KR20170077474A - A real time loss computation method by minimum night flow - Google Patents
A real time loss computation method by minimum night flow Download PDFInfo
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- 238000004458 analytical method Methods 0.000 claims abstract description 20
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- 230000007423 decrease Effects 0.000 claims description 9
- 230000003247 decreasing effect Effects 0.000 claims description 4
- 238000000611 regression analysis Methods 0.000 claims description 4
- 238000005259 measurement Methods 0.000 claims description 3
- 230000002354 daily effect Effects 0.000 description 14
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Abstract
In the present invention, when an event in which a minimum flow value changes occurs, it is initialized to reflect the occurrence of the event, and the minimum flow value is determined as a property. The method of calculating the minimum flow value is a method The present invention relates to a system for calculating a loss by a real-time daily minimum flow rate interval reflecting an occurrence of an event that can calculate a usage amount and a loss amount in real time, 1) collecting flow data at each point; 2) correcting the data; 3) extracting data for analysis; 4) determining the lowest flow rate; 5) Estimating the nighttime use of the lowest flow rate day; 6) calculating the nighttime usage of all days; 7) determining whether a new nighttime minimum flow value has occurred; 8) when a new minimum flow rate value has occurred, returning to step 4) and re-valuating the lowest flow rate value; 9) analyzing the daily nighttime usage and leakage when the new nighttime minimum flow value does not occur; 10) judging whether or not an event has occurred and returning to step 4) if the event occurs, re-valuing the minimum flow value; 11) judging whether or not an event has occurred and calculating the daily minimum data if an event does not occur; 12) Estimating the remaining value obtained by subtracting the minimum data value for each day from the minimum data value to the night minimum use amount.
Description
More particularly, the present invention relates to a system for estimating a loss amount, and more particularly, to an apparatus and method for estimating a minimum flow amount when an event that fluctuates a minimum flow amount occurs, The present invention relates to a system for estimating a loss by a real-time daily minimum flow rate interval reflecting the occurrence of an event that can estimate a minimum usage and a loss amount of a customer in real time through trend analysis of data.
Conventional simple meter based total water inventory analysis method is collected in real time in case of supply flow per zone (small block), but real time analysis of water usage / loss amount is impossible because consumer meter reading data is collected monthly. Also, in the case of the customer meter reading data, since the inspection zone is divided and examined even in the zone (small block), the meter reading date is different even in the small block. Therefore, the difference between the collection time of the supply flow data and the collection time of the water consumption and loss data, etc., is summed to the incorrect water consumption.
In order to solve this problem, the applicant of the present invention analyzes the pattern of the flow rate data of the minimum flow rate (occurring at night time) in the supply flow rate data collected every day, and divides the flow rate data into three sections such as a reduced portion, The trends in the number of active population according to time zone, the types of industries such as residential / commercial / industrial, living standards according to living standards, and climate are different. Therefore, we analyze trends by regression analysis of these various factors , Thereby registering a patent (Korean Patent No. 10-1042176) for estimating the minimum use amount and loss amount at night.
However, there is a problem that the real-time usage amount and loss estimation method can not be applied when an event that changes the overall usage pattern occurs. Therefore, it is required to develop a technology capable of continuously estimating the amount of real-time usage and loss in the event of occurrence of such an event.
SUMMARY OF THE INVENTION The present invention has been made in view of the above problems, and it is an object of the present invention to provide a method of estimating a minimum flow rate value by initializing a minimum flow rate value when an event occurs, The present invention provides a system for estimating a loss amount by analyzing a real time daily minimum flow amount interval reflecting an occurrence of an event that can calculate a minimum use amount and a loss amount of a customer in real time.
According to an aspect of the present invention, there is provided a system for estimating a loss by a real-time daily minimum flow section analyzing an event, comprising: 1) collecting flow data at each point; 2) correcting the data; 3) extracting data for analysis; 4) determining the lowest flow rate; 5) Estimating the nighttime use of the lowest flow rate day; 6) calculating the nighttime usage of all days; 7) determining whether a new nighttime minimum flow value has occurred; 8) when a new minimum flow rate value has occurred, returning to step 4) and re-valuating the lowest flow rate value; 9) analyzing the daily nighttime usage and leakage when the new nighttime minimum flow value does not occur; 10) judging whether or not an event has occurred and returning to step 4) if the event occurs, re-valuing the minimum flow value; 11) judging whether or not an event has occurred and calculating the daily minimum data if an event does not occur; 12) Estimating the remaining value obtained by subtracting the minimum data value for each day from the minimum data value to the night minimum use amount.
