Method for evaluating performance degradation of cable insulation after short-time overtemperature in fire environment

Abstract

The application discloses a kind of cable insulation performance degradation evaluation methods after short-time over-temperature in fire environment, wherein the method includes: step 1: establish cable tunnel fire simulation model, determine the peak temperature of the insulation layer of simulation cable in multiple typical positions in cable tunnel fire simulation model;Step 2: according to the multiple peak temperatures obtained in step 1, carry out multiple over-temperature tests, obtain multiple over-temperature test samples;Step 3: test the six indexes of multiple over-temperature test samples respectively;Step 4: calculate the mean square displacement variation law of the final three-dimensional periodic amorphous cell at different temperatures, obtain multiple temperature intervals;Step 5: determine the main influence index of multiple temperature intervals respectively;Step 6: according to the degradation degree score, and the degradation degree evaluation table determined in advance, determine the degradation degree of sample cable.The application solves the technical problem that the degradation degree of cable insulation performance after short-time over-temperature in fire cannot be quickly evaluated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of fire fighting of high-voltage cable tunnels, in particular to a method for evaluating the degradation of cable insulation performance after short-time overheating in a fire environment. BACKGROUND

[0002] In recent years, the scale of cables has grown rapidly, but due to the limited channel, the laying method of mixed voltage grade of cables in the same channel is often used, which leads to the increasing density of cable laying. Some early operated cables gradually show aging phenomenon, and the risk of breakdown failure of such cables is relatively high, which further leads to the increasing risk of cable fire. Once a cable fire occurs in a tunnel, the insulation performance of the adjacent non-faulty cables will be seriously threatened. At present, fireproof partitions, fire extinguishing bombs and other fire prevention and extinguishing equipment are usually installed in cable tunnels. The fireproof partitions can block the spread of fire to a certain extent, and the fire extinguishing bombs can perform fire extinguishing operation when the temperature of the tunnel reaches the trigger temperature. The action time of fire is relatively short, and the adjacent cables can still retain a certain insulation performance after experiencing the fire. However, under the action of heat convection and heat conduction, the insulation material of the overheated cable in the same channel may be damaged due to overheating, and it is difficult to intuitively analyze the insulation degradation degree, which leads to safety hazards in subsequent operation and may cause power failure accidents due to further degradation and breakdown.

[0003] At present, no effective solution has been proposed for the above problems. SUMMARY

[0004] The embodiments of the present application provide a method for evaluating the degradation of cable insulation performance after short-time overheating in a fire environment, to at least solve the technical problem that the degradation degree of cable insulation performance after short-time overheating in a fire cannot be quickly evaluated.

[0005] According to one aspect of the embodiments of the present application, a method for evaluating the degradation of cable insulation performance after short-time overheating in a fire environment is provided, which comprises: step 1: establishing a cable tunnel fire simulation model by imitating the actual cable tunnel fire situation, determining the peak temperatures of the insulation layers of the simulation cables at a plurality of typical positions in the cable tunnel fire simulation model, and obtaining a plurality of peak temperatures;

[0006] Step 2: building a cable insulation material overheating test platform, and performing a plurality of overheating tests according to the plurality of peak temperatures obtained in step 1 to obtain a plurality of overheating tested samples;

[0007] Step 3: testing six indexes of each of the plurality of overheating tested samples, wherein the six indexes include activation energy, crystallinity, carbonyl index, breakdown field strength, crosslinking degree and elongation at break;

[0008] Step 4: establish a three-dimensional periodic amorphous unit cell containing a plurality of crosslinked polyethylene molecular chains, and process the three-dimensional periodic amorphous unit cell containing a plurality of crosslinked polyethylene molecular chains to obtain a final three-dimensional periodic amorphous unit cell, and calculate the mean square displacement variation law of the final three-dimensional periodic amorphous unit cell at different temperatures, and divide the temperature interval according to the mean square displacement variation law to obtain a plurality of temperature intervals;

[0009] Step 5: combine the six indicators of each of the plurality of samples subjected to the temperature test obtained in step 3 and the plurality of temperature intervals obtained in step 4 to determine the main influencing indicators of each of the plurality of temperature intervals.

[0010] Step 6: according to the main influencing indicators of each of the plurality of temperature intervals determined in step 5, determine the weight corresponding to each main indicator, according to the plurality of performance indicators of the sample cable and the weight corresponding to each main indicator, determine the road degradation degree score of the sample cable, and according to the degradation degree score and the pre-determined degradation degree evaluation table, determine the degradation degree of the sample cable.

[0011] Optionally, step 1: establish a cable tunnel fire simulation model imitating the actual cable tunnel fire situation, and determine the peak temperature of the insulation layer of the simulation cable at each of a plurality of typical positions in the cable tunnel fire simulation model to obtain a plurality of peak temperatures, including the following steps:

[0012] Step 1.1: establish a cable tunnel fire simulation model imitating the actual cable tunnel fire situation, wherein the structure of the cable tunnel fire simulation model is: four layers of supports on one side, a middle passage, and four layers of supports on the other side, the lowermost support of the four layers of supports on one side is taken as the first layer of support, and 3 simulation cables are arranged on each layer of support on one side, and the radii of the simulation cables on each layer are different;

[0013] Step 1.2: take the middle joint of the simulation cable at the middle position on the first layer of support as the fire source position, arrange a fireproof partition plate above the fire source, and start the cable tunnel fire simulation;

[0014] Step 1.3: determine the temperature variation curve of the insulation layer of the simulation cable at each of a plurality of typical positions according to the cable tunnel simulation, and determine the peak temperature of the insulation layer of the simulation cable at each of a plurality of typical positions according to the temperature variation curve of the insulation layer of the simulation cable at each of a plurality of typical positions, to obtain a plurality of peak temperatures, wherein the simulation cables at a plurality of typical positions include: three simulation cables on the fourth layer of support on the other side, a simulation cable on the third layer of support on the other side close to the middle passage, and a simulation cable on the second layer of support on the other side close to the wall surface of the cable tunnel.

[0015] Optionally, step 2: Build a cable insulation material over-temperature test platform, and conduct multiple over-temperature tests based on the multiple peak temperatures obtained in step 1 to obtain multiple samples that have passed the over-temperature test, including the following steps:

[0016] Step 2.1: Construct a cable insulation material over-temperature test platform, which includes a vacuum heating chamber, a vacuum pump, a nitrogen generator, and an air compressor;

[0017] Step 2.2: Place multiple original samples into a crucible in sequence and place it in a vacuum heating chamber. Set the peak temperature in the vacuum heating chamber in sequence according to the multiple peak temperatures obtained in Step 1. The heating rate of the vacuum heating chamber meets the predetermined heating rate, and the absolute pressure in the vacuum heating chamber is regulated by a vacuum pump and meets the predetermined pressure threshold.

[0018] Step 2.3: Perform overheating tests on the original samples at different peak temperatures to obtain multiple samples that have passed the overheating test.

[0019] Optionally, step 3: Test six indicators for each of the multiple samples that have undergone temperature testing. The six indicators include activation energy, crystallinity, carbonyl index, breakdown field strength, degree of crosslinking, and elongation at break, including the following steps:

[0020] Step 3.1: Use a simultaneous thermal analyzer to test the thermogravimetric curve of the sample after the temperature test. Based on the thermogravimetric curve, the Koster-Redfen integral method, and the formula relating activation energy to temperature: draw A relationship diagram was plotted, and a linear fit was performed. The slope of the fitted line was... The activation energy of the target sample after the temperature test is obtained from the slope of the straight line. Following the above steps, the activation energy of multiple samples after the temperature test is tested. Where α is the weight loss rate, A is the pre-exponential factor, T is the Kelvin temperature, K and R are the gas constants, β is the heating rate, and E is the activation energy.

[0021] Step 3.2: The crystallinity of multiple samples that have undergone temperature testing is measured using X-ray diffraction. The formula for calculating crystallinity is: Where Xc is the crystallinity of the sample after temperature test, A1 is the area of ​​the amorphous peak, A2 is the area of ​​the main crystallization peak, and A3 is the area of ​​the secondary crystallization peak.

[0022] Step 3.3: The carbonyl index of each of the multiple samples that underwent the temperature test was measured using Fourier transform infrared spectroscopy. The formula for calculating the carbonyl index is: Where I is the carbonyl index, S1 is the area of ​​the peak corresponding to the carbonyl functional group, and S2 is the area of ​​the sample at 2915 cm⁻¹ after temperature testing. -1 The area of ​​the peak corresponding to the nearby methylene group;

[0023] Step 3.4: The sample after the temperature test is placed between the upper and lower symmetrical column-column electrodes in turn, insulating oil is poured into the oil cup, the oil surface height is higher than the sample after the temperature test and the column-column electrode, the voltage is increased by 1-2 kV per pole from 0 until the sample after the temperature test is broken down, the breakdown test of the sample after the temperature test is repeated for 10 times, 10 breakdown voltages of the sample after the temperature test are obtained, the breakdown probability distribution of the 10 breakdown voltages obeys the Weibull distribution, and the function is: The probability of the 10 breakdown voltages is calculated, the breakdown field strength corresponding to the failure probability of 63.2% is selected as the breakdown field strength of the sample after the temperature test, and the breakdown field strength of each of a plurality of samples after the temperature test is tested according to the method of this step, wherein F(i,n) is the breakdown probability, i is the sample number; n is the total number of samples;

[0024] Step 3.5: The sample after the temperature test is placed in a stainless steel mesh and put into a 110℃ xylene solution for extraction for 24h, and then dried in a 110℃ oven for 24h, and the crosslinking degree of the sample after the temperature test is calculated according to the formula: The crosslinking degree of the sample after the temperature test is calculated according to the formula, and the crosslinking degree of each of a plurality of samples after the temperature test is tested according to the method of this step, wherein M1 is the mass of the mesh bag, M2 is the mass of the sample after the temperature test and the mesh bag before extraction, and M3 is the mass of the sample after the temperature test and the mesh bag after extraction and drying;

[0025] Step 3.6: The elongation at break of the sample after the temperature test is measured by tensile test, the sample after the temperature test is cut into dumbbell shape with a thickness of 1mm, the test tensile rate is 200mm / min, and the elongation at break of the sample after the temperature test is calculated according to the formula: The elongation at break of the sample after the temperature test is calculated according to the formula, and the elongation at break of each of a plurality of samples after the temperature test is tested according to the method of this step, wherein ε t is the elongation at break of the sample after the temperature test, △L b is the elongation within the gauge length of the sample after the temperature test when it breaks, i.e. the reading of the travel when it breaks, and L0 is the measurement gauge length.

