OPGW optical cable health condition evaluation method and system

Abstract

The present application relates to a kind of OPGW cable health condition evaluation method, comprising: S1: collection OPGW cable equipment evaluation index data;S2: according to the first weight of index data numerical distribution calculation;S3: according to the correlation between each index data calculation second weight;S4: according to the first weight and second weight, obtain fusion weight;S5: determine OPGW cable health state index value, assess cable health state.The present application according to the first weight of index data numerical distribution calculation;According to the correlation between each index data calculation second weight;According to the first weight and second weight, obtain fusion weight;Determine OPGW cable health state index value, assess cable health state.The algorithm of the present application can accurately evaluate the health state of OPGW cable, and provide reasonable and effective theoretical support for the equipment state management and routine operation of OPGW cable.

Description

Technical Field

[0001] This invention relates to a method and system for assessing the health status of OPGW optical cables, belonging to the field of OPGW optical cable maintenance technology. Background Technology

[0002] With the development and expansion of power optical transmission networks, the number of OPGW optical cables is rapidly increasing, and their health status directly affects the reliability and risk level of the power optical transmission network. Current technologies typically assess the lifespan of OPGW optical cables by measuring their optical path loss. However, in real-world scenarios, the health of OPGW optical cables is influenced by a complex and diverse range of factors. The health status is not only related to the cable's own parameters but may also be related to its structure and the environment. Therefore, current technologies for assessing the health status of OPGW optical cables have significant errors and are unsuitable as a basis for actual operation and maintenance. Summary of the Invention

[0003] To overcome the aforementioned problems, this invention provides a method and system for assessing the health status of OPGW optical cables. The method calculates a first weight based on the numerical distribution of indicator data; calculates a second weight based on the correlation between the indicator data; obtains a fusion weight based on the first and second weights; determines the health status indicator values ​​of the OPGW optical cable, and assesses the cable's health status. This invention's algorithm can accurately assess the health status of OPGW optical cables, providing reasonable and effective theoretical support for the equipment status management and daily operation and maintenance of OPGW optical cables.

[0004] The technical solution of the present invention is as follows:

[0005] First aspect

[0006] A method for assessing the health status of OPGW optical cables, comprising:

[0007] S1: Collect evaluation index data for OPGW optical cable equipment;

[0008] S2: Calculate the first weight based on the numerical distribution of the indicator data;

[0009] S3: Calculate the second weight based on the correlation between the data of each indicator;

[0010] S4: Obtain the fusion weight based on the first and second weights;

[0011] S5: Determine the health status index values ​​of the OPGW optical cable and assess its health status.

[0012] Furthermore, the indicators include optical cable type, manufacturer, fiber core occupancy rate, optical cable sag, optical cable tension, temperature, humidity, wind speed, historical failure count, scheduled inspection rate, scheduled inspection evaluation, and commissioning time.

[0013] Furthermore, step S2 specifically involves:

[0014] Calculate the first weight W1 based on the numerical distribution of the indicator data, and let:

[0015]

[0016]

[0017] Where G(i) represents the distribution of the values ​​of the i-th indicator, n is the number of indicators, m is the number of possible values ​​for the indicator, and p j This represents the probability of the indicator value occurring.

[0018] Furthermore, step S3 specifically includes:

[0019] The data for each indicator are discretized and sorted in ascending order to form a sequence, and then normalized. The normalization formula is as follows:

[0020]

[0021] Among them, X i (k) represents the k-th value of index i. X′ is the maximum value of index i. i (k) is the normalized index value;

[0022] The average of all data for each sequence is calculated using the following formula:

[0023]

[0024] The average of all corresponding data in the sequence is used to construct a parent sequence X′0, which serves as the reference sequence. The calculation formula is as follows:

[0025] X'0={X'0(1),X'0(2),…,X'0(K)},

[0026] Where n is the number of indicators and K is the length of the sequence;

[0027] Calculate the sum of the absolute values ​​of the differences between corresponding elements of each sequence and the parent sequence, and then calculate the independence coefficient of each sequence.

[0028]

[0029] The second weight W2 is obtained through the independent coefficients:

[0030]

[0031] Furthermore, step S4 specifically involves:

[0032] The aforementioned set of indicators forms the identification framework:

[0033] Ω = {Ω1,Ω2,...,Ω} n};

[0034] Among them, Ω i For the i-th indicator;

[0035] The weights of each indicator, calculated using the first and second weight methods, are mapped to the basic confidence assignment mass function of the criterion under this method. This mapping satisfies:

[0036]

[0037] Where mass1(i) and mass2(i) are the basic criterion confidence of the index under the first weight and second weight calculation methods, respectively;

[0038] To determine whether the basic criterion confidence of index i is in the compatibility region under the two weighting calculation methods, let:

[0039]

[0040] Among them, D B Let D be the set of criteria whose basic criterion confidence falls within the compatibility region under the two weighting calculation methods. R This refers to the set of criteria whose basic criterion confidence is in the fuzzy domain under the two weighting calculation methods.

