KR102522637B1 - Pipe network management system for managing pipe network of waterworks and method of the same - Google Patents

Abstract

The present invention relates to a pipe network management system and operation method for managing distributed water supply, and a pipe network management server system according to an embodiment collects data obtained by measuring the flow rate of constant water measured for a certain period of time from an instrument installed in a block A collection server controls to classify and record the collected data for each instrument, identify missing data in the measured data, replace the identified missing data with preset data, and control the missing data to be supplemented and recorded. It may include a server and a database server that records data in which the missing data is compensated for in a database.

Description

Pipe network management system for managing pipe network of waterworks and method of the same}

The present invention relates to a pipe network management system and operation method for managing distributed water supply.

The tap water we use at home is supplied to each household or consumer through a water source, a water purification plant, and a reservoir. At this time, it is difficult to properly manage water quality or maintain and manage the pipe network through the pipe network that is tangled like a spider's web from the water purification plant to the consumer.

Accordingly, recently, a project to block the water supply network is being conducted in order to optimize the management of the water supply network and to increase the water flow rate. For reference, the water flow rate is the ratio of the tap water produced at the water purification plant that is collected as fee income.

The water pipe block project, for example, divides the large blocks divided by water supply system of the water purification plant into medium blocks with a scale of 2,000 to 5,000 hydrants, and divides each medium block into small blocks with a scale of 500 to 1,000 hydrants to build a water pipe network. It consists of large, medium, and small blocks in a checkerboard pattern, and through real-time monitoring and analysis of the quantity, water quality, and pressure of each block, it is possible to maintain and manage the pipe network more systematically and efficiently.

In particular, as the waterworks pipe network is blocked and maintained remotely, it is economical in terms of cost because there is no need to deploy functional personnel on site, and the whereabouts of the flow can be tracked to solve the problem of increasing the water flow rate and the amount of water leakage , total flow rate and individual flow rate for each house can be accurately identified, making it possible to charge more fair rates.

A general water supply network management system is composed of a monitoring system of measurement data (flow rate, water pressure, water quality) collected on site and an analysis system that processes and analyzes the collected data. Currently, the water pipe network is being changed from a simple pipe network with dendrite knowledge to a block-type pipe network system in order to introduce easy maintenance and effective analysis techniques.

This block-type pipe network structure is easy to manage appropriate flow rate, water pressure, and water quality, and has the advantage of being efficient in diagnosing the effects of pipe network maintenance priorities and old pipe improvement construction by providing block-level oil/leakage analysis results. The water supply network management system according to this block-type pipe network system is built by the system construction process shown in FIG. By storing and analyzing oil/leakage using block system-based flow/water pressure data, high operational effects were expected.

Korean Patent Publication No. 10-2008-0005694 "Remote Integrated Water Leakage Monitoring System and Method" Korean Patent Registration No. 10-0938496 "Remote control monitoring system for water supply pipeline"

An object of the present invention is to provide a technology for quickly and accurately detecting and analyzing water leakage and water leakage by managing a pipe network supplying constant water to each block.

An object of the present invention is to increase the reliability of flow rate measurement in order to utilize the flow rate of constant water for various analyzes during a certain period of time.

The pipe network management server system according to an embodiment includes a collection server for collecting data obtained by measuring the flow rate of constant water measured for a certain period of time from an instrument installed in a block, and controlling the collected data to be classified and recorded for each instrument, wherein the measurement A FEP server that identifies missing data in the identified data, replaces the identified missing data with preset data, and supplements and records the missing data, and a database server that records the data supplemented with the missing data in a database. can

According to an embodiment, the FEP server may determine and identify the occurrence of the missing data when the measured time-minute data and field data are different.

In the FEP server according to an embodiment, the missing data includes a time value, instantaneous data, and accumulated data, the time value inputs a time value at a point in time when the missing occurs, and inputs the instantaneous data and the accumulated data. can be entered as a null value.

According to an embodiment, the database server may search for data for which the missing data is supplemented, identify abnormal data, and classify and record the identified abnormal data.

According to an embodiment, the database server divides the data for which the missing data is supplemented into instantaneous data or accumulated data divided by minute to determine whether or not there is abnormal data, and identifies and records the data as abnormal data according to the determination result. can

The database server according to an embodiment may determine that the instantaneous data is abnormal data when the size is 0 or greater than the maximum value.

According to an embodiment, the database server may determine abnormal data when the size of the accumulated data is greater than or equal to 10 times or less than or equal to 0.1 times the size of the accumulated data immediately before entering the normal value.

According to an embodiment, the database server may correct the identified abnormal data by reflecting a weight to information on other days measured at the same time.

According to an embodiment, the database server identifies at least one or more abnormal data determined to be abnormal data, calculates a previous normal integration value and an immediate integrated integration value of the identified at least one or more abnormal data, and immediately after the calculated integration value. The integration difference is calculated from the difference between the normal integration value and the previous normal integration value, and when the number of the identified at least one or more abnormal data is 1, a value obtained by dividing the integration difference in half can be used to calculate the instantaneous data.