[0026] Step 4: A three-dimensional periodic amorphous unit cell containing a plurality of crosslinked polyethylene molecular chains is established, and the three-dimensional periodic amorphous unit cell containing a plurality of crosslinked polyethylene molecular chains is processed to obtain a final three-dimensional periodic amorphous unit cell, and the mean square displacement variation law of the final three-dimensional periodic amorphous unit cell at different temperatures is calculated, and the temperature interval is divided according to the mean square displacement variation law to obtain a plurality of temperature intervals, including the following steps:

[0027] Step 4.1: setting a force field and a charge for the crosslinked polyethylene molecular chain, and establishing a three-dimensional periodic amorphous unit cell containing a plurality of crosslinked polyethylene molecular chains, wherein the crosslinked polyethylene molecular chain is a H-type simplified crosslinked polyethylene molecular chain;

[0028] Step 4.2: performing structure optimization and energy minimization settings on the three-dimensional periodic amorphous unit cell, then performing a plurality of cycle annealing processes on the structure-optimized and energy-minimized three-dimensional periodic amorphous unit cell, and performing energy minimization processing in each step of the annealing process, to obtain an annealed and energy-minimized three-dimensional periodic amorphous unit cell, sequentially performing kinetic simulation with a time length of ta and a temperature of Td on the annealed and energy-minimized three-dimensional periodic amorphous unit cell, and kinetic simulation with a time length of tb, a temperature of Td and a pressure of Pb, to obtain a three-dimensional periodic amorphous unit cell stable in energy under the condition of a temperature of Td and a pressure of Pb;

[0029] Step 4.3: performing kinetic simulation with a time length of tc and a pressure of Pc on the energy-stable three-dimensional periodic amorphous unit cell at different temperatures, and then performing kinetic simulation with a time length of td and a pressure of Pc, to obtain a final three-dimensional periodic amorphous unit cell, and calculating the mean square displacement change rule of the final three-dimensional periodic amorphous unit cell at different temperatures, wherein the intervals between different temperatures are consistent;

[0030] Step 4.4: dividing the temperature interval by the change rule of the mean square displacement to obtain a plurality of temperature intervals.

[0031] Step 5: combining the six indicators of each of the plurality of samples obtained in step 3 subjected to the temperature test and the plurality of temperature intervals obtained in step 4 to determine the main influencing indicators of each of the plurality of temperature intervals, including:

[0032] Step 5.1: establishing an index linear model y = f j (x) = mx j +b j , performing linear fitting on the six indicators of each of the plurality of temperature intervals to obtain a plurality of fitting curves, wherein x is temperature data, y ij is the specific data of the jth indicator at the ith temperature, n represents the number of temperature points, ∑x i y ij is the sum of the products of all x i and y ij , ∑x i and ∑y ij are the sums of all x i and y ij values, (∑x i ) 2 is the sum of all xi the sum of squares of the values;

[0033] Step 5.2: Calculate R 2 The fitting effect of the index linear model is measured, and the calculation formula is: wherein, represents the fitting result of the index linear model, represents the average number, R 2 The closer to 1, the better the fitting effect is;

[0034] Step 5.3: According to the R 2 value of each fitting curve, determine the main influence index of each temperature interval.

[0035] Step 6: According to the main influence index of each temperature interval determined in step 5, determine the weight corresponding to each main index, according to the multiple performance indexes of the sample cable and the weight corresponding to each main index, determine the road degradation degree score of the sample cable, according to the degradation degree score, and the pre-determined degradation degree evaluation table, determine the degradation degree of the sample cable, including the following steps:

[0036] Step 6.1: According to the main influence index of each temperature interval, establish a plurality of original matrices of each temperature interval, obtain a plurality of original matrices, and normalize each of the plurality of original matrices, calculate the average value and standard deviation of each main influence index according to the plurality of normalized original matrices, and calculate the coefficient of variation of each main influence index according to the average value and standard deviation of each main influence index, and calculate the weight of each main influence index according to the coefficient of variation of each main influence index;

[0037] Step 6.2: Determine the multiple performance index values of the sample cable and normalize the multiple performance index values of the sample cable, according to the multiple performance index values of the sample cable after normalization and the weight of each main influence index, determine the cable insulation degradation degree score S of the sample cable;

[0038] Step 6.3: According to the degradation degree score S, and the pre-determined degradation degree evaluation table, determine the degradation degree of the sample cable.

[0039] According to another aspect of the embodiment of the present application, a cable insulation performance degradation evaluation device after short-time over-temperature in a fire environment is provided, comprising: a first determining module, configured to imitate the real cable tunnel fire situation, establish a cable tunnel fire simulation model, and determine the peak temperature of the insulation layer of each simulation cable at multiple typical positions in the test cable tunnel fire simulation model, to obtain multiple peak temperatures;

[0040] The over-temperature test module is used for building an over-temperature test platform of cable insulation materials, and performing multiple over-temperature tests according to multiple peak temperatures obtained in the test step 1 to obtain multiple over-temperature tested samples;

[0041] The test module is used for testing six indexes of each of the multiple over-temperature tested samples, wherein the six indexes include activation energy, crystallinity, carbonyl index, breakdown field strength, crosslinking degree and elongation at break;

[0042] The division module is used for establishing a three-dimensional periodic amorphous unit cell containing the multiple test crosslinked polyethylene molecular chains, processing the three-dimensional periodic amorphous unit cell containing the multiple test crosslinked polyethylene molecular chains to obtain a final three-dimensional periodic amorphous unit cell, and calculating, by the FORCITE module, a mean square displacement change rule of the final three-dimensional periodic amorphous unit cell at different temperatures, and dividing temperature intervals according to the mean square displacement change rule to obtain multiple temperature intervals;

[0043] The second determination module is used for determining a main influence index of each of the multiple temperature intervals in combination with the six indexes of each of the multiple over-temperature tested samples obtained in the test step 3 and the multiple temperature intervals obtained in the test step 4;

[0044] The third determination module is used for determining a weight corresponding to each main index according to the main influence index of each of the multiple temperature intervals determined in the step 5, determining a road degradation degree score of the sample cable according to the multiple performance indexes of the sample cable and the weight corresponding to each main index, and determining a degradation degree of the sample cable according to the degradation degree score and a pre-determined degradation degree evaluation table.

[0045] According to another aspect of the embodiment of the present application, a non-volatile storage medium is provided, and the non-volatile storage medium stores a plurality of instructions, and the instructions are adapted to be loaded and executed by a processor to implement any one of the cable insulation performance degradation evaluation methods after short-time over-temperature in a fire environment.

[0046] According to another aspect of the embodiment of the present application, an electronic device is provided, which includes one or more processors and a memory, and the memory is used for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement any one of the cable insulation performance degradation evaluation methods after short-time over-temperature in a fire environment.

[0047] According to still another aspect of the embodiment of the present application, a computer program product is provided, which includes a computer program, and the computer program is executed by a processor to implement any one of the cable insulation performance degradation evaluation methods after short-time over-temperature in a fire environment.

[0048] The application provides a cable insulation performance degradation evaluation method after short-time overheating in a fire environment, which has the advantages that:

[0049] (1) The general cable insulation performance evaluation method mainly considers material aging, among which, thermal aging is mostly studied, a large number of thermal aging tests are carried out in the test, and different thermal aging performances are analyzed, but these studies are at most about 180 DEG C, and the material degradation characteristics at a higher temperature are considered in the patent, at this time, different from long-time aging, due to exceeding the phase transition temperature, the crosslinking structure changes and the existing thermal aging has great difference, the patent carries out tests in a higher temperature interval, and the time length is controlled, and the general thermal aging is more than 24 hours, so that the insulation degradation in the special case of short-time overheating in a fire environment can be more accurately reflected.

[0050] (2) The test shows that important index parameters reflecting degradation performance also have great difference in different temperature intervals, therefore, the patent considers more accurate evaluation, considers the essence of material structure, adopts a temperature change interval divided by the change trend of molecular mean square displacement with temperature, then analyzes the correlation between each index and temperature in each temperature interval, and selects a characteristic quantity with good correlation as the basis for evaluating insulation performance degradation, and various indexes are enumerated in the general cable insulation evaluation, which is more accurate and effective. BRIEF DESCRIPTION OF DRAWINGS

[0051] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and serve to explain the principles of the application, and do not limit the application in any way. In the drawings:

[0052] Figure 1 FIG. 1 is a flowchart of a cable insulation performance degradation evaluation method after short-time overheating in a fire environment according to an embodiment of the application;

[0053] Figure 2 FIG. 2 is a schematic diagram of an optional simplified cable tunnel fire simulation model according to an embodiment of the application;

[0054] Figure 3 FIG. 3 is a schematic diagram of a maximum value of temperature reached in a tunnel according to an embodiment of the application;

[0055] Figure 4 FIG. 4 is a schematic diagram of temperature curves at different positions of a cable tunnel simulation model according to an embodiment of the application;

[0056] Figure 5 FIG. 5 is a schematic diagram of an overheating test platform according to an embodiment of the application;

[0057] Figure 6is a schematic diagram of an optional H-type simplified crosslinked polyethylene molecule according to an embodiment of the present application;

[0058] Figure 7 is a schematic diagram of an optional crosslinked polyethylene cell model according to an embodiment of the present application;

[0059] Figure 8 is a schematic diagram of the variation of the mean square displacement of an optional crosslinked polyethylene cell with temperature according to an embodiment of the present application;

[0060] Figure 9 is a schematic diagram of linear fitting curves of different indicators in each temperature interval according to an embodiment of the present application;

[0061] Figure 10 is a flowchart of an optional cable insulation performance degradation evaluation device after short-time over-temperature in a fire environment according to an embodiment of the present application;

[0062] Figure 11 is a schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0063] In order to enable persons skilled in the art to better understand the present application scheme, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by persons skilled in the art without creative labor should belong to the scope of protection of the present application.

[0064] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0065] According to the embodiment of the present application, a method for evaluating the degradation of cable insulation performance after short-time over-temperature in a fire environment is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in a different order.