[0041] Calculate the combined weight W(i) of the first and second weights of index i:

[0042]

[0043]

[0044] Where A and B are the basic criteria in the identification framework, and C is the conflict coefficient.

[0045] Furthermore, step S5 specifically involves:

[0046] The original construction matrix is ​​obtained based on the index values ​​of each OPGW optical cable equipment:

[0047]

[0048] Where, x mn This represents the nth index value of the mth OPGW optical cable device;

[0049] To construct the norm-normalized matrix, divide each column element by the norm of the current column vector, as shown in the following formula:

[0050]

[0051] The normalized matrix Z is obtained after normalization:

[0052]

[0053] Determine the optimal performance and the worst performance, where the optimal performance Z + is composed of the maximum values of the elements in each column of the standardized matrix Z, and the worst performance Z - is composed of the minimum values of the elements in each column of the standardized matrix Z. Let

[0054] Calculate the proximity of the performance of the i-th OPGW cable device to the optimal performance and the worst performance. The formula is as follows:

[0055]

[0056]

[0057] where W j is the fusion weight of the index;

[0058] Obtain the health index of the i-th OPGW cable device:

[0059]

[0060] Furthermore, step S5 further includes:

[0061] Evaluate the health status of the OPGW cable device through the health index, where:

[0062] When 0 < HI ≤ 1, the optical cable is evaluated as a serious state;

[0063] When 1 < HI ≤ 2, the optical cable is evaluated as an abnormal state;

[0064] When 2 < HI ≤ 3, the optical cable is evaluated as a state of attention;

[0065] When 3 < HI ≤ 4, the optical cable is evaluated as a normal state.

[0066] In the second aspect

[0067] An OPGW cable health status evaluation system includes a data acquisition unit, a data processing unit, a data storage unit, and an early warning unit;

[0068] The data acquisition unit acquires the index data of the OPGW cable device and stores it in the data storage unit;

[0069] The data processing unit processes the index data through the OPGW cable health status evaluation method described in the first aspect, evaluates the health status of the OPGW cable device, and stores the evaluation result in the data storage unit;

[0070] The early warning unit provides early warnings about the health status of the OPGW optical cable equipment based on the assessment results.

[0071] Furthermore, the data acquisition unit periodically collects indicator data of the OPGW optical cable equipment. After each assessment of the health status of the OPGW optical cable equipment, the data processing unit compares the assessment results with the previous assessment results and displays the change in the two assessment results through the early warning unit.

[0072] Third aspect

[0073] A storage medium storing a computer program that, when executed, implements the OPGW optical cable health status assessment method described in the first aspect, processes OPGW optical cable equipment assessment index data, and obtains assessment results.

[0074] The present invention has the following beneficial effects:

[0075] This method comprehensively considers the distribution of data indicator values ​​and the correlation between indicators, proposing a method and system for assessing the health status of OPGW optical cables. It reduces the overall weight of indicators with large differences in weight across different methods, emphasizes the overall weight of indicators with consistent weights across different methods, reduces the impact of one-sided analysis on the overall weight, and achieves accurate assessment of the health status of OPGW optical cables. Attached Figure Description

[0076] Figure 1 This is a flowchart of the method of the present invention.

[0077] Figure 2 The index weights are for the compatibility domains in this embodiment of the invention. Detailed Implementation

[0078] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0079] First aspect

[0080] refer to Figure 1 A method for assessing the health status of OPGW optical cables, comprising:

[0081] S1: Collect evaluation index data for OPGW optical cable equipment;

[0082] S2: Calculate the first weight based on the numerical distribution of the indicator data;

[0083] S3: Calculate the second weight based on the correlation between the data of each indicator;

[0084] S4: Obtain the fusion weight based on the first and second weights;

[0085] S5: Determine the health status index values ​​of the OPGW optical cable and assess its health status.

[0086] This invention comprehensively considers the distribution of data indicator values ​​and the correlation between indicators, reduces the overall weight of indicators with large differences in indicator weights under different methods, highlights the overall weight of indicators with consistent weights under different methods, reduces the impact of one-sided analysis on the overall weight, and achieves accurate assessment of the health status of OPGW optical cables.

