Optical fiber composite cable temperature sensing and early warning system

Abstract

The application belongs to the technical field of cable monitoring, and specifically discloses a kind of optical fiber composite cable temperature warning system, the system utilizes multilevel fusion algorithm to analyze communication signal intensity estimation coefficient, filters cable reference temperature value, realizes the correlation verification of temperature and communication performance;And detect each cable detection point corresponding environment data, compare and analyze the reference data under the condition of cable safe operation to estimate the influence degree of environment temperature, combine the cable reference temperature value to obtain the control temperature value, so that the temperature evaluation is more in line with the actual operation state, improve the reliability of monitoring data;According to the actual temperature of each cable detection point and the control temperature value, determine the temperature abnormal fault root cause warning, through the dual determination of abnormal detection point proportion and spatial aggregation degree, accurately distinguish systematic failure and local area failure, guide the differentiated maintenance strategy, reduce unnecessary repair.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of cable detection and relates to an optical fiber composite cable temperature sensing and early warning system. BACKGROUND

[0002] As a key carrier for underground power transmission and communication, the operating temperature of the optical fiber composite cable directly affects the transmission stability and service life. The complexity of the underground environment easily leads to abnormal local temperature of the cable, and if not timely warned, may cause short circuit, accelerated aging and other faults, threatening the safety of power and communication systems. Therefore, a temperature sensing and early warning system that integrates multi-dimensional data is urgently needed to improve monitoring accuracy and timeliness of early warning.

[0003] For example, Chinese Patent Publication No. CN117589331A discloses a downhole cable temperature detection method and system. The method measures the underground cable in segments, moves at a uniform speed along the length of the cable with a temperature detection device, detects the temperature of each detection segment, transmits the results to the central control center for analysis, and issues an abnormal alarm through the monitoring system while pushing information to the user terminal to determine the temperature abnormal trend. This method realizes comprehensive detection of cable temperature and provides a feasible solution for downhole cable temperature monitoring, with the characteristics of mobile detection without dead angles and timely information transmission.

[0004] The above prior art has the following deficiencies: 1. The prior art only collects cable temperature directly through a temperature detection device without considering the influence of temperature changes on the communication signals of the optical fiber composite cable. The communication performance of the optical fiber composite cable is strongly related to temperature, and ignoring this relationship will result in temperature evaluation only reflecting the surface state, unable to verify the authenticity of the temperature in combination with signal characteristics, and possible misjudgment.

[0005] 2. The prior art does not analyze environmental data such as soil temperature, thermal conductivity, and current load interference on cable temperature. In the underground environment, soil thermal conductivity and current load intensity directly affect cable heat dissipation and heat generation, and lack of quantitative analysis of these factors will lead to deviation of temperature detection results from reality, reducing monitoring accuracy.

[0006] 3. The prior art only issues an alarm based on temperature abnormalities, lacks analysis of the spatial distribution of abnormal detection points, and cannot distinguish between overall systematic faults and local area faults of the cable, increasing maintenance costs and reducing fault handling efficiency. SUMMARY

[0007] In view of this, in order to solve the problems raised in the background art, an optical fiber composite cable temperature sensing and early warning system is proposed.

[0008] The objective of this invention can be achieved through the following technical solution: This invention provides a fiber optic composite cable temperature sensing and early warning system, including a detection point deployment module, a signal strength analysis module, a reference temperature prediction module, an ambient temperature influence module, and an early warning information determination module.

[0009] The connection between the modules is as follows: the detection point deployment module is connected to the signal strength analysis module; the reference temperature prediction module is connected to both the signal strength analysis module and the ambient temperature influence module; and the early warning information determination module is connected to the ambient temperature influence module.

[0010] The detection point deployment module extracts the underground cable routing layout diagram and deploys cable detection points for all cable lines according to the set deployment rules.

[0011] The signal strength analysis module collects the signal strength, eye diagram, and signal transmission time of each cable detection point during the communication signal transmission process, and uses multi-level fusion analysis to predict the communication signal strength coefficient.

[0012] Referring to the temperature prediction module, the system performs a matching search from the preset temperature-signal mapping relationship library based on the communication signal strength estimation coefficient, and outputs the cable reference temperature value.

