Evaluation method and system for leakage points of pipe network

Abstract

The invention discloses a pipe network leakage point evaluation method and system, and the method comprises the steps: constructing an evaluation decision matrix, carrying out the normalization processing of the evaluation decision matrix, and obtaining the initial weight of each evaluation index; calculating a dynamic adjustment factor based on real-time data and historical data of the pipe network, updating the weight of the evaluation index, performing sensitivity verification, and applying a weight value passing the sensitivity verification as a final weight of the evaluation index; performing weighted normalization processing on the final weight pair by using the initial weight to obtain an index value of the evaluation index; an ideal solution of the pipe network leakage point is constructed based on the index value, the distance between the pipe network leakage point and the ideal solution is calculated, and the relative closeness of the pipe network leakage point is obtained according to the calculation result; and obtaining the relative closeness of each pipe network leakage point, and outputting a priority ranking result based on the relative closeness. According to the method, the weight of the evaluation index can be adaptively adjusted according to the real-time working condition, and the accuracy of judging the priority of the leakage point of the pipe network is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of pipe network, in particular to a pipe network leakage point evaluation method and system. BACKGROUND

[0002] Urban water supply is the lifeline of the city, which is directly related to the stability of society and the development of economy. At present, water supply pipeline leakage is the core problem in urban water management, and water supply pipeline leakage is mainly caused by problems in planning and design, pipeline material and construction quality. If not properly handled, it will bring a series of direct and indirect economic losses and negative effects.

[0003] The leakage risk evaluation of water supply pipeline is the premise of completing leakage control. The traditional pipeline leakage detection method cannot respond to the real-time working condition change of the pipeline, and the misjudgment rate of the priority of the leakage point is high, which leads to poor timeliness in dealing with high-risk leakage points and easy occurrence of secondary disasters. SUMMARY

[0004] In order to solve the problems in the prior art, the technical scheme adopted by the present application is as follows: The present application provides a pipe network leakage point evaluation method, which comprises the following steps: Obtain the historical working condition data of the pipe network, construct an evaluation decision matrix about the pipe network leakage point, the evaluation decision matrix comprising the original value of the pipe network leakage point on each evaluation index, normalize the evaluation decision matrix, and obtain the initial weight of each evaluation index of the pipe network leakage point; Obtain the real-time working condition data of the pipe network, calculate a dynamic adjustment factor based on the real-time working condition data and the historical working condition data, dynamically update the initial weight of the evaluation index through the dynamic adjustment factor, obtain the updated weight of the evaluation index, and verify the sensitivity of the updated weight of the evaluation index. The weight value passing the sensitivity verification is applied as the final weight of the evaluation index; Weight and normalize the final weight of the evaluation index using the initial weight of the evaluation index, and obtain the index value of the evaluation index; Construct an ideal solution of the pipe network leakage point based on the index value, calculate the distance between the pipe network leakage point and the ideal solution, and obtain the relative closeness of the pipe network leakage point according to the calculation result; Obtain the relative closeness of each pipe network leakage point, and output the priority ranking result of the pipe network leakage point based on the size of the relative closeness.

[0005] In summary, the application provides a pipe network leakage point evaluation method, which calculates a dynamic adjustment factor of an evaluation index through pipe network operation data, adjusts the weight of each evaluation index, and further adjusts the influence of each evaluation index on the priority of quantifying the pipe network leakage point, so as to timely respond to the real-time working condition change of the pipe network, improve the accuracy of the priority judgment of the pipe network leakage point, and realize intelligent priority sorting of the pipe network leakage point by constructing an ideal solution of the pipe network leakage point and obtaining the relative closeness of the pipe network leakage point based on the distance between the pipe network leakage point and the ideal solution, thereby improving the response sensitivity to high-risk leakage points, enabling maintenance personnel to prioritize high-risk leakage points for processing according to the priority sorting, reducing resource waste, and reducing the risk of secondary disasters.

[0006] Further, the ideal solution includes a positive ideal solution and a negative ideal solution, the positive ideal solution is a vector composed of the maximum values of the index values of the evaluation indexes, and the negative ideal solution is a vector composed of the minimum values of the index values of the evaluation indexes. The distance between the pipe network leakage point and the positive ideal solution and the distance between the pipe network leakage point and the negative ideal solution are calculated respectively, and the relative closeness is calculated according to the distance between the pipe network leakage point and the positive ideal solution and the distance between the pipe network leakage point and the negative ideal solution.

