JP2022161615A - Unknown water analysis method, unknown water analyzer, and unknown water analysis program - Google Patents

Abstract

To easily and highly accurately analyze unknown water and to easily specify a location of the unknown water.SOLUTION: There is provided an unknown water analysis method for analyzing unknown water flowing into a sewage pipe from outside, the method including: an electric energy acquisition step of acquiring electric energy data (143) of a pump facility (10) for pumping out sewage flowing through a sewage pipe, from a digital electric energy meter (20) by an electric energy acquisition unit (11); a rainfall acquisition step of acquiring rainfall data (142) representing rainfall at a location of the pump facility (10), by the electric energy acquisition unit (11); and an unknown water analysis step of analyzing unknown water by an unknown water analysis unit (18) according to a correlation between a change in electric energy based on the electric energy data (143) and a change in rainfall amount based on the rainfall data (142).SELECTED DRAWING: Figure 11

Description

TECHNICAL FIELD The present invention relates to an unknown water analysis method, an unknown water analysis device, and an unknown water analysis program, and for example, an unknown water analysis method, an unknown water analysis device, and an unknown water analysis program for analyzing unknown water flowing into a sewage pipe. Regarding.

In addition to sewage such as sewage from households and rainwater, unknown water may flow into the sewage pipe. Here, the unknown water is rainwater, groundwater, etc. that enters from the middle of the water pipe network, and can be defined as the total amount of sewage water - the amount of revenue water. The amount of revenue water is the amount of sewage water subject to collection of sewage usage charges, excluding unidentified water, out of the total amount of sewage treated at the sewage treatment plant.

Such unknown water is classified into direct inflow, in which rainwater, etc. from rainfall directly flows into the manhole from the sewage manhole cover, etc., and delayed inflow, in which rainwater, etc. that permeates underground slowly flows into the manhole over time. . Possible causes of direct inflow include, for example, misconnection of rain gutters. In addition, damage to pipes, damage to underground pipelines and sewage manholes, etc. can be considered as causes of delayed inflow.

As a method for estimating such unknown water whose inflow path is unknown, the operating status of the manhole pump is detected by a clamp-type AC current sensor, the operating status of the manhole pump for a certain period of time is recorded, and based on the operating status There is a method for estimating the presence or absence of unknown water through analysis (see, for example, Patent Document 1).

JP 2018-12094 A

However, in the method disclosed in Patent Document 1, a clamp-type AC current sensor for detecting the operating state of the manhole pump is blindly installed at the site, even though the location where the unknown water is generated is unknown. It is necessary to confirm the detection result displayed on the display after connecting to the data processing device.

That is, in order to estimate the presence or absence of unknown water, it is necessary to go to the site of the clamp-type alternating current sensor installed somewhere and connect the clamp-type alternating current sensor and the data processing device. It was not possible to easily estimate the presence or absence of unknown water.

In addition, the method disclosed in Patent Document 1 cannot be said to have sufficient accuracy in estimating unknown water, and it is required to analyze unknown water with even higher accuracy.

The present invention has been made in view of the above problems, and includes an unknown water analysis method, an unknown water analysis apparatus, and an unknown water analysis method that can easily and highly accurately analyze unknown water and easily identify the location of unknown water. The purpose is to realize an unknown water analysis program.

In the present invention, there is provided an unknown water analysis method for analyzing unknown water flowing into a sewage pipe from the outside, wherein the power amount data of a pump facility for pumping out sewage flowing through the sewer pipe is obtained from a digital watt-hour meter. a rainfall acquisition step of acquiring rainfall amount data representing the amount of rainfall at the location of the pump equipment by a rainfall amount acquisition unit; and a change in the power amount waveform based on the power amount data. and an unknown water analysis step of analyzing the unknown water by the unknown water analysis unit according to the correlation with the change in the rainfall waveform based on the rainfall data.

In the unknown water analysis method of the present invention, in the unknown water analysis step, if it is determined that the correlation does not exist between the power amount waveform and the rainfall amount waveform, it is determined that the unknown water is not affected by rainfall. It is preferable to judge

In the unknown water analysis method of the present invention, in the unknown water analysis step, the pattern of increase and decrease of the power amount waveform based on the power amount data follows the pattern of increase and decrease of the rainfall amount waveform based on the rainfall amount data. If so, it is preferable to determine that the unknown water is due to direct inflow due to rainfall.

In the unknown water analysis method of the present invention, in the unknown water analysis step, an increase in the power amount waveform based on the power amount data follows an increase in the rainfall waveform based on the rainfall amount data, and a decrease in the power amount waveform follows. If the decrease is slower than the rainfall waveform, it is preferably determined that the unknown water is due to direct inflow due to rainfall and delayed inflow due to ground seepage.

In the unknown water analysis method of the present invention, in the unknown water analysis step, smoothing is performed by performing moving average processing on the power amount data, and in the unknown water analysis step, the moving average processing is performed on the rainfall data. is preferably smoothed by applying

In the present invention, an unknown water analyzer for analyzing unknown water flowing into a sewage pipe from the outside, wherein power consumption data of a pump facility for pumping out sewage flowing through the sewer pipe is obtained from a digital watt-hour meter. a rainfall amount acquisition unit that acquires rainfall data representing the amount of rainfall at the location of the pump equipment; a change in the power amount waveform based on the power amount data; and a rainfall amount based on the rainfall amount data. an unknown water analysis unit that analyzes the unknown water in accordance with the correlation with waveform changes.

