A method for evaluating the operating status of an in-service bridge monitoring system

Abstract

The present invention relates to the field of bridge technology, and in particular to a method for evaluating the operating status of an in-service bridge monitoring system, the method comprising the following steps: solving the indicator weight according to the mutual influence degree between each evaluation indicator; establishing the evaluation criteria for each evaluation indicator and the operating status of the in-service bridge monitoring system, and evaluating and obtaining the specific score of each evaluation indicator; establishing the membership function and non-membership function of the evaluation indicator for the operating status of the in-service bridge monitoring system, and then evaluating the operating status of the in-service bridge monitoring system according to the indicator weight and the specific score. The present invention uses a triangular intuition network analysis method to divide the relative weights of the evaluation indicators, and uses a fuzzy comprehensive evaluation method integrating triangular intuition fuzzy numbers to evaluate the operating status of the in-service bridge monitoring system. In the evaluation process, the inevitable deviation between subjective opinions and actual conditions is considered, and a complete evaluation system for the in-service bridge monitoring system is established.

Description

Technical Field

[0001] The invention relates to the technical field of bridges, and in particular to a method for evaluating the operating status of an in-service bridge monitoring system. Background Art

[0002] At present, the goals of real-time monitoring, synchronous analysis and data network sharing of bridge monitoring systems have been gradually achieved. As bridge monitoring systems have been in service in the field for a long time, sensor failures, unstable system operation, abnormal monitoring data and other phenomena often occur. The poor operation of the monitoring system will directly affect the accuracy of bridge structure health diagnosis. The reliable operation of the health monitoring system is crucial to obtaining real and effective monitoring data and evaluating the structural status.

[0003] At present, the research on bridge monitoring systems focuses on using monitoring system data to evaluate the state of bridge structures. The evaluation of the operating state of the monitoring system is divided into two categories, namely system reliability verification and sensor abnormal signal detection. The reliability verification of the monitoring system relies on the comparison and verification of the actual monitoring data and the results of finite element simulation. It mainly focuses on the effectiveness of the system in the early stage of construction and ignores the impact of the long-term service process on the operating state of the system; the online diagnosis of sensor faults relies on the classification and positioning of abnormal signals by neural networks, focusing on the operating state diagnosis and abnormal data detection of a single sensor. The evaluation angle is relatively single and lacks a comprehensive evaluation of the overall operating state of the system. The mathematical essence of the operating state evaluation of the bridge monitoring system is a multi-criteria comprehensive evaluation problem, in which some information is difficult to quantify, resulting in the deviation between subjective opinions and actual conditions in the decision-making process. At present, there is a lack of a complete operating state evaluation method for in-service bridge monitoring systems.

[0004] Therefore, how to effectively evaluate the operating status of a bridge monitoring system is an urgent problem that technicians in this field need to solve. Summary of the invention

[0005] In view of the defects in the prior art, the present invention provides a method for evaluating the operating status of an in-service bridge monitoring system.

[0006] In order to achieve the above-mentioned purpose, the present invention provides a method for evaluating the operating status of an in-service bridge monitoring system, the method comprising the following steps: solving the indicator weight according to the mutual influence degree between each evaluation indicator in the evaluation indicator system; establishing the evaluation criteria for each evaluation indicator and the operating status of the in-service bridge monitoring system, and evaluating and obtaining the specific score of each evaluation indicator; constructing the membership function and non-membership function of the evaluation indicator for the operating status of the in-service bridge monitoring system, and then evaluating the operating status of the in-service bridge monitoring system according to the indicator weight and the specific score. The present invention uses the triangular intuition network analysis method to divide the relative weights of the evaluation indicators, and uses the fuzzy comprehensive evaluation method integrating triangular intuition fuzzy numbers to evaluate the operating status of the in-service bridge monitoring system. In the evaluation process, the inevitable deviation between subjective opinions and actual conditions is taken into account, and a complete evaluation system for in-service bridge monitoring systems is established.

[0007] Optionally, the evaluation index system includes system effectiveness evaluation, system operation and maintenance evaluation, system early warning evaluation and human-computer interaction evaluation. The system effectiveness evaluation includes five evaluation indicators: average failure-free rate, sensor online rate, data accuracy, data integrity and data consistency. The system operation and maintenance evaluation includes three evaluation indicators: timeliness of fault handling, timeliness of alarm confirmation and timeliness of report upload. The system early warning evaluation includes three evaluation indicators: threshold setting, early warning accuracy and structural status guidance inspection. The human-computer interaction evaluation includes three evaluation indicators: interface layout, operation response time and over-limit reminder. The evaluation index system of the present invention covers multiple aspects such as system effectiveness, operation and maintenance, early warning and human-computer interaction, which is conducive to the comprehensive evaluation of the overall operation status of the in-service bridge monitoring system.

