WO2005003471A1 - 不明水発生分布推定装置、方法、および記録媒体 - Google Patents
不明水発生分布推定装置、方法、および記録媒体 Download PDFInfo
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- WO2005003471A1 WO2005003471A1 PCT/JP2004/009437 JP2004009437W WO2005003471A1 WO 2005003471 A1 WO2005003471 A1 WO 2005003471A1 JP 2004009437 W JP2004009437 W JP 2004009437W WO 2005003471 A1 WO2005003471 A1 WO 2005003471A1
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- Prior art keywords
- unknown water
- unknown
- rainfall
- data
- occurrence distribution
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M3/00—Investigating fluid-tightness of structures
- G01M3/02—Investigating fluid-tightness of structures by using fluid or vacuum
- G01M3/26—Investigating fluid-tightness of structures by using fluid or vacuum by measuring rate of loss or gain of fluid, e.g. by pressure-responsive devices, by flow detectors
- G01M3/28—Investigating fluid-tightness of structures by using fluid or vacuum by measuring rate of loss or gain of fluid, e.g. by pressure-responsive devices, by flow detectors for pipes, cables or tubes; for pipe joints or seals; for valves ; for welds
- G01M3/2807—Investigating fluid-tightness of structures by using fluid or vacuum by measuring rate of loss or gain of fluid, e.g. by pressure-responsive devices, by flow detectors for pipes, cables or tubes; for pipe joints or seals; for valves ; for welds for pipes
-
- E—FIXED CONSTRUCTIONS
- E03—WATER SUPPLY; SEWERAGE
- E03F—SEWERS; CESSPOOLS
- E03F1/00—Methods, systems, or installations for draining-off sewage or storm water
-
- E—FIXED CONSTRUCTIONS
- E03—WATER SUPPLY; SEWERAGE
- E03F—SEWERS; CESSPOOLS
- E03F1/00—Methods, systems, or installations for draining-off sewage or storm water
- E03F1/001—Methods, systems, or installations for draining-off sewage or storm water into a body of water
-
- E—FIXED CONSTRUCTIONS
- E03—WATER SUPPLY; SEWERAGE
- E03F—SEWERS; CESSPOOLS
- E03F5/00—Sewerage structures
- E03F5/10—Collecting-tanks; Equalising-tanks for regulating the run-off; Laying-up basins
- E03F5/105—Accessories, e.g. flow regulators or cleaning devices
- E03F5/107—Active flow control devices, i.e. moving during flow regulation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/14—Rainfall or precipitation gauges
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
-
- E—FIXED CONSTRUCTIONS
- E03—WATER SUPPLY; SEWERAGE
- E03F—SEWERS; CESSPOOLS
- E03F2201/00—Details, devices or methods not otherwise provided for
- E03F2201/20—Measuring flow in sewer systems
Definitions
- the present invention relates to an unknown water occurrence distribution estimating apparatus and method, and particularly to an unknown water occurrence distribution estimating apparatus and method for estimating the occurrence distribution of unknown water flowing into sewerage, and a recording medium.
- the merged type is a method that treats domestic wastewater and rainwater collectively
- the split type is a method that treats domestic wastewater and rainwater separately.
- the confluence type although sewer pipes under the ground can be used for both domestic wastewater and rainwater, sewage treatment plants need to treat not only domestic wastewater but also rainwater, which imposes a heavy burden on sewage treatment.
- a split-flow type although it is necessary to lay a drain pipe exclusively for rainwater, it is possible to reduce the burden of treating wastewater only by treating domestic wastewater at a sewage treatment plant.
- Fig. 14 shows an example of a diverted sewer system.
- the sewage treatment plant is located 300 downstream of the target area, and after collecting domestic wastewater from buildings / factories 310 and houses 311 in the target area through the sewage pipe 302 and the sewage main line 301 for sewage treatment, Released into rivers and the sea.
- Rainwater is discharged directly to rivers and the sea via a sewer pipe 302 and a drain pipe 303 separate from the sewer main line 301.
- the sewage treatment plant 300 can reduce the scale of the sewage treatment capacity of the sewage treatment plant 300, which can be achieved by treating only the wastewater from the target treatment area, that is, the amount of water consumed by the water supply system. Can be reduced.
- unknown water that causes such an increase in the amount of sewage treatment is called unknown water.
- One of the major causes of this unknown water is infiltration of rainwater into the sewage main line 301 and the sewer pipe 302. This is due to indirect intrusion due to various pipe defects such as broken pipes and poor connection at pipe connection points due to the deterioration of the sewer main line 301 and the sewer pipe 302, as well as poor manhole covers and in-house drainage facilities. There is also intrusion. Therefore, it is necessary to identify the locations where such unknown water is generated in the treatment target area and to repair pipes and facilities and improve watertightness as a countermeasure against trace infiltration.
