A smart optical cable monitoring system and method

Abstract

This invention relates to the field of optical cable monitoring technology, and discloses an intelligent optical cable monitoring system and method. The method first collects the optical fiber transmission loss value and the temperature fluctuation value of the optical cable laying environment at each monitoring moment; then, based on the transmission loss values ​​at multiple monitoring moments, the monitoring parameters are divided into stable parameters and fluctuating parameters; for stable parameters, their baseline fluctuation range is obtained based on the transmission loss value at each moment; for fluctuating parameters, their baseline fluctuation range is obtained by combining the temperature fluctuation value and the transmission loss value at each moment; then, it is determined whether the transmission loss value of each monitoring parameter at the current moment conforms to the corresponding baseline fluctuation range. If it does, the current transmission loss value and temperature fluctuation value are used as the optical cable status monitoring data source; if not, corrected data within the baseline fluctuation range is selected as the optical cable status monitoring data source. This method can more realistically determine optical cable transmission loss and ensure the effectiveness of the monitoring data source.

Description

Technical Field

[0001] This invention relates to the field of optical cable monitoring technology, specifically to an intelligent optical cable monitoring system and method. Background Technology

[0002] As an important carrier of information transmission, optical fiber cables are widely used in many fields such as communications, power, and transportation. The stability of their operation is directly related to the security and continuity of information transmission. Therefore, efficient and accurate monitoring of optical fiber cables is of utmost importance.

[0003] Most existing optical cable monitoring methods fail to differentiate the characteristics of the monitored parameters, employing a uniform benchmark range setting. However, in practical applications, the degree to which different monitoring parameters of optical cables are affected by their own performance and the external environment varies significantly. Some parameters exhibit relatively stable transmission loss changes during long-term operation, with minimal interference from environmental factors such as temperature; while others are more sensitive to environmental changes, and their transmission loss is easily affected by temperature fluctuations. Monitoring these parameters with different characteristics under the same benchmark framework leads to a mismatch between the benchmark range and the actual variation patterns of the parameters, making it difficult to accurately identify normal fluctuations and abnormal states.

[0004] Existing technologies have significant limitations in determining the baseline fluctuation range. For parameters less affected by the environment, some methods still introduce irrelevant environmental variables, leading to complex baseline range calculations and decreased accuracy. For parameters significantly affected by temperature, most methods only set the baseline range based on their transmission loss value, ignoring the direct impact of temperature fluctuations. When the ambient temperature changes significantly, the normal transmission loss fluctuation of the parameter may exceed the set baseline range, thus being misjudged as abnormal and affecting the accuracy of monitoring.

[0005] Existing methods often resort to simplistic approaches when dealing with transmission loss values ​​that do not conform to the baseline range: either discarding the data outright, leading to a break in the monitoring data source and an inability to reflect continuous changes in the optical cable's condition; or using fixed values ​​as substitutes, resulting in significant deviations between the substitute data and the actual situation, thus reducing the reliability of the monitoring data. This approach is insufficient to meet the needs of long-term, accurate monitoring of optical cables, especially in complex environments, and can easily lead to misjudgments or missed detections of potential optical cable faults.

[0006] With the continuous expansion of optical fiber networks and the increasing complexity of application scenarios, higher demands are placed on the accuracy, continuity, and reliability of monitoring data. The shortcomings of existing monitoring methods in areas such as parameter characteristic differentiation, benchmark interval setting, and abnormal data processing have become significant factors restricting the development of intelligent optical fiber monitoring. Therefore, a monitoring method that can specifically address these issues is urgently needed. Summary of the Invention

[0007] The purpose of this invention is to provide an intelligent optical cable monitoring system and method to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides an intelligent optical cable monitoring method, the method comprising:

[0009] The fiber optic transmission loss value and the temperature fluctuation value of the fiber optic cable laying environment were collected at each monitoring time.

[0010] Based on the transmission loss values ​​at multiple monitoring times, the monitoring parameters are divided into stable parameters and fluctuating parameters;

[0011] For each stable parameter, the baseline fluctuation range of the stable parameter is obtained based on the transmission loss value at each monitoring time.

[0012] For each fluctuating parameter, the baseline fluctuation range of the fluctuating parameter is obtained based on the temperature fluctuation value and transmission loss value at each monitoring time.

[0013] Determine whether the transmission loss value of each monitoring parameter at the current moment conforms to the corresponding baseline fluctuation range; if yes, then use the transmission loss value and temperature fluctuation value at the current moment as the data source for optical cable status monitoring; if not, then select the corrected data within the baseline fluctuation range as the data source for optical cable status monitoring.

[0014] Preferably, the step of classifying the monitoring parameters into stable parameters and fluctuating parameters based on the transmission loss values ​​at multiple monitoring times includes,

[0015] Based on the transmission loss value of each monitoring parameter at multiple monitoring times, the maximum and minimum transmission loss values ​​of each monitoring parameter at different monitoring times are obtained;

[0016] The ratio of the difference between the maximum and minimum transmission loss values ​​of the monitoring parameter at different monitoring times to the maximum transmission loss value is used as the fluctuation coefficient of the monitoring parameter.

[0017] The fluctuation coefficients of each monitoring parameter are sorted according to their numerical values, and the average difference between each fluctuation coefficient and its adjacent fluctuation coefficients is calculated as the classification threshold.