In the present invention, there is provided an unknown water analysis program for analyzing unknown water flowing into a sewage pipe from the outside, wherein the power amount data of a pump facility for sending out sewage flowing through the sewage pipe is sent to a computer as a digital electric power. a rainfall acquisition step of acquiring rainfall data representing the amount of rainfall at the location of the pump equipment; a change in the power waveform based on the power data; and the rainfall data. and an unknown water analysis step of analyzing the unknown water according to the correlation with the change in the rainfall waveform based on.

According to the present invention, it is possible to realize an unknown water analysis method, an unknown water analyzer, and an unknown water analysis program that can easily and highly accurately analyze unknown water and easily identify the location of unknown water. can.

BRIEF DESCRIPTION OF THE DRAWINGS It is a schematic diagram which shows the whole structure of the unknown water analysis system which concerns on the 1st Embodiment of this invention. It is a block diagram showing the configuration of the functional unit of the smart meter according to the first embodiment of the present invention. 1 is a block diagram showing the configuration of functional units of an unknown water analyzer according to a first embodiment of the present invention; FIG. FIG. 3 is a block diagram showing the configuration of functional units of the unknown water analysis processing unit according to the first embodiment of the present invention; FIG. 4 is a linear diagram showing original power amount data before weighted average processing is performed by the power amount data processing unit according to the first embodiment of the present invention; Waveforms showing the waveform of the original electric energy data before the weighted average processing is performed by the electric energy data processing unit according to the first embodiment of the present invention, and the waveform of the electric energy data after the weighted average processing is performed. It is a diagram. FIG. 4 is a waveform diagram when it is determined that there is a high possibility of direct inflow due to rainfall in the first embodiment of the present invention. FIG. 4 is a waveform diagram when it is determined that there is no influence of rainfall in the first embodiment of the present invention; FIG. 4 is a waveform diagram when it is determined that there is a high possibility of direct inflow due to rainfall and delayed inflow due to groundwater or the like in the first embodiment of the present invention. FIG. 4 is a waveform diagram of two power amount data and rainfall amount data at different dates and times at a certain place in the first embodiment of the present invention; FIG. 4 is a flowchart for explaining an unknown water analysis processing procedure according to the first embodiment of the present invention; FIG. FIG. 10 is a waveform diagram before and after dividing unknown water into direct inflow and delayed inflow by the unknown water analysis processor according to the second embodiment of the present invention;

[1] Overview of Embodiments of the Present Invention First, an overview of typical embodiments of the invention disclosed in the present application will be described. In the following description, as an example, reference numerals on the drawings corresponding to constituent elements of the invention are described with parentheses.

[1] In a representative embodiment, an unknown water analysis method for analyzing unknown water flowing into a sewage pipe from the outside, wherein power consumption data of a pump facility (10) for sending out sewage flowing through the sewage pipe (143) is acquired from a digital watt-hour meter (20) by an electric power acquisition unit (31), Unknown water according to the correlation between the amount of rainfall acquisition step acquired by the amount acquisition unit (31), the change in power amount based on the power amount data (143), and the change in rainfall amount based on the rainfall amount data (142) and an unknown water analysis step of analyzing unknown water by an analysis unit (38).

[2] In the above unknown water analysis method, if it is determined in the unknown water analysis step that there is no correlation between the power consumption data (143) and the rainfall data (142), the impact of rainfall on unknown water is judge not.

[3] In the above unknown water analysis method, in the unknown water analysis step, the pattern of increase and decrease in power consumption based on the power consumption data (143) corresponds to the pattern of increase and decrease in rainfall based on the rainfall data (142). If it follows, it is determined that the unknown water is due to direct inflow due to rainfall.

[4] In the unknown water analysis method, in the unknown water analysis step, the increase in the amount of power based on the power amount data (143) follows the increase in rainfall based on the rainfall data (142), and the decrease in the amount of power follows. If it is slower than the decrease in rainfall, it is determined that the unknown water is due to direct inflow due to rainfall and delayed inflow due to ground seepage.

[5] In the above unknown water analysis method, in the unknown water analysis step, the electric energy data (143) is smoothed by performing moving average processing, and in the unknown water analysis step, the rainfall data (142) is Smoothing is performed by performing moving average processing.

[6] In a representative embodiment, an unknown water analyzer (30) for analyzing unknown water flowing into a sewage pipe from the outside, and a pump facility (10) for pumping sewage flowing through the sewer pipe. A power acquisition unit (31) that acquires power data (143) from a digital power meter (20), and a rainfall acquisition unit that acquires rainfall data representing rainfall at the location of the pumping equipment (20). (31), and an unknown water analysis unit (38) that analyzes unknown water in accordance with the correlation between changes in power consumption based on the power consumption data (143) and rainfall changes based on the rainfall data (142). and

[7] In a representative embodiment, an unknown water analysis program (140) for analyzing unknown water flowing into a sewage pipe from the outside, and a pump facility for sending sewage flowing through the sewer pipe to a computer (20) an electric energy acquisition step of acquiring electric energy data (143) from a digital electric energy meter (20), and acquiring rainfall data (142) representing rainfall at the location of the pumping equipment (20); a rainfall acquisition step; and an unknown water analysis step of analyzing unknown water according to the correlation between changes in power consumption based on the power consumption data (143) and rainfall changes based on the rainfall data (142). let it run.

