Intelligent optical cable monitoring system and method

Abstract

The invention relates to the technical field of optical cable monitoring, and discloses an intelligent optical cable monitoring system and method. The method comprises the following steps: firstly, acquiring an optical fiber transmission loss value and a temperature fluctuation value of an optical cable laying environment at each monitoring moment; dividing the monitoring parameters into stable parameters and fluctuation parameters according to the transmission loss values at the plurality of monitoring moments; for the stable parameters, a reference fluctuation interval of the stable parameters is obtained according to the transmission loss values at all moments, and for the fluctuation parameters, the reference fluctuation interval of the fluctuation parameters is obtained by combining the temperature fluctuation values and the transmission loss values at all moments; and then judging whether the transmission loss value of each monitoring parameter at the current moment accords with the corresponding reference fluctuation interval, if so, taking the current transmission loss value and the temperature fluctuation value as an optical cable state monitoring data source, and if not, selecting corrected data in the reference fluctuation interval as the optical cable state monitoring data source. The method can judge the transmission loss of the optical cable more practically, and guarantees the effectiveness of a monitoring data source.

Description

Technical Field

[0001] The present invention relates to the technical field of optical cable monitoring, and in particular to an intelligent optical cable monitoring system and method. Background Art

[0002] As an important carrier of information transmission, optical cables are widely used in communications, electricity, transportation and other fields. The stability of their operating status is directly related to the security and continuity of information transmission. Therefore, efficient and accurate monitoring of optical cables is crucial. Most existing optical cable monitoring methods fail to differentiate the characteristics of the monitoring parameters and instead employ a unified baseline interval setting approach. However, in practice, the degree to which different monitoring parameters of optical cables are affected by their own performance and the external environment varies significantly. For some parameters, transmission loss changes are relatively stable over long-term operation, with minimal interference from environmental factors such as temperature. Other parameters, on the other hand, are more sensitive to environmental changes, with transmission loss prone to significant variations with temperature fluctuations. Monitoring these parameters with varying characteristics within the same baseline framework results in a mismatch between the baseline interval and the actual variation patterns of the parameters, making it difficult to accurately identify normal fluctuations and abnormalities in the parameters. Existing technologies have significant limitations in determining the baseline fluctuation range. For parameters less affected by the environment, some methods still incorporate irrelevant environmental variables, complicating the baseline interval calculation and reducing accuracy. For parameters significantly affected by temperature, most methods set the baseline range based solely on the transmission loss value, ignoring the direct impact of temperature fluctuations. When the ambient temperature fluctuates significantly, the normal transmission loss fluctuation of the parameter may exceed the set baseline range, resulting in misinterpretation as an anomaly and affecting monitoring accuracy. Existing methods often take a simplistic approach when dealing with transmission loss values ​​that fall outside the benchmark range: either directly discarding the data, resulting in a broken monitoring data source and an inability to reflect the continuous changes in the optical cable's condition; or replacing it with a fixed value, which results in a significant deviation from the actual data and reduces the reliability of the monitoring data. This approach is difficult to meet the needs of long-term, accurate optical cable monitoring, and is particularly prone to misjudging or missing potential optical cable faults in complex environments. The continuous expansion of optical cable networks and the increasing complexity of their application scenarios are driving higher demands on the accuracy, continuity, and reliability of monitoring data. The shortcomings of existing monitoring methods in areas such as parameter characteristic differentiation, baseline interval setting, and abnormal data processing have become significant constraints on the development of intelligent optical cable monitoring. A monitoring method that can specifically address these issues is urgently needed. Summary of the Invention

[0003] The object of the present invention is to provide an intelligent optical cable monitoring system and method to solve the problems raised in the above background technology.

[0004] To achieve the above object, the present invention provides an intelligent optical cable monitoring method, the method comprising: Collect the optical fiber transmission loss value and the temperature fluctuation value of the optical cable laying environment at each monitoring moment; The monitoring parameters are divided into stable parameters and fluctuating parameters according to the transmission loss values ​​at multiple monitoring moments; For each stable parameter, the benchmark fluctuation range of the stable parameter is obtained according to the transmission loss value at each monitoring moment; For each fluctuating parameter, the reference fluctuation range of the fluctuating parameter is obtained according to the temperature fluctuation value and transmission loss value at each monitoring moment; Determine whether the transmission loss value of each monitoring parameter at the current moment meets the corresponding benchmark fluctuation range; if so, use the current transmission loss value and temperature fluctuation value as the data source for optical cable status monitoring; if not, select the corrected data within the benchmark fluctuation range as the data source for optical cable status monitoring.

[0005] Preferably, the step of dividing the monitoring parameters into stable parameters and fluctuating parameters according to the transmission loss values ​​at multiple monitoring moments includes: Obtaining a maximum transmission loss value and a minimum transmission loss value of each monitoring parameter at different monitoring moments according to the transmission loss value of each monitoring parameter at a plurality of monitoring moments; The ratio of the difference between the maximum transmission loss value and the minimum transmission loss value of the monitoring parameter at different monitoring times to the maximum transmission loss value is taken as the fluctuation coefficient of the monitoring parameter; Sort the fluctuation coefficient of each monitoring parameter by numerical value, and calculate the mean of the difference between each fluctuation coefficient and the adjacent fluctuation coefficients as the classification threshold; The monitoring parameter corresponding to the fluctuation coefficient whose difference with the adjacent fluctuation coefficients of the sorting is less than the classification threshold is used as a stable parameter; The monitoring parameter corresponding to the fluctuation coefficient whose difference with the adjacent fluctuation coefficients in the sorting is greater than the classification threshold is used as the fluctuation parameter.