[0018] The monitoring parameters corresponding to the fluctuation coefficients whose difference from the adjacent fluctuation coefficients in the sorting is less than the classification threshold are taken as stable parameters.

[0019] The monitoring parameter corresponding to the fluctuation coefficient whose difference with the adjacent fluctuation coefficient is greater than the classification threshold is taken as the fluctuation type parameter.

[0020] Preferably, the step of obtaining the reference fluctuation range of the stable parameter based on the transmission loss value at each monitoring time includes,

[0021] For each stable parameter, perform the following steps separately.

[0022] Calculate reference values ​​for transmission loss at all monitoring times, wherein the reference values ​​include the arithmetic mean;

[0023] The transmission loss values ​​at each monitoring time are sorted according to their numerical values, and the average of the differences between each transmission loss value and the adjacent transmission loss values ​​in the sorting is calculated as the fluctuation step size.

[0024] Starting from the reference value, calculate the difference between two adjacent transmission loss values ​​in both increasing and decreasing directions along the transmission loss values. If the difference is less than the fluctuation step size, continue the calculation. If not, use the distribution range of the transmission loss values ​​included in the calculation as the reference fluctuation range of the stable parameter.

[0025] Preferably, the step of obtaining the reference fluctuation range of the fluctuation type parameter based on the temperature fluctuation value and transmission loss value at each monitoring time includes,

[0026] For each volatility parameter, perform the following steps separately.

[0027] Several environmental monitoring points associated with the fluctuating parameter are obtained and together form the associated monitoring group to which the fluctuating parameter belongs;

[0028] The difference in transmission loss values ​​of fluctuating parameters between different monitoring times and the sum of the differences in temperature fluctuation values ​​of several environmental monitoring points are calculated as the state difference of the associated monitoring group between different monitoring times.

[0029] Based on the state differences of the associated monitoring group at different monitoring times, monitoring times with the same state in the associated monitoring group are grouped into the same set of monitoring times;

[0030] For each set of monitoring times, the numerical distribution range of temperature fluctuation values ​​of several environmental monitoring points associated with the fluctuation parameter is obtained, and the numerical distribution range of transmission loss values ​​of the fluctuation parameter is used as the benchmark fluctuation range.

[0031] Preferably, the step of grouping monitoring times with consistent states within the same monitoring time set based on the state differences of the associated monitoring group at different monitoring times includes:

[0032] Select several monitoring times from all the monitoring times as the baseline monitoring times;

[0033] Calculate and obtain the state difference between each baseline monitoring time and other monitoring times;

[0034] The monitoring time with the smallest difference from the state, other than each benchmark monitoring time, is grouped into the same set of monitoring times.

[0035] Within each set of monitoring times, calculate the cumulative value of the state difference between each monitoring time and all other monitoring times;

[0036] Determine whether the monitoring time with the smallest cumulative value of state difference with all other monitoring times in each monitoring time set is the baseline monitoring time; if so, obtain the monitoring time set with consistent state of the associated monitoring group; if not, reselect the baseline monitoring time and redivide the monitoring time set to determine the consistency of state of the associated monitoring group, until the monitoring time set with consistent state of the associated monitoring group is obtained.

[0037] Preferably, the step of reselecting the reference monitoring time includes,

[0038] The monitoring time with the smallest cumulative state difference from all other monitoring times within each monitoring time set is selected as the benchmark monitoring time for reselection.

[0039] Preferably, the step of determining whether the transmission loss value of each monitoring parameter at the current moment conforms to the corresponding reference fluctuation range includes:

[0040] For each volatility parameter, perform the following steps separately.

[0041] Based on the transmission loss value of the fluctuation parameter at the current moment and the temperature fluctuation values ​​of several environmental monitoring points associated with the fluctuation parameter, select a set of monitoring times that conform to the corresponding benchmark fluctuation range;

[0042] Determine whether the transmission loss value of the fluctuating parameter at the current moment falls within the benchmark fluctuation range of the monitoring time set; if yes, then the transmission loss value of the fluctuating parameter is considered to conform to the corresponding benchmark fluctuation range; if no, then the transmission loss value of the fluctuating parameter is considered to not conform to the corresponding benchmark fluctuation range.

[0043] Preferably, the step of selecting corrected data as the data source for optical cable condition monitoring within the reference fluctuation range includes:

[0044] For stable parameters, the arithmetic mean of their baseline fluctuation range is used as the corrected data;

[0045] For fluctuating parameters, the arithmetic mean of the numerical distribution range of the transmission loss values ​​of the fluctuating parameters at each monitoring time included in the set of monitoring times that conform to the corresponding benchmark fluctuation range at the current time is used as the corrected data.

[0046] Preferably, before the step of acquiring the fiber optic transmission loss value and the temperature fluctuation value of the fiber optic cable laying environment at each monitoring time, the following steps are included:

[0047] Obtain historical fault records in the optical cable laying area and extract the transmission loss threshold and temperature fluctuation threshold at the time of the historical fault.

[0048] Set the initial monitoring sensitivity level based on the transmission loss threshold and temperature fluctuation threshold in historical fault records;

[0049] The sampling interval corresponding to the initial monitoring sensitivity level is used as the basic sampling interval for the current monitoring cycle.

[0050] Preferably, the present invention further includes an intelligent optical cable monitoring system for implementing the above-described intelligent optical cable monitoring method, the system comprising:

[0051] Fiber optic sensors are used to collect data on the transmission loss of optical cables.