- FIG. Figure 15 is a work flow showing the unknown water identification work.
- Step 400 a flow rate survey on the sewage main line is performed (Step 400), the current flow rate is quantified, the amount of unknown water is grasped, and the treatment load at the sewage treatment plant is confirmed (Step 401).
- the processing target area is divided into several hundred blocks, and a subdivision flow survey is performed for each block (step 402). At this time, rainfall observations, groundwater level surveys, chlorine concentration surveys, etc. are performed as incidental surveys (step 403).
- a problem block is selected and an unknown water intrusion cause finding method is selected (step 404).
- Step 400 the amount of sewage can be investigated only at sewage treatment plants and at several power stations such as pump stations provided on the sewage main line.
- measuring the amount of sewage in many areas by dividing the sewer requires a large amount of equipment and work, making it difficult to accurately quantify the current flow rate and accurately grasp the unknown water volume. Yes, it was not possible to grasp the occurrence of unknown water in detail and easily!
- An object of the present invention is to solve such a problem, and an object of the present invention is to provide an unknown water occurrence distribution estimating apparatus, method, and recording medium capable of estimating the occurrence distribution of unknown water in detail and easily.
- the unknown water generation distribution estimating apparatus provides unknown water generation function information of each district for estimating the distribution of unknown water flowing into the sewer, and unknown base points located downstream from each of these districts.
- An unknown water occurrence distribution estimating means that outputs the unknown water occurrence distribution in each area based on the comparison result with the water volume function information is provided.
- the unknown water occurrence distribution estimating means includes the rainfall amount in the area including the rainfall in the area.
- First processing means for performing pattern matching analysis of unknown water generation function information of each area generated from unknown water generation factor information with unknown water volume function information including the unknown water volume at the base point, and their pattern matching
- a second processing means is provided for outputting the degree of pattern matching of each district obtained by prayer as an unknown water occurrence distribution in each district.
- the method for estimating the distribution of unknown water generation includes the unknown water generation function information of each district for estimating the distribution of unknown water flowing into the sewer, and the unknown of the base point located downstream from each of these districts.
- An unknown water occurrence distribution estimating step for outputting an unknown water occurrence distribution in each area based on the comparison result with the water function information is provided.
- the recording medium includes an unknown water generation function information of each district for estimating the generation distribution of unknown water flowing into the sewer, and an unknown water volume function of a base point located downstream from each of these districts. Based on the comparison result with the information, the unknown water occurrence distribution in each area is output by the computer of the unknown water occurrence distribution estimation device, which outputs the unknown water occurrence distribution information in the area including the rainfall in the area. Pattern matching analysis of unknown water generation function information for each area with unknown water function information including unknown water volume at the base point And a second step of outputting the degree of pattern matching of each district obtained by these pattern matching analyzes as the distribution of unknown water occurrence in each district. .
- the unknown water generation function information including the unknown water amount at the base point is obtained for the unknown water generation function information of each region generated from the unknown water generation factor information of the relevant region including the rainfall amount in the relevant region.
- Pattern matching analysis is performed, and the pattern matching degree of each district obtained by the pattern matching analysis is output as the unknown water distribution in each district. Eliminates the need for actual measurement, and easily and in detail understands the distribution of unknown water occurrence in each area from unknown water generation function information such as rainfall data in each area and unknown water function information such as unknown water amount data at the base point it can.
- FIG. 1 is a block diagram showing a configuration of an unknown water generation distribution estimating apparatus according to an embodiment of the present invention.
- FIG. 2 is a flowchart showing the operation of the unknown water generation distribution estimation device.
- FIG. 3 is a flowchart showing unknown water calculation processing.
- FIG. 4A is a graph showing a time-series change in the amount of sewage at the base point.
- FIG. 4B is a graph showing a time-series change in the amount of non-rainfall sewage at the base point.
- FIG. 4C is a graph showing a time-series change of an unknown water amount at a base point.
- FIG. 5 is a flowchart showing an unknown water occurrence distribution estimating process.
- Fig. 6 is an example of unknown water occurrence distribution data.
- Fig. 7A is an output example of unknown water occurrence distribution data (laydown diagram of sewage trunk line).
- Fig. 7B is an output example of unknown water occurrence distribution data (estimated value of unknown water occurrence distribution data).
- Fig. 7C is an output example (contour diagram) of unknown water generation distribution data.
- FIG. 7D is an output example of unknown water occurrence distribution data (estimated value of unknown water occurrence distribution data Z laying diagram of sewage trunk line).