[2] First Embodiment A specific example of the first embodiment will be described below with reference to the drawings. In the following description, the same reference numerals are given to the components that are common to the first embodiment, and repeated descriptions will be omitted. Also, it should be noted that the drawings are schematic, and the arrangement of each element, data format, communication method, etc. may differ from reality.

Hereinafter, the configuration of the unknown water analysis system 100 according to the first embodiment of the present invention will be described in detail with reference to FIGS. 1 to 11. FIG.

Here, FIG. 1 is a schematic diagram showing the overall configuration of the unknown water analysis system according to the first embodiment of the present invention. FIG. 2 is a block diagram showing the configuration of functional units of the smart meter according to the first embodiment of the present invention. FIG. 3 is a block diagram showing the configuration of the functional units of the unknown water analyzer according to the first embodiment of the present invention. FIG. 4 is a block diagram showing the configuration of the functional units of the unknown water analysis processor according to the first embodiment of the present invention.

FIG. 5 is a linear diagram showing original power amount data before weighted average processing is performed by the power amount data processing unit according to the first embodiment of the present invention. FIG. 6 shows the waveform of the original electric energy data before the weighted average processing is performed by the electric energy data processing unit according to the first embodiment of the present invention, and the waveform of the electric energy data after the weighted average processing is performed. 3 is a waveform diagram showing . FIG. 7 is a waveform diagram when it is determined that there is a high possibility of direct inflow due to rainfall in the first embodiment of the present invention.

FIG. 8 is a waveform diagram when it is determined that there is no influence of rainfall in the first embodiment of the present invention. FIG. 9 is a waveform diagram when it is determined that there is a high possibility of direct inflow due to rainfall and delayed inflow due to groundwater or the like in the first embodiment of the present invention. FIG. 10 is a waveform diagram of two pieces of power amount data and rainfall amount data at different dates and times at a certain location in the first embodiment of the present invention. FIG. 11 is a flowchart for explaining the unknown water analysis processing procedure according to the first embodiment of the present invention.

As shown in FIG. 1, the unknown water analysis system 100 includes a smart meter 20 that measures the power consumption of a manhole pump 10 installed in a manhole (not shown), a smart meter 20 and a network (for example, the Internet). ) and the unknown water analysis device 30 connected via.

The manhole pump 10 is installed in a manhole (not shown), pumps up sewage in the manhole to the vicinity of the ground surface, flows the sewage by gravity flow from the sewage pipe, and sends it to a sewage treatment plant. Here, it is assumed that a general manhole pump is used.

The smart meter 20 is a digital electricity meter. The smart meter 20 has an internal arithmetic processing function and a communication function for communicating with the outside. The smart meters 20 are unique power meters that are different one by one, and each have unique smart meter identification information. The smart meter identification information is associated with information (address information, latitude/longitude information, etc.) of the installation location of the smart meter 20, and it is possible to know the installation location of the smart meter 20 based on the smart meter identification information. .

As shown in FIG. 2 , the smart meter 20 has a power usage metering unit 21 , a smart meter storage unit 22 and a communication processing unit 25 . The power consumption measuring unit 21 is a functional unit that measures the power consumption when the manhole pump 10 uses power and holds the power consumption data. Arithmetic processing for calculating power consumption data is performed based on the detected value detected by a sensor or the like.

The power usage metering unit 21 is configured by, for example, a CPU (Central Processing Unit), a memory, an MCU (Micro Control Unit) including an interface, and the like. The smart meter 20 stores smart meter identification information in the smart meter storage unit 22 .

The smart meter storage unit 22 is a functional unit that stores unique smart meter identification information assigned to the smart meter 20 in an unrewritable state. The smart meter storage unit 22 is composed of, for example, a ROM (Read Only Memory).

The communication processing unit 25 is a functional unit that transmits the power usage data calculated by the power usage metering unit 21 to the external unknown water analyzer 30, and transmits the power usage data together with the smart meter identification information for, for example, one minute. It is transmitted to the unknown water analyzer 30 at intervals.

The unknown water analysis device 30 functions as an unknown water analysis device in the present invention, and as its functional blocks, as shown in FIG. and a computer having a control unit 37 .

The data acquisition unit 31 is a so-called interface unit that inputs and outputs data, and is a functional unit that acquires data from an external server. The input unit 32 is data input means such as a so-called keyboard. The display unit 33 is a display for displaying information. The storage unit 34 is a storage device such as a hard disk drive or flash memory. The control unit 37 is an arithmetic processing unit having a microcomputer configuration for performing overall control and executing various processes.