[0007] Further, the distance between the pipe network leakage point and the negative ideal solution is calculated by the following formula: ; In the formula, wherein d i represents the distance between the i th pipe network leakage point and the negative ideal solution, n represents the number of evaluation indexes, represents the index value of the j th evaluation index of the i th pipe network leakage point, represents the minimum value of the j th evaluation index.

[0008] Further, the evaluation method further comprises: A penalty term is introduced when calculating the distance between the pipe network leakage point and the positive ideal solution, the penalty term is used to weight the influence of the abnormal index on the priority of the pipe network leakage point, and the abnormal index at least includes pressure drop or leakage alarm.

[0009] Further, the distance between the pipe network leakage point and the positive ideal solution is calculated by the following formula: ; In the formula, wherein d i represents the distance between the i th pipe network leakage point and the positive ideal solution, n represents the number of evaluation indexes, represents the index value of the j th evaluation index of the i th pipe network leakage point, max j represents the maximum value of the jth evaluation index, represents a penalty term.

[0010] Further, the sensitivity verification on the updated weight of the evaluation index comprises: calculating the distance between the pipe network leakage point and the ideal solution based on the updated weight of the evaluation index, obtaining the first relative closeness of the pipe network leakage point based on the calculation result, superimposing a preset floating value on the updated weight of the evaluation index, recalculating the second relative closeness of the pipe network leakage point based on the weight after superimposing the preset floating value, and calculating the change rate between the first relative closeness and the second relative closeness; if the change rate is less than a preset change threshold, applying the updated weight as the final weight of the evaluation index; if the change rate is greater than the preset change threshold, returning to calculate the dynamic adjustment factor and updating the weight of the evaluation index again.

[0011] Further, the evaluation method further comprises: judging whether the data fluctuation of the evaluation index exceeds a preset fluctuation range, if the data fluctuation of the evaluation index does not exceed the preset fluctuation range, not updating the weight of the evaluation index; if the data fluctuation of the evaluation index exceeds the preset fluctuation range, calculating the dynamic adjustment factor corresponding to the evaluation index to update the weight of the evaluation index.

[0012] Further, the calculation of the dynamic adjustment factor based on the real-time working condition data and the historical working condition data comprises: calculating the standard deviation of the evaluation index based on the real-time working condition data, calculating the historical mean of the evaluation index based on the historical working condition data, and calculating the ratio result between the standard deviation and the historical mean; if the ratio result is greater than 0.5, the dynamic adjustment factor is 0.5; if the ratio result is less than 0.5, the dynamic adjustment factor is the ratio result.

[0013] Further, the evaluation method further comprises: the normalization processing adopts a vector normalization method, and the evaluation decision matrix is subjected to positive index processing based on the original value of the evaluation index to obtain the initial weight of the evaluation index.

[0014] In a second aspect, the application also provides an evaluation system for a pipe network leakage point, which applies the evaluation method for a pipe network leakage point as described above. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1A step flowchart of the evaluation method of the pipe network leakage point provided by an embodiment of the present application is shown in the figure; Figure 2 A flowchart of the sensitivity verification in the evaluation method of the pipe network leakage point provided by an embodiment of the present application is shown in the figure; Figure 3 A flowchart of the calculation of the relative closeness of the pipe network leakage point in the evaluation method of the pipe network leakage point provided by an embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0016] The present application will be described in detail below with reference to the specific embodiments shown in the accompanying drawings, but these embodiments do not limit the present application, and the structural, method, or functional changes made by those of ordinary skill in the art based on these embodiments are all included in the protection scope of the present application.

[0017] In the conventional pipe network leakage detection method, the importance of the evaluation index is allocated by using a fixed weight, and the method cannot dynamically respond to the real-time working condition changes of the pipe network, resulting in poor timeliness in leakage treatment and a long average maintenance response time of 7.2 hours, which easily leads to the occurrence of secondary disasters. In order to solve the problems of the prior art, in a first aspect, an evaluation method of a pipe network leakage point is provided, as shown in the figure, the evaluation method comprises the following steps: Figure 1 Step S11, historical working condition data of the pipe network is acquired, an evaluation decision matrix about the pipe network leakage point is constructed, the evaluation decision matrix includes original values of the pipe network leakage point on each evaluation index, the evaluation decision matrix is normalized to obtain initial weights of each evaluation index of the pipe network leakage point.

