of the umbilical cable to be tested is constructed according to the structure, material thermal parameters and boundary conditions of the umbilical cable to be tested, and a neural network is trained according to a time series data set. When the difference between the output value of the neural network and the output value of the finite element model is less than a set value, a trained neural network is obtained; that is, the present application can effectively improve the accuracy of temperature prediction by combining the finite element method with actual testing, and provide accurate data support for the subsequent cable operation status. Based on the real-time monitored operation data, the present application predicts the temperature rise of the umbilical cable under different ambient temperatures, different stacking layers and different current carrying capacity; it solves the problem of online monitoring of the temperature status of the marine umbilical cable, and avoids the umbilical cable temperature rise overload and failure due to different stacking layers, different ambient temperatures and different current carrying capacity when the umbilical cable is under different size drums and different operating depths. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] 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.

[0037] Figure 1 This is a schematic flow chart of a method for monitoring the temperature of an umbilical cable stacked on a winch in one embodiment of the present application;

[0038] Figure 2 A structural schematic diagram of obtaining the operating temperature of the umbilical cable to be tested by using a distributed optical fiber temperature measurement system connected to the external port of the umbilical cable to be tested. DETAILED DESCRIPTION

[0039] 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.

[0040] 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.

[0041] In an exemplary embodiment, Figure 1 As shown, a method for monitoring the temperature of an umbilical cable stacked on a winch is provided, the method comprising the following S101 to S106. Wherein:

[0042] S101, obtaining the structure, material thermal parameters and boundary conditions of the umbilical cable to be tested; the structure of the umbilical cable to be tested includes: conductor, insulation layer, multimode optical fiber, optical fiber steel tube, inner sheath, aramid armor and outer sheath. The material thermal parameters include: thermal conductivity of the conductor, thermal conductivity of the insulation layer, thermal conductivity of the inner sheath, thermal conductivity of the aramid, thermal conductivity of the outer sheath, thermal resistance coefficient of the external environment of the umbilical cable to be tested, temperature of the external environment of the umbilical cable to be tested and convection heat transfer coefficient.

[0043] S102, constructing a finite element model of a multi-layer stack of the umbilical cable to be tested according to the structure, material thermal parameters and boundary conditions of the umbilical cable to be tested; the finite element model is used to determine the stacking temperature of the umbilical cable to be tested;

[0044] Calculate the temperature of each stack layer based on the multi-layer stack finite element model of the umbilical cable to be tested, and then determine the stack temperature of the umbilical cable to be tested;

[0045] The establishment of the finite element model in this application is carried out through the existing finite element analysis software, and the calculation process is implemented using the existing finite element software.

[0046] S103, stacking the umbilical cable to be tested on a winch drum and placing it in an environmental simulation chamber to perform a temperature rise test, and obtaining the operating temperature of the umbilical cable to be tested by using a distributed optical fiber temperature measurement system (DTS) connected to an external port of the umbilical cable to be tested;

[0047] like Figure 2 As shown in the figure, the pulse laser in the distributed optical fiber temperature measurement system (DTS) emits laser pulses and injects them into the multimode optical fiber built in the umbilical cable. The Raman scattered light signal carrying temperature information reflected by the multimode optical fiber returns along the multimode optical fiber. There are two types of light in the Raman scattered light signal: Stokes light and anti-Stokes light. The temperature calculation formula can be expressed as: T is the temperature to be measured, I Stokes is the intensity of the Stokes light, I anti-Stokes is the intensity of anti-Stokes light, C1 and C2 are constants related to the medium and frequency, usually determined by actual experiments;

[0048] S103 specifically includes:

[0049] The umbilical cable to be tested for temperature is stacked on the winch drum through a motor and a cable arranger;

[0050] A distributed optical fiber temperature measurement system and an electric power generator are connected to the outer port of the umbilical cable to be tested, and an adjustable load is connected to the inner port of the umbilical cable to be tested;

[0051] In the environmental simulation chamber, load the ambient temperature;

[0052] Turn on the electric power generator to pass current through the conductor of the umbilical cable to be tested for temperature, causing heat and temperature rise;

[0053] Use the distributed optical fiber temperature measurement system to obtain the operating temperature of the umbilical cable to be tested in real time;

[0054] The number of stacked layers on the winch drum is changed through the motor and the cable arranger, and the ambient temperature and current are changed to regain the operating temperature of the umbilical cable to be tested.