- FIG. 7E is an output example of unknown water occurrence distribution data (an unknown water occurrence location).
- Fig. 7F is an output example of unknown water occurrence distribution data (unknown water occurrence location Z city map).
- FIG. 8 is a flowchart showing a correlation value calculation process.
- FIG. 9 is a configuration example of a sewer.
- FIG. 10 is a configuration example showing delivery time data.
- FIG. 11A is an explanatory diagram showing rainfall data of Area A.
- FIG. 11B is an explanatory diagram showing rainfall data of district B.
- FIG. 11C is an explanatory diagram showing a time difference correction between rainfall data and unknown water volume data of the areas A and B.
- FIG. 12 is a flowchart showing another correlation value calculation process.
- FIG. 13A is an explanatory diagram showing rainfall data of district A.
- FIG. 13B is an explanatory diagram showing an unknown water inflow amount.
- FIG. 13C is an explanatory diagram showing correlation values between rainfall data and unknown water inflow in Area A.
- FIG. 14 is an example of a divided sewer system.
- FIG. 15 is a work flow showing an unknown water identification work.
- FIG. 1 is a block diagram showing a configuration of an unknown water occurrence distribution estimating apparatus according to an embodiment of the present invention.
- the unknown water generation distribution estimating device 1 calculates the unknown water generation function information generated from the unknown water generation factor information including the rainfall in each area to be estimated, and the unknown water amount at the base point located downstream from these areas. It is a device that estimates the distribution of unknown water generation in each area from the unknown water function information.
- the unknown water generation function information indicates the time-series change of rainfall in each area to be estimated.
- various parameters related to the amount of unknown water generation such as the amount of solar radiation, the amount of rain infiltrated into soil, and the amount of evaporation of rain in each area, that is, the function power with unknown water generation factor information is calculated. is there.
- the unknown water flow function information includes unknown water flow data indicating the time-series change of unknown water contained in the sewage flow at an arbitrary base point of the target sewer, weather information such as temperature and humidity at the base point, and the base point. It is data that calculates the functional force having various parameters related to the unknown water volume at the base point, such as the sewage flow rate.
- the unknown water occurrence distribution estimating apparatus 1 performs pattern matching analysis on the unknown water occurrence function information and the unknown water amount function information in each area (first processing means Z, first step), and performs pattern matching.
- the pattern matching degree obtained by the analysis is output as the unknown water occurrence distribution in each district (second processing means Z, second step).
- a general analysis method such as a DP matching (Dynamic Programming) analysis, in addition to a correlation analysis for obtaining a correlation value between the two, may be used.
- the unknown water generation distribution estimation device 1 is connected to the rainfall measurement system 2, the sewage measurement device 3, or the sewage estimation device 4 via the communication network 5, and the calculation of unknown water and the unknown Obtain various data necessary for estimating the distribution of water generation.
- the present invention focuses on a strong correlation between a change in rainfall in an area with a large amount of unknown water and a change in the amount of unknown water contained in sewage at a base point located downstream from the area. By calculating such correlation values for each area, the distribution of unknown water occurrence is estimated.
- the rainfall in each area is used as unknown water generation factor information for each area
- the rainfall data 24 indicating the time series change of these rainfalls is used as unknown water generation function information for each area.
- Is the unknown water function function information at the base point, and the correlation value of the rainfall data 24 at each point with the unknown water amount data at the base point is the pattern matching degree (comparison result) obtained by the pattern matching analysis.
- the following is an example of estimating the unknown water occurrence distribution at each point.
- the unknown water generation distribution estimating apparatus 1 includes a control unit 10, a storage unit 20, a screen display unit 30, an operation input A power unit 40 and a data input / output interface unit (hereinafter, referred to as a data input / output IZF unit) 50 are provided.
- the control unit 10 also functions as a microprocessor such as a CPU and its peripheral circuits.By reading and executing the program 29 stored in the storage unit 20 in advance, the hardware unit and the program cooperate with each other, and It implements various functional means necessary for estimating the occurrence distribution.
- a microprocessor such as a CPU and its peripheral circuits.By reading and executing the program 29 stored in the storage unit 20 in advance, the hardware unit and the program cooperate with each other, and It implements various functional means necessary for estimating the occurrence distribution.
- the storage unit 20 is a storage device such as a hard disk or a memory, and includes various types of data used for processing in the control unit 10, such as sewage amount data 21 indicating time-series changes in sewage amount at an arbitrary base point of the target sewer. , Non-rainfall sewage data showing the time-series change of sewage volume under non-rainfall (clear weather) at the base point, unknown water volume data showing the chronological change of unknown water volume at the base point, and each target area In addition to the rainfall data 24 indicating the time series change of the rainfall at the time, a program 29 executed by the control unit 10 is stored.