According to an embodiment, when the number of the identified at least one or more pieces of data is two or more, the database server calculates past average supply amounts for each of the identified at least one or more pieces of data, and Among the one or more abnormal data, the first correction data is calculated by reflecting the weights preset for the past average supply amounts calculated for the Nth or more data, and the first correction is made for the identified at least one or more abnormal data. summing up the data, generating secondary correction data by distributing the integrated difference to correspond to the primary correction data based on a ratio between each of the primary correction data and the sum data, and generating the generated secondary correction data; At least one or more of the identified data may be corrected as data.

A method for managing measurement data during pipe network management according to an embodiment includes loading measurement data stored in a database after recording in units of minutes for a predetermined time, reading instantaneous data in units of N hours and minutes from the loaded measurement data The first step, the second step of comparing the read instantaneous data and the field data to determine whether or not they are missing, the third step of supplementing the missing data in the unit of N hours and minutes when the data is missing as a result of the determination, and the constant time A fourth step of repeating the first to third steps by increasing the unit of N time minutes within

According to an embodiment, the predetermined time period is 24 hours, and the unit of N hours and minutes increases by 1 minute from 1 minute to 1440 minutes.

The on-site data according to an embodiment is characterized in that all missing parts among machine-measured data are template data supplemented.

The measurement data according to an embodiment is characterized in that it includes instantaneous data measured by a measuring instrument installed in each block of the waterworks pipe network in units of minutes for a day and integrated data in which the instantaneous data is accumulated.

Determining whether the measurement data is abnormal, checking whether or not there is abnormal data in a related field when the measurement data is abnormal data as a result of the determination, and storing abnormal data in a related field among the measurement data according to an embodiment. The method may further include a step of correcting the abnormal data for which is checked.

The step of determining whether the measurement data is abnormal according to an embodiment includes determining whether the instantaneous data is abnormal, but determining the instantaneous data as abnormal data when the size of the instantaneous data is 0 or greater than a maximum value. can do.

The step of determining whether the measurement data is abnormal according to an embodiment may include determining whether or not the accumulated data is abnormal, but the magnitude of the accumulated data is 10 times greater than or greater than 0.1 times that of the previous accumulated data having entered a normal value. A step of determining that the following cases are abnormal data may be included.

The method for managing measurement data during pipe network management according to an embodiment may further include correcting the identified abnormal data by reflecting a weight to information on other days measured at the same time.

According to one embodiment, it is possible to provide a technology for quickly and accurately detecting and analyzing water leakage and water leakage by managing a pipe network supplying constant water to each block.

According to one embodiment, it is possible to increase the reliability of the flow rate measurement in order to utilize the flow rate of constant water during a certain period of time in various analyses.

FIG. 1 is a diagram explaining water supply distributed to consumers blocked by unit blocks.
2 is a diagram illustrating a pipe network management system for managing distributed waterworks.
3 is a diagram for explaining the data processing flow.
4 is a diagram illustrating an operating method of a pipe network management system for managing distributed water supply.
5A is a diagram illustrating an algorithm for determining missing data and compensating for missing data among methods for managing measurement data.
5B is a diagram for explaining an algorithm for determining abnormal data among methods for managing measurement data.
6A and 6B are diagrams illustrating a specific method of correcting the determined abnormal data.

Specific structural or functional descriptions of the embodiments according to the concept of the present invention disclosed in this specification are only illustrated for the purpose of explaining the embodiments according to the concept of the present invention, and the embodiments according to the concept of the present invention These may be embodied in various forms and are not limited to the embodiments described herein.

Embodiments according to the concept of the present invention can apply various changes and can have various forms, so the embodiments are illustrated in the drawings and described in detail herein. However, this is not intended to limit the embodiments according to the concept of the present invention to specific disclosures, and includes modifications, equivalents, or substitutes included in the spirit and scope of the present invention.

Terms such as first or second may be used to describe various components, but the components should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another component, for example, without departing from the scope of rights according to the concept of the present invention, a first component may be named a second component, Similarly, the second component may also be referred to as the first component.

It is understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, but other elements may exist in the middle. It should be. On the other hand, when an element is referred to as “directly connected” or “directly connected” to another element, it should be understood that no other element exists in the middle. Expressions describing the relationship between components, such as "between" and "directly between" or "directly adjacent to" should be interpreted similarly.

Terms used in this specification are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, terms such as "comprise" or "have" are intended to designate that the described feature, number, step, operation, component, part, or combination thereof exists, but one or more other features or numbers, It should be understood that the presence or addition of steps, operations, components, parts, or combinations thereof is not precluded.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related art, and unless explicitly defined in this specification, it should not be interpreted in an ideal or excessively formal meaning. don't

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. However, the scope of the patent application is not limited or limited by these examples. Like reference numerals in each figure indicate like elements.

FIG. 1 is a diagram explaining water supply distributed to consumers blocked by unit blocks.

1 shows a block schematic diagram of a water supply network block system in a pipe network structure in the form of a block 140.

In the water purification plant 120, a pipe network is connected to the reservoir 130 toward each grouped small block.

In addition, in the reservoir 130, a pipe network leading to the house is connected through each of the small blocks. In the house divided into each small block, constant water can be supplied and used from the pipe network connected from the water purification plant 120.

For example, the reservoir 130 may include a water regulating valve or a flow meter to monitor the pipe network going to each small block.

The pipe network management system 110 may prevent water leakage while monitoring the flow rate of the pipe network delivered from the water purification plant to the house.

For example, the pipe network management system 110 may query the flow rate and hydraulic pressure for pipe network operation, and query the flow rate and hydraulic pressure for each period of the block and a certain pattern trend.