[0087] In one embodiment of the present invention, the indicators include optical cable type, manufacturer, fiber core occupancy rate, optical cable sag, optical cable tension, temperature, humidity, wind speed, number of historical faults, scheduled inspection rate, scheduled inspection evaluation, and commissioning time.

[0088] This implementation method, based on existing technology, also takes into account the impact of the structure and environmental conditions of the OPGW optical cable equipment on the monitoring status of the OPGW optical cable.

[0089] In one embodiment of the present invention, step S2 specifically comprises:

[0090] Calculate the first weight W1 based on the numerical distribution of the indicator data, and let:

[0091]

[0092]

[0093] Where G(i) represents the distribution of the values ​​of the i-th indicator, n is the number of indicators, m is the number of possible values ​​for the indicator, and p j This represents the probability of the indicator value occurring.

[0094] In one embodiment of the present invention, step S3 specifically includes:

[0095] The data for each indicator are discretized and sorted in ascending order to form a sequence, and then normalized. The normalization formula is as follows:

[0096]

[0097] Among them, X i (k) represents the k-th value of index i. X is the maximum value of index i. i '(k) is the normalized index value;

[0098] The average of all data for each sequence is calculated using the following formula:

[0099]

[0100] The average of all corresponding data in the sequence is used to construct a parent sequence X0, which serves as the reference sequence. The calculation formula is as follows:

[0101] X'0={X'0(1),X'0(2),…,X'0(K)},

[0102] Where n is the number of indicators and K is the length of the sequence;

[0103] Calculate the sum of the absolute values ​​of the differences between corresponding elements of each sequence and the parent sequence, and then calculate the independence coefficient of each sequence.

[0104]

[0105] The second weight W2 is obtained through the independent coefficients:

[0106]

[0107] In one embodiment of the present invention, step S4 specifically comprises:

[0108] The aforementioned set of indicators forms the identification framework:

[0109] Ω = {Ω1,Ω2,…,Ω} n};

[0110] Among them, Ω i For the i-th indicator;

[0111] The weights of each indicator, calculated using the first and second weight methods, are mapped to the basic confidence assignment mass function of the criterion under this method. This mapping satisfies:

[0112]

[0113] Where mass1(i) and mass2(i) are the basic criterion confidence of the index under the first weight and second weight calculation methods, respectively;

[0114] To determine whether the basic criterion confidence of index i is in the compatibility region under the two weighting calculation methods, let:

[0115]

[0116] Among them, D B Let D be the set of criteria whose basic criterion confidence falls within the compatibility region under the two weighting calculation methods. R This refers to the set of criteria whose basic criterion confidence is in the fuzzy domain under the two weighting calculation methods.

[0117] Calculate the combined weight W(i) of the first and second weights of index i:

[0118]

[0119]

[0120] Where A and B are the basic criteria in the identification framework, and C is the conflict coefficient.

[0121] In one embodiment of the present invention, step S5 specifically comprises:

[0122] The original construction matrix is ​​obtained based on the index values ​​of each OPGW optical cable equipment:

[0123]

[0124] Where, x mn This represents the nth index value of the mth OPGW optical cable device;

[0125] To construct the norm-normalized matrix, divide each column element by the norm of the current column vector, as shown in the following formula:

[0126]

[0127] The normalized matrix Z is obtained after normalization:

[0128]

[0129] Determine the optimal and worst performance, where the optimal performance Z + The worst-case performance Z is composed of the maximum value of each column element in the normalized matrix Z. - It consists of the minimum values ​​of each column elements in the normalized matrix Z, let

[0130] The formula for calculating the degree of closeness between the performance of the i-th OPGW optical cable device and its optimal and worst performance is as follows:

[0131]

[0132]

[0133] Among them, W j The fusion weights for the indicators;

[0134] Obtain the health index of the i-th OPGW optical cable equipment:

[0135]

[0136] In one embodiment of the present invention, step S5 further includes:

[0137] The health status of OPGW optical cable equipment is assessed using a health index, including:

[0138] When 0 < HI ≤ 1, the optical cable is evaluated as in a serious state;

[0139] When 1 < HI ≤ 2, the optical cable is evaluated as in an abnormal state;

[0140] When 2 < HI ≤ 3, the optical cable is evaluated as in a state of concern;

[0141] When 3 < HI ≤ 4, the optical cable is evaluated as in a normal state.