[0008] Optionally, solving the indicator weight according to the mutual influence degree between each evaluation indicator in the evaluation indicator system comprises the following steps:

[0009] Using the principle of network analysis, an analysis structure is constructed to evaluate the mutual influence of each of the evaluation indicators;

[0010] A 1-9 scale of fused triangular intuitionistic fuzzy numbers is established, where the maximum membership is 1, the minimum membership is 0, the fuzzy factor of membership is 1, and the fuzzy factor of non-membership is 1.5;

[0011] The 1-9 scale integrating triangular intuitionistic fuzzy numbers is used to replace the traditional 1-9 scale of the network analysis method, and the network relationship of the mutual influence between the evaluation indicators is analyzed, and then the indicator weight of each evaluation indicator is calculated.

[0012] The present invention uses a 1-9 scale that integrates triangular intuitionistic fuzzy numbers to replace the traditional 1-9 scale of the network analysis method, and then combines the network analysis method with the triangular intuitionistic fuzzy numbers to obtain the triangular intuitionistic network analysis method to divide the relative weights of various evaluation indicators, which are used as the indicator weights of various evaluation indicators, and then more carefully consider the mutual influence and hierarchical relationship between the evaluation indicators, so that the distribution of weights is more scientific and reasonable, and the accuracy and reliability of the evaluation of the operating status of the in-service bridge monitoring system are improved.

[0013] Optionally, the establishing of the evaluation criteria for each evaluation indicator and the operating status of the in-service bridge monitoring system, and evaluating and obtaining the specific score of each evaluation indicator comprises the following steps:

[0014] The three evaluation indicators of the average failure-free rate, the sensor online rate and the data integrity are defined as quantitative evaluation indicators, and the remaining 11 evaluation indicators are defined as qualitative evaluation indicators;

[0015] Each of the evaluation indicators is divided into four indicator evaluation levels: I, II, III and IV, which correspond to the four indicator scoring intervals of [90, 100], [75, 90), [60, 75) and [20, 60) respectively;

[0016] The operating status of the in-service bridge monitoring system is divided into four status evaluation levels: I, II, III and IV, which correspond to four status scoring intervals of [90, 100], [75, 90), [60, 75) and [20, 60) respectively;

[0017] Rewrite each state scoring interval of the in-service bridge monitoring system into a triangular intuitionistic fuzzy number, where the maximum membership is 1, the minimum membership is 0, the fuzzy factor of membership is 5, and the fuzzy factor of non-membership is 10;

[0018] Each evaluation indicator is evaluated to obtain a specific score for each evaluation indicator.

[0019] The present invention provides a clear standard and basis for evaluation by dividing evaluation levels and scoring intervals, and rewriting the corresponding scores of each evaluation level into triangular intuitionistic fuzzy numbers solves the inevitable deviation between subjective opinions and actual conditions, thereby increasing the flexibility and accuracy of the evaluation.

[0020] Optionally, constructing a membership function and a non-membership function of the evaluation index for the operating status of the in-service bridge monitoring system, and then evaluating the operating status of the in-service bridge monitoring system according to the index weight and the specific score comprises the following steps:

[0021] Establishing the membership function and non-membership function of the evaluation index for the operating status of each of the in-service bridge monitoring systems;

[0022] According to the specific scores, the membership function and the non-membership function are used to calculate the membership and non-membership of each evaluation index to the operating status of the in-service bridge monitoring system;

[0023] The membership degree and the non-membership degree are used to form a judgment matrix, and the membership degree and non-membership degree of the operating status of the in-service bridge monitoring system for each status evaluation level are calculated in combination with the indicator weight and the specific score, and then the final status score of the operating status of the in-service bridge monitoring system is calculated to evaluate the operating status of the in-service bridge monitoring system.

[0024] The present invention adopts a fuzzy comprehensive evaluation method integrating triangular intuitionistic fuzzy numbers to deal with the uncertainty and ambiguity in the evaluation process. Triangular intuitionistic fuzzy numbers not only include the fuzziness of fuzzy numbers, but also include three parameters: membership, non-membership and fuzzy factor. This enables the evaluation process to more comprehensively consider the deviation between subjective opinions and actual conditions, thereby obtaining more accurate and reliable evaluation results.