[0066] Figure 1 is a flowchart of a method for evaluating the degradation of cable insulation performance after short-time over-temperature in a fire environment according to the embodiment of the present application, as shown in Figure 1 , the method comprises the following steps:

[0067] Step 1: According to the actual cable tunnel fire situation, a cable tunnel fire simulation model is established, the peak temperature of the insulation layer of the simulation cable at each of the multiple typical positions in the cable tunnel fire simulation model is determined, and multiple peak temperatures are obtained.

[0068] In this step, according to the actual cable tunnel fire situation, a multi-physical field coupled cable tunnel fire simulation model is established, and the peak temperature that can be reached by the insulation layer of the cable at different positions is obtained.

[0069] In an alternative embodiment, step 1: According to the actual cable tunnel fire situation, a cable tunnel fire simulation model is established, the peak temperature of the insulation layer of the simulation cable at each of the multiple typical positions in the cable tunnel fire simulation model is determined, and multiple peak temperatures are obtained, comprising the following steps:

[0070] Step 1.1: According to the actual cable tunnel fire situation, a cable tunnel fire simulation model is established, wherein the structure of the cable tunnel fire simulation model is: one side four-layer support, middle passage, and the other side four-layer support, the lowermost support of the one side four-layer support is taken as the first layer support, 3 simulation cables are arranged on each layer support of the one side four-layer support, and the radii of the simulation cables on each layer are different.

[0071] Step 1.2: The middle joint of the simulation cable at the middle position on the first layer support is taken as the fire source position, a fireproof partition is arranged above the fire source, and the cable tunnel fire simulation is started.

[0072] Step 1.3: According to the cable tunnel simulation, the temperature change curves of the insulation layers of the simulation cables at a plurality of typical positions are determined, and the peak temperatures of the insulation layers of the simulation cables at the plurality of typical positions are determined according to the temperature change curves of the insulation layers of the simulation cables at the plurality of typical positions, to obtain a plurality of peak temperatures, wherein the plurality of typical positions of the simulation cables include: three simulation cables of the fourth layer support of the other side four-layer support, the simulation cable of the third layer support of the other side four-layer support close to the middle aisle, and the simulation cable of the second layer support of the other side four-layer support close to the cable tunnel wall surface.

[0073] Optionally, according to the cable tunnel fire situation, a multi-physical field coupled cable tunnel fire simulation model is established to obtain the temperature change curves of the insulation layers of the adjacent cables in the short-time over-temperature state under different working conditions. Then, according to the temperature change curves, test samples of the insulation materials subjected to short-time over-temperature treatment are prepared. The specific steps are as follows: a simplified cable tunnel fire simulation model is established, the outside of the tunnel is concrete with a thickness of d1, and the outside of the concrete is soil with a thickness of d2. Four layers of supports are arranged on both sides of the tunnel, and three cables are arranged on each layer, with the radii of the cables from top to bottom being r1, r2, r3, and r4 mm. The fire situation of the middle joint of the first layer of cables in the tunnel is simulated, with the fire power being P and the action time being T. A fireproof L-shaped partition is arranged above the fire source, with the length of the partition being L1, the thickness being d3, and the side plate height being h1. The thermal physical properties of the cable materials and the fireproof partition are shown in Table 1:

[0074] Table 1 Thermal physical properties of cable materials and fireproof partition

[0075]

[0076] Fire simulation is performed, and when the heat release rate of the fire source is stable, the maximum temperature in the area near the fire source can reach T max . The second layer of cable laying fireproof partition effectively blocks the vertical spread of fire, and under the action of convective heat transfer, the cold air around the fire source promotes the diffusion of heat to the aisle, and a large amount of heat collects at the top of the tunnel, forming a ceiling jet effect. Ultimately, the cables on the unburned side are more susceptible to the influence of high-temperature hot air, and the third and fourth layers of cables close to the top of the tunnel are more severely damaged. In the tunnel arrangement, the fire extinguishing bomb is suspended above the cable joint close to the ceiling, and the temperature triggering of the temperature-sensitive glass ball of the fire extinguishing bomb is T t . When the ambient temperature of the tunnel continuously reaches this temperature, the fire extinguishing bomb will be triggered after a certain delay. The cable fire is gradually extinguished, and the temperature of the tunnel begins to drop.

[0077] Step 2: Build a cable insulation material over-temperature test platform, and perform multiple over-temperature tests according to the plurality of peak temperatures obtained in test step 1 to obtain a plurality of over-temperature tested samples;

[0078] In this step, a cable insulation material over-temperature test platform is built, and according to the peak temperature obtained by simulation, test samples of insulation materials subjected to different short-time over-temperature treatment are prepared.

[0079] In an alternative embodiment, step 2: build a cable insulation material over-temperature test platform, and perform multiple over-temperature tests according to the multiple peak temperatures obtained in step 1 to obtain multiple over-temperature tested samples, including the following steps:

[0080] Step 2.1: Build a cable insulation material over-temperature test platform, wherein the cable insulation material over-temperature test platform includes a vacuum heating box, a vacuum pump, a nitrogen generator, and an air compressor.

[0081] Step 2.2: Place multiple original samples in the crucible in turn and place them in the vacuum heating box, and set the peak temperature in the vacuum heating box according to the multiple peak temperatures obtained in step 1, wherein the temperature rising rate of the vacuum heating box meets the predetermined temperature rising rate, and the absolute pressure in the vacuum heating box is adjusted by the vacuum pump and meets the predetermined pressure threshold.

[0082] Step 2.3: Perform over-temperature test on the original samples at different peak temperatures to obtain multiple over-temperature tested samples.

[0083] In this step, a cable insulation material processing experiment platform simulating short-time over-temperature of fire is built, and its main equipment includes a vacuum heating box, a vacuum pump, a nitrogen generator, and an air compressor. The box-type atmosphere furnace, the nitrogen generator, the air compressor, and the vacuum pump are connected according to the correct method. The cable insulation sample is placed in the crucible and then placed in the box-type atmosphere furnace. Close the furnace door and connect the power supply. Open the vacuum pump and the air valve, and close when the absolute pressure in the box is reduced to Pa. Set the temperature rising rate of the box-type atmosphere furnace to υ up , according to the peak temperature obtained by simulation, set the peak temperature of the box-type atmosphere furnace to T1, T2, …, Tn, respectively, to obtain test samples subjected to different short-time high temperature treatment. After the temperature rises, open the air compressor and the nitrogen generator, and open the air inlet valve and the pressure regulating valve when the nitrogen purity rises to 99.5%. Open the box door to take out the sample when the temperature cools down to room temperature.

[0084] Step 3: Test the six indicators of each of the multiple over-temperature tested samples, wherein the six indicators include activation energy, crystallinity, carbonyl index, breakdown field strength, crosslinking degree, and elongation at break.

[0085] In this step, the activation energy, crystallinity, carbonyl index, breakdown field strength, crosslinking degree, and elongation at break of the materials under different treatment conditions obtained in step 2 are tested to obtain test data.

[0086] In an alternative embodiment, step 3: testing the six indexes of each of the plurality of samples subjected to the thermal test, wherein the six indexes include the activation energy, the crystallinity, the carbonyl index, the breakdown field strength, the crosslinking degree and the elongation at break, comprises the following steps:

[0087] Step 3.1: using a simultaneous thermal analyzer to test the thermogravimetric curve of the target sample subjected to the thermal test, and according to the thermogravimetric curve and the Kissinger-Redfem integral method, and the formula of the relationship between the activation energy and the temperature: drawing a relationship diagram, and performing linear fitting, and the slope of the straight line after fitting is According to the slope of the straight line, the activation energy of the target sample subjected to the thermal test is obtained, and according to the above steps, the activation energy of each of the plurality of samples subjected to the thermal test is tested, wherein a is the weight loss rate, A is the pre-exponential factor, T is the Kelvin temperature, K and R are the gas constant, b is the heating rate, and E is the activation energy;

[0088] Step 3.2: using an X-ray diffraction test to measure the crystallinity of each of the plurality of samples subjected to the thermal test, and the calculation formula of the crystallinity is: Wherein, Xc is the crystallinity of the sample subjected to the thermal test, A1 is the amorphous peak area, A2 is the main crystalline peak area, and A3 is the secondary crystalline peak area;

[0089] Step 3.3: using a Fourier infrared spectrum test to measure the carbonyl index of each of the plurality of samples subjected to the thermal test, and the calculation formula of the carbonyl index is: Wherein, I is the carbonyl index, S1 is the area of the peak corresponding to the carbonyl functional group, and S2 is the area of the peak corresponding to the methylene group near 2 915 cm -1 of each of the samples subjected to the thermal test;

[0090] Step 3.4: the samples subjected to the thermal test are placed between the upper and lower symmetrical column-column electrodes in turn, and insulating oil is poured into the oil cup, and the oil surface height is higher than the samples subjected to the thermal test and the column-column electrodes, and the voltage is increased by 1-2 kilovolts per pole from 0 until the sample subjected to the thermal test is broken down, and the breakdown test of the sample subjected to the thermal test is repeated for 10 times, and 10 breakdown voltages of the sample subjected to the thermal test are obtained, and the breakdown probability distribution of the 10 breakdown voltages obeys the Weibull distribution, and the probability of the 10 breakdown voltages is calculated using the function: , and the breakdown field strength corresponding to the breakdown voltage with a failure probability of 63.2% is selected as the breakdown field strength of the sample subjected to the thermal test, and the breakdown field strength of each of the plurality of samples subjected to the thermal test is tested according to the method of the step, wherein F(i, n) is the breakdown probability, i is the sample serial number, and n is the total number of samples;

[0091] Step 3.5: The sample after the temperature test is placed in a stainless steel mesh and put into a xylene solution at 110°C for extraction for 24h. After successful extraction, the sample is dried in an oven at 110°C for 24h. The crosslinking degree of the sample after the temperature test is calculated according to the formula: The crosslinking degree of the sample after the temperature test is calculated according to the formula, and the crosslinking degree of each of a plurality of samples after the temperature test is tested according to the method of this step, wherein M1 is the mass of the mesh bag, M2 is the mass of the sample after the temperature test and the mesh bag before extraction, and M3 is the mass of the sample after the temperature test and the mesh bag after extraction;

[0092] Step 3.6: The elongation at break of the sample after the temperature test is measured by a tensile test. The sample after the temperature test is cut into a dumbbell shape with a thickness of 1mm. The test tensile rate is 200mm / min. The elongation at break of the sample after the temperature test is calculated according to the formula: The elongation at break of the sample after the temperature test is calculated according to the formula, and the elongation at break of each of a plurality of samples after the temperature test is tested according to the method of this step, wherein ε t is the elongation at break of the sample after the temperature test, △L b is the elongation within the gauge length of the sample after the temperature test at the time of break, i.e. the travel read at the time of break, and L0 is the gauge length.