In addition, the pipe network management system 110 may query the nighttime minimum flow rate and change trends of the minimum flow rate for the corresponding period through the nighttime minimum flow inquiry.

The pipe network management system 110 can query the usage status by block to inquire the trend of monthly usage (fees and provided data) by block, and can calculate the amount of water leakage through analysis of minimum flow at night and overall balance analysis through water leakage calculation do. In addition, the pipe network management system 110 can inquire the effective water quantity (rate quantity, fractional quantity) and invalid quantity (waterworks project quantity, public water quantity, etc.) by inquiring the total quantity balance, and long-term / Short-term supply can be predicted.

The pipe network management system 110 may create a pattern or analyze a pattern through pattern management. Through this, you can analyze and save patterns by month, day, industry, climate (temperature), or analyze patterns created by blocks.

The pipe network management system 110 may analyze the consumer price status for the water flow rate status and inquire the consumer customer status for each block. In addition, the flow rate status can be investigated to inquire the flow rate status by period of the corresponding block, and the flow rate status by block can be compared by comparing the flow rate status by block. In addition, it is possible to manage blocks with low water flow rates by utilizing the comparison results.

In addition, the pipe network management system 110 may inquire the amount of supply, usage, water flow rate, and leakage amount of the year through water flow rate analysis. In particular, the pipe network management system 110 according to an embodiment may discover and correct missing data and abnormal data.

On the other hand, the pipe network management system 110 can manage information registration and change information on blocks through block management, and register and manage reference values and overall water balance reference values when calculating the night minimum flow through reference value management. In addition, through flow rate and pressure data correction, data correction can be processed when abnormal data occurs due to communication failure, and rate and usage data conversion is possible. In addition, the pipe network management system 110 may perform management of alarm reference values by providing a function of loading usage data by customer provided by the tariff department into a DB, and may create alarm conditions and exceptional situations in real-time monitoring.

For example, the basic data database of the pipe network management system 110 may store data on a water supply pipe network measured by an already built basic infrastructure and basic blocks in which actual data are collected in a time-series manner.

'Basic infrastructure' can be interpreted as TM facilities such as on-site instrumentation and control facilities, communication facilities, and networks installed in reservoirs or water purification plants to manage the flow of water. Accordingly, the basic data database may store data continuously measured by the basic infrastructure in a time-series manner.

The pipe network management system 110 is installed in connection with the basic data database, and can reconstruct and store the data of the basic data database for each block information and block code according to the block system shown in the block system diagram shown by the operator interface unit. there is.

The pipe network management system 110 may be provided with a history management function of assigning a system tree code to each block system diagram displayed on the operator interface and individually storing data for the block system diagram.

The pipe network management system 110 may assign a unique system code for each block system diagram to the block system diagram for which consistency is recognized, and individually store data for the block system diagram in a block database. Therefore, data on individual block hierarchy can be immediately retrieved and utilized by utilizing the hierarchy code for a specific block hierarchy.

When a block is changed or a new block is created, the pipe network management system 110 may generate new block information and a block code, and create and store data about the block in a block database.

The pipe network management system 110 is a component that extracts block attribute information from the basic data database when a block is changed or a new block is created on the operator interface unit. Here, 'block attribute information' refers to the area within the boundary of the block, the number of customers, the pipeline, and the altitude information.

When a block is changed or a new block is created on the operator interface unit, the pipe network management system 110 generates a block code for the block, assigns the block code to the extracted block attribute information, and stores it in the block database for each block code. can

2 is a diagram illustrating a pipe network management system 200 for managing distributed waterworks.

The pipe network management system 200 analyzes the flow rate of constants recorded for a certain period of time, for example, one day, to find errors in pre-collected data and correct them.

To this end, the pipe network management system 200 according to an embodiment may include a collection server 240, an FEP server 250, and a database server 260.

A field device (210) installed around each water pipe to collect data measured in the field, a wired and wireless communication network (220), a security network (230), a collection server (240), a FEP server (250), and a DB server (260) ), a management server 270, and a monitoring server 280 may be included.

Looking more specifically, the field device 210 may measure the flow rate, water pressure, and water quality of constant water in units of minutes. Specifically, the field device 210 may include a pressure gauge installed in each block constituting the pipe network to measure the water pressure of constant water for each block, a flowmeter to measure flow rate, and a water quality gauge to measure water quality.

Measurement data on the water pressure, flow rate, and water quality of the constant water measured by the field device 210 may be transmitted to the collection server 240 via the security network 230 through the wired and wireless communication network 220.

The security network 230 can enhance security by providing functions such as IPS, firewall, VPN, and inter-network data transmission device in moving data.

The collection server 240 may serve as a communication gateway. For example, data from field devices of each block may be collected. In particular, the collection server 240 is a hardware collection server, a TM master, various devices or equipment that collects data, and can be interpreted as a device that centrally processes devices for each region to communicate with each other.

The water pressure, flow rate, and water quality data for each block in the waterworks pipe network measured by the field device 210 may be periodically transmitted to the collection server 240 or every predetermined time. In this case, the wired/wireless communication network 220 may be a mobile communication network including a WCDMA network and a dedicated KT line, but is not limited thereto.

The FEP server 250 may control the database server 260 to match various measurement data obtained from the field device 210 for each block and store them in the database.