[0052] Environmental sensors are used to collect temperature fluctuation data of the environment where optical cables are laid.

[0053] The data processing unit is used to extract the fiber optic transmission loss value and the temperature fluctuation value of the fiber optic cable laying environment at each monitoring time.

[0054] Based on the transmission loss values ​​at multiple monitoring times, the monitoring parameters are divided into stable parameters and fluctuating parameters. For each stable parameter, a baseline fluctuation range is obtained based on the transmission loss value at each monitoring time. For each fluctuating parameter, a baseline fluctuation range is obtained based on the temperature fluctuation value and transmission loss value at each monitoring time. It is then determined whether the transmission loss value of each monitoring parameter at the current time conforms to the corresponding baseline fluctuation range. If yes, the transmission loss value and temperature fluctuation value at the current time are used as the data source for optical cable status monitoring. If not, the corrected data within the baseline fluctuation range is selected as the data source for optical cable status monitoring.

[0055] The monitoring terminal is used to receive optical cable status monitoring data sources and display the optical cable status monitoring data sources in the monitoring terminal.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] This intelligent optical cable monitoring method effectively reflects the actual variation characteristics of different parameters by classifying and processing the monitoring parameters. In reality, the various monitoring parameters of optical cables are affected to varying degrees by their own properties and the external environment. Some parameters have stable transmission characteristics and are less affected by environmental interference, while others are prone to fluctuations with environmental factors such as temperature. Classifying them into stable and fluctuating parameters avoids the drawback of using a uniform standard for all parameters in traditional methods. This ensures that the monitoring benchmark for each parameter matches its own characteristics, reducing monitoring deviations caused by differences in parameter characteristics.

[0058] For stable parameters, the baseline fluctuation range is determined solely based on their transmission loss values ​​at multiple monitoring times, fully considering the inherent stability of this type of parameter. Since stable parameters are less affected by external environmental factors, their transmission loss fluctuations mainly 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 the monitoring of this type of parameter more targeted and avoiding baseline distortion caused by introducing irrelevant factors.

[0059] For fluctuating parameters, a baseline fluctuation range is determined by combining their transmission loss and temperature fluctuation values, fully considering the impact of environmental factors on these parameters. Temperature changes in the optical cable laying environment directly affect the transmission performance of some parameters. Ignoring temperature factors would result in the baseline range failing to cover the normal fluctuation range of parameters under different temperature conditions. Incorporating temperature fluctuations into the baseline range determination process allows the baseline range to be adaptively adjusted with temperature changes, more accurately reflecting the normal variation patterns of fluctuating parameters under different environments and reducing misjudgments caused by environmental fluctuations.

[0060] In terms of data processing, this method corrects transmission loss values ​​that do not conform to the benchmark fluctuation range before using them as monitoring data sources, rather than simply discarding them, thus ensuring the continuity of monitoring data. Optical cable status monitoring requires long-term, continuous data support; data interruptions can lead to the inability to fully track changes in the optical cable's status. By selecting corrected data within the benchmark range, interference from abnormal data on monitoring results is avoided, while maintaining the integrity of the data sequence, enabling the monitoring data source to continuously reflect the operational status of the optical cable.

[0061] The corrected data is derived from a baseline fluctuation range determined based on parameter characteristics and environmental factors. This ensures that the corrected data closely approximates the normal variation level of the parameters within a reasonable range, reducing monitoring bias caused by improper handling of data anomalies. This approach allows the monitoring data to maintain high reference value even when parameters experience brief abnormal fluctuations, better reflecting the actual operation of optical cables where parameters may experience momentary fluctuations but maintain a normal overall trend.

[0062] This method, through precise classification of parameter types, differentiated setting of benchmark intervals, and reasonable handling of abnormal data, enables the acquired optical cable status monitoring data to better reflect the actual operating status of the optical cable. The benchmark intervals for different parameters are adapted to their characteristics and environmental influences, and the correction and processing of abnormal data ensures the continuity and reliability of the data. Overall, this improves the quality of the monitoring data, helps to more accurately grasp the operating status of the optical cable, and promptly detects potential status changes. Attached Figure Description

[0063] Figure 1 This is a schematic diagram illustrating the working principle of the intelligent optical cable monitoring method described in this invention.

[0064] Figure 2 A flowchart illustrating the method for dividing monitoring parameters;

[0065] Figure 3 Design diagrams generated for the stable parameter benchmark fluctuation range;

[0066] Figure 4 A flowchart for generating the benchmark fluctuation range for volatility parameters. Detailed Implementation

[0067] 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.

[0068] Please see Figure 1 This invention provides a smart optical cable monitoring method, the method comprising:

[0069] The fiber optic transmission loss value and the temperature fluctuation value of the fiber optic cable laying environment were collected at each monitoring time.

[0070] Based on the transmission loss values ​​at multiple monitoring times, the monitoring parameters are divided into stable parameters and fluctuating parameters;

[0071] For each stable parameter, the baseline fluctuation range of the stable parameter is obtained based on the transmission loss value at each monitoring time.

[0072] For each fluctuating parameter, the baseline fluctuation range of the fluctuating parameter is obtained based on the temperature fluctuation value and transmission loss value at each monitoring time.

[0073] Determine whether the transmission loss value of each monitoring parameter at the current moment conforms to the corresponding baseline fluctuation range; if yes, then use the transmission loss value and temperature fluctuation value at the current moment as the data source for optical cable status monitoring; if not, then select the corrected data within the baseline fluctuation range as the data source for optical cable status monitoring.

