CN115660160A - Intelligent optimization system and method for sewage pipe network drainage - Google Patents
Intelligent optimization system and method for sewage pipe network drainage Download PDFInfo
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Abstract
The invention relates to the field of sewage pipe networks, in particular to an intelligent optimization system and method for sewage pipe network drainage a ，t b ) In each corresponding time interval, the household garbage accumulation amount and the natural garbage accumulation amount generated in each time interval at different wind speeds are predicted to be (t) in the area to be detected a ，t b ) And (4) the garbage accumulation amount in the time period, and judging the influence of the prediction result on sewage drainage. The invention is based on analysisFitting curves of the domestic garbage and the natural garbage generated in the T time intervals are obtained (T) a ，t b ) The relation between the garbage accumulation amount and sewage drainage in the time period comprehensively considers the drainage rate required to be met by the drainage rate and the rainfall amount under the influence of the garbage accumulation amount, and predicts the pipe network blockage situation in the future time.
Description
Technical Field
The invention relates to the field of sewage pipe networks, in particular to an intelligent optimization system and method for sewage pipe network drainage.
Background
The sewage pipe network is an important way for collecting and draining sewage in a city or an area, sewage is concentrated to the pipelines of the sewage treatment plant through the sewage pipe network, the formed net structure is the sewage pipe network, and when the sewage is collected and drained through the sewage pipe network, because the sewage contains a large amount of domestic garbage and natural garbage, and the domestic garbage and the natural garbage can not be intercepted in time when the sewage is concentrated and drained through the sewage pipe network, the internal blockage of the sewage pipe can be seriously caused, thereby influencing the sewage treatment work.
Disclosure of Invention
The invention aims to provide an intelligent optimization system and method for sewage pipe network drainage, which aim to solve the problems in the background art.
In order to solve the technical problems, the invention provides the following technical scheme:
an intelligent optimization method for sewage pipe network drainage is characterized by comprising the following steps:
s1, acquiring a household garbage accumulation amount, a natural garbage accumulation amount and a wind speed grade corresponding to a jth time interval in an ith time period of an area to be monitored, taking the household garbage accumulation amount, the natural garbage accumulation amount and the wind speed grade as an array, and uniformly dividing each time period into n time intervals;
s2, screening each array corresponding to the same wind speed grade in the area to be tested through a database, inputting each array corresponding to the same wind speed grade into a set, and analyzing the garbage accumulation amount generated in different time intervals in the area to be tested under the same wind speed grade by combining the screened data;
s3, analyzing the subsequent time period (t) based on the current time a ，t b ) In each corresponding time interval, the accumulation amount of the household garbage and the natural garbage generated in each time interval at different wind speeds are used for predicting that the area to be detected is (t) a ，t b ) The garbage accumulation amount in the time period and the influence of the prediction result on sewage drainage are judged;
s4, analyzing the relation between rainfall and sewage drainage rate by combining historical data;
s5, predicting the relation between the sewage drainage rate corresponding to the garbage accumulation amount and the sewage drainage rate corresponding to the rainfall amount,
when the sewage drainage rate corresponding to the garbage accumulation amount is less than or equal to the sewage drainage rate required to be met by the rainfall amount, early warning is sent to a sewage pipeline department, and when the sewage drainage rate corresponding to the garbage accumulation amount is greater than the sewage drainage rate required to be met by the rainfall amount, sewage is normally drained without sending early warning prompts.
Further, the method for obtaining the garbage accumulation amount generated in different time intervals in the region to be measured under the same wind speed level in the step S2 includes the following steps:
s2.1, obtaining each array in the corresponding set when the wind speed is F, respectively obtaining the time interval, the household garbage accumulation amount and the natural garbage accumulation amount corresponding to each array, constructing a first data pair according to the time interval and the household garbage accumulation amount in the same array, constructing a second data pair according to the time interval and the natural garbage accumulation amount in the same array,
recording the accumulation amount of the domestic garbage generated in the Tth time interval when the wind speed is F as TS, recording the accumulation amount of the natural garbage generated in the Tth time interval when the wind speed is F as TZ, wherein the corresponding first data pair is (T, TS) and the second data pair is (T, TZ);
s2.2, constructing a first plane rectangular coordinate system by taking o1 as an origin, a time interval as an x1 axis and household garbage accumulation as a y1 axis, and respectively marking coordinate points corresponding to each first data pair in the first plane rectangular coordinate system;
s2.3, performing curve fitting on coordinate points marked in the first plane rectangular coordinate system by using a first relation function model in the database, taking a fitting curve with the minimum sum of distances between the fitting curve and each marked coordinate point in the first plane rectangular coordinate system as an optimal fitting curve, and taking a function GS corresponding to the optimal fitting result F (x 1) recording the relation between the accumulation amount of the household garbage and the time interval when the wind speed is F;
the first relation function model in the database is y 1 ＝x 1 + sinx1+ a1, a1 is the first coefficient.