[0093] Optionally, the activation energy, crystallinity, carbonyl index, breakdown field strength, crosslinking degree and elongation at break of the obtained sample are measured as follows:

[0094] (1) Activation energy:

[0095] The thermal gravimetric curves of different samples are measured by a simultaneous thermal analyzer. The temperature is raised from 30°C to 800°C at a rate of 10°C / min under high-purity nitrogen protection, and the mass of the sample is 5-6mg. The activation energy of different samples is calculated by the Kostas-Redfern integral method. The relationship between the activation energy and the temperature can be obtained from the thermal gravimetric curve as follows:

[0096]

[0097] In the formula, α is the weight loss rate; A is the pre-exponential factor; T is the Kelvin temperature, K; R is the gas constant, generally taken as 8.314J / (mol·k); β is the heating rate, which is 10K / min in this experiment; E is the activation energy, J / mol; a relationship graph is drawn, the slope of the fitted straight line is The activation energy can be calculated according to the slope.

[0098] (2) Crystallinity:

[0099] The crystallinity of the sample was measured by X-ray diffraction experiment. The sample size was 10 mm x 10 mm, the thickness was 1 mm, the X-ray tube used a Cu target, the scanning rate was 10° / min, and the scanning range was 10°-30°. The calculation of the crystallinity is shown in (2):

[0100]

[0101] In the formula, Xc is the crystallinity of the sample; A1 is the amorphous peak area; A2 is the main crystalline peak area; and A3 is the secondary crystalline peak area.

[0102] (3) Carbonyl index:

[0103] The carbonyl index of the sample was measured by Fourier infrared spectroscopy experiment. The scanning wave number was set to 4000-600 cm -1 . Before testing, the sample was placed in a 50°C oven for 6 h to remove moisture from the sample. The calculation of the carbonyl index is shown in (3):

[0104]

[0105] In the formula, I is the carbonyl index; S1 is the area of the peak corresponding to the carbonyl functional group; and S2 is the area of the peak corresponding to the methylene group near 2 915 cm -1 .

[0106] (4) Breakdown field strength:

[0107] The sample size was 5 cm * 5 cm, and the thickness was 1 mm. During the experiment, the sample was placed between the upper and lower symmetric column-column electrodes, the electrode diameter was 25 mm, the insulating oil was poured into the oil cup, the oil surface height needed to be higher than the experimental sample and the column-column electrode, the voltage was started from 0 and gradually increased by 1-2 kV each time, until the sample was broken down, at this time the breakdown field strength was taken as the breakdown field strength of the sample, and each sample was measured 10 times. The breakdown voltage probability distribution obeys the Weibull distribution, and the probability value of the Weibull distribution data points is calculated using the function as shown in (4):

[0108]

[0109] In the formula: F(i, n) is the breakdown probability, i is the sample number; and n is the total number of samples. The breakdown field strength with a failure probability of 63.2% was selected as the breakdown field strength of the sample.

[0110] (5) Crosslinking degree:

[0111] According to the provisions of JB / T 10437-2004, about 0.5 g of the sample was taken, the sample was placed in a stainless steel wire mesh and immersed in a 110°C xylene solution for 24 h, and after successful extraction, the sample was dried in a 110°C oven for 24 h. The crosslinking degree was calculated according to formula (5):

[0112]

[0113] In the formula, M1 is the mass of the bag; M2 is the mass of the sample before extraction and the bag; and M3 is the mass of the sample after extraction and drying and the bag.

[0114] (6) Elongation at break:

[0115] The elongation at break of the sample is measured by tensile testing, and the sample is cut into a dumbbell shape according to the provisions of GB / T 2951.11-2008, the sample thickness is 1 mm, and the experimental tensile rate is 200 mm / min. The calculation of the elongation at break is shown in formula (6):

[0116]

[0117] In the formula, ε t is the elongation at break of the sample, △L b is the elongation within the gauge length when the sample breaks, i.e. the travel read at break, and L0 is the gauge length. The various performance indicators of the sample are shown in Table 2:

[0118] Table 2: Various indicator parameters of the sample

[0119]

[0120] Step 4: Establishing a three-dimensional periodic amorphous unit cell containing a plurality of cross-linked polyethylene molecular chains, and processing the three-dimensional periodic amorphous unit cell containing a plurality of cross-linked polyethylene molecular chains to obtain a final three-dimensional periodic amorphous unit cell, and calculating the mean square displacement variation law of the final three-dimensional periodic amorphous unit cell at different temperatures, and dividing the temperature interval according to the mean square displacement variation law to obtain a plurality of temperature intervals;

[0121] In this step, a cross-linked polyethylene model is established by molecular dynamics simulation, and the variation law of the mean square displacement of cross-linked polyethylene with temperature is simulated. The mean square displacement reflects the motion of the molecule, and the thermal motion of the molecule is the basis of the properties of the material. Therefore, the temperature variation interval is divided according to the variation trend of the mean square displacement with temperature.

[0122] In an alternative embodiment, step 4.1: setting a force field and charge for the cross-linked polyethylene molecular chain, and establishing a three-dimensional periodic amorphous unit cell containing a plurality of cross-linked polyethylene molecular chains, wherein the cross-linked polyethylene molecular chain is a H-type simplified cross-linked polyethylene molecular chain;

[0123] Step 4.2: structure optimization and energy minimization are performed on the three-dimensional periodic amorphous unit cell, and then the structure-optimized and energy-minimized three-dimensional periodic amorphous unit cell is subjected to multiple cycle annealing processes, and energy minimization is performed in each step of the annealing process, to obtain an annealed and energy-minimized three-dimensional periodic amorphous unit cell; the annealed and energy-minimized three-dimensional periodic amorphous unit cell is subjected to kinetic simulation with a time of ta and a temperature of Td, and kinetic simulation with a time of tb, a temperature of Td and a pressure of Pb in sequence, to obtain a three-dimensional periodic amorphous unit cell that is energy stable under the conditions of a temperature of Td and a pressure of Pb;

[0124] Step 4.3: kinetic simulation with a time of tc and a pressure of Pc is performed on the energy-stable three-dimensional periodic amorphous unit cell at different temperatures, and then kinetic simulation with a time of td and a pressure of Pc is performed, to obtain a final three-dimensional periodic amorphous unit cell, and the mean square displacement change rule of the final three-dimensional periodic amorphous unit cell at different temperatures is calculated, wherein the intervals between different temperatures are consistent.

[0125] Step 4.4: the temperature intervals are divided by the mean square displacement change rule, to obtain a plurality of temperature intervals.

[0126] Optionally, cross-linked polyethylene is a high-molecular polymer with a large degree of polymerization and a three-dimensional network structure. In order to reduce the complexity in the simulation process, a H-shaped simplified cross-linked polyethylene molecule is constructed. The COMPASS III force field in the molecular mechanics tool (FORCITE module) is used to set the force field and charge of the cross-linked polyethylene molecular chain. As shown in FIG. 2, an amorphous cell tool (Amorphous Cell module) is used to establish a three-dimensional periodic amorphous unit cell model containing k cross-linked polyethylene molecular chains optimized above, and the density is set to p. Figure 7

[0127] The molecular mechanics tool (FORCITE module) is used to perform structure optimization and energy minimization on the cross-linked polyethylene unit cell model, and the maximum number of iterations is set to f times. Then the optimized cross-linked polyethylene unit cell is subjected to g times of cycle annealing from temperature Ta to Tb, and the temperature gradient is Ti, and the model energy minimization is performed in each step of the annealing process. The cross-linked polyethylene unit cell model with the minimum energy after annealing is subjected to NVT kinetic simulation with a time of ta and a temperature of Td, and then NPT kinetic simulation with a time of tb, a temperature of Td and a pressure of Pb, to obtain an energy-stable cross-linked polyethylene unit cell model under the conditions of a temperature of Td and a pressure of Pb.

[0128] ​The temperature is set as T1, T2, …, Tn, and the cross-linked polyethylene cell model is subjected to NVT dynamic simulation for a time tc and NPT dynamic simulation for a time td at different temperatures, the pressure of the NPT ensemble is set as Pc, so as to obtain the structural conformation of the cross-linked polyethylene cell at different temperatures, and the mean square displacement variation law of the cross-linked polyethylene cell at different temperatures is calculated by a molecular mechanics tool (FORCITE module), wherein the NPT dynamic simulation refers to simulation under the condition that the temperature and the pressure are constant. The NVT dynamic simulation refers to simulation under the condition that the volume, the temperature and the particle number are constant, and is also referred to as an NVT ensemble.

[0129] The temperature interval is divided into [T1, T2], [T2, T3], …, [Tn-1, Tn] through the mean square displacement variation law, and the variation law of different properties of the cross-linked polyethylene in different temperature intervals is analyzed, so as to provide a basis for selection of subsequent evaluation model indexes.

[0130] Step 5: combining the six indexes of each of the plurality of temperature-tested samples obtained in test step 3 and the plurality of temperature intervals obtained in test step 4, to determine the main influence indexes of each of the plurality of temperature intervals.

[0131] In this step, the variation law of different cross-linked polyethylene samples in the temperature intervals obtained in step 4 is analyzed, and the main influence parameters in each temperature interval are determined as subsequent evaluation indexes.

[0132] In an alternative embodiment, step 5: combining the six indexes of each of the plurality of temperature-tested samples obtained in step 3 and the plurality of temperature intervals obtained in step 4, to determine the main influence indexes of each of the plurality of temperature intervals, includes:

[0133] Step 5.1: a linear model y = f j (x) = mx + b j is established. j The six indexes of the plurality of temperature intervals are linearly fitted to obtain a plurality of fitting curves, wherein x is temperature data, test Test Test y ij is the specific data of the jth index at the ith temperature, test n represents the number of temperature points, test ∑x i y ij is the sum of the products of all x i and y ij , test ∑x i and test ∑y ij are the sums of all x i and y ij values, respectively, test (∑x i) 2 is the sum of squares of all x i values.