[0013] The ambient temperature influence module is used to detect the corresponding environmental data at each cable testing point, compare and analyze the environmental data with reference data under the safe operation conditions of the cable to predict the degree of influence of ambient temperature, and combine the cable reference temperature value with the combined calculation and analysis to obtain the reference temperature value.

[0014] The early warning information determination module collects the actual temperature of each cable detection point, compares it with the corresponding control temperature, filters out abnormal temperature detection points, and determines the root cause of temperature abnormality faults based on the proportion of abnormal temperature detection points across all cable lines.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention lays out cable detection points for all cable lines according to the set layout rules based on the underground cable operation layout diagram. By specifically covering key locations such as bends and joints, the targetedness and comprehensiveness of the monitoring are improved.

[0016] (2) This invention collects the signal strength, eye diagram and signal transmission time of each cable detection point during the communication signal transmission process, uses multi-level fusion analysis to predict the communication signal strength coefficient, and screens the cable reference temperature value. This realizes the correlation verification between temperature and communication performance, improves the evaluation accuracy of the cable's optimal operating temperature range, thereby improving the accuracy of temperature status judgment and reducing the risk of misjudgment.

[0017] (3) This invention detects the environmental data corresponding to each cable detection point, compares and analyzes the environmental data with the reference data under the safe operation of the cable to estimate the influence of environmental temperature, thereby quantifying the interference of environmental factors on temperature, solving the problem of temperature detection distortion caused by environmental factors, and obtaining the reference temperature value by combining the cable reference temperature value, making the temperature assessment more in line with the actual operating state and improving the reliability of monitoring data.

[0018] (4) This invention filters temperature anomaly detection points by comparing the actual temperature of each cable detection point with the corresponding control temperature, determines the root cause warning of temperature anomaly faults based on the proportion of temperature anomaly detection points in all cable lines, and accurately distinguishes between systemic faults and local area faults through the dual judgment of the proportion of anomaly detection points and spatial clustering, guides differentiated maintenance strategies, and reduces unnecessary maintenance. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram showing the connections of the various modules in the system of the present invention.

[0021] Figure 2 This is a schematic diagram illustrating the steps involved in the environmental temperature influence prediction and analysis in this invention.

[0022] Figure 3 This is a schematic diagram illustrating the specific steps of the early warning information determination module in this invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Please see Figure 1 As shown, the present invention provides a fiber optic composite cable temperature sensing and early warning system, which includes a detection point deployment module, a signal strength analysis module, a reference temperature prediction module, an ambient temperature influence module, and an early warning information determination module.

[0025] The connection between the modules is as follows: the detection point deployment module is connected to the signal strength analysis module; the reference temperature prediction module is connected to both the signal strength analysis module and the ambient temperature influence module; and the early warning information determination module is connected to the ambient temperature influence module.

[0026] The detection point deployment module extracts the underground cable routing layout diagram and deploys cable detection points for all cable lines according to the set deployment rules.

[0027] It should be noted that the deployment rules are as follows: retrieve the fault locations and causes of all cable lines within the set historical period, count the cable lines with a fault occurrence frequency greater than the set fault occurrence frequency threshold, and deploy detection points on these cable lines at set intervals. For cable lines with no fault records or a fault occurrence frequency less than or equal to the set fault occurrence frequency threshold, deploy detection points at twice the set intervals to form a dynamic deployment rule. By specifically covering key locations such as bends, joints, or areas with abnormal soil thermal resistance, the targeting and comprehensiveness of cable line temperature monitoring are improved.

[0028] The signal strength analysis module collects the signal strength, eye diagram, and signal transmission time of each cable detection point during the communication signal transmission process, and uses multi-level fusion analysis to predict the communication signal strength coefficient.

[0029] It should be noted that the communication signal strength prediction coefficient analysis method includes: extracting the received signal strength and signal attenuation value from the signal strength of each cable detection point during the communication signal transmission process, comparing and analyzing the received signal strength and signal attenuation value with the corresponding set reference threshold, and outputting the signal strength index based on the comparison and analysis results and the signal strength level grading judgment rule.