S2.4, constructing a second plane rectangular coordinate system by taking o2 as an origin, a time interval as an x2 axis and a natural garbage accumulation amount as a y2 axis, and respectively marking coordinate points corresponding to each second data pair in the second plane rectangular coordinate system;
s2.5, performing curve fitting on coordinate points marked in the second rectangular planar coordinate system by using a second relation function model in the database, taking a fitting curve with the minimum sum of distances between the fitting curve and each marked coordinate point in the second rectangular planar coordinate system as an optimal fitting curve, and taking a function GZ corresponding to the optimal fitting result F (x 2) recording the relation between the natural garbage accumulation amount and the time interval when the wind speed is F;
the second relation function model in the database is y 2 ＝x 2 +cosx 2 + b1, b1 is the second coefficient.
The method analyzes each array corresponding to the same wind speed grade by combining historical data, analyzes the household garbage accumulation amount and the natural garbage accumulation amount generated in T time intervals by fitting a curve, and provides data reference for the subsequent analysis of the household garbage accumulation amount and the natural garbage accumulation amount corresponding to different wind speeds.
Further, in the step S3, a subsequent time period (t) based on the current time is obtained a ，t b ) The method for accumulating the domestic garbage and the natural garbage generated in each time interval at different wind speeds in each corresponding time interval comprises the following steps of:
s3.1, subsequent time period (t) based on current time a ，t b ) In each corresponding time interval, recording the average wind speed of the weather forecast in the r-th time interval as F1 (tr);
s3.2, obtaining a relation function GS between the accumulation amount of the household garbage and the time interval when the wind speed is F according to S2.4 and S2.5 F (x 1) and a relation function GZ between the accumulation amount of the domestic garbage and the time interval when the wind speed is F F (x2)，
When wind speed is highWhen the average value is F1 (tr), according to the formula G F1(tr) (tr)＝GS F1(tr) (tr)+GZ F1(tr) (tr)
Where tr denotes a subsequent time period (t) based on the current time a ，t b ) The time interval serial number of the r-th time interval in each corresponding time interval in the corresponding time period;
G F1(tr) (tr) represents a subsequent time period (t) based on the current time a ，t b ) In each corresponding time interval, the garbage accumulation amount is generated when the average value of the wind speed is F1 (tr) in the r-th time interval;
GS F1(tr) (tr) represents a subsequent time period (t) based on the current time a ，t b ) In each corresponding time interval, the storage amount of the domestic garbage generated when the average value of the wind speed is F1 (tr) in the r-th time interval;
GZ F1(tr) (tr) represents a subsequent time period (t) based on the current time a ，t b ) And in each corresponding time interval, the natural garbage accumulation amount is generated when the average wind speed value is F1 (tr) in the r-th time interval.
Inventive combination (t) a ，t b ) In each time interval corresponding to the time period, the relation between the household garbage accumulation amount and the time interval is obtained when the wind speed average value is F1 of the weather forecast wind speed average value F1 in the r-th time interval.
Further, the region to be detected is predicted to be (t) in S3 a ，t b ) The garbage accumulation amount in the time period and the influence of the prediction result on sewage drainage are judged; the method comprises the following steps:
s3.1, obtaining garbage accumulation amount and corresponding sewage drainage rate corresponding to each time interval in the database, and constructing each third data pair, wherein the first value in each third data pair represents the garbage accumulation amount corresponding to the corresponding time interval, and the second value represents the sewage drainage rate corresponding to the corresponding time interval;
s3.2, constructing a third rectangular coordinate system by taking o3 as an origin, the garbage accumulation amount in a time interval as an x3 axis and the sewage drainage rate as a y3 axis, and respectively marking coordinate points corresponding to each third data pair in the third rectangular coordinate system;
s3.3, performing curve fitting on coordinate points marked in the third plane rectangular coordinate system by using a third relation function model in the database, taking a fitting curve with the minimum sum of distances between the fitting curve and each marked coordinate point in the third plane rectangular coordinate system as an optimal fitting curve, and recording a function VB (x 3) corresponding to the optimal fitting result as the relation between the garbage accumulation amount corresponding to a time interval and the sewage drainage rate;
s3.4, acquiring the region to be detected to be (t) a ，t b ) Amount of garbage accumulated in time zone W ab Combining with VB (x 3) to obtain (t) a ，t b ) Prediction result W of garbage accumulation amount in time zone ab Sewage drainage rate B, B = VB (W) at the corresponding ab /e)。
The third relation function model in the database is y 3 ＝c1*x 3 + c2, c1 is the third coefficient and c2 is the fourth coefficient.