[0018] Step S12, real-time working condition data of the pipe network is acquired, a dynamic adjustment factor is calculated based on the real-time working condition data and the historical working condition data, the initial weights of the evaluation indexes are dynamically updated through the dynamic adjustment factor to obtain updated weights of the evaluation indexes, and the updated weights of the evaluation indexes are verified for sensitivity, and the weight values passing the sensitivity verification are applied as the final weights of the evaluation indexes.

[0019] Step S13, the initial weights of the evaluation indexes are weighted and normalized to obtain index values of the evaluation indexes.

[0020] Step S14, an ideal solution of the pipe network leakage point is constructed based on the index values, the distance between the pipe network leakage point and the ideal solution is calculated, and the relative closeness of the pipe network leakage point is obtained according to the calculation result.

[0021] Step S15, the relative closeness of each pipe network leakage point is acquired, and the priority ranking result of the pipe network leakage point is output based on the relative closeness.

[0022] ​Specifically, historical operating condition data of the pipe network is acquired, and the operating condition data includes data of various evaluation indexes related to the leakage risk, such as: current state parameters of the pipe material (such as real-time monitoring data of the aging degree of the material and the corrosion condition), leakage duration, historical leakage frequency, geographical location sensitivity (such as data of the population density and commercial activity of the region where the current leakage point is located), water pressure fluctuation, pipe diameter (the pipe diameter size of the pipe where the leakage point is located), buried depth (the depth of the pipe buried underground), and surrounding facility influence (such as the traffic condition of the road around the leakage point and the distribution condition of underground cables or other pipelines). Through multi-dimensional evaluation indexes, the operating condition of the pipe network is fully covered, and the total consideration of the pipe network leakage points is realized.

[0023] Based on the pipe network operating condition data, an evaluation decision matrix about the pipe network leakage points is constructed. Assuming that m leakage points are detected in the current pipe network, and each leakage point corresponds to n evaluation indexes, the form of the evaluation decision matrix can be a matrix of m rows and n columns, and the evaluation decision matrix can be represented as: x= [ ], i=(1, 2…m), j=(1, 2…n); each cell value in the evaluation decision matrix represents the original value of the i-th leakage point on the j-th evaluation index. For example, if the 1st leakage point is located in a commercial area, the pipe diameter is 1000 mm, and the leakage duration is 2 hours, then in the evaluation decision matrix, the cells corresponding to the evaluation indexes of “geographical location sensitivity”, “pipe diameter”, and “leakage duration” of this leakage point are filled with the corresponding data values.

[0024] The data units and value ranges of different evaluation indexes are different. The evaluation decision matrix is normalized to convert the data values of all evaluation indexes to a unified value interval (such as 0 to 1). Normalization can eliminate the influence of the differences in dimensions and value ranges between different evaluation indexes, so that all evaluation indexes are in the same order of magnitude, thereby obtaining the initial weights of each evaluation index of the pipe network leakage points.

[0025] After obtaining the initial weights of each evaluation index of the leakage point of the pipe network, in step S12, real-time working condition data of the pipe network is acquired, a dynamic adjustment factor is calculated based on the real-time working condition data and historical working condition data, the dynamic adjustment factor is used to quantify the deviation degree of the real-time working condition and the historical working condition, and the deviation is converted into an adjustment basis of the weight of the evaluation index, so that the weight of the evaluation index can be adaptively adjusted with the change of the running state of the pipe network. In order to further illustrate, an example of calculating the dynamic adjustment factor of the evaluation index is provided as follows: for the water pressure fluctuation index, the historical mean value of the evaluation index is counted from the historical working condition data, the real-time water pressure fluctuation data is compared with the historical mean value, the real-time deviation rate is calculated, the real-time deviation rate is compared with a preset value, and the minimum value is taken as the dynamic adjustment factor of the "water pressure fluctuation" index.