In the present invention, the step 5) includes the steps of: a) dividing the data to be analyzed into a reduction part, a base part and an increasing part; b) generating a trend line by applying a decreasing portion and an increasing portion; c) subtracting the lowest value of the polynomial trend line from the minimum flow rate of the collected flow measurement data at night, and so on.
In the step b) of the present invention, it is preferable to generate a trend line by using a polynomial of the regression analysis.
Also, in the present invention, it is preferable that the event is any one of a block boundary change, a watering population increase / decrease, an additional counterparty generation, or a pipe breakage / restoration.
In addition, in the step 10) of the present invention, d) selecting a period of at least one month after the occurrence of the event; and e) determining that an event has occurred when the change of the increase or decrease after the occurrence of the event has changed by at least a week or more.
Also, in the present invention, it is preferable that the step 12) is performed by subtracting the minimum data value for each day from the minimum data value excluding the daily minimum value data period during the analysis period, and estimating the minimum data amount at the night.
According to the present invention, it is possible to estimate, in real time, the minimum usage and loss amount at night of the customer through trend analysis of the flow data occurring at night time. In particular, The method of determining the minimum usage and loss amount has the advantage of real time calculation of the minimum usage and loss at night in real time despite various events.
FIG. 1 is a flow chart of a system for calculating a loss amount by analyzing a real-time daily minimum flow amount interval reflecting an event occurrence according to an embodiment of the present invention.
2 is a diagram showing a configuration of a flow data collection system.
3 is a flowchart of a trend analysis method according to an embodiment of the present invention.
Figures 4-11 are graphs showing flow data for various examples of event generation.
Hereinafter, a specific embodiment of the present invention will be described in detail with reference to the accompanying drawings.
As shown in FIG. 1, the system for calculating a loss by the real-time daily minimum flow section analyzing the occurrence of events according to the present embodiment starts with step S110 of collecting flow data at each point. In this step S110, data on the flow rate of use (collected data in units of one minute) for each time period collected through the system as shown in Fig.
Next, the step of correcting the data (S120) proceeds. This step (S120) is a step that proceeds according to necessity. When negative or zero data occurs, it is corrected using a test operation pattern or past history data.
Next, a step of extracting data for analysis (S130) is performed. In this step (S130), data on the selected section of the entire data is extracted as analysis target data and proceeded. Of course, when the correction is performed in the previous step S120, the corrected data is used, and the collected data is divided into 10 parts.
Next, step S140 of understanding the lowest flow rate and step S150 of calculating the night flow rate of the lowest flow rate are performed. Although these steps S140 and S150 are separately described, they are actually subjected to a calculation process together to obtain a result value. In this embodiment, the lowest flow rate and the night flow rate can be obtained by the analytical method as shown in Fig.
As shown in FIG. 3, this step includes: a step S40 of dividing the analysis target data into a reduction part, a base part, and an increasing part; a step S50 of generating a trend line by applying a decreasing part and an increasing part; A step of subtracting the minimum value of the polynomial trend line from the minimum flow rate of the flow measurement data at night (S70), and the like. Here, in the step of generating the trend line, it is more preferable to generate the trend line by using the multiple expression of the regression analysis.
Next, a step S160 for calculating the nighttime use amount of all days is performed. In this step S160, the same method is repeated to perform an operation for calculating the nighttime usage for all the days to monitor the nighttime usage change.
Next, the step of determining whether a new nighttime minimum flow value has occurred is proceeded (S170). In step S160, it is determined whether a new nighttime minimum flow value has occurred. If a new minimum nighttime flow value has occurred, the process returns to step S140 to determine the minimum flow value in step S180. If the new nighttime minimum flow value does not occur, a step of performing the daily nighttime use amount and leakage analysis (S190) is performed. Of course, the method of analyzing the nighttime use amount and leakage amount per day is based on the trend analysis method described above.
Next, in step S210, it is determined whether or not an event is generated and a minimum flow rate value is determined when an event occurs. Here, the term 'event' refers to a case where a continuous change occurs in the usage amount or the usage pattern, and it is preferable that the event is any one of block boundary change, watering population increase, additional generation of customers, or pipe breakage / restoration.
Representative examples of changes in usage when these events occur are as follows.
First, as shown in FIGS. 4 and 5, the minimum flow rate at night increases and the nighttime flow rate increases overall. The cause of this phenomenon is the occurrence of one or more events such as an increase in water leakage due to pipeline damage, an increase in water supply population, or a change in block boundary.
On the other hand, as shown in Figs. 6 and 7, the difference between the average flow rate and the day / night flow rate continuously increases. The cause of this phenomenon is the increase in the population of water, or the occurrence of one or more of the events such as the occurrence of additional customers or block boundary change.