[0025] Optionally, the membership function μ of the evaluation index for the state evaluation level I is Ⅰ (x) satisfies the following relationship:

[0026]

[0027] The membership function μ of the evaluation index for the state evaluation level II is Ⅱ (x) satisfies the following relationship:

[0028]

[0029] The membership function μ of the evaluation index for the state evaluation level III Ⅲ (x) satisfies the following relationship:

[0030]

[0031] The membership function μ of the evaluation index for the state evaluation level IV is Ⅳ (x) satisfies the following relationship:

[0032]

[0033] Wherein, x is the specific score of the evaluation indicator.

[0034] The present invention can provide a basis for constructing a judgment matrix by establishing a membership function, thereby realizing a comprehensive evaluation of the operating status of an in-service bridge monitoring system.

[0035] Optionally, the evaluation index is a non-membership function v for the state evaluation level I.Ⅰ (x) satisfies the following relationship:

[0036]

[0037] The evaluation index is for the non-membership function v of the state evaluation level II Ⅱ (x) satisfies the following relationship:

[0038]

[0039] The evaluation index is for the non-membership function v of the state evaluation level III Ⅲ (x) satisfies the following relationship:

[0040]

[0041] The evaluation index is for the non-membership function v of the state evaluation level IV Ⅳ (x) satisfies the following relationship:

[0042]

[0043] Wherein, x is the specific score of the evaluation indicator.

[0044] The present invention can provide a basis for constructing a judgment matrix by establishing a non-membership function, thereby realizing a comprehensive evaluation of the operating status of an in-service bridge monitoring system.

[0045] Optionally, the judgment matrix satisfies the following relationship:

[0046]

[0047] Among them, r ij is the membership and non-membership of the specific score of the i-th evaluation indicator to the state evaluation level j, μ ij is the membership degree of the specific score of the i-th evaluation indicator to the status evaluation level j, v ij is the non-membership degree of the specific score of the i-th evaluation indicator to the state evaluation level j, i=1,2,3,...,C, j=Ⅰ,Ⅱ,...,B=Ⅰ,Ⅱ,Ⅲ,Ⅳ, C is the number of the evaluation indicators, and B is the maximum level of the state evaluation level.

[0048] The judgment matrix can provide a data basis for the subsequent calculation of the membership and non-membership of the operating status of the in-service bridge monitoring system for each status evaluation level, and then calculate an accurate and reliable final status score based on the deviation between subjective opinions and actual conditions.

[0049] Optionally, the membership and non-membership of the operating status of the in-service bridge monitoring system for each status evaluation level satisfy the following relationship:

[0050]

[0051] in, is the membership degree of the operating status of the in-service bridge monitoring system to the status evaluation level j, is the non-membership degree of the operating status of the in-service bridge monitoring system to the status evaluation level j, W i is the indicator weight of the i-th evaluation indicator, r ij is the membership and non-membership of the specific score of the i-th evaluation indicator to the state evaluation level j, i=1,2,3,...,C, j=Ⅰ,Ⅱ,...,B=Ⅰ,Ⅱ,Ⅲ,Ⅳ, C is the number of the evaluation indicators, B is the maximum level of the state evaluation level, and X is a weight vector composed of the indicator weights of each of the evaluation indicators.

[0052] The membership and non-membership of the operating status of the in-service bridge monitoring system for each status evaluation level are calculated to resolve the deviation between subjective opinions and actual conditions, and then an accurate and reliable final status score is calculated.

[0053] Optionally, the final state score satisfies the following relationship:

[0054]

[0055] Wherein, Z is the final state score, is the membership degree of the operating status of the in-service bridge monitoring system to the status evaluation level j, B is the maximum level of the status evaluation level, V j is the lower limit of the state scoring interval corresponding to the operating state of the in-service bridge monitoring system at the state evaluation level j, a and á are the lower limits of the triangular intuitionistic fuzzy numbers of the state scoring interval, b and is the most likely value of the triangular intuitionistic fuzzy number module of the state scoring interval, c and is the upper limit of the triangular intuitionistic fuzzy number modulus of the state scoring interval.

[0056] The present invention utilizes the triangular intuition network analysis method to divide the relative weights of the evaluation indicators, and utilizes the fuzzy comprehensive evaluation method integrating triangular intuition fuzzy numbers. In the evaluation process, the inevitable deviation between subjective opinions and actual conditions is considered, and an accurate and reliable final status score is obtained to achieve an accurate evaluation of the operating status of the in-service bridge monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0058] Figure 1 A schematic flow chart of a method for evaluating the operating status of an in-service bridge monitoring system according to an embodiment of the present invention;

[0059] Figure 2 The schematic diagram is a framework of an operating status evaluation system for an in-service bridge monitoring system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0061] Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. In addition, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any suitable combination and / or subcombination. In addition, it should be understood by those of ordinary skill in the art that the figures provided herein are for illustrative purposes and that the figures are not necessarily drawn to scale.