[0026] The weight of the evaluation index is dynamically updated through the initial weight of the evaluation index and the dynamic adjustment factor, and the update logic is that the initial weight is corrected based on the initial weight and combined with the dynamic adjustment factor to obtain the updated weight. In an embodiment, the weight update can be performed by the following formula: ; In the formula, represents the updated weight of the jth evaluation index at t, represents the initial weight of the jth evaluation index, represents the dynamic adjustment factor of the jth evaluation index at t.

[0027] Further, the updated weight of the evaluation index is verified for sensitivity to improve the robustness of the system. The sensitivity verification is usually performed by simulating a small change (such as an increase or decrease by a certain percentage) of the weight, recalculating the priority of the leakage point, and observing the change degree of the recalculated priority of the leakage point. If the change rate is within an acceptable range, it indicates that the weight adjustment is reasonable; if the change is too large, the dynamic adjustment factor needs to be recalculated. The weight passing the sensitivity verification is applied as the final weight of the evaluation index, which effectively avoids misjudgment caused by improper weight setting, thereby improving the robustness of the evaluation system.

[0028] Further, the final weight obtained by the previous steps is used to perform weighted normalization processing on the normalized evaluation decision matrix, so as to obtain an index value of each evaluation index in the evaluation, and the index value can represent the influence of each evaluation index on the priority of the leakage point of the pipe network. In an embodiment, the index value of the evaluation index can be calculated by the following formula: ; In the formula, represents the index value of the jth evaluation index of the ith leakage point of the pipe network, an initial weight of the jth evaluation index of the ith pipe network leakage point.

[0029] After obtaining the index values of the respective evaluation indexes, in step S14, an ideal solution of the pipe network leakage point is constructed based on the index values. The ideal solution provides a state reference for each actual leakage point, and the priority of the pipe network leakage point is determined by calculating the gap between the actual leakage point and the state reference. The gap between the pipe network leakage point and the ideal solution is quantified by calculating the distance between the pipe network leakage point and the ideal solution. Further, the relative closeness of the pipe network leakage point is calculated based on the distance between the pipe network leakage point and the ideal solution, and the numerical range of the relative closeness is between 0 and 1. The closer the relative closeness is to 1, the higher the priority of the pipe network leakage point. The closer the relative closeness is to 0, the lower the priority of the pipe network leakage point.

[0030] Through the above method, the relative closeness of all leakage points in the pipe network is calculated, and the leakage points are sorted in descending order of the relative closeness. The leakage point with the highest relative closeness is considered the most urgent leakage point and needs to be processed first. The leakage points with lower relative closeness are less urgent.

[0031] According to the above description, the evaluation method for the pipe network leakage point provided by the embodiments of the present application adjusts the dynamic adjustment factor of the evaluation index by using the pipe network operation data to adjust the weight of each evaluation index, and further adjusts the influence of each evaluation index on quantifying the priority of the pipe network leakage point, so as to timely respond to the real-time working condition changes of the pipe network and improve the accuracy of the priority judgment of the pipe network leakage point. By constructing the ideal solution of the pipe network leakage point and obtaining the relative closeness of the pipe network leakage point based on the distance between the pipe network leakage point and the ideal solution, the intelligent priority sorting of the pipe network leakage point is realized, the response sensitivity to the high-risk leakage point is improved, the maintenance personnel can prioritize the high-risk leakage point for processing according to the priority sorting, the resource waste is reduced, and the risk of secondary disasters is reduced.

[0032] As an optional implementation manner, in step S11, the vector normalization method is used to normalize the evaluation decision matrix, and the average decision matrix is processed in a positive direction based on the original values of the evaluation indexes to obtain the initial weight of the evaluation index. The vector normalization method associates the original value of each evaluation index with the overall situation of all original values of the leakage points under the evaluation index, and obtains the standardized value of each leakage point on the corresponding evaluation index. The standardized value is the initial weight of the evaluation index. The vector normalization method can be expressed in the following formula: ; In the formula, an initial weight of the jth evaluation index of the ith pipe network leakage point, represents the original value of the i-th leakage point on the j-th evaluation index, and m represents the number of leakage points of the pipe network.