[0142] In a specific embodiment of the present invention, in the power optical transmission network of a certain area, 20 OPGW optical cables with complete data are selected to calculate their health indexes to verify the rationality and effectiveness of the optical cable health evaluation algorithm.

[0143] Based on the selected OPGW index system, the first weight and the second weight of each index are calculated respectively, and through the DS evidence theory synthesis rule, the fusion weight is obtained. The calculation results are shown in Table 1.

[0144] Table 1

[0145]

[0146]

[0147] In Table 1, for the optical cable type, manufacturer, cable tension, regular inspection rate and operation time, due to the large difference in the evaluation results of the two methods, these indexes are in the fuzzy domain and cannot accurately judge the health degree of the optical cable. The weights of other indexes in the compatible domain are as Figure 2 shown. In this embodiment, different index weight analysis methods are regarded as different "witnesses", and the obtained index weights are regarded as the evidence reliability of this index. All index weights constitute the recognition framework of index credibility. The higher the weight, the higher the basic reliability of this index, and the more trustworthy the discrimination ability for the health status of the optical cable.

[0148] When performing weight fusion, the indexes in the fuzzy domain cannot judge the health status of the optical cable and are excluded, such as the optical cable type, manufacturer, cable tension, regular inspection rate and operation time. For the indexes with relatively high weights under different methods in the compatible domain, the weight of this index remains relatively high after fusion, such as temperature, humidity, wind speed and the number of historical faults. For the indexes with relatively large differences in weights under different methods, their weights will be weakened to reduce the impact of one-sided analysis on the comprehensive weight, such as regular inspection evaluation and cable sag.

[0149] Calculate the health indexes of 20 OPGW optical cables, and judge each optical cable according to the health grades defined in the present invention, as shown in Table 2.

[0150] Table 2

[0151]

[0152] The status data and calculation results of some reliable indicators in the health assessment of OPGW optical cables were compared. Table 2 shows that the key indicator data of cable #16, with the highest health index, are excellent, and the calculation results match the description of a normal state. Cable #16 has significantly shorter durations of abnormal temperature, humidity, and wind speed compared to other cables with lower health indices. Cable #2, in a state of concern, has abnormal temperature and wind speed durations above the average; its working environment needs attention to see if it is beginning to affect its normal operation. Cable #6 has a high duration of abnormal wind speed and has exceeded the allowable tension by 69%, indicating an abnormal state. Cable #4, with the lowest health index, shows most indicators with significant abnormalities and should be repaired or replaced, matching the description of a severe state. Through comparative analysis, the calculation results of the algorithm in this invention are consistent with the actual status data, and the health index can correctly classify the health level of optical cables. This demonstrates that the algorithm for calculating the health index of OPGW optical cables is reasonable and effective, and can accurately assess their health status.

[0153] Based on the above analysis, the method of the present invention can accurately assess the health status of OPGW optical cables.

[0154] Second aspect

[0155] An OPGW optical cable health status assessment system includes a data acquisition unit, a data processing unit, a data storage unit, and an early warning unit;

[0156] The data acquisition unit collects the performance data of the OPGW optical cable equipment and stores it in the data storage unit;

[0157] The data processing unit processes the indicator data using the OPGW optical cable health status assessment method described in the first aspect, assesses the health status of the OPGW optical cable equipment, and stores the assessment results in the data storage unit.

[0158] The early warning unit provides early warnings about the health status of the OPGW optical cable equipment based on the assessment results.

[0159] Furthermore, the data acquisition unit periodically collects indicator data of the OPGW optical cable equipment. After each assessment of the health status of the OPGW optical cable equipment, the data processing unit compares the assessment results with the previous assessment results and displays the change in the two assessment results through the early warning unit.

[0160] Third aspect

[0161] A storage medium storing a computer program that, when executed, implements the OPGW optical cable health status assessment method described in the first aspect, processes OPGW optical cable equipment assessment index data, and obtains assessment results.