- sewage amount data 21 indicating time-series changes in sewage amount at an arbitrary base point of the target sewer.
- Non-rainfall sewage data showing the time-series change of sewage volume under non-rainfall (clear weather) at the base point
- unknown water volume data showing the chronological change of unknown water volume at the base point
- each target area In addition to the rainfall data 24 indicating the time series change of the rainfall
- the program 29 may be read from a recording medium 6 such as a CD-ROM in which the program 29 is recorded, or may be read via a communication network 5 holding the program 29 and a data input / output IZF unit 50. And read and stored in the storage unit 20 in advance.
- a recording medium 6 such as a CD-ROM in which the program 29 is recorded
- a communication network 5 holding the program 29 and a data input / output IZF unit 50.
- the program 29 may be read from a recording medium 6 such as a CD-ROM in which the program 29 is recorded, or may be read via a communication network 5 holding the program 29 and a data input / output IZF unit 50. And read and stored in the storage unit 20 in advance.
- the screen display unit 30 displays various information such as an estimated result of unknown water generation distribution on a screen, such as a display device such as an LCD or a CRT.
- the operation input unit 40 also functions as an operation input device such as a keyboard and a mouse, and detects a user operation and outputs the operation to the control unit 10.
- the IZF unit 50 is connected to the communication network 5 and an external device (not shown) to input and output various data and processing results required for processing in the control unit 10.
- an unknown water calculating means 11 As the functional means of the control unit 10, an unknown water calculating means 11, an unknown water occurrence distribution estimating means 12, and a contour line information calculating means 13 are provided.
- Unknown water calculation means 11 calculates unknown water amount data 23 at the base point from the difference between sewerage data 21 and non-rainfall sewage amount data 22 at storage unit 20 at the base point.
- the unknown water occurrence distribution estimating means 12 estimates the unknown water occurrence distribution by calculating the correlation value between the rainfall data 24 and the unknown water data 23 at each point to be estimated.
- the contour line information calculating means 13 interpolates the correlation value of each area to calculate the circumference of each area.
- the correlation value at the side is calculated as interpolation information, and contour line information indicating the unknown water occurrence distribution is generated using the obtained interpolation information, and is output as unknown water occurrence distribution data 25.
- FIG. 2 is a flowchart showing the operation of the unknown water distribution estimation apparatus.
- the control unit 10 of the unknown water generation distribution estimating apparatus 1 starts the operation of FIG. 2 in response to the processing start operation from the operation input unit 40.
- unknown water amount data 23 indicating a time series change of unknown water at a base point is calculated by executing unknown water calculation processing using unknown water calculation means 11 (step 100).
- any point can be selected from the points where the amount of sewage can be measured downstream of each area of the sewerage system to be estimated, such as a sewage treatment plant or a pump station on the sewage main line. .
- the correlation value (comparison result) between the unknown water amount data 23 (unknown water occurrence function information) and the rainfall data 24 (unknown water occurrence function information) of each area is calculated.
- Estimate the unknown water occurrence distribution by calculating each of them, output these correlation values as unknown water occurrence distribution data 25 (Step 101), and end the series of unknown water occurrence distribution estimation processing.
- the unknown water volume data 23 may be obtained from the sewage volume estimation device 4 via the communication network 5 if the unknown water volume data 23 can be calculated by the sewage volume estimation device 4 outside the device.
- FIG. 3 is a flowchart showing the unknown water calculation process.
- the unknown water calculating means 11 When calculating the unknown water, the unknown water calculating means 11 first obtains the sewage amount data 21 indicating the time-series change of the sewage amount at the base point from the storage unit 20 (step 110), and also obtains the data at the base point under non-rainfall.
- the non-rainfall sewage data 22 indicating the time series change of the sewage is acquired from the storage unit 20 (step 111).
- the sewage amount data 21 data obtained from the sewage amount measuring device 3 or the sewage amount estimation device 4 via the communication network 5 may be used.
- the non-rainfall sewage data is subtracted from the sewage data to calculate unknown water data (step 112), and a series of unknown water calculation processing ends.
- FIGS. 4A, 4B, and 4C are graphs showing time-series changes of sewage, non-rainfall sewage, and unknown water at the base point, respectively.
- the main cause of unknown water is rainwater that does not flow into the sewerage system. As shown in Figure 4A, the measured sewage volume 70 rises significantly with rainfall.