[0030] Eye height, eye width, and eye jitter frequency are obtained from the eye diagram. The signal stability index is determined based on the standard deviation of the eye height, eye width, and eye jitter frequency from the average value of the corresponding parameters.

[0031] Based on the signal transmission duration and signal transmission delay in the signal transmission time, the relative deviation of the signal transmission duration relative to the permitted transmission duration and the relative deviation of the signal transmission delay relative to the permitted delay are calculated. The two relative deviations are then added together to obtain the transmission time deviation index. The analysis process for the relative deviation of the signal transmission duration relative to the permitted transmission duration is as follows: the difference between the signal transmission duration and the permitted transmission duration is compared to obtain the absolute difference between the signal transmission duration and the permitted transmission duration. The ratio of this absolute difference to the permitted transmission duration is taken as the relative deviation.

[0032] The signal strength prediction coefficient is obtained by weighted summation of the comprehensive signal strength index, signal stability index, and transmission time deviation index.

[0033] The dynamic setting method for the weights of the signal strength index, signal stability index, and transmission time deviation index is as follows: multiple test data are selected from historical fiber optic composite cable temperature test records. The signal strength index, signal stability index, and transmission time deviation index from the multiple test data are substituted into different weight combinations. The communication signal strength prediction coefficient is calculated by weighted fusion. Based on the actual communication quality, the fitting error between the communication signal strength prediction coefficient and the actual communication quality is calculated by the least squares method. The weight combination with the smallest error is selected as the final weights of the signal strength index, signal stability index, and transmission time deviation index.

[0034] If the fitting error exceeds the preset threshold, multiple detection data need to be selected again and iterated repeatedly until the error reaches the target.

[0035] In one specific embodiment, the received signal strength is obtained by: sensing and measuring the intensity of the electromagnetic field using a field strength meter placed at the cable detection point, and converting the electromagnetic field intensity into a corresponding electrical signal strength value, thereby obtaining the received signal strength.

[0036] The signal attenuation value is obtained through a signal generator and a power meter. The specific steps are as follows: connect the signal generator to the transmitting end of the cable, set the signal generator to output a signal of appropriate frequency and power, connect a power meter to the detection point of the cable, measure the received signal power, and then obtain the signal attenuation value using the signal attenuation calculation formula. The signal attenuation calculation formula is existing technology and will not be described in detail in this invention.

[0037] The method for obtaining the eye diagram is as follows: connect the signal output terminal of the cable detection point to the input channel of the oscilloscope, ensuring that the connection is correct and stable, so as to obtain accurate signal acquisition. The oscilloscope will superimpose and display the acquired continuous signals to form an eye diagram.

[0038] The signal transmission duration and signal transmission delay duration are obtained as follows: The network analyzer sends a test signal of a specific frequency to the cable, measures the time it takes for the signal to travel from one end to the other based on the transmission characteristics of the signal between the transmitting end and the cable detection point, and thus obtains the signal transmission duration. At the same time, the delay of the signal during transmission is measured, that is, the time difference between the signal sent by the transmitting end and the signal received by the cable detection point, and thus obtains the signal transmission delay duration.

[0039] It should be noted that the signal strength level grading determination rule is set as follows: if the received signal strength is greater than a set received signal strength reference threshold and the signal attenuation value is less than a set signal attenuation value reference threshold, then the signal strength level index is the maximum value within the set range. The set range can be... Its maximum value is 1 and its minimum value is 0.

[0040] If only the received signal strength is greater than the set received signal strength reference threshold or the signal attenuation value is less than the set signal attenuation value reference threshold, then the deviation of the received signal strength from the set received signal strength reference threshold or the deviation of the signal attenuation value from the set signal attenuation value reference threshold is calculated, and the signal strength index is obtained by weighted analysis based on the deviation.

[0041] If the received signal strength is less than or equal to the set received signal strength reference threshold and the signal attenuation value is greater than or equal to the set signal attenuation value reference threshold, then the signal strength index is the minimum value within the set range.