[0074] Example 1: See Figure 2 The process of classifying monitoring parameters into stable and fluctuating parameters based on transmission loss values ​​at multiple monitoring times involves several sequential steps. For each monitoring parameter, its transmission loss values ​​at multiple monitoring times need to be collected. These monitoring times can be set at fixed time intervals or flexibly arranged according to actual monitoring needs, ensuring coverage of different time periods and possible environmental changes to obtain sufficiently comprehensive transmission loss data. After acquiring this data, the maximum and minimum transmission loss values ​​for each monitoring parameter at different monitoring times are extracted from all transmission loss values. These two values ​​represent the upper and lower limits of the parameter's transmission loss during the monitoring period, respectively, and can intuitively reflect the range of transmission loss variation.

[0075] Calculate the fluctuation coefficient for each monitoring parameter. Specifically, divide the difference between the maximum and minimum transmission loss values ​​of the parameter by the maximum transmission loss value; the result is the fluctuation coefficient for that monitoring parameter. The magnitude of the fluctuation coefficient directly reflects the relative fluctuation of the transmission loss of the parameter during the monitoring period. A larger value indicates a more significant change in transmission loss; a smaller value indicates relatively stable transmission loss.

[0076] After obtaining the fluctuation coefficients of all monitored parameters, these coefficients are sorted according to their numerical values. The purpose of this sorting is to clearly present the differences in the degree of fluctuation of different parameters, facilitating the subsequent identification of the boundary between stable and fluctuating parameters. After sorting, the difference between each fluctuation coefficient and its adjacent fluctuating coefficients is calculated, and then the average of these differences is taken 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 objectively reflect the naturally existing classification boundaries within the fluctuation coefficient group.

[0077] The monitoring parameters are classified according to a classification threshold. For each fluctuation coefficient, the difference between it and its adjacent fluctuation coefficients after sorting is examined. If the difference is less than the classification threshold, it indicates that the fluctuation coefficient is numerically close to its adjacent fluctuation coefficients, and the corresponding monitoring parameters have similar fluctuation characteristics in transmission loss. Therefore, it is classified as a stable parameter. The transmission loss of stable parameters changes little during the monitoring period, its fluctuation level is low, and it is relatively less affected by external factors.

[0078] If the difference between a fluctuation coefficient and its adjacent fluctuation coefficients exceeds the classification threshold, it indicates a significant numerical difference between the fluctuation coefficient and its neighbors. The corresponding monitoring parameter exhibits significantly different transmission loss fluctuation characteristics compared to other parameters, and is therefore classified as a fluctuation-type parameter. The transmission loss of fluctuation-type parameters varies considerably during the monitoring period, exhibiting a high degree of volatility and potentially being more susceptible to environmental factors, usage time, or other external conditions.

[0079] 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 time requires a series of sequential steps. For each parameter classified as stable, its transmission loss values ​​at all monitoring times need to be collected. These monitoring times can be recorded at different time periods and under different environmental conditions to ensure that the collected data comprehensively reflects the transmission loss of the parameter under normal operating conditions.

[0080] A reference value for these transmission loss values ​​is calculated, which is the arithmetic mean. To calculate the arithmetic mean, the transmission loss values ​​at all monitoring times are summed, and then divided by the total number of monitoring times. The result represents the central tendency of the transmission loss values ​​for this stable parameter. This reference value reflects the transmission loss level of this parameter in most situations and is an important starting point for subsequently determining the baseline fluctuation range.

[0081] After obtaining the reference values, the transmission loss values ​​at each monitoring time need to be sorted according to their numerical values. Sorting starts with the smallest transmission loss value and proceeds sequentially to the largest, forming an ordered sequence. This sorting method clearly shows the distribution of transmission loss values ​​and facilitates observation of differences between adjacent values. After sorting, the difference between each transmission loss value and its adjacent sorted values ​​is calculated, and then the average of these differences is taken as the fluctuation step size. The fluctuation step size reflects the average variation range between adjacent values ​​of the transmission loss value within the normal fluctuation range of this stable parameter, and is an important basis for judging whether the transmission loss value is within a reasonable fluctuation range.

[0082] Starting from the reference value, the calculation proceeds along both increasing and decreasing directions of the sorted transmission loss values, checking if the difference between any two adjacent transmission loss values ​​is less than the fluctuation step size. In the increasing direction, starting from the reference value, each value is compared to its larger adjacent transmission loss value, the difference is calculated, and it is determined whether this difference is less than the fluctuation step size. If the difference is less than the fluctuation step size, the calculation continues in the direction of increasing values ​​to find the next adjacent transmission loss value; if the difference is greater than the fluctuation step size, the calculation stops in that direction. Similarly, in the decreasing direction, starting from the reference value, each value is compared to its smaller adjacent transmission loss value, the difference is calculated, and it is determined whether this difference is less than the fluctuation step size. This process continues until a value greater than the fluctuation step size is encountered.

[0083] After calculations in both directions have ceased, the range of values ​​covered by all calculated transmission loss values ​​is defined as the baseline fluctuation range for the stable parameter. For example, if the maximum transmission loss value included in the calculation is A in the direction of increasing value, and the minimum transmission loss value included in the calculation is B in the direction of decreasing value, then the baseline fluctuation range for the stable parameter is the range from B to A. This range includes all transmission loss values ​​within the normal fluctuation range and accurately reflects the transmission loss fluctuation of the stable parameter under normal operating conditions.