[0134] Step 5.2: Calculate R 2 of each fitted curve to measure the fitting effect of the linear model of the test index. The calculation formula is: wherein, test represents the fitting result of the linear model of the test index, test represents the average number, and test R 2 is closer to 1, the better the fitting effect is;

[0135] Step 5.3: According to the R 2 value of each fitted curve of the test, determine the main influencing index of each temperature interval of the test.

[0136] Optionally: Linear fitting is performed on the indexes in different temperature intervals. First, assume that the linear model of the jth index is:

[0137] y = f j (x) = mx j + b j (7)

[0138] wherein y ij represents the specific data of the jth index at the ith temperature, and x represents the temperature data. The parameters m j and b j are obtained to determine the linear model of the index, wherein:

[0139]

[0140] wherein n represents the number of temperature points, i.e. the number of data points; ∑x i y ij is the sum of the products of x i and y ij of all data points, ∑x i and ∑y ij are the sum of all x i and y ij values, respectively, (∑x i ) 2 is the sum of squares of all x i values.

[0141] Calculate R 2 of each fitted curve to measure the fitting effect of the linear model. The calculation formula is:

[0142]

[0143] In the formula, test represents the prediction result of the established linear model. R2 The closer to 1, the better the fitting effect. Define R 2 >e, the index has a good correlation with temperature.

[0144] According to R 2 value and the defined R 2 value range of good correlation, determine the main influencing index of each temperature interval, that is, when in the temperature interval [T x , T y ], if the linear correlation coefficient R 2 of the index j with temperature is greater than e, the index j is regarded as the main influencing index in the temperature interval [T x , T y ], and the index j can be used as the evaluation index under the temperature interval [T x , T y ].

[0145] Step 6: According to the main influencing index of each temperature interval of the test determined in step 5, determine the weight corresponding to each main index, determine the road degradation degree score of the test sample cable according to the multiple performance indexes of the sample cable and the weight corresponding to each main index of the test, and determine the degradation degree of the test sample cable according to the test degradation degree score and the pre-determined degradation degree evaluation table.

[0146] In this step, according to the main influencing index in different temperature intervals determined in step 5, the coefficient of variation method is used to give each index a corresponding weight, to calculate the degradation degree score, to establish a degradation degree evaluation table, and to evaluate the cable insulation degradation degree.

[0147] In an alternative embodiment, step 6: According to the main influencing index of each temperature interval of the test determined in step 5, determine the weight corresponding to each main index, determine the road degradation degree score of the test sample cable according to the multiple performance indexes of the sample cable and the weight corresponding to each main index of the test, and determine the degradation degree of the test sample cable according to the test degradation degree score and the pre-determined degradation degree evaluation table, including the following steps:

[0148] Step 6.1: According to the main influencing index of each temperature interval of the test, build the original matrix of each temperature interval of the test, get multiple original matrices, and normalize each of the test multiple original matrices, calculate the average value and standard deviation of each main influencing index according to the normalized multiple original matrices, and calculate the coefficient of variation of each main influencing index according to the average value and standard deviation of each main influencing index of the test, and calculate the weight of each main influencing index according to the coefficient of variation of each main influencing index;

[0149] Step 6.2: Determine the values of the plurality of performance indicators of the test sample cable and normalize the plurality of performance indicators of the test sample cable, and according to the plurality of performance indicators of the normalized sample cable and the weight of each main influencing indicator, determine the cable insulation deterioration degree score S of the test sample cable;

[0150] Step 6.3: According to the test deterioration degree score S and the predetermined deterioration degree evaluation table, determine the deterioration degree of the test sample cable.

[0151] Optionally, an original data matrix X, x ij is the value of the jth indicator of the ith sample.

[0152]

[0153] In order to eliminate the influence of different dimensions and orders of magnitude on data analysis, the minimum-maximum normalization method is used to normalize each indicator. For positive indicators and negative indicators, normalization needs to be performed in different ways, and the calculation method is shown in formula (12),

[0154]

[0155] The normalized matrix Y obtained by formula (12) is shown in formula (13):

[0156]

[0157] The coefficient of variation of each indicator is calculated, and the calculation method is as follows:

[0158] The average value of each indicator is calculated The calculation method is shown in formula (14):

[0159]

[0160] The standard deviation S of each indicator is calculated j , and the calculation method is shown in formula (15):

[0161]

[0162] The coefficient of variation V of each indicator is calculated j , and the calculation method is shown in formula (16):

[0163]

[0164] According to the coefficient of variation V of each indicator j , the weight W of each indicator is calculated j , and the calculation method is shown in formula (17):

[0165]

[0166] The degradation degree of the cable insulation actually experiencing the fire over-temperature environment is evaluated, the peak temperature experienced by the cable insulation is determined, the performance indicators that need to be measured are determined, the degradation degree score is obtained according to the weights of the indicators, and the degradation degree of the cable insulation is evaluated according to the degradation degree evaluation table.

[0167] The specific steps are as follows: for the cable actually experiencing the fire over-temperature environment, the peak temperature of the insulation layer of the cable during the fire is determined, the corresponding values P1, P2, …, P i , and finally the degradation degree score S of the cable insulation after experiencing the fire over-temperature environment is obtained by weighting, and the specific calculation steps are as follows:

[0168] The sample matrix X and P1, P2, …, P i are combined, the measured indicators are normalized according to formula (13), and P1, P2, …, P i are recorded. n .

[0169] According to N1, N2, N3, …, N n , the degradation degree score S of the cable insulation is obtained by formula (18) combined with the weights of the performance indicators:

[0170] S=w1*N1+w2*N2+w3*N3+…+w n *N n (18)

[0171] S is located in the interval [0, 1], and the closer the score is to 0, the more serious the degradation is, so the degradation degree evaluation standard is defined as shown in Table 3. According to the degradation degree score S, the degradation degree evaluation table shown in Table 3 is compared to evaluate the health status of the cable insulation.

[0172] Table 3 Degradation degree evaluation table

[0173]

[0174] When the degradation level is D and E, the cable does not need to be replaced; when the degradation level is B and C, the cable does not need to be replaced, but the inspection frequency needs to be improved, and whether the cable needs to be replaced is considered according to the subsequent operation; when the degradation level is A, the cable needs to be replaced in time.

[0175] Based on the above embodiments and optional embodiments, an optional implementation of the present application is provided,

[0176] Step 1, a simplified cable tunnel fire simulation model was established. The outside of the tunnel was concrete with a thickness of 0.1 m, and the outside of the concrete was soil with a thickness of 1 m. Four layers of supports were arranged on both sides of the tunnel, and three cables were arranged on each layer. The radii of the cables from top to bottom were 20, 20, 42, and 50 mm, respectively. The fire simulation was performed to simulate the fire at the middle joint of the first layer of cables in the tunnel. The fire power was set to 200 kW, and the action time was 500 s. A fireproof L-shaped partition was arranged above the fire source. The partition was 1.2 m long, 5 mm thick, and 200 mm high. The thermal physical properties of the cable materials and the fireproof partition are shown in Table 4. The cable tunnel simulation model is shown in Figure 2 .

[0177] Table 4 Thermal physical properties of cable materials and fireproof partition

[0178]

[0179] The temperature distribution in the tunnel when the heat release rate of the fire source was stable is shown in Figure 3 . It can be seen that the maximum temperature in the area near the fire source can reach 700°C. The fireproof partition on the second layer of 110 kV cables effectively blocks the vertical spread of the fire, and under the action of convective heat transfer, the cold air around the fire source promotes the diffusion of heat to the aisle, and a large amount of heat collects at the top of the tunnel, forming a ceiling jet effect. Ultimately, the cables on the unburned side are more susceptible to the influence of high-temperature hot air, and the third and fourth layers of 10 kV cables near the top of the tunnel are more severely damaged.

[0180] Based on the temperature distribution in the tunnel, typical fourth layer aisle, fourth layer middle, fourth layer wall, third layer aisle, and second layer wall cables were selected as examples. The temperature variation of the insulation layer at the bottom of the cable was obtained, as shown in Figure 4 . It can be seen that the temperature rising trend and rate of the cable insulation layer at the four monitoring points are basically consistent, but the maximum temperature reached is significantly different. The maximum temperatures of the fourth layer aisle, fourth layer middle, fourth layer wall, third layer aisle, and second layer wall are 392°C, 339°C, 298°C, 243°C, and 195°C, respectively. In the typical arrangement of the tunnel, the fire extinguishing bomb is suspended above the cable joint near the ceiling, and the temperature triggering of the temperature-sensitive glass ball of the fire extinguishing bomb is 68°C. When the temperature of the tunnel environment continuously reaches this temperature, the fire extinguishing bomb will be triggered after a certain delay. The cable fire is gradually extinguished, and the temperature of the tunnel begins to drop. The cooling process of the above-mentioned five monitoring points is shown in Figure 3 , and the cooling rate also has a large difference.

[0181] Step 2, an experimental platform for simulating short-time over-temperature of cable insulation materials was built. The main equipment includes a vacuum heating box, a vacuum pump, a nitrogen generator, and an air compressor. The box-type atmosphere furnace, nitrogen generator, air compressor, and vacuum pump were connected according to the correct method, as shown inFigure 5 The cable insulation sample is placed in the crucible and then in the box-type atmosphere furnace. The furnace door is closed and the power is turned on. The vacuum pump and the air exhaust valve are opened, and the absolute pressure in the box is reduced to 0.005 MPa (1 / 20 of atmospheric pressure) when it is closed. The temperature rising rate of the box-type atmosphere furnace is set to 40°C / min, and the peak temperature of the box-type atmosphere furnace is set to 100°C, 125°C, 150°C, …, 400°C according to the simulation peak temperature, to obtain the samples after different short-time high-temperature treatment. After the temperature rises, the air compressor and the nitrogen generator are turned on, and the nitrogen purity is increased to 99.5% when the inlet valve and the pressure regulating valve are opened. When the temperature cools down to room temperature, the box door is opened to take out the sample.