[0042] In one specific embodiment, when the received signal strength is greater than a set received signal strength reference threshold, the absolute difference between the signal attenuation value and the set signal attenuation value reference threshold is obtained. The ratio of this difference to the set signal attenuation value reference threshold is used as the degree of deviation of the signal attenuation value from the set signal attenuation value reference threshold. The product of the degree of deviation and the influence weight corresponding to the signal attenuation value is used as the signal strength index.

[0043] When the signal attenuation value is less than the set signal attenuation reference threshold, the absolute difference between the received signal strength and the set received signal strength reference threshold is obtained. The ratio of this difference to the set received signal strength reference threshold is taken as the degree of deviation. The product of the degree of deviation and the influence weight corresponding to the received signal strength is taken as the signal strength degree index.

[0044] The received signal strength is the most direct factor determining whether the receiver can function effectively. While signal attenuation is an important factor affecting received signal strength, it is not the only one. Factors such as transmit power and environmental interference also influence the final received signal strength. Therefore, when evaluating signal strength, the received signal strength metric is given a higher weight. For example, a typical weighting might be 0.6 for received signal strength and 0.4 for signal attenuation.

[0045] It should be noted that the determination of the signal stability index is as follows: the minimum standard deviation is selected from the standard deviations of eye height, eye width, and eye diagram jitter frequency and the corresponding parameter average values ​​to obtain the deviation between the preset standard deviation threshold and the minimum standard deviation. This deviation is then substituted into the natural exponential function as an independent variable to output the signal stability index.

[0046] The deviation is the ratio of the difference between the preset standard deviation threshold and the minimum standard deviation to the preset standard deviation threshold.

[0047] Referring to the temperature prediction module, the system performs a matching search from the preset temperature-signal mapping relationship library based on the communication signal strength estimation coefficient, and outputs the cable reference temperature value.

[0048] It should be noted that the reference temperature value of the output cable specifically includes: matching and comparing the communication signal strength prediction coefficient with the range of communication signal strength prediction coefficients corresponding to each set temperature in the preset temperature-signal mapping relationship library; if the communication signal strength prediction coefficient is within the range of communication signal strength prediction coefficients corresponding to a certain set temperature, then the set temperature is used as the cable reference temperature value.

[0049] In one specific embodiment, the preset temperature-signal mapping relationship library can be set according to industry standards or obtained through a limited number of experimental data, such as placing a cable sample in a temperature control device and connecting a signal generator and an analyzer to ensure stable line connection.

[0050] Set an initial temperature, and after the temperature stabilizes, measure and record the signal strength, eye diagram, and signal transmission time at this time, and calculate the communication signal strength prediction coefficient.

[0051] The temperature is changed in fixed steps, and the test is repeated multiple times at each temperature point. The range of the communication signal strength prediction coefficient corresponding to each temperature value is recorded, and the coefficients are arranged in ascending order of temperature to build a temperature-signal mapping relationship library.

[0052] This invention collects signal strength, eye diagram, and signal transmission time at various cable detection points during the communication signal transmission process. It utilizes multi-level fusion analysis to predict the communication signal strength coefficient and screens cable reference temperature values. This enables the correlation verification between temperature and communication performance, improves the accuracy of evaluating the optimal operating temperature range of cables, and thus enhances the accuracy of temperature status judgment and reduces the risk of misjudgment.

[0053] The ambient temperature influence module is used to detect environmental data corresponding to each cable testing point. It compares and analyzes the environmental data with reference data under safe cable operation conditions to estimate the degree of ambient temperature influence. Combined with the cable reference temperature value, it performs combined calculations to obtain the control temperature value. The control temperature value is the product of the cable reference temperature value and the ambient temperature influence value, plus the cable reference temperature value.

[0054] like Figure 2 As shown, the environmental temperature influence prediction analysis includes: A1. Retrieving soil temperature and soil thermal conductivity from the environmental data corresponding to each cable detection point, and analyzing the relative deviation between the soil temperature and the set reference cable safe operating temperature. The relative deviation is the ratio of the difference between the soil temperature and the set reference cable safe operating temperature to the set reference cable safe operating temperature.