[0033] After obtaining the initial weight of the evaluation index, as an optional implementation, the evaluation method further determines whether the evaluation index needs to be updated in weight by the following manner: determining whether the data fluctuation of the evaluation index exceeds the preset fluctuation range, if the data fluctuation of the evaluation index does not exceed the preset fluctuation range, the weight of the evaluation index is not updated; if the data fluctuation of the evaluation index exceeds the preset fluctuation range, a dynamic adjustment factor corresponding to the evaluation index is calculated to update the weight of the evaluation index.

[0034] Specifically, the preset fluctuation range is formulated based on the historical operating condition data of the long-term operation of the pipe network, the leakage risk control standards in the industry and the experience of experts in the field, to ensure the rationality of the fluctuation determination and avoid misjudgment due to the attribute difference of the evaluation index.

[0035] If the data fluctuation of the evaluation index does not exceed the preset fluctuation range, it indicates that the current state of the evaluation index is basically consistent with the historical normal state, and the weight of the evaluation index is not updated at this time, reducing the management cost. When the data fluctuation exceeds the preset range, it indicates that the current state of the evaluation index has deviated from the historical normal state, at this time, the dynamic adjustment factor is calculated and the weight of the evaluation index is updated, by changing the weight of the evaluation index, the risk influence of the evaluation index in the leakage point priority evaluation is strengthened, thereby realizing the timely identification and priority processing of high-risk leakage points, avoiding the non-response defect of the traditional static weight to the operating condition change, and preventing the evaluation instability caused by excessive sensitivity, and realizing the precise weight management.

[0036] Further, for the evaluation index that needs to be updated in weight, as an optional implementation, in step S12, the dynamic adjustment factor is calculated by the following manner: The standard deviation of the evaluation index is calculated based on the real-time operating condition data, the historical mean of the evaluation index is calculated based on the historical operating condition data, and the ratio result between the standard deviation and the historical mean is further calculated; if the ratio result is greater than 0.5, the dynamic adjustment factor is 0.5; if the ratio result is less than 0.5, the dynamic adjustment factor is the ratio result.

[0037] By calculating the ratio result between the standard deviation and the historical mean of the evaluation index, the deviation amplitude of the current operating condition relative to the historical operating condition is quantified. The larger the ratio, the more abnormal the data of the evaluation index at the current time, and the more significant the volatility compared to the normal level. A preset threshold is introduced to judge the ratio result, if the ratio result is greater than the preset threshold, the dynamic adjustment factor is equal to the preset threshold; if the ratio result is less than the preset threshold, the dynamic adjustment factor is equal to the ratio result.

[0038] The preset threshold can limit the amplitude. Even if a certain evaluation indicator fluctuates extremely abnormally, by limiting the maximum value of the dynamic adjustment factor to the preset threshold, it can prevent the weight from changing drastically due to a single extreme event or sensor false alarm, thus maintaining the stability and robustness of the evaluation system and avoiding abnormal jumps in the evaluation results.

[0039] In one embodiment, the dynamic adjustment factor for the evaluation index can be calculated using the following formula: ; In the formula, This represents the dynamic adjustment factor of the j-th evaluation indicator at time t. It represents the standard deviation of the j-th evaluation indicator at time t.

[0040] After updating the weights of the evaluation indicators, as an optional implementation method, such as... Figure 2 As shown, sensitivity verification is performed on the updated weights of the evaluation metrics, including: The distance between the pipeline leakage point and the ideal solution is calculated based on the updated weights of the evaluation indicators. The first relative proximity of the pipeline leakage point is obtained based on the calculation results. A preset floating value is added to the updated weights of the evaluation indicators. The second relative proximity of the pipeline leakage point is recalculated based on the added weights. The rate of change between the first relative proximity and the second relative proximity is calculated.

[0041] If the rate of change is less than the preset change threshold, the updated weights are applied as the final weights of the evaluation indicators; if the rate of change is greater than the preset change threshold, the calculation of the dynamic adjustment factor is returned, and the weights of the evaluation indicators are updated again.