In particular, the FEP server 250 may control the collected data to be classified and recorded for each instrument. In this process, the FEP server 250 may control to identify missing data in the measured data, supplement the missing data by replacing the identified missing data with preset data, and record the missing data.

Missing data is data at a specific time and minute among recorded time and minute data measured on a minute-by-minute basis, and the measured value may be recorded as blank.

Accordingly, the FEP server 250 may supplement the missing part and transmit it to the database server 260 . Also, the database server 260 may record data in which missing data is supplemented in the database.

In order for the FEP server 250 to determine missing data, it may maintain a reference in the form of a template table measured for a certain time in units of 1 minute. These references can be recorded in an Oracle DB, and can be used to identify missing data in comparison with actually collected measurement data.

A case where missing occurs in data measured at the 1200th time among time-minute data measured at 1-minute intervals for 24 hours may be considered. In this case, the 1200th data of the measurement data is missing, while the 1200th data is recorded in the template table. The FEP server 250 compares these two pieces of information and can confirm that the 1200th data is missing.

For example, the missing data includes time value, instantaneous data, and accumulated data, and the FEP server 250 inputs a time value at the time when the missing occurs in a field of the time value, and fields of the instantaneous data and integrated data. can be entered as a null value.

The management server 270 may process the measurement data recorded in the database and provide various services to the user terminal.

At this time, the user terminal can access the management server 270 through the Internet network and use various services provided by the management server 270 . Here, the user terminal may be a desktop PC, a laptop computer, a workstation, etc., but is not limited thereto, and may be various mobile devices including a smart phone.

For example, the management server 270 may provide a pattern management service for patterning and managing flow rate data stored for each block. Here, in the pattern management service, the user registers the flow rate pattern for a specific block as a user-defined pattern, monitors the flow rate of the block based on the registered user-defined pattern, and determines whether or not the block is leaking in real time to prevent water leakage. A service that can provide alerts.

In order to provide the pattern management service, the management server 270 may acquire and store flow rate data obtained by measuring the flow rate of constant water from the field device 210 . Specifically, the management server 270 may match the flow rate data of each block in the water supply pipe network obtained from the field device 210 to the measured time and store it for each block.

In addition, when a user-defined pattern registration for a specific block is requested from the user terminal, the management server 270 generates a flow rate pattern according to the time of the specific block using stored flow rate data corresponding to a designated period included in the request, The created flow rate pattern can be registered as a user-defined pattern.

Meanwhile, the management server 270 may provide real-time monitoring of the pipe network or various information search services for pipe network operation in addition to the above-described pattern management service. For example, the management server 270 provides a real-time monitoring service for each block of flow rate/water pressure, a flow rate/water pressure inquiry service for each period, a minimum flow rate inquiry service at night, a usage status inquiry service for each block, a nighttime minimum flow rate analysis method, or a total water balance analysis method. It is possible to provide a water leakage calculation service, a water flow rate search service for each period of a specific block, and the like.

In addition, the management server 270 may provide the above-described various services together with various geographic information provided from the GIS server in association with a Geographic Information System (GIS) server.

For the specific method of processing the measurement data obtained from the field device 210 by the management server 270 and the geographic information obtained from the GIS server in order to provide the above service, known technology may be used, and the method of the present invention Since it is irrelevant to the gist, a detailed description thereof will be omitted.

Some of the functions of the management server 270 described above may be implemented through the monitoring server 280 . In addition, the monitoring server 280 may perform monitoring of the flow rate and water pressure of the pipe network (block) or trend monitoring of the flow rate and water pressure of each block.

As an example, a case in which the FEP server 250 supplements and records missing data may be considered.

In this case, the database server 260 may search data for which missing data is supplemented to identify abnormal data, classify the identified abnormal data, and record the identified abnormal data in the database.

The database server 260 may classify data for which missing data has been supplemented into instantaneous data or accumulated data divided by minute to determine whether or not there is abnormal data, and may identify and record the data as abnormal data according to the determination result.

Missing data or abnormal data can be recorded in a pre-designated area in the data field.

The database server 260 may determine the instantaneous data as abnormal data when the size is 0 or greater than the maximum value.

In addition, the database server 260 may determine the data to be abnormal when the size of the integrated data is 10 times or more or 0.1 times or less compared to the previous integrated data that entered the normal value.

The value of integration data compared to the normal value can be appropriately adjusted by a manager.

The database server 260 may correct the identified abnormal data by reflecting a weight to information on other days measured at the same time.

The database server 260 may identify at least one or more abnormal data determined to be abnormal data, and calculate a previous normal integration value and an immediate integrated integration value of the identified at least one or more abnormal data. In addition, the integration difference is calculated from the difference between the integration value immediately after the calculation and the normal integration value immediately before. there is.

In addition, when the number of the identified at least one or more pieces of data is two or more, the database server 260 may calculate past average supply amounts for each of the one or more pieces of the identified pieces of data.

In particular, among the identified at least one or more abnormal data, the first correction data is calculated by reflecting predetermined weights for past average supply amounts calculated for the Nth or more data, and the identified at least one or more abnormal data Secondary correction data may be generated by summing up primary correction data for each of the first correction data and distributing an integrated difference corresponding to the first correction data based on a ratio between each of the first correction data and the sum data.