[0084] When collecting transmission loss values, it is crucial to ensure the integrity and accuracy of the data to avoid deviations in subsequent calculations due to missing or incorrect data. When calculating the arithmetic mean and fluctuation step size, the value and sorting of each data point must be carefully verified to ensure the calculation process is error-free. When determining the baseline fluctuation range, the comparison rules between adjacent differences and fluctuation step sizes must be strictly followed; the range should not be arbitrarily expanded or reduced to ensure that the baseline fluctuation range accurately reflects the normal fluctuation characteristics of the stable parameters.

[0085] The baseline fluctuation range determined in this way provides a clear reference range for subsequently judging whether the transmission loss value of the stable parameters is normal at the current moment. When the transmission loss value falls within this range, it indicates that the parameter is in normal operating condition; when the transmission loss value exceeds this range, it indicates that there may be an anomaly, and data correction is required. This method of determining the baseline fluctuation range based on actual monitoring data can adapt to the characteristics of different stable parameters, ensuring the rationality and applicability of the baseline fluctuation range, and providing a reliable basis for judgment on optical cable condition monitoring.

[0086] Example 3: See Figure 4For each fluctuating parameter, the process of obtaining its baseline fluctuation range based on the temperature fluctuation value and transmission loss value at each monitoring time requires the following steps: Identify several associated environmental monitoring points for each fluctuating parameter. These monitoring points should be distributed at key locations along the optical cable laying path to comprehensively reflect the temperature changes in the environment where the parameter is located. These monitoring points together form the associated monitoring group for that fluctuating parameter.

[0087] Calculate the state differences of the associated monitoring group at different monitoring times. The calculation of state differences requires combining the transmission loss value of the fluctuation-type parameter and the temperature fluctuation value of the associated monitoring group, specifically achieved through the following formula:

[0088]

[0089] in, This indicates the state difference between two monitoring times. For the first The transmission loss value of fluctuating parameters at each monitoring time. For the first The transmission loss value of fluctuating parameters at each monitoring time. This refers to the number of environmental monitoring points in the associated monitoring group. For the first The monitoring time of the first monitoring moment Temperature fluctuation values ​​at each environmental monitoring point For the first The monitoring time of the first monitoring moment Temperature fluctuation values ​​at each environmental monitoring point.

[0090] After calculating the state differences, monitoring times with consistent states in related monitoring groups are grouped into the same set of monitoring times based on these differences. The grouping process begins by selecting several benchmark monitoring times from all monitoring times. These benchmark times can be evenly distributed throughout the monitoring period to cover states in different time periods. Next, the state difference between each benchmark monitoring time and all other monitoring times is calculated. Each non-benchmark monitoring time is then assigned to the set containing the benchmark monitoring time with the smallest state difference, forming initial sets of multiple monitoring times.

[0091] Within each set of monitoring times, the cumulative value of the state difference between each monitoring time and all other monitoring times in the set is calculated. This calculation requires iterating through all monitoring times in the set, adding the state difference between the target monitoring time and each other monitoring time. Then, it is determined whether the monitoring time with the smallest cumulative value in the set is the original baseline monitoring time for that set. If the monitoring time with the smallest cumulative value is the original baseline monitoring time, then this set is the set of monitoring times with consistent states in the associated monitoring group. If not, the monitoring time with the smallest cumulative value is re-established as the baseline monitoring time, and the above partitioning process is repeated: the state difference between the new baseline monitoring time and other monitoring times is recalculated, the sets are partitioned again, and the cumulative value is calculated again, until the monitoring time with the smallest cumulative value in the set is found as the baseline monitoring time. The resulting set is the set of monitoring times with consistent states.

[0092] For each set of monitoring times with consistent status, it is necessary to obtain the numerical distribution range of temperature fluctuation values ​​of several environmental monitoring points associated with the fluctuation parameter within that set, that is, the range between the minimum and maximum temperature fluctuation values ​​of each environmental monitoring point across all monitoring times in that set. Simultaneously, the numerical distribution range of the transmission loss value of the fluctuation parameter within that set is determined as the baseline fluctuation range of that fluctuation parameter, that is, the range between the minimum and maximum transmission loss values ​​of that parameter across all monitoring times in that set.

[0093] Throughout the process, it is necessary to ensure that each step is based on the actual collected data, the number of environmental monitoring points in the associated monitoring group is 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 according to the comparison results of the accumulated values, so as to ensure that the final benchmark fluctuation range can truly reflect the normal fluctuation of the fluctuation parameters under specific temperature conditions.

[0094] Example 4: The process of determining whether the transmission loss value of each monitoring parameter at the current moment conforms to the corresponding benchmark fluctuation range, and selecting the corrected data as the data source for optical cable status monitoring when it does not conform, requires separate operations for stable parameters and fluctuating parameters depending on the situation.