[0006] Preferably, the step of obtaining a reference fluctuation range of a stable parameter according to the transmission loss value at each monitoring moment includes: For each stable parameter, perform the following steps separately, Calculating and obtaining reference values ​​of transmission loss values ​​at all monitoring moments, wherein the reference value includes an arithmetic mean value; The transmission loss values ​​at each monitoring moment are sorted according to their numerical values, and the mean of the difference between each transmission loss value and the adjacent transmission loss values ​​is calculated as the fluctuation step size; Starting from the reference value, calculate one by one along the increasing and decreasing directions of the transmission loss value sorting to see whether the difference between two adjacent transmission loss values ​​is less than the fluctuation step; if so, continue the calculation; if not, use the numerical distribution interval of the transmission loss values ​​included in the calculation as the benchmark fluctuation interval of the stable parameter.

[0007] Preferably, the step of obtaining a reference fluctuation range of the fluctuation parameter according to the temperature fluctuation value and the transmission loss value at each monitoring moment includes: For each fluctuation parameter, perform the following steps separately: Acquire a number of environmental monitoring points associated with the fluctuating parameter to form a related monitoring group for the fluctuating parameter; Calculate and obtain the cumulative value of the difference in transmission loss values ​​of the fluctuating parameters between different monitoring moments and the difference in temperature fluctuation values ​​of several environmental monitoring points as the state difference of the associated monitoring group between different monitoring moments; According to the status differences between the associated monitoring groups at different monitoring times, the monitoring times with the same status of the associated monitoring groups are divided into the same monitoring time set; For each monitoring time set, the numerical distribution range of the temperature fluctuation values ​​of several environmental monitoring points associated with the fluctuation type parameter is obtained, and the numerical distribution range of the transmission loss value of the fluctuation type parameter is used as the reference fluctuation interval.

[0008] Preferably, the step of grouping the monitoring moments with the same status of the associated monitoring groups into the same monitoring moment set according to the status differences between the associated monitoring groups at different monitoring moments includes: Select several monitoring moments from all monitoring moments as benchmark monitoring moments; Calculate and obtain the status difference between each benchmark monitoring moment and other monitoring moments; Classify the other monitoring moments other than each benchmark monitoring moment and the benchmark monitoring moment with the smallest state difference into the same monitoring moment set; In each monitoring time set, the cumulative value of the state difference between each monitoring time and all other monitoring times is calculated; Determine whether the monitoring moment with the smallest cumulative value of the state difference with all other monitoring moments in each monitoring moment set is the benchmark monitoring moment; if so, obtain a monitoring moment set with consistent states of associated monitoring groups; if not, reselect the benchmark monitoring moment, and re-divide the monitoring moment set to perform consistency judgment on the states of associated monitoring groups, until a monitoring moment set with consistent states of associated monitoring groups is obtained.

[0009] Preferably, the step of reselecting the reference monitoring time includes: The monitoring time with the smallest cumulative value of state differences between each monitoring time set and all other monitoring times is used as the reselected reference monitoring time.

[0010] Preferably, the step of determining whether the transmission loss value of each monitoring parameter at the current moment meets the corresponding reference fluctuation range includes: For each fluctuation parameter, perform the following steps separately: Selecting a set of monitoring moments that conform to a corresponding reference fluctuation interval based on the transmission loss value of the current fluctuation parameter and the temperature fluctuation values ​​of several environmental monitoring points associated with the fluctuation parameter; Determine whether the transmission loss value of the fluctuating parameter at the current moment falls within the benchmark fluctuation interval of the monitoring moment set; if so, it is determined that the transmission loss value of the fluctuating parameter meets the corresponding benchmark fluctuation interval; if not, it is determined that the transmission loss value of the fluctuating parameter does not meet the corresponding benchmark fluctuation interval.

[0011] Preferably, the step of selecting the corrected data within the reference fluctuation range as the data source for optical cable status monitoring includes: For stable parameters, the arithmetic mean of its benchmark fluctuation range is used as the revised data; For the fluctuating parameters, the arithmetic mean of the numerical distribution range of the transmission loss value of the fluctuating parameter at each monitoring moment contained in the set of monitoring moments that conform to the corresponding benchmark fluctuation interval at the current moment is taken as the corrected data.

[0012] Preferably, before the step of collecting and obtaining the optical fiber transmission loss value and the temperature fluctuation value of the optical cable laying environment at each monitoring moment, the step includes: Obtain historical fault records in the optical cable laying area and extract the transmission loss threshold and temperature fluctuation threshold when the historical fault occurred; Set the initial monitoring sensitivity level based on the transmission loss threshold and temperature fluctuation threshold in historical fault records; The sampling interval corresponding to the initial monitoring sensitivity level is used as the basic sampling interval of the current monitoring period.