- the sewage amount 70 includes domestic wastewater and rainwater. Therefore, the amount of unknown water 72 can be calculated by subtracting domestic wastewater, that is, non-rainfall sewage 71, from the measured sewage 70.
- FIG. 4C shows the time series change of the calculated unknown water volume 72.
- the unknown water volume 72 increases accordingly.
- the unknown water amount 72 is calculated by subtracting the non-rainfall sewage amount 71 from the sewage amount 70 at the base point, the unknown water amount can be easily and accurately calculated.
- sewage volume 70 data measured at the base point and the sewage volume measuring device 3 may be used.
- the sewage volume data estimated according to may be used.
- non-rainfall sewage 71 data measured at the base point using the sewage measurement device 3 during non-rainfall may be used, but the season, temperature, Non-rainfall sewage data estimated according to days and holidays may be used.
- FIG. 5 is a flowchart showing the unknown water estimation process.
- the unknown water occurrence distribution estimating means 12 first estimates the unknown water occurrence distribution One of the unestablished areas for which no correlation value has been calculated is selected (step 120), and the rainfall data 24 (unknown water generation function information) and the unknown water An unknown water correlation value calculation process for calculating a correlation value (pattern match degree Z comparison result) with the amount data 23 (unknown water function information) is executed (step 121).
- the unknown water occurrence distribution estimating means 12 performs a pattern matching analysis of the rainfall data 24 (unknown water generation function information) in the area with the unknown water amount data 23 (unknown water function information) at the base point. (1st processing means Z, 1st step), the correlation value (pattern match degree Z comparison result) obtained by this no-turn matching analysis is output as the unknown water occurrence distribution in the area (2nd step). Processing means Z second step).
- Step 122 YES
- the process returns to step 120 to calculate a correlation value for a new area. Execute.
- step 122 when the correlation values are calculated for all the districts (step 122: NO), the correlation values of the respective districts are interpolated to generate the correlation values at the peripheral points of each district as interpolation information ( Step 123), the unknown water occurrence distribution data 25 is generated by calculating contour information indicating the unknown water occurrence distribution using the interpolation information (Step 124), and the unknown water occurrence distribution data 25 is displayed on the screen display unit. A graphic display is displayed at 30 (step 125), and the series of unknown water occurrence distribution estimation processing is terminated.
- FIG. 6 shows an example of the configuration of unknown water occurrence distribution data, in which correlation values calculated for each district are associated.
- This correlation value indicates the similarity between the area and the unknown water over time, and the closer the correlation value is to zero, the closer the relationship (similarity) between the rainfall of the area and the unknown water (similarity) is. It can be seen that the generation of unknown water is relatively small. In addition, the closer the correlation value is to 1, the greater the relevance (similarity) between the rainfall in the area and the unknown water, indicating that the generation of unknown water in the area is relatively large.
- FIG. 7A to FIG. 7F show examples of graphic display of unknown water occurrence distribution data.
- Figure 7A is a sewage trunk line laying diagram laid in the estimation target area, and is a display example in which a city map is superimposed.
- Figure 7B shows the unknown water occurrence distribution data (see Figure 6) estimated by the unknown water occurrence distribution estimation device that is useful in the present embodiment. The correlation value of the area is placed in the field.
- Figure 7C is an unknown water occurrence distribution graph (contour diagram) obtained by interpolating the unknown water occurrence distribution data of Figure 7B. Correlation values in each area are indicated by contour lines. The colors are displayed according to the strength of the occurrence correlation. In this example, it is shown that the unknown area, in particular, has a higher correlation value in the white area.
- Fig. 7D is obtained by superimposing the unknown water distribution graph of Fig. 7B on the sewage trunk line laying diagram of Fig. 7A. A white area exists around the sewage trunk line. The location where unknown water is generated can be easily grasped.
- Fig. 7E shows the locations of unknown water occurrence in Fig. 7C with circles.By overlaying these circles on the map of the city area in Fig. 7F, in which districts many unknown waters actually occur. ⁇ ⁇ , ⁇ ⁇ can easily be confirmed on the street map.
- graphic display examples on the screen display unit are not limited to the examples in FIG. 7, and there are combinations of these display examples, and other display methods may be used.
- the unknown water generation distribution estimating means 12 of the control unit 10 uses the rainfall data 24 (unknown water generation data) indicating the time series change of the rainfall (unknown water generation factor information) in each area to be estimated.
- Function information indicating the time series change of the rainfall (unknown water generation factor information) in each area to be estimated.
- function information indicating the time series change of the rainfall (unknown water generation factor information) in each area to be estimated.
- unknown water volume data 23 unknown water volume function information
- FIG. 8 is a flowchart showing the correlation value calculation process.