[0095] For fluctuating parameters, the first step is to select a baseline fluctuation range from a pre-defined set of monitoring times based on the current transmission loss value and the temperature fluctuation values ​​of several associated environmental monitoring points. For example, if a fluctuating parameter is associated with three environmental monitoring points, and the current transmission loss value is 12dB, with temperature fluctuation values ​​of 2℃, 3℃, and 2.5℃ at the three monitoring points, then it is necessary to find the set from all monitoring times with consistent conditions where the temperature fluctuation range of these three environmental monitoring points is closest to the current temperature fluctuation value. Assuming there exists a set where the temperature fluctuation ranges of the three environmental monitoring points are 1.5-2.5℃, 2.5-3.5℃, and 2-3℃, respectively, matching the current temperature fluctuation value, then the baseline fluctuation range corresponding to this set is the range to be referenced. Next, check whether the transmission loss value of the fluctuation parameter of 12dB at the current moment falls within the reference fluctuation range of this set. If the reference fluctuation range of this set is 10-13dB, then 12dB is within the range and is considered to be compliant; if the reference fluctuation range is 8-11dB, then 12dB is not within the range and is considered to be compliant.

[0096] For stable parameters, the judgment method is relatively straightforward: simply check whether the current transmission loss value is within the established baseline fluctuation range. For example, if the baseline fluctuation range for a certain stable parameter is 5-7 dB, and its current transmission loss value is 6 dB, it is clearly within the range and meets the requirements; if the current value is 8 dB, it is outside the range and therefore does not meet the requirements.

[0097] When the transmission loss value of a monitored parameter does not conform to the corresponding baseline fluctuation range, the corrected data needs to be selected as the data source for optical cable status monitoring. For stable parameters, the corrected data is the arithmetic mean of its baseline fluctuation range. For example, if the baseline fluctuation range of the above stable parameter is 5-7dB and its arithmetic mean is 6dB, then when the current transmission loss value of this parameter does not conform to the range, 6dB will be used as the corrected data.

[0098] For fluctuating parameters, the corrected data is derived from the set of monitoring times corresponding to the baseline fluctuation range that the current time conforms to. For example, if the temperature fluctuation value of a certain fluctuating parameter at the current time conforms to the temperature distribution range of set A, which contains 5 monitoring times, and the transmission loss values ​​of this parameter at these 5 times are 9dB, 10dB, 11dB, 10dB, and 10dB respectively, with a value distribution range of 9-11dB and an arithmetic mean of 10dB, then if the current transmission loss value of this parameter does not conform to the baseline fluctuation range of set A, then 10dB is used as the corrected data.

[0099] In practice, it is crucial to ensure accurate matching between the environmental monitoring point data associated with each fluctuating parameter and the monitoring time set, avoiding deviations in the selection of the baseline fluctuation range due to incorrect environmental data correspondence. Simultaneously, once the baseline fluctuation range for stable parameters is determined, it should remain stable in subsequent monitoring unless there are significant changes in the fiber optic cable laying environment or its own condition; otherwise, frequent adjustments are unnecessary. Records of corrected data must be distinguished from the original data, and the reason for the correction must be noted for future traceability.

[0100] Throughout the process, the judgment and correction logic must strictly adhere to the parameter type classification, and the handling methods for stable and fluctuating parameters must not be confused. Whether using data from the current moment directly or selecting corrected data, the information ultimately used as the data source for optical cable condition monitoring should reflect the actual condition of the optical cable, providing a continuous and reliable basis for subsequent condition assessments.

[0101] Example 5: Before collecting the fiber optic transmission loss value and the temperature fluctuation value of the fiber optic cable laying environment at each monitoring moment, a series of preparatory work needs to be carried out. First, historical fault records of the fiber optic cable laying area are collected. These records cover detailed information on fiber optic cable faults that occurred in the area over a period of time, including the time of the fault, the specific location, and various parameter data at that time. From these historical fault records, the transmission loss threshold and temperature fluctuation threshold at each fault occurrence are extracted one by one. The transmission loss threshold refers to the critical value reached by the fiber optic transmission loss at the moment of the fault or the moment before the fault occurs; the temperature fluctuation threshold is the critical value reached by the temperature fluctuation of the fiber optic cable laying environment at the same moment. These thresholds can intuitively reflect the specific state of the fiber optic cable's transmission performance and the ambient temperature when a fault occurs.

[0102] After extracting sufficient transmission loss and temperature fluctuation thresholds, the initial monitoring sensitivity level is set based on these thresholds. The determination of the monitoring sensitivity level requires comprehensive consideration of the magnitude of both the transmission loss and temperature fluctuation thresholds. A low transmission loss threshold means that the optical cable may fail even with minimal transmission loss; in this case, a higher monitoring sensitivity level is needed to more precisely capture subtle changes in transmission loss. Similarly, a low temperature fluctuation threshold indicates that even small fluctuations in ambient temperature can trigger optical cable failures; again, a higher monitoring sensitivity level is necessary to promptly detect temperature changes. Conversely, if both the transmission loss and temperature fluctuation thresholds are high, the monitoring sensitivity level can be appropriately reduced to avoid unnecessary data redundancy due to over-monitoring.

[0103] After determining the initial monitoring sensitivity level, the sampling interval corresponding to that level is used as the base sampling interval for the current monitoring cycle. Different monitoring sensitivity levels correspond to different sampling intervals. A higher sensitivity level results in a shorter sampling interval, allowing for the collection of more monitoring data per unit time, thus reflecting changes in the optical cable's condition more promptly. Conversely, a lower sensitivity level results in a longer sampling interval, collecting relatively less data, which is suitable for use when the optical cable's condition is relatively stable. For example, when the monitoring sensitivity level is set to high, the sampling interval might be once every 5 minutes; when the level is set to medium, the sampling interval might be once every 15 minutes; and when the level is set to low, the sampling interval might be once every 30 minutes.

