A pipeline network liquid level analysis system, method and device based on tidal data

Abstract

This invention relates to the field of pipeline network liquid level analysis technology, specifically to a pipeline network liquid level analysis system, method, and equipment based on tidal data. The method includes: acquiring liquid level data of the object to be analyzed; acquiring target tidal level data associated with the object to be analyzed; calculating the correlation between the liquid level of the object to be analyzed and the target tidal level based on the liquid level data and the target tidal level data; and analyzing the pipeline network liquid level corresponding to the object to be analyzed based on the correlation, thereby achieving monitoring of the pipeline network liquid level. This invention enables monitoring of pipeline network liquid levels and facilitates understanding of the impact of tides on pipeline network liquid levels.

Description

Technical Field

[0001] The present invention relates to the technical field of pipe network liquid level analysis, and in particular to a pipe network liquid level analysis system, method and equipment based on tidal data. Background Art

[0002] At present, the practice of frontier cities in China is to strictly guard against it. In terms of design, sluice gates are vigorously built and anti-backflow gates are set up. However, even so, the impact of tides on drainage systems is still serious. Various coastal cities have also paid attention to the impact of tides on drainage systems, but very few of them really guide production. The daily management of tidal zone sewage systems still basically remains at the level of manual inspection, laissez-faire, and solving problems by increasing the construction of sewage treatment plants.

[0003] Due to insufficient attention paid to the construction of drainage systems in coastal cities during the early economic development and the design limitations at the time, many sewage pipes were incorrectly mixed, rainwater and sewage were not separated, and the facilities to prevent the backflow of river and seawater were outdated or insufficient. The impact of tides on sewage pipes in tidal zones has always been a serious problem.

[0004] After searching, it was found that there is currently no method to analyze the liquid level of the pipe network based on tidal data to monitor the liquid level of the sewage pipe network in the tidal zone in real time. Summary of the invention

[0005] One of the objects of the present invention is to provide a pipeline liquid level analysis system, method and equipment based on tidal data, which obtains the liquid level data of the analysis object and the target tidal level data associated with the analysis object, calculates the degree of correlation between the liquid level of the analysis object and the target tidal level, and then analyzes the pipeline liquid level corresponding to the analysis object according to the degree of correlation, thereby enabling the monitoring of the pipeline liquid level.

[0006] A pipe network liquid level analysis system based on tidal data, comprising:

[0007] A liquid level data acquisition module, used to acquire liquid level data of the analysis object;

[0008] A tide data acquisition module, used to acquire target tide data associated with the analysis object;

[0009] A calculation module, used for calculating the correlation degree between the analysis object liquid level and the target tidal level according to the liquid level data and the target tidal level data;

[0010] The analysis module is used to analyze the pipe network liquid level corresponding to the analysis object according to the correlation degree, so as to monitor the pipe network liquid level.

[0011] Preferably, the calculation module includes:

[0012] A first calculation unit, configured to calculate the support, confidence and lift between the analysis object liquid level and the target tidal level according to the liquid level data and the target tidal level data;

[0013] The second calculation unit is used to calculate the association degree according to the support degree, the confidence degree and the improvement degree.

[0014] Preferably, the degree of association is based on the formula calculated;

[0015] in, Indicates the degree of association, Express support, Indicates confidence, Indicates the degree of improvement, represents a natural constant, , , Respectively represent the adjustment coefficients corresponding to the support, the confidence, and the improvement.

[0016] Preferably, the analysis module comprises:

[0017] A backflow area determination unit, used to determine the backflow area according to the correlation degree and the target area information corresponding to the analysis object;

[0018] A backflow index acquisition unit, used to acquire the backflow indexes of all possible backflow sources in the backflow area;

[0019] A backflow source acquisition unit, used for acquiring a key backflow source according to the backflow index;

[0020] The pipe network liquid level analysis unit is used to analyze the pipe network liquid level corresponding to the analysis object according to the key backflow source, so as to monitor the pipe network liquid level.

[0021] Preferably, the backflow index ;

[0022] in, Indicates the number of factors that cause backflow at the backflow source. represents a natural constant, Indicates The factor value that causes backflow at the source of backflow, Indicates The adjustment factor of the factor value that causes backflow at the source of backflow, Indicates The correction value of the weight value of the factor that causes backflow at the source of backflow.

[0023] A method for analyzing the liquid level of a pipe network based on tidal data comprises the following steps:

[0024] Acquire liquid level data of the analysis object;

[0025] Acquiring target tide data associated with the analysis object;

[0026] Calculating the correlation between the analysis object liquid level and the target tidal level according to the liquid level data and the target tidal level data;

[0027] According to the correlation degree, the pipe network liquid level corresponding to the analysis object is analyzed to achieve monitoring of the pipe network liquid level.

[0028] Preferably, the specific method for calculating the degree of correlation between the analysis object liquid level and the target tidal level according to the liquid level data and the target tidal level data comprises the following steps:

[0029] Calculate the support, confidence and lift between the analysis object liquid level and the target tidal level according to the liquid level data and the target tidal level data;

[0030] The association degree is calculated according to the support, the confidence and the lift.