[0182] Step 3: The activation energy, crystallinity, carbonyl index, breakdown field strength, crosslinking degree and elongation at break of the materials treated in step 1 are tested respectively, and the parameters of each sample are shown in Table 5:

[0183] Table 5 Experimental parameters of different samples

[0184]

[0185] Step 4: A crosslinked polyethylene model is established by molecular dynamics simulation, and the variation of the mean square displacement of crosslinked polyethylene with temperature is simulated. The temperature variation interval is divided by the variation trend of the mean square displacement. Step 4 includes the following steps:

[0186] Step 4.1: Crosslinked polyethylene is a high molecular polymer with high degree of polymerization and three-dimensional network structure. In order to reduce the complexity in the simulation process, a H-shaped simplified crosslinked polyethylene molecule is constructed, as shown in Figure 6 .

[0187] Step 4.2: The COMPASS III force field in the FORCITE module is used to set the force field and charge of the crosslinked polyethylene molecular chain. An amorphous cell module is used to establish a three-dimensional periodic amorphous unit cell containing 80 crosslinked polyethylene molecular chains optimized above, and the density is set to 0.93 g / cm 3 .

[0188] Step 4.3: Using Geometry Optimization in the FORCITE module, the cross-linked polyethylene (CPE) unit cell model was structurally optimized and its energy minimized, with a maximum iteration count of 20,000. The optimized CPE unit cell model was then subjected to five cyclic annealing cycles from 100K to 600K, with a temperature gradient of 50K and an NVT ensemble. Energy minimization was performed in each annealing step. The CPE unit cell model with the lowest energy after annealing was first subjected to an NVT kinetic simulation for 200 ps at 25°C, followed by an NPT kinetic simulation for 200 ps at 25°C and 0.1 MPa. This yielded the energy-stable model of the CPE unit cell at 25°C and 0.1 MPa. Figure 7 As shown.

[0189] Step 4.4: Set the temperature to 100℃, 125℃, 150℃…, 400℃. At each temperature, perform a 50ps NVT kinetic simulation and a 200ps NPT kinetic simulation on the cross-linked polyethylene (CPE) unit cell model obtained in Step 4.3. The pressure of the NPT ensemble is set to 0.1MPa. This yields the structural conformation of the CPE unit cell at different temperatures. The mean square displacement variation of the CPE unit cell at different temperatures is calculated using the FORCITE module. The results are as follows: Figure 8 As shown.

[0190] Step 4.5: From Figure 8 It can be seen that the mean square displacement curve increases sharply from 200℃ to 225℃, and the mean square displacement changes drastically after 300℃. Therefore, the temperature range is divided into [100℃, 225℃], [225℃, 300℃], and [300℃, 400℃].

[0191] Step 5: Analyze the variation of various properties of different cross-linked polyethylene samples in the temperature range obtained in Step 4.5, and determine the main influencing parameters in each temperature range as subsequent evaluation indicators.

[0192] Step 5.1: By performing linear fitting on the indices within each temperature range, the fitted curve is shown below. Figure 9 As shown, the R-squared values ​​of each fitted curve are obtained. 2 The values ​​are shown in Table 6:

[0193] Table 6. R² values ​​of different fitted curves

[0194]

[0195] Step 5.2: Define when R 2 When the value is greater than 0.5, the index shows a good correlation with temperature.

[0196] Step 5.3: R 2 defined in step 5.2 2 The range of values with good correlation, determine the main influence index in the temperature interval of [100℃,225℃] is activation energy, crystallinity, breakdown field strength, crosslinking degree and elongation at break; the main influence index in the temperature interval of [225℃,300℃] is activation energy, crystallinity, crosslinking degree and elongation at break; the main influence index in the temperature interval of [300℃,400℃] is crystallinity, carbonyl index and breakdown field strength.

[0197] Step 6, according to the main influence index of each temperature interval determined in step 5, the variation coefficient method is used to calculate the variation coefficient of each index.

[0198] The specific steps are as follows:

[0199] First, determine the weight of each main influence index in the temperature interval of [100℃,225℃]:

[0200] Step 6.1: According to the experimental data obtained in table 5 and the main influence index in the temperature interval of [100℃,225℃] determined in step 5.4, establish the original data matrix X, x ij is the value of the jth index of the ith sample, and each column represents the index of activation energy, crystallinity, breakdown field strength, crosslinking degree and elongation at break. The matrix X is shown in formula (19).

[0201]

[0202] Step 6.2: According to formula (12), normalize each index, and the normalized matrix Y is:

[0203]

[0204] Step 6.3: Calculate the variation coefficient of each index, and determine the importance of each index according to the variation coefficient, the specific method is as follows:

[0205] According to formula (21), the average value of each index is obtained:

[0206]

[0207] According to formula (22), the standard deviation of each index is obtained:

[0208] S j =(0.40,0.38,0.42,0.40,0.38) (22)

[0209] According to formula (23), the variation coefficient of each index is calculated from the average value and the standard deviation:

[0210] V j = (0.87, 0.90, 0.82, 0.82, 0.69) (23)

[0211] Step 6.4: Calculate the weight of each index according to the coefficient of variation of each index obtained in step 6.3 by formula (24):

[0212] W j = (0.21, 0.22, 0.20, 0.20, 0.17) (24)

[0213] Therefore, in the temperature range of [100℃, 225℃], the weights of activation energy, crystallinity, breakdown field strength, crosslinking degree and elongation at break are 0.21, 0.22, 0.20, 0.20 and 0.17, respectively. Similarly, in the temperature range of [225℃, 300℃], the weights of activation energy, crystallinity, crosslinking degree and elongation at break are 0.25, 0.23, 0.30 and 0.22, respectively; in the temperature range of [300℃, 400℃], the weights of crystallinity, carbonyl index and breakdown field strength are 0.34, 0.34 and 0.32, respectively.

[0214] Step 6.5: Evaluate the degradation degree of cable insulation actually experienced in fire temperature environment. According to the peak temperature experienced by cable insulation, combine step 4 to determine the performance indicators that need to be measured, normalize the indicators, and calculate the degradation degree score according to the weights of each index obtained in step 5. The specific steps are as follows:

[0215] The highest temperature of the insulation layer of a certain cable in a fire is 330℃. In the temperature range of [300℃, 400℃], the crystallinity, carbonyl index and breakdown field strength are determined by step 3, and the measured results are crystallinity P1 = 40.12%, carbonyl index P2 = 0.030, and breakdown field strength P3 = 61.92. The normalized values of each index are N1 = 0.59, N2 = 0.17 and N3 = 0.85 obtained by formula (13). The degradation degree score is S = 0.44 obtained by formula (18). According to Table 3, the degradation degree is C level, and the cable does not need to be replaced, but the inspection frequency needs to be increased, and whether to replace the cable needs to be considered according to the subsequent operation.

[0216] The above-mentioned optional embodiments at least achieve the following effects: (1) the general cable insulation performance evaluation method mainly considers material aging, among which the thermal aging is mainly studied, a large number of thermal aging tests are carried out during the test, and different thermal aging performances are analyzed, but these studies are at about 180℃ at most, and the material degradation characteristics at a higher temperature are considered in the present patent, which is different from long-term aging at this time, because the crosslinking structure changes due to exceeding the phase transition temperature, which is quite different from the existing thermal aging, the present patent carries out tests in a higher temperature range, and the time length is controlled, which is more than 24 hours in general thermal aging, and can more accurately reflect the insulation degradation in the special case of short-time over-temperature in a fire environment;

[0217] (2) the test shows that the important index parameters reflecting the degradation performance are quite different in different temperature ranges, therefore, the present patent considers more accurate evaluation, considers the essence of material structure, divides the temperature change range by the change trend of molecular mean square displacement with temperature, then analyzes the correlation of each index with temperature in each temperature range, and selects the characteristic quantity with good correlation as the basis for insulation performance degradation evaluation, which is more accurate and effective than general cable insulation evaluation.

[0218] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a group of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0219] In the present embodiment, a cable insulation performance degradation evaluation device after short-time over-temperature in a fire environment is also provided, which is used to realize the above-mentioned embodiments and preferred embodiments, and will not be described again. As used below, the term "module" "device" can be a combination of software and / or hardware that realizes a predetermined function. Although the device described in the following embodiments is preferably realized in software, the realization of hardware, or a combination of software and hardware, is also possible and conceived.

[0220] According to the embodiment of the present application, a device embodiment for implementing the cable insulation performance degradation evaluation method after short-time over-temperature in a fire environment is also provided, Figure 10 is a schematic diagram of a cable insulation performance degradation evaluation device after short-time over-temperature in a fire environment according to an embodiment of the present application, as Figure 10 shown, the above-mentioned cable insulation performance degradation evaluation device after short-time over-temperature in a fire environment comprises a first determination module 101, an over-temperature test module 102, a test module 103, a division module 104, a second determination module 105, a third determination module 106, and the device will be described below.

[0221] The first determination module 101 is configured to establish a cable tunnel fire simulation model by imitating a real cable tunnel fire situation, and obtain peak temperatures of insulating layers of simulation cables at a plurality of typical positions in the test cable tunnel fire simulation model, to obtain a plurality of peak temperatures.

[0222] The over-temperature test module 102 is connected with the first determination module 101, and is configured to build an over-temperature test platform for cable insulating materials, and perform a plurality of over-temperature tests according to the plurality of peak temperatures obtained in step 1, to obtain a plurality of over-temperature tested samples.

[0223] The test module 103 is connected with the over-temperature test module 102, and is configured to test six indexes of each of the plurality of over-temperature tested samples, wherein the six indexes include activation energy, crystallinity, carbonyl index, breakdown field strength, crosslinking degree and elongation at break.

[0224] The division module 104 is connected with the test module 103, and is configured to establish a three-dimensional periodic amorphous unit cell containing a plurality of test crosslinked polyethylene molecular chains, process the three-dimensional periodic amorphous unit cell containing the plurality of test crosslinked polyethylene molecular chains, obtain a final three-dimensional periodic amorphous unit cell, calculate a mean square displacement change rule of the final three-dimensional periodic amorphous unit cell at different temperatures by using a FORCITE module, and divide temperature intervals according to the mean square displacement change rule, to obtain a plurality of temperature intervals.