[0013] Preferably, the present invention further includes an intelligent optical cable monitoring system for implementing the above-mentioned intelligent optical cable monitoring method, the system comprising: Fiber optic sensor, used to collect transmission loss data of optical cables; Environmental sensors are used to collect temperature fluctuation data of the optical cable laying environment; A data processing unit is used to extract the optical fiber transmission loss value and the temperature fluctuation value of the optical cable laying environment at each monitoring moment; The monitoring parameters are divided into stable parameters and fluctuating parameters based on the transmission loss values ​​at multiple monitoring moments; for each stable parameter, a reference fluctuation interval of the stable parameter is obtained based on the transmission loss value at each monitoring moment; for each fluctuating parameter, a reference fluctuation interval of the fluctuating parameter is obtained based on the temperature fluctuation value and the transmission loss value at each monitoring moment; it is determined whether the transmission loss value of each monitoring parameter at the current moment meets the corresponding reference fluctuation interval; if so, the transmission loss value and temperature fluctuation value at the current moment are used as the data source for optical cable status monitoring; if not, the corrected data within the reference fluctuation interval is selected as the data source for optical cable status monitoring; The monitoring terminal is used to receive the optical cable status monitoring data source; and display the optical cable status monitoring data source in the monitoring terminal.

[0014] Compared with the prior art, the present invention has the following beneficial effects: This intelligent optical cable monitoring method effectively adapts to the actual variations of different parameters by classifying them. In reality, optical cable monitoring parameters are affected to varying degrees by their own properties and the external environment. Some parameters have stable transmission characteristics and are less susceptible to environmental interference, while others are susceptible to fluctuations due to environmental factors such as temperature. Categorizing these parameters into stable and fluctuating parameters avoids the drawback of traditional methods that use a single standard for all parameters. This ensures that the monitoring benchmark for each parameter matches its own characteristics, reducing monitoring deviations caused by these differences. For stable parameters, the baseline fluctuation range is determined solely based on their transmission loss values ​​at multiple monitoring moments, fully accounting for the inherent stability of these parameters. Since stable parameters are less affected by the external environment, fluctuations in their transmission loss primarily stem from subtle changes in their own performance. The baseline range, determined based on their own data, accurately reflects their normal range of variation, making monitoring of these parameters more targeted and avoiding baseline distortion caused by irrelevant factors. For fluctuating parameters, the reference fluctuation range is determined by combining transmission loss and temperature fluctuation values, fully accounting for the impact of environmental factors on these parameters. Temperature fluctuations in the optical cable installation environment directly affect the transmission performance of some parameters. Ignoring temperature factors results in the reference range failing to capture the normal fluctuation range of the parameters under different temperature conditions. Incorporating temperature fluctuations into the reference range determination process allows the reference range to be adaptively adjusted with temperature changes, more accurately reflecting the normal variation patterns of fluctuating parameters in different environments and reducing misjudgments caused by environmental fluctuations. In terms of data processing, this method corrects transmission loss values ​​that do not conform to the benchmark fluctuation range before using them as a monitoring data source, rather than simply discarding them. This ensures the continuity of monitoring data. Optical cable status monitoring requires long-term, continuous data support. Data interruptions can prevent the complete tracking of cable status trends. By selecting corrected data within the benchmark range, this method avoids interference from abnormal data on monitoring results while maintaining the integrity of the data sequence, ensuring that the monitoring data source can continuously reflect the operating status of the optical cable. Corrected data is derived from a baseline fluctuation range determined based on parameter characteristics and environmental factors. This ensures that the corrected data remains within a reasonable range, closely tracking the normal variation of the parameters and reducing monitoring deviations caused by improper handling of data anomalies. This approach ensures that even when parameters experience brief, abnormal fluctuations, the monitoring data maintains a high reference value, more consistent with the actual operation of optical cables, where parameters may experience momentary fluctuations but the overall trend remains normal. This method ensures that the acquired optical cable status monitoring data better reflects the cable's true operating status by precisely classifying parameter types, setting differentiated benchmark intervals, and rationally handling abnormal data. The benchmark intervals for different parameters are tailored to their characteristics and environmental influences. Correction of abnormal data ensures data continuity and reliability, ultimately improving the overall quality of monitoring data. This helps more accurately assess the cable's operating status and promptly identify potential changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a working principle diagram of the intelligent optical cable monitoring method of the present invention; Figure 2 Flowchart of the method for classifying monitoring parameters; Figure 3 Design diagrams generated for the benchmark fluctuation range of stable parameters; Figure 4 Flowchart generated for the baseline fluctuation range of the volatility parameter. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0017] See also Figure 1 The present invention provides an intelligent optical cable monitoring method, the method comprising: Collect the optical fiber transmission loss value and the temperature fluctuation value of the optical cable laying environment at each monitoring moment; The monitoring parameters are divided into stable parameters and fluctuating parameters according to the transmission loss values ​​at multiple monitoring moments; For each stable parameter, the benchmark fluctuation range of the stable parameter is obtained according to the transmission loss value at each monitoring moment; For each fluctuating parameter, the reference fluctuation range of the fluctuating parameter is obtained according to the temperature fluctuation value and transmission loss value at each monitoring moment; Determine whether the transmission loss value of each monitoring parameter at the current moment meets the corresponding benchmark fluctuation range; if so, use the current transmission loss value and temperature fluctuation value as the data source for optical cable status monitoring; if not, select the corrected data within the benchmark fluctuation range as the data source for optical cable status monitoring.