[0031] Preferably, according to the correlation degree, the pipe network liquid level corresponding to the analysis object is analyzed, and the specific method for monitoring the pipe network liquid level includes the following steps:

[0032] Determine the backflow area according to the correlation degree and the target area information corresponding to the analysis object;

[0033] Obtain the backflow index of all possible backflow sources in the backflow area;

[0034] Obtaining key backflow sources according to the backflow index;

[0035] The liquid level of the pipe network corresponding to the analysis object is analyzed according to the key backflow source, so as to monitor the liquid level of the pipe network.

[0036] Preferably, the backflow index ;

[0037] in, Indicates the number of factors that cause backflow at the backflow source. represents a natural constant, Indicates The value of the factor that causes backflow at the source of backflow. Indicates The adjustment factor of the factor value that causes backflow at the source of backflow, Indicates The correction value of the weight value of the factor that causes backflow at the source of backflow, Indicates the degree of association.

[0038] A pipe network liquid level analysis device based on tidal data, comprising:

[0039] Controller;

[0040] A memory storing executable instructions;

[0041] Among them, the executable instructions can be run on the controller and implement the pipeline network liquid level analysis method based on tidal data.

[0042] The present invention provides a pipeline network liquid level analysis system, method and device based on tidal data, which has the following beneficial effects:

[0043] 1. By acquiring the liquid level data of the analysis object and the target tide level data associated with the analysis object, calculating the correlation degree between the liquid level of the analysis object and the target tide level, and then analyzing the pipe network liquid level corresponding to the analysis object according to the correlation degree, the pipe network liquid level can be monitored, and the influence of tide on the pipe network liquid level can be understood conveniently.

[0044] 2. By determining the backflow area, obtaining the backflow index of all possible backflow sources in the backflow area, and obtaining the key backflow source according to the backflow index, the liquid level of the pipe network corresponding to the analysis object can be analyzed according to the key backflow source, and the key backflow point can be found, so as to strengthen the protection measures for the key backflow point, thereby preventing external water from entering the sewage pipe network and contributing to improving the quality and efficiency of the sewage pipe network.

[0045] 3. By obtaining the backflow index of all possible backflow sources in the backflow area and obtaining the key backflow sources based on the backflow index, the sewage pipe network in the tidal zone can be analyzed, investigated and cleaned up in a targeted manner, so that front-line personnel can accurately and efficiently deal with sewage pipe network problems and strengthen the investigation and cleaning of key backflow sources, so as to reduce the blocking factor of sewage and combined pipe networks, improve water dynamics, and achieve the goal of lowering the water level of the overall pipe network. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily drawn to scale, but the emphasis is placed on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0047] Figure 1 It is a schematic diagram of the overall process of a pipeline network liquid level analysis method based on tidal data of the present invention;

[0048] Figure 2It is a flow chart of the method for calculating the degree of association of the present invention;

[0049] Figure 3 It is a schematic diagram of the flow chart of the pipe network liquid level control method of the present invention;

[0050] Figure 4 It is a schematic diagram of the data table format of the present invention;

[0051] Figure 5 It is a schematic diagram of the changing effect of the liquid level gauge curve and the tidal curve in the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with its embodiments. It should be understood that the specific implementation methods described herein are only used to explain the present invention and do not limit the protection scope of the present invention.

[0053] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only and do not represent the only implementation method.

[0054] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0055] The “first” and “second” mentioned in the present invention do not represent specific quantities and orders, but are merely used to distinguish names.

[0056] Before elaborating on the pipeline network liquid level analysis system, method and device based on tidal data described in the present invention, the problems existing in the prior art are first explained.

[0057] Since the water bodies in coastal cities are seriously affected by tides, the drainage system will inevitably be severely impacted. At present, the practices of frontier cities in China are to strictly guard against it, vigorously build sluices and set up anti-backflow gates, but even so, the impact of tides on the drainage system is still serious. Various coastal cities have also paid attention to the impact of tides on the drainage system, but very few of them really guide production. The daily management of the tidal zone sewage system is still basically at the level of manual inspection, laissez-faire, and solving the problem by increasing the construction of sewage treatment plants.

[0058] Due to insufficient attention paid to the construction of drainage systems in coastal cities during the early economic development and the design limitations at the time, many sewage pipes were incorrectly mixed, rainwater and sewage were not separated, and the facilities to prevent the backflow of river and seawater were outdated or insufficient. The impact of tides on sewage pipes in tidal zones has always been a serious problem.

[0059] Some coastal cities, such as Guangzhou, have already started rainwater and sewage diversion and remediation work, and most areas have achieved the "last meter" of sewage connection. However, due to limited construction conditions, some areas have not been able to completely separate rainwater and sewage, and can only collect water from existing drainage pipes (box culverts) through interception wells. The interception wells along the river have the following hidden dangers: the interception weir is too low or buried too deep, and the river water is easy to flow back through the flap gate at high tide; the flap gate is not closed tightly, which aggravates the degree of river water backflow; due to the use of combined sewer interception method, rainwater entering the interception well will be inevitable. In addition, some coastal cities, such as Guangzhou, still have a large number of tidal zone pipe networks, rainwater and sewage use combined channel boxes, and the sewage pipe network laid in the urban river is mixed, leaking, and backflowing.