The invention obtains (t) a ，t b ) Prediction result W of garbage accumulation amount in time zone ab And analyzing the relation between the corresponding sewage drainage rates by combining the prediction results, analyzing a function corresponding to the best fitting result through the fitting curve, and providing data reference for subsequently judging the relation between the sewage drainage rate B and the sewage drainage rate A.
Further, the method for analyzing the relationship between the rainfall capacity and the sewage drainage rate in combination with the historical data in S4 comprises the following steps:
s4.1, obtaining road surface area information S of a region to be monitored;
s4.2, obtaining time period (t) a ，t b ) Rainfall Q of medium weather forecast 1 ；
S4.3, according to formula J 1 = Q1 × S total rainfall of the area to be monitored, wherein J 1 Represents (t) a ，t b ) The total rainfall of the area to be monitored in the time period;
s4.4, searching through a databasePolling precipitation amount is J 1 The sewage drainage rate is A.
The invention obtains the time period (t) a ，t b ) Rainfall Q of medium weather forecast 1 Information S of road surface area of region to be detected, company J 1 And acquiring the total rainfall of the area to be monitored by using the (= Q1S), and inquiring the relation between the sewage drainage rates required to be met by the corresponding rainfall through a database, thereby providing data reference for influencing the sewage drainage rate with the subsequent garbage accumulation.
Further, the method for predicting the relationship between the sewage drainage rate corresponding to the garbage accumulation amount and the sewage drainage rate corresponding to the rainfall amount in S5 includes the following steps:
s5.1, obtaining (t) a ，t b ) Prediction result W of garbage accumulation amount in time zone ab The corresponding sewage drainage rate B;
s5.2, obtaining (t) a ，t b ) The time period corresponds to the sewage drainage rate A required by rainfall;
s5.3, comparison (t) a ，t b ) Prediction result W of garbage accumulation amount in time zone ab Sewage drainage rate at corresponding B and t a ，t b ) The time period corresponds to the sewage drainage rate A required by rainfall,
when the sewage drainage rate A is less than or equal to the sewage drainage rate B, no early warning is required to be sent out; when the sewage drainage rate A is greater than the sewage drainage rate B, a pre-warning intention is sent to a sewage pipeline department (t) a ，t b ) A blocked sewage network may occur during the period.
According to the invention, the sewage pipe network blockage condition is judged by comparing the relation between the sewage drainage rate A and the sewage drainage rate B, and corresponding early warning prompt is carried out according to the sewage pipe network blockage condition.
The intelligent optimization system for sewage pipe network drainage is characterized by comprising the following modules:
monitoring area divides module: the monitoring region dividing module acquires the household garbage accumulation amount, the natural garbage accumulation amount and the wind speed grade corresponding to the jth time interval in the ith time period of the region to be monitored as an array, and each time period is uniformly divided into n time intervals;
a monitoring data acquisition module: the monitoring data acquisition module screens each array corresponding to the same wind speed grade in the region to be detected through a database, records each array corresponding to the same wind speed grade into a set, and analyzes the garbage accumulation amount generated in different time intervals in the region to be detected under the same wind speed grade by combining the screened data;
garbage accumulation amount information acquisition module: the garbage accumulation amount information obtaining module analyzes a subsequent time period (t) based on the current time a ，t b ) In each corresponding time interval, the domestic garbage accumulation amount and the natural garbage accumulation amount generated in each time interval at different wind speeds are used for predicting that the area to be detected is in (t) a ，t b ) The garbage accumulation amount in the time period and the influence of the prediction result on sewage drainage are judged;
an environmental information influence analysis module; the environmental information influence analysis module is used for analyzing the relation between rainfall and sewage drainage rate by combining historical data;
the integrated environment information management module: the comprehensive information management module predicts the relation between the sewage drainage rate corresponding to the garbage accumulation amount and the sewage drainage rate corresponding to the rainfall amount,
when the sewage drainage rate corresponding to the garbage accumulation amount is less than or equal to the sewage drainage rate required to be met by the rainfall amount, early warning is sent to a sewage pipeline department, and when the sewage drainage rate corresponding to the garbage accumulation amount is greater than the sewage drainage rate required to be met by the rainfall amount, sewage is normally drained without sending early warning prompts.