[0018] Example 1: See Figure 2 , the process of dividing the monitoring parameters into stable parameters and fluctuating parameters according to the transmission loss values ​​at multiple monitoring moments requires multiple consecutive steps. For each monitoring parameter, it is necessary to collect its transmission loss values ​​at multiple monitoring moments. These monitoring moments can be set according to fixed time intervals, or they can be flexibly arranged according to actual monitoring needs to ensure that different time periods and possible environmental changes are covered, so as to obtain sufficiently comprehensive transmission loss data. After obtaining these data, the maximum transmission loss value and the minimum transmission loss value of each monitoring parameter at different monitoring moments are extracted from all the transmission loss values. These two values ​​represent the upper and lower limits of the transmission loss of the parameter during the monitoring period, respectively, and can intuitively reflect the range of change in the transmission loss.

[0019] Calculate the coefficient of fluctuation for each monitored parameter. Specifically, divide the difference between the maximum and minimum transmission loss values ​​for that parameter by the maximum transmission loss value. The resulting coefficient of fluctuation is the parameter's coefficient of fluctuation. The magnitude of the coefficient of fluctuation directly reflects the relative fluctuation in transmission loss during the monitoring period. A larger value indicates a more significant change in transmission loss; a smaller value indicates a relatively stable transmission loss.

[0020] After obtaining the fluctuation coefficients of all monitored parameters, these fluctuation coefficients are sorted according to their numerical values. The purpose of sorting is to clearly present the differences in the degree of fluctuation of different parameters, so as to facilitate the subsequent search for the boundaries between stable and fluctuating parameters. After the sorting is completed, the difference between each fluctuation coefficient and the adjacent fluctuation coefficients after sorting is calculated, and then these differences are averaged. The obtained mean is determined as the classification threshold. The classification threshold is a key reference indicator for distinguishing parameter types. It comprehensively considers the differences between all adjacent fluctuation coefficients and can more objectively reflect the naturally existing classification boundaries in the fluctuation coefficient group.

[0021] Monitoring parameters are classified according to classification thresholds. For each fluctuation coefficient, the difference between it and the adjacent sorted fluctuation coefficients is examined. If this difference is less than the classification threshold, it indicates that the fluctuation coefficient is numerically close to the adjacent fluctuation coefficients and that the corresponding monitoring parameters have similar transmission loss fluctuation characteristics. Therefore, these parameters are classified as stable. Stable parameters have minimal transmission loss fluctuations during the monitoring period, exhibit low fluctuations, and are relatively less susceptible to external factors.

[0022] If the difference between a particular fluctuation coefficient and its adjacent fluctuation coefficients is greater than the classification threshold, it indicates a significant numerical difference between the two. The corresponding monitored parameter exhibits significantly different transmission loss fluctuation characteristics than other parameters, and is therefore classified as a fluctuating parameter. Fluctuating parameters exhibit significant transmission loss fluctuations over the monitoring period, exhibiting a high degree of volatility and are likely to be more susceptible to environmental factors, usage time, or other external conditions.

[0023] Example 2: See Figure 3 For each stable parameter, the process of deriving its baseline fluctuation range based on the transmission loss value at each monitoring moment requires a series of coherent steps. For each parameter classified as stable, its transmission loss values ​​at all monitoring moments must be collected. These monitoring moments can be recorded at different time periods and under different environmental conditions to ensure that the collected data fully reflects the transmission loss of the parameter under normal operating conditions.

[0024] Calculate the reference value for these transmission loss values ​​using the arithmetic mean. To calculate the arithmetic mean, add the transmission loss values ​​for all monitoring moments and divide by the total number of monitoring moments. The result represents the central trend of the transmission loss values ​​for that stable parameter. This reference value reflects the transmission loss level of that parameter in most situations and serves as an important starting point for subsequently determining the benchmark fluctuation range.

[0025] After obtaining the reference value, the transmission loss values ​​at each monitoring moment need to be sorted by numerical value. When sorting, start from the smallest transmission loss value and arrange in order to the largest transmission loss value to form an ordered series. This sorting method can clearly show the distribution of transmission loss values ​​and facilitate the observation of the differences between adjacent values. After the sorting is completed, the difference between each transmission loss value and the adjacent transmission loss value after sorting is calculated, and then these differences are averaged. The result is used as the fluctuation step size. The fluctuation step size reflects the average change in the transmission loss value of the stable parameter within the normal fluctuation range. It is an important basis for judging whether the transmission loss value is within a reasonable fluctuation range.

[0026] Starting from the reference value, calculate the difference between two adjacent transmission loss values ​​in both the increasing and decreasing directions after the transmission loss values ​​are sorted, and see if it is less than the fluctuation step. In the direction of increasing values, starting from the reference value, compare it with the adjacent transmission loss values ​​that are larger than it, calculate the difference between the two, and determine if the difference is less than the fluctuation step. If the difference is less than the fluctuation step, continue to calculate the difference of the next adjacent transmission loss value in the direction of larger values; if the difference is greater than the fluctuation step, stop calculating in that direction. Similarly, in the direction of decreasing values, starting from the reference value, compare it with the adjacent transmission loss values ​​that are smaller than it, calculate the difference and determine if it is less than the fluctuation step. Process according to the same rules as the direction of increasing values ​​until the difference is greater than the fluctuation step.