In addition, the database server 260 may correct at least one or more pieces of data identified as the generated secondary correction data.

For example, among 1440 pieces of time-minute data measured in units of 1 minute for 24 hours, when the 1110th data is identified as abnormal data, the 1110th time-minute data can be corrected by reflecting the weight of information on other days.

Specifically, the 1110th hour minute data among the measurement data of 1 day ago, the average of the 1110th hour minute data among the measurement data for the past 3 days, the average of the 1110th hour minute data among the measurement data for the past 7 days, and the last month The missing 1110th time minute data may be corrected by using an average of the 1110th time minute data among the measurement data.

In this case, weights may be differently reflected in the average of each time-minute data.

3 is a diagram for explaining the data processing flow.

The measurement data 320 measured by the meter 310 may be interpreted as raw data. Thereafter, the measurement data may be secondary processed into calibration data 330 through a process of supplementing missing data or correcting abnormal data.

4 is a diagram illustrating an operating method of a pipe network management system for managing distributed water supply.

In the operation method of the pipe network management system for managing the distributed water supply, time-minute data can be measured in units of minutes for a certain period of time, for example, 24 hours, using a measuring instrument installed in the block (step 401). In addition, the operation method of the pipe network management system may calculate instantaneous data obtained by dividing the time-minute data by minute, and accumulated data accumulated from the start time to the calculation time of the time-and-minute data (step 402).

Apart from the time-minute data, the time-minute data to be measured is accumulated with the previously measured time-minute data and recorded as integration data. The time-minute data and integrated data recorded in this way can be recorded as one cycle of 24 hours as measurement data.

The recorded measurement data may be complemented or corrected for missing parts and abnormal parts.

To this end, the operation method of the pipe network management system in step 403 may identify missing data at a specific point in time due to discrepancies between time-minute data and field data at a specific point in time.

Field data can be interpreted as a reference template as previous data recorded at the same site without missing parts.

Compensation can be processed for missing parts while preparing for each time minute. For example, in the operating method of the pipe network management system, a time value at the time of occurrence of the missing data may be input for a time value among missing data, and instantaneous data and accumulated data among missing data may be input as null values.

In addition, in the operating method of the pipe network management system, abnormal data may be identified by searching for measurement data in which missing data is supplemented (step 405).

At this time, the operation method of the pipe network management system may determine whether or not there is abnormal data by dividing the data for which missing data is supplemented into instantaneous data or integrated data divided by minute.

For example, the operation method of the pipe network management system may determine abnormal data when the size of instantaneous data is 0 or greater than the maximum value in order to determine whether or not there is abnormal data.

In addition, the operation method of the pipe network management system may determine abnormal data when the size of the accumulated data is 10 times or more or 0.1 times or less than the previous accumulated data that entered the normal value in order to determine whether or not there is abnormal data.

In addition, when the data is identified as abnormal according to the determination result, the operating method of the pipe network management system may replace the identified missing data with preset data to correct and record the missing data (step 406).

The identified abnormal data may be corrected by reflecting weights on information of other days measured at the same time.

As a result, using the present invention, it is possible to provide a technology for quickly and accurately detecting and analyzing water flow and leaks by managing a pipe network supplying constant water to each block.

In addition, by using the present invention, it is possible to increase the reliability of the flow rate measurement in order to utilize the flow rate of constant water for various analyzes during a certain period of time.

5A is a diagram illustrating an algorithm for determining missing data and compensating for missing data among methods for managing measurement data.

The measurement data may include instantaneous data measured by a measuring device installed in each block of the waterworks pipe network in units of minutes for a day and integrated data obtained by accumulating the instantaneous data.

The measurement data is data measured for a certain period of time and recorded in the database, and it is necessary to supplement it by determining whether or not there is a missing part where data is not measured at a specific hour (N hour). In addition, if the missing part is supplemented, it is necessary to determine whether there is an anomaly part representing an outlier value as a whole, and correct the corresponding part.

N is an integer from 1 to 1440, and may be used to determine missing data by repeating 1440 time-minute data.

The measurement data for this may be data measured for a certain period of time, and in the present specification, data measured and recorded for 24 hours may be the target.

The measurement data may include time-minute data measured in units of one minute and integrated data obtained by accumulating the time-minute data.

Accordingly, there may be 1440 time-minute data measured for 24 hours (1440 minutes).

Specifically, the method for managing measurement data may initialize N to 1 in order to process from the first among 1440 pieces of time-minute data (step 501).

Next, a method for managing measurement data may read time-minute data at N times among the measurement data and increase N by 1 so that the next time-minute data can be read in the next cycle (step 502).

Measurement data according to an embodiment may include time-minute data measured in units of 1 minute and integrated data obtained by accumulating data up to a point in time of measurement.

In the method of managing measurement data, since the missing part must be filled in prior to correcting the abnormal part, only the time-and-minute data is first read to investigate the time-and-time data first.

Next, the method for managing measurement data may compare current time-minute data and field data to determine whether they match (step 503).

Field data is template data in which all missing parts among machine-measured data are supplemented, and can be used as a criterion for determining whether or not there is a missing part.

As a result of the determination in step 503, when the time-minute data and the field data are the same (matched), it may be determined that there is no missing part. In addition, when there is no missing part, a process of reading time-division data corresponding to 2 in which N is further increased by 1 from the initial value 1 may be performed by branching to step 502 .

