Optimized layout method of sensors of fireproof blanket for cable joint
By optimizing the cable joint sensor layout using finite element simulation models and multi-objective risk scoring functions, the problem of inaccurate monitoring in existing technologies has been solved, enabling precise fire prevention monitoring and timely early warning of cable joints.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-29
- Publication Date
- 2026-04-10
AI Technical Summary
The existing cable joint sensor deployment method fails to fully consider factors such as the heat source inside the joint and the difference in thermal conductivity of multiple layers of materials, as well as the convection and radiation heat dissipation on the surface of the fire blanket, resulting in inaccurate fire monitoring of cable joints.
By establishing a finite element simulation model, the temperature and potential distribution of the cable joint and the fire blanket are simulated. The optimal placement of the sensor is determined by using a multi-objective risk scoring function, taking into account the influence of various factors such as electric field and ambient temperature on the cable joint during actual operation.
This ensures the accuracy of fire monitoring of cable joints, improves the precision and effectiveness of sensor deployment, and enables timely warning of potential fire risks.
Smart Images
Figure CN121835277A_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of cable temperature monitoring technology, and in particular to an optimized deployment method for fire blanket sensors for cable joints. Background Technology
[0002] Power cables are widely used in power distribution networks and industrial settings. Cable joints, intermediate joints, and terminal joints are particularly prone to localized heating and failure risks due to their complex structures, multiple material layers, and concentrated contact resistance and electric field stress. If abnormal temperature rise occurs at a cable joint due to poor contact, current fluctuations, or partial discharge, it can lead to accelerated insulation aging, thermal runaway, and even fire risks. Therefore, it is necessary to deploy sensors to continuously monitor and provide early warning of cable joint temperatures.
[0003] In practical engineering applications, to reduce the impact of high external temperatures on cable joints, fireproof covering measures are often taken for the joint area, such as wrapping the cable joint with fireproof blankets or flame-retardant tape. For this structure of cable joints covered with fireproof blankets, existing sensor deployment typically relies on experience or fixed templates, for example, placing sensors in the middle and at both ends of the joint. However, this existing sensor deployment method does not consider the combined effects of internal heat sources and the thermal conductivity differences of multiple layers of materials, as well as the convective and radiative heat dissipation on the surface of the fireproof blanket. It also does not fully consider the influence of various factors such as the electric field and ambient temperature on the cable temperature during actual operation, thus failing to ensure the accuracy of fire prevention monitoring of cable joints.
[0004] Therefore, it is necessary to provide a new technical solution to improve one or more of the problems existing in the above solutions.
[0005] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention
[0006] The purpose of this disclosure is to provide an optimized deployment method for fire blanket sensors for cable joints, ensuring the accuracy of fire monitoring of cable joints.
[0007] According to an embodiment of this disclosure, a method for optimizing the deployment of fire blanket sensors for cable joints is provided, including: A finite element simulation model is established based on the cable joint and the fire blanket covering structure. The finite element simulation model includes the multi-layer structure of the cable joint and the multi-layer structure of the fire blanket. The temperature distribution of the cable joint and the fire blanket under preset operating conditions is simulated using the finite element simulation model to obtain hot spot distribution coordinate data; the preset operating conditions include normal load conditions and / or overload conditions; The potential distribution of the cable joint and the fire blanket under normal load conditions was simulated using the finite element simulation model to obtain the coordinate data of the extreme potential distribution. The hotspot distribution coordinate data and the potential extreme value distribution coordinate data are weighted according to the multi-objective risk scoring function to determine the main measurement deployment location of the sensor.
[0008] In an exemplary embodiment of this disclosure, before establishing the finite element simulation model based on the cable joint and the fire blanket covering structure, the method further includes: Define the Z-axis direction of the finite element simulation model along the axial direction of the cable joint, and determine the coordinate position of the fire blanket roll edge in the Z-axis direction.
[0009] In an exemplary embodiment of this disclosure, the step of simulating the temperature distribution of the cable joint and the fire blanket under preset operating conditions using the finite element simulation model to obtain hotspot distribution coordinate data includes: Determine the material property settings of the finite element simulation model, including thermal conductivity, density, and constant pressure heat capacity; The heat conduction control equation of the finite element simulation model and the boundary energy balance equation between the fire blanket and the outside air are set. The heat conduction control equation uses the aluminum core of the cable joint as the heat source. Finite element thermal simulation is performed on the finite element simulation model based on the heat conduction control equation and the boundary energy balance equation to obtain the temperature distribution of the cable joint and the fire blanket under preset working conditions. The coordinates of the extreme temperature points in the Z-axis direction are extracted from the temperature distribution under the preset operating conditions to obtain the hotspot distribution coordinate data.