[0104] After setting the basic sampling interval, it is necessary to verify and adjust it appropriately. By reviewing the parameter change trends before the fault occurred in historical fault records, check whether the set basic sampling interval can capture key parameter anomalies before the fault occurred. If it is found that the sampling interval corresponding to a certain sensitivity level failed to record parameter changes before the fault in a timely manner in past fault cases, the sampling interval corresponding to that level needs to be adjusted to shorten the interval time to improve the timeliness of data acquisition. Conversely, if the sampling interval is too short, resulting in an excessive amount of data, and contains a large amount of repetitive or meaningless information, the interval time can be appropriately extended to optimize the efficiency of data acquisition.

[0105] Furthermore, during the preparation process, it is essential to ensure the completeness and accuracy of the collected historical fault records. For transmission loss thresholds and temperature fluctuation thresholds that are missing or unclear in the records, verification and improvement are necessary by consulting relevant maintenance logs, monitoring reports, and other supplementary materials to avoid inaccurate data leading to unreasonable initial monitoring sensitivity level settings. Simultaneously, a field investigation of the current environment in the fiber optic cable laying area is crucial to identify any new factors that differ from historical conditions, such as newly added heat sources or construction areas. These factors may affect the operating status of the fiber optic cable and the fault occurrence threshold. These new factors must be taken into account when setting the initial monitoring sensitivity level to ensure that the basic sampling interval is adapted to the current situation.

[0106] 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.

[0107] 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. A method for monitoring intelligent optical cables, characterized in that, include, The fiber optic transmission loss value and the temperature fluctuation value of the fiber optic cable laying environment were collected at each monitoring time. Based on the transmission loss values ​​at multiple monitoring times, the monitoring parameters are divided into stable parameters and fluctuating parameters; For each stable parameter, the baseline fluctuation range of the stable parameter is obtained based on the transmission loss value at each monitoring time. For each fluctuating parameter, the baseline fluctuation range of the fluctuating parameter is obtained based on the temperature fluctuation value and transmission loss value at each monitoring time. Determine whether the transmission loss value of each monitored parameter at the current moment conforms to the corresponding baseline fluctuation range; If so, the current transmission loss value and temperature fluctuation value will be used as the data source for optical cable status monitoring. If not, then the corrected data within the baseline fluctuation range shall be selected as the data source for optical cable status monitoring. The step of obtaining the reference fluctuation range of the fluctuation type parameter based on the temperature fluctuation value and transmission loss value at each monitoring time. include, For each volatility parameter, perform the following steps separately. Several environmental monitoring points associated with the fluctuating parameter are obtained and together form the associated monitoring group to which the fluctuating parameter belongs; The difference in transmission loss values ​​of fluctuating parameters between different monitoring times and the sum of the differences in temperature fluctuation values ​​of several environmental monitoring points are calculated as the state difference of the associated monitoring group between different monitoring times. Based on the state differences of the associated monitoring group at different monitoring times, monitoring times with the same state in the associated monitoring group are grouped into the same set of monitoring times; For each set of monitoring times, obtain the numerical distribution range of temperature fluctuation values ​​of several environmental monitoring points associated with the fluctuation parameter, and use the numerical distribution range of transmission loss values ​​of the fluctuation parameter as the benchmark fluctuation range. The step of determining whether the transmission loss value of each monitoring parameter at the current moment conforms to the corresponding benchmark fluctuation range. include, For each volatility parameter, perform the following steps separately. Based on the transmission loss value of the fluctuation parameter at the current moment and the temperature fluctuation values ​​of several environmental monitoring points associated with the fluctuation parameter, select a set of monitoring times that conform to the corresponding benchmark fluctuation range; Determine whether the transmission loss value of the fluctuating parameter at the current moment falls within the baseline fluctuation range of the monitoring time set; If so, the transmission loss value of the fluctuation parameter is considered to conform to the corresponding benchmark fluctuation range; If not, then the transmission loss value of the fluctuation parameter is deemed not to conform to the corresponding benchmark fluctuation range; The step of selecting corrected data as the data source for optical cable condition monitoring within the reference fluctuation range includes: For stable parameters, the arithmetic mean of their baseline fluctuation range is used as the corrected data; For fluctuating parameters, the arithmetic mean of the numerical distribution range of the transmission loss values ​​of the fluctuating parameters at each monitoring time included in the set of monitoring times that conform to the corresponding benchmark fluctuation range at the current time is used as the corrected data.

2. The intelligent optical cable monitoring method according to claim 1, characterized in that, The step of classifying the monitoring parameters into stable parameters and fluctuating parameters based on the transmission loss values ​​at multiple monitoring times includes, Based on the transmission loss value of each monitoring parameter at multiple monitoring times, the maximum and minimum transmission loss values ​​of each monitoring parameter at different monitoring times are obtained; The ratio of the difference between the maximum and minimum transmission loss values ​​of the monitoring parameter at different monitoring times to the maximum transmission loss value is used as the fluctuation coefficient of the monitoring parameter. The fluctuation coefficients of each monitoring parameter are sorted according to their numerical values, and the average difference between each fluctuation coefficient and its adjacent fluctuation coefficients is calculated as the classification threshold. The monitoring parameters corresponding to the fluctuation coefficients whose difference from the adjacent fluctuation coefficients in the sorting is less than the classification threshold are taken as stable parameters. The monitoring parameter corresponding to the fluctuation coefficient whose difference with the adjacent fluctuation coefficient is greater than the classification threshold is taken as the fluctuation type 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 parameters based on the transmission loss value at each monitoring time. include, For each stable parameter, perform the following steps separately. Calculate reference values ​​for transmission loss at all monitoring times, wherein the reference values ​​include the arithmetic mean; The transmission loss values ​​at each monitoring time are sorted according to their numerical values, and the average of the differences between each transmission loss value and the adjacent transmission loss values ​​in the sorting is calculated as the fluctuation step size. Starting from the reference value, calculate the difference between two adjacent transmission loss values ​​in both increasing and decreasing directions along the transmission loss values. If the difference is less than the fluctuation step size, continue the calculation. If not, use the distribution range of the transmission loss values ​​included in the calculation as the reference fluctuation range of the stable parameter.