[0062] It should be noted in advance that, in an optional embodiment, except for independent explanations, the same symbols or letters appearing in all formulas have the same meanings and values.

[0063] In an alternative embodiment, see Figure 1 The present invention provides a method for evaluating the operating status of an in-service bridge monitoring system, the method comprising the following steps:

[0064] S1. Determine the indicator weight according to the mutual influence degree between each evaluation indicator in the evaluation indicator system.

[0065] Specifically, in this embodiment, the evaluation index system includes system effectiveness evaluation, system operation and maintenance evaluation, system early warning evaluation and human-computer interaction evaluation. The system effectiveness evaluation includes five evaluation indicators: average failure-free rate, sensor online rate, data accuracy, data integrity and data consistency. The system operation and maintenance evaluation includes three evaluation indicators: timeliness of fault handling, timeliness of alarm confirmation and timeliness of report upload. The system early warning evaluation includes three evaluation indicators: threshold setting, early warning accuracy and structural status guidance inspection. The human-computer interaction evaluation includes three evaluation indicators: interface layout, operation response time and over-limit reminder. Therefore, the evaluation index system includes 14 evaluation indicators, covering multiple aspects such as system effectiveness, operation and maintenance, early warning and human-computer interaction, which is conducive to the comprehensive evaluation of the overall operation status of the in-service bridge monitoring system.

[0066] S1 specifically includes the following steps:

[0067] S11. Using the principle of network analysis method, an analysis structure for evaluating the mutual influence of each evaluation index is constructed.

[0068] S12. Establish a 1-9 scale of fused triangular intuitionistic fuzzy numbers, where the maximum membership is 1, the minimum membership is 0, the fuzzy factor of membership is 1, and the fuzzy factor of non-membership is 1.5.

[0069] Specifically, in this embodiment, when the maximum membership is 1 and the minimum membership is 0, the form of the triangular intuitionistic fuzzy number is Where a and á are the lower limits of fuzzy numbers, b and is the most likely value of the fuzzy number, c and is the upper limit of the fuzzy number. When the fuzzy factor of membership is 1 and the fuzzy factor of non-membership is 1.5, a 1 =b 1 -1, v 1 =b 1 +1,

[0070] Furthermore, the 1-9 scale of the fused triangular intuitionistic fuzzy number is shown in Tables 1 and 2.

[0071] Table 1 1-9 scale of fused triangular intuitionistic fuzzy numbers

[0072]

[0073]

[0074] Table 2 1-9 scale of fused triangular intuitionistic fuzzy numbers

[0075] Importance Scale Triangular intuitionistic fuzzy numbers Equally unimportant 1 [(1 / 2,1,1),(1 / 2.5,1,1)] 2 [(1 / 3,1 / 2,1),(1 / 3.5,1 / 2,1)] Slightly unimportant 3 [(1 / 4,1 / 3,1 / 2),(1 / 4.5,1 / 3,1 / 1.5)] 4 [(1 / 5,1 / 4,1 / 3),(1 / 5.5,1 / 4,1 / 2.5)] Obviously not important 5 [(1 / 6,1 / 5,1 / 4),(1 / 6.5,1 / 5,1 / 3.5)] 6 [(1 / 7,1 / 6,1 / 5),(1 / 7.5,1 / 6,1 / 4.5)] Strongly unimportant 7 [(1 / 8,1 / 7,1 / 6),(1 / 8.5,1 / 7,1 / 5.5)] 8 [(1 / 9,1 / 8,1 / 7),(1 / 9,1 / 8,1 / 6.5)] Extremely unimportant 9 [(1 / 9,1 / 9,1 / 8),(1 / 9,1 / 9,1 / 7.5)]

[0076] S13, using a 1-9 scale that integrates triangular intuitionistic fuzzy numbers instead of the traditional 1-9 scale of the network analysis method, analyzing the network relationship of the mutual influence between the various evaluation indicators, and then calculating the indicator weight of each evaluation indicator.

[0077] Specifically, in this embodiment, the indicator weights of each evaluation indicator are: average failure-free rate, 0.076; sensor online rate, 0.079; data accuracy, 0.116; data integrity, 0.118; data consistency, 0.076; fault handling timeliness, 0.084; alarm confirmation timeliness, 0.076; threshold setting, 0.087; warning accuracy, 0.058; structural status inspection guidance, 0.040; interface layout, 0.039; operation response time, 0.017; over-limit reminder, 0.056.