Each of these functional blocks is realized by cooperation of hardware resources constituting the unknown water analyzer 30 with software (unknown water analysis program), which is an application program installed in the unknown water analyzer 30. be.

Practically, hardware resources constituting the unknown water analyzer 30 include a CPU (Central Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), hard disk drive, keyboard, monitor, and the like.

In the storage unit 34, an unknown water analysis program 340 and an inspection point estimation program 341 are pre-installed in addition to a basic program for overall control of the unknown water analysis device 30. FIG.

Therefore, the unknown water analysis unit 38 of the control unit 37 analyzes the unknown water based on the unknown water analysis program 340, and stores the analysis result data (hereinafter referred to as "analysis result data") 344 in the storage unit. 34.

In addition, the inspection location estimation unit 39 of the control unit 37 estimates the installation location of the manhole to be inspected by using the analysis result data 344 and the smart meter identification information based on the inspection location estimation program 341, and estimates the installation location of the manhole to be inspected. (Hereinafter, this is called “estimation result data”.) 345 can be held in the storage unit 34 .

The storage unit 34 stores data representing the rainfall amount acquired by the unknown water analysis device 30 from an external server device (not shown) of, for example, the Japan Meteorological Agency through the data acquisition unit 31 (hereinafter referred to as "rainfall data ) 342 can be held.

Similarly, in the storage unit 34, the data 343 indicating the amount of power consumption (hereinafter referred to as "power amount data") acquired by the unknown water analyzer 30 from the manhole pump 10 via the data acquisition unit 31 is stored. can also be held.

As shown in FIG. 4, the unknown water analysis unit 38 of the control unit 37 includes, as functional blocks, a power amount data processing unit 381, a rainfall data processing unit 382, an analysis processing unit 383, and a data processing result presentation unit 384. , and an analysis result storage processing unit 385 .

The power amount data processing unit 381 of the unknown water analysis unit 38 performs weighted average processing and moving average processing on the power amount data 343org (FIG. 5) acquired from the manhole pump 10, thereby obtaining the power amount data of the manhole pump 10. is a functional unit that generates electric energy data 343 vis (FIG. 7) in which the change in is approximated to the change in the actual amount of rainfall.

Here, the weighted average processing performed by the power amount data processing unit 381 will be described. FIG. 5 is a linear diagram showing changes in the power consumption data 343org of the manhole pump 10 in chronological order. This electric energy data 343org is raw data in an original state that has not been subjected to any processing by the electric energy data processing unit 381 .

For example, in the electric energy data 343org in this case, there is a time period in which the electric energy is "0 kWh" in 24 hours from 0:00 on May 19, 2019 to 0:00 on May 20, 2019. . That is, there is a period of time during which the manhole pump 10 is not operating. For example, it is a time zone such as midnight when there is little domestic wastewater, or a time zone in the afternoon.

However, if it rains in the middle of the night when the manhole pump 10 is not in operation, there is a possibility that unknown water due to rainfall will flow into the manhole in addition to household wastewater. The manhole pump 10 does not operate when the amount of water accumulated is such that it is not necessary to pump it out.

However, even if the manhole pump 10 is not operating, it is necessary to produce an approximation of the amount of power approximately equal to the actual amount of rainfall. The amount of sewage inflow into manholes varies depending on the amount of rainfall depending on the time of day. Therefore, it is necessary to set a different ratio (weighting) for each time slot rather than uniform for each time slot.

Therefore, even if the power amount is "0 kWh", if the power amount (for example, 1.0 kWh) is recorded in the time period immediately after that, the power amount By weighting with the ratio, an approximate waveform is generated in which the amount of electric power is averaged.

Specifically, for example, the amount of power is "0 kWh" in the time zone from 1:00 am to 3:00 am, but the power amount of 10 kWh is used in the time zone of 4:00 am immediately after this time. Assume that the amount of electric power to be allocated to each period is 10 kWh, and the weighting coefficients for each time period are 1:00=0.2, 2:00=0.3, and 3:00=0.5. In this case, the power amounts corrected by these weighting factors are 1:00=2 kWh, 2:00=3 kWh, and 3:00=5 kWh. Incidentally, the weighting factors may be statistically determined based on the values of the power amount data for each time period.

In this manner, the power amount data processing unit 381 performs noise filtering processing of weighted average processing, thereby smoothing the waveform of the original power amount data 343org as shown in FIG. Electric energy data 343app having an approximate waveform that approximates the amount of rainfall that is expected to occur is generated.

Next, moving average processing performed by the power amount data processing unit 381 will be described. The moving average process is a method of smoothing time-series data by calculating the average value of the latest N values while moving the data along the time-series.

For example, if there are data with values of 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10, the average value of 1, 2, and 3 (in this case, "2") , then find the average value of 2, 3, and 4 (“3” in this case), find the average value of 3, 4, and 5 (“4” in this case), and so on one by one This is a method of finding the average value while moving the data.