[0060] In addition, in rural areas and old urban areas, there is a general lack of awareness of sewage management among villagers and the problem of privately installing and connecting pipes. The pipe network is interconnected and complex, and the pipes are connected to rivers, which can easily cause river water to backflow when the tide changes.

[0061] In order to analyze and monitor the liquid level of the sewage pipe network and avoid backflow of river and sea water, the present invention provides a pipe network liquid level analysis system based on tidal data, including a liquid level data acquisition module, a tidal level data acquisition module, a calculation module and an analysis module.

[0062] The liquid level data acquisition module is used to acquire the liquid level data of the analysis object; wherein the analysis object refers to the liquid level meter of the analysis target area, and the liquid level data is the liquid level meter data of the analysis target area.

[0063] The tidal data acquisition module is used to acquire target tidal data associated with the analysis object; wherein the target tidal data is river water level data close to the analysis target area, and the river water level data is calculated by combining measured values ​​and predicted values ​​to improve accuracy.

[0064] The measured value is collected by the level gauge installed in the river area close to the target area for analysis. The predicted value is obtained by fitting the historical target tide data to obtain the target tide data curve function, and then is obtained based on the target tide data curve function. The target tide data can be taken as the average of the measured value and the predicted value.

[0065] The time points and frequencies of the liquid level data of the analysis object and the target tide level data should be ensured to be the same or similar, and the data frequency should be no less than once every 15 minutes. The data storage format of the two can be xls or xlsx format.

[0066] The calculation module is used to calculate the degree of correlation between the liquid level of the analysis object and the target tide level according to the liquid level data and the target tide level data; the analysis module is used to analyze the pipe network liquid level corresponding to the analysis object according to the degree of correlation to realize the monitoring of the pipe network liquid level.

[0067] Generally speaking, the greater the correlation degree, the greater the influence of the target tide data on the liquid level data of the analysis object, and the greater the influence of the target tide on the liquid level of the pipe network corresponding to the analysis object. Therefore, by analyzing the liquid level of the pipe network corresponding to the analysis object through the correlation degree, it is possible to monitor the liquid level of the pipe network, understand the influence of the tide on the liquid level of the pipe network, and then take corresponding measures, such as targeted inspection and detoxification of certain pipe networks, to avoid the entry of external water into the sewage pipe network and the occurrence of backflow, and contribute to improving the quality and efficiency of the sewage pipe network.

[0068] That is to say, by acquiring the liquid level data of the analysis object and the target tide level data associated with the analysis object, calculating the degree of correlation between the liquid level of the analysis object and the target tide level, and then analyzing the pipe network liquid level corresponding to the analysis object based on the degree of correlation, the pipe network liquid level can be monitored, making it easier to understand the impact of the tide on the pipe network liquid level.

[0069] As a preferred technical solution, the calculation module includes a first calculation unit and a second calculation unit.

[0070] The first calculation unit is used to calculate the support, confidence and lift between the analysis object liquid level and the target tidal level according to the liquid level data and the target tidal level data. The second calculation unit is used to calculate the association degree according to the support, confidence and lift.

[0071] The sewage pipe network laid in the urban river in the tidal zone is more prone to external water intrusion due to problems such as wrong mixing and leakage. The liquid level change of the urban sewage pipe network is mainly based on the law of domestic water use. Once external water invades, its change law will show the characteristics of the combination of tidal level change and water use law change. By superimposing the tidal level change curve and the liquid level change curve, it can be visually judged that they have related characteristics. However, when the tide level runs in certain intervals, it will cause external water intrusion. The operation change law of the sewage pipe network will be very complicated, and sometimes even chaotic. It is generally difficult to determine the possibility of intrusion based on graphic superposition analysis. The graphic superposition method is a process of manually judging the data after presenting it through drawing tools. It is difficult to handle large amounts of data and cannot give numerical results.

[0072] If the basic principle of the graphic overlay method is applied, the drawing analysis process is abandoned, and the target tide data and the analysis object data are directly used for synchronous percentage statistics, it can be concluded that when a certain value is exceeded, the analysis point is more likely to be affected by the tide, and the connection between the river water body and the sewage network can be determined. The above process can be calculated by writing a computer program and importing the liquid level meter data for analysis to obtain numerical results. For operation and maintenance managers, the effort invested in organizing targeted small-scale surveys guided by numerical results will be greatly reduced, and work efficiency can be doubled. At the same time, as long as the range and accuracy of the input data are guaranteed, the accuracy and credibility of the analysis results can be guaranteed, and human misjudgment, omission and wrong judgment can be avoided.

[0073] Apriori algorithm is a frequent itemset algorithm for mining association rules. It uses an iterative method of layer-by-layer search to find the relationship between item sets in the database to form rules. The process consists of connection (matrix-like operation) and pruning (removing unnecessary intermediate results). The concept of item set in this algorithm is a set of items. A set containing K items is a k-item set. The frequency of an item set is the number of transactions containing the item set, which is called the frequency of the item set. If an item set meets the minimum support, it is called a frequent item set. Frequent item sets can be measured by support, confidence, and lift.