[0010] In an exemplary embodiment of this disclosure, the heat conduction control equation is expressed as: (1) in, Indicates the density of the material. T represents the constant-pressure heat capacity, and T represents the temperature field. Represents the volumetric heat source term. Represents the Hamiltonian operator. Represents the heat flux vector. k represents the thermal conductivity. Represents the temperature gradient; The boundary energy balance equation is expressed as: (2) Where h represents the convective heat transfer coefficient, Indicates ambient temperature. Indicates the temperature of the boundary surface. Indicates surface emissivity, This represents the Stefan-Boltzmann constant. It indicates an outward direction.
[0011] In an exemplary embodiment of this disclosure, after determining the main sensor deployment location, the method further includes: The hot spot location deviation is determined based on the coordinate position of the temperature extreme point corresponding to the preset working condition in the Z-axis direction; The hot spot position deviation is compared with a preset deviation threshold. If the hot spot position deviation is greater than the preset deviation threshold, the temperature gradient feature distribution is obtained based on the temperature distribution, and the sensor calibration layout position is determined based on the coordinate position of the local extreme point in the temperature gradient feature distribution in the Z-axis direction.
[0012] In an exemplary embodiment of this disclosure, the step of simulating the potential distribution of the cable joint under a preset operating condition using the finite element simulation model to obtain the potential extreme value distribution coordinate data includes: Determine the material electric field parameter settings for the finite element simulation model, wherein the material electric field parameters include the relative permittivity; Set the electric field control equation of the finite element simulation model, and perform finite element electric field simulation on the finite element simulation model based on the electric field control equation to obtain the potential distribution of the cable joint and the fire blanket under the normal load condition. The coordinate positions of the potential extrema points in the potential distribution along the Z-axis are used as the coordinate data of the potential extrema distribution.
[0013] In an exemplary embodiment of this disclosure, the main test placement position is the coordinate position of the sensor in the Z-axis direction.
[0014] In an exemplary embodiment of this disclosure, in the multi-objective risk scoring function, the weighting coefficient corresponding to the hotspot distribution coordinate data is greater than the weighting coefficient corresponding to the potential extreme value distribution coordinate data.
[0015] In an exemplary embodiment of this disclosure, the multilayer structure of the cable connector includes an aluminum core, a semiconductor layer, a main insulation layer, a copper shielding layer, an outer insulation layer, a silicone grease layer, a semiconductor electrical tape layer, a waterproof tape layer, a stress tube layer, and an intermediate insulation layer.
[0016] In an exemplary embodiment of this disclosure, the multilayer structure of the fire blanket includes a silicone rubber fireproof cloth layer, a high silica layer, a ceramic fiber layer, a Kevlar layer, and a polyimide layer.
[0017] The technical solution provided in this disclosure may include the following beneficial effects: In the embodiments of this disclosure, the finite element simulation model established based on the cable joint and the fire blanket covering structure includes the multi-layer structure of the cable joint and the multi-layer structure of the fire blanket. This ensures that when using the finite element simulation model for temperature field simulation and electric field simulation, the superposition of the heat source inside the joint and the thermal conductivity difference of the multi-layer materials is fully considered, so as to ensure that the simulation results are close to the actual working conditions. By combining the hot spot distribution coordinate data and the potential extreme value distribution coordinate data, the main detection deployment position of the sensor is determined based on the multi-objective risk scoring function. This ensures that the sensor deployment position also fully considers the influence of various factors such as electric field and ambient temperature on the cable temperature during actual operation of the cable joint, thereby ensuring the accuracy of fire prevention monitoring of the cable joint.
[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description
[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.
[0020] Figure 1 This diagram illustrates the steps of a method for optimizing the placement of fire blanket sensors for cable joints in an exemplary embodiment of this disclosure. Figure 2 This diagram illustrates the coordinate position of the fire blanket roll edge in the Z-axis direction in an exemplary embodiment of this disclosure. Figure 3 A simulation modeling diagram of the multi-layer structure of a cable connector in an exemplary embodiment of this disclosure is shown. Figure 4 This illustration shows the simulation results of the temperature distribution of the cable joint and fire blanket under normal load conditions in an exemplary embodiment of this disclosure. Figure 1 ; Figure 5 This illustration shows the simulation results of the temperature distribution of the cable joint and fire blanket under normal load conditions in an exemplary embodiment of this disclosure. Figure 2 ; Figure 6 This illustration shows the simulation results of temperature distribution of cable joints and fire blankets under overload conditions in an exemplary embodiment of this disclosure. Figure 1 ; Figure 7 This illustration shows the simulation results of temperature distribution of cable joints and fire blankets under overload conditions in an exemplary embodiment of this disclosure. Figure 2 ; Figure 8This illustration shows the simulation results of the potential distribution of the cable joint under preset operating conditions in an exemplary embodiment of this disclosure. Figure 1 ; Figure 9 This illustration shows the simulation results of the potential distribution of the cable joint under preset operating conditions in an exemplary embodiment of this disclosure. Figure 2 . Detailed Implementation
[0021] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[0022] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.