[0225] The second determination module 105 is connected with the division module 104, and is configured to determine main influence indexes of the plurality of temperature intervals according to the six indexes of each of the plurality of over-temperature tested samples obtained in step 3 and the plurality of temperature intervals obtained in step 4.

[0226] The third determination module 106 is connected with the second determination module 105, and is configured to determine a weight corresponding to each main index according to the main influence indexes of the plurality of temperature intervals determined in step 5, determine a road degradation degree score of the test sample cable according to a plurality of performance indexes of the sample cable and the weight corresponding to each main index, and determine a degradation degree of the test sample cable according to the degradation degree score and a pre-determined degradation degree evaluation table.

[0227] The cable insulation performance deterioration evaluation device after short-time overheating in a fire environment provided by the embodiment has the following advantages: (1) the general cable insulation performance evaluation method mainly considers material aging, among which, thermal aging is studied more, and a large number of thermal aging tests are carried out during the test, and different thermal aging performances are analyzed, but these studies are at a maximum of about 180 DEG C, and the material deterioration characteristics at a higher temperature are considered in the patent, which is different from long-term aging at this time, because it exceeds the phase transition temperature, causing the crosslinking structure to change and be quite different from the existing thermal aging, the patent carries out tests in a higher temperature range, and the time length is controlled, and the general thermal aging is more than 24 hours, which can more accurately reflect the insulation deterioration in the special case of short-time overheating in a fire environment.

[0228] (2) At the same time, the test shows that the important index parameters reflecting the deterioration performance are quite different in different temperature ranges, so the patent considers more accurate evaluation, considers the essence of the material structure, divides the temperature change range by the change trend of the molecular mean square displacement with temperature, then analyzes the correlation of each index with temperature in each temperature range, and selects the characteristic quantity with good correlation as the basis for evaluating the insulation performance deterioration, which is more accurate and effective than the general cable insulation evaluation of various indexes.

[0229] It should be noted that the above-mentioned modules can be realized by software or hardware, for example, for the latter, the above-mentioned modules can be located in the same processor, or the above-mentioned modules are located in different processors in any combination.

[0230] It should be noted that the first determination module 101, the overheating test module 102, the test module 103, the division module 104, the second determination module 105 and the third determination module 106 correspond to steps 1 to 6 in the embodiment, and the above-mentioned modules and the corresponding steps have the same instances and application scenarios, but are not limited to the contents disclosed in the above-mentioned embodiment. It should be noted that the above-mentioned modules as part of the device can run in a computer terminal.

[0231] It should be noted that the optional or preferred embodiments of the present embodiment can refer to the related description in the embodiment, which will not be repeated here.

[0232] The cable insulation performance deterioration evaluation device after short-time overheating in a fire environment can further include a processor and a memory, the first determination module 101, the overheating test module 102, the test module 103, the division module 104, the second determination module 105 and the third determination module 106 are stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions.

[0233] The processor includes a core, and the core retrieves corresponding program units from the memory. The core can be one or more. The memory can include a non-permanent memory in a computer readable medium, a random access memory (RAM), and / or a non-volatile memory such as a read-only memory (ROM) or a flash memory (flash RAM), and the memory includes at least one memory chip.

[0234] The embodiment of the present application provides a non-volatile storage medium, which stores a program, and the program is executed by a processor to realize the cable insulation performance degradation evaluation method after short-time over-temperature in a fire environment.

[0235] As Figure 11 The embodiment of the present application provides an electronic device, and the electronic device 10 includes a processor, a memory, and a program stored in the memory and executable on the processor. The processor executes the program to realize the cable insulation performance degradation evaluation method after short-time over-temperature in a fire environment. The device in the present application can be a server, a PC, or the like.

[0236] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program codes.

[0237] The present application is described with reference to flowcharts and / or block diagrams of the method, device (system), and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one or more flows and / or blocks Figure 1 The means for implementing the functions specified in one or more flows and / or blocks.

[0238] These computer program instructions can also be stored in a computer readable memory capable of guiding a computer or other programmable data processing devices to work in a specific manner, so that the instructions stored in the computer readable memory produce a product including instruction means, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one or more flows and / or blocks Figure 1the function(s) specified in the block or blocks.

[0239] These computer program instructions can also be loaded into computer or other programmable data processing devices to cause a series of operational steps to be performed on the computer or other programmable devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable devices provide steps for implementing the flowchart Figure 1 the flowchart or flowchart and / or block Figure 1 the function(s) specified in the block or blocks.

[0240] In one typical configuration, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0241] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) about which the processor can execute instructions. The memory can also include non-volatile memory, such as read only memory (ROM), electrically programmable read only memory (EPROM), electrically erasable programmable read only memory (EEPROM), flash memory, or other memory technologies, CD-ROM, digital versatile disc (DVD), or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to store information for access by a computing device. In no case does the disclosure rely on any specific format of the non-transitory medium for the software module to execute the operations described herein. In no case does the disclosure rely on any specific format of the non-transitory medium for the software module to execute the operations described herein.

[0242] Computer readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically programmable read only memory (EEPROM), flash memory or other memory technologies, compact disc read only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to store information that can be accessed by a computing device. According to the definition herein, computer readable media does not include transitory media such as modulated data signals and carrier waves.

[0243] It should also be noted that the terms "comprising", "containing", or any other variant thereof, are intended to encompass non-exclusive inclusion, such that a process, method, article or apparatus that comprises a list of elements does not necessarily include only those elements in the list, but can include other elements not expressly listed or inherent to such process, method, article or apparatus. Without further limitation, an element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or apparatus that includes the element.

[0244] Those skilled in the art will appreciate that embodiments of the present application can be devised for a method, a system or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer readable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer readable program code thereon for use by or in connection with an instruction execution system. For the purposes of this description, a computer usable or computer readable storage medium can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The medium can be electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or apparatus or device) including a computer readable storage medium. Examples of a computer readable storage medium include an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or apparatus or device) including a computer readable storage medium.

[0245] The foregoing is merely illustrative of the principles of the application, and various modifications can be made by those skilled in the art without departing from the scope and spirit of the application. Any such modifications are intended to fall within the scope of the claims.

Claims

1. A method for evaluating deterioration of cable insulation performance after short-time overtemperature in a fire environment, characterized by, The method comprises the following steps: Step 1: A cable tunnel fire simulation model is established according to a real cable tunnel fire situation, and peak temperatures of insulating layers of simulation cables at multiple typical positions in the cable tunnel fire simulation model are determined to obtain multiple peak temperatures; Step 2: A cable insulation material over-temperature test platform is built, and multiple over-temperature tests are performed according to the multiple peak temperatures obtained in step 1 to obtain multiple over-temperature tested samples; Step 3: Six indexes of each of the multiple over-temperature tested samples are tested, wherein the six indexes include activation energy, crystallinity, carbonyl index, breakdown field strength, crosslinking degree and elongation at break; Step 4: A three-dimensional periodic amorphous unit cell containing multiple crosslinked polyethylene molecular chains is established, and the three-dimensional periodic amorphous unit cell containing multiple crosslinked polyethylene molecular chains is processed to obtain a final three-dimensional periodic amorphous unit cell, and the mean square displacement variation law of the final three-dimensional periodic amorphous unit cell at different temperatures is calculated, and the temperature intervals are divided according to the mean square displacement variation law to obtain multiple temperature intervals; Step 5: The six indexes of each of the multiple over-temperature tested samples obtained in step 3 and the multiple temperature intervals obtained in step 4 are combined to determine the main influence indexes of the multiple temperature intervals; Step 6: According to the main influence indexes of the multiple temperature intervals determined in step 5, the weight corresponding to each main index is determined, the performance indexes of the sample cable and the weight corresponding to each main index are used to determine the road degradation degree score of the sample cable, and the degradation degree score and the pre-determined degradation degree evaluation table are used to determine the degradation degree of the sample cable.

2. The method of claim 1, wherein, Step 1: A cable tunnel fire simulation model is established according to a real cable tunnel fire situation, and peak temperatures of insulating layers of simulation cables at multiple typical positions in the cable tunnel fire simulation model are determined to obtain multiple peak temperatures, comprising the following steps: Step 1.1: The cable tunnel fire simulation model is established according to the real cable tunnel fire situation, wherein the structure of the cable tunnel fire simulation model is: four-layer support on one side, middle aisle, four-layer support on the other side, the lowermost support of the four-layer support on one side is taken as the first layer support, 3 simulation cables are arranged on each layer of the four-layer support on one side, and the radii of the simulation cables on each layer are different; Step 1.2: The middle joint of the simulation cable at the middle position on the first layer support is taken as the fire source position, a fireproof partition plate is arranged above the fire source, and the cable tunnel fire simulation is started. Step 1.3: According to the cable tunnel simulation, determine the temperature change curve of the insulation layer of the simulation cable at each of the plurality of typical positions, and determine the peak temperature of the insulation layer of the simulation cable at each of the plurality of typical positions according to the temperature change curve of the insulation layer of the simulation cable at each of the plurality of typical positions, to obtain a plurality of peak temperatures, wherein the plurality of typical positions of the simulation cable include: three simulation cables of the fourth layer support of the other side four-layer support, the simulation cable of the third layer support of the other side four-layer support close to the middle aisle, and the simulation cable of the second layer support of the other side four-layer support close to the cable tunnel wall surface.

3. The method of claim 1, wherein, Step 2: Build a cable insulation material over-temperature test platform, and perform multiple over-temperature tests according to the plurality of peak temperatures obtained in step 1 to obtain a plurality of over-temperature tested samples, including the following steps: Step 2.1: Build the cable insulation material over-temperature test platform, wherein the cable insulation material over-temperature test platform includes a vacuum heating box, a vacuum pump, a nitrogen generator, and an air compressor; Step 2.2: Place a plurality of original samples in a crucible in sequence and in the vacuum heating box, and set the peak temperature in the vacuum heating box in sequence according to the plurality of peak temperatures obtained in step 1, wherein the temperature rising rate of the vacuum heating box meets a predetermined temperature rising rate, and the absolute pressure in the vacuum heating box is adjusted by the vacuum pump and meets a predetermined pressure threshold; Step 2.3: Perform the over-temperature test on the original samples at different peak temperatures to obtain the plurality of over-temperature tested samples.