[0074] Support: The proportion of the number of times one or several interrelated things appear in a data set to the total data set. .

[0075] Confidence: It indicates the probability of another thing occurring when one thing occurs, that is, conditional probability. .

[0076] Lift: The ratio of the probability of X occurring when Y is present to the probability of X occurring overall. .

[0077] Generally speaking, to select a frequent data set in a data set, you need to customize the evaluation criteria. The most commonly used evaluation criteria are to use a customized support, or a combination of customized support and confidence.

[0078] In the analysis of the correlation between tides and the liquid level of sewage pipe networks in tidal zones, since the changing patterns of sewage pipe networks will show the characteristics of a combination of tidal changes and water use patterns, through a large amount of data analysis and comparison, it is empirically determined that when the support degree is ≥ 0.3, it indicates that there is a correlation between the liquid level of the sewage pipe network and the tide.

[0079] The advantage of the Apriori algorithm is that it processes a large amount of data and has no restrictions on the data volume. Generally speaking, when the data volume is more than 24 nodes and the data source is accurate, the larger the data volume, the higher the accuracy of the correlation analysis. Specifically, based on the Apriori algorithm, the support, confidence and lift of frequent itemsets are obtained by referencing an external calculation module (apiori module in the apyori library) for calculation.

[0080] Generally speaking, support is the most important data. The higher the support data, the stronger the correlation between the analysis object and the target tide level. According to experience, when support < 0.3, the correlation is weak and can be regarded as unrelated. When 0.3 < support < 0.4, the correlation strength is medium and needs attention. When 0.4 < support < 0.5, the correlation strength is strong, and it is necessary to actively investigate the target area where the analysis object is located. When support > 0.5, it is extremely strong, indicating that the target tide level has caused obvious fluctuations in water quality and quantity in the target area. The role of confidence and lift values ​​is to assist support in more accurate analysis and judgment.

[0081] After the first calculation unit calculates the support, confidence and lift between the analysis object liquid level and the target tide level according to the liquid level data and the target tide level data and based on the Apriori algorithm, the second calculation unit calculates the degree of association according to the support, confidence and lift.

[0082] The analysis module obtains possible backflow sources in the target area according to the degree of association, and analyzes the pipe network liquid level corresponding to the analysis object based on the obtained possible backflow sources, thereby realizing the monitoring of the pipe network liquid level.

[0083] Based on the support as the most important data, the higher the support data, the stronger the correlation between the analysis object and the target tide level, and the role of the confidence and lift values ​​is to assist the support to make a more accurate analysis and judgment. Preferably, the correlation degree is calculated according to the formula Calculated.

[0084] in, Indicates the degree of association, Express support, Indicates confidence, Indicates the degree of improvement, represents a natural constant, , , They represent adjustment coefficients corresponding to the support, the confidence, and the lift, respectively, and can be set by technicians based on experience. , , The values ​​can be set to 1.1, 0.62, and 0.25 respectively.

[0085] Through the correlation degree formula The support, confidence and lift calculated based on the Apriori algorithm can be combined. Through the correlation, the inspection and maintenance personnel of the drainage company can clearly know which liquid level gauge in the target area is closer to the source of backflow, and then strengthen the protection measures for the source of backflow in a targeted manner, so as to prevent external water from entering the sewage network, contribute to improving the quality and efficiency of the sewage network, and timely and accurately check and clean the sewage network at the source of backflow, reduce the blocking factor of sewage and combined pipe networks, improve water dynamics, and achieve the goal of lowering the water level of the overall pipe network.

[0086] As a preferred technical solution, the analysis module includes a backflow area determination unit, a backflow index acquisition unit, a backflow source acquisition unit and a pipe network liquid level analysis unit.

[0087] The backflow area determination unit is used to determine the backflow area according to the correlation degree and the target area information corresponding to the analysis object.

[0088] The object of analysis is the level meter of the target area for analysis, and the level data of the object of analysis is the level meter data of the target area for analysis. The larger the value of the correlation degree is, the more likely the source of the backflow is close to the level meter of the corresponding target area for analysis. If the value of the correlation degree is too small, it means that the possibility of backflow of the pipe network close to the corresponding level meter is very small, and it can be considered to be ignored. Preferably, the backflow area determination unit can compare the size between the correlation degree and the preset minimum correlation degree threshold, and take the pipe network within a preset radius centered on the target area level meter with a correlation degree greater than the preset minimum correlation degree threshold as the backflow area. On top of this, after obtaining the backflow area, the backflow area can also be divided into key backflow areas and general backflow areas according to the size of the correlation degree of the backflow area, and based on the correlation degree value, the inspection intensity of the key backflow area and the general backflow area is adjusted accordingly, and more inspection resources are allocated to the key backflow area, and basic daily inspections are carried out on the general backflow area. Specifically, the higher the correlation degree value is, the more inspection resources are allocated to the key backflow area.