- the time difference between the rainfall data 24 and the unknown water data 23 is corrected (step 130).
- Rain that falls in one area is downstream through the sewer It takes some time to reach the base point. Therefore, when calculating the correlation between the rainfall data 24 and the unknown water data 23, it is necessary to correct the time difference.
- a delivery time to the local power base point obtained in advance may be used.
- part of the rainwater in Area A will enter the sewage trunk line 61 and flow to the downstream sewage treatment plant 63 via the sewage trunk line 60.
- part of the rainwater in Area B enters the sewer main line 62, merges with the sewer from the sewer main line 61 at the sewer main line 60, and reaches the sewerage treatment 63.
- the delivery time data as shown in FIG. 10 is stored in the storage unit 20 in advance, and when calculating the correlation value of an arbitrary area, the rainfall data 24 and the unknown water amount are calculated using the arrival time of the area. What is necessary is just to correct the time difference from the data 23.
- FIG. 11A to FIG. 11C are explanatory diagrams showing the time difference correction between the rainfall data and the unknown water data in the areas A and B.
- the rainfall data 71 starts to increase at the time T1
- the rainfall data 72 starts to increase at the time T2.
- the base point as shown in FIG. 11C, it is assumed that unknown water starts to increase at time T3.
- these ATa and ATb are the delivery times of the areas A and B, respectively.
- the time difference ⁇ may be calculated from the rainfall data 24 and the unknown water data 23 used for calculating the correlation value instead of measuring the arrival time in each district in advance.
- the peaks (maximum values) of the rainfall data 24 and the unknown water data 23 may be found, and the time difference between these peaks may be used as the time difference ⁇ .
- the start point and end point of rainfall data and unknown water data may be used instead of peaks.
- the correlation value between the rainfall data 24 with the time difference corrected and the unknown water volume data 23 is obtained using the time-series data included in a predetermined period among these data.
- the time difference between the rainfall data 24 and the unknown water volume data 23 is corrected, and the correlation value between the two data is obtained. Therefore, it is possible to obtain an appropriate correlation value for each district. it can.
- the rainwater arrival time is prepared in advance for each district, and the time difference between the two data is corrected using the arrival time in the corresponding district. Time difference can be corrected.
- the time difference between the peaks of both data can be corrected based on the obtained time difference.
- the time difference between both data can be corrected without preparing a time difference for each district.
- FIG. 12 is a flowchart showing another correlation value calculation process.
- the time difference between the rainfall data 24 and the unknown water amount data 23 is determined in advance by using the time difference corresponding to the area or the time difference between the peaks of the two data. This has been described in the case where the time difference of the data is collectively corrected.
- the time difference between the rainfall data 24 and the unknown water data 23 is slightly shifted to obtain the most appropriate correlation value.
- FIGS. 13A to 13C are explanatory diagrams showing the rainfall data, the inflow of unknown water, and their correlation values in the area A as a specific example of the correlation value calculation processing of FIG.
- a correlation value is calculated using each time-series data included in a predetermined period of the rainfall data 24 and the unknown water data 23 (step 140).
- the correlation value between the rainfall data 71 at the time T11 and the unknown water data 75 is obtained.
- the time difference between the two data is not corrected, and the correction amount is zero.
- step 141 If the correction amount has not reached the upper limit (step 141: NO), the time difference between the two data is corrected by the unit shift time At (step 142), and a new correlation value is obtained. Return to step 140. From this, the correlation value between the rainfall data 71 shifted to time T12 and the unknown water data 75 is obtained. In this way, the correlation value is obtained for each correction amount until the correction amount reaches the upper limit.
- step 141 when the correction amount reaches the upper limit value Tmax, (step 141).
- step 143 select the maximum correlation value of each correlation value obtained so far, and output it as the correlation value between rainfall data 24 and unknown water volume data 23 in the area.
- the correlation value is calculated by slightly shifting the time difference between the rainfall data 24 and the unknown water data 23, and the maximum correlation value is calculated as the correlation value in the area.
- the correlation value of both data can be calculated with high accuracy.
- the rainfall data 24 and the unknown water volume data 23 for which the correlation values are actually obtained can be obtained by using data for several hours, for several days, for several weeks, and for several months. May be used.
- unknown water amount data 23 used for estimating unknown water occurrence distribution is calculated using unknown water calculation means 11 of control unit 10
- the present invention is not limited to this.
- the unknown water volume data calculated by another device, for example, the sewage volume estimation device 4, may be obtained and used.
- the unknown water generation distribution estimating means 12 of the control unit 10 may be provided in the sewage amount estimating device 4.