[0023] This example embodiment provides a method for optimizing the deployment of fire blanket sensors for cable joints, referencing... Figure 1 As shown, the method includes the following steps.
[0024] Step S101: Establish a finite element simulation model based on the cable joint and the fire blanket covering structure. The finite element simulation model includes the multi-layer structure of the cable joint and the multi-layer structure of the fire blanket.
[0025] Step S102: Use the finite element simulation model to simulate the temperature distribution of the cable joint and the fire blanket under preset working conditions to obtain hot spot distribution coordinate data; the preset working conditions include normal load conditions and / or overload conditions.
[0026] Step S103: Use the finite element simulation model to simulate the potential distribution of the cable joint and the fire blanket under normal load conditions, and obtain the potential extreme value distribution coordinate data.
[0027] Step S104: The hotspot distribution coordinate data and the potential extreme value distribution coordinate data are weighted according to the multi-objective risk scoring function to determine the main measurement deployment location of the sensor.
[0028] In the embodiments of this disclosure, the finite element simulation model established based on the cable joint and the fire blanket covering structure includes the multi-layer structure of the cable joint and the multi-layer structure of the fire blanket. This ensures that when using the finite element simulation model for temperature field simulation and electric field simulation, the superposition of the heat source inside the joint and the thermal conductivity difference of the multi-layer materials is fully considered, so as to ensure that the simulation results are close to the actual working conditions. By combining the hot spot distribution coordinate data and the potential extreme value distribution coordinate data, the main detection deployment position of the sensor is determined based on the multi-objective risk scoring function. This ensures that the sensor deployment position also fully considers the influence of various factors such as electric field and ambient temperature on the cable temperature during actual operation of the cable joint, thereby ensuring the accuracy of fire prevention monitoring of the cable joint.
[0029] The steps of the method described above in this example implementation will now be explained in more detail.
[0030] In one embodiment, before establishing the finite element simulation model based on the cable joint and the fire blanket's covering structure, the method further includes: Define the Z-axis direction of the finite element simulation model along the axial direction of the cable joint, and determine the coordinate position of the fire blanket roll edge in the Z-axis direction.
[0031] By defining the Z-axis direction as the axial direction along the cable joint, which is the length direction of the cable, the coordinate position of the fire blanket roll edge and the subsequent sensor placement positions can be determined based on the defined Z-axis direction. (Referencing...) Figure 2 As shown, the coordinate position of the fire blanket roll edge in the Z-axis direction is z0 = 450 mm. Since the fire blanket roll edge can be reliably identified at the construction site, the above setup achieves a direct mapping from simulation coordinates to construction coordinates, allowing on-site personnel to directly install the sensors according to the sensor placement locations determined in this application.
[0032] In one embodiment, in the step of establishing the finite element simulation model in step S101, a 10kV cable joint is taken as the object, and a fireproof blanket is wrapped around the outside of the cable joint. Two-dimensional axisymmetric geometric modeling is used for the wrapping structure to reduce the amount of simulation calculation.
[0033] Specifically, in step S101, refer to Figure 3 As shown, the multi-layer structure of the cable connector includes an aluminum core, a semiconductor layer, a main insulation layer, a copper shielding layer, an outer insulation layer, a silicone grease layer, a semiconductor electrical tape layer, a waterproof tape layer, a stress tube layer, and an intermediate insulation layer.
[0034] The stress cone serves to homogenize the electric field distribution, solve the problem of electric field stress concentration at the cut point of the cable's outer shielding layer, and prevent insulation breakdown.
[0035] Specifically, in step S101, the multi-layer structure of the fire blanket includes a silicone rubber fireproof cloth layer, a high silica layer, a ceramic fiber layer, a Kevlar layer, and a polyimide layer.
[0036] Furthermore, in the step of establishing the finite element simulation model in step S101, the two-dimensional cross-sectional geometry of the cable joint is first established, and then a fireproof blanket layered structure is established on the outside of the two-dimensional cross-sectional geometry of the cable joint and the covering is completed.