[0055] S104, constructing a time series data set according to the operating temperature, operating time, ambient temperature, number of stacked layers, and current carrying capacity of the umbilical cable to be tested, training a neural network according to the time series data set, and predicting the temperature rise of the umbilical cable to be tested using the trained neural network;

[0056] Among them, a time series data set is constructed according to the operating temperature, operating time, ambient temperature, number of stacked layers and current carrying capacity of the umbilical cable to be tested, and then the time series data set is preprocessed. The preprocessing includes: cleaning data, filling missing values ​​and checking outliers in the data, correcting outliers, and normalizing the operating temperature of the umbilical cable to [0,1]; setting a time window, dividing the operating temperature into an input sequence of fixed length, taking the operating time, ambient temperature, number of stacked layers and current carrying capacity data as input, and predicting the temperature of each layer of the umbilical cable at the next moment;

[0057] Train the neural network according to the time series data set, use a suitable loss function, such as mean square error, to optimize the model, select the optimizer (ADAM), and set the learning rate; divide the time series data set into a training set (70%), a validation set (15%), and a test set (15%), and continuously optimize the model parameters through training cycles; use the validation set to evaluate the model performance, calculate the error between the predicted temperature and the actual temperature, adjust the model parameters such as learning rate, number of layers, neurons, etc. according to the performance of the validation set, judge whether the model is overfitting by the performance of the validation set, use the prediction curve to compare with the actual curve to visualize the results, use the test set to evaluate the final performance of the model, and obtain a trained neural network;

[0058] Among them, the neural network uses transformer neural network.

[0059] The trained neural network is used to predict the temperature rise of the umbilical cable to be tested, and the data and model are updated regularly to improve the accuracy of the prediction.

[0060] Based on the same inventive concept, the embodiment of the present application also provides an umbilical cable temperature monitoring device for stacking on a winch for implementing the above-mentioned umbilical cable temperature monitoring method for stacking on a winch. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above-mentioned method, so the specific limitations of one or more embodiments of the umbilical cable temperature monitoring device for stacking on a winch provided below can refer to the limitations of the umbilical cable temperature monitoring method for stacking on a winch above, and will not be repeated here.

[0061] In an exemplary embodiment, a temperature monitoring device for an umbilical cable stacked on a winch is provided, comprising:

[0062] A data acquisition module, used to obtain the structure, material thermal parameters and boundary conditions of the umbilical cable to be tested;

[0063] A finite element model building module is used to build a finite element model of a multi-layer stack of the umbilical cable to be tested according to the structure, material thermal parameters and boundary conditions of the umbilical cable to be tested; the finite element model is used to determine the stacking temperature of the umbilical cable to be tested;

[0064] The operating temperature acquisition module is used to stack the umbilical cable to be tested on the winch drum and place it in the environmental simulation chamber to perform a temperature rise test, and obtain the operating temperature of the umbilical cable to be tested by using a distributed optical fiber temperature measurement system connected to the external port of the umbilical cable to be tested; the pulse laser in the distributed optical fiber temperature measurement system emits laser pulses, which are injected into the built-in multimode optical fiber of the umbilical cable, and the Raman scattered light signal carrying the temperature information is reflected in the multimode optical fiber and returned along the multimode optical fiber;

[0065] The prediction module is used to construct a time series data set according to the operating temperature, operating time, ambient temperature, number of stacking layers and current carrying capacity of the umbilical cable to be tested, train a neural network according to the time series data set, and use the trained neural network to predict the temperature rise of the umbilical cable to be tested.

[0066] In an exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O for short) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via 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 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 via a network connection. When the computer program is executed by the processor, a temperature monitoring method for an umbilical cable stacked on a winch is implemented.

[0067] 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.

[0068] 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.

[0069] 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.

[0070] 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).

[0071] 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.

[0072] 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.

[0073] 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 monitoring the temperature of an umbilical cable stacked on a winch, characterized in that: The temperature monitoring method for an umbilical cable stacked on a winch comprises: Obtain the structure, material thermal parameters and boundary conditions of the umbilical cable to be tested; Constructing a finite element model of a multi-layer stack of the umbilical cable to be tested according to the structure, material thermal parameters and boundary conditions of the umbilical cable to be tested; the finite element model is used to determine the stacking temperature of the umbilical cable to be tested; The umbilical cable to be tested is stacked on a winch drum and placed in an environmental simulation chamber for a temperature rise test, and the operating temperature of the umbilical cable to be tested is obtained using a distributed optical fiber temperature measurement system connected to the external port of the umbilical cable to be tested; a pulse laser in the distributed optical fiber temperature measurement system emits laser pulses, which are injected into the built-in multimode optical fiber of the umbilical cable, and the Raman scattered light signal carrying the temperature information is reflected in the multimode optical fiber and returned along the multimode optical fiber; A time series data set is constructed according to the operating temperature, operating time, ambient temperature, number of stacked layers and current carrying capacity of the umbilical cable to be tested. A neural network is trained according to the time series data set, and the temperature rise of the umbilical cable to be tested is predicted using the trained neural network.