[0027] After calculations in both directions have ceased, the range of values ​​covered by all transmission loss values ​​included in the calculation is determined as the baseline fluctuation range of the stable parameter. For example, if the maximum transmission loss value included in the calculation in the increasing direction is A, and the minimum transmission loss value included in the calculation in the decreasing direction is B, then the baseline fluctuation range of the stable parameter is the range from B to A. This range includes all transmission loss values ​​within the normal fluctuation range and can accurately reflect the transmission loss fluctuation of the stable parameter under normal operating conditions.

[0028] When collecting transmission loss values, ensure data integrity and authenticity to avoid bias in subsequent calculations due to missing or erroneous data. When calculating the arithmetic mean and fluctuation step size, carefully verify the numerical value and order of each data point to ensure the accuracy of the calculation process. When determining the baseline fluctuation range, strictly follow the comparison rules for adjacent differences and fluctuation step sizes, and avoid arbitrarily expanding or reducing the range. This ensures that the baseline fluctuation range truly reflects the normal fluctuation characteristics of the stable parameter.

[0029] The benchmark fluctuation range determined in this way provides a clear reference range for subsequent judgments about the normality of the transmission loss value of the current stable parameter. When the current transmission loss value falls within this range, it indicates that the parameter is operating normally; when the transmission loss value exceeds this range, it indicates a possible abnormality and requires data correction. This method of determining the benchmark fluctuation range based on actual monitoring data can adapt to the characteristics of different stable parameters, ensuring the rationality and applicability of the benchmark fluctuation range, and providing a reliable basis for judgment during optical cable status monitoring.

[0030] Example 3: See Figure 4For each fluctuating parameter, the process of deriving its baseline fluctuation range based on the temperature fluctuation value and transmission loss value at each monitoring moment requires the following steps. For each fluctuating parameter, several associated environmental monitoring points are determined. These monitoring points must be distributed at key locations along the optical cable installation path and be able to fully reflect the temperature changes in the environment in which the parameter is located. These monitoring points together constitute the associated monitoring group for the fluctuating parameter.

[0031] Calculate the state difference of the associated monitoring group at different monitoring times. The calculation of the state difference needs to combine the transmission loss value of the fluctuation parameter and the temperature fluctuation value of the associated monitoring group, which is specifically achieved through the following formula:

[0032] in, Represents the state difference between two monitoring moments, For the The transmission loss value of the fluctuating parameter at each monitoring moment, For the The transmission loss value of the fluctuating parameter at each monitoring moment, is the number of environmental monitoring points in the associated monitoring group, For the Monitoring time The temperature fluctuation value of each environmental monitoring point, For the Monitoring time The temperature fluctuation value of each environmental monitoring point.

[0033] After calculating the state differences, the monitoring moments with the same state in the associated monitoring groups are grouped into the same set of monitoring moments based on the state differences. The grouping process begins by selecting a number of benchmark monitoring moments from all monitoring moments, evenly distributed throughout the monitoring cycle to cover states in different time periods. Next, the state difference between each benchmark monitoring moment and all other monitoring moments is calculated, and each non-baseline monitoring moment is grouped into the set containing the benchmark monitoring moment with the smallest state difference, forming a preliminary set of multiple monitoring moments.

[0034] In each set of monitoring moments, calculate the cumulative value of the state difference between each monitoring moment and all other monitoring moments in the set. The calculation of the cumulative value needs to traverse all monitoring moments in the set, and add the state differences between the target monitoring moment and each other monitoring moment one by one. Afterwards, determine whether the monitoring moment with the smallest cumulative value in the set is the initial benchmark monitoring moment of the set. If the monitoring moment with the smallest cumulative value is the initial benchmark monitoring moment, then the set is the set of monitoring moments with consistent states for the associated monitoring groups; if not, then the monitoring moment with the smallest cumulative value is re-used as the benchmark monitoring moment, and the above division process is repeated, that is, the state difference between the new benchmark monitoring moment and other monitoring moments is recalculated, the set is divided again and the cumulative value is calculated, until the monitoring moment with the smallest cumulative value in the set is found as the benchmark monitoring moment, and the set obtained at this time is the set of monitoring moments with consistent states.

[0035] For each set of consistent monitoring moments, the numerical distribution range of the temperature fluctuation values ​​associated with the fluctuating parameter within the set is obtained. This is the range between the minimum and maximum temperature fluctuation values ​​for each environmental monitoring point across all monitoring moments in the set. Simultaneously, the numerical distribution range of the transmission loss values ​​of the fluctuating parameter within the set is determined as the baseline fluctuation interval for the fluctuating parameter. This is the range between the minimum and maximum transmission loss values ​​for the parameter across all monitoring moments in the set.

[0036] Throughout the entire process, it is necessary to ensure that the operation of each step is based on the actual collected data, the number of environmental monitoring points of the associated monitoring group must be reasonably set according to the complexity of the optical cable laying environment, the calculation of state differences must be accurate, and the division and adjustment of the set must be strictly carried out in accordance with the comparison results of the accumulated values ​​to ensure that the final benchmark fluctuation range can truly reflect the normal fluctuation of the fluctuation type parameters under a specific temperature environment.