The power data processing unit 381 smoothes the waveform represented by the power amount data 343app by performing moving average processing on the power amount data 343app a plurality of times (for example, four times) within the data range of the most recent 12 hours. It is possible to highlight the waveform portion of the power amount in the time period when there was

Specifically, for example, focusing on the power amount at 8:00 am, the power amount at 7:00 am is 2 kWh, the power amount at 8:00 am is 2 kWh, and the power amount at 9:00 am is 3 kWh. 2.0), 8:00(2.0), 9:00(3.0), the moving average value of electric energy at 8:00 is 2.333 for the first time. Next, using this 8:00 (2.333) to calculate the moving average values for 7:00 (1.0), 8:00 (2.333), and 9:00 (3.0), the moving average value for 8:00 is is 2.111 for the second time. Similarly, using 8:00 (2.111) to calculate the moving average values for 7:00 (2.0), 8:00 (2.111), and 9:00 (3.0), the moving average value for 8:00 is , 2.370 for the third time. Finally, using 8:00 (2.370) to calculate the moving average values at 7:00 (2.0), 8:00 (2.370), and 9:00 (3.0), the moving average value at 8:00 is , 2.456 for the fourth time. Therefore, let the amount of electricity at 8:00 be 2.456.

Next, focusing on 9:00 a.m., calculate the moving averages of 8:00 (2.456), 9:00 (3.0), and 10:00 (5.0), and use the moving averages to calculate four times as described above. Calculate the moving average value. Here, 2.456, which has already been obtained as the moving average value, is used as the electric power amount at 8:00 am. Of course, a moving average value may be used as the electric power amount at 10:00 am. That is, the moving average in the data range of one hour before and after the time of interest may be calculated by using again the value calculated by the calculation of the moving average in the data range of one hour before and after the time of interest.

In this way, the electric energy data processing unit 381 performs moving average processing on the electric energy data 343app, thereby smoothing the waveform of the electric energy data 343app as shown in FIG. The corresponding waveform portion of the electric energy of the manhole pump 10 can be converted into the electric energy data 343vis in a state in which it can be confirmed and visualized.

In addition, the rainfall amount data processing unit 382 of the unknown water analysis unit 38, like the power amount data processing unit 381, moves the original rainfall data 342org acquired from the server device of the Meteorological Agency within the data range of the most recent 12 hours. This is a functional unit that performs the averaging process a plurality of times (for example, four times). As a result, the rainfall data processing unit 382 smoothes the waveform represented by the rainfall data 342org and converts it into the rainfall data 342vis in a state in which the rainfall time period is emphasized and visualized so as to be confirmed.

The data processing result presentation unit 384 is a functional unit that simultaneously displays the power amount waveform of the power amount data 343vis and the rainfall amount waveform of the rainfall amount data 342vis on the display unit 33 to visualize and present them in a comparable state. be.

The analysis processing unit 383 analyzes the power amount data 343vis converted by the power amount data processing unit 381 and the rainfall amount data 342vis converted by the rainfall amount data processing unit 382 to determine changes in the power amount based on the power amount waveform. It is a functional part that analyzes unknown water according to the correlation between rainfall changes based on rainfall waveforms and rainfall waveforms.

Specifically, as shown in FIG. 7, the analysis processing unit 383 compares the power amount waveform of the power amount data 343vis and the rainfall amount waveform of the rainfall amount data 342vis by pattern matching, and the degree of matching is a predetermined value. It is determined that there is a correlation when a certain degree of similarity is recognized, such as a ratio (which can be set arbitrarily) or more.

In this case, the analysis processing unit 383 determines the degree of agreement between the rainfall amount waveform of the rainfall range RR obtained by the moving average in the rainfall amount data 342vis and the power amount waveform of the actual rain influence range EF of the power amount data 343vis. Based on this, it is analyzed whether it corresponds to "(1) no rainfall effect", "(2) direct inflow", or "(3) direct inflow + delayed inflow".

For example, in FIG. 7, a constant amount of rainfall (7.5 mm) can be confirmed in the rainfall range RR by the moving average of the rainfall amount waveform of the rainfall amount data 342vis, and the power amount waveform of the power amount data 343vis is rising rightward. Moreover, it can be confirmed that the rising timing of the electric energy waveform and the rising timing of the rainfall waveform are the same, and that the falling timing of the electric energy waveform and the falling timing of the rainfall waveform are also the same. Although the decrease in the electric energy waveform is slightly slower than the decrease in the amount of rainfall, it can be recognized that it quickly converges to a certain level from the fall timing.

Therefore, the analysis processing unit 383 determines that the degree of coincidence between the rainfall waveform and the electric energy waveform is equal to or higher than a predetermined ratio, and that the electric energy waveform and the rainfall waveform follow the rise timing and the fall timing of the electric energy waveform and the rainfall waveform. Therefore, it is considered that there is a correlation between the two, and it is possible to obtain the analysis result (“(2) direct inflow”) that there is a high possibility of “direct inflow due to rainfall”.

In FIG. 8, the rainfall amount data 342vis shows a constant amount of rainfall in the moving average rainfall range RR, whereas the power amount data 343vis shows little change in the amount of power. , there is no correlation between the two. In such a case, the analysis processing unit 383 can obtain an analysis result (“(1) no rain effect”) indicating that the matching degree of the waveform pattern falls below a predetermined ratio, and that it corresponds to “no rain effect”. can.