4. The intelligent optical cable monitoring method according to claim 1, characterized in that, The step of grouping monitoring times with consistent states within the same monitoring time set based on the state differences of the associated monitoring group at different monitoring times includes: Select several monitoring times from all the monitoring times as the baseline monitoring times; Calculate and obtain the state difference between each baseline monitoring time and other monitoring times; The monitoring time with the smallest difference from the state, other than each benchmark monitoring time, is grouped into the same set of monitoring times. Within each set of monitoring times, calculate the cumulative value of the state difference between each monitoring time and all other monitoring times; Determine whether the monitoring time with the smallest cumulative value of state difference with all other monitoring times in each monitoring time set is the baseline monitoring time; if so, obtain the monitoring time set with consistent state of the associated monitoring group; if not, reselect the baseline monitoring time and redivide the monitoring time set to determine the consistency of state of the associated monitoring group, until the monitoring time set with consistent state of the associated monitoring group is obtained.

5. The intelligent optical cable monitoring method according to claim 4, characterized in that, The step of reselecting the reference monitoring time includes, The monitoring time with the smallest cumulative state difference from all other monitoring times within each monitoring time set is selected as the benchmark monitoring time for reselection.

6. The intelligent optical cable monitoring method according to claim 1, characterized in that, Before the step of collecting the fiber optic transmission loss value and the temperature fluctuation value of the fiber optic cable laying environment at each monitoring time. include, Obtain historical fault records in the optical cable laying area and extract the transmission loss threshold and temperature fluctuation threshold at the time of the historical fault. 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 for the current monitoring cycle.

7. An intelligent optical cable monitoring system, used to implement the intelligent optical cable monitoring method as described in any one of claims 1 to 6, characterized in that, include, Fiber optic sensors are used to collect data on the transmission loss of optical cables. Environmental sensors are used to collect temperature fluctuation data of the environment where optical cables are laid. The data processing unit is used to extract the fiber optic transmission loss value and the temperature fluctuation value of the fiber optic cable laying environment at each monitoring time. The monitoring parameters are divided into stable parameters and fluctuating parameters based on the transmission loss values ​​at multiple monitoring times; for each stable parameter, the baseline fluctuation range of the stable parameter is obtained based on the transmission loss value at each monitoring time. For each fluctuating parameter, the baseline fluctuation range of the fluctuating parameter is obtained based on the temperature fluctuation value and transmission loss value at each monitoring time. Determine whether the transmission loss value of each monitored parameter at the current moment conforms to the corresponding baseline fluctuation range; If so, the current transmission loss value and temperature fluctuation value will be used as the data source for optical cable status monitoring. If not, then the corrected data within the baseline fluctuation range shall be selected as the data source for optical cable status monitoring. The monitoring terminal is used to receive optical cable status monitoring data sources and display the optical cable status monitoring data sources in the monitoring terminal. The data processing unit is also used for: For each volatility parameter, perform the following steps separately. Several environmental monitoring points associated with the fluctuating parameter are obtained and together form the associated monitoring group to which the fluctuating parameter belongs; The difference in transmission loss values ​​of fluctuating parameters between different monitoring times and the sum of the differences in temperature fluctuation values ​​of several environmental monitoring points are calculated as the state difference of the associated monitoring group between different monitoring times. Based on the state differences of the associated monitoring group at different monitoring times, monitoring times with the same state in the associated monitoring group are grouped into the same set of monitoring times; For each set of monitoring times, obtain the numerical distribution range of temperature fluctuation values ​​of several environmental monitoring points associated with the fluctuation parameter, and use the numerical distribution range of transmission loss values ​​of the fluctuation parameter as the benchmark fluctuation range. The data processing unit is also used for: For each volatility parameter, perform the following steps separately. Based on the transmission loss value of the fluctuation parameter at the current moment and the temperature fluctuation values ​​of several environmental monitoring points associated with the fluctuation parameter, select a set of monitoring times that conform to the corresponding benchmark fluctuation range; Determine whether the transmission loss value of the fluctuating parameter at the current moment falls within the baseline fluctuation range of the monitoring time set; If yes, then the transmission loss value of the fluctuation parameter is considered to conform to the corresponding benchmark fluctuation range; if no, then the transmission loss value of the fluctuation parameter is considered to not conform to the corresponding benchmark fluctuation range. The data processing unit is also used for: For stable parameters, the arithmetic mean of their baseline fluctuation range is used as the corrected data; For fluctuating parameters, the arithmetic mean of the numerical distribution range of the transmission loss values ​​of the fluctuating parameters at each monitoring time included in the set of monitoring times that conform to the corresponding benchmark fluctuation range at the current time is used as the corrected data.

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