[0042] Specifically, based on the updated weights of the evaluation indicators, the first relative proximity of the pipeline leakage points is calculated. Then, a preset floating value is added to the updated weight values. The relative proximity is recalculated based on the weights after adding the preset floating value to obtain the second relative proximity of the pipeline leakage points. The rate of change between the first and second relative proximity is calculated. If this rate of change is less than a preset threshold, it indicates that the updated weights of the evaluation indicators have good stability, and these updated weights are applied as the final weights of the evaluation indicators. If the rate of change is greater than the preset threshold, it indicates that the weights of the evaluation indicators are too sensitive to small fluctuations, which may lead to unreliable ranking results. In this case, the evaluation system returns to recalculate the dynamic adjustment factor and re-updates the weights of the evaluation indicators to ensure the robustness of the evaluation method.

[0043] To further illustrate, the following provides an example of sensitivity verification: set the preset floating value to ±10%, the preset change threshold to 5%, and for the weight value of the updated evaluation index, after superimposing the preset floating value, if the change rate between the first relative closeness and the second relative closeness is less than 5%, the updated weight is applied as the final weight of the evaluation index; if the change rate between the first relative closeness and the second relative closeness is greater than 5%, the dynamic adjustment factor is recalculated, and the weight of the evaluation index is updated again.

[0044] After obtaining the final weight of the evaluation index, the initial weight of the evaluation index is used to perform weighted normalization processing on the final weight, to obtain an index value of the evaluation index, and an ideal solution of the pipe network leakage point is constructed based on the index value. As an optional implementation manner, as shown in Figure 3 The ideal solution includes a positive ideal solution and a negative ideal solution, the positive ideal solution is a vector composed of the maximum value of the index value of the evaluation index, and the negative ideal solution is a vector composed of the minimum value of the index value of the evaluation index.

[0045] The distance between the pipe network leakage point and the positive ideal solution and the distance between the pipe network leakage point and the negative ideal solution are calculated respectively, and the relative closeness is calculated according to the distance between the pipe network leakage point and the positive ideal solution and the distance between the pipe network leakage point and the negative ideal solution.

[0046] Specifically, the positive ideal solution is composed of the optimal value of each evaluation index, and the positive ideal solution represents the best leakage point state in the ideal solution; the negative ideal solution is composed of the worst value of each evaluation index, and the negative ideal solution represents the most undesirable leakage point state.

[0047] In an embodiment, the positive ideal solution can be represented by the following formula: ; In the formula, represents the positive ideal solution, represents the index value of the jth evaluation index of the ith pipe network leakage point.

[0048] The negative ideal solution can be represented by the following formula: ; In the formula, represents the negative ideal solution, represents the index value of the jth evaluation index of the ith pipe network leakage point.

[0049] The distance between each leakage point and the positive ideal solution and the negative ideal solution is calculated. The closer to the positive ideal solution, the better the state of the leakage point; the closer to the negative ideal solution, the worse the state. According to the distance calculation result, the relative closeness of each leakage point is calculated. The greater the relative closeness, the more the leakage point should be prioritized. According to the relative closeness of each leakage point from large to small, the priority ranking result of the pipe network leakage point is output. Optionally, the priority ranking result of the pipe network leakage point can also generate a treatment plan corresponding to the pipe network leakage point.

[0050] In an embodiment, the relative closeness can be calculated by the following formula: ; In the formula, denotes the relative closeness of the i th pipe network leakage point, denotes the distance between the i th pipe network leakage point and the negative ideal solution, denotes the distance between the i th pipe network leakage point and the positive ideal solution.

[0051] In an embodiment, the distance between the pipe network leakage point and the negative ideal solution can be calculated by the following formula: ; In the formula, denotes the distance between the i th pipe network leakage point and the negative ideal solution, and n denotes the number of evaluation indexes, denotes the index value of the j th evaluation index of the i th pipe network leakage point, denotes the minimum value of the j th index.

[0052] Further, as an optional implementation, a penalty term is introduced when calculating the distance between the pipe network leakage point and the positive ideal solution. The penalty term is used to weight the influence of abnormal indexes on the priority of the pipe network leakage point. The abnormal indexes at least include pressure drop or leakage alarm.