- rainfall data For rainfall data, rainfall data provided every 17 km from AMeDAS of the Japan Meteorological Agency may be used as rainfall measurement system 2 or rainfall data provided every 2.5 km from Radar AMeDAS may be used. Is also good. You can also use the rainfall data provided every 250 m from local government radar AMeDAS.
- the unknown water occurrence factor information at each point is determined by the rain at each point.
- the rainfall data 24 indicating the time series change of rainfall at each point is used as the unknown water generation function information at each point, and the unknown time series change of unknown water at the base point is used as the unknown water function function information at the base point.
- the case where the water volume data 23 is used has been described as an example, but the present invention is not limited to this.
- various parameters related to the amount of unknown water such as the amount of solar radiation, the amount of rain seeping into soil, and the amount of evaporation of rain, can be used as unknown water generation factor information.
- Functional force having parameters The calculated time-series data may be used as unknown water generation function information instead of the rainfall data 24.
- the unknown water volume function information that is, unknown water volume data23
- time-series data calculated from various parameters related to unknown water volume at the base point such as meteorological information such as temperature and humidity at the base point and sewage flow rate at the base point, is used.
- correlation analysis is used as the pattern matching analysis between the unknown water generation function information and the unknown water function information
- the correlation value is used as the pattern matching degree (comparison result) obtained by the pattern matching analysis.
- the unknown water generation distribution estimating apparatus, method, and recording medium according to the present invention are suitable for estimating the generation distribution of unknown water flowing into a sewer, and in particular, separate and treat domestic wastewater and rainwater. It is suitable for estimating the distribution of unknown water generated at a sewage treatment plant or inflow piping.
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Abstract
Description
Claims
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| EP04746906A EP1643042A4 (en) | 2003-07-04 | 2004-07-02 | DEVICE AND METHOD FOR ESTIMATING THE APPEARANCE AND DISTRIBUTION OF UNCONTAINTED WATER AND RECORDING MEDIUM |
| US10/561,781 US7519473B2 (en) | 2003-07-04 | 2004-07-02 | Device and method for estimating occurrence distribution of unascertained water and recording medium |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2003-271029 | 2003-07-04 | ||
| JP2003271029A JP3857670B2 (ja) | 2003-07-04 | 2003-07-04 | 不明水発生分布推定装置、方法およびプログラム |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2005003471A1 true WO2005003471A1 (ja) | 2005-01-13 |
Family
ID=33562637
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/JP2004/009437 Ceased WO2005003471A1 (ja) | 2003-07-04 | 2004-07-02 | 不明水発生分布推定装置、方法、および記録媒体 |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US7519473B2 (ja) |
| EP (1) | EP1643042A4 (ja) |
| JP (1) | JP3857670B2 (ja) |
| KR (1) | KR100804203B1 (ja) |
| WO (1) | WO2005003471A1 (ja) |
Families Citing this family (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4486004B2 (ja) * | 2005-07-27 | 2010-06-23 | 株式会社山武 | 河川汚濁負荷推定システム、方法、およびプログラム |
| JP4745759B2 (ja) * | 2005-08-31 | 2011-08-10 | 株式会社山武 | 河川汚濁負荷源推定装置、方法、およびプログラム |
| FR2895508B1 (fr) * | 2005-12-28 | 2008-03-07 | Sccm Soc Par Actions Simplifie | Detection d'une fuite de fluide dans un circuit par intercorrelation |