[0089] Inspection resources include the number of inspection and maintenance personnel, inspection frequency, and inspection depth. Basic daily inspections can be arranged by arranging two or more inspection and maintenance personnel, with an inspection frequency of once every three hours and an inspection within ten minutes, without the use of professional tools and relying only on the experience of the inspection and maintenance personnel. Allocating more inspection resources to key backflow areas can arrange more inspection and maintenance personnel, increase the inspection frequency, and use professional tools to conduct in-depth inspections of the pipeline network in key backflow areas by detecting the working status of pipeline valves, the specific liquid level of the pipeline network, the water flow rate, etc.

[0090] By dividing the backflow area into key backflow areas and general backflow areas, and arranging different degrees of pipeline inspection intensity and depth according to the degree of correlation, we can further strengthen the inspection and protection measures for the backflow source and avoid the backflow of river and sea water.

[0091] The backflow index acquisition unit is used to respectively acquire the backflow indexes of all possible backflow sources in the backflow area.

[0092] Each possible backflow source corresponds to a backflow index. Preferably, the backflow index ;

[0093] in, Indicates the number of factors that cause backflow at the backflow source. represents a natural constant, Indicates The value of the factor that causes backflow at the source of backflow. Indicates The adjustment factor of the factor value that causes backflow at the source of backflow, Indicates The correction value of the weight value of the factor causing backflow at the source of backflow can be set by the technician based on experience.

[0094] Specifically, the factors that cause backflow at the source of backflow include but are not limited to the pipe network density of the source of backflow, the historical backflow frequency, the age of the pipe network, the degree of blockage of the pipe network failure, whether the water from the existing drainage pipes is collected through the interception well, and the height of the terrain.

[0095] For different factor values ​​that cause backflow at the backflow source, the values ​​can be adjusted and set based on experience. That is, the factor values ​​that cause backflow at the backflow source can be assigned by the value assignment method to obtain the factor values ​​that cause backflow at the backflow source.

[0096] The backflow source acquisition unit is used to acquire the key backflow source according to the backflow index; the pipe network liquid level analysis unit is used to analyze the pipe network liquid level corresponding to the analysis object according to the key backflow source, so as to monitor the pipe network liquid level.

[0097] The backflow index is calculated , taking into account multiple factors that cause backflow at the source of backflow, the liquid level in the pipeline network at the key backflow source can be monitored more deeply and carefully according to the backflow index, which will further facilitate the inspection and operation and maintenance personnel to investigate the source of backflow and avoid the backflow of river and sea water in the pipeline network.

[0098] The present invention also provides a pipeline network liquid level analysis method based on tidal data, such as Figure 1 As shown, it includes the following steps:

[0099] S1, obtaining the liquid level data of the analysis object.

[0100] S2, obtaining target tide level data associated with the analysis object.

[0101] S3, calculating the correlation degree between the analysis object liquid level and the target tide level according to the liquid level data and the target tide level data.

[0102] S4, analyzing the pipe network liquid level corresponding to the analysis object according to the correlation degree, and realizing monitoring of the pipe network liquid level.

[0103] Specifically, the time points and frequencies of the liquid level data of the analysis object and the target tide level data should be ensured to be the same or similar, and the data frequency should be no less than once every 15 minutes. The data storage format of the two can be xls or xlsx format.

[0104] The correlation degree between the analysis object liquid level and the target tide level can be calculated by writing a correlation degree analysis application and inputting the liquid level data and the target tide level data into the correlation degree analysis application.

[0105] For the preprocessing of the data table, the input requirement of the association degree analysis application can be a data table with a fixed format. The data table for making input program operations can be processed as follows: the first line in a single data table is the name of the level gauge, the first column should be the target tide data, and the remaining columns are the analysis object data. If a basin analysis object wants to compare multiple target tides, it should be divided into different sub-tables for multiple analyses. The analysis object data in the same table should be the same basin object with a topological relationship. At the same time, since the level gauge data inevitably has data loss or obvious data errors, the loss or error of a small amount of data can be supplemented by interpolation. If there is a large amount of data loss or errors, the analysis value may be small, and manual judgment will be required when the subsequent program operation results appear. To ensure that the program can still run normally, this part of the data in the data table can be kept blank or marked with special symbols.

[0106] For the writing of association degree analysis application, python3.1+pandas can be used to write script programs, jupyter is used as the editor, and the running computer configuration is Intel(R) Core(TM) i5-8400 CPU @ 2.80GHz, 8.00GBRAM, and the operating system is Windows 11 Home Chinese Edition 64-bit operating system.

[0107] For the output format of data, the data output result is a data table, such as Figure 4 As shown in the figure, there are two level gauge numbers in the "Association Rules" column of rows 0 and 1. The first number is called the front set item, and the second number is called the back set item. The data in the "Support" column is the support of the front set item, the data in the "Confidence" column is the probability of the back set appearing when the front set appears, and the data in the "Lift" column is the degree to which the front set increases the probability of the back set appearing.