[0078] The 1-9 scale of the integrated triangular intuitionistic fuzzy number is used to replace the traditional 1-9 scale of the network analysis method, and then the triangular intuitionistic fuzzy number in the network analysis method is combined to obtain the triangular intuitionistic network analysis method to divide the relative weights of each evaluation index, which is used as the index weight of each evaluation index, and then the mutual influence and hierarchical relationship between the evaluation indicators are considered more carefully, so that the weight distribution is more scientific and reasonable, and the accuracy and reliability of the evaluation of the operating status of the in-service bridge monitoring system are improved. This step can refer to the existing technology, and will not be described in detail here.

[0079] S2. Establishing evaluation criteria for each of the evaluation indicators and the operating status of the in-service bridge monitoring system, and evaluating and obtaining specific scores for each of the evaluation indicators.

[0080] This embodiment provides a clear standard and basis for evaluation by dividing the evaluation levels and scoring intervals, and rewriting the corresponding scores of each evaluation level into triangular intuitive fuzzy numbers solves the inevitable deviation between subjective opinions and actual conditions, thereby increasing the flexibility and accuracy of the evaluation.

[0081] S2 specifically includes the following steps:

[0082] S21. The three evaluation indicators, namely, the average failure-free rate, the sensor online rate and the data integrity, are defined as quantitative evaluation indicators, and the remaining 11 evaluation indicators are defined as qualitative evaluation indicators.

[0083] Specifically, in this embodiment, the quantitative evaluation indicators respectively satisfy the following relationship:

[0084]

[0085] Among them, P 1 is the average failure-free rate, M is the total number of units in the in-service bridge monitoring system, t mis the normal working time of the mth unit in the in-service bridge monitoring system, T 1 is the total working time of the mth unit in the in-service bridge monitoring system, P 2 is the sensor online rate, N is the total number of sensors in the in-service bridge monitoring system, t n is the offline time of the nth sensor in the in-service bridge monitoring system within the query time, T 2 is the query time, P 3 For data integrity, L nd is the total amount of missing values ​​or non-numeric data at the monitoring point where the nth sensor is located, L n is the total amount of data at the monitoring point where the nth sensor is located.

[0086] Furthermore, when calculating the online rate of the sensor, if the in-service bridge monitoring system does not receive characteristic data sent by a certain sensor for 6 consecutive hours, the sensor is judged to be offline, and this moment is recorded as the offline start time of the in-service bridge monitoring system.

[0087] S22. Divide each of the evaluation indicators into four indicator evaluation levels, namely, I, II, III and IV, which correspond to four indicator scoring intervals of [90, 100], [75, 90), [60, 75) and [20, 60) respectively.

[0088] S23. Divide the operating status of the in-service bridge monitoring system into four status evaluation levels: I, II, III and IV, which correspond to four status scoring intervals of [90, 100], [75, 90), [60, 75) and [20, 60) respectively.

[0089] Specifically, in this embodiment, the operating status of the in-service bridge monitoring system corresponding to the condition evaluation level I is "excellent", and the corresponding status score interval is [90, 100] points; the operating status of the in-service bridge monitoring system corresponding to the condition evaluation level II is "good", and the corresponding status score interval is [75, 90) points; the operating status of the in-service bridge monitoring system corresponding to the condition evaluation level III is "medium", and the corresponding status score interval is [60, 75) points; the operating status of the in-service bridge monitoring system corresponding to the condition evaluation level IV is "poor", and the corresponding status score interval is [20, 60) points.

[0090] S24. Rewrite each status score interval of the in-service bridge monitoring system into a triangular intuitionistic fuzzy number, where the maximum membership is 1, the minimum membership is 0, the fuzzy factor of the membership is 5, and the fuzzy factor of the non-membership is 10.

[0091] Specifically, in this embodiment, the triangular intuitionistic fuzzy numbers of each state scoring interval are shown in Table 3.

[0092] Table 3 Triangular intuitionistic fuzzy numbers of each state scoring interval

[0093] Status rating Status score range Triangular intuitionistic fuzzy numbers Ⅰ [90,100] [(85,90,95),(80,90,100)] Ⅱ [75,90) [(70,75,80),(65,75,90)] Ⅲ [60,75) [(55,60,65),(50,60,70)] Ⅳ [20,60) [(15,20,25),(10,20,30)]

[0094] S25. Evaluate each of the evaluation indicators to obtain a specific score for each of the evaluation indicators.

[0095] Specifically, in this embodiment, the evaluation criteria for each evaluation indicator are shown in Table 4. Each evaluation indicator is evaluated according to the evaluation criteria in Table 4 to obtain a specific score for each evaluation indicator.