As a result of the determination in step 503, if the time-minute data and the field data are not identical, that is, if they do not match, the process may branch to step 504.

If the time-sequence data and field data are not the same, it may be interpreted that a missing part exists in the corresponding time-sequence data.

In step 504, a process of filling in missing parts of the time-minute data (1-minute data) (supplementation process) may be processed.

In the process of compensating for the missing part, a part corresponding to time among fields of time-minute data may be filled with a time value. In addition, the instantaneous field and accumulated field can be recorded as null.

Next, in the method for managing measurement data, the steps 402 to 404 may be repeated by increasing the unit of N hours and minutes within a predetermined time.

To this end, the method for managing measurement data may determine whether N is greater than or equal to 1440 through step 505 .

If N is less than or equal to 1440, the measurement data management method branches to step 502 and can be repeatedly processed from the process of obtaining time-minute data.

In addition, as a result of the determination in step 505, if N is greater than or equal to 1440, processing of missing data for time-minute data for 24 hours has been completed, and branching to step 506 may be performed by setting C to 1 to prepare for processing of abnormal data.

C is a variable distinct from N, and is an integer from 1 to 1440, and can be used to determine abnormal data by repeating 1440 time-minute data.

5B is a diagram for explaining an algorithm for determining abnormal data among methods for managing measurement data.

The method for managing measurement data may initiate a flow for finding abnormal data among the measurement data (step 507).

The measurement data may include instantaneous data and accumulated data, and if any one of the instantaneous data and accumulated data has an abnormal part, it may be determined as abnormal data.

Accordingly, the method for managing measurement data may first determine whether instantaneous data is abnormal among the measurement data in order to determine whether the measurement data is abnormal (508).

For example, in order to determine whether measurement data is abnormal, when the size of instantaneous data is 0 or greater than the maximum value, it may be determined as abnormal data.

If the size of the instantaneous data is 0 or greater than or equal to the maximum value, branching to step 511 may be performed to check that the field corresponding to the current C value is abnormal data among related fields of the measurement data.

If the size of the instantaneous data is not 0 and is less than or equal to the maximum value, it may be determined that the instantaneous data corresponding to the current C value does not have an abnormal part.

Accordingly, the method for managing the measurement data may branch to step 509 to determine whether the data is abnormal by checking the accumulated data.

For example, in the method for managing measurement data, if the size of integrated data is 10 times or more or 0.1 times or less compared to the previous integrated data that entered the normal value, the portion corresponding to the current C value can be determined as abnormal data. .

If the corresponding part of the accumulated data is determined to be abnormal data, the method for managing the measurement data may branch to 511 to check that the field corresponding to the current C value is abnormal data among related fields of the measurement data.

If, as a result of the determination in step 509, it is determined that the corresponding portion of the accumulated data is normal data rather than abnormal data, it is possible to branch to step 510 and determine whether C is greater than or equal to 1440. Step 510 is a process of checking whether it is the last data to determine whether all 1440 pieces of data are abnormal.

Therefore, if it is not the last data, since C is less than 1440, the flow for finding abnormal data may be restarted by branching to step 507.

In addition, as a result of the determination in step 510, if the current data is the last data, it is possible to branch to a correction process for the data determined as abnormal data.

Various correction methods may be used to correct the data determined as abnormal data. For example, the identified abnormal data may be corrected by reflecting a weight to information on other days measured at the same time.

For example, among 1440 pieces of time-minute data measured in units of 1 minute for 24 hours, when the 1110th data is identified as abnormal data, the 1110th time-minute data can be corrected by reflecting the weight of information on other days.

Specifically, the 1110th hour minute data among the measurement data of 1 day ago, the average of the 1110th hour minute data among the measurement data for the past 3 days, the average of the 1110th hour minute data among the measurement data for the past 7 days, and the last month The missing 1110th time minute data may be corrected by using an average of the 1110th time minute data among the measurement data.

In this case, weights may be differently reflected in the average of each time-minute data.

A specific embodiment of correcting abnormal data will be described in detail with reference to FIGS. 6A and 6B.

6A and 6B are diagrams illustrating a specific method of correcting the determined abnormal data.

First, referring to FIG. 6A , the pipe network management server system may correct abnormal data using a database server.

First, the database server may set numerical values for correction for at least one or more abnormal data identified as abnormal data (step 601).

Based on the identified instantaneous data, the previous normal integration value (PVS), the immediately following normal integration value (PVE), the calibration target start time (ST), and the calibration target end time (ET) can be set.

Next, the database server may calculate a total difference (VP) using the difference between PVE and PVS (step 602).

The instantaneous data of the correction target that needs to be corrected may be one or several.

First, the database server may determine whether there is one piece of instantaneous data requiring correction through step 603 .

If there is only one instantaneous data to be corrected, the database server may halve the accumulated difference and calculate the instantaneous data to be corrected (step 604).

In FIG. 6B, a process of calculating instantaneous data to be corrected, that is, a correction value, when there are two or more instantaneous data to be corrected will be described.

First, if there are two or more pieces of instantaneous data that require correction, the database server may calculate past average supply amounts for each of the instantaneous data to be corrected (step 605).

In addition, the database server may calculate first correction data by reflecting preset weights for past average supply amounts calculated for Nth or higher data among instantaneous data to be corrected (step 606).