[0108] Among the three values ​​in the output result table, support is the most important data. The higher the support data, the stronger the correlation between the analysis object and the tide level. According to experience, when support < 0.3, the correlation is weak and can be regarded as unrelated. When 0.3 < support < 0.4, the correlation strength is medium and needs attention. When 0.4 < support < 0.5, the correlation strength is strong and needs to be actively investigated. When support > 0.5, it is extremely strong and has caused obvious fluctuations in water quality and quantity. The confidence and lift values ​​are used to assist the support for more accurate analysis and judgment.

[0109] by Figure 4Taking the data table shown as an example, the support and lift values ​​of rows 0 and 1 are the same, but the two level gauges are far apart. Since the confidence of row 0 is higher, the source of backflow may be closer to the level gauge with the number of the previous set item in row 0. After determining that the source of backflow may be closer to a specific level gauge, it is also possible to combine the reliability of the level gauge data quality revealed by the manual inspection problem to judge, and at the same time combine the specific pipe network data to analyze the possible path and source of the actual backflow.

[0110] Based on the pipe network liquid level analysis method, for Niuduwan Creek in the Xilang system, after analyzing the Xilang system liquid level meter in July 2022, it was found that the correlation between the Huadi River West Bank (XLYW10018) and the North Bank Sewage Interception Pipe Level Meter (XLYW10019) and the Huadi River Water Level was high, and the support degree reached 0.45, as shown in the following table:

[0111] Location Association Rules Support Confidence Lift 31 Huadi River West Bank Sewage Interception Pipe ['XLYW10019'] → ['XLYW10018'] 0.45 0.969 2.025 30 Huadihe North Bank Sewage Interception Pipe ['XLYW10018'] → ['XLYW10019'] 0.45 0.941 2.025

[0112] like Figure 5 As shown in the figure, further manual verification after graphic superposition also shows that the trend of the level gauge curve is highly similar to that of the tidal curve. Confidence indicates the probability of another thing occurring when one thing occurs, that is, conditional probability. , and further analyze the confidence data, ['XLYW10019']→['XLYW10018']>['XLYW10018']→['XLYW10019'], the fluctuation of the XLYW10019 level gauge is more affected by the XLYW10018 level gauge, and the actual backflow source may be more inclined to the direction of XLYW10018. Based on the above information, the investigation should be carried out in the Niuduwan River upstream of the XLYW10018 level gauge.

[0113] Based on the above information, the survey should be conducted in the Niuduwan River. After conducting targeted surveys in the suspected areas, a total of 4 backflow points were found in about a week, during which about 3 survey personnel were dispatched, and the results involved an external water volume of 10,200 tons / day.

[0114] In summary, by acquiring the liquid level data of the analysis object and the target tide level data associated with the analysis object, calculating the degree of correlation between the liquid level of the analysis object and the target tide level, and then analyzing the pipe network liquid level corresponding to the analysis object according to the degree of correlation, the pipe network liquid level can be monitored, and the influence of tides on the pipe network liquid level and the situation of external water intrusion can be understood conveniently, and then effective measures can be taken to reduce the blocking factors affecting the sewage pipe network and the combined pipe network, improve the water dynamics of the pipe network, improve the patency of the pipe network, and achieve the goal of lowering the water level of the overall pipe network.

[0115] As a preferred technical solution, in step S3, as Figure 2 As shown, the specific method for calculating the correlation degree between the analysis object liquid level and the target tidal level according to the liquid level data and the target tidal level data includes the following steps:

[0116] S31, calculating the support, confidence and lift between the analysis object liquid level and the target tide level according to the liquid level data and the target tide level data.

[0117] S32, calculating the association degree according to the support degree, the confidence degree and the improvement degree.

[0118] The degree of association is based on the formula Calculated.

[0119] in, Indicates the degree of association, Express support, Indicates confidence, Indicates the degree of improvement, represents a natural constant, , , They represent adjustment coefficients corresponding to the support, the confidence, and the lift, respectively, and can be set by technicians based on experience. , , They can be set to 0.62, 0.25, and 0.13 respectively.

[0120] Through the correlation degree formula The support, confidence and lift calculated based on the Apriori algorithm can be combined. Through the correlation, the inspection and maintenance personnel of the drainage company can clearly know which liquid level gauge in the target area is closer to the source of backflow, and then strengthen the protection measures for the source of backflow in a targeted manner, so as to prevent external water from entering the sewage network, contribute to improving the quality and efficiency of the sewage network, and timely and accurately check and clean the sewage network at the source of backflow, reduce the blocking factor of sewage and combined pipe networks, improve water dynamics, and achieve the goal of lowering the water level of the overall pipe network.

[0121] As a preferred technical solution, in step S4, Figure 3 As shown, according to the correlation degree, the pipe network liquid level corresponding to the analysis object is analyzed, and the specific method for monitoring the pipe network liquid level includes the following steps:

[0122] S41, determining a backflow area according to the correlation degree and target area information corresponding to the analysis object.

[0123] S42, obtaining backflow indexes of all possible backflow sources in the backflow area.

[0124] S43, obtaining a key backflow source according to the backflow index. By setting a backflow index threshold, a backflow source whose backflow index is greater than the backflow index threshold can be used as a key backflow source.