In addition, in FIG. 9, comparing the rainfall amount waveform of the rainfall amount data 342vis and the power amount waveform of the power amount data 343vis, it can be said that both waveforms are not necessarily similar (the degree of coincidence exceeds a predetermined ratio). below).

However, the rise timing of the increase in the power amount waveform based on the power amount data 343vis follows the increase timing of the rainfall amount waveform based on the rainfall amount data 342vis, and the fall timing of the decrease in the power amount waveform based on the power amount data 343vis follows. It follows the fall timing of the decrease of the rainfall waveform. In other words, there is a high possibility of direct inflow due to rainfall in this area.

In addition, although the fall timing of the decrease of the power amount waveform follows the fall timing of the decrease of the rainfall amount waveform, even if the rainfall amount becomes 0, the power amount does not sufficiently decrease to the level before the increase, The decreasing speed of the electric energy waveform draws a gentler curve than the decreasing speed of the rainfall waveform. In other words, there is a high possibility that unknown water is delayed inflow due to ground seepage in this part. Therefore, comprehensively, it is possible to obtain an analysis result (“(3) direct inflow + delayed inflow”) that there is a high possibility of direct inflow due to rainfall and delayed inflow due to ground seepage.

Therefore, in FIG. 9, although the degree of matching as a waveform pattern between the rainfall amount waveform of the rainfall amount data 342vis and the power amount waveform of the power amount data 343vis is not high, the rising timing and the falling edge, which are waveform change points, are not high. A certain degree of similarity is observed in the coincidence of timing, so it is considered that there is at least a certain degree of correlation between the two.

For example, FIGS. 10A and 10B show the results of comparison between the rainfall amount waveform of the rainfall amount data 342vis and the power amount waveform of the power amount data 343vis detected when it rained on different days at the same point. there is

In this case, "(3) direct inflow + delayed inflow" can be considered on the rainy day (May 21, 2019) in FIG. July 18, 2018), the amplitude level of both the electric energy waveform and the rainfall waveform is small, so the influence of rainfall is small, and the analysis result is that it is not "(3) direct inflow + delayed inflow". can be done.

The analysis result storage processing unit 385 stores the analysis results obtained by the analysis processing unit 383 (“(1) no rainfall effect”, “(2) direct inflow”, or “(3) direct inflow + delayed inflow”). It is a functional unit that stores the analysis result data 344 represented in the storage unit 34 .

By the way, the inspection location estimation unit 39 of the control unit 37 also estimates the installation location of the manhole to be inspected by using the analysis result data 344 and the smart meter identification information based on the inspection location estimation program 341, and performs the estimation. The result data 345 is held in the storage unit 34 together with the analysis result data 344 .

An unknown water analysis processing procedure by the unknown water analyzer 30 having such a configuration will be described. As shown in FIG. 11, the unknown water analysis unit 38 of the control unit 37 first acquires power amount data 343 supplied from the power usage amount measurement unit 21 of the smart meter 20 installed in the manhole pump 10. (Step sp1). At this time, the unknown water analysis unit 38 also acquires the unique smart meter identification information of the manhole pump 10 via the data acquisition unit 31 .

Since the unknown water analysis unit 38 can recognize the installation location of the manhole pump 10 based on the smart meter identification information, the rainfall data 342 corresponding to the installation location is obtained from the Meteorological Agency server via the data acquisition unit 31. acquire (step sp1).

As a result, the unknown water analysis unit 38 associates the rainfall amount data 342 of the installation location of the manhole pump 10 with the power amount data 343 of the smart meter 20 installed in the manhole pump 10 and stores them in the storage unit 34. be able to.

The unknown water analysis unit 38 applies a weighted average process and a moving average process to the original power amount data 343org, thereby approximating changes in the power amount data 343org of the manhole pump 10 to changes in actual rainfall. The power amount waveform (approximate waveform) of the amount data 343vis is converted (step sp2).

In addition, the unknown water analysis unit 38 smoothes the waveform represented by the rainfall data 342org by performing moving average processing four times on the original rainfall data 342org within the data range of the most recent 12 hours, thereby smoothing the waveform represented by the rainfall data 342org. It is converted into rainfall data 342vis of an approximate waveform visualized by highlighting the time zone (step sp2).

Next, the unknown water analysis unit 38 compares the power amount waveform of the power amount data 343vis and the rainfall amount waveform of the rainfall amount data 342vis by pattern matching, and determines whether or not there is a correlation between the two (step sp3). ).

The unknown water analysis unit 38 determines whether or not the increase in the power amount waveform based on the power amount data 343vis follows the increase in the rainfall amount waveform based on the rainfall amount data 342vis (step sp4). A negative result is obtained for (step sp4: No), and a positive result is obtained if it follows (step sp4: Yes).

If the increase in the power amount waveform does not follow the increase in the rainfall amount waveform, the unknown water analysis unit 38 determines that this corresponds to the case of FIG. Therefore, the unknown water is not generated in the first place, that is, the analysis result of "(1) no influence of rainfall" is obtained, and the processing is terminated (step sp5).