The method obtains the result in (T) by analyzing the fitting curve of the domestic garbage and the natural garbage generated in T time intervals a ，t b ) The influence of the garbage accumulation amount and the sewage drainage rate generated in the time period is obtained by (t) a ，t b ) The rainfall and the drainage rate value required to be met in the weather forecast corresponding to the time period are comprehensively considered, and the drainage rate required to be met under the influence of the garbage accumulation are comprehensively consideredAnd the water rate is used for predicting the pipe network blockage situation in the future time and giving out early warning, so that the blockage rate of the sewage pipe network is reduced.
Drawings
FIG. 1 is a schematic flow chart of an intelligent optimization method for sewage pipe network drainage according to the present invention;
fig. 2 is a schematic block diagram of an intelligent optimization system for sewage pipe network drainage.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1-2, in the embodiment of the present invention: an intelligent optimization method for sewage pipe network drainage comprises the following steps:
s1, acquiring a household garbage accumulation amount, a natural garbage accumulation amount and a wind speed grade corresponding to a jth time interval in an ith time period of an area to be monitored, taking the household garbage accumulation amount, the natural garbage accumulation amount and the wind speed grade as an array, and uniformly dividing each time period into n time intervals;
s2, screening each array corresponding to the same wind speed grade in the area to be tested through a database, inputting each array corresponding to the same wind speed grade into a set, and analyzing the garbage accumulation amount generated in different time intervals in the area to be tested under the same wind speed grade by combining the screened data;
the method for obtaining the garbage accumulation amount generated in different time intervals in the region to be detected under the same wind speed level in the S2 comprises the following steps:
s2.1, obtaining each array in the corresponding set when the wind speed is F, respectively obtaining the time interval, the household garbage accumulation amount and the natural garbage accumulation amount corresponding to each array, constructing a first data pair according to the time interval and the household garbage accumulation amount in the same array, constructing a second data pair according to the time interval and the natural garbage accumulation amount in the same array,
recording the accumulation amount of the household garbage generated in the Tth time interval when the wind speed is F as TS, recording the accumulation amount of the natural garbage generated in the Tth time interval when the wind speed is F as TZ, and correspondingly, taking the first data pair as (T, TS) and the second data pair as (T, TZ);
s2.2, constructing a first plane rectangular coordinate system by taking o1 as an origin, a time interval as an x1 axis and the household garbage accumulation amount as a y1 axis, and respectively marking coordinate points corresponding to each first data pair in the first plane rectangular coordinate system;
s2.3, performing curve fitting on coordinate points marked in the first plane rectangular coordinate system by using a first relation function model in the database, taking a fitting curve with the minimum sum of distances between the fitting curve and each marked coordinate point in the first plane rectangular coordinate system as an optimal fitting curve, and taking a function GS corresponding to the optimal fitting result F (x 1) recording the relation between the accumulation amount of the household garbage and the time interval when the wind speed is F;
the first relational function model in the database is y 1 ＝x 1 + sinx1+ a1, a1 is the first coefficient.
S2.4, constructing a second plane rectangular coordinate system by taking o2 as an origin, a time interval as an x2 axis and a natural garbage accumulation amount as a y2 axis, and respectively marking coordinate points corresponding to each second data pair in the second plane rectangular coordinate system;
s2.5, performing curve fitting on coordinate points marked in the second rectangular planar coordinate system by using a second relation function model in the database, taking a fitting curve with the minimum sum of distances between the fitting curve and each marked coordinate point in the second rectangular planar coordinate system as an optimal fitting curve, and taking a function GZ corresponding to the optimal fitting result F (x 2) recording the relation between the natural garbage accumulation amount and the time interval when the wind speed is F;
the second relational function model in the database is y 2 ＝x 2 +cosx 2 + b1, b1 is the second coefficient.
S3, analyzing the subsequent time period (t) based on the current time a ，t b ) Corresponding toIn each time interval, the accumulation amount of the household garbage and the natural garbage generated in each time interval at different wind speeds are used for predicting that the area to be detected is in (t) a ，t b ) The garbage accumulation amount in the time period and the influence of the prediction result on sewage drainage are judged;
in the step S3, a subsequent time period (t) based on the current time is obtained a ，t b ) The method for accumulating the household garbage and the natural garbage generated in each time interval at different wind speeds in each corresponding time interval comprises the following steps of:
s3.1, subsequent time period (t) based on current time a ，t b ) In each corresponding time interval, recording the average wind speed of the weather forecast in the r-th time interval as F1 (tr);
s3.2, obtaining a relation function GS between the household garbage accumulation amount and the time interval when the wind speed is F according to S2.4 and S2.5 F (x 1) and a relation function GZ between the accumulation amount of the domestic garbage and the time interval when the wind speed is F F (x2)，
When the average wind speed is F1 (tr), according to the formula G F1(tr) (tr)＝GS F1(tr) (tr)+GZ F1(tr) (tr)
Where tr denotes a subsequent time period (t) based on the current time a ，t b ) The time interval sequence number of the r-th time interval in each corresponding time interval in the corresponding time period;
G F1(tr) (tr) represents a subsequent time period (t) based on the current time a ，t b ) In each corresponding time interval, the garbage accumulation amount is generated when the average value of the wind speed is F1 (tr) in the r-th time interval;
GS F1(tr) (tr) represents a subsequent time period (t) based on the current time a ，t b ) In each corresponding time interval, the storage amount of the domestic garbage generated when the average value of the wind speed is F1 (tr) in the r-th time interval;
GZ F1(tr) (tr) represents a subsequent time period (t) based on the current time a ，t b ) In each corresponding time interval, at the r-th time interval,the average wind speed is F1 (tr) and the amount of natural garbage accumulated.