[0053] Specifically, there are sudden abnormal events in the operation of the pipe network, for example, the water pressure of a certain point is monitored to drop sharply in a very short time, or an automatic leakage alarm signal is received from the region, which may indicate that a serious accident such as pipe burst is occurring at the location. The penalty term is added to the distance calculation between the leakage point and the positive ideal solution. If a sudden event such as pressure drop or leakage alarm is monitored at the location of a leakage point, the penalty term calculation for the leakage point is activated. The distance between the leakage point and the positive ideal solution is changed through the penalty term, thereby affecting the calculation result of the relative closeness of the pipe network leakage point. By introducing the penalty term mechanism, the evaluation system can actively identify and respond to sudden abnormal events, improve the response sensitivity to high-risk leakage points, and significantly improve the acuteness of the priority ranking.

[0054] In an embodiment, the distance between the pipe network leakage point and the positive ideal solution can be calculated by the following formula: In the formula, represents the distance between the i-th pipe network leakage point and the positive ideal solution, n represents the number of evaluation indexes, represents the index value of the j-th evaluation index of the i-th pipe network leakage point, represents the maximum value of the j-th evaluation index, represents a penalty term.

[0055] According to the above description, the evaluation method for the pipe network leakage point provided by the embodiments of the present application can calculate the dynamic adjustment factor of the evaluation index through the pipe network operation data, adjust the weight of each evaluation index, and further adjust the influence of each evaluation index on the quantification of the priority of the pipe network leakage point, so as to timely respond to the real-time working condition change of the pipe network and improve the accuracy of the judgment of the priority of the pipe network leakage point. The relative closeness of the pipe network leakage point is obtained based on the distance between the pipe network leakage point and the positive and negative ideal solutions, the intelligent priority sorting of the pipe network leakage point is realized, and the accuracy of the judgment of the priority of the leakage point is significantly improved. In addition, the penalty term mechanism is introduced when calculating the distance between the pipe network leakage point and the positive ideal solution, the response sensitivity to the high-risk leakage point is improved, the maintenance personnel can prioritize the high-risk leakage point for processing according to the priority sorting, the resource waste is reduced, and the risk of secondary disasters is reduced.

[0056] In a second aspect, based on the same inventive concept, the embodiments of the present application also provide an evaluation system for a pipe network leakage point. The evaluation system applies the evaluation method for the pipe network leakage point described above. The evaluation system can adaptively adjust the weight of each evaluation index according to the real-time working condition, and improve the accuracy of the judgment of the priority of the pipe network leakage point.

[0057] It can be understood that the word "exemplary" used herein means "serving as an example, illustration, or description". Any embodiment described as "exemplary" is not necessarily superior or preferred to other embodiments and / or does not exclude features combined with other embodiments. It should be understood that certain features of the present application described in the context of separate embodiments can also be provided in combination, for the sake of clarity. Conversely, various features of the present application described in the context of a single embodiment can also be provided separately or in any suitable combination or as part of any other described embodiment of the present application.

[0058] ​In the description of the application, unless otherwise specified, " / " means the meaning of "or", for example, A / B can mean A or B. "And / or" in this paper is only a description of the relationship between the associated objects, which means that there can be three relationships, for example, A and / or B, which can mean: A exists alone, A and B exist together, and B exists alone. In addition, "at least one" means one or more, and "multiple" means two or more. "First", "second" and the like are not limited in quantity and execution order, and "first", "second" and the like are not necessarily different.

[0059] The above only discloses the preferred embodiments of the application, but does not limit the scope of the application. Those skilled in the art can understand that changes, modifications, substitutions, combinations and simplifications without departing from the spirit and scope of the application and the appended claims, are equivalent replacement methods still within the scope of the application.

Claims

1. A method of assessing a leak point in a pipe network, characterised by, The method comprises the following steps: obtaining historical working condition data of the pipe network, constructing an evaluation decision matrix about the pipe network leakage points, the evaluation decision matrix comprising original values of the pipe network leakage points on each evaluation index, performing normalization processing on the evaluation decision matrix to obtain initial weights of each evaluation index about the pipe network leakage points; obtaining real-time working condition data of the pipe network, calculating a dynamic adjustment factor based on the real-time working condition data and the historical working condition data, dynamically updating the initial weights of the evaluation indexes through the dynamic adjustment factor to obtain updated weights of the evaluation indexes, and performing sensitivity verification on the updated weights of the evaluation indexes, applying the weights passing the sensitivity verification as final weights of the evaluation indexes; performing weighted normalization processing on the final weights of the evaluation indexes using the initial weights of the evaluation indexes to obtain index values of the evaluation indexes; constructing an ideal solution of the pipe network leakage points based on the index values, calculating distances between the pipe network leakage points and the ideal solution, and obtaining relative closeness degrees of the pipe network leakage points according to the calculation results; obtaining the relative closeness degrees of each pipe network leakage point, and outputting a priority ranking result of the pipe network leakage points based on the sizes of the relative closeness degrees.