[0037] Example 4: The process of determining whether the transmission loss value of each monitoring parameter at the current moment meets the corresponding benchmark fluctuation range, and selecting the corrected data as the data source for optical cable status monitoring when it does not meet the requirements, needs to be operated separately for stable parameters and fluctuating parameters according to different situations.

[0038] For fluctuating parameters, the first step is to select a corresponding baseline fluctuation range from a pre-defined set of monitoring moments based on the current transmission loss value and the temperature fluctuation values ​​of several associated environmental monitoring points. For example, consider a fluctuating parameter associated with three environmental monitoring points. The current transmission loss value is 12dB, and the temperature fluctuation values ​​at the three monitoring points are 2°C, 3°C, and 2.5°C, respectively. From all sets of consistent monitoring moments, the goal is to find the set whose temperature fluctuation range for these three monitoring points is closest to the current temperature fluctuation value. Assuming there exists a set where the temperature fluctuation values ​​for the three monitoring points range from 1.5-2.5°C, 2.5-3.5°C, and 2-3°C, respectively, matching the current temperature fluctuation value, then the baseline fluctuation range corresponding to this set serves as the reference range. Next, check whether the transmission loss value of the fluctuation parameter 12dB at the current moment falls within the benchmark fluctuation range of this set. If the benchmark fluctuation range of the set is 10-13dB, then 12dB is within the range and is considered to be compliant; if the benchmark fluctuation range is 8-11dB, then 12dB is not within the range and is considered to be non-compliant.

[0039] For stable parameters, the determination is relatively straightforward: simply check whether the current transmission loss value is within a predetermined reference fluctuation range. For example, if the reference fluctuation range for a stable parameter is 5-7dB, and the current transmission loss value is 6dB, it is clearly within the range and meets the requirement. However, if the current value is 8dB, it is outside the range and does not meet the requirement.

[0040] When the transmission loss value of a monitored parameter does not conform to the corresponding reference fluctuation range, corrected data is selected as the data source for optical cable status monitoring. For stable parameters, the corrected data is the arithmetic mean of the reference fluctuation range. For example, if the reference fluctuation range of the stable parameter is 5-7dB and its arithmetic mean is 6dB, then when the current transmission loss value of that parameter does not conform to the range, 6dB is used as the corrected data.

[0041] For fluctuating parameters, the corrected data is derived from the set of monitoring moments corresponding to the benchmark fluctuation range that the current moment meets. For example, the temperature fluctuation value of a fluctuating parameter at the current moment meets the temperature distribution range of Set A. Set A contains five monitoring moments, and the transmission loss values ​​of this parameter at these five moments are 9dB, 10dB, 11dB, 10dB, and 10dB, respectively. The value distribution range is 9-11dB, and the arithmetic mean is 10dB. If the current transmission loss value of this parameter does not meet the benchmark fluctuation range of Set A, 10dB is used as the corrected data.

[0042] In practice, it is necessary to ensure that the environmental monitoring point data associated with each fluctuating parameter accurately matches the monitoring time set to avoid bias in the selection of the baseline fluctuation range due to incorrect environmental data matching. Furthermore, once the baseline fluctuation range for a stable parameter is determined, it should remain stable during subsequent monitoring, and frequent adjustments are not required unless there are significant changes in the installation environment or the cable's own state. Corrected data records must be distinguished from the original data, and the reason for the correction must be noted for subsequent traceability.

[0043] Throughout the entire process, the judgment and correction logic must strictly adhere to the classification of parameter types, and the treatment of stable and fluctuating parameters must not be confused. Whether directly using current data or selecting corrected data, the information ultimately used as the data source for optical cable status monitoring should be able to reflect the actual condition of the optical cable, providing a continuous and reliable basis for subsequent status assessments.

[0044] Example 5: Before collecting the optical fiber transmission loss value and the temperature fluctuation value of the optical cable laying environment at each monitoring moment, a series of preliminary preparations need to be carried out. First, collect the historical fault records of the optical cable laying area. These records cover detailed information about the optical cable failures in the area over the past period of time, including the time and specific location of the failure and the various parameter data at the time. From these historical fault records, extract the transmission loss threshold and temperature fluctuation threshold at each failure one by one. The transmission loss threshold refers to the critical value reached by the optical fiber transmission loss at the moment of failure or just before the failure occurs; the temperature fluctuation threshold refers to the critical value reached by the temperature fluctuation of the optical cable laying environment at the same moment. These thresholds can intuitively reflect the transmission performance of the optical cable and the specific state of the ambient temperature when a failure occurs.

[0045] After extracting sufficient transmission loss and temperature fluctuation thresholds, the initial monitoring sensitivity level is set based on these thresholds. The classification of monitoring sensitivity levels requires a comprehensive consideration of the transmission loss and temperature fluctuation thresholds. A low transmission loss threshold indicates that optical cable failures may occur even with minimal transmission loss. In this case, a higher monitoring sensitivity level is required to more accurately capture subtle changes in transmission loss. A low temperature fluctuation threshold indicates that even minor fluctuations in ambient temperature may trigger optical cable failures. Similarly, a higher monitoring sensitivity level is required to promptly detect temperature changes. Conversely, if both the transmission loss and temperature fluctuation thresholds are high, the monitoring sensitivity level can be appropriately lowered to avoid unnecessary data redundancy caused by excessive monitoring.