In addition, the database server may calculate first correction data for all of the instantaneous data instead of correction (step 607).

In addition, the database server sums the first correction data for the instantaneous data to be corrected (step 608), and distributes the integration difference to the instantaneous data of each correction target based on the ratio between the first correction data and the summed data for correction. Instantaneous data can be calculated (step 609).

The instantaneous data calculated by distributing the integration difference to the instantaneous data of the correction target can be interpreted as secondary correction data.

As a specific example, a case where 8 instantaneous data collected at 1-minute intervals from 1110 to 1117 hours are identified as abnormal data may be considered.

According to a specific embodiment, the cases in Table 1 below can be considered in which the integrated values normally collected right before and after the section identified as abnormal data are normally collected.

[Table 1]

Meanwhile, the intervals identified as abnormal data are eight intervals from time 1110 to 1117, and an embodiment of calculating integrated data in each of 1110 to 1117 using the correction concept in the present invention will be described.

First, the database server may calculate past average supply amounts for each of the identified at least one or more pieces of data.

For example, past average supply amounts corresponding to the previous day, 3-day average, weekly average, and monthly average can be calculated.

Next, the database server may calculate first correction data by reflecting predetermined weights for past average supply amounts calculated for Nth or more data among the identified at least one or more data.

[Table 2]

[Table 3]

[Table 4]

[Table 5]

More specifically, looking at the average supply amount in the past corresponding to the time '1110', as shown in [Table 2], the average supply amount is confirmed as a value corresponding to '28.970' on the previous day. This is average data calculated from information determined to be normal data, not past abnormal data.

On the other hand, looking at [Table 2] to [Table 5], the past average supply amount corresponding to '1110' is '38.853' for the 3-day average, '44.561' for the weekly average, and '41.770' for the monthly average. can be confirmed

Accordingly, the database server may assign the highest weight to the previous day, which is the latest supply amount, and the lowest weight to the monthly average including the most recent supply amount.

The weight can be changed appropriately, but in this specification, the supply of the previous day is given a 40% weight, the 3-day average supply is given a 30% weight, the weekly average supply is given a 20% weight, and the monthly average supply is given a 10% weight. weight can be assigned.

The data added by reflecting the weight (supply quantity of the previous day *0.4 + average supply quantity of 3 days *0.3 + average supply quantity of the week *0.2 + supply quantity of the month average *0.1) is the first correction data, as shown in [Table 6] below. It corresponds to the calculation pattern.

[Table 6]

In addition, the application rate is the ratio of each primary correction data and summed data obtained by summing the primary correction data of all sections in which abnormal data is identified.

For example, the application rate of the 1110 time zone may be interpreted as '0.121', which is a value obtained by dividing '36.333', which is the first correction data, by '299.379', which is the sum data (TI).

Therefore, as shown in [Table 7] below, the application rate of the 1110 time zone can be determined as '0.121', and the value reflecting the application rate for the total difference of 500 can be calculated as the secondary correction data in the 1110 time zone. .

That is, in the 1110 time zone, '60.500' can be calculated by multiplying the integration difference '500' with the applicable application rate '0.121', and the corrected integration value in the 1110 time zone is added to the previous settlement integration value '105200.000', That is, the secondary correction data may be calculated as '105261.000'.

In the same way, the abnormal data may be corrected by calculating secondary correction data in each of the time zones 1111 to 1117.

[Table 7]

As a result, by using the present invention, it is possible to compensate for missing or abnormal parts by managing the accumulated measurement data in the waterworks on a daily basis. In addition, it is possible to provide a technology for quickly and accurately detecting and analyzing water leakage and leakage by managing a pipe network supplying constant water to each block.

In addition, by using the present invention, it is possible to increase the reliability of the flow rate measurement in order to utilize the flow rate of constant water for various analyzes during a certain period of time.

The devices described above may be implemented as hardware components, software components, and/or a combination of hardware components and software components. For example, devices and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), It may be implemented using one or more general purpose or special purpose computers, such as a programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. A processing device may run an operating system (OS) and one or more software applications running on the operating system. A processing device may also access, store, manipulate, process, and generate data in response to execution of software. For convenience of understanding, there are cases in which one processing device is used, but those skilled in the art will understand that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that it can include. For example, a processing device may include a plurality of processors or a processor and a controller. Other processing configurations are also possible, such as parallel processors.

Software may include a computer program, code, instructions, or a combination of one or more of the foregoing, which configures a processing device to operate as desired or processes independently or collectively. The device can be commanded. Software and/or data may be any tangible machine, component, physical device, virtual equipment, computer storage medium or device, intended to be interpreted by or provide instructions or data to a processing device. , or may be permanently or temporarily embodied in a transmitted signal wave. Software may be distributed on networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer readable media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer readable medium. The computer readable medium may include program instructions, data files, data structures, etc. alone or in combination. Program commands recorded on the medium may be specially designed and configured for the embodiment or may be known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. - includes hardware devices specially configured to store and execute program instructions, such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter, as well as machine language codes such as those produced by a compiler. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

As described above, although the embodiments have been described with limited drawings, those skilled in the art can make various modifications and variations from the above description. For example, the described techniques may be performed in an order different from the method described, and/or components of the described system, structure, device, circuit, etc. may be combined or combined in a different form than the method described, or other components may be used. Or even if it is replaced or substituted by equivalents, appropriate results can be achieved.