[0096] Table 4 Evaluation criteria for each evaluation indicator

[0097]

[0098]

[0099]

[0100] Furthermore, for quantitative evaluation indicators, the specific score can be obtained by interpolation. For example, the average failure-free rate is calculated to be 96%, which satisfies 95% ≤ P 1 <99%, the corresponding indicator evaluation level is II, and the corresponding indicator scoring range is [75,90), then the specific score of the average failure-free rate is For qualitative evaluation indicators, the numerical values ​​can be defined according to the opinions of decision makers, and the deviation between the actual situation and personal opinions is corrected for the final result in the form of non-membership.

[0101] S3. Constructing a membership function and a non-membership function of the evaluation index for the operating status of the in-service bridge monitoring system, and then evaluating the operating status of the in-service bridge monitoring system according to the index weight and the specific score.

[0102] Among them, this embodiment adopts the fuzzy comprehensive evaluation method integrating triangular intuitionistic fuzzy numbers to deal with the uncertainty and fuzziness in the evaluation process. Triangular intuitionistic fuzzy numbers not only include the fuzziness of fuzzy numbers, but also include three parameters: membership, non-membership and fuzzy factor. This enables the evaluation process to more comprehensively consider the deviation between subjective opinions and actual conditions, thereby obtaining more accurate and reliable evaluation results. S3 specifically includes the following steps:

[0103] S31, establishing the membership function and non-membership function of the evaluation index for the operating status of each of the in-service bridge monitoring systems.

[0104] Specifically, in this embodiment, the membership function μ of the evaluation index for the state evaluation level I is Ⅰ(x) and non-membership function v Ⅰ (x) respectively satisfy the following relations:

[0105]

[0106] The membership function μ of the evaluation index for the state evaluation level II Ⅱ (x) and non-membership function v Ⅱ (x) respectively satisfy the following relations:

[0107]

[0108] The membership function μ of the evaluation index for the state evaluation level III Ⅲ (x) and non-membership function v Ⅲ (x) respectively satisfy the following relations:

[0109]

[0110] The membership function μ of the evaluation index for the state evaluation level IV Ⅳ (x) and non-membership function v Ⅳ (x) respectively satisfy the following relations:

[0111]

[0112] Among them, x is the specific score of the evaluation indicator.

[0113] S32. According to the specific scores, the membership function and the non-membership function are used to calculate the membership and non-membership of each evaluation index to the operating status of the in-service bridge monitoring system.

[0114] Specifically, in this embodiment, the specific scores of each evaluation indicator are brought into the corresponding membership function and non-membership function in step S31 to calculate the membership and non-membership of each evaluation indicator to the operating status of different in-service bridge monitoring systems, thereby providing a basis for the subsequent construction of a judgment matrix, and further realizing a comprehensive evaluation of the operating status of the in-service bridge monitoring system.

[0115] S33. Use the membership degree and the non-membership degree to form a judgment matrix, and combine the indicator weight and the specific score to calculate the membership degree and non-membership degree of the operating status of the in-service bridge monitoring system for each status evaluation level, and then calculate the final status score of the operating status of the in-service bridge monitoring system to evaluate the operating status of the in-service bridge monitoring system.

[0116] Specifically, in this embodiment, the judgment matrix satisfies the following relationship:

[0117]

[0118] Among them, r ij is the membership and non-membership of the specific score of the i-th evaluation indicator to the state evaluation level j, μ ij is the membership degree of the specific score of the i-th evaluation indicator to the status evaluation level j, v ij is the non-membership degree of the specific score of the i-th evaluation indicator to the state evaluation level j, i=1,2,3,...,C, j=Ⅰ,Ⅱ,...,B=Ⅰ,Ⅱ,Ⅲ,Ⅳ, C is the number of the evaluation indicators, and B is the maximum level of the state evaluation level.

[0119] Furthermore, the membership and non-membership of the operating status of the in-service bridge monitoring system for each status evaluation level satisfy the following relationship:

[0120]

[0121] in, is the membership degree of the operating status of the in-service bridge monitoring system to the status evaluation level j, is the non-membership degree of the operating status of the in-service bridge monitoring system to the status evaluation level j, W i is the indicator weight of the ith evaluation indicator, C is the number of the evaluation indicators, B is the maximum level of the state evaluation level, X is the weight vector composed of the indicator weights of each evaluation indicator, X=(W 1 ,W 2 ,W 3 ,...,W C ).

[0122] Furthermore, the final status score satisfies the following relationship:

[0123]

[0124] Where Z is the final state score, V j is the lower limit of the state scoring interval corresponding to the operating state of the in-service bridge monitoring system at the state evaluation level j, a and á are the lower limits of the triangular intuitionistic fuzzy numbers of the state scoring interval, b and is the most likely value of the triangular intuitionistic fuzzy number model of the state score interval, c and is the upper limit of the triangular intuitionistic fuzzy modulus of the state scoring interval. According to the description of step S12 and step S24, when the maximum membership is 1, the minimum membership is 0, the fuzzy factor of membership is 5, and the fuzzy factor of non-membership is 10, a=b-5, c=b+5,

[0125] Finally, by judging in which state score interval the final state score Z falls in step S23, it is possible to determine at which state evaluation level the operating state of the in-service bridge monitoring system is located, thereby realizing the evaluation of the operating state of the in-service bridge monitoring system.