[0125] S44, analyzing the pipe network liquid level corresponding to the analysis object according to the key backflow source, and realizing monitoring of the pipe network liquid level.

[0126] Specifically, the backflow index .in, Indicates the number of factors that cause backflow at the backflow source. represents a natural constant, Indicates The value of the factor that causes backflow at the source of backflow. Indicates The adjustment factor of the factor value that causes backflow at the source of backflow, Indicates The correction value of the weight value of the factor that causes backflow at the source of backflow, Indicates the degree of association.

[0127] The factors causing backflow at the source of backflow include, but are not limited to, the density of the pipe network at the source of backflow, the historical frequency of backflow, the age of the pipe network, the degree of blockage of the pipe network failure, whether the water from the existing drainage pipe is collected through the interception well, and the height of the terrain.

[0128] The density of the pipe network can be calculated based on the length of the pipe network within the preset radius of the backflow source. The larger the pipe network density, the larger the corresponding factor value; the historical backflow frequency can be obtained by calculating the average annual backflow times of the backflow source in a preset historical time period, such as ten years. The larger the historical backflow frequency, the larger the corresponding factor value; the age of the pipe network, that is, the time the pipe network has been put into use, the greater the possibility of fault blockage, and the larger the corresponding factor value; the degree of pipe network fault blockage can be obtained by comprehensively calculating the degree of pipe network fault blockage found in historical inspections. The degree of pipe network fault blockage can generally be divided into several levels: none, low, medium, high, and severe. Different levels can be assigned different values. The higher the degree of pipe network fault blockage, the larger the corresponding factor value; as to whether the water from the existing drainage pipe is collected through the interception well, if the existing drainage pipe is collected through the interception well, the corresponding factor value can be set to 1, otherwise it is 0; corresponding to the height of the terrain, the lower the terrain, the larger the corresponding factor value.

[0129] Preferably, after obtaining the backflow area, the backflow area is divided into key backflow area and general backflow area according to the degree of correlation of the backflow area. For the key backflow sources in the key backflow area, they are listed as priority inspection backflow sources and as many inspection resources as possible are allocated.

[0130] In addition, through the backflow index formula It can be seen that the backflow index is proportional to the degree of association and the factor value. By setting the backflow index threshold, the backflow source with a backflow index greater than the backflow index threshold can be used as the key backflow source, and the backflow source with the largest backflow index can be used as the optimal patrol backflow source and patrol resources can be allocated to the maximum extent. In this way, the pipe network points that are most likely to have backflow problems can be inspected to the greatest extent possible to check the backflow risks, so that front-line personnel can accurately and efficiently handle sewage pipe network problems and strengthen the inspection and cleaning of key backflow sources in key backflow areas.

[0131] The present invention also provides a pipeline network liquid level analysis device based on tidal data, which includes: a controller; a memory storing executable instructions; wherein the executable instructions can be run on the controller and implement the pipeline network liquid level analysis method based on tidal data.

[0132] In summary, the present invention provides a pipeline network liquid level analysis system, method and device based on tidal data, which has the following beneficial effects:

[0133] 1. By acquiring the liquid level data of the analysis object and the target tide level data associated with the analysis object, calculating the correlation degree between the liquid level of the analysis object and the target tide level, and then analyzing the pipe network liquid level corresponding to the analysis object according to the correlation degree, the pipe network liquid level can be monitored, and the influence of tide on the pipe network liquid level can be understood conveniently.

[0134] 2. The present invention can collect effective liquid level data of the analysis object in the target area and the publicly available tidal data close to the analysis object according to the different deployment conditions of existing urban drainage equipment and facilities. By deeply mining the existing data and using information technology, the correlation between tidal data and the liquid level of the pipe network can be intelligently obtained. Without increasing additional hardware costs, the purpose of improving the quality and efficiency of daily pipe network operation and maintenance and management can be achieved, saving a lot of manpower and material resources for the operation and maintenance management of the drainage company.

[0135] 3. By determining the backflow area, obtaining the backflow index of all possible backflow sources in the backflow area, and obtaining the key backflow source according to the backflow index, the liquid level of the pipe network corresponding to the analysis object can be analyzed according to the key backflow source, and the key backflow point can be found, so as to strengthen the protection measures for the key backflow point, thereby preventing external water from entering the sewage pipe network and contributing to improving the quality and efficiency of the sewage pipe network.

[0136] 4. By obtaining the backflow index of all possible backflow sources in the backflow area and obtaining the key backflow sources based on the backflow index, the sewage pipe network in the tidal zone can be analyzed, investigated and cleaned up in a targeted manner, so that front-line personnel can accurately and efficiently deal with sewage pipe network problems and strengthen the investigation and cleaning of key backflow sources, so as to reduce the blocking factor of sewage and combined pipe networks, improve water dynamics, and achieve the goal of lowering the water level of the overall pipe network.