[0037] It should be explained that the two-dimensional cross-sectional geometry of the cable joint corresponds to the multi-layer structure of the cable joint, and the layered structure of the fire blanket corresponds to the multi-layer structure of the fire blanket.
[0038] It should be noted that the two-dimensional axisymmetric geometric modeling is mainly for scenarios where cable joints and sheathing structures satisfy rotational symmetry or approximately rotational symmetry. For cable joints and sheathing structures with non-axisymmetric structures, such as partial overlaps, fasteners, and irregularly shaped covers, the two-dimensional axisymmetric geometric modeling can be replaced with an equivalent three-dimensional model, and the method provided in this application can still be followed.
[0039] In one embodiment, the step of using the finite element simulation model to simulate the temperature distribution of the cable joint and the fire blanket under preset working conditions to obtain hot spot distribution coordinate data includes the following steps S1021 to S1024: Step S1021: Determine the material property settings of the finite element simulation model, including the material property settings of the multi-layer structure of the cable joint and the multi-layer structure of the fire blanket. The material properties include thermal conductivity k, density, etc. and constant pressure heat capacity .
[0040] Step S1022: Set the heat conduction control equation of the finite element simulation model and the boundary energy balance equation between the fire blanket and the outside air. The heat conduction control equation uses the aluminum core of the cable joint as the heat source.
[0041] Step S1023: Perform finite element thermal simulation on the finite element simulation model based on the heat conduction control equation and the boundary energy balance equation to obtain the temperature distribution of the cable joint and fire blanket under preset operating conditions; the preset operating conditions include normal load conditions and overload conditions. The temperature distribution of the cable joint and fire blanket under the preset conditions includes the temperature distribution of the cable joint and fire blanket under normal load conditions and the temperature distribution of the cable joint and fire blanket under overload conditions.
[0042] Step S1024: Extract the coordinate positions of the temperature extreme points in the Z-axis direction from the temperature distribution under the preset operating conditions to obtain the hot spot distribution coordinate data. For example, extract the coordinate positions of the corresponding temperature extreme points in the Z-axis direction from the temperature distribution under normal load conditions, and extract the coordinate positions of the corresponding temperature extreme points in the Z-axis direction from the temperature distribution under overload conditions; average the coordinate positions of the temperature extreme points in the Z-axis direction corresponding to the normal load conditions and overload conditions to obtain the hot spot distribution coordinate data.
[0043] It should be noted that the finite element thermal simulation of the finite element simulation model based on the aforementioned thermal conductivity control equation is performed under the assumptions of two-dimensional axisymmetry and material isotropy. The finite element thermal simulation can obtain the temperature distribution of the cable joint and the fire blanket covering structure, and extract the hotspot locations from the temperature distribution as hotspot distribution coordinate data.
[0044] Specifically, in step S1021, the material property settings of the finite element simulation model are shown in Tables 1 and 2 below. Table 1 shows the material property settings of the multi-layer structure of the cable joint, and Table 2 shows the material property settings of the multi-layer structure of the fire blanket.
[0045] Table 1 Material property settings for multi-layered cable joints Table 2 Material property settings for multi-layer fire blankets Specifically, in step S1022, the step of setting the heat conduction control equation of the finite element simulation model, the heat conduction control equation is expressed as: (1) in, Indicates the density of the material. T represents the constant-pressure heat capacity, and T represents the temperature field. Represents the volumetric heat source term. Represents the Hamiltonian operator; Represents the heat flux vector. k represents the thermal conductivity. This represents the temperature gradient. It's necessary to explain the Hamiltonian operator. It is the general standard differential operator in vector analysis.
[0046] It should be explained that, considering that during the operation of the cable joint, the heat of the cable is mainly generated by the Joule heat produced by the current carrying capacity of the conductor, the innermost aluminum core of the cable joint is designated as the heat source area. The Joule heat power is determined according to the following formula: (3) Where P represents Joule thermal power, I represents the load current of the aluminum conductor in the cable core, and R represents the resistance of the aluminum conductor in the cable core. , Let L represent the resistivity of the aluminum conductor in the cable core, L represent the length of the aluminum conductor in the cable core, and A represent the cross-sectional area of the aluminum conductor in the cable core. When the cross-sectional area A of the aluminum conductor in the cable core is circular, ... , where r represents the radius of the cross-sectional area of the aluminum conductor in the cable core.
[0047] Converting the Joule heat power into a volumetric heat source term, for a uniformly distributed volume V of the aluminum conductor in the cable core, the volumetric heat source term is expressed as: (4) in, This represents the volumetric heat source term, with units of W / m³.