[0126] The present invention utilizes the triangular intuition network analysis method to divide the relative weights of the evaluation indicators, and utilizes the fuzzy comprehensive evaluation method integrating triangular intuition fuzzy numbers. In the evaluation process, the inevitable deviation between subjective opinions and actual conditions is considered, and an accurate and reliable final status score is obtained to achieve an accurate evaluation of the operating status of the in-service bridge monitoring system.

[0127] It should be noted that, in some cases, the actions described in the specification can be performed in a different order and still achieve the desired results. In this embodiment, the order of steps given is only to make the embodiment appear clearer and easier to explain, rather than to limit it.

[0128] In an alternative embodiment, see Figure 2 The present invention also provides an operating status evaluation system for an in-service bridge monitoring system, the system uses an operating status evaluation method for an in-service bridge monitoring system provided by the present invention, the system includes an input device A1, an output device A4 and a storage A3, the input device A1, the output device A4, the processor A2 and the storage A3 are interconnected. The storage A3 includes a computer-readable storage medium, the computer-readable storage medium stores a computer program, the computer program includes program instructions, and when the program instructions are executed by the processor A2, the processor A2 executes the contents described in steps S1 to S3.

[0129] Specifically, in this embodiment, the input device A1 and the output device A4 both include an electronic display screen, and the relevant personnel can modify the evaluation index system, the evaluation index and the evaluation criteria of the operating status of the in-service bridge monitoring system through the input device A1, and the output device A4 can output the final status score and the status evaluation level to which the final status score belongs. The system provided by the present invention can stably execute steps S1 to S3, and can improve the practical application ability of the present invention.

[0130] In summary, the present invention is based on an evaluation index system covering multiple aspects such as system effectiveness, operation and maintenance, early warning, and human-computer interaction. The relative weights of the evaluation indicators are divided by the triangular intuition network analysis method, and the fuzzy comprehensive evaluation method integrating triangular intuition fuzzy numbers is used to evaluate the operating status of the in-service bridge monitoring system. In the process of evaluating the operating status of the in-service bridge monitoring system, the inevitable deviation between subjective opinions and actual conditions is taken into account, and a complete evaluation system for the operating status of the in-service bridge monitoring system is established, thereby realizing a comprehensive evaluation of the overall operating status of the in-service bridge monitoring system.

[0131] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A method for evaluating the operating status of an in-service bridge monitoring system, characterized in that: The steps include: Using the principle of network analysis method, we construct an analytical structure of the mutual influence of various evaluation indicators in the evaluation indicator system; A 1-9 scale of fused triangular intuitionistic fuzzy numbers is established, where the maximum membership is 1, the minimum membership is 0, the fuzzy factor of membership is 1, and the fuzzy factor of non-membership is 1.5; When the maximum membership is 1 and the minimum membership is 0, the form of triangular intuitionistic fuzzy number is ,in and is the lower limit of the fuzzy number, and is the most likely value of the fuzzy number, and is the upper limit of the fuzzy number; Using the 1-9 scale of the integrated triangular intuitionistic fuzzy number instead of the traditional 1-9 scale of the network analysis method, analyzing the network relationship between the various evaluation indicators that influence each other, and then calculating the indicator weight of each evaluation indicator; Establishing evaluation criteria for each of the evaluation indicators and the operating status of the in-service bridge monitoring system, and evaluating and obtaining specific scores for each of the evaluation indicators; Constructing a membership function and a non-membership function of the evaluation index for the operating status of the in-service bridge monitoring system, and then evaluating the operating status of the in-service bridge monitoring system according to the index weight and the specific score; The step of constructing the membership function and the non-membership function of the evaluation index for the operating status of the in-service bridge monitoring system, and then evaluating the operating status of the in-service bridge monitoring system according to the index weight and the specific score comprises the following steps: Establishing the membership function and non-membership function of the evaluation index for the operating status of each of the in-service bridge monitoring systems; According to the specific scores, the membership function and the non-membership function are used to calculate the membership and non-membership of each evaluation index to the operating status of the in-service bridge monitoring system; The membership degree and the non-membership degree are used to form a judgment matrix, and the membership degree and the non-membership degree of the operating state of the in-service bridge monitoring system for each state evaluation level are calculated in combination with the indicator weight and the specific score, and then the final state score of the operating state of the in-service bridge monitoring system is calculated to evaluate the operating state of the in-service bridge monitoring system; The judgment matrix satisfies the following relationship: in, is the membership and non-membership of the specific score of the i-th evaluation indicator to the state evaluation level j, is the membership degree of the specific score of the i-th evaluation indicator to the status evaluation level j, is the non-membership degree of the specific score of the i-th evaluation indicator to the state evaluation level j, , , C is the number of the evaluation indicators, B is the maximum level of the status evaluation level, B=Ⅳ; The membership and non-membership of the operating status of the in-service bridge monitoring system for each status evaluation level satisfy the following relationship: in, , is the membership degree of the operating status of the in-service bridge monitoring system to the status evaluation level j, is the non-membership degree of the operating status of the in-service bridge monitoring system to the status evaluation level j, is the indicator weight of the i-th evaluation indicator, is the membership and non-membership of the specific score of the i-th evaluation indicator to the state evaluation level j, , , C is the number of the evaluation indicators, B is the maximum level of the state evaluation level, B=Ⅳ, X is the weight vector composed of the indicator weights of each of the evaluation indicators; The final status score satisfies the following relationship: Wherein, Z is the final state score, is the membership degree of the operating status of the in-service bridge monitoring system to the status evaluation level j, B is the maximum level of the status evaluation level, is the lower limit of the status score interval corresponding to the operating status of the in-service bridge monitoring system at the status evaluation level j, and is the lower limit of the triangular intuitionistic fuzzy number of the state scoring interval, and is the most likely value of the triangular intuitionistic fuzzy number model of the state scoring interval, and is the upper limit of the triangular intuitionistic fuzzy number modulus of the state scoring interval.