4. The method of claim 1, wherein, Step 3: Test the six indicators of each of the plurality of over-temperature tested samples, wherein the six indicators include activation energy, crystallinity, carbonyl index, breakdown field strength, crosslinking degree, and elongation at break, including the following steps: Step 3.1: testing the thermogravimetric curve of the target sample subjected to the temperature test by using a simultaneous thermal analyzer, drawing a relationship graph according to the thermogravimetric curve and the Kissinger-Redfem integral method, and a formula of the relationship between the activation energy and the temperature, and performing linear fitting, a slope of the fitted straight line is , , a relationship between the activation energy and the temperature is , according to the slope of the straight line, obtaining the activation energy of the target sample subjected to the temperature test, testing the activation energy of each of the plurality of samples subjected to the temperature test according to the above steps, wherein a is the weight loss rate, A is the pre-exponential factor, T is the Kelvin temperature, K and R are the gas constant, β is the heating rate, and E is the activation energy; Step 3.2: The crystallinity of each of the plurality of temperature tested samples is measured using X-ray diffraction testing, the crystallinity being calculated according to the formula: wherein, A1 is the amorphous peak area, A2 is the main crystalline peak area, and A3 is the secondary crystalline peak area. Step 3.3: Measure the carbonyl index of each of the plurality of samples subjected to the heat test using Fourier infrared spectroscopy, the carbonyl index being calculated according to the formula: where I is the carbonyl index, S1 is the area of the peak corresponding to the carbonyl functional group, and S2 is the area of the peak corresponding to the methylene group near 2 915 cm −1 near 2 915 cm-1 of each of the plurality of samples subjected to the heat test. Step 3.4: the temperature-tested sample is placed between upper and lower symmetric column-column electrodes in turn, insulating oil is poured into the oil cup, the oil surface height is higher than the temperature-tested sample and the column-column electrode, the voltage is increased by 1-2 kV per pole from 0 until the temperature-tested sample is broken down, the breakdown test of the temperature-tested sample is repeated for 10 times, 10 breakdown voltages of the temperature-tested sample are obtained, the breakdown probability distribution of the 10 breakdown voltages obeys Weibull distribution, the function is as follows: , the probability of the 10 breakdown voltages is calculated, the breakdown field strength corresponding to the breakdown voltage with a failure probability of 63.2% is selected as the breakdown field strength of the temperature-tested sample, and the breakdown field strength of each of the plurality of temperature-tested samples is tested according to the method of this step, wherein F(i,n) is the breakdown probability, i is the sample number; n is the total number of samples; Step 3.5: The sample after the heat test is placed in a stainless steel mesh, put into a xylene solution at 110°C for extraction for 24 h, and after successful extraction, is placed in a 110°C oven for drying for 24 h. The crosslinking degree of the sample after the heat test is calculated according to the formula: , and the crosslinking degree of each of the plurality of samples after the heat test is tested according to the method of this step, wherein M1 is the mass of the bag, M2 is the mass of the sample after the heat test and the bag before extraction, and M3 is the mass of the sample after the heat test and the bag after extraction and drying. Step 3.6: The elongation at break of the temperature aged sample is measured using a tensile test, the temperature aged sample is cut into dumbbell shapes with a thickness of 1 mm, the test is performed at a tensile rate of 200 mm / min, and the elongation at break of the temperature aged sample is calculated according to the formula: , where ε t is the elongation at break of the temperature aged sample, ΔL b is the elongation within the gauge length of the temperature aged sample at break, i.e. the travel read at break, and L0 is the gauge length.

5. The method of claim 1, wherein, Step 4: Establish a three-dimensional periodic amorphous unit cell containing a plurality of crosslinked polyethylene molecular chains, and process the three-dimensional periodic amorphous unit cell containing a plurality of crosslinked polyethylene molecular chains to obtain a final three-dimensional periodic amorphous unit cell, and calculate the mean square displacement change law of the final three-dimensional periodic amorphous unit cell at different temperatures, and divide the temperature interval according to the mean square displacement change law to obtain a plurality of temperature intervals, including the following steps: Step 4.1: Set a force field and a charge for the crosslinked polyethylene molecular chain to establish the three-dimensional periodic amorphous unit cell containing a plurality of crosslinked polyethylene molecular chains, wherein the crosslinked polyethylene molecular chain is a H-type simplified crosslinked polyethylene molecular chain; Step 4.2: structure optimization and energy minimization settings are performed on the three-dimensional periodic amorphous unit cell, and then multiple cycle annealing treatments are performed on the structure optimized and energy minimized three-dimensional periodic amorphous unit cell, and energy minimization treatment is performed in each step of annealing treatment, to obtain an annealed and energy minimized three-dimensional periodic amorphous unit cell, and then kinetic simulation with a time of ta and a temperature of Td, and kinetic simulation with a time of tb, a temperature of Td and a pressure of Pb are sequentially performed on the annealed and energy minimized three-dimensional periodic amorphous unit cell, to obtain a three-dimensional periodic amorphous unit cell with stable energy under the condition of a temperature of Td and a pressure of Pb; Step 4.3: kinetic simulation with a time of tc and a pressure of Pc is performed on the energy stable three-dimensional periodic amorphous unit cell at different temperatures, and then kinetic simulation with a time of td and a pressure of Pc is performed, to obtain the final three-dimensional periodic amorphous unit cell, and the mean square displacement change rule of the final three-dimensional periodic amorphous unit cell at different temperatures is calculated, wherein the intervals between the different temperatures are consistent; Step 4.4: the temperature intervals are divided by the change rule of the mean square displacement, to obtain the plurality of temperature intervals.

6. The method of claim 1, wherein, Step 5: combining the six indexes of each of the plurality of samples subjected to the temperature test obtained in step 3 and the plurality of temperature intervals obtained in step 4, the main influencing indexes of each of the plurality of temperature intervals are determined, including: Step 5.1: Establishing the linear model of the indicators Linear fitting is performed on the six indicators of each of the temperature intervals to obtain a plurality of fitting curves, wherein x is the temperature data, , y ij is the specific data of the jth indicator at the ith temperature, n represents the number of temperature points, is the sum of the products of all and , and the are the sums of all and values, respectively, is the sum of squares of all values; Step 5.2: Calculate R of each fitted curve 2 The fitting effect of the index linear model is measured, and the calculation formula is: Wherein, represents the fitting result of the index linear model, represents the average number, R 2 The closer to 1 means the better the fitting effect; Step 5.3: determining the main impact indicator for each of the plurality of temperature intervals based on the R 2 values of the respective fitted curves.

7. The method of claim 1, wherein, Step 6: according to the main influencing indexes of each of the plurality of temperature intervals determined in step 5, the weight corresponding to each main index is determined, according to the plurality of performance indexes of the sample cable and the weight corresponding to each main index, the cable degradation degree score of the sample cable is determined, and according to the degradation degree score and the pre-determined degradation degree evaluation table, the degradation degree of the sample cable is determined, including the following steps: Step 6.1: according to the main influencing indexes of each of the plurality of temperature intervals, the original matrix of each of the plurality of temperature intervals is established, to obtain a plurality of original matrices, and the plurality of original matrices are normalized respectively, the average value and the standard deviation of each main influencing index are calculated according to the plurality of normalized original matrices, the coefficient of variation of each main influencing index is calculated according to the average value and the standard deviation of each main influencing index, and the weight of each main influencing index is calculated according to the coefficient of variation of each main influencing index; Step 6.2: the plurality of performance index values of the sample cable are determined and normalized, and the cable insulation degradation degree score S of the sample cable is determined according to the plurality of normalized performance index values of the sample cable and the weight of each main influencing index; Step 6.3: according to the degradation degree score S and the pre-determined degradation degree evaluation table, the degradation degree of the sample cable is determined.

8. A device for evaluating the degradation of cable insulation performance after short-term overheating in a fire environment, characterized in that, The device is applied to the cable insulation performance degradation evaluation method of the cable after short-time over-temperature in the fire environment of any one of claims 1 to 7, including: The first determining module is configured to establish a cable tunnel fire simulation model by imitating a real cable tunnel fire situation, and determine peak temperatures of insulating layers of simulated cables at a plurality of typical positions in the cable tunnel fire simulation model, to obtain a plurality of peak temperatures. The over-temperature test module is configured to build an over-temperature test platform for cable insulating materials, and perform a plurality of over-temperature tests according to the plurality of peak temperatures obtained in step 1, to obtain a plurality of over-temperature tested samples. The testing module is configured to test six indexes of the plurality of over-temperature tested samples, respectively, wherein the six indexes include activation energy, crystallinity, carbonyl index, breakdown field strength, crosslinking degree, and elongation at break. The dividing module is configured to establish a three-dimensional periodic amorphous unit cell containing a plurality of crosslinked polyethylene molecular chains, process the three-dimensional periodic amorphous unit cell containing the plurality of crosslinked polyethylene molecular chains, obtain a final three-dimensional periodic amorphous unit cell, calculate a mean square displacement change rule of the final three-dimensional periodic amorphous unit cell at different temperatures by using a FORCITE module, and divide temperature intervals according to the mean square displacement change rule, to obtain a plurality of temperature intervals. The second determining module is configured to determine main influence indexes of the plurality of temperature intervals, in combination with the six indexes of the plurality of over-temperature tested samples obtained in step 3 and the plurality of temperature intervals obtained in step 4. The third determining module is configured to determine a weight corresponding to each main index according to the main influence indexes of the plurality of temperature intervals determined in step 5, determine a road degradation degree score of a sample cable according to a plurality of performance indexes of the sample cable and the weight corresponding to each main index, and determine a degradation degree of the sample cable according to the degradation degree score and a pre-determined degradation degree evaluation table.

9. A non-volatile storage medium, characterized by, The non-volatile storage medium stores a plurality of instructions, and the instructions are adapted to be loaded and executed by a processor to implement the cable insulation performance degradation evaluation method after short-time over-temperature in a fire environment according to any one of claims 1 to 7.

10. An electronic device, comprising: The non-volatile storage medium stores a plurality of instructions, and the instructions are adapted to be loaded and executed by a processor to implement the cable insulation performance degradation evaluation method after short-time over-temperature in a fire environment according to any one of claims 1 to 7. The non-volatile storage medium stores a plurality of instructions, and the instructions are adapted to be loaded and executed by a processor to implement the cable insulation performance degradation evaluation method after short-time over-temperature in a fire environment according to any one of claims 1 to 7.

Images