[0048] It should also be explained that the thermal conductivity control equation satisfies the assumptions of two-dimensional axisymmetry and material isotropy, and neglects circumferential heat conduction.
[0049] Specifically, considering that there is both natural convection and surface radiation heat transfer between the outer surface of the fire blanket and the environment (outside air), in step S1022, the boundary energy balance equation between the fire blanket and the outside air is expressed as follows: (2) Where h represents the convective heat transfer coefficient, Indicates ambient temperature. Indicates the temperature of the boundary surface. Indicates surface emissivity, This represents the Stefan-Boltzmann constant. It indicates an outward direction.
[0050] It should be explained that the convective heat transfer coefficient can be taken as 10 W / (m²·K), the ambient temperature can be taken as 293.15 K, and the surface emissivity can be taken as 0.9.
[0051] It should be noted that when performing finite element thermal simulation on the finite element simulation model based on the heat conduction control equation and the boundary energy balance equation, the initial conditions are as follows: initial temperature The ambient temperature is set to 20℃, and x represents the location coordinates.
[0052] Specifically, in step S1023, under normal load and overload conditions, the temperature distribution of the cable joint and fire blanket under normal load and overload conditions is obtained by discretizing and solving the heat conduction control equation, the volume heat source term, and the boundary energy balance equation. X represents the position coordinates, and t represents the time.
[0053] It should be explained that during the finite element thermal simulation of the aforementioned finite element simulation model, transient solutions can be used, iterating until the temperature rise tends to stabilize, for example, by satisfying the convergence criterion: , The preset iteration threshold is used. In this embodiment, a stable temperature distribution is used as the basis for hotspot extraction.
[0054] refer to Figure 4 and Figure 5 The diagram shows the temperature distribution of the cable connector and fire blanket under normal load conditions, with the load current set to 160A. From... Figure 4 and Figure 5 The highest temperature value of the fireproof blanket is extracted from the temperature distribution under normal load conditions, along with the coordinate position of this highest temperature value along the Z-axis. It should be noted that this highest temperature value is the temperature extreme point.
[0055] refer to Figure 6 and Figure 7 The diagram shows the temperature distribution of the cable joint and fire blanket under overload conditions, with the load current set to 210A. From... Figure 6 and Figure 7 The highest temperature value of the fire blanket is extracted from the temperature distribution under the overload condition shown, along with the coordinate position of this highest temperature value along the Z-axis. It should be noted that this highest temperature value is the temperature extreme point.
[0056] Specifically, in step S1024, the coordinates of extreme temperature points along the Z-axis are extracted from the temperature distribution under normal load conditions, and the coordinates of extreme temperature points along the Z-axis are extracted from the temperature distribution under overload conditions. Extreme temperature points can be understood as the highest temperature value of the fire blanket. Furthermore, the coordinates of the extreme temperature points along the Z-axis corresponding to these two preset conditions (normal load and overload) are averaged to obtain the hotspot distribution coordinate data.
[0057] For example, in step S1024, from Figure 4 and Figure 5 The temperature distribution under normal load conditions shows that the highest temperature of the aluminum core of the electrical connector is 85℃, the highest temperature of the fire blanket is 50.2℃, and the coordinate position of the highest temperature of the fire blanket in the Z-axis direction is z. a1 =171.66mm; Based on the coordinate position of the fire blanket roll edge in the Z-axis direction as z0=450, the distance L from the fire blanket roll edge in the Z-axis direction to the highest temperature value of the fire blanket can be obtained. a1 =450-171.66=278.34mm.
[0058] For example, in step S1024, from Figure 6 and Figure 7 The temperature distribution under the overload condition shown indicates that the highest temperature of the aluminum core of the cable connector is 132.998℃, the highest temperature of the fire blanket is 71.44℃, and the coordinate position of the highest temperature of the fire blanket in the Z-axis direction is also z. a2 =171.66mm; Based on the coordinate position of the fire blanket roll edge in the Z-axis direction as z0=450mm, the distance L from the fire blanket roll edge in the Z-axis direction to the highest temperature value of the fire blanket can be obtained. a2 =450-171.66=278.34mm.
[0059] For example, in step S1024, the coordinate position L of the temperature extreme point corresponding to the normal load condition obtained above is set in the Z-axis direction. a1 The coordinate position L of the temperature extreme point corresponding to the overload condition in the Z-axis direction. a2 The mean value L is obtained by averaging. a =278.34mm, this mean value is used as the coordinate data for hotspot distribution. .