[0137] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0138] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A pipeline network liquid level analysis system based on tidal data, characterized in that: The pipeline network liquid level analysis system based on tidal data includes: A liquid level data acquisition module, used to acquire liquid level data of the analysis object; A tide data acquisition module, used to acquire target tide data associated with the analysis object; A calculation module, used for calculating the correlation degree between the analysis object liquid level and the target tidal level according to the liquid level data and the target tidal level data; An analysis module, used to analyze the pipe network liquid level corresponding to the analysis object according to the correlation degree, so as to monitor the pipe network liquid level; The calculation module comprises: A first calculation unit, configured to calculate the support, confidence and lift between the analysis object liquid level and the target tidal level according to the liquid level data and the target tidal level data; A second calculation unit, used for calculating the association degree according to the support degree, the confidence degree and the lift degree; The degree of association is based on the formula calculated; Wherein, Relation Degree represents the degree of association, Support represents the support, Confidence represents the confidence, Lift represents the lift, e represents the natural constant, α, β, and γ represent the adjustment coefficients corresponding to the support, the confidence, and the lift, respectively; The analysis module comprises: A backflow area determination unit, used to determine the backflow area according to the correlation degree and the target area information corresponding to the analysis object; A backflow index acquisition unit, used to acquire the backflow indexes of all possible backflow sources in the backflow area; A backflow source acquisition unit, used for acquiring a key backflow source according to the backflow index; A pipe network liquid level analysis unit, used to analyze the pipe network liquid level corresponding to the analysis object according to the key backflow source, so as to monitor the pipe network liquid level; The backflow index Among them, n represents the number of factors that cause backflow at the source of backflow, e represents a natural constant, and factor i represents the value of the factor causing backflow at the i-th backflow source, γ i represents the adjustment factor of the factor value causing backflow at the i-th backflow source, c i Indicates the correction value of the weight value of the factor causing backflow at the i-th backflow source; The backflow area determination unit compares the correlation degree with a preset minimum correlation degree threshold, and regards the pipe network within a preset radius with the target area liquid level meter as the backflow area, whose correlation degree is greater than the preset minimum correlation degree threshold; after obtaining the backflow area, the backflow area is divided into key backflow areas and general backflow areas according to the correlation degree of the backflow area, and based on the correlation degree value, the inspection intensity of the key backflow areas and the general backflow areas is adjusted accordingly, more inspection resources are allocated to the key backflow areas, and basic daily inspections are carried out on the general backflow areas.

2. A method for analyzing the liquid level of a pipe network based on tidal data, applied to the pipe network liquid level analysis system based on tidal data as claimed in claim 1, characterized in that: The pipeline network liquid level analysis method based on tidal data comprises the following steps: Acquire liquid level data of the analysis object; Acquiring target tide data associated with the analysis object; Calculating the correlation between the analysis object liquid level and the target tidal level according to the liquid level data and the target tidal level data; Analyzing the pipe network liquid level corresponding to the analysis object according to the correlation degree, and realizing monitoring of the pipe network liquid level; The specific method for calculating the correlation degree between the analysis object liquid level and the target tidal level according to the liquid level data and the target tidal level data comprises the following steps: Calculate the support, confidence and lift between the analysis object liquid level and the target tidal level according to the liquid level data and the target tidal level data; Calculating the degree of association according to the support, the confidence, and the lift; The degree of association is based on the formula calculated; Wherein, Relation Degree represents the degree of association, Support represents the support, Confidence represents the confidence, Lift represents the lift, e represents the natural constant, α, β, and γ represent the adjustment coefficients corresponding to the support, the confidence, and the lift, respectively; According to the correlation degree, analyzing the pipe network liquid level corresponding to the analysis object, and realizing the specific method of monitoring the pipe network liquid level comprises the following steps: Determine the backflow area according to the correlation degree and the target area information corresponding to the analysis object; Obtain the backflow index of all possible backflow sources in the backflow area; Obtaining key backflow sources according to the backflow index; Analyze the pipe network liquid level corresponding to the analysis object according to the key backflow source, and realize monitoring of the pipe network liquid level; The backflow index Among them, n represents the number of factors that cause backflow at the source of backflow, e represents a natural constant, and factor i represents the value of the factor causing backflow at the i-th backflow source, γ i represents the adjustment factor of the factor value causing backflow at the i-th backflow source, c i It represents the correction value of the weight value of the factor causing backflow at the i-th backflow source, and Relation Degree represents the degree of association; By comparing the degree of correlation with a preset minimum correlation degree threshold, the pipe network within a preset radius with the target area liquid level meter as the center and whose correlation degree is greater than the preset minimum correlation degree threshold is taken as the backflow area; after obtaining the backflow area, the backflow area is divided into key backflow areas and general backflow areas according to the degree of correlation of the backflow area, and based on the correlation degree value, the inspection intensity of the key backflow areas and the general backflow areas is adjusted accordingly, more inspection resources are allocated to the key backflow areas, and basic daily inspections are carried out on the general backflow areas.

3. A pipe network liquid level analysis device based on tidal data, characterized in that: The pipeline network liquid level analysis device based on tidal data includes: Controller; A memory storing executable instructions; The executable instructions can be run on the controller and implement the pipeline network liquid level analysis method based on tidal data as described in claim 2.

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