[0162] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structure made using the contents of the present invention specification and drawings, or directly or indirectly applied to other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for assessing the health status of OPGW optical cables, characterized in that, Including: S1: Collect OPGW optical cable equipment evaluation index data; S2: Calculate the first weight according to the numerical distribution of the index data; S3: Calculate the second weight according to the correlation between the index data; S4: Obtain the fusion weight according to the first weight and the second weight; S5: Determine the OPGW optical cable health status index value and evaluate the optical cable health status; Step S4 specifically is: Aggregate the said indexes into an identification framework: ； in, For the first i One indicator; The weights obtained by the first weight and the second weight calculation methods for each of the said indexes are mapped to the basic belief assignment mass function of the criterion under this method, and this mapping satisfies: ； in, mass 1( i )and mass 2( i ( ) represent the basic criterion confidence of the indicator under the first and second weight calculation methods, respectively; Judging the index under two weighting calculation methods i The basic criterion for whether the confidence level is within the compatibility region is: Let: ； in, D B This is the set of criteria whose basic criterion confidence levels fall within the compatibility region under the two weighting calculation methods. D R This refers to the set of criteria whose basic criterion confidence is in the fuzzy domain under the two weighting calculation methods. Calculation indicators i The combined weight of the first and second weights W ( i ): ； ； in, A , B To identify the basic criteria in the framework, C The conflict coefficient; Step S5 specifically is: Obtain the original construction matrix according to the index values of each OPGW optical cable equipment; ； in, For the first m The first OPGW optical cable equipment n Individual indicator values; Construct a norm normalization matrix, and divide each column element by the norm of the current column vector. The formula is as follows: ； Obtain the normalized matrix after normalization. : ； Determine the optimal and worst performance, where the optimal performance is... Z + The worst-case performance Z is composed of the maximum value of each column element in the normalized matrix Z. - It consists of the minimum values ​​of each column elements in the normalized matrix Z, let , ; Calculate the first i The formula for determining the degree to which the performance of an OPGW optical cable device approaches its optimal and worst performance is as follows: ； ； in, The fusion weights for the indicators; Get the first i Health index of OPGW optical cable equipment: 。 2. The OPGW optical cable health status assessment method according to claim 1, characterized in that, The said indexes include optical cable type, production manufacturer, core occupancy rate, optical cable sag, optical cable tension, temperature, humidity, wind speed, historical failure times, regular inspection rate, regular inspection evaluation, and commissioning time.

3. The OPGW optical cable health status assessment method according to claim 1, characterized in that, Step S2 specifically is: The first weight is calculated based on the numerical distribution of the indicator data. W 1. Order: ， ； in, G ( i ) is the first i The distribution of indicator values ​​for each indicator. n For the number of indicators, m The number of possible values ​​for the indicator. p j This represents the probability of the indicator value occurring.

4. The OPGW optical cable health status assessment method according to claim 3, characterized in that, Step S3 specifically is: Discretize and sort the data of each index in ascending order to form a sequence, and then perform normalization. The normalization formula is: ； in, As an indicator i The k One value, As an indicator i The maximum value, These are the normalized index values; Calculate the average value of the data corresponding to all sequences. The formula is as follows: ； The parent sequence is formed by averaging the corresponding data of all sequences. As a reference sequence, the calculation formula is as follows: ， in, n For the number of indicators, K The length of the sequence; Statistically calculate the sum of the absolute values of the differences between the elements of each sequence and the corresponding elements of the mother sequence, and calculate the independent coefficient of each sequence: ； The second weight is obtained through the independence coefficient. W 2: 。 5. The OPGW optical cable health status assessment method according to claim 4, characterized in that, Step S5 further includes: Evaluate the health status of the OPGW optical cable equipment through a health index, where: When 0 < HI ≤ 1, the optical cable is evaluated as a serious state; When 1 < HI ≤ 2, the optical cable is evaluated as an abnormal state; When 2 < HI ≤ 3, the optical cable is evaluated as a state of concern; When 3 < HI ≤ 4, the optical cable is evaluated as a normal state.

6. An OPGW optical cable health status assessment system, characterized in that, Including a data acquisition unit, a data processing unit, a data storage unit, and an early warning unit; The said data acquisition unit acquires the index data of the OPGW optical cable equipment and stores it in the said data storage unit; The said data processing unit processes the said index data through the OPGW optical cable health status evaluation method according to any one of claims 1 - 5, evaluates the health status of the OPGW optical cable equipment, and stores the evaluation result in the said data storage unit; The said early warning unit gives an early warning of the health status of the OPGW optical cable equipment according to the evaluation result.

7. The OPGW optical cable health status assessment system according to claim 6, characterized in that, The said data acquisition unit periodically acquires the index data of the OPGW optical cable equipment. After each evaluation of the health status of the OPGW optical cable equipment by the data processing unit, it compares the evaluation result with the previous evaluation result, and displays the change amount of the two evaluation results through the said early warning unit.

8. A storage medium, characterized in that, Among them, the stored computer program, when executed, implements the OPGW optical cable health status evaluation method according to any one of claims 1 - 5, processes the OPGW optical cable equipment evaluation index data, and obtains an evaluation result.

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