[0060] In one embodiment, the step of simulating the potential distribution of the cable joint under a preset operating condition using the finite element simulation model to obtain the potential extreme value distribution coordinate data includes the following steps: Step S1031: Determine the material electric field parameter settings of the finite element simulation model, wherein the material electric field parameters include the relative permittivity.
[0061] Step S1032: Set the electric field control equation of the finite element simulation model, and perform finite element electric field simulation on the finite element simulation model based on the electric field control equation to obtain the potential distribution of the cable joint and the fire blanket under the normal load condition.
[0062] Step S1033: The coordinate positions of the potential extrema points in the potential distribution along the Z-axis are used as the coordinate data of the potential extrema distribution.
[0063] It should be noted that the above-mentioned finite element electric field simulation based on the electric field control equation is conducted under the assumption that the charge distribution does not change with time and the influence of the magnetic field on the electric field is negligible in electrostatic field analysis. Finite element electric field simulation can obtain the potential distribution of the cable joint and the fire blanket, and extract the coordinate data of the potential extremum distribution from the potential distribution.
[0064] Specifically, in step S1031, in the step of determining the material electric field parameter settings of the finite element simulation model, the material electric field parameter settings of the cable joint are shown in Table 3 below, and the material electric field parameter settings of the fireproof blanket are shown in Table 4 below.
[0065] Table 3 Material electric field parameter settings Table 4. Material electric field parameter settings for fire blankets Specifically, in step S1032, the step of setting the electric field control equation of the finite element simulation model is a coupling of the differential form of Gauss's theorem and the electric field-potential relationship, as follows: (5) Where E represents the electric field intensity vector, and V represents the electric potential. D represents the Hamiltonian operator; D represents the electric displacement vector. Represents the vacuum permittivity. Values , Represents the relative permittivity of the material. This represents the volume charge density.
[0066] It needs to be explained that, in Hamiltonian operator It acts on a scalar field (electric potential V). Represents the Hamiltonian operator By taking the gradient with respect to the electric potential V, we obtain the electric field intensity vector. middle, Represents the Hamiltonian operator By applying a dot product to the electric displacement vector D, the divergence of the electric displacement vector D is calculated to obtain the volume charge density.
[0067] Based on the above formula (5), we can obtain the Poisson equation describing the scalar potential distribution: (6) in, Possible values .
[0068] For example, in step S1032, a finite element electric field simulation is performed on a 10kV AC cross-linked polyethylene cable joint. According to the GB / T standard, the nominal voltage of the cable system is 10kV, which is the line voltage. Therefore, the effective value of the phase voltage is: The potential distribution of the cable joint and fire blanket under normal load conditions was obtained through finite element electric field simulation. The potential distribution referenced... Figure 8 and Figure 9As shown in the image.
[0069] Specifically, in step S1033, from Figure 8 and Figure 9 The coordinate position of the potential extremum point extracted from the potential distribution under normal load conditions shown is z in the Z-axis direction. c =33.55mm, the distance L from the edge of the fire blanket to the extreme potential point along the Z-axis can be obtained. c =450-33.55=416.45mm, which is used as the coordinate data of the potential extremum distribution. .
[0070] In one embodiment, the multi-objective risk scoring function in step S104 is expressed as: (7) in, Indicates the main measurement location of the sensor. This represents the weighting coefficients corresponding to the hotspot distribution coordinate data. Represents hotspot distribution coordinate data. This represents the weighting coefficients corresponding to the coordinate data of the electric potential extreme value distribution. This represents the coordinate data of the extreme potential distribution.
[0071] Optionally, in the multi-objective risk scoring function, the weight coefficients corresponding to the hotspot distribution coordinate data... The weighting coefficient corresponding to the extreme potential distribution coordinate data is greater than the weighting coefficient. .
[0072] For example, the weighting coefficients corresponding to the hotspot distribution coordinate data. The value is 0.9, which is the weighting coefficient corresponding to the potential extreme value distribution coordinate data. The value is 0.1.
[0073] In one embodiment, the main test deployment location is the coordinate position of the sensor in the Z-axis direction.
[0074] For example, the distance Z from the edge of the fire blanket in the Z-axis direction can be measured using a sensor. s This indicates the location where the sensor is deployed.
[0075] In step S104, the weighting coefficients corresponding to the hotspot distribution coordinate data are... The value is 0.9, which is the weighting coefficient corresponding to the potential extreme value distribution coordinate data. When the value is 0.1, the previously obtained hotspot distribution coordinate data L a =278.34mm and potential extreme value distribution coordinate data L cSubstituting 416.55mm into formula (7), we get... =292.16mm, which means that the position of the sensor is located 292.16mm away from the edge of the fireproof blanket in the Z-axis direction.