[0055] A2. Analyze the influence of external environmental temperature on each cable testing point using an exponential function, comparing the relative deviation of soil temperature with soil thermal conductivity. The external environmental temperature influence factor is calculated by substituting the product of the relative deviation of soil temperature and soil thermal conductivity as the independent variable into the natural exponential function, which then outputs the dependent variable.

[0056] A3. Based on the current load intensity in the environmental data corresponding to each cable detection point, generate an internal environmental temperature influence factor by comparing the current load intensity with the set reference cable current load intensity safety threshold.

[0057] A4. Analyze the degree of influence of environmental temperature based on the external and internal environmental temperature influence factors and through a weighted fusion algorithm.

[0058] The weighting method for the external and internal environmental temperature influence factors is as follows: retrieve the abnormal causes of each cable fault warning event from the historical operation data of the cable. The abnormal causes include external and internal factors. Calculate the proportion of external and internal factors as the main abnormal causes and allocate corresponding weights accordingly.

[0059] In one specific embodiment, the internal ambient temperature influence factor is generated as follows: if the current load intensity at a certain cable detection point is less than the set safety threshold for the reference cable current load intensity, then the set value is used as the internal ambient temperature influence factor. This set value can be set to 0.

[0060] If the current load intensity at a certain cable testing point is greater than or equal to the set reference cable current load intensity safety threshold, then the deviation between the current load intensity and the set reference cable current load intensity safety threshold will be used as the internal ambient temperature influence factor.

[0061] It should be added that the soil temperature was obtained by a soil temperature detector placed near the cable detection point, and the soil thermal conductivity was obtained by a soil thermal conductivity sensor placed near the cable detection point.

[0062] The process of obtaining the current load intensity involves detecting the actual current using a current sensor placed at the cable detection point, extracting the rated current of the cable from the cable's own parameter information, and then using the ratio of the actual current to the rated current as the current load intensity.

[0063] This invention detects environmental data corresponding to each cable detection point, compares and analyzes the environmental data with reference data under safe cable operation conditions to predict the influence of environmental temperature, thereby quantifying the interference of environmental factors on temperature, solving the problem of temperature detection distortion caused by environmental factors, and obtaining a comparison temperature value by combining the cable reference temperature value with correction, making the temperature assessment more in line with the actual operating state and improving the reliability of monitoring data.

[0064] The early warning information determination module collects the actual temperature of each cable detection point, compares it with the corresponding control temperature, filters out abnormal temperature detection points, and determines the root cause of temperature abnormality faults based on the proportion of abnormal temperature detection points across all cable lines.

[0065] like Figure 3 As shown, the specific content of the early warning information determination module is as follows: The absolute temperature difference is obtained by comparing the reference temperature and the actual temperature at each cable detection point. The abnormal temperature detection point is determined based on the comparison result between the absolute temperature difference and the set permissible temperature difference threshold for the cable. Specifically, when the absolute temperature difference at a cable detection point is greater than the set permissible temperature difference threshold, that cable detection point is recorded as a temperature abnormality detection point.

[0066] Mark the locations of all temperature anomaly detection points from the underground cable layout diagram, count the number of temperature anomaly detection points for all cable lines, and use the ratio of this number to the total number of detection points for the corresponding line as the percentage of temperature anomaly detection points.

[0067] Based on the location of all temperature anomaly detection points on each cable line, anomaly point spatial clustering is constructed. The root cause of temperature anomaly faults is determined according to the proportion of temperature anomaly detection points and the anomaly point spatial clustering, and corresponding early warnings are issued.

[0068] In one specific embodiment, the spatial clustering analysis of the anomaly points is performed by determining the distance between each temperature anomaly monitoring point and its nearest neighbor based on the location of all temperature anomaly detection points, and using the average of these distances as the actual average nearest neighbor distance.

[0069] Obtain the total length of each cable line, and use the ratio of this length to the number of all temperature anomaly detection points on that cable line as the expected average nearest neighbor distance under random distribution. Use the ratio of the expected average nearest neighbor distance to the actual average nearest neighbor distance as the spatial clustering degree of the anomaly points. A higher spatial clustering degree indicates a higher density of anomaly detection points along the cable line.