| JP4695008B2 (ja) * | 2006-04-17 | 2011-06-08 | 株式会社山武 | 保水能力推定装置およびプログラム |
| JP4782656B2 (ja) * | 2006-10-24 | 2011-09-28 | 株式会社山武 | 雨水流出量推定装置およびプログラム |
| JP5273531B2 (ja) * | 2008-08-25 | 2013-08-28 | 国立大学法人横浜国立大学 | 流入位置推定装置、流入位置推定方法、プログラム |
| JP5489593B2 (ja) * | 2009-08-19 | 2014-05-14 | メタウォーター株式会社 | 水位計測用マンホールユニット |
| JP5574769B2 (ja) * | 2009-09-10 | 2014-08-20 | 株式会社東芝 | 不明水監視装置及び不明水監視方法 |
| JP4980478B1 (ja) * | 2011-05-10 | 2012-07-18 | 株式会社日水コン | 不明水流入箇所特定装置 |
| JP6290072B2 (ja) * | 2014-12-02 | 2018-03-07 | 株式会社東芝 | 不明水発生区域推定装置、不明水発生区域推定方法及びコンピュータプログラム |
| US10501925B1 (en) * | 2015-03-20 | 2019-12-10 | Christopher Conway Lavenson | Notifications for reducing overflows from combined sewer systems and sanitary sewer systems |
| JP6867638B2 (ja) * | 2016-07-04 | 2021-04-28 | 株式会社明電舎 | 下水道監視システム及び下水道監視プログラム |
| JP6556389B1 (ja) * | 2019-01-30 | 2019-08-07 | 株式会社日圧機販 | 排水路監視システムおよび排水路監視方法並びに排水路監視プログラム |
| CN111519732A (zh) * | 2020-04-17 | 2020-08-11 | 广东中林建筑园林工程有限公司 | 一种市政工程排水系统 |
| JP7527268B2 (ja) * | 2021-12-07 | 2024-08-02 | 株式会社クボタ | 不明水推定システム |
| JP7143542B1 (ja) | 2022-03-30 | 2022-09-28 | 公益財団法人日本下水道新技術機構 | 分流式下水管への浸入水推定システム、方法、およびプログラム |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH11272336A (ja) | 1998-03-26 | 1999-10-08 | Meidensha Corp | ポンプ場の処理水監視制御システム |
| JP2000204642A (ja) * | 1999-01-08 | 2000-07-25 | Kajima Corp | 中継ポンプ場の不明水検知方法およびその装置 |
| JP2001126074A (ja) * | 1999-08-17 | 2001-05-11 | Atl Systems:Kk | パターンマッチングによるデータ検索方法及びそのプログラムを記録した記録媒体 |
| JP2003184160A (ja) * | 2001-12-17 | 2003-07-03 | Hitachi Ltd | 下水道の有収率向上方法および有収率向上システム |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3815749A (en) * | 1973-04-23 | 1974-06-11 | L Thompson | Street drain for use with a sewer system |
| JPH0833157B2 (ja) * | 1988-06-25 | 1996-03-29 | 株式会社東芝 | 雨水ポンプの運転制御装置 |
| AU669419B2 (en) * | 1992-12-30 | 1996-06-06 | Merpro Tortek Limited | Water management system |
| JP2001184160A (ja) | 1999-12-22 | 2001-07-06 | Fujitsu Takamisawa Component Ltd | 座標入力装置およびその製造方法 |
| JP2001182135A (ja) * | 1999-12-22 | 2001-07-03 | Toshiba Corp | 下水道システムの制御装置 |
| JP3795775B2 (ja) | 2001-07-16 | 2006-07-12 | 株式会社山武 | 下水流入量予測装置および方法、サーバ装置 |
| BR0301519B1 (pt) * | 2003-05-30 | 2014-01-28 | Acoplamento de estação de tratamento de esgoto ETE ao conjunto de tratamento por floculação e flotação de cursos dágua | |
| JP4179259B2 (ja) * | 2004-09-27 | 2008-11-12 | 株式会社デンソー | スタータ |
-
2003
- 2003-07-04 JP JP2003271029A patent/JP3857670B2/ja not_active Expired - Lifetime
-
2004
- 2004-07-02 KR KR1020067000062A patent/KR100804203B1/ko not_active Expired - Fee Related
- 2004-07-02 US US10/561,781 patent/US7519473B2/en not_active Expired - Fee Related
- 2004-07-02 EP EP04746906A patent/EP1643042A4/en not_active Withdrawn
- 2004-07-02 WO PCT/JP2004/009437 patent/WO2005003471A1/ja not_active Ceased
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH11272336A (ja) | 1998-03-26 | 1999-10-08 | Meidensha Corp | ポンプ場の処理水監視制御システム |
| JP2000204642A (ja) * | 1999-01-08 | 2000-07-25 | Kajima Corp | 中継ポンプ場の不明水検知方法およびその装置 |
| JP2001126074A (ja) * | 1999-08-17 | 2001-05-11 | Atl Systems:Kk | パターンマッチングによるデータ検索方法及びそのプログラムを記録した記録媒体 |
| JP2003184160A (ja) * | 2001-12-17 | 2003-07-03 | Hitachi Ltd | 下水道の有収率向上方法および有収率向上システム |
Non-Patent Citations (1)
| Title |
|---|
| See also references of EP1643042A4 |
Also Published As
| Publication number | Publication date |
|---|---|
| JP2005023763A (ja) | 2005-01-27 |
| US20070095729A1 (en) | 2007-05-03 |
| EP1643042A1 (en) | 2006-04-05 |
| KR20060035717A (ko) | 2006-04-26 |
| JP3857670B2 (ja) | 2006-12-13 |
| EP1643042A4 (en) | 2011-04-27 |
| KR100804203B1 (ko) | 2008-02-18 |
| US7519473B2 (en) | 2009-04-14 |
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