2. The temperature monitoring method for an umbilical cable stacked on a winch according to claim 1, characterized in that: The structure of the umbilical cable to be tested includes: a conductor, an insulating layer, a multimode optical fiber, an optical fiber steel tube, an inner sheath, an aramid armor and an outer sheath.

3. The temperature monitoring method for an umbilical cable stacked on a winch according to claim 2, characterized in that: The material thermal parameters include: thermal conductivity of the conductor, thermal conductivity of the insulation layer, thermal conductivity of the inner sheath, thermal conductivity of the aramid, thermal conductivity of the outer sheath, thermal resistance coefficient of the external environment of the umbilical cable to be tested, temperature of the external environment of the umbilical cable to be tested, and convection heat transfer coefficient.

4. The temperature monitoring method for an umbilical cable stacked on a winch according to claim 1, characterized in that: The umbilical cable to be tested is stacked on the winch drum and placed in an environmental simulation chamber for a temperature rise test. The operating temperature of the umbilical cable to be tested is obtained using a distributed optical fiber temperature measurement system connected to the external port of the umbilical cable to be tested, including: The umbilical cable to be tested for temperature is stacked on the winch drum through a motor and a cable arranger; A distributed optical fiber temperature measurement system and an electric power generator are connected to the outer port of the umbilical cable to be tested, and an adjustable load is connected to the inner port of the umbilical cable to be tested; In the environmental simulation chamber, load the ambient temperature; Turn on the electric power generator to pass current through the conductor of the umbilical cable to be tested for temperature, causing heat and temperature rise; Use the distributed optical fiber temperature measurement system to obtain the operating temperature of the umbilical cable to be tested in real time; The number of stacked layers on the winch drum is changed through the motor and the cable arranger, and the ambient temperature and current are changed to regain the operating temperature of the umbilical cable to be tested.

5. The temperature monitoring method for an umbilical cable stacked on a winch according to claim 1, characterized in that: The neural network is trained based on the time series data set, including: Preprocess the time series data set; preprocessing includes: data cleaning, filling missing values, checking and correcting outliers in the data, and normalizing the operating temperature of the umbilical cable; Set a time window; use the time window to split the operating temperature into fixed-length input sequences; use the operating time, ambient temperature, number of stacked layers, and current carrying capacity data as input to predict the temperature of each layer of the umbilical cable at the next moment; Divide the time series data set into training set, validation set and test set; and use the training set to train the neural network; The performance of the neural network is evaluated using the validation set, the error between the predicted temperature and the actual temperature is calculated, and the model parameters of the neural network are adjusted according to the performance of the validation set; the model parameters include: learning rate, number of layers, and neurons; and the performance of the validation set is used to determine whether the neural network is overfitting, and the visualization result is determined by comparing the predicted curve with the actual curve; The final performance of the neural network is evaluated using the test set to obtain a trained neural network. The temperature rise of the umbilical cable to be tested is predicted using the trained neural network, and the data and model parameters are updated regularly.

6. The temperature monitoring method for an umbilical cable stacked on a winch according to claim 1, characterized in that: The neural network is a transformer neural network.

7. An umbilical cable temperature monitoring device for stacking on a winch, characterized in that: The umbilical cable temperature monitoring device for stacking on a winch comprises: A data acquisition module, used to obtain the structure, material thermal parameters and boundary conditions of the umbilical cable to be tested; A finite element model building module is used to build a finite element model of a multi-layer stack of the umbilical cable to be tested according to the structure, material thermal parameters and boundary conditions of the umbilical cable to be tested; the finite element model is used to determine the stacking temperature of the umbilical cable to be tested; An operating temperature acquisition module is used to stack the umbilical cable to be tested on a winch drum and place it in an environmental simulation chamber to perform a temperature rise test, and to obtain the operating temperature of the umbilical cable to be tested by using a distributed optical fiber temperature measurement system connected to the external port of the umbilical cable to be tested; a pulse laser in the distributed optical fiber temperature measurement system emits laser pulses, which are injected into the built-in multimode optical fiber of the umbilical cable, and the Raman scattered light signal carrying the temperature information is reflected in the multimode optical fiber and returned along the multimode optical fiber; The prediction module is used to construct a time series data set according to the operating temperature, operating time, ambient temperature, number of stacked layers and current carrying capacity of the umbilical cable to be tested, train a neural network according to the time series data set, and use the trained neural network to predict the temperature rise of the umbilical cable to be tested.

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 temperature monitoring method for an umbilical cable stacked on a winch according to 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 temperature monitoring method for an umbilical cable stacked on a winch according to 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 temperature monitoring method for an umbilical cable stacked on a winch according to any one of claims 1 to 6 is implemented.

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