2. The method for evaluating the operating status of an in-service bridge monitoring system according to claim 1 is characterized in that: The evaluation index system includes system effectiveness evaluation, system operation and maintenance evaluation, system early warning evaluation and human-computer interaction evaluation. The system effectiveness evaluation includes five evaluation indicators: average failure-free rate, sensor online rate, data accuracy, data integrity and data consistency. The system operation and maintenance evaluation includes three evaluation indicators: timeliness of fault handling, timeliness of alarm confirmation and timeliness of report upload. The system early warning evaluation includes three evaluation indicators: threshold setting, early warning accuracy and structural status guidance inspection. The human-computer interaction evaluation includes three evaluation indicators: interface layout, operation response time and over-limit reminder.

3. The method for evaluating the operating status of an in-service bridge monitoring system according to claim 2 is characterized in that: The steps of establishing the evaluation criteria for each evaluation indicator and the operating status of the in-service bridge monitoring system, and evaluating and obtaining the specific scores of each evaluation indicator include the following steps: The three evaluation indicators of the average failure-free rate, the sensor online rate and the data integrity are defined as quantitative evaluation indicators, and the remaining 11 evaluation indicators are defined as qualitative evaluation indicators; Each of the evaluation indicators is divided into four indicator evaluation levels: I, II, III and IV, which correspond to the four indicator scoring intervals of [90, 100], [75, 90), [60, 75) and [20, 60) respectively; The operating status of the in-service bridge monitoring system is divided into four status evaluation levels: I, II, III and IV, which correspond to four status scoring intervals of [90, 100], [75, 90), [60, 75) and [20, 60) respectively; Rewrite each state scoring interval of the in-service bridge monitoring system into a triangular intuitionistic fuzzy number, where the maximum membership is 1, the minimum membership is 0, the fuzzy factor of membership is 5, and the fuzzy factor of non-membership is 10; Each evaluation indicator is evaluated to obtain a specific score for each evaluation indicator.

4. The method for evaluating the operating status of an in-service bridge monitoring system according to claim 1, characterized in that: The membership function of the evaluation index for the status evaluation level I is Satisfies the following relationship: The membership function of the evaluation index for the status evaluation level II is Satisfies the following relationship: The membership function of the evaluation index for the status evaluation level III Satisfies the following relationship: The membership function of the evaluation index for the state evaluation level IV is Satisfies the following relationship: in, is the specific score of the evaluation indicator.

5. The method for evaluating the operating status of an in-service bridge monitoring system according to claim 1, characterized in that: The evaluation index is a non-membership function for the state evaluation level I Satisfies the following relationship: The evaluation index is a non-membership function for the state evaluation level II. Satisfies the following relationship: The evaluation index has a non-membership function for the status evaluation level III Satisfies the following relationship: The evaluation index is a non-membership function for the state evaluation level IV Satisfies the following relationship: in, is the specific score of the evaluation indicator.

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