When the increase in the waveform of the amount of electric power follows the increase in the waveform of the amount of rainfall, the unknown water analysis unit 38 further determines that the waveform of the amount of electric power gradually descends from an upward sloping state, as shown in FIG. (step sp6).

The unknown water analysis unit 38 determines that the case of FIG. 7 corresponds to the case in which the power amount waveform does not gradually descend from an upward sloping state (step sp6: No), and there is a possibility of direct inflow due to rainfall. is high (“(2) direct inflow”) (step sp7).

On the other hand, the unknown water analysis unit 38 determines that the case of FIG. An analysis result (“(3) direct inflow+delayed inflow”) is obtained indicating that there is a high possibility of both delayed inflows of groundwater and the like (step sp8).

Next, the unknown water analysis unit 38 similarly determines whether or not the waveform of the amount of electric energy on other rainy days is a waveform pattern in which the waveform gradually descends from an upward sloping state (step sp9).

If the power waveform pattern is not the same on other rainy days (step sp9: No), the unknown water analysis unit 38 determines that it corresponds to the case of FIG. Although there are both possibilities of inflow (“(3) direct inflow + delayed inflow”), the effect of rainfall is small. (Step sp10).

On the other hand, if the power waveform pattern is the same on other rainy days (step sp9: Yes), the unknown water analysis unit 38 determines that "(3) direct inflow and delayed inflow" due to rainfall is significant because rainfall has a large effect. After obtaining the analysis result that the possibility is high (step sp11), the process is terminated.

After that, the inspection location estimation unit 39 estimates the installation location of the manhole pump 10 where direct inflow and delayed inflow are thought to occur due to the influence of rainfall based on the smart meter identification information, and inspects for damage to pipes, etc. The installation location can be presented on the display unit 13 as the area to be inspected.

According to the first embodiment described above, the unknown water analyzer 30 detects unknown water flowing into the manhole based on the correlation between the actual rainfall change and the power consumption change of the manhole pump 10 . It is possible to determine with high accuracy whether the cause is "(1) no rainfall effect", "(2) direct inflow", or "(3) direct inflow + delayed inflow".

In particular, the unknown water analysis unit 38 of the unknown water analyzer 30 generates approximate waveform power amount data 343app in consideration of the actual rainfall influence range EF from the original power amount data 343org. By applying moving average processing to the data, it is possible to obtain the electric energy data 343vis corresponding to the change in the actual amount of rainfall.

In addition, when the unknown water analysis device 30 analyzes that the possibility of direct inflow is high, or the possibility of direct inflow and delayed inflow is high, the direct inflow based on the installation location of the manhole pump 10 at the time of analysis Also, it is possible to present locations where damage to piping or the like that may cause delayed inflow should be investigated. As a result, the operator can quickly and easily discover the damage to the pipes, etc., and perform maintenance such as repair or replacement.

[3] Second Embodiment Next, an unknown water analyzer 30 according to a second embodiment will be described. The unknown water analysis apparatus 30 in the second embodiment basically has the same configuration as that in the first embodiment, and the only difference is the processing performed by the analysis processing section 383 of the unknown water analysis section 38 .

In the analysis processing unit 383, as shown in FIG. 12, there is a mutual correlation based on the power amount data 343vis (eg, FIG. 9) and the rainfall amount data 342vis (eg, FIG. 9), and there is an influence of rainfall. A section to be analyzed that is likely to exist (hereinafter referred to as an "analysis section") is extracted. Specifically, when the analysis processing unit 383 determines that there is a correlation between the power amount waveform and the rainfall amount waveform, a wider range including the rising timing and the falling timing of the power amount data 343vis is analyzed. Extract.

The analysis processing unit 383 calculates the amount of power corresponding to the direct inflow (hereinafter referred to as the “direct inflow power amount moving average result”) according to the following equation (1) using the power amount in each time period in this analysis section. ) can be obtained. Here, the direct inflow coefficient P is a value calculated by using a nonlinear analysis method for the rainfall amount data 342vis and the electric energy data 343vis, and is 0<P<1.0.
Direct inflow power amount moving average result = rainfall data 342 vis × direct inflow coefficient P (1)

Also, the analysis processing unit 383 uses the power amount in each time period in this analysis section to calculate the power amount corresponding to the delayed inflow (hereinafter referred to as the "delayed inflow power amount moving average result”) can be obtained. Here, the delayed inflow coefficient Q is a value calculated by using a nonlinear analysis method for the rainfall amount data 342vis and the power amount data 343vis, and is 0<Q<1.0. However, P+Q≤1.0. Here, the symbol "^" means exponentiation.
Delayed inflow power amount moving average result = rainfall data 342 vis × delayed inflow coefficient Q × ((reference time + elapsed time) ^ decay rate) ………(2)
That is, it means that it becomes (reference time+elapsed time) to the power of "attenuation rate".