Also, as shown in Figs. 8 and 9, the minimum flow rate at night and the night time flow rate are continuously decreased. The cause of this phenomenon is the occurrence of one or more of events such as water leakage reduction due to pipeline restoration, water population decrease, or block boundary change.
Also, as shown in Figs. 10 and 11, the difference between the average flow rate and the day / night flow rate continuously decreases. The cause of this phenomenon is the occurrence of one or more of the following events: population decline, population increase, or block boundary change.
Step S210 of determining whether or not the event has occurred may include selecting a period of at least one month or more after the occurrence of the event, and determining whether an event occurs when the change in the increase or decrease after the occurrence of the event has changed by at least a week or more Stage of the process. That is, it is judged whether the phenomenon that the increase or decrease change value exceeds ± 50% of the reference data lasts more than a week.
As a result of the determination, when the event occurs, it is determined that the new minimum flow value has occurred, and the flow returns to the step of calculating the minimum flow amount and the night use amount to newly calculate the lowest flow amount and the night use amount.
In step S220, it is determined whether or not an event has occurred, and in the event that an event does not occur, step S220 of calculating daily minimum data is performed. In other words, the minimum data is calculated by analyzing the daily minimum flow interval in real time, and the trend analysis method is also used for calculating the minimum data.
Next, a step S230 of estimating the residual value obtained by subtracting the minimum data value for each day from the minimum data value as the minimum nighttime consumption amount is performed. In this step S230, the minimum data amount at each day is subtracted from the minimum data value except for the daily minimum value data period, and the minimum nighttime use amount is calculated by estimating the minimum data amount at the night.
10: central control unit 11: input unit
12: Display part 13: Dry water amount calculation module
14: Daily oil yield / leakage analysis module
15: input-based leakage calculation module
16: Daily oil yield / leakage analysis module
Claims (6)
2) correcting the data;
3) extracting data for analysis;
4) determining the lowest flow rate;
5) Estimating the nighttime use of the lowest flow rate day;
6) calculating the nighttime usage of all days;
7) determining whether a new nighttime minimum flow value has occurred;
8) when a new minimum flow rate value has occurred, returning to step 4) and re-valuating the lowest flow rate value;
9) analyzing the daily nighttime usage and leakage when the new nighttime minimum flow value does not occur;
10) judging whether or not an event has occurred and returning to step 4) if the event occurs, re-valuing the minimum flow value;
11) judging whether or not an event has occurred and calculating the daily minimum data if an event does not occur;
12) Estimating the remaining value obtained by subtracting the minimum data value for each day from the minimum data value as the minimum nighttime consumption amount, and calculating the loss amount by analyzing the real time daily minimum flow amount interval reflecting the occurrence of the event.
a) dividing the data to be analyzed into a reduction part, a base part and an increasing part;
b) generating a trend line by applying a decreasing portion and an increasing portion;
and c) subtracting the minimum value of the polynomial trend line from the minimum flow rate of the collected flow measurement data at a time of a minimum time.
A trend line is generated by using a multivariate equation of regression analysis.
A block boundary change, a water population increase / decrease, an additional generation of a customer, or a pipeline damage / restoration, based on a real time daily minimum flow rate analysis.
d) selecting a period of at least one month after the occurrence of the event;
and e) determining that an event has occurred when the change of the increase or decrease after the occurrence of the event has changed by at least one week. The system for estimating the loss by real-time daily minimum flow interval analysis reflecting the event occurrence.
The minimum data value of each day is subtracted from the minimum data value excluding the daily minimum value data interval during the analysis period, and the minimum data value is calculated as the minimum minimum usage amount at the nighttime.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115419837A (en) * | 2022-07-27 | 2022-12-02 | 大连莱立佰信息技术有限公司 | Method for judging leakage quantity of secondary water supply pipe network based on minimum flow of outlet of pump station |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| KR101042176B1 (en) * | 2010-08-20 | 2011-06-16 | (주) 그린텍아이엔씨 | Real time loss computation method by using minimum night flow |
| KR101205103B1 (en) * | 2012-04-04 | 2012-11-26 | 한국수자원공사 | System for operating and managing water supply network |
| KR101554981B1 (en) * | 2014-12-16 | 2015-10-06 | (주)엔와이인포텍 | Water supply pipe network management server, system for water supply pipe network management and pipe network management method using the same |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115419837A (en) * | 2022-07-27 | 2022-12-02 | 大连莱立佰信息技术有限公司 | Method for judging leakage quantity of secondary water supply pipe network based on minimum flow of outlet of pump station |
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