Subsequent time period (t) based on current time in said S3.2 a ，t b ) In each corresponding time interval, the prediction result W is obtained according to the garbage accumulation amount generated when the average value of the wind speed is F1 in the r-th time interval ab ，
Wherein e represents a subsequent time period (t) based on the current time a ，t b ) The number of time intervals in (1).
In the present embodiment, the subsequent time period (t) based on the current time a ，t b ) In the time period (t) when the number of time intervals in (1) is 5 a ，t b ) The prediction result of the medium garbage accumulation amount is as follows:
wherein the subsequent time period (t) is based on the current time a ，t b ) The amount of the household garbage accumulated when the number of the time intervals in (1) is 5 is as follows:
the natural garbage accumulation amount is as follows:
predicting the region to be detected in (t) in S3 a ，t b ) The method for judging the garbage accumulation amount in the time period and judging the influence of the prediction result on the sewage drainage comprises the following steps of:
s3.1, obtaining garbage accumulation amount and corresponding sewage drainage rate corresponding to each time interval in the database, and constructing each third data pair, wherein the first value in each third data pair represents the garbage accumulation amount corresponding to the corresponding time interval, and the second value represents the sewage drainage rate corresponding to the corresponding time interval;
s3.2, constructing a third rectangular coordinate system by taking o3 as an origin, the garbage accumulation amount in a time interval as an x3 axis and the sewage drainage rate as a y3 axis, and respectively marking coordinate points corresponding to each third data pair in the third rectangular coordinate system;
s3.3, carrying out curve fitting on coordinate points marked in the third plane rectangular coordinate system by using a third relation function model in the database, taking a fitting curve with the minimum sum of distances of all marked coordinate points in the third plane rectangular coordinate system as an optimal fitting curve, and recording a function VB (x 3) corresponding to the optimal fitting result as the relation between the garbage accumulation amount corresponding to a time interval and the sewage drainage rate;
s3.4, acquiring the region to be detected to be (t) a ，t b ) Amount of garbage accumulated in time zone W ab Combining with VB (x 3) to obtain (t) a ，t b ) Prediction result W of garbage accumulation amount in time zone ab Sewage drainage rate B, B = VB (W) at the corresponding ab /e)。
The third relation function model in the database is y 3 ＝c1*x 3 + c2, c1 is the third coefficient and c2 is the fourth coefficient.
S4, analyzing the relation between the rainfall and the sewage drainage rate by combining historical data;
the method for analyzing the relation between the rainfall capacity and the sewage drainage rate in combination with the historical data in S4 comprises the following steps:
s4.1, obtaining road surface area information S of a region to be monitored;
s4.2, acquiring time period (t) a ，t b ) Rainfall Q of medium weather forecast 1 ；
S4.3, according to formula J 1 Obtaining the total rainfall of the area to be monitored by using the equation of Q1S, wherein J 1 Represents (t) a ，t b ) Total rainfall of the area to be monitored in a time period;
s4.4, inquiring the precipitation amount J through the database 1 The sewage drainage rate is A.
S5, predicting the relation between the sewage drainage rate corresponding to the garbage accumulation amount and the sewage drainage rate corresponding to the rainfall amount,
when the sewage drainage rate corresponding to the garbage accumulation amount is less than or equal to the sewage drainage rate required to be met by the rainfall amount, early warning is sent to a sewage pipeline department, and when the sewage drainage rate corresponding to the garbage accumulation amount is greater than the sewage drainage rate required to be met by the rainfall amount, sewage is normally drained without sending early warning prompts.