In this case, it is considered that the amount of rainwater that has penetrated into the underground (hereinafter referred to as "delayed inflow water") intruding into the pipeline will decrease over time. This rate of decrease is defined as "attenuation rate". Therefore, if the rainfall 30 minutes ago permeates underground and enters the pipeline as delayed inflow water, the moving average result of the delayed inflow power amount is the rainfall data 342 vis × delayed inflow coefficient Q × (( It can be expressed by the reference time + 30 minutes)^decay rate). The sum of the values obtained by repeatedly calculating this up to an arbitrary point n is the moving average result of the amount of delayed inflow electric power. If it is difficult to specify an arbitrary point n, a fixed threshold value such as 48 hours before may be set. This attenuation factor can also be calculated by a nonlinear analysis method in the same manner as the delayed inflow coefficient Q. FIG. Note that 30 minutes = elapsed time.

As a result, the analysis processing unit 383 can decompose the power amount data 343 vis into the direct power amount moving average result and the delayed power amount moving average result. Based on the result, it is also possible to obtain the determination result of which has a greater influence.

For example, when there is only direct inflow due to rainfall, the analysis processing unit 383 can obtain the value of the moving average result of the amount of direct inflow electric power, but the value of the moving average result of the amount of delayed inflow electric power is 0 or almost 0. In this way, the analysis processing unit 383 can obtain analysis results that quantify the direct inflow and the delayed inflow.

[4] Other Embodiments In the first and second embodiments described above, the analysis processing unit 383 of the unknown water analysis unit 38 detects unknown water based on the correlation between the power amount waveform and the rainfall amount waveform. Although the case of analyzing water has been described, the present invention is not limited to this, and the operator himself/herself can The cause of unknown water may be analyzed.

Furthermore, the above-described flowchart (FIG. 12) by the unknown water analyzer 30 is an example for explaining the flow of processing up to analysis of unknown water, and is not limited to this. That is, each step of the flowchart by the unknown water analyzer 30 is a specific example, and is not limited to this flow. For example, the order of some steps may be changed, another process may be inserted between the processes of each step, and in some cases the processes of some steps may be performed in parallel. .

DESCRIPTION OF SYMBOLS 10... Manhole pump, 20... Smart meter, 21... Electric power consumption measurement part, 22... Smart meter storage part, 25... Communication processing part, 30... Unknown water analyzer, 31... Data acquisition part, 32... Input part, 33 Display unit 34 Storage unit 35 Bus 37 Control unit 38 Unknown water analysis unit 381 Power amount data processing unit 382 Rainfall amount data processing unit 383 Analysis processing unit 384 Data Processing result presentation unit 385 Analysis result storage processing unit 39 Inspection point estimation unit 100 Unknown water analysis system.

Claims (7)

An unknown water analysis method for analyzing unknown water flowing into a sewage pipe from the outside,
an electric energy acquisition step of acquiring electric energy data of a pump facility for pumping out sewage flowing through the sewage pipe from a digital electric energy meter by an electric energy acquisition unit;
a rainfall acquisition step of acquiring rainfall data representing the amount of rainfall at the location of the pump equipment by a rainfall acquisition unit;
an unknown water analysis step of analyzing the unknown water by an unknown water analysis unit according to a correlation between a change in the power amount waveform based on the power amount data and a change in the rainfall amount waveform based on the rainfall amount data. Water analysis method. The unknown water analysis step determines that the unknown water is not affected by rain when it is determined that the correlation does not exist between the power amount waveform and the rainfall amount waveform. Water analysis method. In the unknown water analysis step, if the pattern of increase and decrease of the power amount waveform based on the power amount data follows the pattern of increase and decrease of the rainfall amount waveform based on the rainfall amount data, the unknown water is rainfall. 2. The method for analyzing unknown water according to claim 1, wherein the water is determined to be due to direct inflow by In the unknown water analysis step, the increase in the power amount waveform based on the power amount data follows the increase in the rainfall waveform based on the rainfall amount data, and the decrease in the power amount waveform is gentler than the decrease in the rainfall amount waveform. 2. The method of analyzing unknown water according to claim 1, wherein the unknown water is determined to be due to direct inflow due to rainfall and delayed inflow due to underground infiltration, if . In the unknown water analysis step, smoothing is performed by performing moving average processing on the power amount data,
The unknown water analysis method according to any one of claims 1 to 4, wherein, in said unknown water analysis step, said rainfall data is smoothed by performing a moving average process. An unknown water analyzer for analyzing unknown water flowing into a sewage pipe from the outside,
a power acquisition unit that acquires, from a digital power meter, power data of a pump facility that pumps out sewage flowing through the sewage pipe;
a rainfall acquisition unit that acquires rainfall data representing the amount of rainfall at the location of the pumping equipment;
An unknown water analyzer, comprising: an unknown water analysis unit that analyzes the unknown water according to a correlation between changes in the power amount waveform based on the power amount data and changes in the rainfall amount waveform based on the rainfall amount data. An unknown water analysis program for analyzing unknown water flowing into a sewage pipe from the outside,
to the computer,
an electric energy acquisition step of acquiring electric energy data of a pump facility for pumping out sewage flowing through the sewage pipe from a digital watt-hour meter;
a rainfall acquisition step of acquiring rainfall data representing rainfall at the location of the pumping equipment;
an unknown water analysis step of analyzing the unknown water in accordance with the correlation between changes in the power amount waveform based on the power amount data and changes in the rainfall amount waveform based on the rainfall amount data.

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