[0070] In one specific embodiment, the step of determining the root cause of temperature anomaly based on the proportion of temperature anomaly detection points and the spatial clustering of anomaly points is as follows: if the proportion of temperature anomaly detection points in a certain cable line is greater than a set threshold for the proportion of the number of anomaly detection points, then the cable line has a temperature anomaly fault.

[0071] The spatial clustering degree of abnormal points in the cable line is compared with the set clustering degree threshold. When the spatial clustering degree of abnormal points in the cable line is less than the set clustering degree threshold, the cable line is considered to have a systemic fault.

[0072] When the spatial concentration of abnormal points in a cable line exceeds a set concentration threshold, the cable line is considered to have a localized fault.

[0073] This invention filters temperature anomaly detection points by comparing the actual temperature of each cable detection point with the corresponding control temperature. It determines the root cause warning of temperature anomaly faults based on the proportion of temperature anomaly detection points across all cable lines. Through the dual judgment of the proportion of anomaly detection points and spatial clustering, it accurately distinguishes between systemic faults and localized faults, guides differentiated maintenance strategies, and reduces unnecessary repairs.

[0074] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0075] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0076] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0077] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0078] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0079] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A fiber optic composite cable temperature sensing and early warning system, characterized in that: include: The detection point deployment module extracts the underground cable routing layout diagram and deploys cable detection points for all cable lines according to the set deployment rules. The signal strength analysis module collects the signal strength, eye diagram and signal transmission time of each cable detection point during the communication signal transmission process, and uses multi-level fusion analysis to predict the communication signal strength coefficient. Referring to the temperature prediction module, the cable reference temperature value is output by matching and searching the preset temperature-signal mapping relationship library based on the communication signal strength prediction coefficient; The ambient temperature influence module is used to detect the corresponding environmental data at each cable detection point, compare and analyze the environmental data with the reference data under the safe operation of the cable to predict the degree of environmental temperature influence, and combine the cable reference temperature value with the combined calculation and analysis to obtain the reference temperature value. The reference temperature value is the product of the cable reference temperature value and the influence of the ambient temperature, plus the cable reference temperature value. The early warning information determination module collects the actual temperature of each cable detection point, compares it with the corresponding control temperature, filters out temperature abnormality detection points, and determines the root cause of temperature abnormality faults based on the proportion of temperature abnormality detection points in all cable lines. The communication signal strength prediction coefficient analysis method includes: extracting the received signal strength and signal attenuation value from the signal strength of each cable detection point during the communication signal transmission process; comparing the received signal strength and signal attenuation value with the corresponding set reference threshold values; and outputting a signal strength index based on the signal strength level classification judgment rule according to the comparison analysis results. The method also includes: obtaining eye height, eye width, and eye diagram jitter frequency from the eye diagram; determining a signal stability index based on the standard deviation of the eye height, eye width, and eye diagram jitter frequency from the average value of the corresponding parameters; calculating the relative deviation of the signal transmission duration relative to the permitted transmission duration and the relative deviation of the signal transmission delay relative to the permitted delay duration based on the signal transmission duration and signal transmission delay duration in the signal transmission time; adding the two relative deviations to obtain a transmission time deviation index; and finally, combining the signal strength index, signal stability index, and transmission time deviation index, and obtaining the communication signal strength prediction coefficient through weighted summation. The environmental temperature influence prediction analysis includes: A1. Retrieving soil temperature and soil thermal conductivity from the environmental data corresponding to each cable detection point, and analyzing the relative deviation between the soil temperature and the set safe operating temperature of the reference cable; A2. Performing an exponential function statistical analysis on the relative deviation of the soil temperature and the soil thermal conductivity to determine the external environmental temperature influence factor for each cable detection point; A3. Generating an internal environmental temperature influence factor based on the comparison between the current load intensity and the set safe threshold of the current load intensity of the reference cable, according to the current load intensity in the environmental data corresponding to each cable detection point; A4. Calculating and analyzing the environmental temperature influence degree based on the external and internal environmental temperature influence factors using a weighted fusion algorithm.