[0076] It should be noted that, in addition to considering the influence of temperature and potential distribution on the sensor placement, parameters such as temperature gradient, partial discharge intensity, ambient humidity, and moisture content can be introduced to further optimize the sensor placement. In other embodiments, the multi-objective risk scoring function is expressed as: (8) in, Indicates the main measurement location of the sensor. This represents the weighting coefficients corresponding to the hotspot distribution coordinate data. Represents hotspot distribution coordinate data. This represents the weighting coefficients corresponding to the coordinate data of the electric potential extreme value distribution. Represents the coordinate data of the extreme potential distribution. This represents the weighting coefficients corresponding to the coordinate data of the temperature gradient distribution. Represents the coordinate data of the temperature gradient distribution. This represents the weighting coefficients corresponding to the coordinate data of the partial discharge intensity distribution. This represents the coordinate data of the partial discharge intensity distribution. This represents the weighting coefficients corresponding to the moisture content distribution coordinate data. This represents the coordinate data of the moisture content distribution.
[0077] It needs to be explained that the temperature gradient distribution coordinate data = Characterizing local risk features; partial discharge intensity distribution coordinate data and moisture content distribution coordinate data It can be determined based on existing empirical models or monitoring data, and its role is to provide supplementary characterization for areas where the temperature distribution is not fully apparent but where risks already exist.
[0078] For example, partial discharge intensity distribution coordinate data can be obtained through existing partial discharge monitoring systems on cable lines. This partial discharge monitoring system typically has a pulse current sensor deployed at the grounding end of the cable accessory. The pulse current sensor can acquire the amplitude and location information of the partial discharge in real time, and obtain the coordinate data of the partial discharge intensity distribution based on the acquired amplitude and location information. For example, the moisture content distribution coordinate data can be measured by measuring the dielectric loss factor during periodic power outages for maintenance. Alternatively, moisture content distribution coordinate data can be obtained through distributed fiber optic humidity sensors. Alternatively, the moisture content distribution coordinate data can be calculated based on historical humidity data of the operating environment and empirical formulas of the insulation aging model. It should be noted that the above method for obtaining partial discharge intensity distribution coordinate data... and moisture content distribution coordinate data The methods used are all existing technical means in this field and will not be elaborated here.
[0079] In one embodiment, after determining the main deployment location of the sensor, the method further includes the following steps: Step S1051: Determine the hot spot location deviation based on the coordinate position of the temperature extreme point corresponding to the preset working condition in the Z-axis direction.
[0080] For example, the hot spot location deviation is determined based on the coordinates of the extreme temperature points under normal load conditions and the extreme temperature points under overload conditions along the Z-axis. ; This indicates the coordinate position of the extreme temperature point corresponding to normal load conditions along the Z-axis. This indicates the coordinate position of the extreme temperature point corresponding to the overload condition along the Z-axis.
[0081] Step S1052: Adjust the hotspot location deviation Deviation threshold from preset If the hotspot location deviates during the comparison... Greater than the preset deviation threshold Then, based on the temperature distribution obtained from the simulation in step S102, the temperature gradient feature distribution is obtained, and the sensor's calibration layout position is determined based on the coordinate position of the local extreme points in the temperature gradient feature distribution in the Z-axis direction.
[0082] It should be noted that the temperature gradient feature distribution is obtained based on the temperature distribution obtained from the simulation in step S102. Specifically, the temperature gradient feature distribution is obtained by taking the derivative of the temperature distribution.
[0083] It should also be noted that local extreme points in the temperature gradient characteristic distribution can be considered as the maximum temperature gradient value in the temperature gradient characteristic distribution. The sensor's calibration placement position is determined based on the coordinate position of the maximum temperature gradient value along the Z-axis. The calibration placement position determined in this way is more sensitive to hotspot drift. Deploying the sensors according to both the main sensor placement position and the calibration placement position ensures the accuracy and comprehensiveness of fire monitoring of cable joints.
[0084] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.
Claims
1. A method for optimizing the deployment of fire blanket sensors for cable joints, characterized in that, include: A finite element simulation model is established based on the cable joint and the fire blanket covering structure. The finite element simulation model includes the multi-layer structure of the cable joint and the multi-layer structure of the fire blanket. The temperature distribution of the cable joint and the fire blanket under preset working conditions was simulated using the finite element simulation model to obtain hot spot distribution coordinate data. The preset operating conditions include normal load conditions and / or overload conditions; The potential distribution of the cable joint and the fire blanket under normal load conditions was simulated using the finite element simulation model to obtain the coordinate data of the extreme potential distribution. The hotspot distribution coordinate data and the potential extreme value distribution coordinate data are weighted according to the multi-objective risk scoring function to determine the main measurement deployment location of the sensor.