[0046] After determining the initial monitoring sensitivity level, the sampling interval corresponding to that level will serve as the basic sampling interval for the current monitoring cycle. Different monitoring sensitivity levels correspond to different sampling intervals. Higher sensitivity levels have shorter sampling intervals, allowing more monitoring data to be collected per unit time, thus more timely reflecting changes in the optical cable's status. Lower sensitivity levels have longer sampling intervals, resulting in a relatively small amount of collected data, making them suitable for use when the optical cable's status is relatively stable. For example, when the monitoring sensitivity level is set to high, the sampling interval might be every 5 minutes; when the level is set to medium, the sampling interval might be every 15 minutes; and when the level is set to low, the sampling interval might be every 30 minutes.

[0047] After setting the basic sampling interval, it also needs to be properly verified and adjusted. By reviewing the parameter change trends before the fault occurred in the historical fault records, check whether the set basic sampling interval can capture key parameter anomalies before the fault occurs. If it is found that the sampling interval corresponding to a certain sensitivity level fails to record the parameter changes before the fault in the past fault case, the sampling interval corresponding to that level needs to be adjusted to shorten the interval time to improve the timeliness of data collection. Conversely, if the sampling interval is too short, resulting in an excessive amount of data, and it contains a lot of repeated or meaningless information, the interval time can be appropriately extended to optimize the efficiency of data collection.

[0048] In addition, during the preparation process, it is also necessary to ensure the completeness and accuracy of the collected historical fault records. For transmission loss thresholds and temperature fluctuation thresholds that are missing or ambiguous in the records, they need to be verified and improved by consulting relevant maintenance logs, monitoring reports, and other supplementary materials to avoid unreasonable initial monitoring sensitivity level settings due to inaccurate data. At the same time, it is necessary to conduct on-site inspections of the current environment in the optical cable laying area to understand whether there are new factors that are different from historical conditions, such as new heat sources in the surrounding area and construction areas. These factors may affect the operating status of the optical cable and the threshold for fault occurrence. These new factors need to be taken into consideration when setting the initial monitoring sensitivity level to ensure that the basic sampling interval can adapt to the current actual situation.

[0049] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0050] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent optical cable monitoring method, characterized in that: include, Collect the optical fiber transmission loss value and the temperature fluctuation value of the optical cable laying environment at each monitoring moment; The monitoring parameters are divided into stable parameters and fluctuating parameters according to the transmission loss values ​​at multiple monitoring moments; For each stable parameter, the benchmark fluctuation range of the stable parameter is obtained according to the transmission loss value at each monitoring moment; For each fluctuating parameter, the reference fluctuation range of the fluctuating parameter is obtained according to the temperature fluctuation value and transmission loss value at each monitoring moment; Determine whether the transmission loss value of each monitoring parameter at the current moment meets the corresponding benchmark fluctuation range; If yes, the transmission loss value and temperature fluctuation value at the current moment are used as the data source for optical cable status monitoring; If not, the corrected data within the reference fluctuation range is selected as the data source for optical cable status monitoring.

2. The intelligent optical cable monitoring method according to claim 1, characterized in that: The step of dividing the monitoring parameters into stable parameters and fluctuating parameters according to the transmission loss values ​​at multiple monitoring moments includes: Obtaining a maximum transmission loss value and a minimum transmission loss value of each monitoring parameter at different monitoring moments according to the transmission loss value of each monitoring parameter at a plurality of monitoring moments; The ratio of the difference between the maximum transmission loss value and the minimum transmission loss value of the monitoring parameter at different monitoring times to the maximum transmission loss value is taken as the fluctuation coefficient of the monitoring parameter; Sort the fluctuation coefficient of each monitoring parameter by numerical value, and calculate the mean of the difference between each fluctuation coefficient and the adjacent fluctuation coefficients as the classification threshold; The monitoring parameter corresponding to the fluctuation coefficient whose difference with the adjacent fluctuation coefficients of the sorting is less than the classification threshold is used as a stable parameter; The monitoring parameter corresponding to the fluctuation coefficient whose difference with the adjacent fluctuation coefficients in the sorting is greater than the classification threshold is used as the fluctuation parameter.

3. The intelligent optical cable monitoring method according to claim 1, characterized in that: The step of obtaining the reference fluctuation range of the stable parameter according to the transmission loss value at each monitoring moment, include, For each stable parameter, perform the following steps separately, Calculating and obtaining reference values ​​of transmission loss values ​​at all monitoring moments, wherein the reference value includes an arithmetic mean value; The transmission loss values ​​at each monitoring moment are sorted according to their numerical values, and the mean of the difference between each transmission loss value and the adjacent transmission loss values ​​is calculated as the fluctuation step size; Starting from the reference value, calculate one by one along the increasing and decreasing directions of the transmission loss value sorting to see whether the difference between two adjacent transmission loss values ​​is less than the fluctuation step; if so, continue the calculation; if not, use the numerical distribution interval of the transmission loss values ​​included in the calculation as the benchmark fluctuation interval of the stable parameter.