The method for predicting the relation between the sewage drainage rate corresponding to the garbage accumulation amount and the sewage drainage rate corresponding to the rainfall amount in the S5 comprises the following steps:
s5.1, obtaining (t) a ，t b ) Prediction result W of garbage accumulation amount in time zone ab The sewage drainage rate B is correspondingly set;
s5.2, obtaining (t) a ，t b ) The time period corresponds to the sewage drainage rate A required by rainfall;
s5.3, comparison (t) a ，t b ) Prediction result W of garbage accumulation amount in time zone ab Sewage drainage rate at corresponding B and t a ，t b ) The time period corresponds to the sewage drainage rate A required by rainfall,
when the sewage drainage rate A is less than or equal to the sewage drainage rate B, no early warning is required to be sent out; when the sewage drainage rate A is greater than the sewage drainage rate B, a pre-warning intention is sent to a sewage pipeline department (t) a ，t b ) A blocked sewage network may occur during the period.
The intelligent optimization system for sewage pipe network drainage is characterized by comprising the following modules:
monitoring area divides module: the monitoring region dividing module acquires the household garbage accumulation amount, the natural garbage accumulation amount and the wind speed grade corresponding to the jth time interval in the ith time period of the region to be monitored as an array, and each time period is uniformly divided into n time intervals;
a monitoring data acquisition module: the monitoring data acquisition module screens each array corresponding to the same wind speed grade in the region to be detected through a database, records each array corresponding to the same wind speed grade into a set, and analyzes the garbage accumulation amount generated in different time intervals in the region to be detected under the same wind speed grade by combining the screened data;
garbage accumulation amount information acquisition module: the garbage accumulation amount information obtaining module analyzes a subsequent time period (t) based on the current time a ，t b ) In each corresponding time interval, the domestic garbage accumulation amount and the natural garbage accumulation amount generated in each time interval at different wind speeds are used for predicting that the area to be detected is in (t) a ，t b ) The garbage accumulation amount in the time period and the influence of the prediction result on sewage drainage are judged;
an environmental information influence analysis module; the environmental information influence analysis module is used for analyzing the relation between rainfall and sewage drainage rate by combining historical data;
the comprehensive environment information management module: the comprehensive information management module predicts the relation between the sewage drainage rate corresponding to the garbage accumulation amount and the sewage drainage rate corresponding to the rainfall amount,
when the sewage drainage rate corresponding to the garbage accumulation amount is less than or equal to the sewage drainage rate required to be met by the rainfall amount, early warning is sent to a sewage pipeline department, and when the sewage drainage rate corresponding to the garbage accumulation amount is greater than the sewage drainage rate required to be met by the rainfall amount, sewage is normally drained without sending early warning prompts.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
It should be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described in the foregoing embodiments, or that equivalents may be substituted for elements thereof. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. An intelligent optimization method for sewage pipe network drainage is characterized by comprising the following steps:
s1, acquiring the household garbage accumulation amount, the natural garbage accumulation amount and the wind speed grade corresponding to the jth time interval in the ith time period of a region to be monitored, taking the household garbage accumulation amount, the natural garbage accumulation amount and the wind speed grade as an array, and uniformly dividing each time period into n time intervals;
s2, screening each array corresponding to the same wind speed grade in the area to be tested through a database, inputting each array corresponding to the same wind speed grade into a set, and analyzing the garbage accumulation amount generated in different time intervals in the area to be tested under the same wind speed grade by combining the screened data;
s3, analyzing the follow-up time based on the current timeSegment (t) a ，t b ) In each corresponding time interval, the household garbage accumulation amount and the natural garbage accumulation amount generated in each time interval at different wind speeds are predicted to be (t) in the area to be detected a ，t b ) The garbage accumulation amount in the time period and the influence of the prediction result on sewage drainage are judged;
s4, analyzing the relation between rainfall and sewage drainage rate by combining historical data;
s5, predicting the relation between the sewage drainage rate corresponding to the garbage accumulation amount and the sewage drainage rate corresponding to the rainfall amount,
when the sewage drainage rate corresponding to the garbage accumulation amount is less than or equal to the sewage drainage rate required to be met by the rainfall amount, the early warning is sent to a sewage pipeline department, and when the sewage drainage rate corresponding to the garbage accumulation amount is greater than the sewage drainage rate required to be met by the rainfall amount, the sewage is drained normally, and the early warning prompt is not sent.