2. The evaluation method according to claim 1, characterized in that The ideal solution comprises a positive ideal solution and a negative ideal solution, the positive ideal solution is a vector composed of maximum values of the index values of the evaluation indexes, and the negative ideal solution is a vector composed of minimum values of the index values of the evaluation indexes; distances between the pipe network leakage points and the positive ideal solution and distances between the pipe network leakage points and the negative ideal solution are calculated respectively, and the relative closeness degrees are calculated according to the distances between the pipe network leakage points and the positive ideal solution and the distances between the pipe network leakage points and the negative ideal solution.

3. The evaluation method according to claim 2, characterized in that The distance between the pipe network leakage point and the negative ideal solution is calculated by the following formula: ； In the formula, represents the distance between the i-th pipe network leakage point and the negative ideal solution, n represents the number of evaluation indexes, represents the index value of the j-th evaluation index of the i-th pipe network leakage point, represents the minimum value of the j-th index.

4. The evaluation method according to claim 2, characterized in that The evaluation method further comprises: a penalty term is introduced when calculating the distance between the pipe network leakage point and the positive ideal solution, the penalty term is used to weight the influence of an abnormal index on the priority of the pipe network leakage point, and the abnormal index at least comprises a pressure drop or a leakage alarm.

5. The evaluation method according to claim 4, characterized in that The distance between the pipe network leakage point and the positive ideal solution is calculated by the following formula: ； In the formula, represents the distance between the i-th pipe network leakage point and the positive ideal solution, n represents the number of evaluation indexes, represents the index value of the j-th evaluation index of the i-th pipe network leakage point, represents the maximum value of the j-th evaluation index, represents the penalty term.

6. The evaluation method according to claim 1, characterized in that The sensitivity verification on the updated weights of the evaluation indexes comprises: distances between the pipe network leakage points and the ideal solution are calculated based on the updated weights of the evaluation indexes, first relative closeness degrees of the pipe network leakage points are obtained based on the calculation results, preset floating values are superimposed on the updated weights of the evaluation indexes, second relative closeness degrees of the pipe network leakage points are recalculated based on the weights superimposed with the preset floating values, and a change rate between the first relative closeness degrees and the second relative closeness degrees is calculated; if the change rate is less than a preset change threshold, the updated weights are applied as the final weights of the evaluation indexes; if the change rate is greater than the preset change threshold, the dynamic adjustment factor is returned to be calculated, and the weights of the evaluation indexes are updated again.

7. The evaluation method according to claim 1, characterized in that The evaluation method further comprises: determining whether the data fluctuation of the evaluation index exceeds a preset fluctuation range, and if the data fluctuation of the evaluation index does not exceed the preset fluctuation range, not updating the weight of the evaluation index; if the data fluctuation of the evaluation index exceeds the preset fluctuation range, calculating the dynamic adjustment factor corresponding to the evaluation index to update the weight of the evaluation index.

8. The evaluation method according to claim 1, characterized in that The calculation of the dynamic adjustment factor based on the real-time working condition data and the historical working condition data comprises: calculating the standard deviation of the evaluation index based on the real-time working condition data, calculating the historical mean of the evaluation index based on the historical working condition data, and calculating the ratio between the standard deviation and the historical mean; if the ratio is greater than 0.5, the dynamic adjustment factor is 0.5; if the ratio is less than 0.5, the dynamic adjustment factor is the ratio.

9. The evaluation method according to claim 1, characterized in that The evaluation method further comprises: The normalization processing adopts a vector normalization method, and the evaluation decision matrix is subjected to positive index processing based on the original value of the evaluation index to obtain the initial weight of the evaluation index.

10. A system for assessing leakage points in a pipeline network, characterized in that, The evaluation system applies the evaluation method of the leakage point of the pipe network as claimed in any one of claims 1 to 9.

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