4. The intelligent optical cable monitoring method according to claim 1, characterized in that: The step of obtaining the reference fluctuation range of the fluctuation parameter according to the temperature fluctuation value and the transmission loss value at each monitoring moment, include, For each fluctuation parameter, perform the following steps separately: Acquire a number of environmental monitoring points associated with the fluctuating parameter to form a related monitoring group for the fluctuating parameter; Calculate and obtain the cumulative value of the difference in transmission loss values ​​of the fluctuating parameters between different monitoring moments and the difference in temperature fluctuation values ​​of several environmental monitoring points as the state difference of the associated monitoring group between different monitoring moments; According to the status differences between the associated monitoring groups at different monitoring times, the monitoring times with the same status of the associated monitoring groups are divided into the same monitoring time set; For each monitoring time set, the numerical distribution range of the temperature fluctuation values ​​of several environmental monitoring points associated with the fluctuation type parameter is obtained, and the numerical distribution range of the transmission loss value of the fluctuation type parameter is used as the reference fluctuation interval.

5. The intelligent optical cable monitoring method according to claim 4, characterized in that: The step of dividing the monitoring moments with the same status of the associated monitoring groups into the same monitoring moment set according to the status differences between the associated monitoring groups at different monitoring moments includes: Select several monitoring moments from all monitoring moments as benchmark monitoring moments; Calculate and obtain the status difference between each benchmark monitoring moment and other monitoring moments; Classify the other monitoring moments other than each benchmark monitoring moment and the benchmark monitoring moment with the smallest state difference into the same monitoring moment set; In each monitoring time set, the cumulative value of the state difference between each monitoring time and all other monitoring times is calculated; Determine whether the monitoring moment with the smallest cumulative value of the state difference with all other monitoring moments in each monitoring moment set is the benchmark monitoring moment; if so, obtain a monitoring moment set with consistent states of associated monitoring groups; if not, reselect the benchmark monitoring moment, and re-divide the monitoring moment set to perform consistency judgment on the states of associated monitoring groups, until a monitoring moment set with consistent states of associated monitoring groups is obtained.

6. The intelligent optical cable monitoring method according to claim 5, characterized in that: The step of reselecting the reference monitoring time includes: The monitoring time with the smallest cumulative value of state differences between each monitoring time set and all other monitoring times is used as the reselected reference monitoring time.

7. An intelligent optical cable monitoring method according to claim 1 or 4, characterized in that: The step of determining whether the transmission loss value of each monitoring parameter at the current moment meets the corresponding reference fluctuation range, include, For each fluctuation parameter, perform the following steps separately: Selecting a set of monitoring moments that conform to a corresponding reference fluctuation interval based on the transmission loss value of the current fluctuation parameter and the temperature fluctuation values ​​of several environmental monitoring points associated with the fluctuation parameter; Determine whether the transmission loss value of the current fluctuation parameter falls within the reference fluctuation range of the monitoring time set; If so, it is determined that the transmission loss value of the fluctuation type parameter meets the corresponding benchmark fluctuation range; if not, it is determined that the transmission loss value of the fluctuation type parameter does not meet the corresponding benchmark fluctuation range.

8. An intelligent optical cable monitoring method according to claim 1 or 4, characterized in that: The step of selecting the corrected data within the reference fluctuation range as the data source for optical cable status monitoring includes: For stable parameters, the arithmetic mean of its benchmark fluctuation range is used as the revised data; For the fluctuating parameters, the arithmetic mean of the numerical distribution range of the transmission loss value of the fluctuating parameter at each monitoring moment contained in the set of monitoring moments that conform to the corresponding benchmark fluctuation interval at the current moment is taken as the corrected data.

9. The intelligent optical cable monitoring method according to claim 1, characterized in that: Before the step of collecting and obtaining the optical fiber transmission loss value and the temperature fluctuation value of the optical cable laying environment at each monitoring moment, include, Obtain historical fault records in the optical cable laying area and extract the transmission loss threshold and temperature fluctuation threshold when the historical fault occurred; Set the initial monitoring sensitivity level based on the transmission loss threshold and temperature fluctuation threshold in historical fault records; The sampling interval corresponding to the initial monitoring sensitivity level is used as the basic sampling interval of the current monitoring period.

10. An intelligent optical cable monitoring system, used to implement an intelligent optical cable monitoring method according to any one of claims 1 to 9, characterized in that: include, Fiber optic sensor, used to collect transmission loss data of optical cables; Environmental sensors are used to collect temperature fluctuation data of the optical cable laying environment; A data processing unit is used to extract the optical fiber transmission loss value and the temperature fluctuation value of the optical cable laying environment at each monitoring moment; The monitoring parameters are divided into stable parameters and fluctuating parameters according to the transmission loss values ​​at multiple monitoring moments; for each stable parameter, the reference fluctuation range of the stable parameter is obtained according to the transmission loss value at each monitoring moment; For each fluctuating parameter, the reference fluctuation range of the fluctuating parameter is obtained according to the temperature fluctuation value and transmission loss value at each monitoring moment; Determine whether the transmission loss value of each monitoring parameter at the current moment meets the corresponding benchmark fluctuation range; If yes, the transmission loss value and temperature fluctuation value at the current moment are used as the data source for optical cable status monitoring; If not, the corrected data within the reference fluctuation range is selected as the data source for optical cable status monitoring; A monitoring terminal, used for receiving a data source for optical cable status monitoring; The optical cable status monitoring data source is displayed in the monitoring terminal.

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