2. The method for optimizing the deployment of fire blanket sensors for cable joints according to claim 1, characterized in that, Before establishing the finite element simulation model based on the cable joint and the fire blanket covering structure, the following steps are also included: Define the Z-axis direction of the finite element simulation model along the axial direction of the cable joint, and determine the coordinate position of the fireproof blanket roll edge in the Z-axis direction.
3. The method for optimizing the deployment of fire blanket sensors for cable joints according to claim 2, characterized in that, The process of using the finite element simulation model to simulate the temperature distribution of the cable joint and fire blanket under preset operating conditions to obtain hotspot distribution coordinate data includes: Determine the material property settings of the finite element simulation model, including thermal conductivity, density, and constant pressure heat capacity; The heat conduction control equation of the finite element simulation model and the boundary energy balance equation between the fire blanket and the outside air are set. The heat conduction control equation uses the aluminum core of the cable joint as the heat source. Finite element thermal simulation is performed on the finite element simulation model based on the heat conduction control equation and the boundary energy balance equation to obtain the temperature distribution of the cable joint and the fire blanket under preset working conditions. The coordinates of the extreme temperature points in the Z-axis direction are extracted from the temperature distribution under the preset operating conditions to obtain the hotspot distribution coordinate data.
4. The method for optimizing the deployment of fire blanket sensors for cable joints according to claim 3, characterized in that, The heat conduction control equation is expressed as: （1） in, Indicates the density of the material. T represents the constant-pressure heat capacity, and T represents the temperature field. Represents the volumetric heat source term. Represents the Hamiltonian operator. Represents the heat flux vector. k represents the thermal conductivity. Represents the temperature gradient; The boundary energy balance equation is expressed as: （2） Where h represents the convective heat transfer coefficient, Indicates ambient temperature. Indicates the temperature of the boundary surface. Indicates surface emissivity, This represents the Stefan-Boltzmann constant. It indicates an outward direction.
5. The method for optimizing the deployment of fire blanket sensors for cable joints according to claim 3, characterized in that, After determining the main deployment location of the sensor, the process also includes: The hot spot location deviation is determined based on the coordinate position of the temperature extreme point corresponding to the preset working condition in the Z-axis direction; The hot spot position deviation is compared with a preset deviation threshold. If the hot spot position deviation is greater than the preset deviation threshold, the temperature gradient feature distribution is obtained based on the temperature distribution, and the sensor calibration layout position is determined based on the coordinate position of the local extreme point in the temperature gradient feature distribution in the Z-axis direction.
6. The method for optimizing the deployment of fire blanket sensors for cable joints according to claim 2, characterized in that, The step of simulating the potential distribution of the cable joint under preset operating conditions using the finite element simulation model to obtain the potential extreme value distribution coordinate data includes: Determine the material electric field parameter settings for the finite element simulation model, wherein the material electric field parameters include the relative permittivity; Set the electric field control equation of the finite element simulation model, and perform finite element electric field simulation on the finite element simulation model based on the electric field control equation to obtain the potential distribution of the cable joint and the fire blanket under the normal load condition. The coordinate positions of the potential extrema points in the potential distribution along the Z-axis are used as the coordinate data of the potential extrema distribution.
7. The method for optimizing the deployment of fire blanket sensors for cable joints according to any one of claims 2-6, characterized in that, The main test deployment position is the coordinate position of the sensor in the Z-axis direction.
8. The method for optimizing the deployment of fire blanket sensors for cable joints according to any one of claims 1-6, characterized in that, In the multi-objective risk scoring function, the weighting coefficient corresponding to the hotspot distribution coordinate data is greater than the weighting coefficient corresponding to the potential extreme value distribution coordinate data.
9. The method for optimizing the deployment of fire blanket sensors for cable joints according to any one of claims 1-6, characterized in that, The multi-layer structure of the cable joint includes an aluminum core, a semiconductor layer, a main insulation layer, a copper shielding layer, an outer insulation layer, a silicone grease layer, a semiconductor electrical tape layer, a waterproof tape layer, a stress tube layer, and an intermediate insulation layer.
10. The method for optimizing the deployment of fire blanket sensors for cable joints according to any one of claims 1-6, characterized in that, The fire blanket has a multi-layered structure including a silicone rubber fireproof cloth layer, a high silica layer, a ceramic fiber layer, a Kevlar layer, and a polyimide layer.