2. The intelligent optimization method for sewer network drainage according to claim 1, wherein the method for obtaining the garbage accumulation amount generated in different time intervals in the region to be tested under the same wind speed level in S2 comprises the following steps:
s2.1, obtaining each array in the corresponding set when the wind speed is F, respectively obtaining the time interval, the household garbage accumulation amount and the natural garbage accumulation amount corresponding to each array, constructing a first data pair according to the time interval and the household garbage accumulation amount in the same array, constructing a second data pair according to the time interval and the natural garbage accumulation amount in the same array,
recording the accumulation amount of the domestic garbage generated in the Tth time interval when the wind speed is F as TS, recording the accumulation amount of the natural garbage generated in the Tth time interval when the wind speed is F as TZ, wherein the corresponding first data pair is (T, TS) and the second data pair is (T, TZ);
s2.2, constructing a first plane rectangular coordinate system by taking o1 as an origin, a time interval as an x1 axis and the household garbage accumulation amount as a y1 axis, and respectively marking coordinate points corresponding to each first data pair in the first plane rectangular coordinate system;
s2.3, performing curve fitting on coordinate points marked in the first plane rectangular coordinate system by using a first relation function model in the database, taking a fitting curve with the minimum sum of distances between the fitting curve and each marked coordinate point in the first plane rectangular coordinate system as a best fitting curve, and taking a function GS corresponding to the best fitting result F (x 1) recording the relation between the household garbage accumulation amount and the time interval when the wind speed is F;
the first relation function model in the database is y 1 ＝x 1 + sinx1+ a1, a1 is the first coefficient.
S2.4, constructing a second plane rectangular coordinate system by taking o2 as an origin, a time interval as an x2 axis and a natural garbage accumulation amount as a y2 axis, and respectively marking coordinate points corresponding to each second data pair in the second plane rectangular coordinate system;
s2.5, performing curve fitting on coordinate points marked in the second rectangular planar coordinate system by using a second relation function model in the database, taking a fitting curve with the minimum sum of distances between the fitting curve and each marked coordinate point in the second rectangular planar coordinate system as a best fitting curve, and taking a function GZ corresponding to the best fitting result F (x 2) recording the relation between the natural garbage accumulation amount and the time interval when the wind speed is F;
the second relation function model in the database is y 2 ＝x 2 +cosx 2 + b1, b1 are the second coefficients.
3. The intelligent optimization method for sewer network drainage according to claim 1, wherein the subsequent time period (t) based on the current time is obtained in S3 a ，t b ) The method for accumulating the domestic garbage and the natural garbage generated in each time interval at different wind speeds in each corresponding time interval comprises the following steps of:
s3.1, subsequent time period (t) based on current time a ，t b ) In each corresponding time interval, recording the average wind speed of the weather forecast in the r-th time interval as F1 (tr);
s3.2, obtaining the domestic waste at the wind speed of F according to S2.4 and S2.5Relation function GS between rubbish accumulation amount and time interval F (x 1) and a relation function GZ between the accumulation amount of the domestic garbage and the time interval when the wind speed is F F (x2)，
When the average wind speed is F1 (tr), according to the formula G F1(tr) (tr)＝GS F1(tr) (tr)+GZ F1(tr) (tr)
Where tr denotes a subsequent time period (t) based on the current time a ，t b ) The time interval serial number of the corresponding r-th time interval in each time interval in the corresponding time period;
G F1(tr) (tr) represents a subsequent time period (t) based on the current time a ，t b ) In each corresponding time interval, the garbage accumulation amount is generated when the average value of the wind speed is F1 (tr) in the r-th time interval;
GS F1(tr) (tr) represents a subsequent time period (t) based on the current time a ，t b ) In each corresponding time interval, the storage amount of the domestic garbage generated when the average value of the wind speed is F1 (tr) in the r-th time interval;
GZ F1(tr) (tr) represents a subsequent time period (t) based on the current time a ，t b ) And in each corresponding time interval, the natural garbage accumulation amount is generated when the average wind speed value is F1 (tr) in the r-th time interval.
4. The intelligent optimization method for sewer network drainage according to claim 2, characterized in that in S3.2, the subsequent time period (t) based on the current time is a ，t b ) In each corresponding time interval, the prediction result W is obtained according to the garbage accumulation amount generated when the average value of the wind speed is F1 in the r-th time interval ab ，
Where e denotes a subsequent time period (t) based on the current time a ，t b ) The number of time intervals in (1).