2. The fiber optic composite cable temperature sensing and early warning system according to claim 1, characterized in that: The method for setting the signal strength level classification judgment rule is as follows: If the received signal strength is greater than the set received signal strength reference threshold and the signal attenuation value is less than the set signal attenuation value reference threshold, then the signal strength index is the maximum value of the set range. If only the received signal strength is greater than the set received signal strength reference threshold or the signal attenuation value is less than the set signal attenuation value reference threshold, then the deviation of the received signal strength from the set received signal strength reference threshold or the deviation of the signal attenuation value from the set signal attenuation value reference threshold is calculated, and the signal strength index is obtained by weighted analysis based on the deviation. If the received signal strength is less than or equal to the set received signal strength reference threshold and the signal attenuation value is greater than or equal to the set signal attenuation value reference threshold, then the signal strength index is the minimum value within the set range.

3. The fiber optic composite cable temperature sensing and early warning system according to claim 1, characterized in that: The determination of the signal stability index is detailed below: The minimum standard deviation is selected from the standard deviations of eye height, eye width, and eye diagram jitter frequency and the corresponding average values ​​of the parameters. The deviation between the preset standard deviation threshold and the minimum standard deviation is obtained. This deviation is then substituted into the natural exponential function as an independent variable to output the signal stability index.

4. The fiber optic composite cable temperature sensing and early warning system according to claim 1, characterized in that: The analysis process for the relative deviation of the signal transmission duration relative to the permitted transmission duration is as follows: The signal transmission duration is compared with the permitted transmission duration to obtain the absolute difference between the signal transmission duration and the permitted transmission duration. The ratio of the absolute difference to the permitted transmission duration is taken as the relative deviation.

5. The fiber optic composite cable temperature sensing and early warning system according to claim 1, characterized in that: The reference temperature value for the output cable specifically includes: The communication signal strength prediction coefficient is matched and compared with the range of communication signal strength prediction coefficients corresponding to each set temperature in the preset temperature-signal mapping relationship library. If the communication signal strength prediction coefficient is within the range of communication signal strength prediction coefficients corresponding to a certain set temperature, then the set temperature is used as the cable reference temperature value.

6. The fiber optic composite cable temperature sensing and early warning system according to claim 5, characterized in that: The internal environmental temperature influencing factor is generated as follows: If the current load intensity at a certain cable detection point is less than the set safety threshold for the reference cable current load intensity, then the set value will be used as the internal ambient temperature influence factor. If the current load intensity at a certain cable testing point is greater than or equal to the set reference cable current load intensity safety threshold, then the deviation between the current load intensity and the set reference cable current load intensity safety threshold will be used as the internal ambient temperature influence factor.

7. The fiber optic composite cable temperature sensing and early warning system according to claim 1, characterized in that: The specific content of the early warning information determination module is as follows: The absolute temperature difference is obtained by comparing the reference temperature and the actual temperature at each cable testing point. The abnormal temperature testing point is determined based on the comparison result of the absolute temperature difference and the set cable permissible temperature difference threshold. Mark the locations of all temperature anomaly detection points from the underground cable layout diagram, count the number of temperature anomaly detection points for all cable lines, and use the ratio of this number to the total number of detection points for the corresponding line as the percentage of temperature anomaly detection points. Based on the location of all temperature anomaly detection points on each cable line, anomaly point spatial clustering is constructed. The root cause of temperature anomaly faults is determined according to the proportion of temperature anomaly detection points and the anomaly point spatial clustering, and corresponding early warnings are issued.

8. The fiber optic composite cable temperature sensing and early warning system according to claim 7, characterized in that: The method for determining the root cause of temperature anomaly faults based on the proportion of abnormal temperature detection points and the spatial clustering of these points is as follows: If the proportion of abnormal temperature detection points in a cable line is greater than the set threshold for the proportion of abnormal detection points, then the cable line has an abnormal temperature fault. The spatial clustering degree of abnormal points in the cable line is compared with the set clustering degree threshold. When the spatial clustering degree of abnormal points in the cable line is less than the set clustering degree threshold, the cable line is considered to have a systemic fault. When the spatial concentration of abnormal points in a cable line exceeds a set concentration threshold, the cable line is considered to have a localized fault.

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