Therefore, other implementations, other embodiments, and equivalents of the claims are within the scope of the following claims.

Claims (18)

In the pipe network management server system installed in each block of the waterworks pipe network to measure and manage the flow rate of water for each block,
A collection server that collects data obtained by measuring the flow rate of constant water measured for a certain period of time from a meter installed in the block;
a FEP server controlling to classify and record the collected data for each measuring instrument, identify missing data in the measured data, replace the identified missing data with preset data, and supplement and record the missing data; and
A database server for recording data in which the missing data is supplemented in a database;
The database server,
Identifying at least one or more abnormal data determined to be abnormal data;
Calculating the immediately preceding normal integration value and the immediately following settlement integration value of the identified at least one or more abnormal data;
An integration difference is calculated from the difference between the integration value immediately after the calculation and the normal integration value immediately before the calculation,
When the number of the identified at least one or more data is 1, the pipe network management server system calculates a value obtained by dividing the accumulated difference in half as correction data. According to claim 1,
The FEP server,
A pipe network management server system that determines and identifies the occurrence of the missing data when the measured time-minute data and field data are different. According to claim 2,
The FEP server,
The missing data includes a time value, instantaneous data, and accumulated data, and the time value inputs a time value at the time when the missing occurs, and inputs the instantaneous data and the integrated data as a null value. management server system. According to claim 1,
The database server,
A pipe network management server system that searches data for which the missing data is supplemented, identifies abnormal data, and classifies and records the identified abnormal data. According to claim 4,
The database server,
The pipe network management server system for determining whether or not there is abnormal data by dividing the data for which the missing data is supplemented into instantaneous data or accumulated data divided by minute, and identifying and recording the data as abnormal data according to the result of the determination. According to claim 5,
The database server,
The pipe network management server system, characterized in that it is determined as abnormal data when the size of the instantaneous data is 0 or greater than the maximum value. According to claim 5,
The database server,
The pipe network management server system, characterized in that it is determined as abnormal data when the size of the integrated data is 10 times or more or 0.1 times or less compared to the previous integrated data that entered the normal value. According to claim 7,
The database server,
A pipe network management server system that corrects the identified abnormal data by reflecting weights on information on other days measured at the same time. delete According to claim 8,
The database server,
When the number of the identified at least one or more data is 2 or more,
Calculate past average supply amounts for each of the identified at least one or more abnormal data,
Among the identified at least one or more abnormal data, primary correction data is calculated by reflecting predetermined weights for past average supply amounts calculated for the Nth or more data,
First correction data for the identified at least one or more abnormal data is added, and based on a ratio between each of the first correction data and the summed data, the integrated difference is calculated to correspond to the first correction data. Distribute to generate secondary correction data;
A pipe network management server system for correcting at least one or more of the identified data with the generated secondary correction data. Loading measurement data stored in a database after recording in minutes for a predetermined time;
A first step of reading instantaneous data in units of N hours and minutes from the loaded measurement data;
a second step of comparing the read instantaneous data and field data to determine whether or not there is a missing data;
a third step of supplementing the missing data in the unit of N time minutes when the data is missing as a result of the determination;
a fourth step of repeating the first to third steps by increasing the number of N time minutes within the predetermined time period; and
Including the step of determining whether the measurement data is abnormal,
In the step of determining whether the measurement data is abnormal,
Identifying at least one or more abnormal data determined to be abnormal data;
Calculating the immediately preceding normal integration value and the immediately following settlement integration value of the identified at least one or more abnormal data;
An integration difference is calculated from the difference between the integration value immediately after the calculation and the normal integration value immediately before the calculation,
When the number of the identified at least one or more data is 1, a value obtained by dividing the accumulated difference in half is calculated as correction data, a method for managing measurement data during pipe network management. According to claim 11,
The method for managing measurement data during pipe network management, characterized in that the constant time is 24 hours, and the N hour-minute unit increases by 1 minute from 1 minute to 1440 minutes. According to claim 11,
The field data,
A method for managing measurement data during pipe network management, characterized in that all missing parts of the machine-measured data are supplemented template data. According to claim 11,
The measurement data,
A method for managing measurement data during pipe network management, characterized in that it includes instantaneous data measured in minutes for a day by a measuring device installed in each block of the waterworks pipe network and integrated data in which the instantaneous data is accumulated. According to claim 14,
determining whether the measurement data is abnormal;
If the measured data is abnormal data as a result of the determination, checking and storing abnormal data in a related field; and
A step of correcting abnormal data for which abnormal data is checked in a related field among measurement data
A method for managing measurement data during pipe network management that further includes. According to claim 15,
The step of determining whether the measurement data is abnormal,
Determining whether the instantaneous data is abnormal, but determining that the instantaneous data is abnormal if the size of the instantaneous data is 0 or greater than the maximum value
A method for managing measurement data during pipe network management that includes. According to claim 15,
The step of determining whether the measurement data is abnormal,
Determining whether the integrated data is abnormal, but determining that the integrated data is abnormal if the size of the integrated data is 10 times or more or 0.1 times or less compared to the previous integrated data that entered the normal value.
A method for managing measurement data during pipe network management that includes. According to claim 15,
Correcting the identified abnormal data by reflecting a weight to information on other days measured at the same time
A method for managing measurement data during pipe network management that further includes.

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