5. The intelligent optimization method for sewer network drainage according to claim 4, characterized in that in S3, the area to be detected is predicted to be (t) a ，t b ) The method for judging the garbage accumulation amount in the time period and the influence of the prediction result on sewage drainage comprises the following steps of:
s3.1, obtaining garbage accumulation amount and corresponding sewage drainage rate corresponding to each time interval in the database, and constructing each third data pair, wherein the first value in each third data pair represents the garbage accumulation amount corresponding to the corresponding time interval, and the second value represents the sewage drainage rate corresponding to the corresponding time interval;
s3.2, taking o3 as an origin, taking the garbage accumulation amount in a time interval as an x3 axis and taking the sewage drainage rate as a y3 axis, constructing a third plane rectangular coordinate system, and respectively marking coordinate points corresponding to each third data pair in the third plane rectangular coordinate system;
s3.3, performing curve fitting on coordinate points marked in the third rectangular coordinate system by using a third relation function model in the database, taking a fitting curve with the minimum sum of distances between the fitting curve and each marked coordinate point in the third rectangular coordinate system as a best fitting curve, and recording a function VB (x 3) corresponding to a best fitting result as a relation between garbage accumulation amount and sewage drainage rate corresponding to a time interval;
s3.4, acquiring the region to be detected to be (t) a ，t b ) Amount of garbage accumulated in time zone W ab Combining with VB (x 3) to obtain (t) a ，t b ) Prediction result W of garbage accumulation amount in time zone ab Sewage drainage rate B, B = VB (W) at the corresponding ab /e)。
The third relation function model in the database is y 3 ＝c1*x 3 + c2, c1 is the third coefficient and c2 is the fourth coefficient.
6. The intelligent optimization method for sewer pipe network drainage according to claim 5, wherein the method for analyzing the relation between rainfall capacity and sewage drainage rate in combination with historical data in S4 comprises the following steps:
s4.1, obtaining road surface area information S of a region to be monitored;
s4.2, obtaining time period (t) a ，t b ) Rainfall Q of medium weather forecast 1 ；
S4.3, according to formula J 1 Obtaining the total rainfall of the area to be monitored by using the equation of Q1S, wherein J 1 Represents (t) a ，t b ) Total rainfall of the area to be monitored in a time period;
s4.4, inquiring the precipitation amount J through the database 1 The sewage drainage rate is A.
7. The intelligent optimization method for sewer network drainage according to claim 6, wherein the method for predicting the relationship between the sewage drainage rate corresponding to garbage accumulation amount and the sewage drainage rate corresponding to rainfall amount in S5 comprises the following steps:
s5.1, obtaining (t) a ，t b ) Prediction result W of garbage accumulation amount in time zone ab The sewage drainage rate B is correspondingly set;
s5.2, obtaining (t) a ，t b ) The time period corresponds to the sewage drainage rate A required by rainfall;
s5.3, comparison (t) a ，t b ) Prediction result W of garbage accumulation amount in time zone ab Sewage drainage rate at corresponding B and t a ，t b ) The time period corresponds to the sewage drainage rate A required by rainfall,
when the sewage drainage rate A is less than or equal to the sewage drainage rate B, no early warning is required to be sent out; when the sewage discharge rate A is greater than the sewage discharge rate B, a warning is given to a sewer department (t) a ，t b ) A blocked sewer network may occur during the period of time.
8. The intelligent optimization system for sewage pipe network drainage is characterized by comprising the following modules:
monitoring area divides module: the monitoring region dividing module acquires the household garbage accumulation amount, the natural garbage accumulation amount and the wind speed grade corresponding to the jth time interval in the ith time period of the region to be monitored, and the household garbage accumulation amount, the natural garbage accumulation amount and the wind speed grade are used as an array, and each time period is uniformly divided into n time intervals;
a monitoring data acquisition module: the monitoring data acquisition module screens each array corresponding to the same wind speed grade in the area to be detected through a database, records each array corresponding to the same wind speed grade into a set, and analyzes the garbage accumulation amount generated in different time intervals in the area to be detected under the same wind speed grade by combining the screened data;
garbage accumulation amount information acquisition module: the garbage accumulation amount information acquisition module analyzes a subsequent time period (t) based on the current time a ，t b ) In each corresponding time interval, the accumulation amount of the household garbage and the natural garbage generated in each time interval at different wind speeds are used for predicting that the area to be detected is (t) a ，t b ) The garbage accumulation amount in the time period and the influence of the prediction result on sewage drainage are judged;
an environmental information influence analysis module; the environmental information influence analysis module is used for analyzing the relation between rainfall and sewage drainage rate by combining historical data;
the integrated environment information management module: the comprehensive information management module predicts the relation between the sewage drainage rate corresponding to the garbage accumulation amount and the sewage drainage rate corresponding to the rainfall amount,
when the sewage drainage rate corresponding to the garbage accumulation amount is less than or equal to the sewage drainage rate required to be met by the rainfall amount, early warning is sent to a sewage pipeline department, and when the sewage drainage rate corresponding to the garbage accumulation amount is greater than the sewage drainage rate required to be met by the rainfall amount, sewage is drained normally, and early warning prompts are not sent.
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